Reducing risk with clinical decision support: a study of closed malpractice claims.


OBJECTIVE Identify clinical opportunities to intervene to prevent a malpractice event and determine the proportion of malpractice claims potentially preventable by clinical decision support (CDS). MATERIALS AND METHODS Cross-sectional review of closed malpractice claims over seven years from one malpractice insurance company and seven hospitals in the Boston area. For each event, clinical opportunities to intervene to avert the malpractice event and the presence or absence of CDS that might have a role in preventing the event, were assigned by a panel of expert raters. Compensation paid out to resolve a claim (indemnity), was associated with each CDS type. RESULTS Of the 477 closed malpractice cases, 359 (75.3%) were categorized as substantiated and 195 (54%) had at least one opportunity to intervene. Common opportunities to intervene related to performance of procedure, diagnosis, and fall prevention. We identified at least one CDS type for 63% of substantiated claims. The 41 CDS types identified included clinically significant test result alerting, diagnostic decision support and electronic tracking of instruments. Cases with at least one associated intervention accounted for $40.3 million (58.9%) of indemnity. DISCUSSION CDS systems and other forms of health information technology (HIT) are expected to improve quality of care, but their potential to mitigate risk had not previously been quantified. Our results suggest that, in addition to their known benefits for quality and safety, CDS systems within HIT have a potential role in decreasing malpractice payments. CONCLUSION More than half of malpractice events and over $40 million of indemnity were potentially preventable with CDS.

DOI: 10.4338/ACI-2014-02-RA-0018
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@article{Zuccotti2014ReducingRW, title={Reducing risk with clinical decision support: a study of closed malpractice claims.}, author={Gina Zuccotti and Francine L. Maloney and Joshua Feblowitz and Lipika Samal and Luke Sato and Antony Wright}, journal={Applied clinical informatics}, year={2014}, volume={5 3}, pages={746-56} }