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Patient acuity
- 1. Best Practices forStaffing: Acuity vs. Census BACKGROUND • Patient Classification Systems have been utilized since the 1960’s without standardization or consensus (Harper & McCully, 2007). • With a combination of increasing health costs, decreasing nurse satisfaction, a lack of communication tools, and staffing shortages; acuity tools can appropriately coordinate staff with patient needs (Twigg, Duffield, Bremner, Rapley, & Finn 2011). • Low nurse-to-patient ratios are related to lower rates of adverse patient outcomes (Harper & McCully, 2007). • “Patient classification systems and acuity tools allow managers and administrators to predict staffing needs and more accurately control nurse-to-patient ratios” (Harper & McCully 2007) Lauren Bachman, Heath Chrisianson, Sylvia Davis, Heidi Kidd, Eric Stuemke SEARCHABLE QUESTION What are the best practices for staffing adult inpatient acute care units regarding patient census and patient acuity? Databases Searched CINAL & PUBMED CONCLUSIONS •Nurse leadership should pay careful attention to seeking buy in from staff nurses and other interdisciplinary members (Harper and McCully, 2007). •Each unit should seek out workable acuity tools, and implement them within their specific environment (Heede, Diya, Lesaffre, Vleugels, & Sermeus, 2008). RESULTS Evidence Answers Original Question •Research was inconclusive related to our original question. At this time there is a continued need for establishing a universal acuity rating tool. Additional experimentation, and possibly a meta- analysis of previous research is needed. Not Found in Evidence •There was no universal tool for patient acuity measurement found in the literature search. For addition information please contact: University of Anchorage School of Nursing (907) 786-4550 Suggestions for Future Research •Meta-analysis of all currently available acuity tools. •Unit specific measures of acuity should be considered in development of future acuity staffing tools. •A patient acuity tool should be developed, and measured against patient outcomes. Summary of Evidence What does it all mean? •Nurse tracking call light systems are an underutilized tool that can be used to effectively communicate patient needs among the interdisciplinary team, (Lucero, Ji, Cordova, & Stone, 2011) •There is a need to have a universal acuity tool, (Harper & McCully, 2007). •There is an association between acuity based staffing and improvements in patient safety, (Twigg, Duffield, Bremner, Rapley, & Finn, 2011). •Nursing satisfaction is related to patient acuity, nursing workload, and understaffing (McGillis & Kiesners, 2005). •Universal system for collection of nurses involved in patient care (Mark & Harless, 2011). •A standardized acuity system needs to be developed, tested, and implemented widely in hospitals and adopted by researchers (Mark & Harless, 2011) •Patient satisfaction is related to nurse staffing and the availability of hospital support services. (Bacon & Mark, 2009) •High acuity increases workload due to understaffing. Fixing staffing would decrease the workload per patient (Acar, 2010). •Patient acuity scoring systems and distance scoring systems can be used to estimate total workload of nurses, (Acar, 2010). •Units cannot use a minimum nurse patient ratio alone, a number of factors must be incorporated to determine an appropriate patient to nurse ratio, including patient acuity, skill mix, nurse competence, nursing process variables, technological sophistication (Lang, Hodge, Olson, Romano, & Kravitz, 2004). •There is a lack of support offered in the literature for specific minimum nurse patient ratios ,(Lang, Hodge, Olson, Romano, Kravitz, 2004). •The use of acuity tools alone is not sufficient to determine adequate staffing requirements, (Hayes & Ball, 2012) Level of Evidence/ Citation Key Measures Settings and sample Research Design Key Strengths/Weaknesses Results Level IV Evidence Lucero, R.J., Ji, H., de Cordova, P.B., & Stone, P. (2011). Information technology, nurse staffing, and patient needs. NursingEconomics,29(4), 189-194. IV: DV: Orthopedic surgical unit Sample, n=34: -FTE RNs Retrospective Exploratory -Convenience, non-randomised sample Strengths: -Readily available data & use of existing technology -Application to clinical practice Weaknesses: -All patient calls (needs) were assumed equally important -Admissions increased response times more than discharges. -Tracking call light study demonstrated the busiest times of the day. -Nurse staffing was adjusted accordingly. Level VI Evidence Harper & McCully. (2007). Acuity systems dialogue and patient classification system essentials. Nursing AdministrationQuarterly, 31(4), 284-299 IV: DV: Medical-surgical unit Sample, n=15: -RNs -5 Criteria of patient classification: medications, complicated procedures, education, psychosocial issues, complicated IV medications. -Yielded: 1-4 patient acuity rating Descriptive Strengths: -Use of staff nurses input to develop PCS tool. -5 rating concepts evaluate time and frequency required for interventions -Includes education and psychosocial considerations Weaknesses: -Small sample size -No clear recommendation on how to use the tool to make specific assignments The PCS tool was well received by nurses with 77% rating it as an effective voice for nurses in communicating about their patients. Level IV Evidence Twigg, D.I., Duffield, C., Bremner, A., Rapley, P., & Finn, J. (2011). The impact of the nursing hours per patient day (NHPPD) staffing method on patient outcomes: A retrospective analysis of patient and staffing data. International Journal of NursingStudies,48(5), 540-548. IV: Mandatory staffing levels: Nursing hours per patient day (NHPPD) DV: Patient outcomes Western Australian hospitals. Sample, n= 235,454: -patient records Sample, n=150,925: -staffing records Interrupted time series, retrospective analysis of patient and staffing data throughout the implementation of the mandated staffing level. Strengths: Extensive patient and nurse staffing records. Weaknesses: California hospitals did not have similar findings following mandatory staffing ratio implementation. This study found an association between implementing the NHPPD staffing method and improvements in patient safety. Specifically, there have been significant reductions in the rates of nine nursing- sensitive patient outcome indicators following the implementation of the NHPPD staffing method. Level VI Evidence McGillis Hall, L., & Kiesners, D. (2005). A narrative approach to understanding the nursing work environment in Canada. Social Science & Medicine, 61(12), 2482-2491. doi: 10.1016/j.socscimed.2005.05.002 8 acute care, publicly funded, Canadian hospitals (randomly selected) Sample, n=8: -nurses -selected by purposive sampling Qualitative -Detailed analysis of transcripts Strengths: -Themes dominated conversations and were interrelated Weaknesses: -Group size was preselected -No mention of data saturation Detailed analysis of transcripts revealed three key themes: patient acuity, workload, and understaffing. Workload and understaffing dominated the narrative and showed a strong link to patient acuity. Level IV Evidence Mark, B. A., & Harless, D. W. (2011, March/April). Adjusting for patient acuity in measurement of nurse staffing. Nursing Research, 60(2), 107-113. Non-Experimental 13 states from 2000 - 2006 Sample, n=579: - Hospitals - Included were: three measures of nurse staffing and hospital characteristics (ownership, geographic location, teaching status, hospital size, and percent Medicare inpatient days). Non-Experimental - Cross-sectional - Longitudinal study Strengths: - Large sample size Weaknesses: - NIWs provide a true estimate of patient needs -CMI doesn’t reflect acuity - CMI only for Medicare patients The study used descriptive statistics and simple correlation analysis and found no statistically significant relationship between NIW- adjusted and CMI adjusted staffing. This study suggests one way to start addressing staffing based on patient acuity is to have a “standardized acuity system developed, tested, implemented widely in hospitals, and adopted by researchers”. Level IV Evidence Heede, K. V., Diya, L., Lesaffre, E., Vleugels, A., & Sermeus, W. (2008). Benchmarking nurse staffing levels: The development of a nationwide feedback tool. Journal of Advanced Nursing,63, 607-618. Non-Experimental 1637 acute care nursing units in 115 hospitals Sample, n=690,258: - inpatient days for 298,691 patients Non-Experimental -Retrospective analysis of cross- sectional data Strengths: -Random selection of patients data Weaknesses: -Data assumes units within hospitals are correlated -Aim of study to report, not predict staffing -Feedback tool only available online The study found that variability in nurse staffing levels occurs within a specific unit and not the whole hospital. Another finding was the feedback tool develops accurate reflection of staffing in the past, but “the figures generated do not indicate the optimal or evidence-based nurse staffing level.” Level IV Evidence Acar, I. (2010). A decision model for nurse-to-patient assignment. Western Michigan University. IV: Acuity; distance traveled by RN per shift (each based on detailed scoring system) DV: Total workload Single adult medical/oncology unit (general medical unit) Sample, n=40: -RNs -Approximately 100, 12-hour shifts were observed. Quantitative - After-only, comparative design, looking at two models developed to balance total workload of RN's. -Model(1): focused on acuity and distance - Model(2): considered total workload of nurses Strengths: - Measurement tools demonstrated validity and reliability, and may be useful for a future workload measurement system. Weaknesses: -The population of the study was hand- selected, lending to some possible internal bias. -A single-hospital study may have limited generalizability. -Scoring measures were designed specifically for this study and have not been tested elsewhere. Of the two models tested, the model with a focus on patient acuity and distance traveled by the RN resulted in a more balanced total workload, reducing the variability between the workload of all nurses on the unit per shift. Level IV Evidence Bacon, C.T. & Mark, B. (2009). Organizational effects on patient satisfaction in hospital medical surgical units. Journal of NursingAdministration,39(5), 220-227. IV: Organizational characteristics, nursing unit characteristics, patient characteristics DV: Patient satisfaction 286 Medical-surgical units in 146 hospitals Sample, n=3718 RNs; 2720 patients: -Randomly selected Descriptive/correlational study -3 questionnaires, over 6-month period (RNs) -1 questionnaire (patients) Strengths: -Large sample size Weaknesses: -Sampling bias -Possible threat to internal validity -Questionnaires have limited reliability Measures to reduce work complexity, such as regulation of nursing assignments based on patient acuity and improved support services, positively influence patient satisfaction. Level V Evidence Lang, T.A., Hodge, M., Olson, V., Romano, P.S., & Kravitz, R.L. (2004). A systematic review on the effects of nurse staffing on patient, nurse employee, and hospital outcomes. JONA, 34(7/8), 326-337. IV: Nurse staffing DV: Patient, nurse employee, and hospital outcomes Acute care, rehabilitation, or psychiatric hospitals Sample, n=43: -research studies Systematic review of descriptive/correlational studies -assessed relationship between some measure of nurse staffing and patient, nurse employee, or hospital outcomes. Strengths: -former nurse with 15 years experience as a medical reference librarian performed the literature search Weaknesses: -49% of studies analyzed hospital-level data, rather than nursing-unit-level data. -include data from ICUs, which have different staffing patterns and different patient characteristics A minimum nurse-patient ratio alone is likely not appropriate to ensure quality of care. Patient acuity, skill mix, nurse competence, nursing process variables, technological sophistication, and institutional support of nursing should also be taken into consideration when establishing minimum staffing requirements. Level VI Evidence Hayes, N. & Ball, J. (2012). Achieving safe staffing for older people in hospital. NursingOlder People 24(4), 20-24. IV: Nurse staffing levels DV: Quality of care NHS hospitals in the United Kingdom Sample, n=240: -nurses working on older people’s wards Descriptive -Mixed Methods -quantitative, yet from a 2 survey method -focus groups, though no mention of qualitative method Strengths: -Royal College of Nursing’s (2012) guidance and recommendations can be used by nurses at all levels - Multiple focus groups with front-line nurses -Workshops & discussions with invited gerontological nurses Weaknesses: -focused on older people’s wards in the UK -focus groups not randomized, may introduce bias -The use of acuity tools alone is not sufficient to determine adequate staffing requirements. During periods of high patient acuity, charge nurses must have instant access to additional nursing resources. They should also have access to senior clinical support and leadership from nurse experts. -Further work is needed to develop suitable metrics and measures that include all aspects of complex care.
- 2. Heidi Kidd, SylviaDavis, Eric Stuemke, Heath Christianson, and Lauren Bachman
- 3. Background & Significance Patient Classification Systems have been utilized since the 1960’s without standardization or consensus (Harper & McCully, 2007). With a combination of increasing health costs, decreasing nurse satisfaction, a lack of communication tools, and staffing shortages; acuity tools can appropriately coordinate staff with patient needs (Twigg, Duffield, Bremner, Rapley, & Finn 2011). Low nurse-to-patient ratios are related to lower rates of adverse patient outcomes (Harper & McCully, 2007). “Patient classification systems and acuity tools allow managers and administrators to predict staffing needs and more accurately control nurse-to-patient ratios” (Harper & McCully 2007)
- 4. Searchable Question What arethe best practices for staffing adult inpatient acute care units regarding patient census and patient acuity?
- 5. Information Technology, NurseStaffing, and Patient Needs (Lucero, Ji, Cordova, & Stone, 2011) Retrospective Exploratory, Level IV FTE RN’s on an orthopedic surgical unit N=34 Convenience Non-Random Sample Admissions increased response times more than discharges Tracking call light study demonstrated the busiest times of day Nurse staffing was adjusted accordingly Strengths Readily available data & use of existing technology Application to clinical practice Weaknesses All patient calls (needs) were assumed equally important
- 6. Acuity Systems Dialogueand Patient Classification System Essentials (Harper & McCully, 2007) Descriptive Level VI Evidence N = 15 RN’s on a Medical-Surgical Unit Author’s Patient Classification System Employed 5 Criteria Medications, Complicated Procedures, Education, Psychosocial Issues, and Complicated IV Medications. Criteria yielded a level 1-4 patient acuity rating The PCS tool was well received by nurses with 77% rating it as an effective voice for nurses in communicating about their patients Strengths Use of staff nurses input to develop PCS tool 5 rating concepts evaluate time & frequency required for interventions Includes education & psychosocial considerations Weaknesses Small Sample Size No clear recommendation on how to use tool to make specific assignments
- 7. The impact ofthe nursing hours per patient day (NHPPD) staffing method on patient outcomes: A retrospective analysis of patient and staffing data. (Twigg et al., 2011) • Interrupted time series using retrospective analysis. Level IV • Three adult tertiary teaching hospitals that received 88.9% of the staffing increases • All patient records (N = 236,454) and nurse staffing records (N = 150,925) . • Measurements taken pre implementation, transitional period and post implementation. • Significant decreases in the rates of nine nursing-sensitive outcomes following implementation of NHPPD Strengths Large sample size Extensive patient and nurse staffing records Weaknesses DRG’s not consistent through time California did not produce similar results
- 8. A narrative approachto understanding the nursing work environment in Canada (McGillis et al., 2005) • Qualitative . Level VI. • Purposive sampling from eight randomly selected hospitals. • 8 nurses from 8 different acute care units • Revealed three key themes: patient acuity, workload, and understaffing as effecting quality of work environment Strengths Themes dominated conversations and were interrelated Weaknesses Group size was preselected & no mention of data saturation
- 9. Adjusting for PatientAcuity in Measurement of Nurse Staffing (Mark and Harless, 2011) Cross Sectional and Longitudinal, Level IV Sample 579 hospitals in 13 states from 2000 to 2006 Purpose to examine if CMI can substitute for NIW CMI=Case Mix Index High CMI =more care NIW = Nursing Intensity Workload Strengths Descriptive Statistics with simple correlation analysis Large sample size Weakness NIWs provide a true estimate of Patient needs CMI doesn’t reflect acuity. CMI only for Medicare patients No distinction between inpatient and outpatient employee Level IV Study
- 10. Benchmarking nurse staffinglevels: the development of a nationwide feedback tool (Heede et al., 2008) Retrospective analysis of cross-sectional data, Level IV Sample 690,258 inpatient days for 298,691 patients from 1637 acute care nursing units in 115 hospitals Feedback tool developed based on satistical model Spearman rank correlations from 0.91-0.99 High reliability and validity for tool developed Strengths Inter-rater reliability 78.8 % Random selection of patients data Weakness Data assumes units within hospitals are correlated Aim of study to report not predict staffing Feedback tool only available online Level IV evidence
- 11. Organizational Effects OnPatient Satisfaction In Hospital Medical Surgical Units (Bacon, C.T. & Mark, B., 2009) Single, correlation study, level IV Random sample Included 2720 patients and 3718 RNs in 286 medical-surgical units in 146 hospitals Investigated the relationship of patient satisfaction with floor staffing and support services. Strengths Patient acuity is used as a variable Weaknesses Sampling bias is a potential problem. Variables used (patient acuity and work complexity) are difficult to operationalize.
- 12. A Decision Modelfor Nurse-To-Patient Assignment (Acar, I., 2010) After-only Comparative Design, level IV. 40 RN’s on General Medical Unit. Approximately 100 12-hour shifts observed. Models for staff assignment included maximizing patient acuity and minimizing RN distance traveled during a shift, or minimizing the maximum workload assigned to a nurse. Results compared to the Charge Nurse’s manual assignments’ resulting workload Strengths Initially planned to study nurses in NICU, and realized generalizability may be limited. Switched the study to a General Medical Unit. Weaknesses Study took place in one hospital, which may limit generalizability.
- 13. Nurse-patient ratios: Asystematic review on the effects of nurse staffing on patient, nurse employee, and hospital outcomes (Lang et al., 2004) • Level V • Systematic review of descriptive/correlational studies • Sample: 43 research studies on acute care, rehabilitation, or psychiatric hospitals • Patient acuity, skill mix, nurse competence, nursing process variables, technological sophistication, and institutional support of nursing should be considered when setting minimum nurse staffing requirements, and not a minimum nurse-patient ratio alone. Strengths Former nurse with 15 years experience as a medical reference librarian performed the literature search Weaknesses 49% of studies analyzed hospital-level data, rather than nursing-unit-level data. Include data from ICUs, which have different staffing patterns and different patient characteristics
- 14. Achieving safe staffingfor older people in hospital (Hayes & Ball, 2012) • Level VI • Mixed Methods (quantitative from a 2 survey method) • Nurses who worked on older people’s wards (n=240) • The use of acuity tools alone is not sufficient to determine adequate staffing requirements. • During periods of high patient acuity, charge nurses must have instant access to additional nursing resources. • Charge nurses should also have access to senior clinical support and leadership from nurse experts. Strengths Royal college of Nursing’s (2012) guidance and recommendations can be used by nurses at all levels Multiple focus groups with front-line nurses Workshops & discussions w/ invited gerontological nurses Weaknesses Focused on older people’s ward’s in the U.K. Focused groups not randomized, may introduce bias
- 15. Stake Holders FacilityAdministration/Accounting Insurance Companies/Third Party Payer Nurse Leadership Nurse Educators Staff Nurses Patient Care Technicians/CNA’s Patients-(Outcomes)
- 16. Summary of Evidence Nurse tracking call light systems are an underutilized tool that can be used to effectively communicate patient needs among the interdisciplinary team (Lucero, Ji, Cordova, & Stone, 2011). There is a need to have a universal acuity tool (Harper & McCully, 2007). There is an association between acuity based staffing and improvements in patient safety (Twigg, Duffield, Bremner, Rapley, & Finn, 2011). Nursing satisfaction is related to patient acuity, nursing workload, and understaffing (McGillis & Kiesners, 2005). A standardized acuity system needs to be developed, tested, and implemented widely in hospitals and adopted by researchers (Mark & Harless, 2011) Patient satisfaction is related to nurse staffing and the availability of hospital support services. (Bacon & Mark, 2009)
- 17. Summary of Evidence High acuity increases workload due to understaffing. Fixing staffing would decrease the workload per patient (Acar, 2010). Patient acuity scoring systems and distance scoring systems can be used to estimate total workload of nurses (Acar, 2010). Units cannot use a minimum nurse patient ratio alone, a number of factors must be incorporated to determine an appropriate patient to nurse ratio, including patient acuity, skill mix, nurse competence, nursing process variables, technological sophistication (Lang, Hodge, Olson, Romano, & Kravitz, 2004). There is a lack of support offered in the literature for specific minimum nurse patient ratios (Lang, Hodge, Olson, Romano, Kravitz, 2004). The use of acuity tools alone is not sufficient to determine adequate staffing requirements (Hayes & Ball, 2012).
- 18. Results Evidence Answers OriginalQuestion Research was inconclusive related to our original question. At this time there is a continued need for establishing a universal acuity rating tool. Additional experimentation, and possibly a meta-analysis of previous research is needed. Not Found in Evidence There was no universal tool for patient acuity measurement found in the literature search.
- 19. Future Research Meta-analysisof all currently available acuity tools. Unit specific measures of acuity should be considered in development of future acuity staffing tools. A patient acuity tool should be developed, and measured against patient outcomes.
- 20. Plan of Implementation A meta analysis should be performed. Focus groups, comprised of stake holders, should conduct a literature review. Unit specific acuity tools would then be implemented. Pre-implementation data should be measured against post-implementation data in relation to pre-defined patient outcomes.
- 21. Conclusions Nurse leadershipshould pay careful attention to seeking buy in from staff nurses and other interdisciplinary members (Harper and McCully, 2007). Each unit should seek out workable acuity tools, and implement them within their specific environment (Heede, Diya, Lesaffre, Vleugels, & Sermeus, 2008).
- 22. References Acar, I. (2010).A decision model for nurse-to-patient assignment. Western Michigan University. Bacon, C.T. & Mark, B. (2009). Organizational effects on patient satisfaction in hospital medical surgical units. Journal of Nursing Administration, 39(5), 220-227. Harper & McCully. (2007). Acuity systems dialogue and patient classification system essentials. Nursing Administration Quarterly, 31(4), 284-299 Hayes, N. & Ball, J. (2012). Achieving safe staffing for older people in hospital. Nursing Older People 24(4), 20-24. Heede, K. V., Diya, L., Lesaffre, E., Vleugels, A., & Sermeus, W. (2008). Benchmarking nurse staffing levels: The development of a nationwide feedback tool. Journal of Advanced Nursing, 63, 607-618.
- 23. References Lang, T.A., Hodge,M., Olson, V., Romano, P.S., & Kravitz, R.L. (2004). A systematic review on the effects of nurse staffing on patient, nurse employee, and hospital outcomes. JONA, 34(7/8), 326-337. Lucero, R.J., Ji, H., de Cordova, P.B., & Stone, P. (2011). Information technology, nurse staffing, and patient needs. Nursing Economics, 29(4), 189-194. Mark, B. A., & Harless, D. W. (2011, March/April). Adjusting for patient acuity in measurement of nurse staffing. Nursing Research, 60(2), 107- 113. McGillis Hall, L., & Kiesners, D. (2005). A narrative approach to understanding the nursing work environment in Canada. Social Science & Medicine, 61(12), 2482-2491. doi: 10.1016/j.socscimed.2005.05.002 Twigg, D.I., Duffield, C., Bremner, A., Rapley, P., & Finn, J. (2011). The impact of the nursing hours per patient day (NHPPD) staffing method on patient outcomes: A retrospective analysis of patient and staffing data. International Journal of Nursing Studies, 48(5), 540-548.
Editor's Notes
- #6 Lucero, Ji, Cordova, & Stone (2011) performed a retrospective level IV study to determine how patient needs, seen as using the call light, influenced nurse response time as monitored by an RN tracking system. The population consisted of 34 FTE RN’s on an orthopedic surgical unit at a magnet hospital over one year. Variations in data were accounted for in this one group study without randomization. Findings indicate that admissions increased response times more than discharges, and increased staffing during periods of increased patient needs may have been due to proactive nurse management. Call light tracking systems are an underutilized way to assist in staffing adjustments, yet there was no significant relationship between nurse staffing and call light response times. Strengths include inexpensive study as existing technology was used, and recommendations for clinical practice. Weaknesses include that there was no differentiation regarding needs that could be met by aids vs RN’s thus all calls were assumed equally important.
- #7 Harper & McCully, (2007) used a descriptive study yielding Level VI Evidence. The authors developed a Patient Classification System or PCS around 5 criteria; medications, complicated procedures, education, psychosocial issues, and complicated IV medications. After developing the tool with bedside nurses, two questionnaires were sent out and responded to voluntarily and anonymously by 15 RN’s functioning either as unit staff, charge/coordinators, or nurse educators at a small rural hospital on a medical-surgical unit. One questionnaire asked the nurse to evaluate the effectiveness of the PCS, while the other assessed the nurses expert opinion of the 5 criteria used. 77% rated the tool as effective in serving as a voice, 64% believed it accurately discriminated between patients, and 55% rated the representation of patient needs as accurate while 45% were neutral on this point. Additionally 5 patients were evaluated with the PCS by 3 different RN’s yielding 87% interrater reliability. Strengths included the use of bedside nurses in PCS development, validity of 5 criteria, & high interrater reliability. Weaknesses include small sample size, and a lack of clear indication regarding how to use the tool in making specific assignments.
- #8 Twigg, Duffield, Bremner, Rapley, and Finn (2011) investigated the impact of the nursing hours per patient day (NHPPD) staffing method on nursing sensitive patient outcomes in Western Australian hospitals. They performed an interrupted time series, retrospective analysis of patient and staffing data throughout the implementation of the mandated staffing level. This study yielded level IV evidence. This study found an association between implementing the NHPPD staffing method and improvements in patient safety. Specifically, there have been significant reductions in the rates of nine nursing-sensitive patient outcome indicators following the implementation of NHPPD staffing method. This study was strengthened by the fact that extensive patient and nurse staffing records from NHPPD wards were included for the entire Western Australia region. One possible weakness was that similar results in California hospitals were not found following mandatory staffing ratio implementation, but there were differences in data collection and completeness.
- #9 McGillis Hall and Kiesners (2005) used a narrative approach in an attempt to understand the nursing work environment in Canadian hospitals. This study yielded level VI evidence. Purposive sampling was used to select eight nurses from eight different acute care, publicly funded hospitals that were randomly selected. Detailed analysis of transcripts revealed three key themes: patient acuity, workload, and understaffing. Workload and understaffing dominated the narrative and showed a strong link to patient acuity.
- #10 Mark and Harless (2011) conducted a cross sectional and longitudinal study to determine the correlation between case mix index (CMI) and nursing intensity workload (NIW). This Level IV study collected data from 579 hospitals in 13 states from 2000 to 2006. A higher CMI is correlated with patients that require more resources and have a more severe illness. NIW reflects the staffing hours of nurses. A higher NIW reflects the need for more personal. The study used descriptive statistics and simple correlation analysis and found no statistically significant relationship between NIW-adjusted and CMI adjusted staffing. This study suggest one way to start addressing staffing based on patient acuity is to have a “standardized acuity system developed, tested, implemented widely in hospitals, and adopted by researches” (2011). Mark, B. A., & Harless, D. W. (2011, March/April). Adjusting for Patient Acuity in Measurement of Nurse Staffing. Nursing Research, 60, No 2, 107-113.
- #11 Heede et al. (2011) conducted a Retrospective analysis of cross-sectional data that was used to develop a feedback tool. The level of evidence for this study was IV. The sample for the study was gathered from data of 690,258 inpatient days for 298,691 patients from 1637 acute care nursing units in 115 hospitals. The study found that variability in nurse staffing levels occurs within a specific unit and not the whole hospital. Another finding was the feedback tool develops accurate reflection of staffing in the past, but “the figures generated do not indicate the optimal or evidence-based nurse staffing level”. One important suggestion that the article makes is “One possible way to determine whether a unit is under- or over-staffed is to survey nurses”. Finally there are things that this tool can not predict and that is the type of staff and the experience that that staff has in a particular hospital. Heede, K. V., Diya, L., Lesaffre, E., Vleugels, A., & Sermeus, W. (2008). Benchmarking nurse staffing levels: the development of a nationwide feedback tool. Journal of Advanced Nursing, 63, 607-618.
- #12 Bacon and Mark (2009) conducted a correlation study, providing level IV evidence. The study involved 2720 patients and 3718 RN’s in 286 medical surgical units in 146 hospitals. Study coordinators assisted with data collection to include 2 different questionnaires, completed by the nurses, and 1 questionnaire completed by patients. The relationship between organizational, nursing unit, and patient characteristics on patient satisfaction was observed, collecting information about support services using a 21-item checklist, and patient acuity, using a 24-item Likert-type questionnaire. Patients completed questionnaires detailing their satisfaction with their care, with response ranges from “excellent” to “poor”, or “always” to “never”. The study demonstrated a clear association between work engagement and availability of support services with patient satisfaction. Study measures included patient acuity and work complexity. These variables are difficult to operationalize, and the measures used may have lacked sensitivity to adequately capture the full range of patient acuity and work complexity.
- #13 Acar, I (2010) conducted an after-only, comparative design study, resulting in level IV evidence. The study involved direct observation of 40 RN’s working on the General Medical Unit of a single hospital, observing about 100 12 hour shifts. Patient acuity scoring system and distance scoring systems were developed for the study, used to estimate total workload. 2 models for unit staffing using Analytical Hierarchy Process were implemented, with patient acuity and RN distances traveled as objectives. Total workloads were compared to Charge Nurse’s manual assignments. Based on a scale estimating the quality and variability of the workload of nurses, staffing which focused on patient acuity and total distance per shift traveled by the nurse, resulted in more balanced staffing assignments in the workload of the unit.
- #14 Lang et al. (2004) conducted a systematic review of 43 descriptive/correlational studies to determine the effects of nurse staffing on patient, nurse employee, and hospital outcomes. It had a level V of evidence. The most important finding is that a minimum nurse-patient ratio alone is likely not appropriate to ensure quality of care. Patient acuity, skill mix, nurse competence, nursing process variables, technological sophistication, and institutional support of nursing should also be taken into consideration when establishing minimum staffing requirements. One of this study’s strengths was that a former nurse with 15 years experience as a medical reference librarian performed the literature search and collected the data. Some weaknesses were that 49% of the studies analyzed hospital level data, rather than nursing-unit level data. Also, it included data from ICUs, which have different staffing patterns and different patient characteristics.
- #15 Hayes and Ball (2012) conducted a mixed-method, double survey study of 240 nurses who worked directly on older people’s wards in the UK. The most important findings with respect to the question being asked to the group were that the use of acuity tools alone is not sufficient to determine adequate staffing requirements. During periods of high patient acuity charge nurses must have instant access to additional nursing resources. They should also have access to senior clinical support and leadership from nurse experts. Strengths of this study were: The Royal College of Nursing’s (2012) guidance and recommendations can be used by nurses at all levels, and the study had focus groups with front-line nurses and workshops with invited gerontological nurses. Weaknesses of this study were that it focused on older people’s wards in the U.K. and the focus group methods may introduce bias because they were not randomized.
- #20 Future research projects include a meta-anlysis of all currently available acuity tools; the development of future acuity staffing tools to include unit specific measures of acuity; a relational study of patient outcomes measured against a patient acuity tool.
- #21 After a meta analysis is performed, focus groups comprised of stake holders, should conduct a literature review. Once the best acuity rating tool for that unit is determined, it should systematically be implemented. Finally,