Abstract
Objectives
Patients referred to general internal medicine (GIM) outpatient clinics may face a higher risk of diagnostic errors than non-referred patients. This difference in risk is assumed to be due to the differences in diseases and clinical presentations between referred and non-referred patients; however, clinical data regarding this issue are scarce. This study aimed to determine the frequency of diagnostic errors and compare the characteristics of referred and non-referred patients visit GIM outpatient clinics.
Methods
This study included consecutive outpatients who visited the GIM outpatient clinic at a university hospital, with or without referral. Data on age, sex, chief complaints, referral origin, and final diagnosis were collected from medical records. The Revised Safer Dx Instrument was used to detect diagnostic errors.
Results
Data from 534 referred and 599 non-referred patients were analyzed. The diagnostic error rate was higher in the referral group than that in the non-referral group (2.2 % vs. 0.5 %, p=0.01). The prevalence of abnormal test results and sensory disturbances was higher in the chief complaints, and the prevalence of musculoskeletal system disorders, connective tissue diseases, and neoplasms was higher in the final diagnoses of referred patients compared with non-referred patients. Among referred patients with diagnostic errors, abnormal test results and sensory disturbances were the two most common chief complaints, whereas neoplasia was the most common final diagnosis. Problems with data integration and interpretation were found to be the most common factors contributing to diagnostic errors.
Conclusions
Paying more attention to patients with abnormal test results and sensory disturbances and considering a higher pre-test probability for neoplasms may prevent diagnostic errors in patients referred to GIM outpatient clinics.
-
Research ethics: The Institutional Ethics Committee of Dokkyo Medical University Hospital approved this study (R45-15J) and waived the requirement for written informed consent from the patients because we used an opt-out method.
-
Informed consent: Not applicable.
-
Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Competing interests: The authors state no conflict of interest.
-
Research funding: None declared.
-
Data availability: The raw data can be obtained on request from the corresponding author.
References
1. Balogh, EP, Miller, BT, Ball, JR, editors. Committee on diagnostic error in health care, board on health care services, Institute of Medicine, the National Academies of Sciences, Engineering, and Medicine. In: Improving diagnosis in health care; 2015:21794 p. Published Online.10.17226/21794Search in Google Scholar PubMed
2. van den Berge, K, Mamede, S. Cognitive diagnostic error in internal medicine. Eur J Intern Med 2013;24:525–9. https://doi.org/10.1016/j.ejim.2013.03.006.Search in Google Scholar PubMed
3. Wijesekera, TP, Sanders, L, Windish, DM. Reflections on diagnosis and diagnostic errors: a survey of internal medicine resident and attending physicians. J Gen Intern Med 2020;35:614–5. https://doi.org/10.1007/s11606-019-05045-z.Search in Google Scholar PubMed PubMed Central
4. Regina, ML, Vecchié, A, Bonaventura, A, Prisco, D. Patient safety in internal medicine. In: Donaldson, L, Ricciardi, W, Sheridan, S, Tartaglia, R, editors. Textbook of patient safety and clinical risk management [Internet]. Cham (CH): Springer; 2021. [Chapter 17]. 2020 dec 15.10.1007/978-3-030-59403-9_17Search in Google Scholar PubMed
5. Singh, H, Graber, ML. Improving diagnosis in health care-the next imperative for patient safety. N Engl J Med 2015;373:2493–5. https://doi.org/10.1056/nejmp1512241.Search in Google Scholar PubMed
6. Singh, H, Meyer, AN, 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
7. Sakamoto, H, Rahman, M, Nomura, S, Okamoto, E, Koike, S. 2018. Japan health system review. In: Health systems in transition, 8(1), World Health Organization. Regional Office for South-East Asia. https://iris.who.int/handle/10665/259941.Search in Google Scholar
8. Yokose, M, Harada, Y, Hanai, S, Tomiyama, S, Shimizu, T. Outcomes of general internal medicine consultations for diagnosis from specialists in a tertiary hospital: a retrospective observational study. Int J Gen Med 2022;15:7209–17. https://doi.org/10.2147/ijgm.s378146.Search in Google Scholar PubMed PubMed Central
9. Watari, T. Malpractice claims of internal medicine involving diagnostic and system errors in Japan. Intern Med 2021;60:2919–25. https://doi.org/10.2169/internalmedicine.6652-20.Search in Google Scholar PubMed PubMed Central
10. Watari, T, Tokuda, Y, Mitsuhashi, S, Otuki, K, Kono, K, Nagai, N, et al.. Factors and impact of physicians’ diagnostic errors in malpractice claims in Japan. PLoS One 2020;15:e0237145. https://doi.org/10.1371/journal.pone.0237145.Search in Google Scholar PubMed PubMed Central
11. Watari, T, Gupta, A, Amano, Y, Tokuda, Y. Japanese internists’ most memorable diagnostic error cases: a self-reflection survey. Intern Med 2024;63:221–9. https://doi.org/10.2169/internalmedicine.1494-22.Search in Google Scholar PubMed PubMed Central
12. Harada, Y, Otaka, Y, Katsukura, S, Shimizu, T. Effect of contextual factors on the prevalence of diagnostic errors among patients managed by physicians of the same specialty: a single-centre retrospective observational study. BMJ Qual Saf 2024;33:386–94. https://doi.org/10.1136/bmjqs-2022-015436.Search in Google Scholar PubMed
13. Schiff, GD, Hasan, O, Kim, S, Abrams, R, Cosby, K, Lambert, BL, et al.. Diagnostic error in medicine: analysis of 583 physician-reported errors. Arch Intern Med 2009;16:1881–7. https://doi.org/10.1001/archinternmed.2009.333.Search in Google Scholar PubMed
14. Graber, ML, Franklin, N, Gordon, R. Diagnostic error in internal medicine. Arch Intern Med 2005;165:1493–9. https://doi.org/10.1001/archinte.165.13.1493.Search in Google Scholar PubMed
15. Singh, H, Weingart, SN. Diagnostic errors in ambulatory care: dimensions and preventive strategies. Adv Health Sci Educ Theory Pract 2009;14:57–61. https://doi.org/10.1007/s10459-009-9177-z.Search in Google Scholar PubMed PubMed Central
16. Wilson, E, Seifert, C, Durning, SJ, Torre, D, Daniel, M. Distributed cognition: interactions between individuals and artifacts. Diagnosis (Berl) 2020;7:343–4. https://doi.org/10.1515/dx-2020-0012.Search in Google Scholar PubMed
17. van den Berge, K, Mamede, S, van Gog, T, Romijn, JA, van Guldener, C, van Saase, JL, et al.. Accepting diagnostic suggestions by residents: a potential cause of diagnostic error in medicine. Teach Learn Med 2012;24:149–54. https://doi.org/10.1080/10401334.2012.664970.Search in Google Scholar PubMed
18. Staal, J, Speelman, M, Brand, R, Alsma, J, Zwaan, L. Does a suggested diagnosis in a general practitioners’ referral question impact diagnostic reasoning: an experimental study. BMC Med Educ 2022;22:256. https://doi.org/10.1186/s12909-022-03325-7.Search in Google Scholar PubMed PubMed Central
19. Chao, S, Lotfi, J, Lin, B, Shaw, J, Jhandi, S, Mahoney, M, et al.. Diagnostic journeys: characterization of patients and diagnostic outcomes from an academic second opinion clinic. Diagnosis 2022;9:340–7. https://doi.org/10.1515/dx-2022-0029.Search in Google Scholar PubMed
20. Kajiwara, N, Hayashi, K, Misago, M, Murakami, S, Ueoka, T. First-visit patients without a referral to the Department of Internal Medicine at a medium-sized acute care hospital in Japan: an observational study. Int J Gen Med 2017;10:335–45. https://doi.org/10.2147/ijgm.s146830.Search in Google Scholar
21. Takeshima, T, Kumada, M, Mise, J, Ishikawa, Y, Yoshizawa, H, Nakamura, T, et al.. Reasons for encounter and diagnoses of new outpatients at a small community hospital in Japan: an observational study. Int J Gen Med 2014;7:259–69. https://doi.org/10.2147/ijgm.s62384.Search in Google Scholar PubMed PubMed Central
22. Burger, PM, Westerink, J, Vrijsen, BEL. Outcomes of second opinions in general internal medicine. PLoS One 2020;15:e0236048. https://doi.org/10.1371/journal.pone.0236048.Search in Google Scholar PubMed PubMed Central
23. Al-Mutairi, A, Meyer, AN, Thomas, EJ, Etchegaray, JM, Roy, KM, Davalos, MC, et al.. Accuracy of the safer Dx instrument to identify diagnostic errors in primary care. J Gen Intern Med 2016;31:602–8. https://doi.org/10.1007/s11606-016-3601-x.Search in Google Scholar PubMed PubMed Central
24. Singh, H, Khanna, A, Spitzmueller, C, Meyer, AND. Recommendations for using the Revised Safer Dx Instrument to help measure and improve diagnostic safety. Diagnosis 2019;6:315–23. https://doi.org/10.1515/dx-2019-0012.Search in Google Scholar PubMed
25. Lam, D, Dominguez, F, Leonard, J, Wiersma, A, Grubenhoff, JA. Use of e-triggers to identify diagnostic errors in the paediatric ED. BMJ Qual Saf 2022;31:735–43. https://doi.org/10.1136/bmjqs-2021-013683.Search in Google Scholar PubMed
26. Kawamura, R, Harada, Y, Sugimoto, S, Nagase, Y, Katsukura, S, Shimizu, T. Incidence of diagnostic errors among unexpectedly hospitalized patients using an automated medical history-taking system with a differential diagnosis generator: retrospective observational study. JMIR Med Inform 2022;10:e35225. https://doi.org/10.2196/35225.Search in Google Scholar PubMed PubMed Central
27. Cifra, CL, Custer, JW, Smith, CM, Smith, KA, Bagdure, DN, Bloxham, J, et al.. Prevalence and characteristics of diagnostic error in pediatric critical care: a multicenter study. Crit Care Med 2023;51:1492–501. https://doi.org/10.1097/ccm.0000000000005942.Search in Google Scholar
28. Brady, PW, Ruddy, RM, Ehrhardt, J, Corathers, SD, Kirkendall, ES, Walsh, KE. Assessing the Revised Safer Dx Instrument® in the understanding of ambulatory system design changes for type 1 diabetes and autism spectrum disorder in pediatrics. Diagnosis 2024;11:266–72. https://doi.org/10.1515/dx-2023-0166.Search in Google Scholar PubMed PubMed Central
29. Gwet, KL. Handbook of inter-rater reliability: the definitive guide to measuring the extent of agreement among raters, 4th ed. Gaithersburg, Md: Advanced Analytics, LLC; 2014.Search in Google Scholar
30. Landis, JR, Koch, GG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159–74. https://doi.org/10.2307/2529310.Search in Google Scholar
31. Cheraghi-Sohi, S, Holland, F, Singh, H, Danczak, A, Esmail, A, Morris, RL, et al.. Incidence, origins and avoidable harm of missed opportunities in diagnosis: longitudinal patient record review in 21 English general practices. BMJ Qual Saf 2021;30:977–85. https://doi.org/10.1136/bmjqs-2020-012594.Search in Google Scholar PubMed PubMed Central
32. Khoo, EM, Lee, WK, Sararaks, S, Abdul Samad, A, Liew, SM, Cheong, AT, et al.. Medical errors in primary care clinics--a cross sectional study. BMC Fam Pract 2012;13:127. https://doi.org/10.1186/1471-2296-13-127.Search in Google Scholar PubMed PubMed Central
33. Aoki, T, Watanuki, S. Multimorbidity and patient-reported diagnostic errors in the primary care setting: multicentre cross-sectional study in Japan. BMJ Open 2020;10:e039040. https://doi.org/10.1136/bmjopen-2020-039040.Search in Google Scholar PubMed PubMed Central
34. Cifra, CL, Custer, JW, Singh, H, Fackler, JC. Diagnostic errors in pediatric critical care: a systematic review. Pediatr Crit Care Med 2021;22:701–12. https://doi.org/10.1097/pcc.0000000000002735.Search in Google Scholar PubMed PubMed Central
35. Sherbino, J, Sibbald, M, Norman, G, LoGiudice, A, Keuhl, A, Lee, M, et al.. Crowdsourcing a diagnosis? Exploring the accuracy of the size and type of group diagnosis: an experimental study. BMJ Qual Saf 2024. https://doi.org/10.1136/bmjqs-2023-016695 [Epub ahead of print].Search in Google Scholar PubMed
36. Barnett, ML, Boddupalli, D, Nundy, S, Bates, DW. Comparative accuracy of diagnosis by collective intelligence of multiple physicians vs individual physicians. JAMA Netw Open 2019;2:e190096. https://doi.org/10.1001/jamanetworkopen.2019.0096.Search in Google Scholar PubMed PubMed Central
37. Khoong, EC, Nouri, SS, Tuot, DS, Nundy, S, Fontil, V, Sarkar, U. Comparison of diagnostic recommendations from individual physicians versus the collective intelligence of multiple physicians in ambulatory cases referred for specialist consultation. Med Decis Making 2022;42:293–302. https://doi.org/10.1177/0272989x211031209.Search in Google Scholar PubMed PubMed Central
38. 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
© 2024 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Editorial
- Should APTT become part of thrombophilia screening?
- Review
- n-3 fatty acids and the risk of atrial fibrillation, review
- Guidelines and Recommendations
- Root cause analysis of cases involving diagnosis
- Opinion Papers
- What is diagnostic safety? A review of safety science paradigms and rethinking paths to improving diagnosis
- Interprofessional clinical reasoning education
- Original Articles
- Quality of heart failure registration in primary care: observations from 1 million electronic health records in the Amsterdam Metropolitan Area
- Typology of solutions addressing diagnostic disparities: gaps and opportunities
- Diagnostic errors and characteristics of patients seen at a general internal medicine outpatient clinic with a referral for diagnosis
- Cost-benefit considerations of the biased diagnostician
- Delayed diagnosis of new onset pediatric diabetes leading to diabetic ketoacidosis: a retrospective cohort study
- Monocyte distribution width (MDW) kinetic for monitoring sepsis in intensive care unit
- Are shortened aPTT values always to be attributed only to preanalytical problems?
- External Quality Assessment (EQA) scheme for serological diagnostic test for SARS-CoV-2 detection in Sicily Region (Italy), in the period 2020–2022
- Recent mortality rates due to complications of medical and surgical care in the US
- Short Communication
- The potential, limitations, and future of diagnostics enhanced by generative artificial intelligence
- Case Report – Lessons in Clinical Reasoning
- Lessons in clinical reasoning – pitfalls, myths, and pearls: a case of persistent dysphagia and patient partnership
- Letters to the Editor
- The ‘curse of knowledge’: when medical expertise can sometimes be a liability
- A new approach for identifying innate immune defects
Articles in the same Issue
- Frontmatter
- Editorial
- Should APTT become part of thrombophilia screening?
- Review
- n-3 fatty acids and the risk of atrial fibrillation, review
- Guidelines and Recommendations
- Root cause analysis of cases involving diagnosis
- Opinion Papers
- What is diagnostic safety? A review of safety science paradigms and rethinking paths to improving diagnosis
- Interprofessional clinical reasoning education
- Original Articles
- Quality of heart failure registration in primary care: observations from 1 million electronic health records in the Amsterdam Metropolitan Area
- Typology of solutions addressing diagnostic disparities: gaps and opportunities
- Diagnostic errors and characteristics of patients seen at a general internal medicine outpatient clinic with a referral for diagnosis
- Cost-benefit considerations of the biased diagnostician
- Delayed diagnosis of new onset pediatric diabetes leading to diabetic ketoacidosis: a retrospective cohort study
- Monocyte distribution width (MDW) kinetic for monitoring sepsis in intensive care unit
- Are shortened aPTT values always to be attributed only to preanalytical problems?
- External Quality Assessment (EQA) scheme for serological diagnostic test for SARS-CoV-2 detection in Sicily Region (Italy), in the period 2020–2022
- Recent mortality rates due to complications of medical and surgical care in the US
- Short Communication
- The potential, limitations, and future of diagnostics enhanced by generative artificial intelligence
- Case Report – Lessons in Clinical Reasoning
- Lessons in clinical reasoning – pitfalls, myths, and pearls: a case of persistent dysphagia and patient partnership
- Letters to the Editor
- The ‘curse of knowledge’: when medical expertise can sometimes be a liability
- A new approach for identifying innate immune defects