Difference between revisions of "Journal:Design and implementation of a clinical laboratory information system in a low-resource setting"
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==Introduction== | ==Introduction== | ||
[[Laboratory]] testing plays a vital role in clinical decision-making. It is estimated that up to 70% of medical decisions in high-resource healthcare settings are made based on [[clinical laboratory]] test results.<ref name="BecichInform00">{{cite journal |title=Information management: moving from test results to clinical information |journal=Clinical Leadership & Management Review |author=Becich, M.J. |volume=14 |issue=6 |pages=296–300 |year=2000 |pmid=11210218}}</ref><ref name="HallworthThe70_11">{{cite journal |title=The '70% claim': what is the evidence base? |journal=Annals of Clinical Biochemistry |author=Hallworth, M.J. |volume=48 |issue=Pt. 6 |pages=487–8 |year=2011 |doi=10.1258/acb.2011.011177 |pmid=22045648}}</ref> Even though access to clinical laboratory services is comparatively lower in low-resource settings, studies show that clinicians in low-resource settings also make most decisions based on laboratory testing.<ref name="WilsonAccess18">{{cite journal |title=Access to pathology and laboratory medicine services: A crucial gap |journal=Lancet |author=Wilson, M.L.; Fleming, K.A.; Kuti, M.A. et al. |volume=391 |issue=10133 |pages=1927–38 |year=2018 |doi=10.1016/S0140-6736(18)30458-6 |pmid=29550029}}</ref><ref name="MoyoUse15">{{cite journal |title=Use of laboratory test results in patient management by clinicians in Malawi |journal=African Journal of Laboratory Medicine |author=Moyo, K.;, Porter, C.; Chilima, B. et al. |volume=4 |issue=1 |at=277 |year=2015 |doi=10.4102/ajlm.v4i1.277 |pmid=27213139 |pmc=PMC4870597}}</ref> Despite the importance of laboratory test results in clinical decision-making, little effort has been made in low-resource settings to improve the entire laboratory testing process, which starts when the test is first ordered and ends when the results are interpreted and a clinical decision is made.<ref name="PriceLever16">{{cite journal |title=Leveraging the real value of laboratory medicine with the value proposition |journal=Clinical Chimica Acta |author=Price, C.P.; John, A.S.; Christenson, R. et al. |volume=462 |pages=183–6 |year=2016 |doi=10.1016/j.cca.2016.09.006 |pmid=27649855}}</ref> | |||
Laboratory errors include a wide variety of mistakes in the testing process and have no universally accepted definition. We define a laboratory error as any event or mistake that leads to failure to perform a laboratory test, misdiagnosis of a laboratory test, or delayed reporting of laboratory test results. In 2001, it was estimated that laboratory errors accounted for $200 to $400 million in American healthcare expenditures per annum.<ref name="BolognaReduc01">{{cite journal |title=Reducing specimen and medication error with handheld technology |journal=Proceedings of the 2001 HIMSS Annual Conference |author=Bologna, L.; Hardy, G.; Mutter, M. |year=2001}}</ref> Since then, the rate of utilization of laboratory services has increased, making the reduction of laboratory errors a significant opportunity for cost reduction and healthcare [[Quality (business)|quality]] improvement. | |||
Recent studies have tried to categorize errors using phases of the total testing process, which comprises pre-analytical, analytical, and post-analytical phases.<ref name="PlebaniExplor09">{{cite journal |title=Exploring the iceberg of errors in laboratory medicine |journal=Clinical Chimica Acta |author=Plebani, M. |volume=404 |issue=1 |pages=16–23 |year=2009 |doi=10.1016/j.cca.2009.03.022 |pmid=19302995}}</ref> The pre-analytical phase covers all activities from when the test is ordered to when the specimen is delivered to the laboratory for testing. The analytical phase covers the activities involved in the actual testing of the specimen, and the post-analytical phase involves the reporting and interpretation of the laboratory result. Among the phases of the total testing process, it has been observed that most laboratory errors happen outside of the analytical phase.<ref name="PlebaniErrors06">{{cite journal |title=Errors in clinical laboratories or errors in laboratory medicine? |journal=Clinical Chemistry and Laboratory Medicine |author=Plebani, M. |volume=44 |issue=6 |pages=750–9 |year=2006 |doi=10.1515/CCLM.2006.123 |pmid=16729864}}</ref> An example of an error outside the analytical phase is the mislabeling of a specimen, which could happen during the drawing of a sample in the pre-analytical phase. While error rates vary between health facilities, it is estimated that 32% to 75% of all laboratory errors happen in the pre-analytical phase.<ref name="LewinLab08">{{cite web |url=https://www.cdc.gov/labbestpractices/pdfs/2007-status-report-laboratory_medicine_-_a_national_status_report_from_the_lewin_group_updated_2008-9.pdf |format=PDF |title=Laboratory Medicine: A National Status Report |author=The Lewin Group |publisher=Centers for Disease Control and Prevention |date=May 2008}}</ref> Error rates in the analytical phase are estimated in the range of 13% to 32% and in the post-analytical phase in the range of 9% to 31%.<ref name="LewinLab08" /> | |||
Informatics interventions may be useful in reducing such laboratory errors. Examples of such interventions are computer-aided ordering of laboratory tests, barcode labeling of specimen tubes, and automated reporting of laboratory test results. These interventions are often provided using computer systems that allow physicians to order diagnostic tests, medications, and other procedures, commonly referred to as [[Computerized physician order entry|computerized provider order entry]] (CPOE)<ref name="BaronCompu11">{{cite journal |title=Computerized provider order entry in the clinical laboratory |journal=Journal of Pathology Informatics |author=Baron, J.M.; Dighe, A.S. |volume=2 |pages=35 |year=2011 |doi=10.4103/2153-3539.83740 |pmid=21886891 |pmc=PMC3162747}}</ref>, which is often a part of a larger [[electronic health record]] system. However, such comprehensive electronic health record systems have low penetration in low-resource settings where the burden of disease is high and laboratory errors are further exacerbated by poor infrastructure, shortages in trained workforce, and [[information]]al challenges.<ref name="BecichInform00" /><ref name="PetroseAss16">{{cite journal |title=Assessing Perceived Challenges to Laboratory Testing at a Malawian Referral Hospital |journal=American Journal of Tropical Medicine and Hygiene |author=Petrose, L.G.; Fisher, A.M.; Douglas, G.P. et al. |volume=94 |issue=6 |pages=1426-32 |year=2016 |doi=10.4269/ajtmh.15-0867 |pmid=PMC4889768 |pmc=PMC3162747}}</ref> | |||
==References== | ==References== | ||
Revision as of 20:26, 16 March 2020
| Full article title | Design and implementation of a clinical laboratory information system in a low-resource setting |
|---|---|
| Journal | African Journal of Laboratory Medicine |
| Author(s) |
Mtonga, Timothy M.; Choonara, Faheema E.; Espino, Jeremy U.; Kachaje, Chimwemwe; Kapundi, Kenneth; Mengezi, Takondwa E.; Mumba, Soyapi L.; Douglas, Gerald P. |
| Author affiliation(s) | University of Pittsburgh, Kamuzu Central Hospital, Baobab Health Trust |
| Primary contact | Email: tmm113 at pitt dot edu |
| Year published | 2019 |
| Volume and issue | 8(1) |
| Article # | a841 |
| DOI | 10.4102/ajlm.v8i1.841 |
| ISSN | 2225-2010 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://ajlmonline.org/index.php/ajlm/article/view/841/1391 |
| Download | None |
 |
This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
Background: Reducing laboratory errors presents a significant opportunity for both cost reduction and healthcare quality improvement. This is particularly true in low-resource settings where laboratory errors are further exacerbated by poor infrastructure and shortages in a trained workforce. informatics interventions can be used to address some of the sources of laboratory errors.
Objectives: This article describes the development process for a clinical laboratory information system (LIS) that leverages informatics interventions to address problems in the laboratory testing process at a hospital in a low-resource setting.
Methods: We designed interventions using informatics methods for previously identified problems in the laboratory testing process at a clinical laboratory in a low-resource setting. First, we reviewed a pre-existing LIS functionality assessment toolkit and consulted with laboratory personnel. This provided requirements that were developed into a LIS with interventions designed to address the problems that had been identified. We piloted the LIS at the Kamuzu Central Hospital in Lilongwe, Malawi.
Results: We implemented a series of informatics interventions in the form of a LIS to address sources of laboratory errors and support the entire laboratory testing process. Custom hardware was built to support the ordering of laboratory tests and review of laboratory test results.
Conclusion: Our experience highlights the potential of using informatics interventions to address systemic problems in the laboratory testing process in low-resource settings. Implementing these interventions may require innovation of new hardware to address various contextual issues. We strongly encourage thorough testing of such innovations to reduce the risk of failure when implemented.
Keywords: low-resource setting, laboratory testing, laboratory information system, Malawi, informatics interventions
Introduction
Laboratory testing plays a vital role in clinical decision-making. It is estimated that up to 70% of medical decisions in high-resource healthcare settings are made based on clinical laboratory test results.[1][2] Even though access to clinical laboratory services is comparatively lower in low-resource settings, studies show that clinicians in low-resource settings also make most decisions based on laboratory testing.[3][4] Despite the importance of laboratory test results in clinical decision-making, little effort has been made in low-resource settings to improve the entire laboratory testing process, which starts when the test is first ordered and ends when the results are interpreted and a clinical decision is made.[5]
Laboratory errors include a wide variety of mistakes in the testing process and have no universally accepted definition. We define a laboratory error as any event or mistake that leads to failure to perform a laboratory test, misdiagnosis of a laboratory test, or delayed reporting of laboratory test results. In 2001, it was estimated that laboratory errors accounted for $200 to $400 million in American healthcare expenditures per annum.[6] Since then, the rate of utilization of laboratory services has increased, making the reduction of laboratory errors a significant opportunity for cost reduction and healthcare quality improvement.
Recent studies have tried to categorize errors using phases of the total testing process, which comprises pre-analytical, analytical, and post-analytical phases.[7] The pre-analytical phase covers all activities from when the test is ordered to when the specimen is delivered to the laboratory for testing. The analytical phase covers the activities involved in the actual testing of the specimen, and the post-analytical phase involves the reporting and interpretation of the laboratory result. Among the phases of the total testing process, it has been observed that most laboratory errors happen outside of the analytical phase.[8] An example of an error outside the analytical phase is the mislabeling of a specimen, which could happen during the drawing of a sample in the pre-analytical phase. While error rates vary between health facilities, it is estimated that 32% to 75% of all laboratory errors happen in the pre-analytical phase.[9] Error rates in the analytical phase are estimated in the range of 13% to 32% and in the post-analytical phase in the range of 9% to 31%.[9]
Informatics interventions may be useful in reducing such laboratory errors. Examples of such interventions are computer-aided ordering of laboratory tests, barcode labeling of specimen tubes, and automated reporting of laboratory test results. These interventions are often provided using computer systems that allow physicians to order diagnostic tests, medications, and other procedures, commonly referred to as computerized provider order entry (CPOE)[10], which is often a part of a larger electronic health record system. However, such comprehensive electronic health record systems have low penetration in low-resource settings where the burden of disease is high and laboratory errors are further exacerbated by poor infrastructure, shortages in trained workforce, and informational challenges.[1][11]
References
- ↑ 1.0 1.1 Becich, M.J. (2000). "Information management: moving from test results to clinical information". Clinical Leadership & Management Review 14 (6): 296–300. PMID 11210218.
- ↑ Hallworth, M.J. (2011). "The '70% claim': what is the evidence base?". Annals of Clinical Biochemistry 48 (Pt. 6): 487–8. doi:10.1258/acb.2011.011177. PMID 22045648.
- ↑ Wilson, M.L.; Fleming, K.A.; Kuti, M.A. et al. (2018). "Access to pathology and laboratory medicine services: A crucial gap". Lancet 391 (10133): 1927–38. doi:10.1016/S0140-6736(18)30458-6. PMID 29550029.
- ↑ Moyo, K.;, Porter, C.; Chilima, B. et al. (2015). "Use of laboratory test results in patient management by clinicians in Malawi". African Journal of Laboratory Medicine 4 (1): 277. doi:10.4102/ajlm.v4i1.277. PMC PMC4870597. PMID 27213139. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4870597.
- ↑ Price, C.P.; John, A.S.; Christenson, R. et al. (2016). "Leveraging the real value of laboratory medicine with the value proposition". Clinical Chimica Acta 462: 183–6. doi:10.1016/j.cca.2016.09.006. PMID 27649855.
- ↑ Bologna, L.; Hardy, G.; Mutter, M. (2001). "Reducing specimen and medication error with handheld technology". Proceedings of the 2001 HIMSS Annual Conference.
- ↑ Plebani, M. (2009). "Exploring the iceberg of errors in laboratory medicine". Clinical Chimica Acta 404 (1): 16–23. doi:10.1016/j.cca.2009.03.022. PMID 19302995.
- ↑ Plebani, M. (2006). "Errors in clinical laboratories or errors in laboratory medicine?". Clinical Chemistry and Laboratory Medicine 44 (6): 750–9. doi:10.1515/CCLM.2006.123. PMID 16729864.
- ↑ 9.0 9.1 The Lewin Group (May 2008). "Laboratory Medicine: A National Status Report" (PDF). Centers for Disease Control and Prevention. https://www.cdc.gov/labbestpractices/pdfs/2007-status-report-laboratory_medicine_-_a_national_status_report_from_the_lewin_group_updated_2008-9.pdf.
- ↑ Baron, J.M.; Dighe, A.S. (2011). "Computerized provider order entry in the clinical laboratory". Journal of Pathology Informatics 2: 35. doi:10.4103/2153-3539.83740. PMC PMC3162747. PMID 21886891. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3162747.
- ↑ Petrose, L.G.; Fisher, A.M.; Douglas, G.P. et al. (2016). "Assessing Perceived Challenges to Laboratory Testing at a Malawian Referral Hospital". American Journal of Tropical Medicine and Hygiene 94 (6): 1426-32. doi:10.4269/ajtmh.15-0867. PMC PMC3162747. PMID PMC4889768. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3162747.
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. The original reference the author used for "Baldominos et al." was incorrect; the presumably correct citation was added in its place.
