Development and Usability Testing of the Agency for Healthcare Research and Quality Common Formats to Capture Diagnostic Safety Events

Performance evaluation of ChatGPT in detecting diagnostic errors and their contributing factors: an analysis of 545 case reports of diagnostic errors

BACKGROUND

Manual chart review using validated assessment tools is a standardised methodology for detecting diagnostic errors. However, this requires considerable human resources and time. ChatGPT, a recently developed artificial intelligence chatbot based on a large language model, can effectively classify text based on suitable prompts. Therefore, ChatGPT can assist manual chart reviews in detecting diagnostic errors.

OBJECTIVE

This study aimed to clarify whether ChatGPT could correctly detect diagnostic errors and possible factors contributing to them based on case presentations.

METHODS

We analysed 545 published case reports that included diagnostic errors. We imputed the texts of case presentations and the final diagnoses with some original prompts into ChatGPT (GPT-4) to generate responses, including the judgement of diagnostic errors and contributing factors of diagnostic errors. Factors contributing to diagnostic errors were coded according to the following three taxonomies: Diagnosis Error Evaluation and Research (DEER), Reliable Diagnosis Challenges (RDC) and Generic Diagnostic Pitfalls (GDP). The responses on the contributing factors from ChatGPT were compared with those from physicians.

RESULTS

ChatGPT correctly detected diagnostic errors in 519/545 cases (95%) and coded statistically larger numbers of factors contributing to diagnostic errors per case than physicians: DEER (median 5 vs 1, p<0.001), RDC (median 4 vs 2, p<0.001) and GDP (median 4 vs 1, p<0.001). The most important contributing factors of diagnostic errors coded by ChatGPT were 'failure/delay in considering the diagnosis' (315, 57.8%) in DEER, 'atypical presentation' (365, 67.0%) in RDC, and 'atypical presentation' (264, 48.4%) in GDP.

CONCLUSION

ChatGPT accurately detects diagnostic errors from case presentations. ChatGPT may be more sensitive than manual reviewing in detecting factors contributing to diagnostic errors, especially for 'atypical presentation'.

Developing the Safer Dx Checklist of Ten Safety Recommendations for Health Care Organizations to Address Diagnostic Errors

BACKGROUND

Most health care organizations (HCOs) find diagnostic errors hard to address. The research team developed a checklist (the Safer Dx Checklist) of 10 high-priority safety practices HCOs can use to conduct a proactive risk assessment to address diagnostic error.

METHODS

First, the team identified potential practices based on reviews of recent literature, reports by national and international organizations, and interviews with quality/safety leaders. Then a Delphi panel was conducted, followed by an online expert panel, to prioritize 10 practices. The prioritization process considered impact on safety and feasibility of practice implementation within a one- to three-year time frame. Finally, cognitive walkthroughs were conducted for a face-validity check with end users. The team also conducted content analysis in each step to look for themes that influenced prioritization or checklist implementation.

RESULTS

A total of 71 practices for prioritization were identified through the Delphi panel of 28 experts; 65% of participants reached consensus on 28 practices. A multidisciplinary panel of 10 experts helped prioritize and refine the top 10 practices, which were then developed into a checklist paired with implementation guidance. Practices included themes related to creating organizational and leadership accountability for improving diagnosis, including patients in diagnostic safety work, and developing and implementing organizational infrastructure for measurement and improvement activities. Qualitative analysis revealed insights for implementation. End users at three different HCOs helped refine implementation guidance for the checklist.

CONCLUSION

The researchers identified 10 safety practices to help organizations conduct a proactive, systematic assessment of risks to timely and accurate diagnosis. The Safer Dx Checklist can enable HCOs to begin implementing strategies to address diagnostic error.