Efficiency, efficacy and subjective user satisfaction of alternative laboratory report formats. An investigation on behalf of the Working Group for Postanalytical Phase (WG-POST), of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM).
format
information design
laboratory report
postanalyticsz
Journal
Clinical chemistry and laboratory medicine
ISSN: 1437-4331
Titre abrégé: Clin Chem Lab Med
Pays: Germany
ID NLM: 9806306
Informations de publication
Date de publication:
26 08 2022
26 08 2022
Historique:
received:
21
03
2022
accepted:
31
05
2022
pubmed:
14
6
2022
medline:
5
8
2022
entrez:
13
6
2022
Statut:
epublish
Résumé
Although laboratory result presentation may lead to information overload and subsequent missed or delayed diagnosis, little has been done in the past to improve this post-analytical issue. We aimed to investigate the efficiency, efficacy and user satisfaction of alternative report formats. We redesigned cumulative (sparkline format) and single reports (improved tabular and z-log format) and tested these on 46 physicians, nurses and medical students in comparison to the classical tabular formats, by asking standardized questions on general items on the reports as well as on suspected diagnosis and follow-up treatment or diagnostics. Efficacy remained at a very high level both in the new formats as well as in the classical formats. We found no significant difference in any of the groups. Efficiency improved in all groups when using the sparkline cumulative format and marginally when showing the improved tabular format. When asking medical questions, efficiency and efficacy remained similar between report formats and groups. All alternative reports were subjectively more attractive to the majority of participants. Showing cumulative reports as a graphical display led to faster detection of general information on the report with the same level of correctness. Considering the familiarity bias of the classical single report formats, the borderline-significant improvement of the alternative tabular format and the non-inferiority of the z-log format, suggests that single reports might benefit from some improvements derived from basic information design.
Identifiants
pubmed: 35696446
pii: cclm-2022-0269
doi: 10.1515/cclm-2022-0269
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1356-1364Informations de copyright
© 2022 Walter de Gruyter GmbH, Berlin/Boston.
Références
Wright, MC, Borbolla, D, Waller, RG, Del Fiol, G, Reese, T, Nesbitt, P, et al.. Critical care information display approaches and design frameworks: a systematic review and meta-analysis. J Biomed Inf 2019;100S:100041. https://doi.org/10.1016/j.yjbinx.2019.100041.
Few, S Show me the numbers, 2nd ed. El Dorado Hills, CA, USA: Analytics Press; 2012.
Lenicek Krleza, J, Honovic, L, Vlasic Tanaskovic, J, Podolar, S, Rimac, V, Jokic, A. Post-analytical laboratory work: national recommendations from the working group for post-analytics on behalf of the croatian society of medical biochemistry and laboratory medicine. Biochem Med 2019;29:020502. https://doi.org/10.11613/bm.2019.020502.
National Institutes of Health. DAIDS guidelines for good clinical laboratory practice standards. Bethesda, MD, USA: National Institutes of Health; 2019.
Office of the National Coordinator for Health Information Technology (ONC). The SAFER Guides [Guideline]; 2014. Available from: https://www.healthit.gov/topic/safety/safer-guides.
The Royal College of Pathologists of Australia. Standards for pathology informatics in australia (SPIA) [Guideline]; 2017. Available from: https://www.rcpa.edu.au/Library/Practising-Pathology/PTIS/APUTS-Downloads.
International Organization for Standardization. EN-ISO 15189 - medical laboratories - requirements for quality and competence. Geneva, Switzerland: International Organization for Standardization; 2012.
Lippi, G, Plebani, M. A Six-Sigma approach for comparing diagnostic errors in healthcare-where does laboratory medicine stand? Ann Transl Med 2018;6:180. https://doi.org/10.21037/atm.2018.04.02.
Burches, E, Burches, M. Efficacy, effectiveness and efficiency in the health care: the need for an agreement to clarify its meaning. IJCMPH 2020;4:035. https://doi.org/10.23937/2643-4512/1710035.
Cadamuro, J, Hillarp, A, Unger, A, von Meyer, A, Bauca, JM, Plekhanova, O, et al.. Presentation and formatting of laboratory results: a narrative review on behalf of the european federation of clinical chemistry and laboratory medicine (EFLM) working group “postanalytical phase” (WG-POST). Crit Rev Clin Lab Sci 2021;58:329–53. https://doi.org/10.1080/10408363.2020.1867051.
Makary, MA, Daniel, M. Medical error-the third leading cause of death in the US. BMJ 2016;353:i2139. https://doi.org/10.1136/bmj.i2139.
Slawomirski, L, Auraaen, A, Klazinga, N. The economics of patient safety - strengthening a value-based approach to reducing patient harm at national level: organisation for economic co-operation and development - OECD; 2017. Available from: https://www.oecd.org/els/health-systems/The-economics-of-patient-safety-March-2017.pdf.
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.
Bawden, D, Robinson, L. The dark side of information: overload, anxiety and other paradoxes and pathologies. J Inf Sci 2008;35:180–91. https://doi.org/10.1177/0165551508095781.
Bold, AM. Clinical chemistry reporting. problems and proposals. Lancet 1976;1:951–5. https://doi.org/10.1016/s0140-6736(76)92726-4.
Bauer, DT, Guerlain, S, Brown, PJ. The design and evaluation of a graphical display for laboratory data. J Am Med Inf Assoc 2010;17:416–24. https://doi.org/10.1136/jamia.2009.000505.
Torsvik, T, Lillebo, B, Mikkelsen, G. Presentation of clinical laboratory results: an experimental comparison of four visualization techniques. J Am Med Inf Assoc 2013;20:325–31. https://doi.org/10.1136/amiajnl-2012-001147.
Schaubroeck, J, Muralidhar, K. A meta-analysis of the relative effects of tabular and graphic display formats on decision-making performance. Hum Perform 1991;4:127–45. https://doi.org/10.1207/s15327043hup0402_3.
Senathirajah, Y, Bakken, S, Kaufman, D. The clinician in the driver’s seat: part 1 - a drag/drop user-composable electronic health record platform. J Biomed Inf 2014;52:165–76. https://doi.org/10.1016/j.jbi.2014.09.002.
Senathirajah, Y, Kaufman, D, Bakken, S. The clinician in the driver’s seat: part 2 - intelligent uses of space in a drag/drop user-composable electronic health record. J Biomed Inf 2014;52:177–88. https://doi.org/10.1016/j.jbi.2014.09.008.
Mrazek, C, Lippi, G, Cadamuro, J, Keppel, MH, Felder, TK, Oberkofler, H, et al.. Errors within the total laboratory testing process, from test selection to medical decision-making - a review of causes, consequences, surveillance and solutions. Biochem Med 2020;30:020502. https://doi.org/10.11613/bm.2020.020502.