Electronic tools in clinical laboratory diagnostics: key examples, limitations, and value in laboratory medicine
Author:
Bohn Mary Kathryn12, Fabiano Giulia F.1, Adeli Khosrow12
Affiliation:
1. Molecular Medicine and Clinical Biochemistry , The Hospital for Sick Children , Toronto , ON , Canada 2. Laboratory Medicine and Pathobiology , University of Toronto , Toronto , ON , Canada
Abstract
Abstract
Electronic tools in clinical laboratory diagnostics can assist laboratory professionals, clinicians, and patients in medical diagnostic management and laboratory test interpretation. With increasing implementation of electronic health records (EHRs) and laboratory information systems worldwide, there is increasing demand for well-designed and evidence-based electronic resources. Both complex data-driven and simple interpretative electronic healthcare tools are currently available to improve the integration of clinical and laboratory information towards a more patient-centered approach to medicine. Several studies have reported positive clinical impact of electronic healthcare tool implementation in clinical laboratory diagnostics, including in the management of neonatal bilirubinemia, cardiac disease, and nutritional status. As patients have increasing access to their medical laboratory data, it is essential that accessible electronic healthcare tools are evidence-based and user-friendly for individuals of varying digital and medical literacy. Indeed, studies suggest electronic healthcare tool development processes significantly lack the involvement of relevant healthcare professionals and often present misinformation, including erroneous calculation algorithms or inappropriate interpretative recommendations. The current review provides an overview of the utility of available electronic healthcare tools in clinical laboratory diagnostics and critically reviews potential limitations and benefits of their clinical implementation. The Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) online database is also detailed as an example of a pediatric diagnostic tool with widespread global impact.
Publisher
Walter de Gruyter GmbH
Subject
Biochemistry (medical),Clinical Biochemistry,Discrete Mathematics and Combinatorics
Reference24 articles.
1. Singh, H, Spitzmueller, C, Petersen, NJ, Sawhney, MK, Sittig, DF. Information overload and missed test results in electronic health record–based settings. JAMA Intern Med 2013;173:702–4. https://doi.org/10.1001/2013.jamainternmed.61. 2. Mandel, JC, Kreda, DA, Mandl, KD, Kohane, IS, Ramoni, RB. SMART on FHIR: a standards-based, interoperable apps platform for electronic health records. J Am Med Inf Assoc 2016;23:899–908. https://doi.org/10.1093/jamia/ocv189. 3. Kawamoto, K, Kukhareva, P, Shakib, JH, Kramer, H, Rodriguez, S, Warner, PB, et al.. Association of an electronic health record add-on app for neonatal bilirubin management with physician efficiency and care quality. JAMA Netw Open 2019;2:e1915343. https://doi.org/10.1001/jamanetworkopen.2019.15343. 4. Twichell, SA, Rea, CJ, Melvin, P, Capraro, AJ, Mandel, JC, Ferguson, MA, et al.. The effect of an electronic health record-based tool on abnormal pediatric blood pressure recognition. Congenit Heart Dis 2017;12:484. https://doi.org/10.1111/chd.12469. 5. Sinha, S, Jensen, M, Mullin, S, Elkin, PL. Safe opioid prescription: a SMART on FHIR approach to clinical decision support. Online J Public Health Inf 2017;9:193. https://doi.org/10.5210/ojphi.v9i2.8034.
|
|