Japanese Internists' Most Memorable Diagnostic Error Cases: A Self-reflection Survey

Diagnostic errors in patients admitted directly from new outpatient visits

Objectives

Diagnostic errors frequently represent significant adverse events that can occur in any medical setting, particularly in rushed handovers and constrained timing. Cases that result in emergency hospitalization at the time of the initial outpatient visit are more likely to have complex or serious patient conditions and more detrimental diagnostic errors. Our study investigated diagnostic errors in these under reported situations.

Methods

We conducted a retrospective study using electronic medical record data on patients who were directly admitted to a newly established outpatient clinic at a single university hospital in Japan. Diagnostic errors were assessed independently by two physicians using the Revised Safer Dx instrument. We analyzed patient demographics, symptoms, referrals, and resident doctor (postgraduate-year-1) involvement using logistic regression to compare groups with and without diagnostic error. Additionally, we employed the Diagnostic Error Evaluation and Research (DEER) taxonomy and Generic Diagnostic Pitfalls (GDP) to examine the factors associated with diagnostic errors.

Results

The study included 321 patients, with diagnostic errors identified in 39 cases (12.1 %). Factors contributing to diagnostic errors included the involvement of young residents, male patients, the number of symptoms, and atypical presentation. The most common causes of diagnostic errors were "too much weight given to competing/coexisting diagnosis" as indicated by DEER and "atypical presentation" by GDP.

Conclusions

The frequency of diagnostic errors in this study was higher than those in previous studies of new outpatient visits, underscoring the imperative for heightened scrutiny in cases involving medical residents especially when patients present with multiple or atypical symptoms. This vigilance is crucial to mitigating the risk of diagnostic inaccuracies in these settings. Cases that result in emergency hospitalization at the time of the initial outpatient visit are more likely to have complex or serious patient conditions and more detrimental diagnostic errors.

Diagnostic errors and characteristics of patients seen at a general internal medicine outpatient clinic with a referral for diagnosis

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.

The Big Three diagnostic errors through reflections of Japanese internists

OBJECTIVES

To analyze the Big Three diagnostic errors (malignant neoplasms, cardiovascular diseases, and infectious diseases) through internists' self-reflection on their most memorable diagnostic errors.

METHODS

This secondary analysis study, based on a web-based cross-sectional survey, recruited participants from January 21 to 31, 2019. The participants were asked to recall the most memorable diagnostic error cases in which they were primarily involved. We gathered data on internists' demographics, time to error recognition, and error location. Factors causing diagnostic errors included environmental conditions, information processing, and cognitive bias. Participants scored the significance of each contributing factor on a Likert scale (0, unimportant; 10, extremely important).

RESULTS

The Big Three comprised 54.1 % (n=372) of the 687 cases reviewed. The median physician age was 51.5 years (interquartile range, 42-58 years); 65.6 % of physicians worked in hospital settings. Delayed diagnoses were the most common among malignancies (n=64, 46 %). Diagnostic errors related to malignancy were frequent in general outpatient settings on weekdays and in the mornings and were not identified for several months following the event. Environmental factors often contributed to cardiovascular disease-related errors, which were typically identified within days in emergency departments, during night shifts, and on holidays. Information gathering and interpretation significantly impacted infectious disease diagnoses.

CONCLUSIONS

The Big Three accounted for the majority of cases recalled by Japanese internists. The most relevant contributing factors were different for each of the three categories. Addressing these errors may require a unique approach based on the disease associations.