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PERCEIVED BARRIERS TO QUALITY IMPROVEMENT AND REDUCED MEDICAL ERROR: A QUANTITATIVE STUDY by Cynthia J. Bergs Copyright 2014 A Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Health Administration UNIVERSITY OF PHOENIX All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. Microform Edition © ProQuest LLC. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code ProQuest LLC. 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, MI 48106 - 1346 UMI 3647288 Published by ProQuest LLC (2014). Copyright in the Dissertation held by the Author. UMI Number: 3647288 Abstract This quantitative, descriptive study explored the perceptions of hospital personnel with regard to quality-improvement initiatives as a collective barrier potentially inhibiting the reduction of medical error. A sample population of 162 personnel drawn from a nonprofit hospital within central Florida participated in an online questionnaire known as the Safety Climate Survey. The findings revealed a statistically significant relationship between the perceptions of personnel implementing quality-improvement measures and their positions within the hospital, the largest variance occurring between unit nurses and hospital administration. No significant relationships were found among the demographic variables of age, gender, ethnicity, specialty certification, educational level, years with current employer, years within specialty area, title, shift, employment status, and job satisfaction. The perception differences between unit nurses and hospital administration was, overwhelmingly, the strongest indicator of impeded quality-improvement measures. The findings hold leadership implications for nurse educators, preceptors, administrators, recruiters, and managers. Recommendations for practice are presented for health-care leaders to support decisions with the potential to reduce medical error. Dedication To my parents who provided the opportunity, strength, and guidance to reach this life goal. Your own strength, kindness, and perseverance guided me to successful completion. To my husband, who never questioned the long nights nor my ability. To all those within health-care leadership who are striving to effectively reduce medical error and improve the patient experience while acknowledging the perceptions of those working under their authority. This work is offered as a contribution toward our mutual goal of improved quality of care. Acknowledgments My deepest appreciation is expressed to my mentor, Dr.

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PERCEIVED BARRIERS TO QUALITY IMPROVEMENT AND REDUCED MEDICAL ERROR: A QUANTITATIVE STUDY by Cynthia J. Bergs Copyright 2014 A Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Health Administration
UNIVERSITY OF PHOENIX All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. Microform Edition © ProQuest LLC. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code ProQuest LLC. 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, MI 48106 - 1346 UMI 3647288 Published by ProQuest LLC (2014). Copyright in the Dissertation held by the Author.
UMI Number: 3647288 Abstract This quantitative, descriptive study explored the perceptions of hospital personnel with regard to quality-improvement initiatives as a collective barrier potentially inhibiting the reduction of medical error. A sample population of 162 personnel drawn from a nonprofit hospital within central Florida participated in an online questionnaire known as the Safety Climate Survey. The findings revealed a statistically significant relationship between the perceptions of personnel implementing quality- improvement measures and their positions within the hospital, the largest variance occurring between unit nurses and hospital administration. No significant relationships were found among the demographic variables of age, gender, ethnicity, specialty certification,
educational level, years with current employer, years within specialty area, title, shift, employment status, and job satisfaction. The perception differences between unit nurses and hospital administration was, overwhelmingly, the strongest indicator of impeded quality-improvement measures. The findings hold leadership implications for nurse educators, preceptors, administrators, recruiters, and managers. Recommendations for practice are presented for health-care leaders to support decisions with the potential to reduce medical error. Dedication To my parents who provided the opportunity, strength, and guidance to reach this life goal. Your own strength, kindness, and perseverance guided me to successful completion. To my husband, who never questioned the long
nights nor my ability. To all those within health-care leadership who are striving to effectively reduce medical error and improve the patient experience while acknowledging the perceptions of those working under their authority. This work is offered as a contribution toward our mutual goal of improved quality of care. Acknowledgments My deepest appreciation is expressed to my mentor, Dr. Mary Tan, who was always available to provide a solid, clear perspective; answer questions, and offer strong encouragement. Dr. Tan’s constructive feedback significantly contributed to the guidance needed in the completion of this study. Committee members, Dr. Julia Aucoin and Dr. Hans-Peter de Ruiter, also extended invaluable support, enrichment, direction, and honest feedback. I am grateful for the guidance and support
of Dr. Timothy DeGroot who supported me through the last stages of my dissertation process. Special thanks to my editor, Jill Eastwood, and my statistician, Fanchao Yi, both of whom played an important role in my success through their provision of specialized expertise and guidance. Table of Contents List of Tables ............................................................................................... ...................... ix List of Figures ............................................................................................... .......................x Chapter 1: Introduction………………………………………………………… …………1
Background ............................................................................................... ...............3 Problem Statement .......................................................................................... ..... ....4 Purpose of the Study ............................................................................................... .6 Significance of the Study .........................................................................................7 Nature of the Study ............................................................................................... ...8 Research Questions and Hypotheses .....................................................................11 Theoretical Framework ..........................................................................................12 Definitions …………….............................................................................. ...........15 Assumptions ............................................................................................... ............16 Scope, Limitations, and Delimitations ...................................................................17
Chapter Summary ............................................................................................... ...............19 Chapter 2: Literature Review .............................................................................................2 1 Historical Overview ............................................................................................... 21 Health-Care Culture ............................................................................................... 24 Health-Care Leadership .........................................................................................25 Outcomes of Medical Error ...................................................................................27 Perceptions ......................................................................................... ...... ..........................30 Patients and Hospital Personnel ...................................................................................30 Medical Professionals
............................................................................................... ...32 Improvement Initiatives ............................................................................................... ......34 Reduction Strategies ............................................................................................... .....37 Regulatory Oversight ............................................................................................... ....40 Local Mandates ..................................................................................... .......... .............42 Disparities ............................................................................................... ...........................44 Culture of Safety ............................................................................................... .................46 Reporting................................................................................ ............................................49 Quality Improvement ............................................................................................... ..........51 Chapter Summary ...............................................................................................
...............52 Chapter 3: Research Methods ............................................................................................5 4 Research Design…….............................................................................. ...............54 Methodology Appropriateness…………………………………………………...55 Accomplishing the Study’s Goals………………………………………………..56 Informed Consent and Confidentiality........................................................................ .58 Population and Sampling ...................................................................................... .......5 9 Data Collection Methods .......................................................................................62 Instrument ….. ............................................................................................... ........63 Validity and Reliability ..........................................................................................64 Data Analysis ...............................................................................................
..........66 Chapter Summary ............................................................................................... ...69 Chapter 4: Results ............................................................................................... ...............70 Instrument…………………………………………………………… …………..70 Demographic Data ………………………………………………………………71 Findings ……........................................................................................ .................73 Chapter Summary ............................................................................................... ...93 Chapter 5: Conclusions and Recommendations ................................................................95 Findings and Interpretations………………………………………………..……96
Limitations…………………………………………………………… ………….99 Implications and Recommendations……………………………………………100 Future Research……………………………………………………….…… …..102 Chapter Summary……………………………………………………………... 103 References ............................................................................................... .........................105 Appendix A: Study-Site Permission ................................................................................129 Appendix B: Informed Consent .......................................................................................130 Appendix C: Invitation to Participate ..............................................................................131 Appendix D: Permission to Use Survey ..........................................................................132
List of Tables Table 1. Mean and Standard Deviations for Age and Experience of the Study Participants ............................................................................................... .........................73 Table 2. Frequency Distribution for the Administrators Study Group (n = 44) ............77 Table 3. Frequency Distribution for the Nurse-Managers Study Group (n = 37).........79 Table 4. Frequency Distribution of the Nurses Study Group (n = 81) ..........................80 Table 5. Descriptive Statistics From Survey Responses ................................................81 Table 6. Spearman Product-Moment Correlation .........................................................83 Table 7. Kruskal-Wallis Test and Multiple Comparison ...............................................84 Table 8. Survey Responses According to the Age of the Participants ...........................86 Table 9. Survey Responses According to Years of Participant Experience in Position
............................................................................................... ...........................86 Table 10. Survey Responses According to Participant Experience in Specialty .............86 Table 11. Survey Responses According to Years of Participant Experience in Organization ............................................................................................... ...................87 Table 12. Gender of Study Participants ...........................................................................88 Table 13. Cronbach’s Alpha Results by Domain .............................................................89 Table 14. Basic Statistics ............................................................................................... ..90 Table 15. Normality Check .............................................................................................. 90 Table 16. Constant Variance Check ................................................................................92 List of Figures
Figure 1. Number and percentages of study participants by gender .................................72 Figure 2. Mean age of the study participants and mean years of experience within the health-care field ............................................................................................... .73 Figure 3. Safety-climate domains based upon participant age .........................................75 Figure 4. Safety-climate domains based upon number of years participants in specialty ............................................................................................... ..........................76 Figure 5. Safety-climate domains based upon years of participant experience in position................................................................................... ........................................76 1
Chapter 1: Introduction Medical errors and other human mistakes within the hospital setting can result in unnecessary injury to patients or death (Kohn, Corrigan, & Donaldson, 2000). The consequences have been identified by various studies (Berntsen, 2004; Young, 2005), motivating multiple initiatives toward improved quality of medical care within hospitals. Special-interest groups have taken action to encourage hospital administrators to make related changes to reduce medical error. This action has included new patient-safety standards, mandatory and voluntary event reporting, and public awareness through hospital-performance ―scorecards‖ (Deavers, Pham, & Liu, 2004; Pawlson, 2002; Weinberg, Hilborne, & Nguyen, 2005). This current study was conducted to determine whether the perceptions of hospital personnel regarding barriers to implementing quality- improvement measures contributed to either the reduction or elimination of medical error
within hospitals. Hospital leaders have instituted strategies to reduce or eliminate medical error in the interest of risk management, to adhere to new regulations, and to decrease the potential loss of customers from public awareness of such error (Messner, 1998; Orser, 2000). A key factor to reducing patient injury from such error is public awareness because it spurs implementation of the appropriate steps for institutional protection. However, barriers can exist that impede quality-improvement efforts. Messner (1998) cited organizational culture, restructuring, quality-control functions, and costs as contributing to slowed progress with quality-improvement programs. According to 2 Walshe and Shortell (2004), the future success of such programs ―depends on cultural as
much as structural change in health care systems and organizations‖ (p. 103). Steep authority hierarchies, lack of teamwork, an unwillingness to acknowledge human fallibility, and the tendency to take punitive action rather than learn from error are all prevailing aspects of the organizational and professional culture within the realm of health care. These characteristics act as barriers to quality care improvement and patient safety (Akins & Cole, 2005; Sexton, Pronovost, & Thomas, 2000; VanGeest & Cummins 2003). Scott (2003) found that highly skilled workers employed in hospital positions may be resistant to formal organizational structure and controls. Such organizational resistance can also serve as a barrier to accepting additional quality-improvement controls and structure. Additional research on related change initiatives and barriers may contribute to the improvement of care quality and reduce medical error while adding to the existing body of knowledge within this area of study. The aim behind this current quantitative study was to explore
the perceptions of hospital personnel related to quality-improvement initiatives as barriers potentially inhibiting the reduction of medical error. Addressing such reduction is difficult. No standardized system of measurement exists, resulting in various interpretations of data. Additionally, the perceptions of both patients and medical personnel, in terms of existing barriers, may impede progress toward the reduction of medical error. The perceptions of nurses, hospital management, and administrative leaders may also affect quality- improvement measures toward such reduction (Bognár et al., 2008). In the current study, data were collected from a sample of nurses, as well as management and administrative leaders within the health-care setting, with the aim of providing a clearer understanding 3 of how perceived barriers to the implementation of quality-
improvement systems may adversely affect the reduction of medical error. Existing literature was reviewed on the impact of related regulations and quality systems in place, as well as research focused on how patients and medical personnel perceive hospital cultures of safety. Background A number of patients are injured each year within the United States as a result of unnecessary medical error within hospital settings (Bilawka & Craig, 2003; Kohn et al., 2000). The Harvard Medical Practices Study reviewed patient records during 1984 at 51 hospitals located within the state of New York (Brennen et al., 1991). A substantial amount of medical error was found to be due to negligence. The Institute of Medicine (IOM) introduced the Quality of Healthcare in America Project during 1998 to investigate the problem of medical error and develop improvement strategies (Kohn et al., 2000). The project (IOM, 1999) identified medication procedural error and
diagnostic error as common problems within hospitals. Their prevention requires systems improvement with a goal toward higher quality patient care. The Harvard Medical Practices Study (Brennan et al., 1991) and the IOM (1999) report became catalysts for the public awareness that brought not only public but also media attention to the development of possible solutions for medical error. During 2003, the Joint Commission on Accreditation of Healthcare Organizations (JCAHO; 2005) issued new patient-safety standards that prompted multiple states to enact mandatory medical-error reporting (Weinberg et al., 2005). Both published studies on medical error and hospital-performance scorecards stimulated public awareness and demanded overall improvement in health care (Collins, Block, Arnold, & Cristakis, 2009). However, 4
despite the subsequent initiatives, implementation of standards, and mandatory reporting, evidence of these measures resulting in sufficient improvement in patient care and a positive effect on reducing medical error is inconclusive. This is due to a lack of consistent, comparable data, as well as a lack of protocol standardization in the measurement and evaluation of such error (Berntsen, 2004). In fact, studies have indicated an increased amount of medical error following initiative implementation (Berntsen, 2004; Young, 2005). Barriers to progress in hospital-improvement systems include (a) inconsistent definitions, (b) voluntary versus mandatory reporting, and (c) ineffective systems of measurement (Young, 2005). Problem Statement A general problem for the health-care industry is the increased medical error that has resulted in as many as 98,000 deaths per year and adds $29 billion to annual health- care costs (Berntsen, 2004). The specific problem is the
perceptions of hospital personnel regarding quality-improvement initiatives, which may act as a collective barrier inhibiting the reduction of medical error. Studies conducted after the related IOM (1999) report revealed minimal hospital progress toward reducing the number and significance of medical errors (Berntsen, 2004; Young, 2005). As a result, federal and state mandates were imposed on health-care providers toward this end (Weinberg et al., 2005). Health-care organizations have instituted safer practice and agencies and professional societies have issued safety guidelines and recommendations to address medical error. Additionally, funding was dedicated to patient- safety research. The JCAHO issued national patient-safety goals, and patient-safety legislation was introduced 5
(Burney, 2001; Deavers et al., 2004). Despite these efforts, health care is not measurably safer than it was in 2000 (Weinburg et al., 2005). Existing data suggest an underestimation of the magnitude of preventable health-care error. Many errors continue to go unreported; consequently, accurate incidence rates are unknown (Berntsen, 2004). The use and effectiveness of safety measures are also unknown due to unreliable outcome measures. Advances in patient safety include the increased use of technology to reduce medical error, increased training toward improved teamwork, and full disclosure of medical error (Leape & Berwick, 2005). Barriers to progress include the culture and complexity of health care, continuing skepticism resulting in the perception of system failures as the underlying cause of most health-care error, and the fear of malpractice liability that inhibits a willingness to discuss or even admit such error. Research on
causal factors has been traditionally focused on clinical indicators. While this body of study was centered in specific errors occurring within specific situations, the need remains to find evidence of commonality among measures and related theory (Rathert, Fleig-Palmer, & Palmer, 2006). Few empirical studies have asked frontline employees for their perceptions of key contributing factors in the prevention of medical error. Reason (2001) indicated that hospital employees can add valuable information in this regard because they ―are at the sharp end of complex systems‖ (p. 14). The current quantitative study was conducted to determine whether the perceptions of hospital personnel created barriers to the implementation of quality- improvement measures to reduce or eliminate medical error. The population sample included nurses, health-care managers, and hospital administrators. The findings may 6
benefit hospital leaders seeking successful implementation of quality-improvement strategies to reduce medical error through clearer communication of goals, increased management and support, and planning that is adequate to effectively address the problem under study (Messner, 1998). Purpose of the Study The purpose of this current quantitative study was to explore the perceptions of hospital personnel regarding quality-improvement initiatives as a collective barrier potentially inhibiting the reduction of medical error. The research method was suitable for the study because it led to identifying possible solutions to ineffective quality- improvement processes. The independent variable for this study was the perceptions of barriers to quality care improvement measured by a Likert-type scale survey. The dependent variable was the statistical data of the sample characteristics.
A simple descriptive survey design was appropriate for this study because it supported a description of the characteristics or behaviors of a particular population in a systematic and accurate fashion. A systematic sample was selected by obtaining a list of employees meeting the following criteria: (a) employed a minimum of six months within the study-site hospital; and (b) currently employed as a floor nurse, nurse manager, or administrative employee. The participants were chosen through stratified, systematic sampling. Every employee meeting the criteria was selected for study participation. The goal was to obtain 110 total participants. Discoveries are measurable in quantitative study, and data are presented from an objective rather than subjective viewpoint (Balnaves & Caputi, 2001). Questions surrounding the perceptions of the participants in the current study regarding the culture 7
of safety within the health-care environment were formulated to use quantifiable data for explaining and predicting phenomena (Creswell, 2003). Ordinal data were collected through a Likert-type, self-administered survey completed by hospital personnel. At the ordinal level of measurement, the data were ranked in a manner resulting in an order to the data but with no definite interval. Significance of the Study A survey on the safety climate of hospitals was expected to detect employee concerns related to patient safety and help foster communication on this topic; however, limited evidence existed to indicate that survey scores are related to patient-safety outcomes (Colla, Bracken, Kinney, & Weeks, 2005). The findings contributed to existing knowledge on the effectiveness of quality-improvement programs in reducing medical error within hospital settings through clearer communication of organizational
goals, increased management and support, and planning that is adequate to effectively address the problem under study (Messner, 1998; Rathert et al., 2006). Rathert et al. (2006) recommended that further study address the perceptions of frontline hospital employees in this regard. Such study was expected to validate the problems and lead to positive change via a system approach. Increasing knowledge surrounding quality improvement and perceptions contributing to medical error is important to both American society and hospital administration because it addresses implementation of the proper tools to reduce such error. This, in turn, will reduce the potential for patient injury or death and the medical costs associated with related insurance coverage and lawsuits. Responsibility for quality care must involve both clinicians and nonclinicians and their effective interaction in response to conflict (Lagrosen & Lagrosen, 2006;
8 Reinertsen, 2005; Stanley, 2006). The working/professional relationship between employees and leadership influences work attitudes (Tangirala, Green, & Ramanujam, 2007). Leadership is not static, and the influence of these relationships can be a predictor of employee performance (Bauer, Erdogan, Linden, & Wayne, 2006; Tangirala et al., 2007). The ability of management to acknowledge and understand employee misconceptions surrounding quality improvement can result in improved methods of training and deployment. Multidisciplinary health-care teams are reliant upon information and tools they are provided to dispense quality care to patients. Understanding differences in the perceptions of nurses, managers, and administrators regarding quality-improvement processes was expected to provide a better opportunity for the development of quality-improvement processes.
Nature of the Study In the current study, a quantitative survey design was applied to collect data facilitating description of the perceptions of medical personnel surrounding barriers to implementing quality-improvement measures that may impede the reduction of medical error. Data analysis addressed the research questions and hypotheses via simple frequency distribution, central tendency, and variability. Several factors justify the application of a quantitative design such as the type of data collected, analyzed, and interpreted; identified variables; and verified theories or explanations supporting the proposed hypothesis (Creswell & Clark, 2007). The use of quantitative research designs may determine whether relationships exist between variables while controlling certain occurrences (Leedey & Ormrod, 2001). Researchers have used quantitative descriptive designs to question participants
9 surrounding their attitudes, opinions, and behaviors and to find relationships between respondent characteristics and the behaviors they exhibit. The design also provides an opportunity for participants to be autonomous with regard to their particular roles in quality improvement because the survey allows for the collection of information through confidential means. Survey responses were extended in an anonymous fashion with no identifying information collected such as names or addresses. Each participant was assigned a five-digit identification number to protect confidentiality. Quantitative methods analyze variables, test hypotheses, measure numbers, replicate findings, and generate statistics (Neuman, 2003). Quantitative data may produce identifiable trends across a broad spectrum of participants, as well as identify improvement processes, controls, and results (Creswell, 2003). Quantitative
methodologies focus on surveys and the statistics drawn from the data. A quantitative research design was appropriate for the current study due to its potential for identifying possible solutions for ineffective quality-improvement processes. A descriptive, quantitative method was appropriate for this study because of its logic of inquiry, which gains a greater amount of information on a particular characteristic within a particular field of study. Barriers or problems to implementing quality-improvement programs were identified (Creswell, 2003). There was no manipulation of variables or attempt to establish causality occurred. Quantitative studies produce measurable or testable data that are objective in nature and provide a general conclusion from specific findings (Balnaves & Caputi, 2001). The data collected in quantitative research provides information that can be applied to a more generalized population through theories and/or hypotheses pertaining to
10 the phenomena under study. Such research is typically conducted from an approach that views knowledge as acquired through direct observation and experimentation. Consequently, in the current research, data were collected from a select group of participants who were representative of a larger population. The transferability of data refers to how findings can be generalized or transferred to other contexts or settings. Thus, the survey administered in the current study included questions surrounding the relationships among measured variables and using numeric data for purposes of explaining phenomena. A simple, systematic survey ensured the equal probability of participation in the current study. Respondents were grouped into subsets sharing particular characteristics (Creswell, 2003), which included their professional position as
a general nurse, nurse manager, or administrator within a central-Florida hospital. Demographic information included gender; age; marital status; educational level; employment (i.e., full or part time); and occupational status. The aim of sample selection was to obtain an unbiased cross section of a hospital population. The simple descriptive survey design was appropriate for the quantitative method to gain a general sense of the phenomenon under study and to form theories that could be tested in future quantitative research (de la Torre, 2011; Polonsky & Waller, 2005). A qualitative method was not deemed appropriate for the current study because such research ―is typically used to answer questions about the complex nature of phenomena, often with the purpose of describing and understanding the phenomena from the participants’ point of view‖ (Leedy & Ormrod, 2001, p. 101). While qualitative methods are effective in the appropriate research environment, ―qualitative researchers
11 construct interpretive narratives from their data and try to capture the complexity of the phenomenon under study‖ (p. 103). The current study is quantitative in nature because the research was conducted to gain a clearer understanding of intentionality or meaning. Quantitative research is designed to quantify relationships between variables. This study explored the perceptions of hospital personnel regarding quality-improvement initiatives as a collective potential barrier inhibiting the reduction of medical error. The identification of relationships and the measurement of variables was conducted through descriptive statistics (Hopkins, 2000). A self-administered, Likert-type survey provided a quantitative description of the trends, attitudes, and opinions of the population sample in the current study (Creswell,
2005). Survey research enables generalization of the findings and inferences surrounding particular characteristics or attitudes. A simple descriptive design allows the opportunity to determine specific times for data collection and analysis (Polonsky & Waller, 2005), as opposed to a longitudinal design that produces immediate results. A survey questionnaire was appropriate for the statistical analysis of the current study because it generated quantitative data with measurable findings (Balnaves & Caputi, 2001). Overall, the simple descriptive design accomplished the goals of the research. Research Questions and Hypotheses The following research questions and corresponding hypotheses guided this study: R1.Do perceptions of barriers exist that influence quality care improvement within hospitals and the reduction of medical error? H1A stated that significant barriers exist that impede quality care improvement within hospitals and the reduction of
12 medical error. H10 stated that no significant barriers exist that impede quality care improvement within hospitals and the reduction of medical error. R2. Do the perceptions of barriers to quality care improvement within hospitals differ among nurses and hospital managers and administrators? H2A stated that the perceptions of nurses and hospital managers and administrators significantly differ with regard to barriers to quality care improvement within the hospital setting. H20 stated that the perceptions of nurses and hospital managers and administrators do not significantly differ with regard to barriers to quality care improvement within the hospital setting. Theoretical Framework Organizational-change theory explains the safety of patients and
employees within health-care environments and facilitates the advancement of health-care institutions toward the successful implementation of quality improvement. Organizational change identifies the commitment of organization members toward change and the efficacy of change implementation. Specific habits, learned ―work- arounds,‖ and organizational cultures can contribute to the stagnation of quality- improvement programs (Weiner, 2009). Herscovitch and Meyer (2002) observed that organizational members can commit to implementing organizational change because it is their personal desire to do so (i.e., they value the change); because they are expected to do so (i.e., they have little choice); or because they feel they must do so (i.e., they feel obliged). True commitment is based upon personal motives that reflect the highest level of commitment to organizational change.
13 Quality and quality improvement have been considered concepts of importance for centuries; yet, they continue to lack universally accepted definitions and theoretical basis. Early quality-improvement efforts within the realm of health care included the standardization of nursing care and the development of medical- education standards in 1917 for hospital physicians by the American College of Physicians in 1917 (Bilawka & Craig, 2003). One approach to the development of a related theoretical basis segregates the broad concept of quality into two distinct areas—quality management practice and quality performance (Fynes, 1999). The benefit of this approach is its separation of theory and models into process and measurement. A second approach is to separate the definitions of product and service quality (Bright & Cooper, 1993). The diversity of quality definitions and lack of consensus have contributed to
scarce research into the development of quality theory and models (Bright & Cooper, 1993; Fynes, 1999). Quality-improvement theory is an integration of several management theories including strategic planning, organizational-change processes, and double-loop learning processes (Bilawka & Craig, 2003). Strategic planning not only establishes a vision and goal for an organization, but also identifies the desired goals and ultimate state of the organization. Change management is the process of changing the organizational culture and behavior of the participants to progress toward the desired end state. Double-loop learning is the process of implementing feedback from participants and customers to identify changes or other factors affecting progress toward the desired end state. Quality controls are multilevel processes within complex organizations. Institutional quality processes and controls are developed for specific operations
14 impacting the success of an organization. Institutional quality improvement within hospital settings is focused on the interrelationships between policy, control, and operational functions (Scott, 2003). Multiple feedback loops monitor and correct output from the operational functions. Feedback loops are necessary to identify deviations from the planned outcomes and potential weaknesses within the operations. Contemporary theories and models for quality improvement began to emerge following World War II, during the reconstruction of the Japanese economic system (Landesberg, 1999). During the 1950s, both Deming and Juran participated in the rebuilding of Japanese industry (Dotchin & Oakland, 1992). The Deming (as cited in Ravichandran & Rai, 2000) quality-improvement theory suggests that a systems view of
quality is necessary to address the interrelationships between stakeholders. The Juran (1986) theory focuses on a management approach to quality and quality-improvement processes. Together, the success of Deming and Juran in the recovery of Japanese industry gave rise to the interest of U.S. organizations in quality and quality-improvement models (Walton, 1986). Accredited hospitals receive certification through compliance with the patient-safety standards developed by the JCAHO. These standards are consistent with the major elements of contemporary quality- improvement theories and models. The theory of planned behavior evaluates the manner in which human action is guided (Eccles, Hrisos, Steen, Bosch, & Johnston, 2009). Such a theory-based approach identifies the potential to generate a framework within which to consider factors influencing behavior and the development of interventions toward their modification. The model hypothesizes that three cognitive variables will
predict the intention to 15 perform a behavior. The intention is the major precursor of the behavior; however, perceived behavior control is also a predictor. The application of this theory in the current study to identify perceived barriers of quality improvement toward reduced medical error was expected to facilitate determination as to whether good intentions can be prevented from becoming actions due to a perceived internal or external barrier. Definition of Terms To ensure shared meaning, definitions of operational terms are necessary (Creswell, 2005). The following terms are used throughout the current study and are defined for purposes of the research: Barriers are factors impeding the implementation of error- reduction techniques
(McFadden, Stock, & Gowen, 2006, p. 127). Employee perception is the employee interpretation of the impact of quality- improvement programs on work responsibilities. Walz-Feher, Strickland, and Lenz (1991) indicated that the theoretical definition includes ―critical attributes of the concept’s meaning that differentiate it from other terms‖ (p. 39). Three key steps in the process of developing a theoretical definition are (a) the extent to which assistance is needed, (b) the type of research information obtained, and (c) the level of satisfaction. The process of identifying individual perceptions reveals differences in the manner in which expectations are set. The operational definition of perception is the means used to measure the variables of interest. A Likert-type survey measured the perceptions of selected frontline personnel in the current study. Medical error refers to ―the failure of a planned action to be completed as intended or the use of a wrong plan to achieve an aim‖ (Kohn et al., 2000, p. 54).
16 Quality is ―the extent to which the health care provided is expected to achieve the most favorable balance of risks and benefits‖ (De Leon, 2004, p. 1). Quality assessment is ―a process for measuring quality of care. It consists of numerous approaches which define quality of care, select indicators for measurement, collect data, [and] analyze and interpret results‖ (Larson & Muller, 2003, p. 2). Quality assurance is ―an effort to change or improve the level of health care based upon measures of quality‖ (Larson & Muller, 2003, p. 2). Quality of care is ―the minimum acceptable level of performance or results, what constitutes excellent performance or results, and the range in between‖ (Kinney, 2001, p. 2). Quality improvement refers to ―the ongoing systematic process
of using quality measurements to identify problems and to implement strategies to improve the quality of care‖ (Weissman et al., 2005, p. 3). Transferability refers to ―generalizability of the findings and results of the study to other settings, situations, populations, or circumstances‖ (Lincoln & Guba, 1990, p. 56). Assumptions An assumption is an accepted belief in the absence of evidence to the contrary (Ramsey, 2005). The current study was subject to several assumptions. Nurses and hospital managers and administrators were assumed to be willing to participate in research that identifies their perceptions surrounding why quality improvement is not more effective within their employing institutions. Medical error can have significant legal and financial implications to the institution and negative consequences for
17 employees. It was also assumed in this study that health-care leaders may be hesitant to participate in research that may result in negative findings surrounding their employing organizations. However, survey distribution through internal mail generated reversal of this concern. Unlike self-administered surveys, the distribution of questionnaires through an internal mail system provides sufficient privacy for participants to respond with confidence in terms of confidentially (Rea & Parker, 2005). Additionally, use of a secured, advanced tracking Web site allowed the exclusion of any information identifying participants. Another assumption of the current study was that the participants would be honest in their survey responses. With self-reported data, respondents can be prone to memory error or harbor an unwillingness to disclose accurate information (Rea & Parker, 2005).
Hospital personnel may desire to project a positive image regarding their institutions, particularly when dealing with a potentially controversial topic such as medical error. Consequently, they may not reply candidly to all questions (Singleton & Straits, 1999). The number and cross section of respondents in this study was assumed to adequately represent the target population. Surveys were distributed across the hospital system to nurses and hospital managers and administrative personnel; however, data collection was reliant upon voluntary participation. Therefore, the risk was present of data inaccurately reflecting the diversity of hospital personnel. Scope, Limitations, and Delimitations Data were collected in the current study through a survey to evaluate if perceived barriers to quality improvement impact the reduction of medical error. A sample of 162 clinical and administrative personnel employed within a central- Florida hospital provided
18 a representative sample of this population within a hospital setting. The data collected in the research provided a clearer understanding of how the perceptions of hospital personnel related to quality-improvement barriers affect the reduction or elimination of medical error. Many confounding variables associated to hospital management systems exist that are related to medical error including hospital size, resources, and leadership. These variables could have affected the data collection and/or findings of this current study. This potential limitation and possible lack of honesty with the survey responses could impact both the data and generalization of the findings. This investigation involved variables describing quality- improvement practice within hospital settings or other professional medical environments. Survey distribution included personnel across the hospital setting. A letter of introduction instructed
participants to answer all questions and to answer them honestly to reduce response bias. According to Creswell and Clark (2007), ―Wave analysis is a procedure that monitors response bias. Surveys are checked at regular intervals to see if responses are consistent during the survey collection process‖ (p. 411). Although surveys tend to produce weak validity and strong reliability, such research presents all subjects with a standardized stimulus and facilitates the elimination of unreliability in the observations of the respective study. A small sample size and low response rate can be problematic (Sivo, Saunders, Chang, & Jiang, 2006); hence, a response rate of 60% was targeted in the current research. Literature on the use of surveys for data collection has indicated that an acceptable return rate is between 50% and 60% (Kaplowitz, Hadlock, & Levine, 2004; Sills & Song, 2002). 19
Delimitations imply deliberately imposed limitations on a research design (Russell, 2004). A delimitation in the current study involved other hospital personnel possibly differing significantly from the characteristics of the hospital personnel within the research sample. The focus of the study was to determine how various personnel perceptions of barriers to the implementation of quality improvement impact the reduction of medical error. Differences between medical-error management systems within the study-site hospital, or differences that may exist between adverse-event reporting systems, are beyond the scope of the research. Finally, leadership and organizational structures could impact the implementation and effectiveness of quality- improvement strategies; however, these variables were also excluded from the research. Summary Patient care within hospitals has been affected by the high rate
of medical error adversely impacting patient safety (Kohn et al., 2000). Accredited hospitals have implemented peer-reviewed medical-error management systems to comply with federal and state standards. Understanding why efforts have not resulted in a higher reduction of medical error is necessary to reduce the potential risk of harm to patients including death. Quality-improvement systems and controls may not be the most effective because of the perception of direct-care personnel and hospital management and administration. Collecting the perceptions of various hospital personnel was expected to assist in identifying causal factors for the lack of progress in quality improvement. Hospital leadership will benefit from the findings of this study and the data related to personal beliefs associated with implementation of quality-improvement processes potentially leading to the reduction of medical error. The results will contribute to improving the
20 manner in which hospital personnel respond to external and internal pressures connected to the implementation of change and the effectiveness of those efforts. An extensive literature review was conducted to guide this quantitative study. 21 Chapter 2: Literature Review The United States is renowned for one of the most innovative health-care systems in the world. However, with the increased focus on quality improvement and medical error, this status is declining (Kohn et al., 2000). National programs and supporting federal agencies are in place, poised to develop quality measurement standards for hospitals toward minimizing medical error (Harrington, 2005). Despite efforts toward
quality metric standardization and acknowledgement of medical error within hospitals, the cost associated with these errors remains a major challenge for hospitals (Mello, Studdert, Thomas, Yoon, & Brennan, 2007). An analysis of literature pertaining to medical error, quality improvement, and barriers to the reduction of medical error reveals the need to examine the perceptions of medical personnel, as they relate to causal factors for medical error, toward the development of more effective quality-improvement systems. A historical overview lays the foundation for an examination of how medical error impacts the health-care industry financially and structurally. A culture of health-care safety can motivate employee commitment toward quality improvement and set a tone toward success with the reduction of medical error. Through an investigation of perspectives on medical error, the impact of health-care leadership, and the outcomes of medical-error strategies and initiatives toward its reduction and improved regulatory
oversight, are likely to be more consistent and effective. Historical Overview The IOM (1999) published a report that served as a catalyst to raising public concern and focusing attention on the problem of medical error and potential solutions. 22 The report estimated that medical error has caused up to 98,000 deaths per year within the United States. A key recommendation was to reduce such error by 50% over the following 5 years. During 2003, the JCAHO issued new patient-safety standards (Deavers et al., 2004). As a result, 24 states enacted mandatory medical-error reporting (Weinberg et al., 2005). Public awareness of medical error within hospitals increased due to the publication of related studies and increased availability of hospital-quality report
cards (Pawlson, 2002). Despite these initiatives, investigation into the progress made by hospitals in reducing medical error during the 5 years following the IOM (2006) report has been inconclusive due to a lack of consistent methods of measurement and evaluation (Berntsen, 2004; Young, 2005). Prior to the 1999 IOM publication, health-care organizations engaged in investigations of events that caused harm to patients; however, this was a systems-based approach to the problem. The focus was on individuals and mistakes, rather than on the events that combined to cause the incidents. Based upon a ―name and blame‖ culture, the emphasis of such investigations was on punishment rather than prevention (Department of Veteran Affairs, 2009). The tendency to ―play the blame game‖ is an unfortunate aspect of human nature (Simpson, 2002). The increasing number of malpractice suits filed each year reinforces the practice of assigning fault, which is automatically paired with the search for monetary retribution. However, studies have
indicated that only a fraction of medical errors are caused by individual actions, and over one third of the cases studied were unable to assign blame to a single individual (Krizek, 2000). Blame is often interpreted as punishment and remains a major concern of medical professionals. Wolf and Serembus (2004) surveyed 400 medical professionals using 23 open- and closed-ended questions related to actions following medical error. Clinicians who made mistakes and reported them in good faith typically endured humiliation and reprisal. Fear of administrative response was a common theme in examinations seeking causal factors for unreported medical error. An assumption remains that errors are actions with intention that failed to achieve desired results. Paget (1998) identified medical error linked to the intentions of medical personnel to
establish a culture of blame and provide an opportunity for others to criticize those who made the mistakes. Waring (2005) conducted a qualitative case study with particular focus on factors inhibiting medical-error reporting. Interviews were conducted with 42 medical and management staff within a medium-sized hospital located within the English midlands. The interviews gathered information related to changes in the management of safety, incident reporting systems, attitudes and practice regarding incident reporting, and issues surrounding the management of medical performance. The transcribed interview data were analyzed through a qualitative data-analysis computer package, which identified several findings; one was related to both the fear of blame and the fear of reporting. All of the physicians interviewed in the Waring (2005) study made reference to the ―blame thing‖ or ―blame culture‖ when discussing apprehension surrounding incident reporting. Blame equated to poor performance and the potential
for punishment. The most common source of blame was associated with the public and the press. Contributing to this external source of blame was increased litigation and questioned professional competence, leading to poor references and tarnished reputations. 24 Health-Care Culture Recent changes in health-care approaches to patient safety have dissipated the culture of blame because medical error is primarily attributed to systems rather than individuals (Collins et al., 2009). Observation supported by interview data collected from 163 physicians in a study conducted by Collins et al. (2009) revealed three forms of blame—self-blame, blame targeting impersonal forces or the system, and blame targeting other individuals. Physicians were primarily blamed for perceived error and bad
outcomes spurring scrutiny of their actions and their inability to foresee impending problems. Physician self-blame extended beyond minor errors to those causing patient deaths. Second to physician self-blame was placing the responsibility of error on forces such as lack of time, difficult diagnoses, and the transfer of care, indicating passive acceptance of the manner in which the health-care system operates. Data have also revealed physicians assigning blame to colleagues as a last resort, which often resulted in questioning this logic. Adjusting to a blame-free culture is challenging due to the prevalence of physician self-blame (Engel, Rosenthal, & Sutcliffe, 2006). The shift requires a systems perspective (Collins et al., 2009). A prevailing blame culture points to this environment as a major source of medical error (Khatri, Brown, & Hicks, 2009). The movement to improve quality of care is imperative as informed patients are actively engaging in
health-care choices. However, health-care organizations are finding it difficult to move from a culture of blame to a more just culture without establishing a balance between control-based and commitment- 25 based management. Medical error has always been present and is likely to continue because it involves human behavior. Smith (2005) suggested that human behavior contributes to medical error because of heuristics, fixation, pattern thinking, and overconfidence. Heuristics enables individuals to judge situations based upon first impression rather than logical examination of all involved factors. Under stress, the focus of attention may lead to creative solutions that can miss obvious factors. Fixation error is the persistent failure to revise diagnoses, even in the face of available evidence. Pattern thinking results in
individuals seeing what they expect rather than what exists, increasing the number of misdiagnoses. Overconfident behavior in medical personnel can lead to believing personal knowledge is greater than is demonstrated, adversely affecting patient perspectives of care quality. Health-Care Leadership Many studies on hospital quality of care have focused on the patient perspective (Gonzalez-Valetin & Padin-Lopez, 2005; Juwaheer & Kassean, 2006; Pakdil & Harwood, 2005; Wann-Yih, Shih-Wen, & Hsin-Ping, 2004). This patient-centered approach operates from the assumption that leaders are unaware of the quality perceptions of patients, resulting in low service performance (Caruana & Pitt, 1997; Frost & Kumar, 2001; Parasuraman, Zeithaml, & Berry, 1988; Rohini & Mahadevappa, 2006; Wann-Yih et al., 2004). Fewer health-care studies have discussed the perceptions of executive leaders, as they pertain to quality care (Frost &
Kumar, 2001; Ovretveit, 2005). Ovretveit (2005) indicated that further study is necessary to examine the theoretical gap between the provider perspective of care quality and that of executive 26 leaders who influence the quality-management process. Research on medical error has identified that, in addition to poor resource development for improvement systems, organizational culture and personnel behavior contribute to the progress of quality improvement (Jiang, Lockee, Bass, & Fraser, 2008; Ovretveit, 2005). The perceptions of hospital personnel, as they pertain to barriers, impact the implementation of quality- improvement measures targeting the reduction of medical error (Jiang et al., 2008). Studies have also shown the importance of hospital leadership to the success of quality initiatives (Jiang et al., 2008; Meyers, 2004; Sandrick, 2005).
The improvement of health-care service begins with recognition of the need for effective, empowering leaders at all organizational levels (Janes & Mullan, 2007). The success of hospital leadership affects quality improvement and the reduction of medical error. These leaders understand the practice of care, but may lack the confidence, knowledge, and skill to take action on needed improvements. Health-care leaders maintain that medical health care is unique, and solutions for quality improvement must be sought from the inside out (Krause & Hidley, 2008). Quality-improvement leadership requires the implementation of reliable systems that support the organization as a whole and serve as a collaborative tool across the culture (Krause & Hidley, 2008). Leadership drives the organizational shift to a culture of safety. Krause and Hidley (2008) suggested the following components to sustain such a culture: (a) alignment among leadership across the health-care system with the
objective of patient safety to create an effective coalition, and (b) analysis of system performance versus individual performance for an inclusive culture. Medical error typically results from complex processes across the organization. To sustain improved 27 patient safety, all personnel must be included in communication via organizational leadership. The IOM (1999) described the aims and components of an ideal health-care system, but did not provide a template for the organizational leadership needed for its achievement. Medical staff, nursing staff, ancillary services, and executive management all play a role in the organizational leadership that sustains patient care. Successful programs characterize improvement teams and leadership support (Cowen et al., 2008). Health-care systems must determine how to deploy and manage
patient-focused teams and maintain a connection with resources and the priorities of organizational leadership. In response to the need for leadership competencies, the National Center for Healthcare Leadership developed an empirically derived model focused on leadership. This common model provides the framework to guide health- care leadership and the improved performance of individuals and organizations (Calhoun et al., 2008). The health-leadership competency model includes three domains— transformation, execution, and people. Competencies reflect individual performance and provide indications for additional development opportunities. Organizational leadership shapes a safety culture, contributing to a reduction in medical error. Outcomes of Medical Error According to the Agency for Healthcare Research and Quality (AHRQ; 2005), thousands of patients die each year as a result of medical error. Common mistakes
include minor infractions such as medication error resulting in minimal to no harm to patients. However, other errors result in serious harm including death (McFadden et al., 2006). Such events are unexpected and, if not death, involve serious physical or 28 psychological injury (JCAHO, 2005). Of all medical errors reported to the JCAHO, 13.4% were surgeries performed on inaccurate patient sites; 10.8% caused postoperation complications. Those medical errors resulting in patient suicide totaled 11.9%. With the exception of the suicides, the reporting of these events has been 64.6% self-report and 15% via patient complaint. Researchers have suggested that conflicting and dysfunctional improvement programs complicate the delivery of quality within American health-care environments (McFadden et al., 2006; Sahney, 2003). The IOM (1999)
confirmed that the cost of medical error within the United States was $29 billion. However, additional psychosocial variables include loss of morale among providers, diminished patient satisfaction, increased patient discomfort, and loss of trust within the health- care system. These factors take their toll in the form of decreased worker productivity, reduced school attendance by children, and lower levels of population health status (Wexler, 2007). The IOM (1999) reported that between 44,000 and 98,000 patients are injured on an annual basis (Kohn et al., 2000). Crane and Crane (2006) similarly concluded that medical error is widespread within contemporary hospitals. Health Grades Inc. (2005) reported that 195,000 Americans die each year due to preventable errors, ranking hospital error between the fifth and eighth leading cause of death. As a result, increased pressure is placed on hospital leaders to focus on quality-improvement programs and provide a safe environment for all stakeholders (Bradley et al., 2003;
Crane & Crane, 2006; Kohn et al., 2000). McFadden et al. (2006) described the critical nature of improved understanding of the linkage between quality-improvement processes and human lives when addressing the issue of medical error. 29 The magnitude of injury and death resulting from medical error was researched in an extensive Harvard medical-practice study that reviewed the patient records of 51 hospitals across the state of New York (Brennan et al., 1991). Using weighted totals, the researchers estimated that, among 2,671,863 patients discharged from New York hospitals during 1984, 98,609 experienced adverse events (3.6%) and 27,179 (1%) involved negligence. Adverse events of any kind occurred in 4% to 14% of all admissions; 50% to 70% were due to preventable error (Wu, Huang, Stokes, &
Pronovost, 2009). The IOM investigated the problem of medical error to develop improvement strategies (Kohn et al., 2000). The researchers compiled a comprehensive literature review of related studies published within the decade following the Harvard Medical Practices Study (Brennan et al., 1991; Kohn et al., 2000). A subsequent IOM (2006) report concluded that medical error remains a pervasive and widespread problem and additional research was indicated. Health Grades Inc. (2005) conducted a study focused on hospital patient safety, sampling the records of nearly 40 million Medicare patients to assess the mortality and economic impact of medical error and related injury. Records corresponding to nationwide hospital admissions from 2002 through 2004 were analyzed. The findings indicated that 250,246 individuals within the United States died as a result of potentially preventable, in-hospital medical error during the study period. Additionally, the
incidence of errors from a lack of patient safety increased from 1.18 million to 1.24 million. The IOM (2006) reported that 1.5 million preventable, adverse events related to medication error occur within the United States each year, costing as much as $3.5 billion 30 annually. The report noted that, of the five steps involved in medication administration— procuring, prescribing, dispensing, administering, and monitoring a drug—errors occur most often during the prescribing and administration phases. Medication-related error occurs frequently within hospitals. Although not all medical errors result in actual harm, those that do, can be costly. A single adverse drug event adds, on average, more than $2,000 in hospitalization costs. This translates to $2 billion per year, nationwide, in hospital costs alone (Birkmeyer & Diminck, 2004).
Perceptions Patients and hospital personnel. A search for existing literature related to quality-improvement systems, medical error, and barriers to progress was conducted for the current study using the following databases: EBSCO host, Medline, Gale PowerSearch, and ProQuest. The search revealed multiple studies on the perceptions of patients and hospital personnel regarding barriers to quality improvement, as well as the impact of these barriers on the implementation of improvement measures to reduce avoidable medical error. Mazor, Goff, Dodd, and Alper (2008) conducted a qualitative study to understand patient perceptions of medical error and their perceptions surrounding how providers respond to such error. The manner in which provider response or nonresponse influences patient reaction was also examined. During the 17 interviews of the Mazor et al. study, 23 incidents of medical error were identified through
data collected from patients or their families. Provider responses to the error varied from not meeting family needs to neglecting the establishment of a trust of care. Mazor et al. concluded that lack of disclosure will not ensure against patients or their families learning of error. In fact, this will often lead patients to suspect error where none exists. 31 Dean, Farooqi, and McKinley (2004) described the perceptions and attitudes of primary health-care team members with regard to quality- improvement initiatives to identify any potential obstacles. The researchers found two major challenges in implementing quality improvement. First, a perceived gap exists between the potential of health-care workers and what they can actually achieve. Effective implementation of quality-improvement systems is dependent upon organizational staff. Effective
teamwork can be accomplished when each participant engages in the process and the process engages each participant. Systems aimed at reducing medical error are most beneficial when the process not only meets the needs of the organization, but also meets the skill level of the frontline workers. The second challenge to implementing quality improvement is the need to promote team understanding and involvement. Utilization of quality-improvement initiatives toward reduced medical error must uniformly address each employee, fully employing the skills each worker has developed. The role of each employee must be understood and each must be actively engaged in the change process. Griffin and Neal (2000) combined theories of individual performance with those of organizational climate to develop a framework for investigating perceptions of safety within organizations. The framework provides a link between perceptions of the work environment and individual behavior within that environment.
The measurement of employee perceptions and measurable indicators of improvement within the work environment is important to understanding the impact perceptions have on workplace outcomes. Understanding the framework for identifying the type of quality-improvement 32 interventions that will best meet the needs of the organization provides an environment most conducive to reducing medical error through engaged employee participation. Exploration of the perceptions of health-care workers with regard to quality improvement can facilitate the implementation of effective quality-improvement processes. Clinical personnel play a pivotal role in the success of such initiatives. Understanding and participating in the quality-improvement process increases ownership and success (Ashley, 2000; Bolton & Goodenough, 2003; Koch
& Fairly, 1993; Packer, 1998). A management gap exists between theory and practice when it comes to the role of management. This, in turn, leads to ineffective processes (Williams, Pladevall, & Fendrick, 2003). Further, policies and required data collection can lead to a failure in personnel participation in quality improvement. Price, Fitzgerald, and Kinsman (2007) explored the perceptions of nurse managers and clinical nurses with regard to quality improvement within their respective practices. A descriptive, qualitative research method was employed by collecting data through semistructured interviews and constant comparative analysis. The findings confirmed variant understanding of quality improvement by clinical personnel including how it applies to practice. Participating nurse managers and clinical nurses blamed each other for not recognizing the potential benefits. Integral to any quality-improvement process is the need to generate participation and commitment from each employee engaged in the
initiative. Medical professionals. Historically, considerable reluctance has been evident among medical professionals to openly discussing medical error for fear of legal recourse or a compromised reputation. Deterrents to such discussion include the threat of 33 malpractice suits, high expectations of patient families and/or society, disciplinary action by licensing boards, and threats to job security. However, experts believe that individual providers are not the underlying cause of medical error. The high level of stress associated with delivering medical care, the similarities in spelling and pronunciation of many drug names, the nationwide shortage of health-care workers, and the lagging attention to safety within the health-care industry contribute to the nondisclosure of
medical error. Increased awareness of medical error has increased interest in how patients, families, and providers respond to such error (Mazor et al., 2008). It is therefore important to study how perceived conclusions are generalized with patients experiencing medical error. Past studies of these patients included only those who considered taking legal action or who participated in a formal disclosure program. Mazor et al. (2008) interviewed a sample of patients and family members to describe events they perceived as medical error and the subsequent consequences. During the 17 interviews, 23 incidents of perceived medical error were recounted. A variety of factors led the patients and family members to conclude that an error had occurred. These included the health- care provider who administered care informing the patient or family of an error, or the health-care provider informing the patient or family that the outcome of care resulted in an error.
Physician perspectives on quality care and medical error within the health-care setting are both negative and positive. Manwell, Williams, Babbott, Rabatin, and Linzer (2009) conducted a study with a sample of 32 family physicians and internists located in the upper midwest region of the United States and New York City. The study was 34 conducted to determine how medical error can be minimized while maximizing medical outcomes. Areas targeted for improvement toward reduced medical error included teamwork, aligned leadership values, diversity, collegiality, and respect among workers. Factors identified by the physicians as adversely affecting quality care were related to practice management and an inability to participate in decision making. Inadequate resources and time, as well as a lack of necessary equipment, were additional factors.
Despite strong motivation to minimize medical error, several barriers to the implementation of positive patient-safety practice are evident within existing literature. Kalisch and Aebersold (2006) suggested that lack of leadership support is a significant barrier to eliminating adverse care events. If hospital employees perceive that the reduction of medical error is not a priority of the executive leadership of their organizations, the staff will tend to adopt a similar viewpoint, regardless of their personal perspectives. Fear of blame or punishment is a significant barrier to reform. Kalisch and Aebersold reported that many nurses believe retribution is an inherent aspect of a plan targeting the reduction of medical error. Administrators operate on the assumption that fear of punishment motivates hospital staff to act more responsibly. As indicated earlier, the opposite is typically true. When a medical error occurs, fearful employees may intentionally neglect to report the incident (Crane & Crane, 2006; Gawande, Studdert,
Orav, Brennan, & Zinner, 2003; Kalisch & Aebersold, 2006). Improvement Initiatives Existing literature has suggested that quality-improvement initiatives have failed to engage health-care workers (Davies, Powell, & Rushmer, 2007), especially physicians. This has been attributed to the lack of time and resources necessary to enable physicians 35 to participate in improvement efforts. However, Davies et al. (2007) concluded that causal factors go deeper than these issues to involve differing definitions of quality care, conflicting views on responsibility, concern over the impact of medical error, and the belief that a high quality of care is already being delivered. The perceptions of health- care workers also indicate that quality initiatives are ineffective, a waste of resources, and hold the potential to adversely impact patient care (Reason &
Hobbs, 2003). Engaging health-care workers in quality-improvement measures to reduce medical error will require addressing these perceptions and utilizing skills and experience to harness appropriate processes toward positive change. Hospital leaders have an incentive to reduce or eliminate medical error due to financial risk from lawsuits, the potential for increased regulation, and loss of customers from greater public awareness (Savey, 2003). Important barriers exist within hospitals, impeding quality-improvement efforts. Scott (2003) found that highly skilled workers employed in various hospital positions are resistant to formal organizational structure and controls. Organizational resistance can be a barrier to accepting additional quality- improvement controls. Gaining related knowledge was the cornerstone of the current research study. Understanding how hospital organizations have responded to change initiatives targeting improved quality will benefit future study of organizational and
leadership theory and models. The development and implementation of initiatives implemented to improve quality rely upon successful execution (McAlearney, 2008; Singla, Kitch, Weissman, & Campbell, 2006; Wachter & Pronovost, 2006). Health-care leaders overwhelmed with the daily demands of addressing clinical, managerial, and community issues may not 36 sufficiently prepare for leadership (Hoffmann & Perry, 2005; Ramanujam & Rousseau, 2004; Russell & Greenspan, 2005). McAlearney (2008) suggested using leadership- development programs to improve quality and efficiency within realms of health care impacting medical error. He conducted qualitative research employing standard, semistructured interviews with more than 200 experts filling health-care leadership
positions. The objective of the McAlearney study was to investigate the perspectives of various health-care leaders on quality care, patient safety, and their organizational impact. The identified perceptions provided opportunities to improve quality and efficiency within health-care environments. These opportunities included increasing the caliber and care quality of the workforce, improving education, reducing turnover, and focusing on specific strategic priorities related to quality and efficacy. As consumers, patients have a high degree of interest in hospital quality (Sofaer, Crofton, Goldstein, Hoy, & Crabb, 2005). The Centers for Medicare and Medicaid Services (2005) engaged in several initiatives to publicly report the results of measures of care-provider performance to help consumers make more informed decisions and hold hospitals accountable. During the mid 1990s, the AHRQ (2005) developed a survey entitled Consumer Assessments of Healthcare Providers and Systems. The instrument is focused on a national effort to measure, report, and improve the
quality of health care based upon the perspectives of patients and care providers. Sofaer et al. (2005) conducted a qualitative study using 16 patient focus groups across Baltimore, Los Angeles, Phoenix, and Orlando. These markets offered the best opportunity to recruit a diversity of participants due to the wide range of regional hospital facilities and available health-care coverage options. The participants indicated which 37 safety domains of the Consumer Assessments of Healthcare Providers and Systems were the most important to them, which did not impact their choice of hospitals, and those domains they perceived as unimportant. The results of the study indicated that both consumers and patients have a high degree of interest in hospital quality and considered a high proportion of safety-domain items on the survey as sufficiently important to force
them to change hospitals. The important areas highlighted by the patients were physician communication, nurse and hospital-staff communication, staff responsiveness to patient needs, and the manner in which problems were avoided with medications or care following hospital discharge. Reduction strategies. Although past literature has suggested various approaches to the reduction of medical error, research focused on one common approach seems to present a panacea to such reduction—standardization (Hoffman & Mark, 2006). Processes, tools, technology, and equipment are standardized because variation increases complexity and the risk of error (Griffin & Haraden, 2005; Hosford, 2008; Ransom, Kini, Jones, & Ransom, 2005; Williams, Schmalt, Morton, Koss, & Loeb, 2005). Kohn et al. (2000) opined that many errors are prevented by designing standardized processes that make it difficult for incorrect actions to manifest. Leape (2002) indicated that research
has been inconsistent in determining the extent of processes, tools, and technology methods that reduces medical error. Naveh, Katz-Navron, and Stern (2005) disagreed with the view of traditional methods of developing and implementing safety procedures providing definitive results. Kohn et al. (2000) defined a medical error as ―the failure of a planned action to be completed as intended or the use of a wrong plan to achieve an aim‖ (p. 28). McFadden 38 et al. (2006) explored current strategies for reducing medical error within hospitals. Past research approaches to medical error are limited to a small subset of systems-oriented solutions (Bright & Cooper, 1993). Studies have indicated that hospitals are making progress toward implementing improvement measures to successfully reduce medical error (Clarke, Krause, & Hidley, 2006). However, findings
have also identified an ongoing gap between hospital practice and the perceived importance of such measures. McFadden et al. sampled 21 medical units within a general hospital and cross-validated the data collected to 15 units in another hospital. The findings demonstrated that perceived safety procedures and clear communication flow reduce medical error only when managers practice safety to demonstrate its priority within the respective hospital unit. Health-care providers are motivated to report medical error. Clarke et al. (2006) opined that this motivation is developed from professionalism, regular feedback, addressing system problems to avoid work-arounds, and developing a nonpunitive workplace culture. The development of a culture of safety must make reporting easy, communicate the benefits of reporting, ensure confidentiality, and commit to changing the system rather than the individual. Crane and Crane (2006) proposed that the use of
failure mode affects analysis as a solution to medical error. This process identifies potential failures, identifies actions that could eliminate the failures, and actively documents the process for review and training. Mandatory or nonmandatory medical-error reporting continues to challenge organizations attempting to obtain a realistic measure of organizational performance. Mehta and Gogtay (2005) indicated that health-care organizations are responsible for 39 acknowledging medical error and expressing concern to the involved staff, physicians, patients, families, and community. The effectiveness of mandatory error reporting is measureable. Bhattacharya and Catherine (2004) conducted a survey study with physicians and hospital administrators that revealed the reporting of medical error as
causal to improvements in health care. Weissman et al. (2005) concluded that more than two thirds of hospital executives are opposed to mandatory medical-error reporting when the information is made public. This indicates that public disclosure of medical-error information discourages the internal reporting of such error. Existing literature on improvement strategies and their implementation has revealed that little is known surrounding the design of effective quality-improvement interventions (Bosch, van der Weijden, Wensing, & Grol, 2006). Rather than analyzing perspective barriers to the development and content of effective interventions, most literature has analyzed solely obstacles to their implementation. Bosch et al. (2006) conducted a qualitative analysis of a sample of 20 quality- improvement studies reporting barriers to both educational and organizational quality interventions. Their findings indicated that the design of quality-improvement interventions remains within an infancy stage due to a continued mismatch between the level of
identified barriers and the type of interventions selected for use. Quality-improvement initiatives effectively implemented within health-care organizations perform as operational and strategical responses to system challenges (Alavi & Yasin, 2008). Alavi and Yasin (2008) conducted a qualitative study to determine if the utilization of quality-improvement initiatives affect the operational environment of health-care facilities. Instrumentation consisted of four open-ended 40 questions and 80 items focused on environmental-change factors, response factors, and the effectiveness of quality-improvement initiatives with a Likert-type response scale. The population sample consisted of 39 health-care organizations—hospitals, outpatient clinics, laboratories, and pharmaceutical firms. The findings indicated that the
participating health-care organizations were aware of the challenges associated with quality improvement and medical error and were actively engaged in safety initiatives to address those challenges. However, the effectiveness of safety initiatives depends largely upon their interpretation by health-care personnel. Regulatory oversight. Numerous initiatives implemented to improve the quality of health care aim to establish standards for the management of medical error within hospitals. During 1996, the JCAHO created a sentinel event policy for the management of such error (Schyve, 2000). The federal government established the AHRQ in 1999 as an effort to coordinate federal quality-improvement efforts. National patient-safety goals introduced during 2003 by the JCAHO focused on health-care improvement efforts targeting a set of high-priority problem areas (Hyman, 2006). Accreditation standards developed by the JCAHO were providing hospitals with latitude on the manner in which
they complied with the standards. During the nine years between publication of the Harvard Medical Practices Study and the 2001 IOM report, various initiatives toward improving the quality of health care within hospitals were implemented. Legislation was enacted in 20 states for voluntary and mandatory reporting of medical error. In 1996, the JCAHO instituted the sentinel event policy that established standards for the management of medical error within accredited hospitals and the federal government established the AHRQ. Despite 41 these initiatives and increased public awareness, the 2000 IOM identified ―few tangible actions to improve patient safety‖ (as cited in Kohn et al., 2000, p. 5). On July 29, 2005, the Patient Safety and Quality Improvement Act of 2005 was enacted to improve patient safety by encouraging voluntary and
confidential reporting of medical-error events adversely affecting patients. The Act signified the commitment of the federal government to fostering a culture of safety (AHRQ, 2005). It established a national voluntary reporting system for medical error and public disclosure of the reported information was prohibited (Kinnaman, 2007). The Patient Safety and Quality Improvement Act of 2005 achieved one of the IOM goals of establishing an environment that encourages voluntary reporting while protecting information from public disclosure. Private entities known as patient-safety organizations were created to collect confidential information related to medical error, analyze it, and provide recommendations toward improved patient safety, which began to transform the reporting system. The Patient Safety and Quality Improvement Act served to improve patient safety through confidentiality and established reporting standards that eliminated patient and provider identity. The Act embraced a culture of nonpunitive
support (Mewshaw, White, & Walrath, 2006). In December 2005, the American Medical Association (2005) developed approximately 140 performance measures covering 34 clinical areas. An agreement with Congress called for physicians to voluntarily report their performance on these measures as part of a national quality-improvement program. The measures were collectively considered best practice and consisted of diagnostic tests and treatments that 42 demonstrated the ability to improve clinical outcomes. The American Medical Association also developed measures to assess physician performance and compensation. Local mandates. In addition to federal legislation mandating the measurement and monitoring of medical error, individual states implemented additional oversight
measures. In 2000, the Florida legislature appointed the Florida Commission on Excellence in Healthcare, which focuses on issues of quality health care, patient safety, and the reduction of medical error. In September 2003, the Medical Incidents Law went into effect within the state of Florida, which impacted the responsibilities of licensed health-care providers. Some of these requirements include recognition of error-prone situations, process improvement for patient outcomes, reporting responsibilities, and public education. Patient-safety organizations were deployed in compliance with the Patient Safety and Quality Improvement Act of 2005. They worked with clinicians and health-care organizations to identify, analyze, and reduce the risks and hazards associated with patient care. Florida was one of the first states to recognize the link between medical malpractice, medical error, and patient safety. Primarily in response to the 1999 IOM report, the Florida legislature established the Florida Patient
Safety Corporation (FPSC) with the purpose of monitoring patient safety throughout the state. In 2005, the Florida legislature provided funding for the FPSC to establish the voluntary Near Miss Reporting System, based upon a successful system used within the commercial-aviation industry. The objective of the program was to establish a statewide reporting system that was timely, anonymous, standardized, and easy to use. An important aspect of the system was the provision of immunity from legal penalties and sanctions (FPSC, 2008). 43 Unfortunately, in response to an ongoing budget crisis, funding for the FPSC was discontinued in 2008 and indefinitely suspended. In 2004, two state amendments were passed in Florida—the Patients’ Right-to- Know About Adverse Medical Incidents Act of 2004, known as Amendment 7, and the
Three Strikes and You Are Out Act of 2004, known as Amendment 8 (as cited in Yaeger, 2009). Collectively, this legislation was aggressively promoted by Florida trial attorneys and their efforts reversed many of the patient-safety gains of the FPSC mandates. Amendment 7 eliminated confidentiality provisions and allowed full access to all patient records including all meetings, morbidity and mortality conferences, root-cause analysis, and any other professional exchanges of information related to patient injury or death. Upon first analysis, this appears to be a positive change; however, according to risk- management professionals, Amendment 7 has done immense harm to the quality assurance and peer-review protections developed over 2 decades and caused an immediate decline in the reporting of adverse events throughout the state (Barach & Small, 2005). The Three Strikes You Are Out Act of 2004 (as cited in Yaeger, 2009) presented
an unintended adverse effect on the reporting of near misses and adverse medical events. It directed the Florida Board of Medicine to revoke medical licenses from providers with three ―adjudicated malpractice incidents‖ (p. 126). A strike is considered ―any malpractice judgment, findings from disciplinary cases, decisions of binding arbitration finding malpractice, and malpractice judgments from any other state‖ (Barach & Small, 2005, p. 762). It is hoped that the new federal regulations from the patient-safety organizations will help resolve the Florida situation. They went into effect on January 44 19, 2009 and described a clear, legally-protected framework for how hospitals, clinicians, and health-care organizations can work together to improve patient safety and nationwide quality of care. Thirty-nine states, including Florida, have mandatory or
voluntary systems in place for reporting medical error. Florida requires that all licensed health-care facilities establish an internal risk-management program that includes (a) investigation and analysis of the frequency and causes of general categories and specific types of adverse patient incidents, and (b) the development of appropriate measures to minimize the risk of adverse patient incidents (Kaiser Family Foundation, 2008). Health-care facilities within the state of Florida must electronically report data on hospital-acquired infections to the Agency for Healthcare Administration, as specified in federal regulations. Health- care facilities must also submit annual reports to the Department of Health on adverse sentinel events (Rosenthal & Takach, 2008). Disparities Hospitals are complex organizations requiring diverse technology and specialized skills in personnel. They must manage data, consumer demands, market fluctuations, and
changing medical information while assimilating these elements into quality patient care. The fallibility of human nature renders quality management difficult (Griffin & Haraden, 2005; Hughes & Clancy, 2005). As a result, when a significant medical error occurs, hospitals must cope with a variety of adverse consequences. They must effectively execute key processes related to patient access, service delivery, and revenue realization to optimize the relationships among quality, efficiency, and cost (Orlikoff & Totten, 2010). 45 The U.S. Bureau of Labor Statistics (2006) reported that health care is the largest U.S. industry, providing 14 million jobs. Between 2006 and 2016, this industry is predicted to generate 3 million new wage and salary positions (DeGeetern, 2009). The delivery of quality health care is accomplished through offering
personal services. The connection between the health-care provider and patient requires development to improve the current delivery model. The IOM (2001) identified the need for a redesigned health- care delivery system to improve patient safety. Areas were identified that contributed to quality problems such as an increase in chronic disease, a poorly organized delivery system, and constraints in deploying information technology. The IOM (2001) set forth six aims for improvement and 10 rules for a redesigned health-care system. The ten rules included care based upon continuous healing of relationships, the patient as the source of control, a free flow of shared knowledge and information, evidence-based decision making, safety as a system priority, transparency, anticipated needs, decreased waste, and cooperation among clinicians. Health Grades Inc. (2005), an independent health-care quality research organization that grades hospitals based upon a range of criteria and provides hospital ratings to health plans and other
payers, issued its third update to the 1999 IOM report. The report found that, despite widespread participation in patient-safety initiatives to reduce the frequency of medical error, progress toward improved safety was slow during the 6 years since the IOM report. According to Brady, Ho, and Clancey (2008), ―Quality improvement is, by definition, an endeavor, never completely fulfilled. Quality improvement is marked by the constant effort to raise performance and produce results that are consistently better‖ (p. 396). Realistically, 100% improvement cannot be achieved; however, continuous 46 improvement from one measurement period to the next must be evident. The AHRQ (2005) has been documenting steady improvement in the quality of American health care since it began publishing reports on the quality of U.S. health care and disparities in
2003. Improvement has occurred; however, at a modest annual rate of 1.5%. The Brady et al. analysis draws on more than three dozen data sources to measure quality and disparity in five areas—the effectiveness of care, patient safety, the timeliness of care, patient centeredness, and the efficiency of care. Culture of Safety Time is a barrier to patient safety. Staff reduction, complex procedures, and heavy patient loads contribute to the frequency of medical error (Gawande et al., 2003; Kalisch & Aebersold, 2006; McFadden et al., 2006). When staff perceives an insufficient amount of time to conduct a root-cause analysis of medical incidents, the tendency is to dismiss the error so the provider can return to patient care (Kalisch & Aebersold, 2006; McFadden et al., 2006; Weeks & Bagian, 2000). Similarly, daily workload interruptions are a barrier to reducing medical error. Nurses frequently multitask while attending to critically ill patients, carrying cell phones or pagers for both
hospital and personal calls. Kalisch and Aebersold (2006) found that nurses reported 84 to 120 interruptions during a single shift. Ineffective teamwork and lack of accountability often prevent the development of quality-improvement programs (Gawande et al., 2003; Kalisch & Aebersold, 2006). Kalisch and Aebersold reported that poor teamwork increases the number of medical errors. Promoting a culture of safety within health-care organizations is an important strategy toward improving patient safety. A positive culture recognizes errors will occur 47 and seeks opportunities to implement preventative strategies (Edwards et al., 2008). A safe culture must move from a punitive to a blame-free environment. Edwards et al. (2008) used the AHRQ hospital survey on patient safety to measure the safety culture
within various units of a hospital. The survey facilitated identification of common dimensions of organizational climate and the assessment of staff perceptions of safety. The instrument consists of questions measuring the dimensions of a safety culture and patient-safety outcomes. Edwards et al. distributed the survey to various hospital personnel employed within two Atlanta hospitals. Their findings identified key areas of concern regarding perceptions of the frequency of reporting error, manager expectations and actions, and teamwork. Understanding personnel perceptions allowed the development of safety initiatives such as safety rounds, education in event reporting, and a nonpunitive response to error. Public awareness of medical error has increased since the 1990s. Information sources, such as report cards comparing health-care providers, provide consumers access to patient-outcome information. Access to the Internet, public notification, and media
focus transformed the consumer into an informed participant. Studies analyzing evidence-based quality ratings motivated hospital administrators to improve patient safety to retain customers. Access to health-care reports appears to be a positive motivator for consumers and industry leaders. Werner and Asch (2005) investigated the negative impact of health-care reports on patient-care services. These researchers found that physicians may avoid certain patients or overly rely upon interventions to improve their ratings. 48 Despite claims within existing literature that most medical error is due to system problems (Collins et al., 2009), Menachemi, Shewchuk, O’Connor, Berner, and Allison (2005) concluded that physicians tend to underestimate medical error and generally favor remedies. The researchers examined perceptions potentially
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  • 1. PERCEIVED BARRIERS TO QUALITY IMPROVEMENT AND REDUCED MEDICAL ERROR: A QUANTITATIVE STUDY by Cynthia J. Bergs Copyright 2014 A Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Health Administration
  • 2. UNIVERSITY OF PHOENIX All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. Microform Edition © ProQuest LLC. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code ProQuest LLC. 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, MI 48106 - 1346 UMI 3647288 Published by ProQuest LLC (2014). Copyright in the Dissertation held by the Author.
  • 3. UMI Number: 3647288 Abstract This quantitative, descriptive study explored the perceptions of hospital personnel with regard to quality-improvement initiatives as a collective barrier potentially inhibiting the reduction of medical error. A sample population of 162 personnel drawn from a nonprofit hospital within central Florida participated in an online questionnaire known as the Safety Climate Survey. The findings revealed a statistically significant relationship between the perceptions of personnel implementing quality- improvement measures and their positions within the hospital, the largest variance occurring between unit nurses and hospital administration. No significant relationships were found among the demographic variables of age, gender, ethnicity, specialty certification,
  • 4. educational level, years with current employer, years within specialty area, title, shift, employment status, and job satisfaction. The perception differences between unit nurses and hospital administration was, overwhelmingly, the strongest indicator of impeded quality-improvement measures. The findings hold leadership implications for nurse educators, preceptors, administrators, recruiters, and managers. Recommendations for practice are presented for health-care leaders to support decisions with the potential to reduce medical error. Dedication To my parents who provided the opportunity, strength, and guidance to reach this life goal. Your own strength, kindness, and perseverance guided me to successful completion. To my husband, who never questioned the long
  • 5. nights nor my ability. To all those within health-care leadership who are striving to effectively reduce medical error and improve the patient experience while acknowledging the perceptions of those working under their authority. This work is offered as a contribution toward our mutual goal of improved quality of care. Acknowledgments My deepest appreciation is expressed to my mentor, Dr. Mary Tan, who was always available to provide a solid, clear perspective; answer questions, and offer strong encouragement. Dr. Tan’s constructive feedback significantly contributed to the guidance needed in the completion of this study. Committee members, Dr. Julia Aucoin and Dr. Hans-Peter de Ruiter, also extended invaluable support, enrichment, direction, and honest feedback. I am grateful for the guidance and support
  • 6. of Dr. Timothy DeGroot who supported me through the last stages of my dissertation process. Special thanks to my editor, Jill Eastwood, and my statistician, Fanchao Yi, both of whom played an important role in my success through their provision of specialized expertise and guidance. Table of Contents List of Tables ............................................................................................... ...................... ix List of Figures ............................................................................................... .......................x Chapter 1: Introduction………………………………………………………… …………1
  • 7. Background ............................................................................................... ...............3 Problem Statement .......................................................................................... ..... ....4 Purpose of the Study ............................................................................................... .6 Significance of the Study .........................................................................................7 Nature of the Study ............................................................................................... ...8 Research Questions and Hypotheses .....................................................................11 Theoretical Framework ..........................................................................................12 Definitions …………….............................................................................. ...........15 Assumptions ............................................................................................... ............16 Scope, Limitations, and Delimitations ...................................................................17
  • 8. Chapter Summary ............................................................................................... ...............19 Chapter 2: Literature Review .............................................................................................2 1 Historical Overview ............................................................................................... 21 Health-Care Culture ............................................................................................... 24 Health-Care Leadership .........................................................................................25 Outcomes of Medical Error ...................................................................................27 Perceptions ......................................................................................... ...... ..........................30 Patients and Hospital Personnel ...................................................................................30 Medical Professionals
  • 9. ............................................................................................... ...32 Improvement Initiatives ............................................................................................... ......34 Reduction Strategies ............................................................................................... .....37 Regulatory Oversight ............................................................................................... ....40 Local Mandates ..................................................................................... .......... .............42 Disparities ............................................................................................... ...........................44 Culture of Safety ............................................................................................... .................46 Reporting................................................................................ ............................................49 Quality Improvement ............................................................................................... ..........51 Chapter Summary ...............................................................................................
  • 10. ...............52 Chapter 3: Research Methods ............................................................................................5 4 Research Design…….............................................................................. ...............54 Methodology Appropriateness…………………………………………………...55 Accomplishing the Study’s Goals………………………………………………..56 Informed Consent and Confidentiality........................................................................ .58 Population and Sampling ...................................................................................... .......5 9 Data Collection Methods .......................................................................................62 Instrument ….. ............................................................................................... ........63 Validity and Reliability ..........................................................................................64 Data Analysis ...............................................................................................
  • 11. ..........66 Chapter Summary ............................................................................................... ...69 Chapter 4: Results ............................................................................................... ...............70 Instrument…………………………………………………………… …………..70 Demographic Data ………………………………………………………………71 Findings ……........................................................................................ .................73 Chapter Summary ............................................................................................... ...93 Chapter 5: Conclusions and Recommendations ................................................................95 Findings and Interpretations………………………………………………..……96
  • 12. Limitations…………………………………………………………… ………….99 Implications and Recommendations……………………………………………100 Future Research……………………………………………………….…… …..102 Chapter Summary……………………………………………………………... 103 References ............................................................................................... .........................105 Appendix A: Study-Site Permission ................................................................................129 Appendix B: Informed Consent .......................................................................................130 Appendix C: Invitation to Participate ..............................................................................131 Appendix D: Permission to Use Survey ..........................................................................132
  • 13. List of Tables Table 1. Mean and Standard Deviations for Age and Experience of the Study Participants ............................................................................................... .........................73 Table 2. Frequency Distribution for the Administrators Study Group (n = 44) ............77 Table 3. Frequency Distribution for the Nurse-Managers Study Group (n = 37).........79 Table 4. Frequency Distribution of the Nurses Study Group (n = 81) ..........................80 Table 5. Descriptive Statistics From Survey Responses ................................................81 Table 6. Spearman Product-Moment Correlation .........................................................83 Table 7. Kruskal-Wallis Test and Multiple Comparison ...............................................84 Table 8. Survey Responses According to the Age of the Participants ...........................86 Table 9. Survey Responses According to Years of Participant Experience in Position
  • 14. ............................................................................................... ...........................86 Table 10. Survey Responses According to Participant Experience in Specialty .............86 Table 11. Survey Responses According to Years of Participant Experience in Organization ............................................................................................... ...................87 Table 12. Gender of Study Participants ...........................................................................88 Table 13. Cronbach’s Alpha Results by Domain .............................................................89 Table 14. Basic Statistics ............................................................................................... ..90 Table 15. Normality Check .............................................................................................. 90 Table 16. Constant Variance Check ................................................................................92 List of Figures
  • 15. Figure 1. Number and percentages of study participants by gender .................................72 Figure 2. Mean age of the study participants and mean years of experience within the health-care field ............................................................................................... .73 Figure 3. Safety-climate domains based upon participant age .........................................75 Figure 4. Safety-climate domains based upon number of years participants in specialty ............................................................................................... ..........................76 Figure 5. Safety-climate domains based upon years of participant experience in position................................................................................... ........................................76 1
  • 16. Chapter 1: Introduction Medical errors and other human mistakes within the hospital setting can result in unnecessary injury to patients or death (Kohn, Corrigan, & Donaldson, 2000). The consequences have been identified by various studies (Berntsen, 2004; Young, 2005), motivating multiple initiatives toward improved quality of medical care within hospitals. Special-interest groups have taken action to encourage hospital administrators to make related changes to reduce medical error. This action has included new patient-safety standards, mandatory and voluntary event reporting, and public awareness through hospital-performance ―scorecards‖ (Deavers, Pham, & Liu, 2004; Pawlson, 2002; Weinberg, Hilborne, & Nguyen, 2005). This current study was conducted to determine whether the perceptions of hospital personnel regarding barriers to implementing quality- improvement measures contributed to either the reduction or elimination of medical error
  • 17. within hospitals. Hospital leaders have instituted strategies to reduce or eliminate medical error in the interest of risk management, to adhere to new regulations, and to decrease the potential loss of customers from public awareness of such error (Messner, 1998; Orser, 2000). A key factor to reducing patient injury from such error is public awareness because it spurs implementation of the appropriate steps for institutional protection. However, barriers can exist that impede quality-improvement efforts. Messner (1998) cited organizational culture, restructuring, quality-control functions, and costs as contributing to slowed progress with quality-improvement programs. According to 2 Walshe and Shortell (2004), the future success of such programs ―depends on cultural as
  • 18. much as structural change in health care systems and organizations‖ (p. 103). Steep authority hierarchies, lack of teamwork, an unwillingness to acknowledge human fallibility, and the tendency to take punitive action rather than learn from error are all prevailing aspects of the organizational and professional culture within the realm of health care. These characteristics act as barriers to quality care improvement and patient safety (Akins & Cole, 2005; Sexton, Pronovost, & Thomas, 2000; VanGeest & Cummins 2003). Scott (2003) found that highly skilled workers employed in hospital positions may be resistant to formal organizational structure and controls. Such organizational resistance can also serve as a barrier to accepting additional quality-improvement controls and structure. Additional research on related change initiatives and barriers may contribute to the improvement of care quality and reduce medical error while adding to the existing body of knowledge within this area of study. The aim behind this current quantitative study was to explore
  • 19. the perceptions of hospital personnel related to quality-improvement initiatives as barriers potentially inhibiting the reduction of medical error. Addressing such reduction is difficult. No standardized system of measurement exists, resulting in various interpretations of data. Additionally, the perceptions of both patients and medical personnel, in terms of existing barriers, may impede progress toward the reduction of medical error. The perceptions of nurses, hospital management, and administrative leaders may also affect quality- improvement measures toward such reduction (Bognár et al., 2008). In the current study, data were collected from a sample of nurses, as well as management and administrative leaders within the health-care setting, with the aim of providing a clearer understanding 3 of how perceived barriers to the implementation of quality-
  • 20. improvement systems may adversely affect the reduction of medical error. Existing literature was reviewed on the impact of related regulations and quality systems in place, as well as research focused on how patients and medical personnel perceive hospital cultures of safety. Background A number of patients are injured each year within the United States as a result of unnecessary medical error within hospital settings (Bilawka & Craig, 2003; Kohn et al., 2000). The Harvard Medical Practices Study reviewed patient records during 1984 at 51 hospitals located within the state of New York (Brennen et al., 1991). A substantial amount of medical error was found to be due to negligence. The Institute of Medicine (IOM) introduced the Quality of Healthcare in America Project during 1998 to investigate the problem of medical error and develop improvement strategies (Kohn et al., 2000). The project (IOM, 1999) identified medication procedural error and
  • 21. diagnostic error as common problems within hospitals. Their prevention requires systems improvement with a goal toward higher quality patient care. The Harvard Medical Practices Study (Brennan et al., 1991) and the IOM (1999) report became catalysts for the public awareness that brought not only public but also media attention to the development of possible solutions for medical error. During 2003, the Joint Commission on Accreditation of Healthcare Organizations (JCAHO; 2005) issued new patient-safety standards that prompted multiple states to enact mandatory medical-error reporting (Weinberg et al., 2005). Both published studies on medical error and hospital-performance scorecards stimulated public awareness and demanded overall improvement in health care (Collins, Block, Arnold, & Cristakis, 2009). However, 4
  • 22. despite the subsequent initiatives, implementation of standards, and mandatory reporting, evidence of these measures resulting in sufficient improvement in patient care and a positive effect on reducing medical error is inconclusive. This is due to a lack of consistent, comparable data, as well as a lack of protocol standardization in the measurement and evaluation of such error (Berntsen, 2004). In fact, studies have indicated an increased amount of medical error following initiative implementation (Berntsen, 2004; Young, 2005). Barriers to progress in hospital-improvement systems include (a) inconsistent definitions, (b) voluntary versus mandatory reporting, and (c) ineffective systems of measurement (Young, 2005). Problem Statement A general problem for the health-care industry is the increased medical error that has resulted in as many as 98,000 deaths per year and adds $29 billion to annual health- care costs (Berntsen, 2004). The specific problem is the
  • 23. perceptions of hospital personnel regarding quality-improvement initiatives, which may act as a collective barrier inhibiting the reduction of medical error. Studies conducted after the related IOM (1999) report revealed minimal hospital progress toward reducing the number and significance of medical errors (Berntsen, 2004; Young, 2005). As a result, federal and state mandates were imposed on health-care providers toward this end (Weinberg et al., 2005). Health-care organizations have instituted safer practice and agencies and professional societies have issued safety guidelines and recommendations to address medical error. Additionally, funding was dedicated to patient- safety research. The JCAHO issued national patient-safety goals, and patient-safety legislation was introduced 5
  • 24. (Burney, 2001; Deavers et al., 2004). Despite these efforts, health care is not measurably safer than it was in 2000 (Weinburg et al., 2005). Existing data suggest an underestimation of the magnitude of preventable health-care error. Many errors continue to go unreported; consequently, accurate incidence rates are unknown (Berntsen, 2004). The use and effectiveness of safety measures are also unknown due to unreliable outcome measures. Advances in patient safety include the increased use of technology to reduce medical error, increased training toward improved teamwork, and full disclosure of medical error (Leape & Berwick, 2005). Barriers to progress include the culture and complexity of health care, continuing skepticism resulting in the perception of system failures as the underlying cause of most health-care error, and the fear of malpractice liability that inhibits a willingness to discuss or even admit such error. Research on
  • 25. causal factors has been traditionally focused on clinical indicators. While this body of study was centered in specific errors occurring within specific situations, the need remains to find evidence of commonality among measures and related theory (Rathert, Fleig-Palmer, & Palmer, 2006). Few empirical studies have asked frontline employees for their perceptions of key contributing factors in the prevention of medical error. Reason (2001) indicated that hospital employees can add valuable information in this regard because they ―are at the sharp end of complex systems‖ (p. 14). The current quantitative study was conducted to determine whether the perceptions of hospital personnel created barriers to the implementation of quality- improvement measures to reduce or eliminate medical error. The population sample included nurses, health-care managers, and hospital administrators. The findings may 6
  • 26. benefit hospital leaders seeking successful implementation of quality-improvement strategies to reduce medical error through clearer communication of goals, increased management and support, and planning that is adequate to effectively address the problem under study (Messner, 1998). Purpose of the Study The purpose of this current quantitative study was to explore the perceptions of hospital personnel regarding quality-improvement initiatives as a collective barrier potentially inhibiting the reduction of medical error. The research method was suitable for the study because it led to identifying possible solutions to ineffective quality- improvement processes. The independent variable for this study was the perceptions of barriers to quality care improvement measured by a Likert-type scale survey. The dependent variable was the statistical data of the sample characteristics.
  • 27. A simple descriptive survey design was appropriate for this study because it supported a description of the characteristics or behaviors of a particular population in a systematic and accurate fashion. A systematic sample was selected by obtaining a list of employees meeting the following criteria: (a) employed a minimum of six months within the study-site hospital; and (b) currently employed as a floor nurse, nurse manager, or administrative employee. The participants were chosen through stratified, systematic sampling. Every employee meeting the criteria was selected for study participation. The goal was to obtain 110 total participants. Discoveries are measurable in quantitative study, and data are presented from an objective rather than subjective viewpoint (Balnaves & Caputi, 2001). Questions surrounding the perceptions of the participants in the current study regarding the culture 7
  • 28. of safety within the health-care environment were formulated to use quantifiable data for explaining and predicting phenomena (Creswell, 2003). Ordinal data were collected through a Likert-type, self-administered survey completed by hospital personnel. At the ordinal level of measurement, the data were ranked in a manner resulting in an order to the data but with no definite interval. Significance of the Study A survey on the safety climate of hospitals was expected to detect employee concerns related to patient safety and help foster communication on this topic; however, limited evidence existed to indicate that survey scores are related to patient-safety outcomes (Colla, Bracken, Kinney, & Weeks, 2005). The findings contributed to existing knowledge on the effectiveness of quality-improvement programs in reducing medical error within hospital settings through clearer communication of organizational
  • 29. goals, increased management and support, and planning that is adequate to effectively address the problem under study (Messner, 1998; Rathert et al., 2006). Rathert et al. (2006) recommended that further study address the perceptions of frontline hospital employees in this regard. Such study was expected to validate the problems and lead to positive change via a system approach. Increasing knowledge surrounding quality improvement and perceptions contributing to medical error is important to both American society and hospital administration because it addresses implementation of the proper tools to reduce such error. This, in turn, will reduce the potential for patient injury or death and the medical costs associated with related insurance coverage and lawsuits. Responsibility for quality care must involve both clinicians and nonclinicians and their effective interaction in response to conflict (Lagrosen & Lagrosen, 2006;
  • 30. 8 Reinertsen, 2005; Stanley, 2006). The working/professional relationship between employees and leadership influences work attitudes (Tangirala, Green, & Ramanujam, 2007). Leadership is not static, and the influence of these relationships can be a predictor of employee performance (Bauer, Erdogan, Linden, & Wayne, 2006; Tangirala et al., 2007). The ability of management to acknowledge and understand employee misconceptions surrounding quality improvement can result in improved methods of training and deployment. Multidisciplinary health-care teams are reliant upon information and tools they are provided to dispense quality care to patients. Understanding differences in the perceptions of nurses, managers, and administrators regarding quality-improvement processes was expected to provide a better opportunity for the development of quality-improvement processes.
  • 31. Nature of the Study In the current study, a quantitative survey design was applied to collect data facilitating description of the perceptions of medical personnel surrounding barriers to implementing quality-improvement measures that may impede the reduction of medical error. Data analysis addressed the research questions and hypotheses via simple frequency distribution, central tendency, and variability. Several factors justify the application of a quantitative design such as the type of data collected, analyzed, and interpreted; identified variables; and verified theories or explanations supporting the proposed hypothesis (Creswell & Clark, 2007). The use of quantitative research designs may determine whether relationships exist between variables while controlling certain occurrences (Leedey & Ormrod, 2001). Researchers have used quantitative descriptive designs to question participants
  • 32. 9 surrounding their attitudes, opinions, and behaviors and to find relationships between respondent characteristics and the behaviors they exhibit. The design also provides an opportunity for participants to be autonomous with regard to their particular roles in quality improvement because the survey allows for the collection of information through confidential means. Survey responses were extended in an anonymous fashion with no identifying information collected such as names or addresses. Each participant was assigned a five-digit identification number to protect confidentiality. Quantitative methods analyze variables, test hypotheses, measure numbers, replicate findings, and generate statistics (Neuman, 2003). Quantitative data may produce identifiable trends across a broad spectrum of participants, as well as identify improvement processes, controls, and results (Creswell, 2003). Quantitative
  • 33. methodologies focus on surveys and the statistics drawn from the data. A quantitative research design was appropriate for the current study due to its potential for identifying possible solutions for ineffective quality-improvement processes. A descriptive, quantitative method was appropriate for this study because of its logic of inquiry, which gains a greater amount of information on a particular characteristic within a particular field of study. Barriers or problems to implementing quality-improvement programs were identified (Creswell, 2003). There was no manipulation of variables or attempt to establish causality occurred. Quantitative studies produce measurable or testable data that are objective in nature and provide a general conclusion from specific findings (Balnaves & Caputi, 2001). The data collected in quantitative research provides information that can be applied to a more generalized population through theories and/or hypotheses pertaining to
  • 34. 10 the phenomena under study. Such research is typically conducted from an approach that views knowledge as acquired through direct observation and experimentation. Consequently, in the current research, data were collected from a select group of participants who were representative of a larger population. The transferability of data refers to how findings can be generalized or transferred to other contexts or settings. Thus, the survey administered in the current study included questions surrounding the relationships among measured variables and using numeric data for purposes of explaining phenomena. A simple, systematic survey ensured the equal probability of participation in the current study. Respondents were grouped into subsets sharing particular characteristics (Creswell, 2003), which included their professional position as
  • 35. a general nurse, nurse manager, or administrator within a central-Florida hospital. Demographic information included gender; age; marital status; educational level; employment (i.e., full or part time); and occupational status. The aim of sample selection was to obtain an unbiased cross section of a hospital population. The simple descriptive survey design was appropriate for the quantitative method to gain a general sense of the phenomenon under study and to form theories that could be tested in future quantitative research (de la Torre, 2011; Polonsky & Waller, 2005). A qualitative method was not deemed appropriate for the current study because such research ―is typically used to answer questions about the complex nature of phenomena, often with the purpose of describing and understanding the phenomena from the participants’ point of view‖ (Leedy & Ormrod, 2001, p. 101). While qualitative methods are effective in the appropriate research environment, ―qualitative researchers
  • 36. 11 construct interpretive narratives from their data and try to capture the complexity of the phenomenon under study‖ (p. 103). The current study is quantitative in nature because the research was conducted to gain a clearer understanding of intentionality or meaning. Quantitative research is designed to quantify relationships between variables. This study explored the perceptions of hospital personnel regarding quality-improvement initiatives as a collective potential barrier inhibiting the reduction of medical error. The identification of relationships and the measurement of variables was conducted through descriptive statistics (Hopkins, 2000). A self-administered, Likert-type survey provided a quantitative description of the trends, attitudes, and opinions of the population sample in the current study (Creswell,
  • 37. 2005). Survey research enables generalization of the findings and inferences surrounding particular characteristics or attitudes. A simple descriptive design allows the opportunity to determine specific times for data collection and analysis (Polonsky & Waller, 2005), as opposed to a longitudinal design that produces immediate results. A survey questionnaire was appropriate for the statistical analysis of the current study because it generated quantitative data with measurable findings (Balnaves & Caputi, 2001). Overall, the simple descriptive design accomplished the goals of the research. Research Questions and Hypotheses The following research questions and corresponding hypotheses guided this study: R1.Do perceptions of barriers exist that influence quality care improvement within hospitals and the reduction of medical error? H1A stated that significant barriers exist that impede quality care improvement within hospitals and the reduction of
  • 38. 12 medical error. H10 stated that no significant barriers exist that impede quality care improvement within hospitals and the reduction of medical error. R2. Do the perceptions of barriers to quality care improvement within hospitals differ among nurses and hospital managers and administrators? H2A stated that the perceptions of nurses and hospital managers and administrators significantly differ with regard to barriers to quality care improvement within the hospital setting. H20 stated that the perceptions of nurses and hospital managers and administrators do not significantly differ with regard to barriers to quality care improvement within the hospital setting. Theoretical Framework Organizational-change theory explains the safety of patients and
  • 39. employees within health-care environments and facilitates the advancement of health-care institutions toward the successful implementation of quality improvement. Organizational change identifies the commitment of organization members toward change and the efficacy of change implementation. Specific habits, learned ―work- arounds,‖ and organizational cultures can contribute to the stagnation of quality- improvement programs (Weiner, 2009). Herscovitch and Meyer (2002) observed that organizational members can commit to implementing organizational change because it is their personal desire to do so (i.e., they value the change); because they are expected to do so (i.e., they have little choice); or because they feel they must do so (i.e., they feel obliged). True commitment is based upon personal motives that reflect the highest level of commitment to organizational change.
  • 40. 13 Quality and quality improvement have been considered concepts of importance for centuries; yet, they continue to lack universally accepted definitions and theoretical basis. Early quality-improvement efforts within the realm of health care included the standardization of nursing care and the development of medical- education standards in 1917 for hospital physicians by the American College of Physicians in 1917 (Bilawka & Craig, 2003). One approach to the development of a related theoretical basis segregates the broad concept of quality into two distinct areas—quality management practice and quality performance (Fynes, 1999). The benefit of this approach is its separation of theory and models into process and measurement. A second approach is to separate the definitions of product and service quality (Bright & Cooper, 1993). The diversity of quality definitions and lack of consensus have contributed to
  • 41. scarce research into the development of quality theory and models (Bright & Cooper, 1993; Fynes, 1999). Quality-improvement theory is an integration of several management theories including strategic planning, organizational-change processes, and double-loop learning processes (Bilawka & Craig, 2003). Strategic planning not only establishes a vision and goal for an organization, but also identifies the desired goals and ultimate state of the organization. Change management is the process of changing the organizational culture and behavior of the participants to progress toward the desired end state. Double-loop learning is the process of implementing feedback from participants and customers to identify changes or other factors affecting progress toward the desired end state. Quality controls are multilevel processes within complex organizations. Institutional quality processes and controls are developed for specific operations
  • 42. 14 impacting the success of an organization. Institutional quality improvement within hospital settings is focused on the interrelationships between policy, control, and operational functions (Scott, 2003). Multiple feedback loops monitor and correct output from the operational functions. Feedback loops are necessary to identify deviations from the planned outcomes and potential weaknesses within the operations. Contemporary theories and models for quality improvement began to emerge following World War II, during the reconstruction of the Japanese economic system (Landesberg, 1999). During the 1950s, both Deming and Juran participated in the rebuilding of Japanese industry (Dotchin & Oakland, 1992). The Deming (as cited in Ravichandran & Rai, 2000) quality-improvement theory suggests that a systems view of
  • 43. quality is necessary to address the interrelationships between stakeholders. The Juran (1986) theory focuses on a management approach to quality and quality-improvement processes. Together, the success of Deming and Juran in the recovery of Japanese industry gave rise to the interest of U.S. organizations in quality and quality-improvement models (Walton, 1986). Accredited hospitals receive certification through compliance with the patient-safety standards developed by the JCAHO. These standards are consistent with the major elements of contemporary quality- improvement theories and models. The theory of planned behavior evaluates the manner in which human action is guided (Eccles, Hrisos, Steen, Bosch, & Johnston, 2009). Such a theory-based approach identifies the potential to generate a framework within which to consider factors influencing behavior and the development of interventions toward their modification. The model hypothesizes that three cognitive variables will
  • 44. predict the intention to 15 perform a behavior. The intention is the major precursor of the behavior; however, perceived behavior control is also a predictor. The application of this theory in the current study to identify perceived barriers of quality improvement toward reduced medical error was expected to facilitate determination as to whether good intentions can be prevented from becoming actions due to a perceived internal or external barrier. Definition of Terms To ensure shared meaning, definitions of operational terms are necessary (Creswell, 2005). The following terms are used throughout the current study and are defined for purposes of the research: Barriers are factors impeding the implementation of error- reduction techniques
  • 45. (McFadden, Stock, & Gowen, 2006, p. 127). Employee perception is the employee interpretation of the impact of quality- improvement programs on work responsibilities. Walz-Feher, Strickland, and Lenz (1991) indicated that the theoretical definition includes ―critical attributes of the concept’s meaning that differentiate it from other terms‖ (p. 39). Three key steps in the process of developing a theoretical definition are (a) the extent to which assistance is needed, (b) the type of research information obtained, and (c) the level of satisfaction. The process of identifying individual perceptions reveals differences in the manner in which expectations are set. The operational definition of perception is the means used to measure the variables of interest. A Likert-type survey measured the perceptions of selected frontline personnel in the current study. Medical error refers to ―the failure of a planned action to be completed as intended or the use of a wrong plan to achieve an aim‖ (Kohn et al., 2000, p. 54).
  • 46. 16 Quality is ―the extent to which the health care provided is expected to achieve the most favorable balance of risks and benefits‖ (De Leon, 2004, p. 1). Quality assessment is ―a process for measuring quality of care. It consists of numerous approaches which define quality of care, select indicators for measurement, collect data, [and] analyze and interpret results‖ (Larson & Muller, 2003, p. 2). Quality assurance is ―an effort to change or improve the level of health care based upon measures of quality‖ (Larson & Muller, 2003, p. 2). Quality of care is ―the minimum acceptable level of performance or results, what constitutes excellent performance or results, and the range in between‖ (Kinney, 2001, p. 2). Quality improvement refers to ―the ongoing systematic process
  • 47. of using quality measurements to identify problems and to implement strategies to improve the quality of care‖ (Weissman et al., 2005, p. 3). Transferability refers to ―generalizability of the findings and results of the study to other settings, situations, populations, or circumstances‖ (Lincoln & Guba, 1990, p. 56). Assumptions An assumption is an accepted belief in the absence of evidence to the contrary (Ramsey, 2005). The current study was subject to several assumptions. Nurses and hospital managers and administrators were assumed to be willing to participate in research that identifies their perceptions surrounding why quality improvement is not more effective within their employing institutions. Medical error can have significant legal and financial implications to the institution and negative consequences for
  • 48. 17 employees. It was also assumed in this study that health-care leaders may be hesitant to participate in research that may result in negative findings surrounding their employing organizations. However, survey distribution through internal mail generated reversal of this concern. Unlike self-administered surveys, the distribution of questionnaires through an internal mail system provides sufficient privacy for participants to respond with confidence in terms of confidentially (Rea & Parker, 2005). Additionally, use of a secured, advanced tracking Web site allowed the exclusion of any information identifying participants. Another assumption of the current study was that the participants would be honest in their survey responses. With self-reported data, respondents can be prone to memory error or harbor an unwillingness to disclose accurate information (Rea & Parker, 2005).
  • 49. Hospital personnel may desire to project a positive image regarding their institutions, particularly when dealing with a potentially controversial topic such as medical error. Consequently, they may not reply candidly to all questions (Singleton & Straits, 1999). The number and cross section of respondents in this study was assumed to adequately represent the target population. Surveys were distributed across the hospital system to nurses and hospital managers and administrative personnel; however, data collection was reliant upon voluntary participation. Therefore, the risk was present of data inaccurately reflecting the diversity of hospital personnel. Scope, Limitations, and Delimitations Data were collected in the current study through a survey to evaluate if perceived barriers to quality improvement impact the reduction of medical error. A sample of 162 clinical and administrative personnel employed within a central- Florida hospital provided
  • 50. 18 a representative sample of this population within a hospital setting. The data collected in the research provided a clearer understanding of how the perceptions of hospital personnel related to quality-improvement barriers affect the reduction or elimination of medical error. Many confounding variables associated to hospital management systems exist that are related to medical error including hospital size, resources, and leadership. These variables could have affected the data collection and/or findings of this current study. This potential limitation and possible lack of honesty with the survey responses could impact both the data and generalization of the findings. This investigation involved variables describing quality- improvement practice within hospital settings or other professional medical environments. Survey distribution included personnel across the hospital setting. A letter of introduction instructed
  • 51. participants to answer all questions and to answer them honestly to reduce response bias. According to Creswell and Clark (2007), ―Wave analysis is a procedure that monitors response bias. Surveys are checked at regular intervals to see if responses are consistent during the survey collection process‖ (p. 411). Although surveys tend to produce weak validity and strong reliability, such research presents all subjects with a standardized stimulus and facilitates the elimination of unreliability in the observations of the respective study. A small sample size and low response rate can be problematic (Sivo, Saunders, Chang, & Jiang, 2006); hence, a response rate of 60% was targeted in the current research. Literature on the use of surveys for data collection has indicated that an acceptable return rate is between 50% and 60% (Kaplowitz, Hadlock, & Levine, 2004; Sills & Song, 2002). 19
  • 52. Delimitations imply deliberately imposed limitations on a research design (Russell, 2004). A delimitation in the current study involved other hospital personnel possibly differing significantly from the characteristics of the hospital personnel within the research sample. The focus of the study was to determine how various personnel perceptions of barriers to the implementation of quality improvement impact the reduction of medical error. Differences between medical-error management systems within the study-site hospital, or differences that may exist between adverse-event reporting systems, are beyond the scope of the research. Finally, leadership and organizational structures could impact the implementation and effectiveness of quality- improvement strategies; however, these variables were also excluded from the research. Summary Patient care within hospitals has been affected by the high rate
  • 53. of medical error adversely impacting patient safety (Kohn et al., 2000). Accredited hospitals have implemented peer-reviewed medical-error management systems to comply with federal and state standards. Understanding why efforts have not resulted in a higher reduction of medical error is necessary to reduce the potential risk of harm to patients including death. Quality-improvement systems and controls may not be the most effective because of the perception of direct-care personnel and hospital management and administration. Collecting the perceptions of various hospital personnel was expected to assist in identifying causal factors for the lack of progress in quality improvement. Hospital leadership will benefit from the findings of this study and the data related to personal beliefs associated with implementation of quality-improvement processes potentially leading to the reduction of medical error. The results will contribute to improving the
  • 54. 20 manner in which hospital personnel respond to external and internal pressures connected to the implementation of change and the effectiveness of those efforts. An extensive literature review was conducted to guide this quantitative study. 21 Chapter 2: Literature Review The United States is renowned for one of the most innovative health-care systems in the world. However, with the increased focus on quality improvement and medical error, this status is declining (Kohn et al., 2000). National programs and supporting federal agencies are in place, poised to develop quality measurement standards for hospitals toward minimizing medical error (Harrington, 2005). Despite efforts toward
  • 55. quality metric standardization and acknowledgement of medical error within hospitals, the cost associated with these errors remains a major challenge for hospitals (Mello, Studdert, Thomas, Yoon, & Brennan, 2007). An analysis of literature pertaining to medical error, quality improvement, and barriers to the reduction of medical error reveals the need to examine the perceptions of medical personnel, as they relate to causal factors for medical error, toward the development of more effective quality-improvement systems. A historical overview lays the foundation for an examination of how medical error impacts the health-care industry financially and structurally. A culture of health-care safety can motivate employee commitment toward quality improvement and set a tone toward success with the reduction of medical error. Through an investigation of perspectives on medical error, the impact of health-care leadership, and the outcomes of medical-error strategies and initiatives toward its reduction and improved regulatory
  • 56. oversight, are likely to be more consistent and effective. Historical Overview The IOM (1999) published a report that served as a catalyst to raising public concern and focusing attention on the problem of medical error and potential solutions. 22 The report estimated that medical error has caused up to 98,000 deaths per year within the United States. A key recommendation was to reduce such error by 50% over the following 5 years. During 2003, the JCAHO issued new patient-safety standards (Deavers et al., 2004). As a result, 24 states enacted mandatory medical-error reporting (Weinberg et al., 2005). Public awareness of medical error within hospitals increased due to the publication of related studies and increased availability of hospital-quality report
  • 57. cards (Pawlson, 2002). Despite these initiatives, investigation into the progress made by hospitals in reducing medical error during the 5 years following the IOM (2006) report has been inconclusive due to a lack of consistent methods of measurement and evaluation (Berntsen, 2004; Young, 2005). Prior to the 1999 IOM publication, health-care organizations engaged in investigations of events that caused harm to patients; however, this was a systems-based approach to the problem. The focus was on individuals and mistakes, rather than on the events that combined to cause the incidents. Based upon a ―name and blame‖ culture, the emphasis of such investigations was on punishment rather than prevention (Department of Veteran Affairs, 2009). The tendency to ―play the blame game‖ is an unfortunate aspect of human nature (Simpson, 2002). The increasing number of malpractice suits filed each year reinforces the practice of assigning fault, which is automatically paired with the search for monetary retribution. However, studies have
  • 58. indicated that only a fraction of medical errors are caused by individual actions, and over one third of the cases studied were unable to assign blame to a single individual (Krizek, 2000). Blame is often interpreted as punishment and remains a major concern of medical professionals. Wolf and Serembus (2004) surveyed 400 medical professionals using 23 open- and closed-ended questions related to actions following medical error. Clinicians who made mistakes and reported them in good faith typically endured humiliation and reprisal. Fear of administrative response was a common theme in examinations seeking causal factors for unreported medical error. An assumption remains that errors are actions with intention that failed to achieve desired results. Paget (1998) identified medical error linked to the intentions of medical personnel to
  • 59. establish a culture of blame and provide an opportunity for others to criticize those who made the mistakes. Waring (2005) conducted a qualitative case study with particular focus on factors inhibiting medical-error reporting. Interviews were conducted with 42 medical and management staff within a medium-sized hospital located within the English midlands. The interviews gathered information related to changes in the management of safety, incident reporting systems, attitudes and practice regarding incident reporting, and issues surrounding the management of medical performance. The transcribed interview data were analyzed through a qualitative data-analysis computer package, which identified several findings; one was related to both the fear of blame and the fear of reporting. All of the physicians interviewed in the Waring (2005) study made reference to the ―blame thing‖ or ―blame culture‖ when discussing apprehension surrounding incident reporting. Blame equated to poor performance and the potential
  • 60. for punishment. The most common source of blame was associated with the public and the press. Contributing to this external source of blame was increased litigation and questioned professional competence, leading to poor references and tarnished reputations. 24 Health-Care Culture Recent changes in health-care approaches to patient safety have dissipated the culture of blame because medical error is primarily attributed to systems rather than individuals (Collins et al., 2009). Observation supported by interview data collected from 163 physicians in a study conducted by Collins et al. (2009) revealed three forms of blame—self-blame, blame targeting impersonal forces or the system, and blame targeting other individuals. Physicians were primarily blamed for perceived error and bad
  • 61. outcomes spurring scrutiny of their actions and their inability to foresee impending problems. Physician self-blame extended beyond minor errors to those causing patient deaths. Second to physician self-blame was placing the responsibility of error on forces such as lack of time, difficult diagnoses, and the transfer of care, indicating passive acceptance of the manner in which the health-care system operates. Data have also revealed physicians assigning blame to colleagues as a last resort, which often resulted in questioning this logic. Adjusting to a blame-free culture is challenging due to the prevalence of physician self-blame (Engel, Rosenthal, & Sutcliffe, 2006). The shift requires a systems perspective (Collins et al., 2009). A prevailing blame culture points to this environment as a major source of medical error (Khatri, Brown, & Hicks, 2009). The movement to improve quality of care is imperative as informed patients are actively engaging in
  • 62. health-care choices. However, health-care organizations are finding it difficult to move from a culture of blame to a more just culture without establishing a balance between control-based and commitment- 25 based management. Medical error has always been present and is likely to continue because it involves human behavior. Smith (2005) suggested that human behavior contributes to medical error because of heuristics, fixation, pattern thinking, and overconfidence. Heuristics enables individuals to judge situations based upon first impression rather than logical examination of all involved factors. Under stress, the focus of attention may lead to creative solutions that can miss obvious factors. Fixation error is the persistent failure to revise diagnoses, even in the face of available evidence. Pattern thinking results in
  • 63. individuals seeing what they expect rather than what exists, increasing the number of misdiagnoses. Overconfident behavior in medical personnel can lead to believing personal knowledge is greater than is demonstrated, adversely affecting patient perspectives of care quality. Health-Care Leadership Many studies on hospital quality of care have focused on the patient perspective (Gonzalez-Valetin & Padin-Lopez, 2005; Juwaheer & Kassean, 2006; Pakdil & Harwood, 2005; Wann-Yih, Shih-Wen, & Hsin-Ping, 2004). This patient-centered approach operates from the assumption that leaders are unaware of the quality perceptions of patients, resulting in low service performance (Caruana & Pitt, 1997; Frost & Kumar, 2001; Parasuraman, Zeithaml, & Berry, 1988; Rohini & Mahadevappa, 2006; Wann-Yih et al., 2004). Fewer health-care studies have discussed the perceptions of executive leaders, as they pertain to quality care (Frost &
  • 64. Kumar, 2001; Ovretveit, 2005). Ovretveit (2005) indicated that further study is necessary to examine the theoretical gap between the provider perspective of care quality and that of executive 26 leaders who influence the quality-management process. Research on medical error has identified that, in addition to poor resource development for improvement systems, organizational culture and personnel behavior contribute to the progress of quality improvement (Jiang, Lockee, Bass, & Fraser, 2008; Ovretveit, 2005). The perceptions of hospital personnel, as they pertain to barriers, impact the implementation of quality- improvement measures targeting the reduction of medical error (Jiang et al., 2008). Studies have also shown the importance of hospital leadership to the success of quality initiatives (Jiang et al., 2008; Meyers, 2004; Sandrick, 2005).
  • 65. The improvement of health-care service begins with recognition of the need for effective, empowering leaders at all organizational levels (Janes & Mullan, 2007). The success of hospital leadership affects quality improvement and the reduction of medical error. These leaders understand the practice of care, but may lack the confidence, knowledge, and skill to take action on needed improvements. Health-care leaders maintain that medical health care is unique, and solutions for quality improvement must be sought from the inside out (Krause & Hidley, 2008). Quality-improvement leadership requires the implementation of reliable systems that support the organization as a whole and serve as a collaborative tool across the culture (Krause & Hidley, 2008). Leadership drives the organizational shift to a culture of safety. Krause and Hidley (2008) suggested the following components to sustain such a culture: (a) alignment among leadership across the health-care system with the
  • 66. objective of patient safety to create an effective coalition, and (b) analysis of system performance versus individual performance for an inclusive culture. Medical error typically results from complex processes across the organization. To sustain improved 27 patient safety, all personnel must be included in communication via organizational leadership. The IOM (1999) described the aims and components of an ideal health-care system, but did not provide a template for the organizational leadership needed for its achievement. Medical staff, nursing staff, ancillary services, and executive management all play a role in the organizational leadership that sustains patient care. Successful programs characterize improvement teams and leadership support (Cowen et al., 2008). Health-care systems must determine how to deploy and manage
  • 67. patient-focused teams and maintain a connection with resources and the priorities of organizational leadership. In response to the need for leadership competencies, the National Center for Healthcare Leadership developed an empirically derived model focused on leadership. This common model provides the framework to guide health- care leadership and the improved performance of individuals and organizations (Calhoun et al., 2008). The health-leadership competency model includes three domains— transformation, execution, and people. Competencies reflect individual performance and provide indications for additional development opportunities. Organizational leadership shapes a safety culture, contributing to a reduction in medical error. Outcomes of Medical Error According to the Agency for Healthcare Research and Quality (AHRQ; 2005), thousands of patients die each year as a result of medical error. Common mistakes
  • 68. include minor infractions such as medication error resulting in minimal to no harm to patients. However, other errors result in serious harm including death (McFadden et al., 2006). Such events are unexpected and, if not death, involve serious physical or 28 psychological injury (JCAHO, 2005). Of all medical errors reported to the JCAHO, 13.4% were surgeries performed on inaccurate patient sites; 10.8% caused postoperation complications. Those medical errors resulting in patient suicide totaled 11.9%. With the exception of the suicides, the reporting of these events has been 64.6% self-report and 15% via patient complaint. Researchers have suggested that conflicting and dysfunctional improvement programs complicate the delivery of quality within American health-care environments (McFadden et al., 2006; Sahney, 2003). The IOM (1999)
  • 69. confirmed that the cost of medical error within the United States was $29 billion. However, additional psychosocial variables include loss of morale among providers, diminished patient satisfaction, increased patient discomfort, and loss of trust within the health- care system. These factors take their toll in the form of decreased worker productivity, reduced school attendance by children, and lower levels of population health status (Wexler, 2007). The IOM (1999) reported that between 44,000 and 98,000 patients are injured on an annual basis (Kohn et al., 2000). Crane and Crane (2006) similarly concluded that medical error is widespread within contemporary hospitals. Health Grades Inc. (2005) reported that 195,000 Americans die each year due to preventable errors, ranking hospital error between the fifth and eighth leading cause of death. As a result, increased pressure is placed on hospital leaders to focus on quality-improvement programs and provide a safe environment for all stakeholders (Bradley et al., 2003;
  • 70. Crane & Crane, 2006; Kohn et al., 2000). McFadden et al. (2006) described the critical nature of improved understanding of the linkage between quality-improvement processes and human lives when addressing the issue of medical error. 29 The magnitude of injury and death resulting from medical error was researched in an extensive Harvard medical-practice study that reviewed the patient records of 51 hospitals across the state of New York (Brennan et al., 1991). Using weighted totals, the researchers estimated that, among 2,671,863 patients discharged from New York hospitals during 1984, 98,609 experienced adverse events (3.6%) and 27,179 (1%) involved negligence. Adverse events of any kind occurred in 4% to 14% of all admissions; 50% to 70% were due to preventable error (Wu, Huang, Stokes, &
  • 71. Pronovost, 2009). The IOM investigated the problem of medical error to develop improvement strategies (Kohn et al., 2000). The researchers compiled a comprehensive literature review of related studies published within the decade following the Harvard Medical Practices Study (Brennan et al., 1991; Kohn et al., 2000). A subsequent IOM (2006) report concluded that medical error remains a pervasive and widespread problem and additional research was indicated. Health Grades Inc. (2005) conducted a study focused on hospital patient safety, sampling the records of nearly 40 million Medicare patients to assess the mortality and economic impact of medical error and related injury. Records corresponding to nationwide hospital admissions from 2002 through 2004 were analyzed. The findings indicated that 250,246 individuals within the United States died as a result of potentially preventable, in-hospital medical error during the study period. Additionally, the
  • 72. incidence of errors from a lack of patient safety increased from 1.18 million to 1.24 million. The IOM (2006) reported that 1.5 million preventable, adverse events related to medication error occur within the United States each year, costing as much as $3.5 billion 30 annually. The report noted that, of the five steps involved in medication administration— procuring, prescribing, dispensing, administering, and monitoring a drug—errors occur most often during the prescribing and administration phases. Medication-related error occurs frequently within hospitals. Although not all medical errors result in actual harm, those that do, can be costly. A single adverse drug event adds, on average, more than $2,000 in hospitalization costs. This translates to $2 billion per year, nationwide, in hospital costs alone (Birkmeyer & Diminck, 2004).
  • 73. Perceptions Patients and hospital personnel. A search for existing literature related to quality-improvement systems, medical error, and barriers to progress was conducted for the current study using the following databases: EBSCO host, Medline, Gale PowerSearch, and ProQuest. The search revealed multiple studies on the perceptions of patients and hospital personnel regarding barriers to quality improvement, as well as the impact of these barriers on the implementation of improvement measures to reduce avoidable medical error. Mazor, Goff, Dodd, and Alper (2008) conducted a qualitative study to understand patient perceptions of medical error and their perceptions surrounding how providers respond to such error. The manner in which provider response or nonresponse influences patient reaction was also examined. During the 17 interviews of the Mazor et al. study, 23 incidents of medical error were identified through
  • 74. data collected from patients or their families. Provider responses to the error varied from not meeting family needs to neglecting the establishment of a trust of care. Mazor et al. concluded that lack of disclosure will not ensure against patients or their families learning of error. In fact, this will often lead patients to suspect error where none exists. 31 Dean, Farooqi, and McKinley (2004) described the perceptions and attitudes of primary health-care team members with regard to quality- improvement initiatives to identify any potential obstacles. The researchers found two major challenges in implementing quality improvement. First, a perceived gap exists between the potential of health-care workers and what they can actually achieve. Effective implementation of quality-improvement systems is dependent upon organizational staff. Effective
  • 75. teamwork can be accomplished when each participant engages in the process and the process engages each participant. Systems aimed at reducing medical error are most beneficial when the process not only meets the needs of the organization, but also meets the skill level of the frontline workers. The second challenge to implementing quality improvement is the need to promote team understanding and involvement. Utilization of quality-improvement initiatives toward reduced medical error must uniformly address each employee, fully employing the skills each worker has developed. The role of each employee must be understood and each must be actively engaged in the change process. Griffin and Neal (2000) combined theories of individual performance with those of organizational climate to develop a framework for investigating perceptions of safety within organizations. The framework provides a link between perceptions of the work environment and individual behavior within that environment.
  • 76. The measurement of employee perceptions and measurable indicators of improvement within the work environment is important to understanding the impact perceptions have on workplace outcomes. Understanding the framework for identifying the type of quality-improvement 32 interventions that will best meet the needs of the organization provides an environment most conducive to reducing medical error through engaged employee participation. Exploration of the perceptions of health-care workers with regard to quality improvement can facilitate the implementation of effective quality-improvement processes. Clinical personnel play a pivotal role in the success of such initiatives. Understanding and participating in the quality-improvement process increases ownership and success (Ashley, 2000; Bolton & Goodenough, 2003; Koch
  • 77. & Fairly, 1993; Packer, 1998). A management gap exists between theory and practice when it comes to the role of management. This, in turn, leads to ineffective processes (Williams, Pladevall, & Fendrick, 2003). Further, policies and required data collection can lead to a failure in personnel participation in quality improvement. Price, Fitzgerald, and Kinsman (2007) explored the perceptions of nurse managers and clinical nurses with regard to quality improvement within their respective practices. A descriptive, qualitative research method was employed by collecting data through semistructured interviews and constant comparative analysis. The findings confirmed variant understanding of quality improvement by clinical personnel including how it applies to practice. Participating nurse managers and clinical nurses blamed each other for not recognizing the potential benefits. Integral to any quality-improvement process is the need to generate participation and commitment from each employee engaged in the
  • 78. initiative. Medical professionals. Historically, considerable reluctance has been evident among medical professionals to openly discussing medical error for fear of legal recourse or a compromised reputation. Deterrents to such discussion include the threat of 33 malpractice suits, high expectations of patient families and/or society, disciplinary action by licensing boards, and threats to job security. However, experts believe that individual providers are not the underlying cause of medical error. The high level of stress associated with delivering medical care, the similarities in spelling and pronunciation of many drug names, the nationwide shortage of health-care workers, and the lagging attention to safety within the health-care industry contribute to the nondisclosure of
  • 79. medical error. Increased awareness of medical error has increased interest in how patients, families, and providers respond to such error (Mazor et al., 2008). It is therefore important to study how perceived conclusions are generalized with patients experiencing medical error. Past studies of these patients included only those who considered taking legal action or who participated in a formal disclosure program. Mazor et al. (2008) interviewed a sample of patients and family members to describe events they perceived as medical error and the subsequent consequences. During the 17 interviews, 23 incidents of perceived medical error were recounted. A variety of factors led the patients and family members to conclude that an error had occurred. These included the health- care provider who administered care informing the patient or family of an error, or the health-care provider informing the patient or family that the outcome of care resulted in an error.
  • 80. Physician perspectives on quality care and medical error within the health-care setting are both negative and positive. Manwell, Williams, Babbott, Rabatin, and Linzer (2009) conducted a study with a sample of 32 family physicians and internists located in the upper midwest region of the United States and New York City. The study was 34 conducted to determine how medical error can be minimized while maximizing medical outcomes. Areas targeted for improvement toward reduced medical error included teamwork, aligned leadership values, diversity, collegiality, and respect among workers. Factors identified by the physicians as adversely affecting quality care were related to practice management and an inability to participate in decision making. Inadequate resources and time, as well as a lack of necessary equipment, were additional factors.
  • 81. Despite strong motivation to minimize medical error, several barriers to the implementation of positive patient-safety practice are evident within existing literature. Kalisch and Aebersold (2006) suggested that lack of leadership support is a significant barrier to eliminating adverse care events. If hospital employees perceive that the reduction of medical error is not a priority of the executive leadership of their organizations, the staff will tend to adopt a similar viewpoint, regardless of their personal perspectives. Fear of blame or punishment is a significant barrier to reform. Kalisch and Aebersold reported that many nurses believe retribution is an inherent aspect of a plan targeting the reduction of medical error. Administrators operate on the assumption that fear of punishment motivates hospital staff to act more responsibly. As indicated earlier, the opposite is typically true. When a medical error occurs, fearful employees may intentionally neglect to report the incident (Crane & Crane, 2006; Gawande, Studdert,
  • 82. Orav, Brennan, & Zinner, 2003; Kalisch & Aebersold, 2006). Improvement Initiatives Existing literature has suggested that quality-improvement initiatives have failed to engage health-care workers (Davies, Powell, & Rushmer, 2007), especially physicians. This has been attributed to the lack of time and resources necessary to enable physicians 35 to participate in improvement efforts. However, Davies et al. (2007) concluded that causal factors go deeper than these issues to involve differing definitions of quality care, conflicting views on responsibility, concern over the impact of medical error, and the belief that a high quality of care is already being delivered. The perceptions of health- care workers also indicate that quality initiatives are ineffective, a waste of resources, and hold the potential to adversely impact patient care (Reason &
  • 83. Hobbs, 2003). Engaging health-care workers in quality-improvement measures to reduce medical error will require addressing these perceptions and utilizing skills and experience to harness appropriate processes toward positive change. Hospital leaders have an incentive to reduce or eliminate medical error due to financial risk from lawsuits, the potential for increased regulation, and loss of customers from greater public awareness (Savey, 2003). Important barriers exist within hospitals, impeding quality-improvement efforts. Scott (2003) found that highly skilled workers employed in various hospital positions are resistant to formal organizational structure and controls. Organizational resistance can be a barrier to accepting additional quality- improvement controls. Gaining related knowledge was the cornerstone of the current research study. Understanding how hospital organizations have responded to change initiatives targeting improved quality will benefit future study of organizational and
  • 84. leadership theory and models. The development and implementation of initiatives implemented to improve quality rely upon successful execution (McAlearney, 2008; Singla, Kitch, Weissman, & Campbell, 2006; Wachter & Pronovost, 2006). Health-care leaders overwhelmed with the daily demands of addressing clinical, managerial, and community issues may not 36 sufficiently prepare for leadership (Hoffmann & Perry, 2005; Ramanujam & Rousseau, 2004; Russell & Greenspan, 2005). McAlearney (2008) suggested using leadership- development programs to improve quality and efficiency within realms of health care impacting medical error. He conducted qualitative research employing standard, semistructured interviews with more than 200 experts filling health-care leadership
  • 85. positions. The objective of the McAlearney study was to investigate the perspectives of various health-care leaders on quality care, patient safety, and their organizational impact. The identified perceptions provided opportunities to improve quality and efficiency within health-care environments. These opportunities included increasing the caliber and care quality of the workforce, improving education, reducing turnover, and focusing on specific strategic priorities related to quality and efficacy. As consumers, patients have a high degree of interest in hospital quality (Sofaer, Crofton, Goldstein, Hoy, & Crabb, 2005). The Centers for Medicare and Medicaid Services (2005) engaged in several initiatives to publicly report the results of measures of care-provider performance to help consumers make more informed decisions and hold hospitals accountable. During the mid 1990s, the AHRQ (2005) developed a survey entitled Consumer Assessments of Healthcare Providers and Systems. The instrument is focused on a national effort to measure, report, and improve the
  • 86. quality of health care based upon the perspectives of patients and care providers. Sofaer et al. (2005) conducted a qualitative study using 16 patient focus groups across Baltimore, Los Angeles, Phoenix, and Orlando. These markets offered the best opportunity to recruit a diversity of participants due to the wide range of regional hospital facilities and available health-care coverage options. The participants indicated which 37 safety domains of the Consumer Assessments of Healthcare Providers and Systems were the most important to them, which did not impact their choice of hospitals, and those domains they perceived as unimportant. The results of the study indicated that both consumers and patients have a high degree of interest in hospital quality and considered a high proportion of safety-domain items on the survey as sufficiently important to force
  • 87. them to change hospitals. The important areas highlighted by the patients were physician communication, nurse and hospital-staff communication, staff responsiveness to patient needs, and the manner in which problems were avoided with medications or care following hospital discharge. Reduction strategies. Although past literature has suggested various approaches to the reduction of medical error, research focused on one common approach seems to present a panacea to such reduction—standardization (Hoffman & Mark, 2006). Processes, tools, technology, and equipment are standardized because variation increases complexity and the risk of error (Griffin & Haraden, 2005; Hosford, 2008; Ransom, Kini, Jones, & Ransom, 2005; Williams, Schmalt, Morton, Koss, & Loeb, 2005). Kohn et al. (2000) opined that many errors are prevented by designing standardized processes that make it difficult for incorrect actions to manifest. Leape (2002) indicated that research
  • 88. has been inconsistent in determining the extent of processes, tools, and technology methods that reduces medical error. Naveh, Katz-Navron, and Stern (2005) disagreed with the view of traditional methods of developing and implementing safety procedures providing definitive results. Kohn et al. (2000) defined a medical error as ―the failure of a planned action to be completed as intended or the use of a wrong plan to achieve an aim‖ (p. 28). McFadden 38 et al. (2006) explored current strategies for reducing medical error within hospitals. Past research approaches to medical error are limited to a small subset of systems-oriented solutions (Bright & Cooper, 1993). Studies have indicated that hospitals are making progress toward implementing improvement measures to successfully reduce medical error (Clarke, Krause, & Hidley, 2006). However, findings
  • 89. have also identified an ongoing gap between hospital practice and the perceived importance of such measures. McFadden et al. sampled 21 medical units within a general hospital and cross-validated the data collected to 15 units in another hospital. The findings demonstrated that perceived safety procedures and clear communication flow reduce medical error only when managers practice safety to demonstrate its priority within the respective hospital unit. Health-care providers are motivated to report medical error. Clarke et al. (2006) opined that this motivation is developed from professionalism, regular feedback, addressing system problems to avoid work-arounds, and developing a nonpunitive workplace culture. The development of a culture of safety must make reporting easy, communicate the benefits of reporting, ensure confidentiality, and commit to changing the system rather than the individual. Crane and Crane (2006) proposed that the use of
  • 90. failure mode affects analysis as a solution to medical error. This process identifies potential failures, identifies actions that could eliminate the failures, and actively documents the process for review and training. Mandatory or nonmandatory medical-error reporting continues to challenge organizations attempting to obtain a realistic measure of organizational performance. Mehta and Gogtay (2005) indicated that health-care organizations are responsible for 39 acknowledging medical error and expressing concern to the involved staff, physicians, patients, families, and community. The effectiveness of mandatory error reporting is measureable. Bhattacharya and Catherine (2004) conducted a survey study with physicians and hospital administrators that revealed the reporting of medical error as
  • 91. causal to improvements in health care. Weissman et al. (2005) concluded that more than two thirds of hospital executives are opposed to mandatory medical-error reporting when the information is made public. This indicates that public disclosure of medical-error information discourages the internal reporting of such error. Existing literature on improvement strategies and their implementation has revealed that little is known surrounding the design of effective quality-improvement interventions (Bosch, van der Weijden, Wensing, & Grol, 2006). Rather than analyzing perspective barriers to the development and content of effective interventions, most literature has analyzed solely obstacles to their implementation. Bosch et al. (2006) conducted a qualitative analysis of a sample of 20 quality- improvement studies reporting barriers to both educational and organizational quality interventions. Their findings indicated that the design of quality-improvement interventions remains within an infancy stage due to a continued mismatch between the level of
  • 92. identified barriers and the type of interventions selected for use. Quality-improvement initiatives effectively implemented within health-care organizations perform as operational and strategical responses to system challenges (Alavi & Yasin, 2008). Alavi and Yasin (2008) conducted a qualitative study to determine if the utilization of quality-improvement initiatives affect the operational environment of health-care facilities. Instrumentation consisted of four open-ended 40 questions and 80 items focused on environmental-change factors, response factors, and the effectiveness of quality-improvement initiatives with a Likert-type response scale. The population sample consisted of 39 health-care organizations—hospitals, outpatient clinics, laboratories, and pharmaceutical firms. The findings indicated that the
  • 93. participating health-care organizations were aware of the challenges associated with quality improvement and medical error and were actively engaged in safety initiatives to address those challenges. However, the effectiveness of safety initiatives depends largely upon their interpretation by health-care personnel. Regulatory oversight. Numerous initiatives implemented to improve the quality of health care aim to establish standards for the management of medical error within hospitals. During 1996, the JCAHO created a sentinel event policy for the management of such error (Schyve, 2000). The federal government established the AHRQ in 1999 as an effort to coordinate federal quality-improvement efforts. National patient-safety goals introduced during 2003 by the JCAHO focused on health-care improvement efforts targeting a set of high-priority problem areas (Hyman, 2006). Accreditation standards developed by the JCAHO were providing hospitals with latitude on the manner in which
  • 94. they complied with the standards. During the nine years between publication of the Harvard Medical Practices Study and the 2001 IOM report, various initiatives toward improving the quality of health care within hospitals were implemented. Legislation was enacted in 20 states for voluntary and mandatory reporting of medical error. In 1996, the JCAHO instituted the sentinel event policy that established standards for the management of medical error within accredited hospitals and the federal government established the AHRQ. Despite 41 these initiatives and increased public awareness, the 2000 IOM identified ―few tangible actions to improve patient safety‖ (as cited in Kohn et al., 2000, p. 5). On July 29, 2005, the Patient Safety and Quality Improvement Act of 2005 was enacted to improve patient safety by encouraging voluntary and
  • 95. confidential reporting of medical-error events adversely affecting patients. The Act signified the commitment of the federal government to fostering a culture of safety (AHRQ, 2005). It established a national voluntary reporting system for medical error and public disclosure of the reported information was prohibited (Kinnaman, 2007). The Patient Safety and Quality Improvement Act of 2005 achieved one of the IOM goals of establishing an environment that encourages voluntary reporting while protecting information from public disclosure. Private entities known as patient-safety organizations were created to collect confidential information related to medical error, analyze it, and provide recommendations toward improved patient safety, which began to transform the reporting system. The Patient Safety and Quality Improvement Act served to improve patient safety through confidentiality and established reporting standards that eliminated patient and provider identity. The Act embraced a culture of nonpunitive
  • 96. support (Mewshaw, White, & Walrath, 2006). In December 2005, the American Medical Association (2005) developed approximately 140 performance measures covering 34 clinical areas. An agreement with Congress called for physicians to voluntarily report their performance on these measures as part of a national quality-improvement program. The measures were collectively considered best practice and consisted of diagnostic tests and treatments that 42 demonstrated the ability to improve clinical outcomes. The American Medical Association also developed measures to assess physician performance and compensation. Local mandates. In addition to federal legislation mandating the measurement and monitoring of medical error, individual states implemented additional oversight
  • 97. measures. In 2000, the Florida legislature appointed the Florida Commission on Excellence in Healthcare, which focuses on issues of quality health care, patient safety, and the reduction of medical error. In September 2003, the Medical Incidents Law went into effect within the state of Florida, which impacted the responsibilities of licensed health-care providers. Some of these requirements include recognition of error-prone situations, process improvement for patient outcomes, reporting responsibilities, and public education. Patient-safety organizations were deployed in compliance with the Patient Safety and Quality Improvement Act of 2005. They worked with clinicians and health-care organizations to identify, analyze, and reduce the risks and hazards associated with patient care. Florida was one of the first states to recognize the link between medical malpractice, medical error, and patient safety. Primarily in response to the 1999 IOM report, the Florida legislature established the Florida Patient
  • 98. Safety Corporation (FPSC) with the purpose of monitoring patient safety throughout the state. In 2005, the Florida legislature provided funding for the FPSC to establish the voluntary Near Miss Reporting System, based upon a successful system used within the commercial-aviation industry. The objective of the program was to establish a statewide reporting system that was timely, anonymous, standardized, and easy to use. An important aspect of the system was the provision of immunity from legal penalties and sanctions (FPSC, 2008). 43 Unfortunately, in response to an ongoing budget crisis, funding for the FPSC was discontinued in 2008 and indefinitely suspended. In 2004, two state amendments were passed in Florida—the Patients’ Right-to- Know About Adverse Medical Incidents Act of 2004, known as Amendment 7, and the
  • 99. Three Strikes and You Are Out Act of 2004, known as Amendment 8 (as cited in Yaeger, 2009). Collectively, this legislation was aggressively promoted by Florida trial attorneys and their efforts reversed many of the patient-safety gains of the FPSC mandates. Amendment 7 eliminated confidentiality provisions and allowed full access to all patient records including all meetings, morbidity and mortality conferences, root-cause analysis, and any other professional exchanges of information related to patient injury or death. Upon first analysis, this appears to be a positive change; however, according to risk- management professionals, Amendment 7 has done immense harm to the quality assurance and peer-review protections developed over 2 decades and caused an immediate decline in the reporting of adverse events throughout the state (Barach & Small, 2005). The Three Strikes You Are Out Act of 2004 (as cited in Yaeger, 2009) presented
  • 100. an unintended adverse effect on the reporting of near misses and adverse medical events. It directed the Florida Board of Medicine to revoke medical licenses from providers with three ―adjudicated malpractice incidents‖ (p. 126). A strike is considered ―any malpractice judgment, findings from disciplinary cases, decisions of binding arbitration finding malpractice, and malpractice judgments from any other state‖ (Barach & Small, 2005, p. 762). It is hoped that the new federal regulations from the patient-safety organizations will help resolve the Florida situation. They went into effect on January 44 19, 2009 and described a clear, legally-protected framework for how hospitals, clinicians, and health-care organizations can work together to improve patient safety and nationwide quality of care. Thirty-nine states, including Florida, have mandatory or
  • 101. voluntary systems in place for reporting medical error. Florida requires that all licensed health-care facilities establish an internal risk-management program that includes (a) investigation and analysis of the frequency and causes of general categories and specific types of adverse patient incidents, and (b) the development of appropriate measures to minimize the risk of adverse patient incidents (Kaiser Family Foundation, 2008). Health-care facilities within the state of Florida must electronically report data on hospital-acquired infections to the Agency for Healthcare Administration, as specified in federal regulations. Health- care facilities must also submit annual reports to the Department of Health on adverse sentinel events (Rosenthal & Takach, 2008). Disparities Hospitals are complex organizations requiring diverse technology and specialized skills in personnel. They must manage data, consumer demands, market fluctuations, and
  • 102. changing medical information while assimilating these elements into quality patient care. The fallibility of human nature renders quality management difficult (Griffin & Haraden, 2005; Hughes & Clancy, 2005). As a result, when a significant medical error occurs, hospitals must cope with a variety of adverse consequences. They must effectively execute key processes related to patient access, service delivery, and revenue realization to optimize the relationships among quality, efficiency, and cost (Orlikoff & Totten, 2010). 45 The U.S. Bureau of Labor Statistics (2006) reported that health care is the largest U.S. industry, providing 14 million jobs. Between 2006 and 2016, this industry is predicted to generate 3 million new wage and salary positions (DeGeetern, 2009). The delivery of quality health care is accomplished through offering
  • 103. personal services. The connection between the health-care provider and patient requires development to improve the current delivery model. The IOM (2001) identified the need for a redesigned health- care delivery system to improve patient safety. Areas were identified that contributed to quality problems such as an increase in chronic disease, a poorly organized delivery system, and constraints in deploying information technology. The IOM (2001) set forth six aims for improvement and 10 rules for a redesigned health-care system. The ten rules included care based upon continuous healing of relationships, the patient as the source of control, a free flow of shared knowledge and information, evidence-based decision making, safety as a system priority, transparency, anticipated needs, decreased waste, and cooperation among clinicians. Health Grades Inc. (2005), an independent health-care quality research organization that grades hospitals based upon a range of criteria and provides hospital ratings to health plans and other
  • 104. payers, issued its third update to the 1999 IOM report. The report found that, despite widespread participation in patient-safety initiatives to reduce the frequency of medical error, progress toward improved safety was slow during the 6 years since the IOM report. According to Brady, Ho, and Clancey (2008), ―Quality improvement is, by definition, an endeavor, never completely fulfilled. Quality improvement is marked by the constant effort to raise performance and produce results that are consistently better‖ (p. 396). Realistically, 100% improvement cannot be achieved; however, continuous 46 improvement from one measurement period to the next must be evident. The AHRQ (2005) has been documenting steady improvement in the quality of American health care since it began publishing reports on the quality of U.S. health care and disparities in
  • 105. 2003. Improvement has occurred; however, at a modest annual rate of 1.5%. The Brady et al. analysis draws on more than three dozen data sources to measure quality and disparity in five areas—the effectiveness of care, patient safety, the timeliness of care, patient centeredness, and the efficiency of care. Culture of Safety Time is a barrier to patient safety. Staff reduction, complex procedures, and heavy patient loads contribute to the frequency of medical error (Gawande et al., 2003; Kalisch & Aebersold, 2006; McFadden et al., 2006). When staff perceives an insufficient amount of time to conduct a root-cause analysis of medical incidents, the tendency is to dismiss the error so the provider can return to patient care (Kalisch & Aebersold, 2006; McFadden et al., 2006; Weeks & Bagian, 2000). Similarly, daily workload interruptions are a barrier to reducing medical error. Nurses frequently multitask while attending to critically ill patients, carrying cell phones or pagers for both
  • 106. hospital and personal calls. Kalisch and Aebersold (2006) found that nurses reported 84 to 120 interruptions during a single shift. Ineffective teamwork and lack of accountability often prevent the development of quality-improvement programs (Gawande et al., 2003; Kalisch & Aebersold, 2006). Kalisch and Aebersold reported that poor teamwork increases the number of medical errors. Promoting a culture of safety within health-care organizations is an important strategy toward improving patient safety. A positive culture recognizes errors will occur 47 and seeks opportunities to implement preventative strategies (Edwards et al., 2008). A safe culture must move from a punitive to a blame-free environment. Edwards et al. (2008) used the AHRQ hospital survey on patient safety to measure the safety culture
  • 107. within various units of a hospital. The survey facilitated identification of common dimensions of organizational climate and the assessment of staff perceptions of safety. The instrument consists of questions measuring the dimensions of a safety culture and patient-safety outcomes. Edwards et al. distributed the survey to various hospital personnel employed within two Atlanta hospitals. Their findings identified key areas of concern regarding perceptions of the frequency of reporting error, manager expectations and actions, and teamwork. Understanding personnel perceptions allowed the development of safety initiatives such as safety rounds, education in event reporting, and a nonpunitive response to error. Public awareness of medical error has increased since the 1990s. Information sources, such as report cards comparing health-care providers, provide consumers access to patient-outcome information. Access to the Internet, public notification, and media
  • 108. focus transformed the consumer into an informed participant. Studies analyzing evidence-based quality ratings motivated hospital administrators to improve patient safety to retain customers. Access to health-care reports appears to be a positive motivator for consumers and industry leaders. Werner and Asch (2005) investigated the negative impact of health-care reports on patient-care services. These researchers found that physicians may avoid certain patients or overly rely upon interventions to improve their ratings. 48 Despite claims within existing literature that most medical error is due to system problems (Collins et al., 2009), Menachemi, Shewchuk, O’Connor, Berner, and Allison (2005) concluded that physicians tend to underestimate medical error and generally favor remedies. The researchers examined perceptions potentially