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Characteristics of Disease-Specific and Generic Diagnostic Pitfalls: A Qualitative Study.
Schiff, Gordon D; Volodarskaya, Mayya; Ruan, Elise; Lim, Andrea; Wright, Adam; Singh, Hardeep; Reyes Nieva, Harry.
Afiliação
  • Schiff GD; Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts.
  • Volodarskaya M; Center for Patient Safety Research and Practice, Brigham and Women's Hospital, Boston, Massachusetts.
  • Ruan E; Center for Primary Care, Harvard Medical School, Boston, Massachusetts.
  • Lim A; Department of Surgery, Rush University Medical Center, Chicago, Illinois.
  • Wright A; Department of Medicine, Montefiore Medical Center, Bronx, New York.
  • Singh H; Department of Internal Medicine, Kaiser Permanente, San Francisco, California.
  • Reyes Nieva H; Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee.
JAMA Netw Open ; 5(1): e2144531, 2022 01 04.
Article em En | MEDLINE | ID: mdl-35061037
ABSTRACT
Importance Progress in understanding and preventing diagnostic errors has been modest. New approaches are needed to help clinicians anticipate and prevent such errors. Delineating recurring diagnostic pitfalls holds potential for conceptual and practical ways for improvement.

Objectives:

To develop the construct and collect examples of "diagnostic pitfalls," defined as clinical situations and scenarios vulnerable to errors that may lead to missed, delayed, or wrong diagnoses. Design, Setting, and

Participants:

This qualitative study used data from January 1, 2004, to December 31, 2016, from retrospective analysis of diagnosis-related patient safety incident reports, closed malpractice claims, and ambulatory morbidity and mortality conferences, as well as specialty focus groups. Data analyses were conducted between January 1, 2017, and December 31, 2019. Main Outcomes and

Measures:

From each data source, potential diagnostic error cases were identified, and the following information was extracted erroneous and correct diagnoses, presenting signs and symptoms, and areas of breakdowns in the diagnostic process (using Diagnosis Error Evaluation and Research and Reliable Diagnosis Challenges taxonomies). From this compilation, examples were collected of disease-specific pitfalls; this list was used to conduct a qualitative analysis of emerging themes to derive a generic taxonomy of diagnostic pitfalls.

Results:

A total of 836 relevant cases were identified among 4325 patient safety incident reports, 403 closed malpractice claims, 24 ambulatory morbidity and mortality conferences, and 355 focus groups responses. From these, 661 disease-specific diagnostic pitfalls were identified. A qualitative review of these disease-specific pitfalls identified 21 generic diagnostic pitfalls categories, which included mistaking one disease for another disease (eg, aortic dissection is misdiagnosed as acute myocardial infarction), failure to appreciate test result limitations, and atypical disease presentations. Conclusions and Relevance Recurring types of pitfalls were identified and collected from diagnostic error cases. Clinicians could benefit from knowledge of both disease-specific and generic cross-cutting pitfalls. Study findings can potentially inform educational and quality improvement efforts to anticipate and prevent future errors.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doença / Erros de Diagnóstico / Assistência Ambulatorial / Imperícia Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Qualitative_research Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: JAMA Netw Open Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doença / Erros de Diagnóstico / Assistência Ambulatorial / Imperícia Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Qualitative_research Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: JAMA Netw Open Ano de publicação: 2022 Tipo de documento: Article
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