Development of a Composite Measure of State-Level Malpractice Environment

The U.S. medical malpractice environment has been the subject of much policy and research interest. Despite the volume of research that has been conducted on these topics, measurement of malpractice environment has not been well studied. Researchers have used a number of indicators of malpractice environment, including frequency of malpractice claims within a population (paid claims/capita or per physician) and lawyer density (lawyers/capita) to measure probability of litigation (e.g., Danzon 1986; Chandra, Nundy, and Seabury 2005); malpractice payments per claim or per physician (“claim severity”) to measure expected losses (e.g., Baicker, Fisher, and Chandra 2007); and malpractice premiums to measure both probability and expected magnitude of loss (e.g., Dubay, Kaestner, and Waidmann 1999). State malpractice laws have also been used to proxy for malpractice environments (e.g., Kessler and McClellan 1996). Reforms requiring affidavits of merit or pretrial screening that are intended to reduce claims volume have been used to proxy for claims rates. Caps on noneconomic or total damages, contingency fee limits, and collateral source rules affect the magnitude of payouts and have been used to proxy for claim severity. These indicators have been used as measures of “malpractice environment” (Studdert et al. 2005; Dhankhar, Khan, and Bagga 2007) “malpractice risk” (Dubay, Kaestner, and Waidmann 1999; Kim 2007; Yang et al. 2008) “malpractice pressure” (Kessler and McClellan 1996; Chandra, Nundy, and Seabury 2005), and “malpractice climate” (Matsa 2007), although the literature makes no distinction between these concepts. We define malpractice risk as the expected disutility of a malpractice claim: the probability of experiencing a malpractice loss multiplied by the expected magnitude of loss. Malpractice environment refers to the level of risk inhering in the set of circumstances (e.g., litigiousness), legal structures (e.g., malpractice laws/reforms), and/or market conditions (e.g., availability of underwriters, premiums) in a practice location. Single indicators are useful if research aims to test hypotheses about specific, measurable aspects of malpractice environments, but interest often lies in a broader construct of “malpractice environment.” In these situations, it may be challenging to synthesize results within and across studies if indicators behave inconsistently, if they are inversely correlated, or if the internal consistency of the indicators has not been previously established. From a modeling standpoint, multiple indicators may be too collinear to use simultaneously in a single equation, but including them in separate models may inflate experiment-wise error. For these reasons, a composite measure of malpractice environment may be desirable. Composites may facilitate interpretation and cross-state comparisons. The goal of this research was to use principal component analysis to demonstrate one approach to building a composite measure of state-level malpractice environment to summarize the level of malpractice risk to health care providers in different states, and to explore the validity of this measure.