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R C Morey

Publications and source records attributed to R C Morey.

8 recordsLinked to original sources
PubMed2000

Assessing the operating efficiencies of teaching hospitals by an enhancement of the AHA/AAMC method. American Hospital Association/Association of American Medical Colleges.

In the ongoing effort to control costs, comparisons among hospitals' efficiency levels, if valid, can help identify "best practices" across institutions and uncover situations that need corrective intervention. The authors present an extension of the "adjusted cost per equivalent discharge" approach, which incorporates case-mix-severity differences, regional labor cost differentials, and inpatient/outpatient mix, but does not take into account such factors as the differences in hospital sizes, extents of the teaching mission, or quality of care delivered. The alternative approach yields information that suggests where an institution's total operating costs might be reduced with no change in any of the hospital's outputs or operating environment, through comparison with a "peer group" of other hospitals, matched according to the subject hospital's number of beds, the quality of care the hospital delivers, the extent of medical education carried out, the level of case-mix-adjusted discharges, and outpatient activities. A difficulty with this approach (as with others) is that measurement of some of the additional facets (e.g., quality of care) is still evolving, so its main contribution at this time is to provide a construct and method capable of incorporating these important added considerations. Hospital rankings achieved by applying the current and alternative approaches to a real set of teaching hospitals operating in FY 1987 are compared. While the rankings produced by the two approaches are loosely similar, the authors show that some significant differences do appear and can be at least partially explained by the incorporation of the additional factors mentioned above.

Ambulatory Care↗
PubMed1995

Estimating the hospital-wide cost differentials warranted for teaching hospitals. An alternative to regression approaches.

Under Medicare's Prospective Payment System, teaching hospitals receive additional reimbursements, vis-à-vis nonteaching hospitals, for both "direct" teaching expenses and for "indirect" expenses. They totaled $3.1 billion in fiscal year 1989. The authors propose and illustrate a non-regression-based, nonparametric method for viewing the total hospital-wide reimbursement differential warranted for teaching hospitals, a method utilizing a peer grouping of like hospitals to estimate two different "best practices" cost frontiers. The hospital's efficiently delivered cost to meet all of the hospital's actual service outputs, including its teaching mission, and delivered level of quality of care, is compared to the corresponding cost when only the teaching mission is excluded. The difference in these costs for a particular hospital can be used to estimate a suggested lump sum Medicare reimbursement add-on, in recognition of the hospital's teaching mission. The approach is illustrated using a subset of the Health Care Financing Administration's 1988 hospital data set, with comparisons of actual and suggested reimbursements provided.

Cost Allocation↗
PubMed1992

The trade-off between hospital cost and quality of care. An exploratory empirical analysis.

The debate concerning quality of care in hospitals, its "value" and affordability, is increasingly of concern to providers, consumers, and purchasers in the United States and elsewhere. We undertook an exploratory study to estimate the impact on hospital-wide costs if quality-of-care levels were varied. To do so, we obtained costs and service output data regarding 300 U.S. hospitals, representing approximately a 5% cross section of all hospitals operating in 1983; both inpatient and outpatient services were included. The quality-of-care measure used for the exploratory analysis was the ratio of actual deaths in the hospital for the year in question to the forecasted number of deaths for the hospital; the hospital mortality forecaster had earlier (and elsewhere) been built from analyses of 6 million discharge abstracts, and took into account each hospital's actual individual admissions, including key patient descriptors for each admission. Such adjusted death rates have increasingly been used as potential indicators of quality, with recent research lending support for the viability of that linkage. The authors then utilized the economic construct of allocative efficiency relying on "best practices" concepts and peer groupings, built using the "envelopment" philosophy of Data Envelopment Analysis and Pareto efficiency. These analytical techniques estimated the efficiently delivered costs required to meet prespecified levels of quality of care. The marginal additional cost per each death deferred in 1983 was estimated to be approximately $29,000 (in 1990 dollars) for the average efficient hospital. Also, over a feasible range, a 1% increase in the level of quality of care delivered was estimated to increase hospital cost by an average of 1.34%. This estimated elasticity of quality on cost also increased with the number of beds in the hospital.

Comorbidity↗
PubMed1991

Measuring efficiency in acute care hospitals: an application of data envelopment analysis.

In this article, the authors attempted to demonstrate how DEA can be useful to hospital administrators and health care planners. They used actual data collected by the American Hospital Association through its Monitrend Data Service. Since these were national data, they are presented here for illustrative purposes only. The efficiency with which a hospital operates may well depend upon the local or regional labor market, the competition among health care providers in that market, and the demographics of the service area. The choice of variables was dictated by reasonableness and availability of data. Given the routine collection of case mix data by DRG since 1984, the use of a different set of output variables for any future studies would be quite appropriate. Additionally, if DEA were to be used, a consensus concerning relevant controllable and non-controllable input variables would need to be achieved. There are more technical caveats of which the reader should be aware. 1) The efficiency scores are all relative and are based on the performance of the other hospitals being compared; nothing can be said about the absolute efficiency of a given hospital. However, the relative ratings are conservative in that the approach "bends over backwards" to give the individual hospital the benefit of the doubt in terms of the relative importance of the various outputs and inputs utilized. The approach maintains equity in that any weights chosen for a given hospital must be feasible for all of the other hospitals. 2. The ratings assume a causal impact of the inputs on the outputs. In addition, it is possible that inclusion of additional inputs and outputs could modify the relative scores and/or help explain the differences. However, based on the factors available, any unit rated inefficient is inferior in a very real and demonstrable sense. 3. DEA is based on the generalized notion of convexity which assumes that the performance arrived at by taking any linear weighted combination of other hospitals' inputs and outputs represents a feasible and achievable technology. The general frontier surface is approximated by piecewise-linear segments with the result that observed differences in efficiency cannot be explained away as differences in economies of scale. 4. The inefficiency score and the resource conservation potentials are based on a unit's so-called contraction path, i.e., all of the controllable inputs are required to be reduced by the same factor.(ABSTRACT TRUNCATED AT 400 WORDS)

American Hospital Association↗
PubMed1983

A comparison of alternative medicare reimbursement policies under optimal hospital pricing.

This paper applies and extends the use of a nonlinear hospital pricing model, recently posited in the literature by Dittman and Morey [1]. That model applied a hospital profit-maximizing behavior and studied the effects of optimal pricing of hospital ancillary services on the incidence of payment by private insurance companies and the Medicare trust fund. Here, we examine variations of the above model where both hospital profit-maximizing and profit-satisficing postures are of interest. We apply the model to three types of Medicare reimbursement policies currently in use or under legislative mandate to implement. The policies differ according to hospital size and whether cross-subsidies are allowed. We are interested in determining the effects of profit-maximizing and -satisficing behaviors of these three reimbursement policies on the levels of profits received, and on the respective implications for private payors and the Medicare trust fund.

Cost Allocation↗
PubMedDate not supplied

Hospital profit planning under Medicare reimbursement.

The federal Medicare regulations reimburse hospitals on a pro rata share of the hospital's cost. Hence, to meet its financial requirements, a hospital is forced to shift more of the financial burdens onto its private patients. This procedure has contributed to double digit inflation in hospital prices and to proposed federal regulation to control the rate of increase in hospital revenues. In this regulatory environment, we develop nonlinear programming pricing and cost allocation models to aid hospital administrators in meeting their profit maximizing and profit satisfying goals. The model enables administrators to explore tactical issues such as: (i) studying the relationship between a voluntary or legislated cap on a hospital's total revenues and the hospital's profitability, (ii) identifying those departments within the hospital that are the most attractive candidates for cost reduction or cost containment efforts, and (iii) isolating those services that should be singled out by the hospital manager for renegotiation of the prospective or "customary and reasonable" cap. Finally the modeling approach is helpful in explaining the departmental cross subsidies observed in practice, and can be of aid to federal administrators in assessing the impacts of proposed changes in the Medicare reimbursement formula.

Cost Allocation↗