Abstract
Objectives
The National Academy of Medicine identified diagnostic error as a pressing public health concern and defined failure to effectively communicate the diagnosis to patients as a diagnostic error. Leveraging Patient’s Experience to improve Diagnosis (LEAPED) is a new program for measuring patient-reported diagnostic error. As a first step, we sought to assess the feasibility of using LEAPED after emergency department (ED) discharge.
Methods
We deployed LEAPED using a cohort design at three EDs within one academic health system. We enrolled 59 patients after ED discharge and queried them about their health status and understanding of the explanation for their health problems at 2-weeks, 1-month, and 3-months. We measured response rates and demographic/clinical predictors of patient uptake of LEAPED.
Results
Of those enrolled (n=59), 90% (n=53) responded to the 2-week post-ED discharge questionnaire (1 and 3-month ongoing). Of the six non-responders, one died and three were hospitalized at two weeks. The average age was 50 years (SD 16) and 64% were female; 53% were white and 41% were black. Over a fifth (23%) reported they were not given an explanation of their health problem on leaving the ED, and of those, a fourth (25%) did not have an understanding of what next steps to take after leaving the ED.
Conclusions
Patient uptake of LEAPED was high, suggesting that patient-report may be a feasible method of evaluating the effectiveness of diagnostic communication to patients though further testing in a broader patient population is essential. Future research should determine if LEAPED yields important insights into the quality and safety of diagnostic care.
Funding source: U.S. Department of Health and Human Services
Funding source: National Institutes of Health
Funding source: National Center for Advancing Translational Sciences
Funding source: Institute of Clinical and Translational Research/Institutional Career Development Core/KL2 TR0030
Funding source: National Institute of Nursing Research Hopkins Center
Award Identifier / Grant number: P30NR019083
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Research funding: U.S. Department of Health and Human Services, National Institutes of Health, National Center for Advancing Translational Sciences, Institute of Clinical and Translational Research/Institutional Career Development Core/KL2 TR0030. U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Nursing Research Hopkins Center to Promote Resilience in Persons and families living with multiple chronic conditions (the PROMOTE Center), P30NR019083.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: David Newman-Toker was supported by the Armstrong Institute Center for Diagnostic Excellence, Johns Hopkins University School of Medicine.
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Informed consent: Informed consent was obtained from all individuals included in this study.
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Ethical approval: The Institutional Review Board approved this study (JHM IRB00202800).
References
1. National Academy of Medicine. Improving diagnosis in health Care. Washington, DC: National Academies Press; 2015. Available from: https://iom.nationalacademies.org/Reports/2015/Improving-Diagnosis-in-Healthcare.aspx [Accessed 25 Jun 2020].Search in Google Scholar
2. Berger, ZD, Brito, JP, Ospina, NS, Kannan, S, Hinson, JS, Hess, EP, et al. Patient centred diagnosis: sharing diagnostic decisions with patients in clinical practice. BMJ (Clin Res Ed) 2017;359:j4218. https://doi.org/10.1136/bmj.j4218.Search in Google Scholar PubMed
3. Murphy, DR, Meyer, AND, Sittig, DF, Meeks, DW, Thomas, EJ, Singh, H. Application of electronic trigger tools to identify targets for improving diagnostic safety. BMJ Qual Saf 2019;28:151–9. https://doi.org/10.1136/bmjqs-2018-008086.Search in Google Scholar PubMed PubMed Central
4. Liberman, AL, Newman-Toker, DE. Symptom-Disease Pair Analysis of Diagnostic Error (SPADE): a conceptual framework and methodological approach for unearthing misdiagnosis-related harms using big data. BMJ Qual Saf 2018;27:557–66. https://doi.org/10.1136/bmjqs-2017-007032.Search in Google Scholar PubMed PubMed Central
5. Ward, K, Armitage, G. Can patients report patient safety incidents in a hospital setting? a systematic review. BMJ Qual Saf 2012;21:685–700. https://doi.org/10.1136/bmjqs-2011-000213.Search in Google Scholar PubMed
6. Kistler, CE, Walter, LC, Mitchell, CM, Sloane, PD. Patient perceptions of mistakes in ambulatory care. Arch Intern Med 2010;170:1480–7. https://doi.org/10.1001/archinternmed.2010.288.Search in Google Scholar PubMed PubMed Central
7. Harris, PA, Taylor, R, Thielke, R, Payne, J, Gonzalez, N, Conde, JG. Research electronic data capture (REDCap)-a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inf 2009;42:377–81. https://doi.org/10.1016/j.jbi.2008.08.010.Search in Google Scholar PubMed PubMed Central
8. Harris, PA, Taylor, R, Minor, BL, Elliott, V, Fernandez, M, O’Neal, L, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inf 2019;95:103208. https://doi.org/10.1016/j.jbi.2019.103208.Search in Google Scholar PubMed PubMed Central
9. Otte-Trojel, T, Rundall, TG, De Bont, A, Van De Klundert, J, Reed, ME. The organizational dynamics enabling patient portal impacts upon organizational performance and patient health: a qualitative study of Kaiser Permanente. BMC Health Serv Res 2015;15. https://doi.org/10.1186/s12913-015-1208-2.Search in Google Scholar PubMed PubMed Central
10. Mold, F, de Lusignan, S, Sheikh, A, Majeed, A, Wyatt, JC, Quinn, T, et al. Patients’ online access to their electronic health records and linked online services: a systematic review in primary care. Br J Gen Pract 2015;65:e141–51. https://doi.org/10.3399/bjgp15x683941.Search in Google Scholar
11. Singh, H, Meyer, AND, Thomas, EJ. The frequency of diagnostic errors in outpatient care: estimations from three large observational studies involving US adult populations. BMJ Qual Saf 2014;23:727–31. https://doi.org/10.1136/bmjqs-2013-002627.Search in Google Scholar PubMed PubMed Central
12. Graber, ML. The incidence of diagnostic error in medicine. BMJ Qual Saf 2013;22:ii21–7. https://doi.org/10.1136/bmjqs-2012-001615.Search in Google Scholar PubMed PubMed Central
13. Horwitz, LI, Moriarty, JP, Chen, C, Fogerty, RL, Brewster, UC, Kanade, S, et al. Quality of discharge practices and patient understanding at an academic medical center. JAMA Intern Med 2013;173:1715–22. https://doi.org/10.1001/jamainternmed.2013.9318.Search in Google Scholar PubMed PubMed Central
14. Miller, HN, Gleason, KT, Juraschek, SP, Plante, TB, Lewis-Land, C, Woods, B, et al. Electronic medical record-based cohort selection and direct-to-patient, targeted recruitment: early efficacy and lessons learned. J Am Med Inf Assoc 2019. https://doi.org/10.1093/jamia/ocz168.Search in Google Scholar PubMed PubMed Central
15. Powell, KR. Patient-perceived facilitators of and barriers to electronic portal use. CIN Comput Inform Nurs 2017;35:565–73. https://doi.org/10.1097/CIN.0000000000000377.Search in Google Scholar PubMed
16. Antonio, MG, Petrovskaya, O, Lau, F. Is research on patient portals attuned to health equity? a scoping review. J Am Med Inform Ass 2019;26:871–83. https://doi.org/10.1093/jamia/ocz054.Search in Google Scholar PubMed PubMed Central
17. Singh, H, Sittig, DF. Were my diagnosis and treatment correct? No news is not necessarily good news. J Gen Intern Med 2014;29:1087–9. https://doi.org/10.1007/s11606-014-2890-1.Search in Google Scholar PubMed PubMed Central
Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/dx-2020-0014).
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