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Objective: To determine the effect of joining HMOs (health maintenance organizations) on the inpatient utilization of Medicare beneficiaries., Data Sources: We linked enrollment data on Medicare beneficiaries to patient discharge data from the California Office of Statewide Health Planning and Development (OSHPD) for 1991-1995., Design and Sample: A quasi-experimental design comparing inpatient utilization before and after switching from fee-for-service (FFS) to Medicare HMOs; with comparison groups of continuous FFS and HMO beneficiaries to adjust for aging and secular trends. The sample consisted of 124,111 Medicare beneficiaries who switched from FFS to HMOs in 1992 and 1993, and random samples of 108,966 continuous FFS beneficiaries and 18,276 continuous HMO enrollees yielding 1,227,105 person-year observations over five years., Main Outcomes Measure: Total inpatient days per thousand per year., Principal Findings: When beneficiaries joined a group/staff HMO, their total days per year were 18 percent lower (95 percent confidence interval, 15-22 percent) than if the beneficiaries had remained in FFS. Total days per year were reduced less for beneficiaries joining an IPA (independent practice association) HMO (11 percent; 95 percent confidence interval, 4-19 percent). Medicare group/staff and IPA-model HMO enrollees had roughly 60 percent of the inpatient days per thousand beneficiaries in 1995 as did FFS beneficiaries (976 and 928 versus 1,679 days per thousand, respectively). In the group/staff model HMOs, our analysis suggests that managed care practices accounted for 214 days of this difference, and the remaining 489 days (70 percent) were due to favorable selection. In IPA HMOs, managed care practices appear to account for only 115 days, with 636 days (85 percent) due to selection., Conclusions: Through the mid-nineties, Medicare HMOs in California were able to reduce inpatient utilization beyond that attributable to the high level of favorable selection, but the reduction varied by type of HMO.

Objective: To evaluate whether adjusting the Health Plan Employer Data and Information Set (HEDIS) low birth weight (LBW) measure for maternal risk factors is feasible and improves its validity as a quality indicator., Data Source: The Washington State Birth Event Record Data for calendar years 1989 and 1990, including birth certificate data matched with mothers' and infants' hospital discharge records, with 5,837 records of singlet on infants identified as LBW (< 2,500 g) and a 25 percent sample ( n = 31,570) of the normal-weight births (

Objective: To determine the effect of postpartum length of stay on newborn readmission., Data Sources: Secondary data set consisting of newborns born in Washington state in 1989 and 1990. The data set contains information about the characteristics of the newborn and its parents, physician, hospital, and insurance status., Study Design: Analysis of the effect of length of stay on the probability of newborn readmission using hour of birth and method of delivery as instrumental variables (IVs) to account for unobserved heterogeneity. Of approximately 150,000 newborns born in Washington in 1989 and 1990, 108,551 (72 percent) were included in our analysis., Principal Findings: Newborns with different lengths of stay differ in unmeasured characteristics, biasing estimates based on standard statistical methods. The results of our analyses show that a 12-hour increase in length of stay is associated with a reduction in the newborn readmission rate of 0.6 percentage points. This is twice as large as the estimate obtained using standard statistical (non-IV) methods., Conclusion: An increase in the length of postpartum hospital stays may result in a decline in newborn readmissions. The magnitude of this decline in readmissions may be larger than previously thought.

Objectives: To evaluate the costs of implementing a church-based, telephone-counseling program for increasing mammography use, and to identify the components of costs and the likely cost-effectiveness in hypothetical communities with varying characteristics., Data Sources/study Setting: An ethnically and socioeconomically diverse sample of 1,443 women recruited from 45 churches participating in the Los Angeles Mammography Promotion (LAMP) program were followed from 1995 to 1997., Study Design: Churches were stratified into blocks and randomized into three intervention arms-telephone counseling, mail counseling, and control. We surveyed participants before and after the intervention to collect data on mammography use and demographic characteristics., Data Collection/extraction Methods: We used call records, activity reports, and interviews to collect data on the time and materials needed to organize and carry out the intervention. We constructed a standard model of costs and cost-effectiveness based on these data and the Year One results of the LAMP program., Principal Findings: The cost in materials and overhead to the church site was $10.89 per participant and $188 per additional screening. However, when the estimated cost for church volunteers' time was included, the cost of the intervention increased substantially., Conclusions: A church-based program to promote the use of mammography would be feasible for many churches with the use of volunteer labor and resources.

Objective: To simulate whether allowing small businesses to offer employer-funded medical savings accounts (MSAs) would change the amount or type of insurance coverage., Study Setting: Economic policy evaluation using a national probability sample of nonelderly non-institutionalized Americans from the 1993 Current Population Survey (CPS)., Study Design: We used a behavioral simulation model to predict the effect of MSAs on the insurance choices of employees of small businesses (and their families). The model predicts spending by each family in a FFS plan, an HMO plan, an MSA, and no insurance. These predictions allow us to compute community-rated premiums for each plan, but with firm-specific load fees. Within each firm, employees then evaluate each option, and the firm decides whether to offer insurance-and what type-based on these evaluations. If firms offer insurance, we consider two scenarios: (1) all workers elect coverage; and (2) workers can decline the coverage in return for a wage increase., Principal Findings: In the long run, under simulated conditions, tax-advantaged MSAs could attract 56 percent of all employees offered a plan by small businesses. However, the fraction of small-business employees offered insurance increases only from 41 percent to 43 percent when MSAs become an option. Many employees now signing up for a FFS plan would switch to MSAs if they were universally available., Conclusions: Our simulations suggest that MSAs will provide a limited impetus to businesses that do not currently cover insurance. However, MSAs could be desirable to workers in firms that already offer HMOs or standard FFS plans. As a result, expanding MSA availability could make it a major form of insurance for covered workers in small businesses. Overall welfare would increase slightly.

Objectives: (1) To describe the issues in developing a clinical predictor of cesarean delivery that could be used to adjust reported cesarean rates for case mix, and (2) to compare its performance to other, simpler predictors using clinical and statistical criteria., Data Sources: Singleton births greater than 2,500 grams in Washington State in 1989 and 1990 for whom mothers and infant hospital discharge records could be matched to birth certificate data., Design: Statistical analysis of retrospective merged hospital and birth certificate data, which were used to develop variables and models to predict the probability that any particular delivery would be a cesarean., Principal Findings: Merged data led to better predictor variables than those based on one source. A simple four-category hierarchical classification into births with prior cesarean, breech but no prior cesarean, first birth, and other explains 30 percent of the variance in individual cesarean rates. The full clinical model fit the data well and explained 37 percent of the variance. Multiparas without serious complications comprised 35 percent of the mothers and averaged less than 2 percent cesareans. A hospital's predicted cesarean rate depends strongly on the proportion of its births that are first births., Conclusion: Government and private agencies have reported cesarean rates as measures of hospital performance. Depending on data and resources available, both simple and complex measures of case mix can be used to adjust reported rates. These adjustments should not include all variables related to the rates. Proper adjustments may not alter hospital rankings greatly, but they will improve the validity and acceptability of the reports.

Consumers, payers, and policymakers are demanding to know more about the quality of the services they are purchasing or might purchase. The information provided, however, is often driven by data availability rather than by epidemiologic and clinical considerations. In this article, we present an approach for selecting topics for measuring technical quality of care, based on the expected impact on health of improved quality. This approach employs data or estimates on disease burden, efficacy of available treatments, and the current quality of care being provided. We use this model to select measures that could be used to measure the quality of care in health plans, but the proposed framework could also be used to select quality of care measures for other purposes or in other contexts (for example, to select measures for hospitals). Given the limited resources available for quality assessment and the policy consequences of better information on provider quality, priorities for assessment efforts should focus on those areas where better quality translates into improved health.

The article examines patterns of starting and continuing outpatient mental health care as a function of time, and the implications of these patterns for estimates of the response of demand to generosity of fee-for-service insurance coverage. The data are from the RAND Health Insurance Experiment (HIE), which acquired a random sample of the nonelderly general population in six U.S. sites. People rarely had more than one episode of use of outpatient mental health services in a year. Persons who used in the prior year had high rates of continuing in treatment, while those without prior use entered treatment at a low, steady rate. Similar patterns of use by former users and nonusers were observed across insurance plans that varied widely in generosity, but the absolute probabilities of use were significantly lower in less generous plans. The probability of use of mental health services expanded significantly over time in the HIE; thus, estimates of demand in a steady state would be higher than those based on the HIE study years.

In a randomized trial of the effects of medical insurance on spending and the health status of the nonaged, we previously reported that patients with limited cost sharing had approximately one-third less use of medical services, similar general self-assessed health, and worse blood pressure, functional far vision, and dental health than those with free care. Of the 20 additional measures of physiological health studied here on 3,565 adults, people with cost sharing scored better on 12 measures and significantly worse only for functional near vision. People with cost sharing had less worry and pain from physiological conditions on 33 of 44 comparisons. There were no significant differences between plans in nine health practices, but those with cost sharing fared worse on three types of cancer screening and better on weight, exercise, and drinking. Overall, except for patients with hypertension or vision problems, the effects of cost sharing on health were minor.