Revised Quality Management Basics Texas Histology Society


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  • Some of the topics we will address in this presentation to outline the basic principles of quality management including the fundamental elements of a quality system. Basic terminology related to quality management will be defined. The analysis of quality issues will be related the pre-analytic, analytic and post analytic phases of the histology process for the purposes of defining problems or errors that interfere with quality goals. Application will be made to tools and methods of how to identify errors that reduce quality, and how to identify root causes of defects in your processes. The impact of regulating and accrediting bodies and their requirements for quality monitoring and documentation will be discussed as it relates to development and maintenance of quality supporting policy, procedure, and protocols. We will also briefly touch on personnel training issues and standards as they related to performance quality, and discuss how to develop an organizational culture that supports quality.
  • The histology process remains comparatively a manual, labor-intensive process that has been executed in essentially the same way for over 100 years. In contrast to other sections of the laboratory and areas of medicine, the basic process of histology labs has changed very little with only some intervening, intermittent automation and technology. ( Smith, 2010 Vol. 15., Issue 9). Due to the slower technology utilization ( some experts feel) histology has lagged behind in the quality assurance and process improvement movements. Medical errors do occur in all areas of medicine, but with the increasing specimen volumes, simultaneous workforce shortages, small inefficiencies and errors in the histology workflow become magnified. The most notable issues facing many histology labs is how to maximize their limited resources ( especially labor) for the most timely, and highest quality patient results. Often due to our infrequent contact with patients, it can be easy to become distanced from how our quality of work provides essential information that directly impacts the diagnosis and treatment of each patient. Our goal and focus must always remain on the objectives of patient care and its quality, making management of quality vital to any histology laboratory.
  • Quality improvement monitors, while exceedingly important to patient care, can require a large amount of laboratory resources. Since resources are limited, quality improvement activities must be chosen wisely. This often means that thought and consideration must be given to identifying items that will yeild the most improvement from each quality monitor and control activity. It is recommended that quality monitors should utilize the test cycle ( we will identify those later), to evaluate procedures in each segment, allowing recognition and identification of the part of the test cycle in which the problem is occurring- this can often lead to more effective solutions by breaking the problem down into more manageable parts. Data collection is an important part of improving quality, and will aid in identifying errors and provide a way to quantify and measure for decision making concerning use of resources and time, and also allow progress to be charted in addressing quality issues in the lab. Quality improvement monitors ( things to be measured and sought to be improved), should consider benchmark levels with references from the literature or other sources to compare your internal data. The comparison of gathered data can to compare with internal and external benchmarks also helps in determining whether a problem exists, has improved or needs to continue to be monitored.
  • Quality assurance is defined as an integrated system of management activities involving planning, training, quality control, data review , and finally quality improvements. Quality control on the other hand is a defined system of technical processes that measure performance of a process or serrvice. QC is a technical function, geared to assessing bias and precision against a defined set of criteria.Traditionally the analysis of quality measurement activities have been those which evaluate and measure the uniformity of processes ( amount/number/severity) of variances or non-conformity of the process outcomes to established goals and standards. The baseline for this evaluation is determined using the pre-determined process parameters or desired outcomes. Quality control is used and designed to compare the actual performance and results with the process outcomes. This outcome should be stipulated in the procedure manual. Quality control activities include: maintenance/monitoring of instruments, recording of temperature logs for cryostats, waters baths etc., control records for special stains control slides and tissues, and any records that establish or monitor variations in staining or sectioning. Quality assurance is a term used to describe a system that includes internal quality checks but reflect a higher level of oversight that includes outcome data that has been compiled within quality control. In most cases the outcome data reflects results from multiple processes or procedures. Quality assurance measures include metrics and information such as reporting turn around times and diagnostic error rates, and serve to illustrate the relationship of quality control to post-analytic process steps. Quality assurance activities include; frozen section correlation with final diagnosis, and FS turn-around, error rates for specimen identification errors, diagnostic error or inaccuracies detected in reporting details, such as tumor staging due to non-comformities. Quality improvement is a term that describes activities which seek to improve the outcomes identified from quality assurance. Improvement activities may be part of a departmental group of quality improvement goals, that must include measurable variables such as reducing specimen identification or diagnostic errors, shortening turn around times. Quality improvement activities will utilize those quality assurance monitors to establish benchmarks and to evaluate the effectiveness of improvement-motivated changes to quality checks on processes. Quality improvement may include; identification of process steps that are error prone ( must identify these, and develop indicators), measurement and quantifying of current level of performance, determination of target or goal ( using internal/external benchmarks or historical performance data), design of intervention or process change to minimize problems or errors, collection of new data to monitor changes ( either good or bad), repeat as needed to approach the goal.
  • The scale of the QA program should be created relative to the end-use of the analytical results. The relative cost/benefit ratio of any individual QC components or techniques should be considered during implementation or modification of an existing QA program ( Hoskins, 2009).
  • See Handout for Plan outline. The laboratory needs to be legally identified and have a documented organizational plan and structure set up to ensure that quality services are delivered to patients and clinical customers. Each element of the quality plan exists as a laboratory requirement as outlined accrediting agencies, regulatory agencies, or published standards. Includes: Scope, roles & responsibilities, reporting relationships, quality planning and risk assessment, budget of resources, quality review, management review. The physical facilities are required by law to be designed to optimize work efficiency and risk of injury, meeting governmental standards. Physical and procedural safety can be specified in the lab’s safety program- but how the physical environment impacts delivery quality can be addressed. Personnel – The Clinical Laboratory Improvement act of 1988 regulates minimum qualifications and responsibilities for personnel performing moderate complexity and high complexity laboratory testing. Organizations may set higher or additional qualifications if they desire. These qualifications can be addressed in the job description, but well qualified, adequately trained personnel are also essential to quality. All staff need training in the work processes and procedures that make up their assigned job tasks. Equipment- criteria for the selection, validation records, service and repair records should be kept. The work quality systems essentials- process control of all phases of the lab’s process is crucial to the ultimate quality of the lab’s results. Quality control is used to monitor patient testing processes at the bench level. Documents and records- the “heart” of the lab QMS are the policy, process and procedure documents that tell personnel what to do and how to do it. This includes the records that provide objective data of the results of performing the processes and procedures. Audits have revealed that laboratory documents and records have been missing, incomplete, outdated, or contain inaccuracies. Laboratories are not required to implement document control : Comprised of- Document identification, creation, review and approval for new documents, document master files, document distribution lists, archival, storage and retention of obsolete documents( Berte, 2007). Occurrence management or “non-conforming event management” includes the requirements for documenting and investigating events that do not conform the lab’s established policies, processes or procedures ( or imposed requirements). The goal of this segment is to capture and analyze information about non-conforming events to identify underlying systematic problems and to gain the commitment from management to addressing these causes. This includes the following elements: Identification and reporting, remedial actions, investigation and documentation procedures, action plans, classification with analysis, management review and follow up. In addition, laboratories are now required to have a process for employees to communicate concerns about quality and safety to laboratory management ( see Laboratory Accreditation Program. Laboratory General Checklist. Northfield, IL.; College of American Pathologists, 2006).
  • The QMS is a higher level “umbrella” that unifies the information documented in the QC, QA and includes resource allocation, result data that incorporates how the elements of the quality monitors support and meet organizational goals in lab operations, compliance standards, effectiveness of practices in alignment with patient care driven goals and objectives. Can be effectively supported by QA data, control charts, track and trending of identified quality variables and rates of occurrence with outcomes.
  • All laboratories have a defined test cycle that is composed of pre-analytic, analytic and post-analytic process phases. The separation of the total process into segments, and this separation assists in more narrowly defining and isolating problems. Examples of errors at different points in the Histology test cycle and potential corrective measures: Pre-analytic step errors in handling and identification: The use of bar code technology can dramatically reduce the opportunity for these types of errors, mostly through elimination of multiple manual handling steps that are error prone ( Grimm, 2008). Analytic step: A large percentage of analytic errors are due to improperly labeled slides. One source states that “slide labeling accounts for 67% of histology errors ( defects) ( systems 2007. Slide labeling errors can be reduced by the use of direct slide labelers ( etchers) which can help with reduction of manual transcription error opportunities, but even if you do not want to invest or convert to technology solutions, you can still think about how many transcribing error opportunities can be reduced even within any manual labeling process.
  • It can be difficult not to get caught up in high level documentation and oversight, don’t forget to bring what you are doing back together with its driving purposes- quality patient care. It is important to not only keep yourself mindful of this over-riding goal, but to remind everyone, all the time the “why” or what is behind quality management. Feeback, communication and clarity of goals-essential to success.
  • Two general categories of approaching errors- 1. Systems solutions- related to the structure and function of work processes, 2. personnel solutions-having the right people do the task correctly at the right time. We will talk briefly about personnel principles in a coming slide and this topic is also addressed on page 11 of the handout. Humans are inherently prone to error in routine and repetitive tasks, this is in contrast with machines and automation, which process routine and repetitive tasks very well. However, don’t make judgments, do troubleshooting. Consider how you might alter your processes to simplify them, reduce/consolidate steps, take advantage of the performance characteristics of both people and machines. The principle system solutions rely on reducing reliance on memory ( checklists, automation, etc), use of error-proofing (more on that in the handout page 10).Overall your goal is to increase standardization of processes, by having one standard way of executing a task helps reduce errors in two ways: it reduces the number of times judgment and guess work can/must be applied, it creates consistency. Varied input leads to errors because the system has to be modified to accommodate the different input. A uniform input leads to consistent processes and uniform output. The more complex a situation or systme the greater the chance for error. Inconsistencies of any kind, serve to encourage errors, such as individual performance differences, different methods or steps of execution for example. It has been estimated that if each step in a process has a 1% chance of having error, having a 25 step process will increase the chance of error to 22%, to 39% with 50 steps, illustrating the effect of complexity (Nakhleh, 2005)/.
  • One short mention of personnel factors… time pressures and time constraints increase errors by causing “coupling” between process steps. The reduced time spent on important steps due to this rushing through, tends to not allow for the identification or resolution of errors, which can then travel further down the process stream before they might be caught. Other studies have shown that an environment or culture where individuals are encouraged to work as a team, and not as dividied by rank or hierarchal structure, tend to perform better at both error reduction and resolution ( Nakhleh, 2005). Adjusting work schedules assists with time constraint, improving the environment addresses stress and hierarchical structure, and training/competency addresses multiple issues, such as inconsistency, human intervention, and culture.
  • Clerical examples; order entry errors, inaccuracies in adding or editing patient records or specimen information in LIS. Trascribing errors to specimen jars, cassettes slides, labels etc. potential causes- “human error”, perhaps contributing process problems. Other tools available ( besides RCA): Process mapping Nature of work studies Flow of work studies Error-proofing “poka-yoke” Process correction Use of standardization Can be affected with technology, double checks, eliminating redundant information transcriptions ( reduces error opportunities) Process error examples: skipping steps in stain protocols, using wrong controls, performing stains on wrong tissue, can also result when the technical personnel arrive at an incorrect identification of a process problem, assume incorrect root cause, and then adopt an incorrect correction ( applies to troubleshooting). Potential causes, “rushing”, distractions, processes which are overly redundant or cumbersome ( causing people to rush through, skip steps ) often leads to re-work. Corrections can be adequate staffing, streamline processes, training and education. Technical errors examples: incorrect tissue orientation, cutting too deeply or too shallow into tissue blocks, failure to replenish reagents appropriately, failure to recognize, apply correctable technical problems, failure to troubleshoot and/or self –correct techniques during any procedure. Technical errors can sometimes be due to instrument malfunction ( here is where technical insight and judgment is good), improved by training, education, experience.
  • Diagram depicting the general process and flow of RCA analysis of a problem.
  • Root cause analysis can be utilized with other six sigma methodology as a tool designed to identify the problems which have occurred in a process. It can help to explain what has happened, but also add precision and insight into exactly what/why/how a problem has occurred in a process. Understanding the reason(s) for the occurrence of any problem is an effective means to getting to a solution and for the manager if they utilize a process improvement team, with the stake holders, can yeild valuable suggestions from the team for safeguarding the process from the identified problem. Note that causes over which management has little or no control, will result in no effective recommendations from this type of analysis, and their source cannot be technically a “root cause”. So select your resolution tools and analysis methods in a way that is appropriate and effective to address the issue being discussed.
  • Fishbone diagrams are great for documenting team “brainstorming” on errors or problems. In the initial brainstorming, don’t limit the ideas of anyone in the team, collect all ideas and suggestions, encourage everyone to put in their “two cents”- go around the table or room if necessary- you can always refine and eliminate the more far-fetched contributions in development in the final fishbone from the session. The idea is to get everyone thinking creatively one problem. At this point you don’t need to target one “why” but consider all possibilities, for each category- environment, method, equipment etc., you can narrow to a “vital few” once you have a visual for everyone to work from. Making this effective: If you are the manager- try to resist telling eveyone what you believe is the problem, telling people don’t mislabel etc., is not helpful either, your goal is to get at what/how/why people who do the task gets in the way or makes it more difficult for them to complete accurately/effectively/efficiently. It is your goal to listen, and make sure that everyone gets a chance to contribute ideas- manage “speaking time” in the group. If you are in the meeting, and you have made suggestions before, and you feel that no one listened then, just say your idea again, this is your opportunity to get your ideas documented for consideration in a formal way. You will feel better about any change, which is set to be put into effect, if you have an opportunity to define it.
  • Implementation stragtegy for making changes to improve quality- this is a step by step for the supervisor or manager- when this information is compiled, meet again with your group( this is the important feedback and communication) , tell them the summary of what you identified, any noticed/documented improvements, and acknowledge their efforts towards change and improving, emphasize how what they do each day aligns with organizational goals, and patient care. If something is still off target, this time is also good point to ask for additional feedback for modifications from the original change in process, protocols or procedures how they feel things are working or what could still be improved. It is not likely that any single identified quality issue or error problem will be completely corrected with one attempt, be committed to the continuous process of seeking quality and the on-going nature of process improvement.
  • I suggest dividing process into process phases, identify from error recording, sources of error- use historical data Can rank in terms of frequency or severity to quality or patient outcome. Accuracy and precision help define the limits of what your data can reliably tell you- just something to keep in mind. You want to use all forms of feedback, and not just look at the numbers, which can have limitations of precision /accuracy contingencies, ( due to collection deviations, leave out certain factors that might be subjectively or qualitatively considered or deserve weight in the analysis). Data is essential to making a fact-based ( versus perception-based) analysis of a problem, but it is not ideal to just to view the data in a “vacuum”. Can use fish bone diagram, and/or FMEA ( Failure mode and effects analysis) tools to round out the information available for consideration. We have mentioned fishbone diagrams, but FMEA is a more complicated method, but can yield results that a project team can use to study all the possible problems in a process, the potential impact of each problem, and possible solutions. I like taking the problem and supporting data to a team, consisting of those people who really deal with the problem on a daily basis. Open a dialogue, and create a fishbone from the feedback, consider FMEA if you have the time and resources, and then develop detection and error correction processes for those items identified as contributors. See if what you come up with lines up with your data as far as frequency or severity of impact. You can then work to reduce error opportunities for the biggest issues, as well for the most common variability to the process you are considering.
  • All laboratories are subject to external assessment by licensing agencies such as Centers for Medicare and Medicaid services, under CLIA’ 88, or accreditation organizations such as the Joint Commission, College of American Pathologists, or Commission on Office Laboratory Accreditation. These organizations serve to assessthe laboratory against their published requirements and issue deficiencies for identified non-conformities that require corrective actions for the laboratory to maintain its license or certification. The second external assessment, proficiency testing, involves comparison of the lab’s peformance on a selected process with other laboratories of similar size and scope. CAP offers two such programs- Q-PROBES and Q-Tracks. Internal assessments should consist of at least two types of internal assessments- quality indicators measurements, and laboratory audits. Measurable indicators may be items such as sources of inadequate samples, or TAT. The audit is a process of comparing observed actual conditions with requirements, and then presenting the findings in report format to management. Ideally, the audit can focus on any pre-analytic, analytic or post-analytic process to determine its conformance to the lab’s existing policy, procedure or process, as well as external or accreditation requirements. Currently, CAP inspectors are using auditing techniques where they follow the sample through the entire lab’s process during unannounced inspections. Audit processes are effective methods to point out process problems in need of correction ( Berte, 2007).
  • This image shows the possible internal/external sources that can be used for initial comparison of your internally identified quality issue or process improvement data – Mention CAP benchmarking, Q- probes, ISO, ANSI standards.
  • You can see from this Big 7 list, that creating a “quality culture” relies heavily on leadership and effective management.
  • In traditional organizations, management has attempted to address quality issues by changing the culture, ( seeking to drive certain desired behaviors and attitudes). It is much easier and more straightforward to attempt to fit the change needed to an action- or our usual way of doing things that is not working. With a focus on the system and process ( process excellence) you seek to address defects in the system FIRST, and the new systems drive the new values and attitudes.
  • Tackle those things about the physical environment you can control. Then examine your system weaknesses as we have outlined previously, culture and quality supporting attitudes and behaviors are much more likely to follow.
  • Your out put is created by your existing systems- if you want to do better, you must work on/change your systems. Aristotle quote: “we are what we repeatedly do. Excellence is not a [single] act, but a habit”. Culture is built on what we do. The values and attitudes that support those actions, become part of the “culture”. This diagram shows -Pyramid of elements which may be defined or formalized in your quality plan. Note that this plan encompasses elements which may be considered QC and/or QA information, records or practices. The goal is to unify all of this with your quality and performance standards so that it is in alignment with departmental or organizational quality goals for patient outcomes and patient care.
  • Basic action steps: Plan the improvement Do the improvement Study the results Take further action to keep/abandon/modify the changes. Note: you also need to document what you did ( define), what were the results ( quantify), monitor over time if seems to be on target, and/ or conduct further analysis to support additional gains or maintain
  • The task for management in addressing ( circumventing) errors or quality issues is to create safeguards within the technical and organizational procedures, policies and expectations for performance that provide a structure and method for individual personnel to prevent , catch, and fix as many of the “human errors” in the most timely and efficient way. Note- not to minimize accountability- you may want to include in standards some task performance , which as a single event, is unacceptable at any time, or think about a cumulative number for any error that is unacceptable. (Try to consider the entire range possible)
  • Remember if you are in a management or leadership role: You will need some quantifiable baseline of where you started to compare to ( prior to revisions). Keep careful details of control limits, following changes made ( what/when), and the impact on the targeted problem, error, or quality issue ( compare to pre-established baselines). Get a handle on your document control, make sure you policies, procedures, and protocols currently in place are working and complete. Actively seek actions directed at quality goals- look at the system defects first- I like the process team approach. This is where the communication and feedback really become important. Use primary resources for templates and examples of how to get organized and started. Break things down into managable parts, select key items for change and improvements, don’t try to tackle everything all at once. It is essential that team leaders, supervisors and managers, are prepared for obstacles an set backs, resistance to change. You must keep committed to the goals of improved quality and constantly relate this to patient care- be a “change agent”. Your consistent support of the need and importance of quality goals, supported by action-oriented system changes, will eventually foster values and attitudes of a “quality culture”.
  • Revised Quality Management Basics Texas Histology Society

    1. 1. Quality Management Basics The Histology Laboratory
    2. 2. My introduction <ul><li>Joelle Weaver MAOM, HTL (ASCP) </li></ul><ul><li>Undergrad-BGSU, Masters- Bluffton University, also HTL –ASCP </li></ul><ul><li>My “pet topics” - team approaches to quality and organizational effectiveness, organizational culture, building teams. </li></ul><ul><li>This topic came to me from seeing posts where there was confusion about the terms QA, QC, and quality systems, and my own experiences with process improvement initiatives… </li></ul><ul><li>To me its a question of “how wide you throw the net” in thinking about QC, QA, QMS- the terms each describe a part of the whole to create the environment for excellent quality, good patient care … </li></ul>
    3. 3. Content Description <ul><li>Outline of basic principles of quality management </li></ul><ul><li>Discuss terminology ( define QC, QA, and QMS). </li></ul><ul><li>Identify the phases of any lab processes and relate these to quality considerations. </li></ul><ul><li>Some added ideas for approaching quality management using a team process improvement approach. </li></ul><ul><li>Structure that supports a “quality culture”. </li></ul><ul><li>Implementation ideas for new quality control systems and/ or evaluation of existing methods. </li></ul><ul><li>Identification of external and internal measurement sources for quality assessment. </li></ul>
    4. 4. Learning Objectives <ul><li>Acknowledge historical context and existing challenges within histology </li></ul><ul><li>Clarify terminology associated with quality management </li></ul><ul><li>Outline components of an effective quality management system </li></ul><ul><li>Provide quality management examples for system improvements supporting quality </li></ul><ul><li>Identify errors that impact quality and identify tools to identify and manage errors. </li></ul><ul><li>Relate the above concepts to occurrence management, internal/external assessment and process improvement. </li></ul><ul><li>Discuss practices and organizational attributes which support a “quality culture”. </li></ul>
    5. 5. HISTORICAL PROGRESSION <ul><li>Quality management in Histology </li></ul>
    6. 6. Acknowledge historical context and existing challenges within histology <ul><li>Historically, histology less intervening technology, mostly “labor intensive, manual” process for over 100 years. </li></ul><ul><li>Due to the slower adoption of technology/automation, histology has lagged behind the QA, PI- seen in clinical lab, other medical arenas. </li></ul><ul><li>?Reasons; tradition, staff shortages, manual steps difficult to automate and standardize. </li></ul>
    7. 7. Finding Resources/Time for Quality <ul><li>Necessity-CAP requires a written quality improvement plan ( checklist item ANP.1000). </li></ul><ul><li>Most effective, when direct, as simple as possible, and tied to organization’s mission in a clear way. </li></ul><ul><li>Ideally QC,QA and quality improvement activities –become everyone’s responsibility-not just MGMT. </li></ul>
    8. 8. TERMINOLOGY <ul><li>Key terminology used when discussing quality management </li></ul>
    9. 9. Key terms associated with quality management <ul><li>Quality control- ( technical- identifies inaccurate in the process/system, verifies proper use by testing personnel) . </li></ul><ul><li>Quality assurance- ( management- outlines QC activities, identifies processes/procedures that are not working, provides corrective process steps). </li></ul><ul><li>Quality improvement- ( verifies proper QA and QC, assesses methodologies based on metrics, sets goals and parameters for improvement) . </li></ul><ul><li>Non-conformity- a process failure, error or undesired outcome from a process or process step. </li></ul><ul><li>Process- a series of defined steps in an outcome directed activity that leads to an intermediary product, final product, information output or result. ( note that any process can be broken down into sub-process steps or expanded out to relate to other ongoing processes) . </li></ul>
    10. 10. BASIC COMPONENTS <ul><li>A more detailed look at QC, QA, Quality Management </li></ul>
    11. 11. Quality Control- QC <ul><li>Includes documentation, training, and implementation of desired practices and procedures. </li></ul><ul><li>A complete listing of standard operating procedures or ( SOP’s) are one of the most important practices- helps insure consistency and minimizes variability. </li></ul><ul><li>Suggest: develop a written summary of known error sources identified from doing procedures in the lab from QC/QA records- useful for troubleshooting, new employees and the promotion of continuity over a succession of testing personnel and operations over time with any individual technician/technologist. </li></ul><ul><li>Example sheet in handout. </li></ul>
    12. 12. Quality assessment-QA <ul><li>QA checks the effectiveness of the QC practices used, and is used to determine if an analytical process in compliance with QA guidelines. </li></ul><ul><li>This is achieved through systematic identification, measurement and documentation of quality variables. </li></ul>
    13. 13. Clarifying Goals of QA/QC <ul><li>Important points </li></ul><ul><li>Quality assurance is not quality improvement. </li></ul><ul><li>It is not adequate for management to merely attempt QC. </li></ul><ul><li>Leadership must guide others to quality as the end result. </li></ul><ul><li>How are goals of quality improvement different? </li></ul><ul><li>Key differences to consider </li></ul>Quality Assurance Quality Improvement Motivation Measure compliance with standards Continuous process to meet standards Means Inspection Prevention Focus Individuals Processes and systems Responsibility few ALL
    14. 14. Elements of the “Quality Assurance Plan “ <ul><li>Organizational elements to be outlined (sample included in handout) </li></ul><ul><li>Mission statement </li></ul><ul><li>Overall quality objectives </li></ul><ul><li>Organizational chart </li></ul><ul><li>Code of ethics </li></ul><ul><li>Training, safety practices </li></ul><ul><li>Procedures </li></ul><ul><li>Competency, assessment </li></ul>
    15. 15. Outline components of an effective quality management system( QMS) <ul><li>Quality measure essentials- need QA and QC </li></ul><ul><li>Necessary to assure/promote confidence in analytical results ( support org. goals). </li></ul><ul><li>Comprised of those activities to monitor and document effectiveness of the QC practices ( accuracy & precision). </li></ul><ul><li>Formal documentation useful to set guidelines for all methods within lab operation. </li></ul>
    16. 16. QUALITY MGMT & IMPROVEMENT <ul><li>How to assess where the quality problems are… </li></ul>
    17. 17. The process cycle <ul><li>All laboratories have a defined test cycle that is composed of pre-analytic, analytic and post-analytic process phases. The separation of the total process into segments, and this separation assists in more narrowly defining and isolating problems. </li></ul>
    18. 18. Problem feedback loop <ul><li>Basic important element to dealing with errors and quality- a feedback loop. </li></ul><ul><li>A method that shows what errors are detected ( when in the process) , how they are resolved ( action or correction), then document patient impact. </li></ul><ul><li>This loop reinforces/communicates the relationship to how well we do, and what we do at each step, to its impact on the patient. </li></ul><ul><li>Example worksheet to collect technical error feedback in included in the handout. </li></ul>
    19. 19. HOW TO IDENTIFY ERRORS TO PRODUCING QUALITY <ul><li>Quality Improvement Opportunities </li></ul>
    20. 20. General Principles-error reduction-systems in QI <ul><li>System solutions-related to the structure and function of work processes </li></ul><ul><li>Goal 1- reduce options, complexity/variation, decrease reliance on vigilance ( checklists, automation, work logs etc.) </li></ul><ul><li>A system with internal checks, use of technology, helps address human intervention, and process complexity problems </li></ul><ul><li>Goal 2-Standardization( reduces guesswork, creates consistency, making training simplified) </li></ul><ul><li>Goal 3- Streamline information movement </li></ul>
    21. 21. General Principles-error reduction-people <ul><li>Personnel solutions- having the right people, with the right information/resources to do the task at the right time. </li></ul><ul><li>Schedules </li></ul><ul><li>Environment </li></ul><ul><li>Training </li></ul><ul><li>QI addresses fixing problems not people, but people are essential to success of any process. </li></ul>
    22. 22. Defining-Identifying system/process weak spots <ul><li>Error types- how are they defined? </li></ul><ul><li>Classically defined in original taxonomy( Eiden-Hoven Model for RCA) a commonly applied methodology to identify latent problems </li></ul><ul><li>Categories: </li></ul><ul><li>Technical failure ( equipment & software) </li></ul><ul><li>Organizational error ( policies, procedures, protocols) </li></ul><ul><li>Human errors ( mistakes and violations) </li></ul><ul><li>See handout for more information/examples. </li></ul>
    23. 23. Identifying specific problems <ul><li>Analysis of the error or problem can be approached in two ways: </li></ul><ul><li>One method is analysis of collected data, good if the team goal is mainly to improve effectiveness ( referred to as data analysis). </li></ul><ul><li>The alternate method is analyzing the process itself through process maps, good if the team goal is to improve efficiency ( referred to as process analysis). </li></ul><ul><li>You can use tools to see if system/personnel corrections will apply </li></ul><ul><li>* See hand out for a list of alternate analysis tools-we will discuss RCA in a little more detail…. </li></ul>
    24. 24. Root cause analysis
    25. 25. Pitfalls in RCA applications <ul><li>Root Cause analysis falters when it stops with data collection- you need to use this tool to analyze the “whys”. </li></ul><ul><li>Failing this step, the results are often conclusions that are incomplete, and corrections that are faulty or lacking in follow-up. </li></ul><ul><li>RCA should be considered a criteria framework for improvement opportunities, its best use is to specifically define error sources for process improvements. </li></ul>
    26. 26. Example fishbone –another tool that helps with- What/where are the errors?
    27. 27. IMPLEMENTATION AND DOCUMENTATION <ul><li>Construction of a plan </li></ul>
    28. 28. Implementation ideas for new quality control systems and/ or evaluation of existing methods <ul><li>I am a fan of the team approach- a logical way for mgmt to implement using the project team input is: </li></ul><ul><li>Identify a possible root cause(s) for a specific error (suggest using RCA). </li></ul><ul><li>List all the possible factors of the problem ( fishbone good for this). </li></ul><ul><li>Segment/stratify ( give subjective weight to) the identified factors ( FMEA can be used). </li></ul><ul><li>Prioritize by selecting what the team feels are the vital few ( those with the most impact on errors to target 1 st, and support with data). </li></ul><ul><li>Implement correction , then verify and quantify the impact of the change on the root cause of the process variation ( error) in QA tracking. </li></ul><ul><li>Report and communicate in a concise way, that presents back to the team what was done, and the results or improvements. </li></ul><ul><li>Revise/refine using feedback and data until the target goal is met. </li></ul><ul><li>Note this is a continuous process- on-going. </li></ul>
    29. 29. Ideas for MGMT- Establishing control limits-Descriptive Statistics and Control Charts <ul><li>Descriptive statistics quantify the QA program- can put ↑information for easier analysis/comparison </li></ul><ul><li>Together accuracy and precision document the systematic and random errors which make up the analytical uncertainty in lab results, error sources. </li></ul><ul><li>Accuracy & precision stats are the quantified base for performance criteria if a methodology is in “statistical control”, and whether goals are being met and maintained over time. </li></ul><ul><li>People are often under the impression they give excellent care, defensiveness, resistance result- facts bolster ways to do better. </li></ul>
    30. 30. External/Internal Assessment <ul><li>The laboratory cannot improve the quality of its service without measuring its current performance. </li></ul><ul><li>The data that you have collected and used to both quantify and qualify different quality measures can then be compared to both internal and external quality measures and/or your quality goals. </li></ul><ul><li>The lab should participate in 3 types of external assessments- 1. licensing and accreditation, 2. proficiency testing, and 3. performance comparison. </li></ul><ul><li>The results of these comparisons can help in determining if a problem really exists, has been improved, or needs continued monitoring or changes. </li></ul>
    31. 31. Sources for assessing your quality performance <ul><li>Any Comparisons made should: </li></ul><ul><li>Utilize accredited laboratories </li></ul><ul><li>Be made to validated methods </li></ul><ul><li>Include any estimation or measurement of uncertainty </li></ul>
    32. 32. A QUALITY CULTURE <ul><li>Quality starts at the “top” </li></ul><ul><li>“ Big 7” </li></ul><ul><li>Lack of management commitment </li></ul><ul><li>Inability to establish a quality culture </li></ul><ul><li>Lack of employee buy-in </li></ul><ul><li>Non-supportive measurement systems </li></ul><ul><li>Lack of quality training </li></ul><ul><li>Underinvestment in the quality initiative </li></ul><ul><li>Poorly communicated and unrealistic expectations resulting from a lack of organizational alignment </li></ul>
    33. 33. Why hasn’t this already solved the problem? <ul><li>Change the culture first (conventional thinking); </li></ul><ul><li>Suggest it is better to change the systems first ( using tools), then the culture will more likely follow… </li></ul><ul><li>“ It is easier to act your way to a new way of thinking, than to think your way to a new way of acting…” </li></ul>
    34. 34. Quality/Process Improvement Barriers <ul><li>Usually system and culture status quo are the biggest barriers…( and we will get into this briefly coming up) </li></ul><ul><li>But you can begin with work-engineering-poor workspace design, outdated instrumentation, LIS not effective (poor information flow) </li></ul><ul><li>Use process analysis to improve processes that lack cohesive flow between steps, redundant steps, insufficient detail in procedures, variables affecting outcomes not given consideration in procedure (correction process). </li></ul>
    35. 35. You cannot change within existing systems This diagram depicts some organizational systems
    36. 36. 3 questions asked in the basic improvement model
    37. 37. Provide quality “ actions” for a “culture” that drives quality <ul><li>Management needs to set quality based standards and metrics that: </li></ul><ul><li>Are observable, objective and/or measurable( define quality/quantity/accountability) </li></ul><ul><li>The standard must address performance over which the employee has control! </li></ul><ul><li>There should be clear definitions as to what is acceptable/unacceptable quality or performance ( use QA feedback/correlation), specific examples. </li></ul><ul><li>So called “mistakes” can also be viewed as “learning opportunities”. Where ( at what point) was the wrong judgment applied?, what can be changed to do better next time? Was the correct change available/defined( ask yourself as a manager) before you blame! </li></ul>
    38. 38. Summary- Bringing actions, change and documentation together <ul><li>Newly identified process changes aimed at correcting existing process or QUALITY problems must get included in revisions of protocols/procedures/processes to reinforce changed expectations. </li></ul><ul><li>Be sure to compile an overall tack and trend of where you have been, where you are headed for PI project targets- this will create the foundation for further changes. </li></ul><ul><li>The first improvement project or quality issue you tackle, is usually the most difficult to conceive, implement and sustain . Do not expect clear defined improvements immediately, there will be “fits and starts”. </li></ul><ul><li>The problem-feedback-correction loop , important to reinforce/communicate the relationship to how well we do, and what we do at each step, to its impact on the patient. </li></ul><ul><li>Essential- Leaders have to be committed to any goals they set, stay positive during set backs, and prepared to absorb feelings of discouragement people may feel from their natural resistance to change- Be a “change agent”. </li></ul>
    39. 39. References consulted <ul><li>I have included a reference list for the materials that I have consulted at the end of the handout sheet. </li></ul>
    40. 40. Questions or comments? <ul><li>Thank you for joining me today for a discussion on the basics of quality management in the histology laboratory. </li></ul><ul><li>I want to thank the teleconference Network of Texas and the sponsorship of the University of Texas Health Science Center at San Antonio for providing the opportunity for us to present this information. </li></ul><ul><li>We can now take any questions or comments… </li></ul>