The effect of reimbursement on the intensity of hospital services.

1. Introduction

We examine how an exogenous change in the average reimbursement of a hospital admission affects within-hospital treatment intensity. Treatment intensity has been shown to be correlated with the quality of a patient's outcome (Picone et al. 2003) and may also be correlated with the non-health-related utility of the patient stay. Both health-related and non-health-related intensity will affect overall patient utility and thus a patient's choice of a hospital. However, we focus on treatment intensity that is specific to the patient and disease, such as number of days in the hospital, the number of procedures or tests, or even whether aspirin was given during the patient's hospital stay. Variation in hospital-level attributes that affect all patient's utility, such as nursing staffing ratios or even waterfalls in the lobby, are not examined. Rather, we analyze changes in clinical inputs that are likely to be correlated with clinical quality.

The exogenous change in reimbursement we study is due to the implementation of the Balanced Budget Act (BBA) of 1997. The BBA lowered hospital reimbursement for Medicare inpatient stays by slowing the update factor for the standard dollar payment rate used in the prospective payment system (PPS). Under PPS, hospitals are paid a set amount per Medicare admission based on a patient's diagnosis rather than being paid on the basis of the intensity of services that a patient actually receives. For more severe cases within a diagnosis group, hospitals do not receive additional reimbursement for marginal services provided during the stay. It is well known that the more severely ill patients will incur costs greater than the reimbursement, whereas less severely ill patients will be profitable. The Medicare system includes outlier payments that are designed to lessen the high-powered incentive to reduce intensity for severely ill patients during the hospital stay. However, the outlier payments related to long length of stay were phased out by 2000 under the BBA, but those based on high charges remain. The U.S. Congress sets the level of Medicare reimbursement each year primarily through the annual inflation update factor. One of the primary provisions of BBA was to hold these updates to values less than actual hospital cost inflation. The effect of the BBA on hospital care is important to study because it is likely indicative of future Medicare policy changes. The hospital industry is unlikely to experience another dramatic change in both marginal and average incentives as it did when Medicare shifted from a cost-based payment system to PPS in 1984. Rather, it is likely that policy changes will result in incremental changes in average reimbursement that were similar to what occurred through the BBA.

2. Background

There is a growing literature of the effect of the BBA on hospitals and patients. Bazzoli et al. (2004) looked at operational decisions pre- and post-BBA, including length of stay. They found that hospitals most susceptible to the provisions reacted to the BBA by cutting full-time equivalent employees per bed and costs per admission. Lindrooth et al. (2005), using an identical measure, found that hospitals most affected by the provisions of the BBA cut nurse staffing relative to less affected hospitals. Volpp et al. (2005) found that the BBA had little effect on the process of care for acute myocardial infarction (AMI) patients.

Although there are only a few very recent studies of BBA effects on hospital care, there have been numerous studies that examined the effects of the shift from retrospective, cost-based Medicare reimbursement to PPS. Frank and Lave (1989) looked at the effect of the shift from cost-based to prospective payment on length of stay of psychiatric patients. They found that length of stay increased for less severe patients but decreased for more severe patients. Such a reaction is consistent with theoretical models of the effect of prospective payment (see, e.g., Hodgkin and McGuire 1994; Ellis and McGuire 1996; Ellis 1998). In this case, quality and amenities are provided to less severe (and more profitable patients) and withheld from the more severe, unprofitable patients. Ellis and McGuire (1996) also looked at a shift from cost-based to prospective payments and decomposed the effect into moral hazard, selection, and practice style effects. The moral hazard effect is a change on the intensive margin, whereas the selection effect reflects changes on the extensive margin. The practice style effect was in the spirit of Dranove (1987), who showed that specialization would occur in response to changes in incentives when there are gains to specialization. Meltzer, Chung, and Basu (2002) examined how competition affected the reaction of hospitals to prospective payment. Their model implied that more severe patients would be differentially affected by the shift. They found that competition led to increased costs before prospective payment and was associated with decreased costs after prospective payment.

Our paper differs from previous research in several ways. First, we examine the effect of a cut in reimbursement across a broadly defined set of diagnostic related groups (DRGs). We take into account that some services are unprofitable, and thus the provision of treatment intensity both pre- and post-BBA will depend on the profitability of the services. This approach is in the spirit of Newhouse (1989), who examined the number of admissions and dumping across DRGs using a PPS profitability index. Second, most of the studies using patient-level data were limited to California. In contrast, we use data from 11 states. Third, the BBA reflected a reduction in the average payment for a stay and affected the marginal payment for an additional day only through the phaseout of length-of-stay outliers. However, reimbursement for charge-based outliers remained intact. Dranove and White (1998) also examined the effect of a change in average reimbursement, but they looked at neither the effect across the distribution intensity nor the effect by disease category.

Our identification strategy is based on the notion that quality, in part, is a public good. Spence (1975) introduced a model where quality is a public good and a firm is not able to offer different levels of quality for different consumers. Thus, the firm is unable to differentiate its product to offer higher quality to high-valuation consumers and lower quality to low-valuation consumers. Rather, the firm would offer a quality that is optimal given the weighted average of each consumer's price, or valuation. Dranove and White (1998) tested this model against an alternative "private good" model of quality in the context of the hospital industry and found that treatment intensity is a public good. Haile and Stein (2002) also showed that quality is a public good using, like Dranove and White, the California inpatient discharge data. They found that heterogeneity in outcomes is due to variations in care across hospitals rather than variations within a hospital. Subsequent researchers have assumed a public good aspect of quality (see, e.g., Gowrisankaran and Town 2001; Tay 2003).

In our application, we identify the estimates by comparing the effect of the BBA on high-Medicare share hospitals to low-Medicare share hospitals. A differential effect of the BBA would exist only if, at least to some extent, treatment intensity is a public good. At high-Medicare share hospitals, a greater portion of total reimbursement emanates from the Medicare program, and thus average reimbursement, when calculated across all patients, falls more sharply for a high-Medicare share hospital than would occur at a low-Medicare share hospital. If treatment intensity was a private good instead of a public good, then a hospital would adapt treatment intensity for Medicare patients regardless of how many Medicare patients they treat. In reality, there may be some aspects of treatment intensity that are public and some that are private. However, it is not possible to econometrically identify private good effects because they are equivalent across hospitals regardless of Medicare share.

There are unobserved trends during our study period of 1996-2000 that might disproportionately affect treatment intensity at high-Medicare versus low-Medicare share hospitals that we do not identify in our analysis. One example is upcoding. Upcoding within a disease category, which was found by Silverman and Skinner (2004) and Dafny (2005), would lead to a lessening effect of the BBA because it would be manifested in higher charges. In our analysis, we examine changes in broadly defined disease categories. Upcoding would lead to higher measured treatment intensity and thus work against our hypothesis. The level of private reimbursement also changed during this period. A report by MedPAC (2002) shows that private payment-to-cost ratios were declining during this period. However, the declines in the MedPAC report were confounded by the inclusion of Medicaid and Medicare health maintenance organizations (HMOs) in the calculation. Regardless of the direction of private reimbursement changes, our findings represent the net effect of payment changes in Medicare on treatment intensity.

3. Conceptual Model

Our model follows Meltzer, Chung, and Basu (2002) and Hodgkin and McGuire (1994). For simplicity, we present the model for a profit-maximizing firm, but the extensions to other objectives are straightforward and covered elsewhere (see, e.g., Hodgkin and McGuire 1994):

[pi] = D([I.sub.s])[p - c(s) - C([I.sub.s])], (1)