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Research Briefs

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Dor, A. and Farley, D.E. (1996)."Payment source and the cost of hospital care: Evidence from a multiproduct cost function with multiple payers." Journal of Health Economics 15, pp. 1-21, 1996.

Hospitals are known to shift unpaid costs from uninsured and Medicaid patients to privately insured patients in order to maintain profitability. A recent study shows that they also may modify the intensity of health care services to bring marginal costs (costs for additional medical services) more in line with the level of reimbursement from the patient's insurance plan. The authors, who formerly were with the Agency for Health Care Policy and Research, used the Hospital Cost and Utilization Project (HCUP-2) national database of more than 400 hospitals to compare the marginal costs of patients for Medicare, Medicaid, private payers, and uncompensated care from 1985 to 1987. They controlled for case mix differences by payer class. They found the highest marginal costs for Medicare ($2,006 in 1987 dollars), followed closely by private insurers ($1,635). Marginal costs for similar Medicaid patients tended to be substantially lower ($907) and were even lower for uninsured patients ($715). Reprints (AHCPR Publication No. 96-R115) are available from AHCPR.

East, T.D. and Morris, A.H. (1996, April). "Decision support systems for management of mechanical ventilation." (AHCPR grant HS06594). Respiratory Care 41(4), pp. 327-340.

Decision support systems for clinicians who care for patients on mechanical ventilation may reduce inappropriate therapy and variation in practice and thus profoundly affect the quality and cost of care, according to this commentary. The authors outline the strengths and weaknesses of the tools used for these decisions, such as computerized references and training materials, clinical practice guidelines, care paths, and clinical protocols. They point out that the quality of care increases commensurately with increases in the level of standardization, while the cost of care and legal liability decreases, all without intruding on caregiver autonomy. Decision support systems are not intended to replace the clinician, but they can contribute to more efficient and effective respiratory care at a lower cost, conclude the authors.

Edinger, S., and McCormick, K.A. (1996, April). "Databases-their use in developing clinical practice guidelines and estimating the cost impact of guideline implementation." Journal of the American Health Information Management Association 67(4), pp. 52-60.

This article informs health information management professionals, guideline developers, and other health care providers about the use of health databases in developing practice guidelines and how these databases can be used to estimate the cost impact of practice guideline implementation. The authors, who are Senior Science Advisors in the Agency for Health Care Policy and Research's Center for Information Technology, describe three types of databases: those for topic selection, those for literature review during practice guideline development, and those for estimating the cost impact of a guideline. These databases include health survey data, socioeconomic and demographic data, bibliographic citations and abstract data, and claims and provider data. Reprints (AHCPR Publication No. 96-R108) are available from AHCPR.

Gifford, F. (1996, March-April). "Outcomes research and practice guidelines." (AHCPR grant HS06688). Hastings Center Report 26(2), pp. 38-44.

The author examines reasons underlying the reluctance of some clinicians to adopt clinical practice guidelines. Some providers are skeptical about the validity, reliability, and integrity of the data used to develop the guidelines. Others are responding to patients' preferences, clinical expertise, and other data irrelevant to practice and legal concerns. For example, different patients may have different attitudes about the importance of attaining certain health goals and avoiding certain side effects. Some clinicians also believe that their lifelong experience and the details of individual cases lead them to make better judgments that cannot be specified by clinical rules. Also, some are concerned about the cost-savings aspect of guidelines and its effect on quality and access to care. The authors suggest that those promulgating practice guidelines strive to remove unnecessary barriers to their adoption, for example, by doing a better job of establishing the credibility of those compiling the data and making recommendations and providing a more thorough explanation of the methodology used to analyze and rank the data.

Green, L.A. (1996, April). "Practical issues in conducting small-area variation analysis." (AHCPR grant HS06409). Family Medicine 28, pp. 277-281.

The study of variations in the use of medical and surgical services across small geographic areas is called small-area variation analysis (SAVA). This paper examines the conduct of a SAVA health services research project to aid other researchers in performing and interpreting such projects. The author details each of the steps used in performing SAVA on hospitalizations for suspected acute cardiac ischemia in the State of Michigan. The study team consisted of the principal investigator, a biostatistician, a health economist, a medical geographer, and a systems analyst. They defined small analysis areas by a patient origin clustering method and adjusted crude area rates by the age and sex of the population. Finally, they analyzed the adjusted rates, including sociodemographic variables. The author concludes by discussing issues in interpretation of SAVA and practical barriers to using SAVA to examine primary care.

Newman, S.J., and Reschovsky, J.D. (1996, April). "Neighborhood locations of Section 8 housing certificate users with and without mental illness." Psychiatric Services 47(4), pp. 392-397.

The deinstitutionalization of patients with mental illness often results in their moving into independent housing using the Federal Section 8 housing subsidy program, in which participants pay 30 percent of their income for rent. Some question whether persons with mental illness face greater public housing discrimination than their counterparts without mental illness and whether they are forced to locate in the worst neighborhoods. Actually, being black more than having a mental illness increased the odds of obtaining public housing in a worse neighborhood, according to this study. The researchers evaluated the allocation of Section 8 certificates between 1988 and 1992 to individuals with chronic mental illness at two of nine demonstration sites (Baltimore and Cincinnati) for the Robert Wood Johnson Foundation Program on Chronic Mental Illness (PCMI). Results showed that Section 8 users with mental illness settled in slightly better neighborhoods overall than their general Section 8 counterparts. The most important factor explaining differences in neighborhood quality among Section 8 users was race. Blacks located in lower-quality neighborhoods more often than whites, who made up the larger proportion of Section 8 users with mental illness.

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Current as of July 1996

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