Academic journal article Health Care Financing Review

Allocating Practice Expense under the Medicare Fee Schedule

Academic journal article Health Care Financing Review

Allocating Practice Expense under the Medicare Fee Schedule

Article excerpt

INTRODUCTION AND BACKGROUND

Many believe that the physician fees that evolved under the customary, prevailing, and reasonable (CPR) payment methodology were distorted by insurance coverage and other factors. Historical CPR physician fees often greatly exceeded the cost of providing services (including a reasonable return to the physician's work), especially for invasive procedures. This gave inappropriate incentives for the oversupply of services, especially tests and procedures, and in the long run, for oversupply of specialized physicians relative to general practitioners. Historical physician fees have also been regarded as inequitable because the rate of compensation per unit of physician work varied so greatly among services and specialties. Recent reforms of physician payment have emphasized basing fees on resource costs with the twin goals of improving efficiency (i.e., lessening incentives to oversupply certain services) and equity.

A primary goal of the MFS is to bring payments for Medicare physician services more in line with the relative resource cost of providing services. To this end, relative values for physician work were established through surveys of physicians (Becker, Dunn, and Hsaio, 1988). MFS payments for physician work, however, account for only about 54 percent of total MFS payments. The remainder are allocated to practice expenses and malpractice insurance costs. Practice expense--non-physician labor costs, office rental, equipment, supplies, and miscellaneous--accounts for about 41 percent of total payments, and malpractice insurance expense for about 5 percent. The Omnibus Budget and Reconciliation Act of 1989 (OBRA 1989) required the calculation of separate relative value units (RVUs) for practice expense and malpractice in addition to physician work.

Practice expense and malpractice RVUs are established by multiplying historical Medicare allowed charges for services by the percentage of total practice revenues accounted for by these costs. Thus, the MFS is a mixture of a resource-based fee schedule (for physician work) and a charge-based fee schedule (for practice expense and malpractice costs). Any benefits from resource-based fees--less incentive to overprovide some services and underprovide others, for example--are attenuated i n the MFS.

Recognition that roughly one-half of the MFS is charge-based has stimulated interest in developing resource-based methods for allocating practice expense and malpractice costs. The PPRC has devoted considerable attention to delineating the principles of resource-based allocation of non-physician costs. The PPRC has also evaluated the feasibility of collecting the data necessary to implement a resource-based approach. A recently released report describes the PPRC's approach and results of simulations of resource-based fees with data from one multispecialty clinic (Physician Payment Review Commission, 1992a). In addition, the Leonard Davis Institute at the University of Pennsylvania has suggested an approach to allocating practice expense that focuses on minimizing the incentives facing physicians to provide unnecessary services (Pauly and Wedig, 1991).

Neither the PPRC nor the Pauly and Wedig approach is entirely satisfactory, however, mainly because the information each requires is difficult or expensive to obtain. The PPRC approach requires data on the direct costs of each physician service, which necessitates complex and expensive surveys, or even time and motion studies, of physician practices. The Pauly and Wedig approach presumes that information on the long-run marginal cost and the sensitivity of supply of physician services to their price is available for each service or class of services.

The approach developed in this article has much lower data requirements than either the PPRC or Pauly and Wedig methods. In fact, it can be implemented using data sources already employed in the MFS. The lesser data requirements of this method mean that it can be developed more rapidly and more cheaply than the other methods, and can be validated and updated more easily. …

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