Internal Quality Control Practices in Coagulation Laboratories: recommendations based on a patterns-of-practice survey

Transcription

1 International Journal of Laboratory Hematology ORIGINAL ARTICLE The Official journal of the International Society for Laboratory Hematology INTERNATIONAL JOURNAL OF LABORATORY HEMATOLOGY Internal Quality Control Practices in Coagulation Laboratories: recommendations based on a patterns-of-practice survey A. MCFARLANE*, B. ASLAN*, A. RABY*, K. A. MOFFAT,R.SELBY,R.PADMORE *Institute for Quality Management in Healthcare (IQMH), Toronto, ON, Canada Hamilton Regional Laboratory Medicine Program, Hamilton, ON, Canada Sunnybrook Health Sciences Centre and University Health Network, Toronto, ON, Canada Ottawa Hospital General Campus, Ottawa, ON, Canada Correspondence: A. McFarlane, Institute for Quality Management in Healthcare (IQMH), 393 University AvenueSuite 1500, Toronto M5G 1E6, Ontario, Canada. Tel.: ; Fax: ; amcfarlane@iqmh.org doi: /ijlh Received 18 February 2015; accepted for publication 19 May 2015 Keywords Coagulation, quality control, hemostasis, laboratory practice SUMMARY Introduction: Internal quality control (IQC) procedures are crucial for ensuring accurate patient test results. The IQMH Centre for Proficiency Testing conducted a web-based survey to gather information on the current IQC practices in coagulation testing. Methods: A questionnaire was distributed to 174 Ontario laboratories licensed to perform prothrombin time (PT) and activated partial thromboplastin time (APTT). Results: All laboratories reported using two levels of commercial QC (CQC); 12% incorporate pooled patient plasma into their IQC program; >68% run CQC at the beginning of each shift; 56% following maintenance, with reagent changes, during a shift, or with every repeat sample; 6% only run CQC at the beginning of the day and 25% when the instruments have been idle for a defined period of time. IQC run frequency was determined by manufacturer recommendations (71%) but also influenced by the stability of test (27%), clinical impact of an incorrect test result (25%), and sample s batch number (10%). IQC was monitored using preset limits based on standard deviation (66%), precision goals (46%), or allowable performance limits (36%). 95% use multirules. Failure actions include repeating the IQC (90%) and reporting patient results; if repeat passes, 42% perform repeat analysis of all patient samples from last acceptable IQC. Conclusion: Variability exists in coagulation IQC practices among Ontario clinical laboratories. The recommendations presented here would be useful in encouraging standardized IQC practices. INTRODUCTION The laboratory plays a key role in providing test results that help guide the management of patient care [1]. Laboratories that design and implement good quality assurance (QA) practices, which includes an optimal quality control (QC) program, can minimize analytical errors and better ensure accurate patient results and the quality of test performance [2]. Over time, QA has evolved from just running QC on analysis to included aspects that are outside of the analytic process, such as pre-analytical, postanalytical, and 729

2 730 A. MCFARLANE ET AL. INTERNAL QUALITY CONTROL PRACTICES IN ONTARIO COAGULATION LABORATORIES other issues that may impact patient results [1, 2]. Internal quality control (IQC) remains the fundamental component of most laboratory QA programs and provides documented evidence that the laboratory s results are accurate and acceptable for release [3]. Although, external QC and external quality assessment (EQA) or proficiency testing programs are helpful in assuring accuracy and, to some extent, precision, the daily IQC demonstrates day-to-day method consistency between external challenges and the original method validation [4]. Currently, there are many challenges facing laboratories, such as increased workload and scope of testing, usually with no additional resources or staffing. In addition, implementation of automated platforms for higher throughput and increasing use of auto-verification requires close monitoring of systems to ensure accurate results are reported [5, 6]. The interpretation of IQC data has evolved from manual plotting of data and visual inspection of Levey Jennings graphs to the use of multiple-rule IQC computer software. The use of integrated software programs rapidly alert users to potential IQC changes thereby ensuring better reliability of results. The advent of advanced software, within or interfaced to the laboratory information system (LIS), has greatly accelerated the ability of laboratories to deploy more advanced IQC practices. Ongoing education is required to ensure appropriate understanding and use of IQC when developing and implementing advanced software programs [5, 6]. National and international guidelines focusing on good laboratory practice are available for the management of IQC. It is important for laboratories to consider the appropriate requirements and guidance documents including the International Organization for Standardization (ISO), specifically ISO 15189, and the Clinical and Laboratory Standards Institute (CLSI) in the development of an IQC program [7, 8]. A welldeveloped IQC program will continuously monitor the performance of an assay to ensure the reported results are accurate, reliable, and reproducible. The design of the IQC system in a routine coagulation laboratory consists of a number of critical decisions that will ultimately determine its overall effectiveness. Coagulation tests are essential in the diagnosis of coagulopathies and to monitor the effectiveness of some anticoagulant therapies. Quality assurance practices in coagulation laboratories, as in all clinical laboratories, have a significant role in ensuring accurate and precise patient test results for the management of patient care and improvement of laboratory services [9]. The Institute for Quality Management in Healthcare (IQMH) [formerly Quality Management Program Laboratory Services (QMP-LS)] provides ISO accredited proficiency testing for medical laboratories [10]. In 2012, a web-based patterns-of-practice survey was conducted to gather information on current IQC practices in Ontario laboratories for coagulation testing. The scope of this review is not to provide the basics of QC, but to provide guidance and recommendations to clinical laboratories for the planning and implementation of a good IQC program in coagulation testing. Standardization of IQC practice within and across laboratories will help provide a means for detecting important errors and minimize false rejection of test results to ensure quality patient care. METHODS A web-based questionnaire was created and distributed to 174 Ontario clinical laboratories that are licensed to perform prothrombin time (PT), reported as international normalized ratio (INR) and activated partial thromboplastin time (APTT). Results were collected electronically using QView TM and assessed using MS Excelâ (Microsoft, Redmond, WA, USA). All 174 laboratories responded. One hundred and forty-one (81%) laboratories were affiliated with either small or medium hospitals with less than 500 beds; 12 (7%) participants were from large hospitals with greater than 500 beds; 17 (10%) were community (private) laboratories; and four (2%) participants were affiliated with ambulatory care centers. The average number of patient samples tested for PT/INR and APTT per day varied from less than 20 to greater than 600 (Figure 1). RESULTS Types of quality control materials Laboratories were asked what types of quality control materials they used. All laboratories used commercial quality control materials with 131 (75%) running commercial QC material from their analyzer s manu-

3 A. MCFARLANE ET AL. INTERNAL QUALITY CONTROL PRACTICES IN ONTARIO COAGULATION LABORATORIES 731 APTT PT/INR Figure 1. Average number of patient samples tested for PT and APTT in Ontario laboratories. Average number of tests reported daily > % 10% 20% 30% 40% 50% 60% 70% Laboratories (%) facturer and 56 (32%) using third party QC from another manufacturer s source. Additionally, 13 (7%) participants reported that their laboratory used commercial QC from their analyzer s manufacturer and another source. A minority (22; 12%) of laboratories used an in-house QC of pooled patient plasma. Of these, 18 (10%) used patient controls at times by itself or four (2%) in addition to running a commercial QC material. Two (1%) participants indicated that they used in-house material, one for checking precision and the other ran in-house normal plasma pool every 2 h for monitoring the stability of the analytical system between commercial QC runs. All laboratories ran at least one normal and one abnormal CQC daily. Almost half of the participants reported that their laboratory ran one normal and one level of abnormal commercial QC, PT/INR: 81 (47%) and APTT: 79 (46%). The other participants reported that they ran one normal and two levels of abnormal control, PT/ INR: 93 (53%) and APTT: 92 (54%). Frequency of internal quality control runs Laboratories were asked how they established the frequency for running commercial controls for PT. Of the 172 laboratories who submitted answers for this question, 122 (71%) follow manufacturer recommendations for establishing QC frequency of PT runs, 72 (42%) chose alternate options, with 31 (18%) selecting one other option, and 41 (24%) selecting multiple options. Fifty (29%) laboratories indicated that they use the IQMH Laboratory Accreditation (LA) Standards for determining QC run frequency, two (1%) of these indicated that both College of American Pathologist (CAP) and LA requirements were used, one (0.06%) participant reported use of IQMH Consensus Practice Recommendations, two (1%) participants used recommended or regulatory guidelines which were not specified, and one laboratory (0.06%) used the CLSI guideline H47-A2. Five (3%) participants reported that QC testing frequency was based on past experience, and one participant reported that the length of workday dictated QC frequency. In six (3%) organizations, the medical laboratory director or hematopathologist determined frequency of QC runs. Other factors considered included the following: the stability of the test (46; 27%), clinical impact of incorrect test result (42; 25%), and the number of samples potentially requiring repeat analysis if QC fails (17; 10%) (Figure 2). The results were similar for how laboratories establish the frequency of commercial QC for the APTT test. Of 169 laboratories who responded, the majority 119 (70%) based QC frequency on manufacturer recommendations. Other factors considered included the following: the stability of test (45; 27%), clinical impact of incorrect test result (42; 25%), and the number of samples potentially requiring repeat analysis if QC fails (18; 11%). Seventy-two (41%) participants selected other as an option in the survey with 50 (30%) who reported that they establish frequency of QC runs based on IQMH LA requirements, 2 (1%) of these indicated that both College of American Pathologist (CAP) and LA requirements were used, one (0.06%) participant reported use of IQMH Consensus Practice Recommendations, two (1%) participants

4 732 A. MCFARLANE ET AL. INTERNAL QUALITY CONTROL PRACTICES IN ONTARIO COAGULATION LABORATORIES APTT PT/INR IQMH laboratory accreditation, CAP, CLSI or other guidelines Stability of parameter/test to allow for retesting Clinical impact of incorrect test result if error is undetected Number of samples potentially requiring repeat analysis Manufacturer's recommendation 0% 10% 20% 30% 40% 50% 60% 70% 80% Percent of participant laboratories Figure 2. Sources used in determination of frequency of IQC runs. used recommended or regulatory guidelines which were not specified, and one laboratory (0.06%) used the CLSI guideline H47-A2. Five (3%) participants reported that QC testing frequency was based on past experience, and one participant reported that the length of workday dictated QC frequency. In six (3%) organizations, the medical laboratory director or hematopathologist determined frequency of QC runs (Figure 2). Most laboratories responded that the commercial QC for the PT and APTT was run at the beginning of each shift: 119 (69%) and 116 (68%), respectively, and when the analyzer had not been in use for a defined time period: 44 (25%) and 43 (25%), respectively. A small number of participants only ran commercial QC for the PT and APTT at the beginning of the day: 12 (7%) and 11 (6%), respectively. In addition, some laboratories defined other times that commercial QC would be run for the PT 102 (59%) and APTT 95 (56%). These times included the following: postmaintenance, after a reagent change, in the middle of each shift, with every repeat sample, following a service on the instrument, every 100 patient samples, or at time prespecified intervals of either 1, 2, 3, or 4 h. The majority (146; 84%) of participants reported that they do not use in-house patient QC materials for PT analysis. However, 16 (9%) laboratories specified that in-house QC was performed with each defined analytical run, nine (5%) reported in-house QC was performed when an analyzer had not been used for a defined time, three (2%) ran at the beginning of each day, two (1%) at the beginning of each shift, and six (3%) had other responses which stated that in-house QC was run every one or 2 h between commercial controls and at the end of each analytical run. Twenty-two (13%) participants noted that they determined the stability time frame for in-house QC materials, and six (3%) participants did not. For the APTT, 147 (86%) did not use in-house patient QC materials. However 15 (9%) laboratories specified that they perform in-house QC with each defined analytical run, seven (4%) when an analyzer has not been used for a defined time, three (2%) at the beginning of each day, two (1%) at the beginning of each shift, and three (2%) had other responses which included every one or 2 h between commercial controls, and at least three times during a shift. Nineteen (11%) participants noted that they determined the stability time frame for in-house QC materials, and six (3%) participants did not. Participants were asked how many patient samples they would run before retesting the commercial QC for both the PT and APTT. The most common practice was to run the commercial QC following an analysis batch of <20 samples: PT (75;43%), APTT (97;56%), followed by samples: PT (33;19%), APTT (31;18%); samples PT (21;12%), APTT (12;7%); samples: PT (8;5%), APTT (6;3%); and >80 samples: PT (14;8%), APTT (4;2%) (Figure 3). These results correlate well to the average number of patient samples being run per day (Figure 1). Monitoring internal quality control results All participants reported that preset QC limits were used for coagulation tests, but there was a variation in the procedures used by Ontario laboratories to determine QC limits. The majority (114; 66%) of laborato-

5 A. MCFARLANE ET AL. INTERNAL QUALITY CONTROL PRACTICES IN ONTARIO COAGULATION LABORATORIES 733 Other - every 2, 4 or 8 h or after reagent change Only run commercial quality control(s) once a day >80 patient samples patient samples patient samples APTT PT/INR Figure 3. Number of patient samples run prior to retesting the commercial QC patient samples <20 patient samples 0% 10% 20% 30% 40% 50% 60% ries used the standard deviation (SD) of the QC material to set the QC limits. However, many participants indicated a combination of methods for determining QC limits was used, including precision goals from manufacturer recommendations (79; 46%), published precision goals (45; 26%), and allowable performance limits (APL) (62; 36%). Of the 107 laboratories that reported their precision goals, the majority (94; 88%) of participants use the limit of 5% coefficient of variation (CV) for both the PT and APTT. The remaining laboratories (13; 12%) reported a wide variation of precision goals ranging from 6% to 25% for both PT and APTT (Figure 4). Nine (5%) participants reported that their laboratory used only one QC rule to determine acceptability for reporting patient results; of these, five (56%) use 1 2s and four (44%) use 1 3S. All other laboratories use multirule procedures (Table 1). The majority (165; 95%) of laboratories use a combination of the 1 2s, 1 3S, 2 2s, R 4s, 4 1s, and 10 x rules. Additionally, 34 (20%) laboratories reported also using the following QC rules: 14 (8%) laboratories use two of three 2SD rule (two of last three results outside of 2SD), nine (5%) use 12 x, five (15%) use 8 x, 1 (0.5%) uses 7 x, one (0.5%) 12 x and 7 T (seven consecutive data points for a single level of control show an increasing or decreasing pattern), one (0.5%) uses 7 T, and one (0.5%) uses 1 4s and 1 5s. Two (1%) participants that selected other did not specify the rules that they used. Laboratories used various methods to monitor the IQC results: 114 (66%) used a QC program incorporated into their LIS, 78 (45%) used a QC software from the QC provider, 69 (40%) used the QC software on the coagulation analyzer, 21 (12%) used manual documentation (pen and paper), and five (3%) used an in-house computer software program built in MS Excel â. Actions taken when internal quality control fails Laboratories were asked to choose from a list of troubleshooting actions taken when QC fails. Participants responses are summarized in Table 2. Almost all of the responding laboratories (greater than or equal to 90%) repeat the QC and, if it passes, patient results are reported; participants responded that they would Figure 4. Precision goals for PT and APTT. Number of laboratories Precision goals -PT/ INR Precision goals (%) Number of laboratories Precision goals -APTT Precision goals (%)

6 734 A. MCFARLANE ET AL. INTERNAL QUALITY CONTROL PRACTICES IN ONTARIO COAGULATION LABORATORIES Table 1. QC acceptability rules used by Ontario Laboratories No. of Laboratories (total number of laboratories = 174) 1 2S S S R 4S S x Other Total 174 % of Laboratories Table 3. Documentation of investigation of failed QC Action Number of Laboratories Record level and lot number of QC material Analyzer name Rule violated Lot number of reagents Date and time testing is resumed Root cause analysis Authorization for testing to resume Lot number of calibrators Percent (%) Table 2. Troubleshooting actions when QC fails Action Number of Laboratories Percent (%) Repeat the QC, and if it passes, report results Open new QC Look for trending Discontinue testing until controls are within limits Repeat all patient samples from last acceptable QC Other actions for failed QC results: Change reagent Repeat consecutive samples 8 5 until no discrepancy is observed Contact technical 5 3 service Calibrate if no analyzer 4 2 issue has been identified Use options depending 4 2 on the failure Repeat effected samples 2 1 Confirm calibration 2 1 Repeat random samples Inform charge technologist open a new vial of QC, would look for trending of results, would discontinue testing until QC was within acceptable limits, and 73 (42%) of participants would repeat all patient samples from last acceptable QC. There were 44 (25%) participants that reported they would take other actions for failed QC results, which are itemized in Table 2. Participants were asked what information would be documented in the investigation of failed QC, and these responses are summarized in Table 3. Almost all (170; 98%) participants document actions taken for troubleshooting, but only 24 (14%) of participants include all details listed in their investigation reports. The majority (165; 95%) of laboratories record the level and lot number of QC material, analyzer name, the rule violated, and the lot number of reagents, and the date and time testing was resumed and the root cause analysis was performed. A minority (72; 41%) of laboratories document authorization for testing to resume and lot number of calibrators. Of 168 laboratories that responded to a question regarding using risk assessment for improvements to patient safety, 120 (71%) reported that their laboratory used risk management techniques. In the coagulation laboratories, QC issues were used by 131 (77%) of participants as a mechanism for identification of potential risks for patient safety. DISCUSSION A high percentage of medical decisions are influenced by laboratory results [1]. The results of coagulation tests are essential for the diagnosis of coagulation disorders, assessment of a patient s risk for bleeding, and to monitor effectiveness of some anticoagulant therapies [3, 9]. As such, the QA practices for QC in coagulation laboratories, as in all clinical laboratories, have a significant role in ensuring accurate and precise patient test results [9]. A world leader in quality con-

7 A. MCFARLANE ET AL. INTERNAL QUALITY CONTROL PRACTICES IN ONTARIO COAGULATION LABORATORIES 735 trol, Dr. James Westgard, stated Do the right QC right and when this is applied, there is an assurance of the quality of test results [11]. The incorrect use and monitoring of quality control strategies can be associated with serious patient risk when a wrong result is reported and can add additional costs associated with performing unnecessary repeat or follow-up tests [1]. Performing the QC right is a shared responsibility within the laboratory from the bench technologist to laboratory supervisors, managers, and directors whose responsibility lies in overall quality assurance within a quality management system [1, 2]. Coagulation testing is considered to be one of the most complex in diagnostic laboratory testing and needs to be well controlled for providing reliable results for screening, diagnosis, and monitoring therapy of hemostasis [12]. The summary of the results from the 2012 IQMH patterns-of-practice survey shows significant variability of IQC practices across Ontario laboratories and suggests that standardization could be beneficial for detecting errors, minimizing false rejection of test results, and optimizing productivity [9, 13]. Choosing the right QC is the first step for a good IQC program [10]. In the results of our survey, all participating laboratories reported that they used commercial QC materials with approximately one-third reported using third party QC and a minority of laboratories also using an in-house QC comprised of pooled patient plasma. Third party QC has the advantage of being an independent assessment for the analytical performance over multiple reagents and calibrator lot number changes as it is not optimized for any specific instrument or reagent system. Choosing the appropriate QC material is essential to ensuring optimal error detection [8]. As there is no perfect control material, several factors should be taken into consideration when choosing QC materials, such as matrix, cost, stability, ease of use, and the laboratory s intended application [8, 10, 11]. Part of choosing the right QC is to include QC levels at or near to clinical decision points as recommended in ISO [7]. In addition to commercial controls, patient controls can be run with each batch, or periodically during analytical runs, to show reproducibility over time. This offers an economical approach to rapidly identifying any issue that may develop between running commercial controls. Repeat testing of a stable patient sample can be used as a risk mitigation tool and is a good verification of precision. Results from a stable patient sample are compared against previous results and should be within predetermined and validated limits. If the difference exceeds the limits, an investigation should be performed to determine the cause. The use of patient samples may also be used for interand intralaboratory agreement between different analyzers and they are useful to eliminate matrix effects when reagents are changed [14 17]. However, laboratories need to consider sample stability and the impact on coagulation test results over time (i.e., loss of factor activity that may negatively impact reproducibility of the assays) [18]. It is important to determine the stability of control materials and effects of different reagents that may be used in testing. Commercial control materials offer the advantage of longer storage stability but do have the disadvantage of possible matrix effects and may be prone to errors from inaccurate reconstitution of lyophilized samples [2, 15]. QC material may slightly degenerate after opening, and a small amount of drift may be seen before outdating of the QC material [17]. The frequency of running controls is also an important part of initiating a good QC program [8]. The majority of coagulation laboratories in Ontario indicated that commercial QC was run at the beginning of each shift with 25% of participants reporting that they also ran their QC if the analyzer has not been in use for a certain length of time. A small number of participants only ran commercial QC at the beginning of the day. Additionally, participants reported that QC may be run following maintenance, reagent change, middle of each shift, and with every repeat sample. From the results of our 2012 survey, the frequency of running QC is largely based on manufacturer recommendations. However, other factors considered included the following: stability of test, clinical impact of incorrect test results, the number of samples potentially requiring repeat analysis, directive from the laboratory director, and past practices and/or the length of the workday. About one-third of the participants also reported using laboratory accreditation requirements and regulatory guidelines for determination of IQC frequency. The most common guidance cited in the laboratory responses was IQMH. Both IQMH and CLSI recommend running a minimum of one normal and one abnormal control during every 8 h of contin-

8 736 A. MCFARLANE ET AL. INTERNAL QUALITY CONTROL PRACTICES IN ONTARIO COAGULATION LABORATORIES uous operation with the level of controls spanning the clinically relevant reporting range. They both also recommend running a control specimen immediately following instrument maintenance, reagent change, or a lot number change. Additionally CLSI suggests running QC more frequently in high-volume testing centers by running one of the two or three controls levels once every 4 h [19, 20]. Manufacturers may offer recommendations for the frequency of running QC, but it is the responsibility of the laboratory to evaluate and validate the effectiveness of the control process used in the laboratory [3, 11]. The length of the analytical run is at the discretion of the laboratory and the medical director; however, the decision for length of the analytical run should take into consideration test volumes and time between samples. Periodic reassessment of the analytical performance should be at a frequency that will monitor the system and increase the likelihood of detecting system errors, decreasing the potential release of incorrect results [3, 8, 11, 21, 22]. The concept of an analytical run is the time interval or the number of measurements over which accuracy and precision are expected to remain stable [15]. All Ontario laboratories reported the use of preset QC limits for the assessment of QC results. The majority of survey participants use a combination of the 1 2s, 1 3s, 2 2s, R 4s, 4 1s, and 10 X rules. Additionally, laboratories responded also using the following QC rules: 2 of 3 2SD rule (2 of last 3 results outside of 2SD); 12 x,8 x, 12 x, and 7 T (seven consecutive data points for a single level of control show an increasing or decreasing pattern); and 7 T,1 4s, and 1 5s. Monitoring of QC should be a planned process and reviewed periodically for detection of systematic and random errors. A systematic error is a change in a test system that is always in one direction and causes a shift in the mean. Systematic errors are detected by the 2 2s, 2 of 3 2s,3 1s,4 1s,6 X, and 10 X. A systematic error could occur after a QC sample is tested and could remain undetected for a period of time before the next QC measurement. A random error is inherent in any process. It can be either positive or negative and results in a change in precision. Random errors are detected by the 1 3s,1 5s, and R 4s rules [8, 11, 15]. These errors can be detected on careful review of quality control charts. Precision goals are often used to determine the reproducibility of results. Precision is defined by the closeness of agreement between replicate measurements. It is expressed quantitatively in terms of imprecision either as the standard deviation (SD) or the coefficient of variation (CV) of results in a set of replicate measurements [8, 15, 16]. Most often QC limits are based on the standard deviation of the QC results but may consider other sources such as precision goals provided by manufacturers or published literature or may be determined from allowable performance limits. Clinicians expect that the laboratory report results that are accurate and reproducible in order to allow the correct medical decision to be made [23]. It is the responsibility of the laboratory to determine the appropriate allowable performance limits for each test [24]. In order to do this, laboratories need to understand how precision goals were derived, for instance limits will be more stringent if validated on the same instruments under the same conditions, or may be extremely wide when validated under different conditions, such as different laboratories with different operators or when comparing different instrument/reagent combinations [1, 25]. The majority of participants used the limit of 5% coefficient of variation (CV) for both the PT and APTT. However, our survey demonstrated a wide variation of precision goals ranging from 6% to 25% for both PT and APTT. The majority of laboratories reported they would repeat the QC when values are outside of the target limits. Most would open a new QC sample/vial, and if the repeat passes, patient results would be reported. Other strategies for troubleshooting failed QC included looking for trending, discontinue testing, and repeating all patient samples from last acceptable QC. The development of a good QC plan should include identification of a problem in an assay and maintaining an accurate documentation of actions taken [15]. The concept of risk management analysis has become part of the medical laboratory s day-to-day operations for improved patient safety by reducing the risk of patient harm [23 27]. The laboratory must identify events that could cause the testing process to be susceptible to errors [3, 23]. A comprehensive discussion on risk management is beyond the scope of this document; however, the QC process should include identifying the potential hazards and frequency of occurrence, analyze the risk of each hazard, implement controls, and monitor the process [23, 25].

9 A. MCFARLANE ET AL. INTERNAL QUALITY CONTROL PRACTICES IN ONTARIO COAGULATION LABORATORIES 737 Table 4. Recommendations for IQC in Coagulation Recommendations Selection of control material The QC material needs to reflect the matrix and range of analytes commonly reported for patient samples and at or near the clinical decision values. A minimum of two levels, at least one normal and one abnormal must be run. It is acceptable to use patient controls in combination with commercial controls. Commercial controls that are lyophilized or freeze dried must be reconstituted as per manufacturer s directions. QC should demonstrate stability over the claimed shelf life and the interval after opening or reconstitution. Define the length if the analytical run and frequency of controls The length of the run should be defined for each specific analytical system and procedure. The commercial QC material must be run at least once per day. It is recommended to run controls for routine coagulation with each batch or at appropriate times throughout a 24-hour period. Use of Quality Control Rules Select at minimum the 1 2s, 1 3S, 2 2s, R 4s, 4 1s and 10X QC rules to detect clinically important errors and do not allow for false rejections. The 12s rule is a warning rule; it is not recommended to be used as a rejection rule, as it causes the most false rejections [1]. Actions when quality control fails Failure of a QC rule requires that patient testing should be stopped. It is common practice to hold and not release patients results until the QC results have been evaluated, thus reducing the risk of reporting erroneous results. Depending on the size of the batch, the placement of quality control samples at the beginning and also at the end of an analytical run may help detect shifts in performance. In laboratories that use auto-validation/auto-verification, results may be released as soon as they are run. Good practice includes running controls at the beginning of the analytical run to ensure the system is performing correctly and to include additional controls throughout the analytical run to detect immediate errors and to monitor changes in the analytical performance and environment. In determining the intervals, keep in mind that if there is a failure of the QC run, and investigation demonstrates an analyzer fault, all patient samples since the previous good quality control event should be rerun. Risk management Document an accurate history of actions that have taken place in the testing system. Maintain records of all actions that have impact on performance of the system. Monitor and perform periodic review of records for troubleshooting and to prevent occurrence of QC failures. Risk analysis should include identifying where failures have occurred, the potential hazards and frequency of occurrence, analyze the risk of each hazard and determine the QC required to minimize the risks and monitor the process [3, 5, 8]. One approach is to map the QC process in order to identify where QC failures may occur and brainstorm potential causes and determine the amount of QC needed to minimize patient risk [23, 25]. Documentation records should include information on scheduled maintenance, reagent lot number changes and expiration dates, calibration records, quality control results, summary of statistics including monthly means and standard deviations, as well as cumulative means, standard deviations, and control target limits. In addition, records should include QC problems such as trends and shifts, corrective actions taken, and troubleshooting reports [3, 13, 23]. When a QC failure is detected, all testing on that analyzer for that assay should be discontinued and effective corrective actions implemented before resuming testing. Protocols should be implemented to assess the impact on previously tested specimens since the last successful QC event [3, 15]. CONCLUSIONS Our data illustrate the wide variability in QC practices for coagulation testing in Ontario. Laboratories should establish an IQC program that ensures patient safety by monitoring, detecting, and minimizing errors that

10 738 A. MCFARLANE ET AL. INTERNAL QUALITY CONTROL PRACTICES IN ONTARIO COAGULATION LABORATORIES may cause harm to a patient and documentation of investigation of failed QC. A good QC program should include a minimum of two IQC samples, normal and abnormal, to optimize the probability of error detection, but minimize the probability of false error detection. It is important to establish a review system to include benchmarks to monitor the QC program for its effectiveness over time for confidence that the analytical system is producing accurate and good quality results. This review uses survey results from Ontario laboratories to provide guidance and recommendations (Table 4) for clinical laboratories in the planning and implementation of a good IQC program in coagulation testing. Standardization of IQC practice within and across laboratories will help provide a means for detecting important errors and minimize false rejection of test results to ensure quality patient care. REFERENCES 1. Carlson RO, Amirahmadi F, Hernandez JS. A primer on the cost of quality for improvement of laboratory and pathology specimen processes. Am J Clin Pathol 2012;138: Favaloro EJ, Funk DM, Lippi G. Pre-analytical variables in coagulation testing associated with diagnostic errors in hemostasis. Lab Med 2012;43: Bonar R, Favaloro EJ, Adcock DM. Quality in coagulation and haemostasis testing. Biochem Med 2010;20: College of American Pathologists, Troubleshooting problems with the Prothrombin Time (Protime/INR), the activated Partial Thromboplastin Time (aptt) and the Fibrinogen Assay. Available online last accessed November 21, 2013 at Koepke JA. Technologies for coagulation instruments. Lab Med 2000;31: Zhao Y, Yang L, Zheng G, Cai Y. Building and evaluating the autoverification of coagulation items in the laboratory information system, Clinical Laboratory, 2013 e-publications available online last accessed at November 25 available at: clin-lab-publications.com/files/eaop/2014_01+ 02/ Zhao.pdf 7. International Organization for Standardization ISO 15189:2012(E). Medical Laboratories requirements for quality and competence, Available from 8. National Committee for Clinical Laboratory Standards. Statistical Quality Control for Quantitative Measurements: principles and Definitions; Approved Guidelines, 3rd edn, C24 A3. Wayne, PA: NCCLS, Kitchen S, Olsen JD, Preston FE. Quality in Laboratory Hemostasis and Thrombosis. West Sussex UK: Wiley-Blackwell, International Organization for Standardization ISO 17043:2010 Conformity Assessment General Requirements for Proficiency Testing Available from Westgard JO. Basic QC Practices 3rd edn. Madison, WI: Westgard QC Inc.; Lippi G, Plebani M, Simundic AM. Quality in laboratory diagnostics: from theory to practice. Biochem Med 2010;20: Sonntag O. Quality in the analytical phase, Special issue: quality in laboratory diagnostics: from theory to practice. Biochem Med 2010;20: National Committee for Clinical Laboratory Standards. Evaluation of Matrix Effects; Approved Guidelines, 2nd edn. EP14-A2. Vol 25, No 4 Wayne, PA: NCCLS; WHO, Process control: quality control for quantitative tests, Laboratory Quality Management System: Handbook. Geneva, Switzerland: WHO Press, World Health Organization, 2011;Version 1.1: CLSI. Evaluation of Precision Performance of Quantitative Measurement Methods; Approved Guidelines, 3rd edn. CLSI document EP5-A3, Wayne, PA: Clinical Laboratory Standards Institute; Jennings I, Kitchen DP, Woods TAL, Kitchen S, Preston FE, Walker ID. Stability of coagulation proteins in lyophilized plasma. Int J Lab Hematol 2015;37: Gosselin RC, Honeychurch K, Kang HJ, Dwyre DM. Effects of thawing conditions on coagulation testing. Int J Lab Hematol 2015;37: CLSI. One-stage Prothrombin Time (PT) Test and Activated Partial Thromboplastin Time (APTT) Test; Approved guideline, 2nd edn. CLSI document H47-A2. Wayne, PA: Clinical and Laboratory Standards Institute; IQMH OLA requirements V Parvin CA, Robbins S. Evaluation of the performance of randomised versus fixed time schedules for quality control procedures. Clin Chem 2007;53: Hatjimihail AT. Estimation of the optimal Statistical Quality Control Sampling Time intervals using a residual risk measure, PLoS One, 2009;4:e National Committee for Clinical Laboratory Standards. Laboratory Quality Control Based on Risk Management; Approved Guideline, EP23-A. Wayne, PA: NCCLS, Erasmus RT, Zemlin AE. Clinical audit in the laboratory. J Clin Pathol 2009;62: Powers D. Laboratory Quality Control Requirements Should be Based on Risk Management Principles. Lab Med, 2005;36: Yundt-Pacheco J, Parvin CA. Validating the performance of QC procedures. Clin Lab Med 2013;33: Tankovic AK, Silvestri J, Mails M, Najork C. Total quality in laboratory diagnostics: the role of commercial companies, Special issue: quality in laboratory diagnostics: from theory to practice. Biochem Med, 2010;20: