Home care for Blue Cross insured patients: a case study.
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We analyze the problem of second-best optimal health insurance in the context of a model in which patients and doctors must decide not only on an aggregate quantity of health services to use in treating various kinds of illness, but also have a choice between different kinds of providers (in particular, outpatient services rendered by primary-care physicians or inpatient services provided by hospital-based specialists). We consider well-informed patients' choices of provider when they have conventional insurance so they only pay part of the cost of their health services, as well as the equilibrium strategies of doctors and patients when there is patient-provider asymmetry; in the latter case we also analyze a managed-care insurance setup under which doctors are paid by capitation. We find that under certain plausible conditions, second-best optimal managed-care plans with supply-side incentives dominate second-best optimal conventional plans that rely on cost control through demand-side cost sharing.
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In this document, we are addressing public comments received in response to the interim final rule on payment for the cost of malpractice insurance, insurance, published on April 1, 1986. (51 FR 11142.) In that interim final rule, we established a specific methodology for apportionment of hospital malpractice insurance cost (that is, the cost of premiums or self-insurance) under Medicare that relied on, in part, a "scaling factor formula." We also provided for apportionment of skilled nursing facility malpractice insurance cost on the basis of Medicare patient utilization. With respect to the Medicaid program and the Maternal and Child Health program, we deferred to the States instead of establishing payment methodologies for these programs. As a result of our consideration of timely comments on the interim final rule and reevaluation of appropriate data, we plan to specify the values of the factors used in the scaling factor formula for the hospital methodology separately for short-term acute care hospitals and other hospitals. Accordingly, we have recomputed the values of the factors in the formula and, in this document, we are establishing values for short-term acute care hospitals. The values are the same as those announced in the interim final rule for all hospitals. We will issue another Federal Register document as soon as possible in which, as noted above, we intend to establish the values to be used in applying the formula to other hospitals. In the interim, for these other hospitals, we will continue to use the same formula values that were established in the interim final rule. We are not changing any of the other policies established in the interim final rule.
OBJECTIVE: To assess the effect of possession of private health insurance on hospital use and outcomes in Western Australia. METHOD: Hospital morbidity records were extracted from the Western Australian (WA) Data Linkage System for all 22 major diagnostic categories (MDCs) for the period 1994-99, with follow-up to the end of 2000. Multivariate modelling techniques were used to estimate the effect of possession of private health insurance on hospital admission rates, average and total length of stay (LOS), cumulative incidence of admission at 30 days and one year, and case fatality at one year. RESULTS: Possession of private health insurance had significant effects on hospital use and outcomes, even after adjustments for age, sex, aboriginality, socioeconomic status, location and comorbidity. Non-insured patients tended to have a higher overall hospital admission rate but a lower admission rate for surgical episodes, and they generally had a longer LOS although this difference was only greater than a day in three MDCs. Case fatality was higher in non-insured patients, but there was no systematic trend with regard to readmission rates. CONCLUSIONS: The study found that for all MDCs, other than those where treatment was required on an emergency basis, patients with private health insurance had improved access to surgical procedures. Either non-insured patients were disadvantaged in their access to surgery or the higher intervention rate in privately insured patients represented supplier-/consumer-induced demand which may not always have been to the patient's advantage or both may have occurred.
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The 1975, 1980, and 1986 sample surveys from the National Institute of Mental Health were used to predict the type of inpatient psychiatric facility where people were admitted. Predictors used were demographics (age, gender, race, marital status, and education), psychiatric diagnosis, and insurance status (primary payment source). A discriminant analysis revealed that insurance status was the most important discriminator in predicting hospital type. State hospitals were more likely to care for patients with little or no resources, whereas private hospitals cared for patients with some form of insurance. The authors discuss the implications of insurance status and access to psychiatric treatment.
The health maintenance organization (HMO) is an alternative to the traditional fee-for-service health care system in the United States. Other studies have shown that the HMO reduces hospital utilization and offers greater benefit packages than fee-for-service. This paper tests whether the presence of HMO's provides effective competitive pressure on Blue Cross, the largest insurer of hospital costs. The cross sectional regression analysis supports the hypotheses that Blue Cross has reduced hospital utilization and increased benefit packages in response to HMO competition. Consequently, competitive forces are shown to be operative in at least one area of health care.
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A change in payment mechanism for inpatient care from per diem to per episode creates two incentives - a marginal and an average price effect - to change length of stay. The decrease in marginal price per day to zero should reduce the length of stay, while an increase in average price per inpatient stay should increase the length of stay. This study uses data from a natural experiment to estimate both marginal and average price elasticities, and to test whether the length of stay falls after the introduction of prospective payment in a sample of 8509 severely mentally ill patients. We estimate that the marginal price elasticity is zero, but the average price elasticity is between 0.16 and 0.20. The results were generally robust for short- and long stayers, and for persons admitted early and late after the change in payment mechanism. The model controlled for hospital fixed effects and individual random effects.
In a national sampling of child inpatient directors, survey responses suggested variability in the use of many admission criteria. Yet, severity of symptoms, potential effectiveness of outpatient treatment, and extent of medical complications appeared to be commonly used admission criteria. DSM-III diagnoses were inconsistently used admission criteria, and many diagnoses were considered suitable for admission in extenuating circumstances only.
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The value added by acute-care hospitals is in the form of specific procedures (therapy, operations, testing) and the bed care necessary to make the procedures effective. When more than one hospital exists in a local area (defined in many studies as a radius of 15 mi/24 km) they compete for market share, since greater market share has a positive effect on economies of scale, utilization rates, learning curves and levels of quality. Competition is not only with other hospitals (and 75% of all hospitals do have a competitor within 24 km), but also with doctors who now perform some procedures in their offices, and with specialized clinics. The first strategy is to attract physician allegiance since they act as gate-keepers, directing patients to specific hospitals. This is done through personal amenities, professional amenities and enhancement to personal prestige and income. This competition for physician allegiance has a direct effect on utilization rates (doctors want spare capacity to suit their needs), on the range of services and facilities offered (doctors want more support), and on length of stay (doctors want longer stays). All of these increase the hospital's costs. The second strategy is to enter into contracts with third-party payers who will direct their clients to specific or preferred hospitals. The negative effect is that in competitive markets such payers may be able to bargain prices down. However, hospital differentiation makes it difficult for payers to make complete substitutions among them. As well, since the payers compete for clients, they often use hospital alliances as a selling point and therefore are often cooperative rather than confrontational in their negotiations. One tactic used by hospitals is to stress quality of service. But since quality in health care is hard to measure, patients are often unable to make direct assessments of alternatives. Hospitals therefore often 'signal' quality in various ways which may, and often do, increase hospital costs. (Some of these signals also attract physicians). Price is not a major element in competition. Most other strategies and tactics raise hospital costs and therefore price. Pressure from payers is turned back through differentiation (preventing substitution) and hospital-payer alliances for clients. Health care comes in too many packages to allow effective price competition. A final tactic is to increase the range of services or facilities offered. Enhanced services attract doctors by offering more support; attract some patients direct; and help to recapture market share lost to specialized clinics.(ABSTRACT TRUNCATED AT 400 WORDS)