8 august quality and performance indicators.pptx

While diagnostics tests cost only 4% of the total healthcare budget, lab reports effect more than 60% of all medical decisions. It is essential that the lab reports are accurate, reliable, reproducible and available in clinically relevant time. All steps of the entire diagnostic profile should be moniotred in real time by using performance indicators.

1. Laboratory Quality & Performance indicators Prof. Ashok Rattan, MD, MAMS, Common Wealth Fellow, INSA DFG Fellow , ex SEARO Temporary Advisor, ex WHO Lab Director (CAREC/PAHO); former Chairman Lab Medicine, Medanta The Medicity , Ex All India Institute of Medical Sciences, New Delhi Chairman Medical Committee and Quality, Redcliffe Labs, India

2. Control of any condition starts with diagnosis; Diagnosis brings great value to patient care Within so many clinical decisions being made based on laboratory results It is essential that laboratory results are of high quality

3. What is Quality ? Quality is difficult to define, Invisible when GOOD, impossible to ignore when BAD Doing the right thing right, the first time & every time Meeting and exceeding expectations (STANDARDS)

4. ISO 15189 : 2012 Requirements for Quality and Competence Medical Laboratories Management requirements Organization and management responsibility Quality management system Document control Service agreements Examination by referral laboratories External services and supplies Advisory services Resolution of complaints Identification and control of nonconformities Corrective action Preventive action Continual improvement Control of records Evaluation and audits Management review Technical Requirements Personnel Accommodation and environmental conditions Laboratory equipment, reagents, and consumables Pre-examination processes Examination processes Ensuring quality of examination results Post-examination processes Reporting of results Release of results

5. ISO 15189: 2022 3.26 Quality Indicator Definition measure of the degree to which a large number of characteristics of an object fulfils requirements Note 1 to entry: Measure can be expressed, for example, as % yield (% within specified requirements), % defects (% outside specified requirements), defects per million occasions (DPMO) or on the Six Sigma scale. Note 2 to entry: Quality indicators can measure how well an organization meets the needs and requirements of users and the quality of all operational processes

6. ISO 15189: 2022 8.8.2 Quality Indicators The process of monitoring quality indicators shall be planned, which includes establishing the objectives, methodology, interpretation, limits, action plan and duration of monitoring. The indicators shall be periodically reviewed, to ensure continued appropriateness.

7. ISO 15189: 2022 Clause Number Corresponding ISO 15189: 2012 Clause Number Emphasis of change 8.8.2 4.14.7 Editorial Summary of text/extract from ISO 15189:2022 Quality indicators The process of monitoring quality indicators shall be planned, which includes establishing the objectives, methodology, interpretation, limits, action plan and duration of monitoring. The indicators shall be periodically reviewed, to ensure continued appropriateness.

8. Sample Results Laboratory Performance Indicator PI is an objective & improvable measure through which lab’s performance can be quantified A PI can play an important part in this process But selecting and using PI is not trivial Process Input Output

9. Laboratory Performance Indictors Necessary to understand the performance of the process To monitor and control operational efficiency To make improvements To measure effectiveness of decisions To take suitable actions for maintaining competitiveness

10. IFCC International Harmonization QI Project 2017 IFCC is now (2023) ADLM, Association for Diagnostics and Laboratory Medicine Quality Indicators allow labs to quantify the quality of lab processes, which is fundamental to patient safety Harmonization of Quality Indicator is necessary to ensure that all clinical labs define, report and benchmark their QI to a defined Quality standards Identification of reliable I across the total testing process is a crucial step which helps to identify the quality of lab services

11. Pre-Requisites for Quality Indicator Applicability to a wide range of labs Scientific robustness with a focus on areas of great importance for quality Definition of evidence based threshold for acceptable performance Timeliness and possible use as a measure of lab improvement

12. Requirements of Quality Indicators Patient centred to promote total quality and patient safety Covers the total testing process Consistent with requirements of ISO 15189: 2022 IFCC International model (2017) proposed 57 QI Priority score was designated to highest value of individual QI for assessing: 1. Mandatory 2. Important 3. Suggested 4. Valued

13. IFCC International Harmonization of QI and measurements QI Measurement Priority 1. Key processes 21 43 Pre analytical 11 25 19 2 2 2 Analytical 5 6 6 - - - Post analytical 5 12 9 - - 3 2. Support Processes 3 5 - 4 1 - 3. Outcome measurements 3 5 5 - - -

14. Performance Specification

15. Phases of Diagnostic Cycle Pre Analytical Analytical Post Analytical Pre Examination Examination Post Examination Patient preparation report dispatch sample, transport storeage Pre Analytical Analytical Post Analytical Pre Examination Examination Post Examination Pre Pre Pre Examination Post Post Post Which test What next

16. To err is human 1999 (IOM report) 44,000 to 98,000 Americans die each year from medical error >8 th leading cause of death >motor vehicle deaths, breast cancer or AIDS Laboratory tests errors: 50 % : failure to use indicated tests 32% : failure to act on results of test or findings 55% : involved delay in diagnosis

17. Deaths in USA due to medical error are Equivalent to ONE Jumbo jet crashing every day of the year

18. Medical Errors effect Patient Safety Occur throughout the health care process And Causes Annoyance Inconvenience Diagnostic delays or error Increase cost Institution of inappropriate therapy Increased risk of patient illness, disability & even death

19. Institute of Medicine [IOM] Laboratory is required to systematically assess & improve important functions & work processes & their outcomes [JCI] Essential to lay down certain benchmarks to assess laboratory functions A QI is defined as an objective measure evaluating critical health care domains Patient safety Effectiveness Equity Patient centeredness Timeliness Efficiency A potential QI needs to fulfil 2 inclusion criteria Must be an indicator of laboratory functioning Must cater to alteast 1 IOM health care domains

20. Select & Develop Quality Indicators with care Poorly designed QI lead to confusion & misleading information Resulting in increased work & poor decision making QI maybe well designed but impractical because lab doesnot have resources or capability for follow through with an appropriate action plan Stable QI : Some labs continue to collect information on parameters that are highly stable, should shift focus, time & energy to QI

21. Sigma metrics of Alinity ci system – a study on thirty-nine clinical chemistry and immunoassay parameters Fatima Zehra Kanani *, Adnan Haider Kazmi and Bushra Kaleem Adv Lab Med 2021; 2(2): 267 – 275

22. Suggested QI for core hospital laboratories Greater Toronto Area Laboratories should include all of the following high-priority quality indicators for regular monitoring of critical processes that impact patient care

23. Suggested QI for core hospital laboratories Greater Toronto Area Laboratories should report the quality indicators according to the IFCC harmonization model to enable comparability with performance benchmarks.

24. Suggested QI for core hospital laboratories Greater Toronto Area Quality Indicator Performance Reports

25. CAP’s Q TRACKS program field tested 11 QIs No. Indicator Description 1 Patient/Specimen identification Percent of indoor patients wristband error, percent of ordered tests with pt identification error or percent of results with identification errors 2 Test order accuracy Percent of test orders correctly entered into a lab computer 3 Specimen acceptability Percent of general haematology &/or chemistry specimens accepted for testing 4 Stat test TAT Collection to reporting TAT or receipt in lab to reporting TAT of STAT tests 5 Critical value reporting Percent of critical results with documentation that results have been reported to care giver; percent of critical results for which primary clinicians cannot be contacted in a reasonable period of time 6 Customer satisfaction Must use a standardized satisfaction survey tool with a reference database of physicians, nurse or patient respondents

26. CAP’s Q TRACKS program field tested 11 QIs No. Indicator Description 7 corrected reports percent of reports that are corrected 8 CR in Anatomic pathology percent of reports that are corrected in Anatomic Pathology 9 Surgical Pathology / cytology specimen labelling percent of requisitions or specimen containers with one or more errors of predefined type 10 Blood component wastage percent of red blood cell units or other blood components that are not transfused to patients 11 Blood culture contamination percent of blood cultures that grow bacteria that are highly likely to represent contamination

27. Turnaround time Definition : Turnaround time (TAT) is the time between two steps in the diagnostic process. The definitions of these two steps depend on the goals of the laboratory. Time between the moment the sample arrives at the laboratory until the results are reported, is the most commonly used definition of TAT by clinical laboratories. Measurability : The TAT can be calculated by subtracting the timestamps of the two steps under consideration. A predictable TAT may be preferred over a shorter mean TAT. Impact : TAT is often used by clinicians to benchmark laboratory performance. No significant correlation between routine test TAT and patient length of stay (LOS) in hospital, better correlation with LOS in ER.

28. Identification error Definition : An identification error often arises from a request form or a sample bearing incorrect patient or physician information. Measurability : Impact : Incorrect identification can negatively affect patient safety in the form of misdiagnosis and unsuitable treatment. In a study, 159 h of manual rework was required due to 45 misidentified specimens during a period of three weeks Corrective step : labeling of specimens in the presence of the patient and the selection of suitable identifiers to be noted on the sample and request

29. Sample hemolysis Definition : Hemolysis of blood samples occurs when red blood cells are damaged, leading to free hemoglobin in the sample. Measurability : Impact : Sample hemolysis can cause serious analytical interference Sample hemolysis can be caused by incorrect handling of the sample, inadequate vascular condition during phlebotomy or improper equipment

30. Inadequate sample volume Definition : The sample volume is inadequate when the volume of the provided sample does not meet the minimum volume requirements for testing. Measurability : Impact : In some cases, if the sample volume is insufficient, not all requested tests can be performed. A possible solution is to train phlebotomy staff on the volume requirements for each test

31. Labeling error Definition : unlabeled samples, samples bearing only one identifier and samples that had a container-requisition mismatch were considered to have a labeling error. Measurability : Impact : By implementing a single piece flow and decreasing the batch size, labeling errors can be detected earlier in the testing process, which decreases the associated rework

32. Wrong container Definition: This error occurs when samples are collected in an unsuitable container for analysis, e.g. blood collection in an EDTA container instead of a citrate container in case of hemostasis testing. Measurability: Impact : Samples collected in a wrong container have either an incorrect result or a delayed diagnosis as they have to be resampled. most frequent pre-analytical error, samples were incorrectly sent to the laboratory in anticoagulated tubes. Phlebotomy staff negligence and lack of education are possible causes of this error

33. Sample clotted Definition : Clotted samples can be defined as whole blood samples with a red clot or plasma samples with a fibrin clot. Measurability: Impact : Clotted samples result in time-consuming rework and may lead to incorrect or non-reportable results. The regular occurrence of clotted samples requires intensification of the training of phlebotomy personnel

34. Sample lost/not received Definition : A lost sample can be defined as a sample that is unable to be located to complete all requested tests. Measurability : Impact : Lost samples can be a major burden for the patient as blood has to be resampled, which results in rework and delayed test results. Providing various sample collection points can make phlebotomy more convenient, but this can also increase the rate of lost samples urine samples were missing most often

35. Cost Definition : In a clinical laboratory, there are numerous sources of cost, such as personnel cost, inventory cost, maintenance cost and reagent cost. The cost corresponding to actions and resources is expressed as their monetary value. Measurability : Cost can be directly measured in terms of a monetary value, but often a proxy such as invested time is used. For example, decreasing personnel overtime will decrease the specimen processing costs. Impact : From the VBHC perspective, it is desirable to deliver high quality laboratory services at a reasonable cost. Retesting of critical values increases laboratory running costs, but does not necessarily provide additional value

36. Quality Performance

37. Top 10 performance indicators in production processes literature and their absolute citation frequency

38. Work-in-process Definition : The work-in-process (WIP), or work-in-process inventory, is the amount of unfinished work remaining in the process (e.g. the number of samples that have not finished testing). This unfinished work includes the unfinished samples in queue. Measurability : WIP can be expressed in number of samples or in terms of the remaining processing time for these samples average WIP = average arrival rate x average TAT Impact : High WIP can be due to high queue lengths, which indicate insufficient resource capacity. High WIP also corresponds to increased space occupation and holding costs by aiming for a constant WIP, performance improvements can be achieved

39. Resource utilization Definition : There are several types of resources that can be considered, such as equipment, staff and laboratory space. The utilization of a resource is obtained by comparing the amount of time it is used with its total availability. Measurability: Impact : Manufacturing companies prefer a high machine utilization. The same is true for clinical laboratories that have expensive equipment because high resource utilization indicates efficient use of these resources. customers usually prefer short and reliable delivery times, but this may require a lower resource utilization Laboratory management has to decide on a desired level of resource utilization

40. Material handling cost Definition : The material handling cost is the cost required to transport material from one location to another. The material handling cost can be expressed in terms of a monetary value, but also in terms of time or distance. Measurability : total walking distance of laboratory staff to process a single sample or the total time a sample spends traveling between the work areas before it is completely processed Impact : logistic efficiency can be achieved by improving transport routes within the lab optimal placement of equipment has a significant impact on process performance, which is reflected in the large body of work done on this topic

41. Throughput Definition : The throughput is equal to the total number of items assembled or processed by a system over a predefined period. Measurability: Impact : In general, the aim is to maximize the throughput. An increased throughput corresponds with an increased production rate, which implies that more samples were

42. Waiting time Definition : Waiting time is defined as the time spent waiting for a value-adding operation. Examples are the time samples spend waiting in the queue of an analyzer or the time samples spend waiting before being transferred to the next processing step. Incubation time is not considered as waiting time, as this step is necessary for the testing process. Measurability waiting time = time start of analysis -- time arrived at analyzer Impact : Approximately 50% of the total processing time consists of waiting time. Waiting times are usually positively correlated with sojourn times, which implies that results can be reported earlier if the waiting times are decreased. High waiting times can indicate a bottleneck in the process

43. Maintenance/downtime Definition : the time the laboratory equipment is unable to properly process samples. Downtime may be due to preventive maintenance or due to sudden machine failure. Measurability: Impact: Equipment downtime delays the time it takes to report results. But maintenance operations are unavoidable. Laboratories that have higher failure rates experience more uncertainty and variability in their result reporting time, which can affect patient and physician satisfaction. A suitable maintenance policy can reduce failure rates. equipment malfunction, such as broken probes, is a major source of analytical error. two analyzers that are alternately turned off at night to minimize downtime and extend their lifespan

44. Safety Definition : This PI measures the frequency of accidents or other adverse events related to laboratory services. Measurability : Safety has been measured in terms of the number of accidents the distance to hazardous areas or the risk of pollution An example of an accident is a needle injury Impact : Clinical laboratories aim to provide a safe environment for their staff and patients. A safe working environment positively affects employee satisfaction . A proper laboratory layout, such as the correct placement of units containing chemical waste and proper safety guidelines, such as wearing gloves when handling samples, can decrease the risk of accident

45. Relations between performance indicators .

46. 7 Performance Metrics to Optimize Laboratory Quality and Productivity Richard Hogan

47. 7 Performance Metrics to Optimize Laboratory Quality and Productivity Richard Hogan Turnaround Time Uncertainty Analysis Customer Satisfaction Nonconformities & Complaints Technician Throughput Customer Retention Equipment Failures and Interval Analysis Richard Hogan

48. Turnaround Time Turnaround time (TAT) is a critical factor  customer satisfaction. Many customers claim they are searching for the best price. However, every customer wants test results returned to them as quickly as possible. By reducing TAT  more likely to create repeat customers, attract new Monitoring TAT  gauge the performance of laboratory Help identify ways to improve laboratory processes that reduce TAT Calculating and TAT  to identify problems and indicators that decrease throughput, allocate resources to compensate workloads, and increase customer satisfaction.

49. TAT What is in a name ? Vein to Brain

50. Uncertainty Analysis When it comes to measurement, quality is important. In scientific measurement, measurement uncertainty should be included when reporting measurement results. perceived as an exhibition of the quality and confidence in the measurement result. lower uncertainty equates to better measurement quality.

51. Customer Satisfaction The key to earning repeat business is by providing great customer service, superior quality, and creating a unique customer experience. F eedback from your customers Customer feedback is the true measure of performance for how your business serves its clients. customer survey forms after the completion of a service. Evaluate feedback scores for trends that may indicate increases or declines in customer satisfaction. If a customer claims that they are extremely satisfied, find out why If dissatisfied contact them for feedback on how to improve their experience quality of service and unique customer experience is advantage over the price war.

52. Nonconformities & Complaints Nonconformities and complaints are an important metric for evaluating the quality of laboratory processes. Donot encourage these events to go undocumented and unrecorded. Consider them as opportunities to identify the problems that caused these events. Without identifying problems labs cannot continuously improve. Laboratories should document their findings, statistically monitor for trends, and investigate to identify the root cause of their problems. It is always better to identify problems in-house rather than allow a customer or an assessor to point them out.

53. Technician Throughput Technician throughput is an important measure to identify laboratory’s top performers. Most laboratories have production goals and must learn to effectively balance quality and quantity. Identifying the top performers in laboratory is necessary to improve process efficiency. E valuate their methods to determine where they are succeeding over their coworkers. Use their methods and practices to redesign laboratory processes and train other employees to be more productive

54. Customer Retention Measuring customer retention is an important aspect to staying in business and monitoring growth. If you continuously drive customers away, you will eventually go out of business. As a rule of thumb, 20% of annual revenue must be generated from new business to maintain last fiscal year’s figures. This infers that most laboratories only retain 80% of their client base, on average, each year. If your business is losing customers, you need to know why. Beyond customer feedback surveys, you need to evaluate your client base annually to determine which customers you retained and lost. Make it a priority to reach out to your lost customers to determine why they have decided to take their business elsewhere. Use their feedback to improve your processes and increase customer retention.

55. Equipment Failures and Interval Analysis E quipment perform measurements and generate revenue. Over the course of time, equipment begins to fail. The ability to evaluate past performance and predict future failures is the key to ensuring measurement capability and quality. It is important that laboratories track, monitor, and evaluate equipment failure rates. An excellent method for accomplishing this task is through the use of interval analysis. This method allows laboratories to establish service intervals that more effectively identify or prevent equipment failures and out of tolerance conditions before they produce nonconformities. Preventing and identifying failures is an important aspect of quality control. Equipment failures can be costly, but unidentified nonconformities can be far more severe and bear devastating consequences.