Journal:Utilizing connectivity and data management systems for effective quality management and regulatory compliance in point-of-care testing

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Full article title Utilizing connectivity and data management systems for effective quality management
and regulatory compliance in point-of-care testing
Journal Practical Laboratory Medicine
Author(s) Fung, Angela W.S.
Author affiliation(s) St. Paul’s Hospital, University of British Columbia
Primary contact Email: afung7 at providencehealth dot bc dot ca
Year published 2020
Volume and issue 22
Page(s) e00187
DOI 10.1016/j.plabm.2020.e00187
ISSN 2352-5517
Distribution license Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Website https://www.sciencedirect.com/science/article/pii/S2352551720301505
Download https://www.sciencedirect.com/science/article/pii/S2352551720301505/pdfft (PDF)
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Abstract

Point-of-care testing (POCT) is one of the fastest growing disciplines in clinical laboratory medicine. POCT devices are widely used in both acute and chronic patient management in the hospital and primary care physician office settings. As demands for POCT in various healthcare settings increase, managing POCT testing quality and regulatory compliance are continually challenging. Despite technological advances in applying automatic system checks and built-in quality control to prevent analytical and operator errors, poor planning for POCT connectivity and informatics can limit data accessibility and management efficiency which impedes the utilization of POCT to its full potential. This article will summarize how connectivity and data management systems can improve timely access to POCT results, effective management of POCT programs, and ensure regulatory compliance.

Keywords: point-of-care testing, data management, quality assurance, electronic medical record

Introduction

Point-of-care testing (POCT) refers to near patient testing performed outside the central clinical laboratory by non-laboratory personnel. POCT provides a faster turnaround time (TAT) for test results, which allows rapid clinical decision making. This has led to early adoption in acute care settings such as operating rooms, intensive care units, and emergency departments within hospitals. There are increasing interests in expanding POCT to chronic disease management and community health in settings such as primary care physician offices, pharmacies, remote communities, and even in disaster relief initiatives and military operations.[1][2][3] Rapid TAT is the most commonly cited reason for POCT, yet the clinical utilization of POCT should also ideally be evidence-based, cost-effective, and focus on improving patient outcomes.[4][5][6] A number of systematic reviews and narrative reviews on evidence-based POCT are ongoing.[4][5][6][7][8][9][10][11][12][13][14]

As demands for POCT have increased, managing the quality and regulatory compliance of POCT programs has continually proved challenging. Since POCT is performed by non-laboratory personnel, many clinical staff may not be familiar with quality laboratory practices, including compliance to testing procedures, quality assurance practices, and regulatory requirements. Despite the availability of national and international guidance, as well as standards documents developed by professional and government bodies[15][16][17][18][19][20][21][22], a systematic review identified quality assurance, regulatory, and data management issues as recurrent, which are significant barriers to clinical implementation of POCT.[6]

This article will summarize the benefits of connectivity and data management systems (DMS) for improving timely access to POCT results; supporting integrated patient electronic medical records (EMR), effective quality assurance, and management of POCT programs; and ensuring regulatory compliance.

Connectivity and integration with EMRs

POCT result integration with EMRs

Accreditation and regulatory standards emphasize the increasing need to integrate POCT results into the patient’s EMR.[23] This promotes the accessibility of POCT results, promotes the ability to monitor and trend those results, prevents unnecessary repeat testing, and provides evidence for patient outcomes.[18] As POCT results are used to make clinical decisions, it is important to document results with associated reference intervals, units of measurements, critical values (if applicable), date and time of testing, while also making the results traceable to device serial numbers, operator identification numbers, reagent lot numbers, and quality control (QC) results.[24] POCT results should also be clearly differentiated from other central laboratory results to avoid confusion and trending of results derived from different analytical methodologies.[24]

Manual POCT result documentation and error rates

Traditionally, POCT results and related information are manually transcribed in the patient’s paper chart at the time of testing near the bedside in the hospital.[23] In more recent years, POCT results may be manually entered or electronically scanned into the laboratory information system (LIS) or hospital information system (HIS). In the case of outpatient POCT, such as in a primary physician office, documentation is typically filed with outpatient provider's paper-based or electronic record management system, which is often separate from an LIS or HIS and may not be interfaced to the EMR.

Handwritten records are often illegible and are at risk of transcription error and duplicate charting.[15] Manual entry of POCT results into an LIS or HIS are similarly time-consuming and prone to transcription error. In my institution, for example, an average of 1,200 POC glucose results from 230 glucose meters are manually entered into the HIS by operators every day. If manual entry takes one minute, this approximates to 7,300 hours of staff time in manual entry of POC glucose results annually. This estimate does not include the time needed to log in to systems, confirm patient identification, and verify entered results. In the literature, manual entry for POC glucose results demonstrated an average of 3–5% transcription error rates in an inpatient medicine ward setting.[25][26] Transcription errors may include inversion, addition or loss of digits, rounding errors, and entry of non-numeric characters.[26] An audit at my institution identified cases where the operator entered the plasma glucose result from the central laboratory analyzer into the POC glucose result field, due to the desire to trend POC glucose results, but the affected result was measured above the device’s analytical measuring range. Another audit by Carraro and Plebani identified 12% of POC glucose results were omitted and never recorded into the patient’s chart, in which some of these results would have been useful for clinical and treatment decisions.[25]

Transcription errors are more complex for POCT with multiple test components, such as POC urinalysis and POC blood gas analysis. The semi-quantitative POC urinalysis has ten or more test components (specific gravity, pH, protein, glucose, etc.), with each component having multiple result options. The operator has to scroll through each test component and select several drop-down result options to complete one manual entry of POC urinalysis. Errors may involve selecting an incorrect result, unintentionally switching a result during scrolling, and mismatching test components and results. Test components in quantitative POC blood gas analysis can range from one to over fifteen, depending on the device and cartridge selected. Although there is a lack of published reports on the error rates for blood gas analysis, it is conceivable that the risk increases with each additional test component.

In my institution, medical laboratory technologists (MLTs), instead of the POC operator, manually enter results into the LIS for POCT that are considered at a higher risk for entry errors. In the laboratory, there is a specific procedure that requires verification by a second member of the technical staff as per regulatory requirements. Despite having and following the verification procedure, an audit of the POC hemoglobin A1c program in my institution found that 50% of results missed incorporation of a comment code that identifies the result as a POCT, as well as the operator initials. This workflow often causes delay in POCT results availability and thus affects downstream care. Issues may include incomplete result forms, an increase in workload issues for laboratory staff, and a lack of result traceability. Alternatively, electronic scanning of the instrument printout into the HIS system may be a possible solution. However, these scanned documents are difficult to search and view in the HIS and lack discrete data fields, which prevents trending and data mining.

POCT connectivity and data management systems (DMS)

In the context of POCT, connectivity means interfacing POCT devices to the LIS, HIS, or EMR via a DMS (also known as a middleware). An electronic DMS is the middleware that communicates and integrates data from multiple devices and databases and provides a single comprehensive solution for data management. Connectivity permits automated, real-time, bi-directional, electronic wired or wireless transmission of POCT results and related information.[23][27] This type of intefacing is the safest and most reliable method of data transfer. It reduces the time requirements, eases the burden, and minimizes the errors of POCT result documentation. The use of connectivity and a DMS, wherever possible, are recommended for all POCT programs by national professional bodies.[15][16]

My institution is comprised of acute care hospitals, community hospitals, long term care facilities, primary clinics, and dialysis units. We are currently undergoing system transformation, with implementation of a new HIS, a new DMS, and POCT connectivity for the first time. When an institution is considering POCT connectivity and DMS for the first time, some features to consider (Table 1) include: 1) compliance to connectivity standard CLSI POCT01-A2 (2006)[28][29]; 2) the design of the DMS (e.g., open vs closed systems, remote access capabilities); 3) compatibility with existing and future growth of POCT devices; 4) the ability to communicate bi-directionally; 5) the ability to interface to an admission, discharge, and transfer (ADT) system; 6) the need for a wireless or wired network infrastructure; 7) data storage and server requirements; 8) compatibility with existing LIS, HIS, operating systems, e-learning systems, and human resources databases; and 9) compliance with privacy and security policies. Considerations should also include institution funding for ongoing software licensing, maintenance, and upgrades, as well as technical support from the information technology (IT) department.[23][30][31][32]

Table 1. Summary of desirable features for connectivity and data management systems
Category Features
Connectivity • Connectivity standards (e.g., CLSI POCT01-A2, HL7)
• Vendor-neutral
• Ability for bi-directional connection
• Ability to interface to an admission, discharge, transfer (ADT) system
• Ability for remote access
• Real-time wireless or wired connections
• Compatibility with existing and future growth in infrastructure (e.g., POC devices, operating systems, LIS, HIS, EMR systems, and other technical requirements)
• Compliance with institution privacy and security policies
Result management • Result configuration and test mapping (e.g., location and categorization, units of measurements, decimal places, measuring ranges, reference ranges, instrument flags, critical values)
• Information transmitted with the result (e.g., patient identification number, operator identification number, device serial numbers, reagent lots, QC data, date and time of testing)
• Ability to manually enter third-party POCT data
Resources management • Device management (e.g., serial numbers, locations, dates for purchase, retirement, service, maintenance, software upgrades)
• Inventory management (e.g., activate and inactivate reagent lot numbers; QC lot numbers; acceptable ranges; dates of initiation, preparation and expiration)
• Billing capabilities
Quality assurance management • Quality control documentation (e.g., Levey-Jennings charts)
• Maintenance documentation
• Data management, mining, and audits
• Quality report generation (e.g., critical result reports, utilization reports, misidentification reports)
Operator management • Operator management (e.g., operator profiles of identification number, name, contact information, dates for certification and expiration)
• Ability to connect to online e-learning systems for electronic training and competency assessment
• Ability to connect to institution human resources database
• Automatic reminder and re-certification

A DMS may be an open (vendor-neutral) or closed (vendor-specific) system. An open DMS enables POCT devices from multiple vendors to be interfaced to a single DMS. Examples of open DMSs include Remote Automated Laboratory System (RALS Web 3, Abbott Laboratories, Chicago, IL, USA), Telcor QML (TELCOR Inc, Lincoln, NE, USA), and Orchard Trellis (Orchard Software, Carmel, IN, USA). An open DMS may be an integrated system or interface engine system.[31] An integrated DMS is when multiple vendor devices interface to a single DMS, which requires the DMS vendor to have excellent relationships and experience in interfacing combinations of different POCT device vendors with different LIS, HIS, and EMR vendors. An interface engine DMS is when multiple vendors' DMSs interface to the LIS or HIS, which requires the POCT coordinator to be proficient in multiple vendor-supplied DMSs and databases.[31] With increasing demand for open integrated DMSs, traditionally closed DMSs are now also offering options to interface to devices from other vendors. Remote access capabilities enable the POCT coordinator to monitor, review, and troubleshoot from a remote centralized location.

When considering DMS compatibility with existing and future growth in POCT devices, it is important to keep in mind desirable features for both the devices and the DMS. For instance, not all POCT devices have built-in requirements for connectivity. Some POCT may require purchase of an adaptor or software upgrade to establish connectivity. Some POCT devices also may not transmit pertinent data such as operator identification numbers, serial device numbers, reagent lot numbers, and quality control results in conjunction with the test result, as per regulatory requirements. Manual, visually-read POCT devices such as urine pregnancy, urine drug screens, urinalysis, and occult blood tests may or may not have an automated readout device for connectivity. In these cases, manual entry may still be required. A DMS that enables manual configuration and entry would also allow for comprehensive data management.

Uni-directional connectivity is when data transfers from the POCT device to the DMS (e.g., QC and patient results), but information cannot transfer from the DMS to the POCT device (e.g., updating valid operators, QC data, and reagent lot numbers).[30] Thus, bi-directional connectivity is preferred.[30] Additionally, POCT devices interfaced to the ADT system enable positive patient identification at the bedside, where the device can display patient demographic information when the patient wristband barcode is scanned. Positive patient identification is extremely important when discussing the connectivity of POCT devices, as test results are transmitted often immediately. Patient identification errors can cause POCT results to be recorded to the wrong patient’s chart and may include entry errors; barcode scanning failures (illegible barcodes); barcode substitutions (multiple wristbands, scanning other barcodes, etc.); and use of inactive, incorrect, and unregistered account numbers.[33] A study-based audit comparing pre- and post-implementation of POC glucose meter connectivity demonstrated that 18% of POC glucose results were identified to have an error in patient identification.[34] The use of a DMS can detect unusual digit patterns to patient’s medical record numbers, hold the corresponding POCT result in the DMS, and alert the POCT coordinator for investigation and resolution.[33][34][35] Similarly, for unregistered patients, a set of temporary codes can be assigned for automatic holding in the DMS until the patient is registered.[30]


Abbreviations

DMS: data management system

EMR: electronic medical record

HIS: hospital information system

LIS: laboratory information system

POCT: point-of-care testing

TAT: turnaround time

QC: quality control

References

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  2. ↑ Füzéry, A.K.; Bobyak, J.; Chang, E. et al. (2019). "Challenges of Point-of-Care Testing in Ambulances". Journal of Applied Laboratory Medicine 4 (2): 293–95. doi:10.1373/jalm.2019.029439. PMID 31639680. 
  3. ↑ Albasri, A.; Van den Bruel, A.; Hayward, G. et al. (2020). "Impact of point-of-care tests in community pharmacies: A systematic review and meta-analysis". BMJ Open 10 (5): e034298. doi:10.1136/bmjopen-2019-034298. PMC PMC7232628. PMID 32414821. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7232628. 
  4. ↑ 4.0 4.1 Pecoraro, V.; Germagnoli, L.; Banfi, G. (2014). "Point-of-care testing: Where is the evidence? A systematic survey". Clinical Chemistry and Laboratory Medicine 52 (3): 313–24. doi:10.1515/cclm-2013-0386. PMID 24038608. 
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  6. ↑ 6.0 6.1 6.2 Quinn, A.D.; Dixon, D.; Meenan, B.J. (2016). "Barriers to hospital-based clinical adoption of point-of-care testing (POCT): A systematic narrative review". Critical Reviews in Clinical Laboratory Sciences 53 (1): 1–12. doi:10.3109/10408363.2015.1054984. PMID 26292075. 
  7. ↑ Heneghan, C.J.; Garcia-Alamino, J.M.; Spencer, E.A. et al. (2016). "Self-monitoring and self-management of oral anticoagulation". Cochrane Database of Systematic Reviews 7: CD003839. doi:10.1002/14651858.CD003839.pub3. PMID 27378324. 
  8. ↑ Aabenhus, R.; Jensen, J.-U.S.; Jørgensen, K.J. et al. (2014). "Biomarkers as point-of-care tests to guide prescription of antibiotics in patients with acute respiratory infections in primary care". Cochrane Database of Systematic Reviews 6 (11): CD010130. doi:10.1002/14651858.CD010130.pub2. PMID 25374293. 
  9. ↑ Sharma, P.; Scotland, G.; Cruickshank, M. et al. (2015). "The clinical effectiveness and cost-effectiveness of point-of-care tests (CoaguChek system, INRatio2 PT/INR monitor and ProTime Microcoagulation system) for the self-monitoring of the coagulation status of people receiving long-term vitamin K antagonist therapy, compared with standard UK practice: Systematic review and economic evaluation". Health Technology Assessment 19 (48): 1-172. doi:10.3310/hta19480. PMC PMC4780913. PMID 26138549. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4780913. 
  10. ↑ McTaggart, M.P.; Newall, R.G.; Hirst, J.A. et al. (2014). "Diagnostic accuracy of point-of-care tests for detecting albuminuria: A systematic review and meta-analysis". Annals of Internal Medicine 160 (8): 550–7. doi:10.7326/M13-2331. PMID 24733196. 
  11. ↑ Shivkumar, S.; Peeling, R.; Jafari, Y. et al. (2012). "Accuracy of rapid and point-of-care screening tests for hepatitis C: A systematic review and meta-analysis". Annals of Internal Medicine 157 (8): 558–66. doi:10.7326/0003-4819-157-8-201210160-00006. PMID 23070489. 
  12. ↑ Al-Ansary, L.; Farmer, A.; Hirst, J. et al. (2011). "Point-of-care testing for Hb A1c in the management of diabetes: A systematic review and metaanalysis". Clinical Chemistry 57 (4): 568–76. doi:10.1373/clinchem.2010.157586. PMID 21368238. 
  13. ↑ Gialamas, A.; St. John, A.; Laurence, C.O. et al. (2010). "Point-of-care testing for patients with diabetes, hyperlipidaemia or coagulation disorders in the general practice setting: A systematic review". Family Practice 27 (1): 17–24. doi:10.1093/fampra/cmp084. PMID 19969524. 
  14. ↑ Price, C.P.; Smith, I.; Van den Bruel, A. (2018). "Improving the quality of point-of-care testing". Family Practice 35 (4): 358–64. doi:10.1093/fampra/cmx120. PMID 29253125. 
  15. ↑ 15.0 15.1 15.2 Nichols, J.H.; Alter, D.; Chen, Y. et al. (2020). "AACC Guidance Document on Management of Point-of-Care Testing". Journal of Applied Laboratory Medicine 5 (4): 762–87. doi:10.1093/jalm/jfaa059. PMID 32496555. 
  16. ↑ 16.0 16.1 Yip, P.M.; Venner, A.A.; Shea, J. et al. (2018). "Point-of-care testing: A position statement from the Canadian Society of Clinical Chemists". Clinical Biochemistry 53: 156–59. doi:10.1016/j.clinbiochem.2018.01.015. PMID 29395090. 
  17. ↑ Nichols, J.H.; Christenson, R.H.; Clarke, W. et al. (2007). "Executive summary. The National Academy of Clinical Biochemistry Laboratory Medicine Practice Guideline: Evidence-based practice for point-of-care testing". Clinica Chimica Acta 379 (1–2): 14–28. doi:10.1016/j.cca.2006.12.025. PMID 17270169. 
  18. ↑ 18.0 18.1 International Federation of Clinical Chemistry and Laboratory Medicine (20 March 2014). "Thinking of Introducing PoCT - Things to Consider" (PDF). pp. 19. http://www.ifcc.org/media/253664/2014%2003%2020%20Thinking%20of%20Introducing%20PoCT%20-%20Things%20to%20Consider.pdf. 
  19. ↑ Clinical and Laboratory Standards Institute (2016). POCT04 - Essential Tools for Implementation and Management of a Point-of-Care Testing Program (3rd ed.). pp. 74. ISBN 1562389386. https://clsi.org/standards/products/point-of-care-testing/documents/poct04/. 
  20. ↑ Ehrmeyer, S.S.; Laessig, R.H. (2009). "Regulatory compliance for point-of-care testing: 2009 United States perspective". Clinics in Laboratory Medicine 29 (3): 463–78. doi:10.1016/j.cll.2009.06.012. PMID 19840680. 
  21. ↑ Clinical and Laboratory Standards Institute (2010). POCT09 - Selection Criteria for Point-of-Care Testing Devices (1st ed.). pp. 72. ISBN 1562387227. https://clsi.org/standards/products/point-of-care-testing/documents/poct09/. 
  22. ↑ Clinical and Laboratory Standards Institute (2010). POCT07 - Quality Management: Approaches to Reducing Errors at the Point of Care (1st ed.). pp. 68. ISBN 1562387340. https://clsi.org/standards/products/point-of-care-testing/documents/poct07/. 
  23. ↑ 23.0 23.1 23.2 23.3 Kim, J.Y.; Lewandrowski, K. (2009). "Point-of-care testing informatics". Clinics in Laboratory Medicine 29 (3): 449–61. doi:10.1016/j.cll.2009.06.014. PMID 19840679. 
  24. ↑ 24.0 24.1 International Organization for Standardization (November 2016). "ISO 22870:2016 Point-of-care testing (POCT) — Requirements for quality and competence". https://www.iso.org/standard/71119.html. 
  25. ↑ 25.0 25.1 Carraro, P.; Plebani, M. (2009). "Post-analytical errors with portable glucose meters in the hospital setting". Clinica Chimica Acta 404 (1): 65–7. doi:10.1016/j.cca.2009.03.013. PMID 19298797. 
  26. ↑ 26.0 26.1 Mays, J.A.; Mathias, P.C. (2019). "Measuring the rate of manual transcription error in outpatient point-of-care testing". JAMIA 26 (3): 269–72. doi:10.1093/jamia/ocy170. PMC PMC6351970. PMID 30649499. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6351970. 
  27. ↑ Lee-Lewandrowski, E.; Lewandrowski, K. (2001). "Point-of-care testing. An overview and a look to the future". Clinics in Laboratory Medicine 21 (2): 217–39. PMID 11396080. 
  28. ↑ Dyer, K.; Nichols, J.H.; Taylor, M. et al. (2001). "Development of a universal connectivity and data management system". Critical Care Nursing Quarterly 24 (1): 25–38. doi:10.1097/00002727-200105000-00006. PMID 11868692. 
  29. ↑ Clinical and Laboratory Standards Institute (2006). POCT01 - Point-of-Care Connectivity (2nd ed.). pp. 308. ISBN 1562386166. https://clsi.org/standards/products/point-of-care-testing/documents/poct01/. 
  30. ↑ 30.0 30.1 30.2 30.3 Shaw, J.L.V. (2015). "Practical challenges related to point of care testing". Practical Laboratory Medicine 4: 22–9. doi:10.1016/j.plabm.2015.12.002. PMC PMC5574506. PMID 28856189. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5574506. 
  31. ↑ 31.0 31.1 31.2 Gregory, K.; Lewandrowski, K. (2009). "Management of a point-of-care testing program". Clinics in Laboratory Medicine 29 (3): 433–8. doi:10.1016/j.cll.2009.06.006. PMID 19840678. 
  32. ↑ Halpern, N.A.; Brentjens, T. (1999). "Point of care testing informatics. The critical care-hospital interface". Critical Care Clinics 15 (3): 577–91. doi:10.1016/s0749-0704(05)70072-5. PMID 10442264. 
  33. ↑ 33.0 33.1 Alreja, G.; Setia, N.; Nichols, J. et al. (2011). "Reducing patient identification errors related to glucose point-of-care testing". Journal of Pathology Informatics 2: 22. doi:10.4103/2153-3539.80718. PMC PMC3097526. PMID 21633490. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3097526. 
  34. ↑ 34.0 34.1 Shaw, J.L.V. (2017). "The dark side of point-of-care testing". Clinical Biochemistry 50 (9): 466–7. doi:10.1016/j.clinbiochem.2017.03.003. PMID 28283329. 
  35. ↑ Nichols, J.H.; Bartholomew, C.; Brunton, M. et al. (2004). "Reducing medical errors through barcoding at the point of care". Clinical Leadership & Management Review 18 (6): 328-34. PMID 15597554. 

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. Grammar was cleaned up for smoother reading. In some cases important information was missing from the references, and that information was added.

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