BACKGROUND: Diagnostic errors are an underrecognized source of patient harm, and cardiovascular disease can be challenging to diagnose in the ambulatory setting. Although malpractice data can inform diagnostic error reduction efforts, no studies have examined outpatient cardiovascular malpractice cases in depth. A study was conducted to examine the characteristics of outpatient cardiovascular malpractice cases brought against general medicine practitioners.
METHODS: Some 3,407 closed malpractice claims were analyzed in outpatient general medicine from CRICO Strategies' Comparative Benchmarking System database-the largest detailed database of paid and unpaid malpractice in the world-and multivariate models were created to determine the factors that predicted case outcomes.
RESULTS: Among the 153 patients in cardiovascular malpractice cases for whom patient comorbidities were coded, the majority (63%) had at least one traditional cardiac risk factor, such as diabetes, tobacco use, or previous cardiovascular disease. Cardiovascular malpractice cases were more likely to involve an allegation of error in diagnosis (75% vs. 47%, p <0.0001), have high clinical severity (86% vs. 49%, p <0.0001) and result in death (75% vs. 27%, p <0.0001), as compared to noncardiovascular cases. Initial diagnoses of nonspecific chest pain and mimics of cardiovascular pain (for example, esophageal disease) were common and independently increased the likelihood of a claim resulting in a payment (p <0.01).
CONCLUSION: Cardiovascular malpractice cases against outpatient general medicine physicians mostly occur in patients with conventional risk factors for coronary artery disease and are often diagnosed with common mimics of cardiovascular pain. These findings suggest that these patients may be high-yield targets for preventing diagnostic errors in the ambulatory setting.
}, year = {2017}, journal = {Jt Comm J Qual Patient Saf}, volume = {43}, pages = {508-516}, month = {12/2017}, issn = {1553-7250}, doi = {10.1016/j.jcjq.2017.05.001}, language = {eng}, }