Using Performance Data to Identify Preferred Hospitals

Employers and health plans are experimenting with a variety of market-based approaches to improve the value of health care spending. Many have adopted or are contemplating benefit designs with tiered provider networks that differentiate point-of-service copayments based on the cost and quality of the patient's choice of provider (Gabel, Lo Sasso, and Rice 2002; Mays, Claxton, and Strunk 2003; Robinson 2003, Robinson 2004; Rosenthal and Milstein 2004; Steinbrook 2004). Approximately 13 percent of individuals with employer-sponsored insurance—more than 20 million people—were enrolled in plans with tiered provider networks in 2005 (Kaiser Family Foundation and Health Research and Education Trust 2005). To construct tiered benefit designs, payers must choose and reconcile multiple measures of quality and/or cost to determine which providers patients should be encouraged to select. The implications of empirical strategies to combine cost and quality information are unclear, as these two parameters are not consistently and systematically related (Wennberg, Fisher, and Skinner 2002; Fisher et al. 2003). In practice, payers have used a variety of strategies to designate “preferred” providers (typically, but not always, hospitals). Some have done so based only on cost information, others based only on quality information, and still others have attempted to reconcile both cost and quality information into a single index of performance (Robinson 2003). One key question is whether these alternative strategies differ with regard to the set of providers deemed preferred. For example, if the best quality providers are also the least costly as some have asserted,1 then there should be substantial overlap between the highest quality and lowest cost providers, and ratings that combine cost and quality information should not differ much from ratings on either scale. In this research brief, we examine the sensitivity of hospital tiering outcomes (i.e., the set of hospitals identified as preferred) to whether and how quality and cost information is incorporated into the rating system. Assuming that the purpose of tiering hospitals is to increase the value, or benefits net of costs, from health spending, our goal is to illustrate the challenges a payer seeking to steer enrollees to high-value hospitals might face. We simulate several alternative rating schemes using the same information currently relied on by many health plans to designate groups of hospitals as “preferred” or “top tier.” We examine and compare the implications of two extreme strategies—using quality data or cost data alone for hospital tiering—as well as two alternatives that integrate quality and cost ratings. All four approaches that we simulate have commercial analogs (Table 1). For example, Tufts Health Plan in Massachusetts classifies hospitals into tiers by applying separate thresholds for performance on cost and quality indices (e.g., “best” hospitals are those that are both above the threshold for quality and below the threshold for cost) for three categories of care: adult medical/surgical, pediatric, and obstetrical admissions. We were particularly interested in examining the implications of two strategies that combine cost and quality information to identify high-value hospitals: the application of a separate threshold for cost and/or quality and the use of a single index that is the (weighted or unweighted) sum of standardized quality and cost scores. Table 1 Description of Alternative Strategies of Identifying Preferred Hospitals