Quality Control for Point-of-Care Testing
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1 Quality Control for Point-of-Care Testing James H. Nichols, PhD, DABCC, FACB Professor of Pathology, Microbiology and Immunology Medical Director of Clinical Chemistry and Point-of-Care Testing Vanderbilt University School of Medicine Medical Director, Clinical Chemistry Nashville, Tennessee, USA 1
2 Objectives 1. Review quality control (QC) as a means of controlling laboratory error 2. Identify risk management as a total quality assurance of the testing process 3. Describe regulatory changes adopting risk management in the laboratory 2
3 Historical Quality Control Quality control historically used to reduce errors and prevent the release of incorrect results from the laboratory! Born from the 1950 s industrial model of quality in analytical and factory processes Quality control is a stabilized surrogate sample analyzed like a patient sample containing a known amount of measured analyte. If the analytical test system can achieve the desired result using a QC sample, then the system is stable and quality patient results are assumed to be produced. 3
4 Quality Control Advantages QC has target values, if assay recovers target, then system is assumed to be stable (instrument, reagent, operator, sample) Shift in QC = Shift in quality patient results! Warns of test result problems before release to physician 4
5 Cape Clinic Laboratory L-J Chart for XYZ Chemistry Analyzer Analyte: Glucose Control Material: Level 1 Units: mmol/l Lot #: Exp Date: 19/4/20XX 3.48 SD assign 0.05 From: June 1, 20XX Through: June 30, 20XX Target Value 3.39 TEa 6.90% SD C o n t r o l V a l u e SD + 1 SD X - 1 SD SD SD Run
6 Quality Control Disadvantages If QC not analyzed frequently enough or lab fails to take action when QC fails, quality of patient results affected! With auto-verification or continuous release of results by automated analyzers - Possible to release patient results before a problem is detected When a problem is detected, lab must reanalyze patients since last good QC and possibly send out corrected results. Clinical action could be taken on erroneous results before correcting an unrecognized issue! Despite its limitations, QC remains an important means of detecting and preventing laboratory errors! 6
7 Systematic Errors Liquid QC does a good job at detecting systematic errors, like: Reagent deterioration or preparation Improper storage or shipment conditions Incorrect operator technique (dilution, pipette setting) Calibration errors wrong setpoint, factors Errors which affect every test in a constant and predictable manner Errors that occur from one point forward or for a limited period of time 7
8 Random Errors Liquid QC does a poor job at detecting random errors unless the error specifically occurs with the QC sample or increased result variability is noted. Errors which affect individual samples in a random and unpredictable fashion, like: Clots Bubbles Interfering substances 8
9 QC and Lab Errors QC Hemolyzed sample QC 09:00 11:00 01:15 09:00 Line Leak QC daily at 09:00, two levels Line leak occurs at 11:00, dispenses partial reagent causing 25% decrease in values, not detected until next day QC at 09:00. (Systematic Error), must reanalyze all specimens since previous QC at 09:00, the previous day. Hemolyzed specimen (Random error) affects one sample 9
10 History of Quality Control Quality control has been traditional means of managing error in the laboratory! CLIA 67 required daily QC as integral part of testing process CLIA 88 - reaffirmed two levels of QC per test per day (blood gases and coagulation testing every 8 hours) CAP advocates daily QC The Joint Commission focuses on patient safety, daily QC and preanalytic, analytic and postanalytic processes 10
11 ISO QC Recommendations ISO The laboratory shall design internal control systems that verify the attainment of the intended quality of results. Special attention should be paid to elimination of mistakes in the process of handling samples, requests, examinations, reports, etc. Documentation should include quality control procedures based on manufacturer instructions for use. Internal Quality Control (internal to the laboratory) is defined as a set of procedures undertaken by laboratory staff for the continuous monitoring of operation and the results of measurements in order to decide whether results are reliable enough to be released. The regular analysis of QC materials can serve as an essential component of a laboratory s internal control system. 11
12 Quality in Laboratory Testing Despite analyzing the minimum required 2 levels QC/day, we have all experienced erroneous laboratory results! Quality is more than QC! Quality is: Testing that is safe and reliable Appropriate use of technology to meet medical needs Test results that can be trusted for medical management A lab s reputation depends on quality of its results! What should be the lab goals for errors? 12
13 Sigma Metrics Sigma metrics are an industrial measure of quality in a factory process - estimates rate of defects in products Goal of sigma metrics: Improve customer satisfaction Balance number of rejected products with the increased cost required to improve processes (to lower defect rates) Six sigma consensus for industrial processes Six sigma was adopted and popularized into the clinical laboratories in 1990 s 13
14 Sigma Performance
15 Need for Quality Laboratory Testing Laboratory testing influences >70% of all medical decisions. >7 billion lab tests conducted in the U.S. annually Silverstein MD. An approach to medical errors and patient safety in laboratory services. A white paper prepared for the Quality Institute Meeting, Making the Laboratory a Partner in Patient Safety. Division of Laboratory Systems, Centers for Disease Control and Prevention, April
16 Beyond Six Sigma With > 7 billion tests conducted in the US annually, six sigma (3.4 defects/million tests) means releasing 23,800 incorrect lab tests annually in the US! Any single result error could mean a misdiagnosis, failure to treat an illness or incorrect treatment selection! Virus contamination of blood product, Incorrect cancer diagnosis Missed heart attack! What if that wrong test result belonged to you or a family member? For a medical laboratory, six sigma is an unacceptable goal! We need to go beyond six sigma for laboratory performance, with a goal of ZERO errors that reach the patient! The key is risk management! 16
17 Identifying Risk in the Laboratory There is no perfect device! Any device can and will fail under the right conditions Every device is different! (universal 2 levels QC/day doesn t fit every situation, may need more frequent QC especially if frequent staff turnover or unstable reagent) Any discussion of risk must start with what can go wrong with a test (errors) Lab tests are not fool-proof, for a sufficiently talented fool!
18 CLSI Project: EP23 Laboratory Quality Control Based on Risk Management. James H. Nichols, Ph.D., Chairholder EP23 describes good laboratory practice for developing a quality control plan based on manufacturer s information, applicable regulatory and accreditation requirements, and the individual healthcare and laboratory setting 18
19 EP23 Laboratory QC Based on Risk Management Input Information Medical Requirements for Test Results Regulatory and Accreditation Requirements Test System Information: Provided by the manufacturer Obtained by the Laboratory Information about Health Care and Test- Site Setting Process Risk Assessment Continuous Improvement Output Laboratory Director s QC Plan Post Implementation Monitoring CLSI EP23 Table 19
20 Where is the Risk in the Process? What Could Possibly Go Wrong? 20
21 Identifying Risk in the Laboratory Follow the sample through the testing process! At each step, ask What could possibly go wrong? For each hazard identified, define a mitigation step, a way to minimize the risk of error occurring! Summarize the hazards and actions in a quality control plan! 21
22 Steps of the Testing Process Order Treatment Treatment Postanalytical Patient Need for Test Preanalytical Order Patient Preparation Acknowledge Result Analytical Specimen Collection Processing Result Verification Analysis Lab Receipt Transport to Lab
23 1 Samples 2 Operator 4 Laboratory Environment Sample Integrity - Lipemia - Hemolysis - Interfering subtances - Clotted - Incorrect tube Sample Presentation - Bubbles - Inadequate volume Identify Potential Hazards Reagent Degradation Operator Capacity - Shipping - Storage - Used past expiration - Preparation Quality Control Material Degradation - Shipping - Storage - Used past expiration - Preparation - Training - Competency Operator staffing 3 Reagents - Short staffing - Correct staffing Atmospheric Environment - Dust - Temperature - Humidity Utility Environment - Electrical - Water quality - Pressure Calibrator Degradation - Shipping - Storage - Use past expiration - Preparation 5 Measuring System Instrument Failure - Software failure - Optics drift - Electronic instability Incorrect Test Result Inadequate Instrument Maintenance - Dirty optics - Contamination - Scratches Fishbone Diagram from CLSI EP23 Refer to Appendix A in CLSI EP18 for more comprehensive list of error sources
24 Risk Management Holistic or global approach to quality assurance incorporating preanalytic, analytic and postanalytic phases of testing AND considers the major sources of laboratory error Every instrument or device is different Hazard analysis and mitigation Hazard analysis defines the sources of potential error for an instrument or device and a means of detecting or preventing the error (mitigation) 24
25 Manufacturer Checks Alternative QC Some devices have internal checks which are performed automatically with every specimen: Development of a line (Pregnancy test, Occult blood) Sensor signal (blood gas analyzer, clots) Flow resistance and liquid sensors (clots or bubbles in chemistry and hematology analyzer pipettes) Other checks engineered into instrument: Barcoding of reagent expiration dates (prevents use) Lockout features that require successful QC Disposable analyzer cuvettes/pipette tips (carry-over) Temperature indicator in shipping carton 25
26 Unit-Use (Single Use) POCT QC Device Test Cartridge Chemistry of reaction Reads test cartridge signal Internal electronic checks maintain reader in narrow range Locks out testing if outside specs Acts as analyzer contains fluidics, calibrant, int controls QC consumes test, no guarantee next test performs same Additional control processes needed for specimen and operator technique 26
27 QC and Risk Management QC is expensive, consumes POCT reagent and labor without producing results that can be billed. The presence of engineered control processes on newer POCT devices raise the question of when and how these controls can substitute for two levels of liquid QC? How to best control unit-use POCT devices? Lab Director must balance requirements for QC (2 levels/day) against cost and availability of alternative controls on the test system Risk management steps through the testing process to identify sources of error that can help labs identify the right balance of liquid QC with built in control processes on the POCT devices 27
28 Individualized Quality Control Plan Risk Assessment Quality Control Plan Quality Assessment Individualized Quality Control Plan 28 CLIA
29 29
30 New IQCP CLIA, CAP and Joint Commission Requirements Two levels of liquid QC required each day of testing OR Laboratory develops an Individualized Quality Control Plan (IQCP): Balance built-in control processes with liquid QC Reduce frequency of liquid QC to minimum recommended by manufacturer Maximize clinical outcome, available staff resources and cost effectiveness in the lab Considers the laboratory process for testing and risk of errors at each step of the testing process! 30
31 What Have We Learned From Our IQCPs? 31
32 What Have We Learned From Our IQCPs? Processes on different units were not uniform Some barcoded BG bedside, others waited to satellite lab IQCP supports QC rationale and resources Each action is linked to a specific hazard Gives meaning for why we do what we do rather than simply meeting a regulation Opportunity for improving efficiency QC the device versus QC the reagent (i-stat) Multi-site validations of reagent shipments Monthly 3 level QC versus 6 month cal verifications 32
33 What Have We Learned From Our IQCPs? Before: (QC the device) Shipments = 10 shipments/yr x 2 QC x 7 sites = 140 tests Lot validations = 5 x/yr x 2 levels x 8 meters = 80 tests QC monthly = 2 QC x 8 i-stats x 12 mos = 192 tests 6 mo cal-ver = 8 i-stats x 3 levels x 3 reps x 2x/yr = 144 tests 6 mo correlations = 10 patients x 8 i-stats x 2x/yr = 160 tests TOTAL = 716 tests After: (QC the cartridge lots) Shipments = 4 shipments/yr x 3 QC x 1 site = 12 tests Lot validations = QC shipment, max 4x/yr x 5 pts x 2(old/new) 40 tests QC monthly = 3 QC x 7 sites x 12 mos = 252 tests If additional lot: 3 QC x 7 sites x 4 mos 84 tests 6 mo cal ver and pt correl already done monthly QC/lot val = 0 tests TOTAL = 304/(388) tests 33 Savings of nearly half each year!
34 What Have We Learned From Our IQCPs? Improved quality - Operators now perform all the required testing before the POCT staff would analyze linearities and perform 6 mo comparisons! Enhanced efficiency fewer cartridges required for non-patient testing, saves cost and resources Better quality assurance of cartridges QC every lot of cartridges monthly (the i-stat has internal checks)! 34
35 Falsely Decreased Glucose Meter Results Complaint from an intensive care unit of sporadic falsely decreased glucose meter results Immediate repeat test on same meter, gave significantly higher clinically sensible values Inspection of unit found nurses taking procedural shortcuts to save time Bottles of test strips dumped on counter in spare utility room Some strips not making it into trash, falling back on counter and being REUSED 35
36 Risk of Error from Open Reagents Glucose test strips exposed to air for as little as 2 hours have been shown to cause -26% bias. 1 Strips left on counters pose risk of reuse, leading to falsely low results. Some meters catch reuse and error preventing a result. Other meters do not! 2 1. Keffer P, Kampa IS. Diabetes 1998; 47; abs Silverman BC, Humbertson SK, Stem JE, Nichols JH. Operational errors cause inaccurate glucose results. Diabetes Care 2000;23:
37 Reagent Errors: Expired Reagents Centers for Disease Control Check and record expiration dates of reagents/kits, and discard any reagents or tests that have expired. 1 U.S. Food and Drug Administration Check the expiration date on the test strips. As a test strip ages, its chemical coating breaks down. If the strip is used after this time, it may give inaccurate results Ready? Set? Test! Centers for Disease Control booklet 2. Useful Tips to Increase Accuracy and Reduce Errors in Test Results from Glucose Meters, U.S. Food and Drug Administration 37
38 Strip Wastage When Outdated Operator must check manufacturer s expiration date prior to testing. Vials/strips and controls must be manually dated when opened by operator (prematurely expires once opened) Undated, opened vials must be discarded. (? expiration) Discarded strips due to no date 1 1. Undated vials between September, 2010 and May, 2011, Willis- Knighton Medical Center, Shreveport, Louisiana 38
39 Reagent Errors: Expired Reagents Serialized vials/strips and controls barcoded for lot number and expiration date (good to stamped expiration date) can recognize individual vials on opening (30, 60 or 90 day open expiration) Automatic lockout for expired test strips and controls Some devices can also recognize exposure to humidity (few hours), wet or reused strips as additional control measure 39
40 Manufacturer Mitigations Operator training/competency Operator lock-out Failure to perform QC QC lock-out Result documentation Data management/wireless Patient ID errors barcoding/positive patient ID Mixing sample bubbles/clots clot detection Overfill/Underfill Specimen trigger detection Calibration errors auto calibration with lot barcode 40
41 Resources for Reducing Errors Clinical Chemistry book recently released! Focus on errors in the Chemistry Laboratory including POCT Discussion of real-world errors and what can be done to manage risk by detecting and preventing errors. 41
42 Summary Many POCT devices have built-in control processed POCT requires different approach to QC Risk management is a process to reduce error in the clinical laboratory that can help develop an individualized QC plan for POCT CLSI EP23 is a resource that introduces industrial risk management principles to the laboratory We have reduced errors, saved cost, improved staff efficiency, and enhanced patient care by developing a quality control plan based on risk management for our POCT systems 42
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