Electronic Health Record-Related Events in Medical Malpractice Claims

By Mark L. Graber Dana Siegal Heather Riah Doug Johnston Kathy Kenyon

The goal of this project was to obtain additional information on these health IT-related problems, using a mixed methods (qualitative and quantitative) analysis of electronic health record-related harm in cases submitted to a large database of malpractice suits and claims.

Background: There is widespread agreement that the full potential of health information technology (health IT) has not yet been realized and of particular concern are the examples of unintended consequences of health IT that detract from the safety of health care or from the use of health IT itself. The goal of this project was to obtain additional information on these health IT-related problems, using a mixed methods (qualitative and quantitative) analysis of electronic health record-related harm in cases submitted to a large database of malpractice suits and claims.

Methods: Cases submitted to the CRICO claims database and coded during 2012 and 2013 were analyzed. A total of 248 cases (<1%) involving health IT were identified and coded using a proprietary taxonomy that identifies user- and system-related sociotechnical factors. Ambulatory care accounted for most of the cases (146 cases). Cases were most typically filed as a result of an error involving medications (31%), diagnosis (28%), or a complication of treatment (31%). More than 80% of cases involved moderate or severe harm, although lethal cases were less likely in cases from ambulatory settings. Etiologic factors spanned all of the sociotechnical dimensions, and many recurring patterns of error were identified.

Conclusions: Adverse events associated with health IT vulnerabilities can cause extensive harm and are encountered across the continuum of health care settings and sociotechnical factors. The recurring patterns provide valuable lessons that both practicing clinicians and health IT developers could use to reduce the risk of harm in the future. The likelihood of harm seems to relate more to a patient’s particular situation than to any one class of error.