Assessing the relationship between quality of care and the characteristics of health care organizations.

In the past two decades, relationships among health plans, medical groups, and providers have grown more complex and the number of clinical management strategies has increased. In this context, determining the independent effect of a particular organizational strategy on quality of care has become more difficult. The authors review some of the issues a researcher must address when studying the relationship between organizational characteristics and quality of care. They offer criteria for selecting a research question, list organizational characteristics that may influence quality, and suggest sampling and study design techniques to reduce confounding. Since this type of research often requires a health care organization as collaborator, the authors discuss strategies for developing research partnerships and collecting data from the partner organization. Finally, they offer suggestions for translating research into policy.

Reconciling quality measurement with financial risk adjustment in health plans.

BACKGROUND: Initiatives to improve quality measurement (QM) and to create systems for financial risk adjustment (RA) have developed in response to concerns about price competition's threat to quality and stimulation of risk selection. QM is designed to help purchasers identify best plans, to aid plans in their selection of providers, to facilitate quality improvement by plans and providers, and to assist patients faced with choices among plans and providers. The goal of RA is to eliminate incentives for plans and providers to avoid sick, high-cost patients in favor of healthy, low-cost patients. CONFLICTS BETWEEN QM AND RA: For QM it is often necessary to identify all patients with a particular condition, and many quality measures involve intervening on patients early in the course of their disease. Identifying patients through utilization decisions (for example, identifying patients with depression through receipt of an antidepressant prescription) may bias QM. For RA, the focus is on the highest-cost patients, and patient capture through resource utilization is more likely to be appropriate. DISCUSSION: Achieving QM and RA depends on improving information systems and patient identification processes and developing standard definitions for important variables. QM and RA could both be improved, and the conflicts between them reduced, if they were based more on detailed clinical data, if consensus definitions of quality of care for specific diagnoses could be achieved, if the number of QM measures that target acute and chronic care (versus preventive care) were increased, and if information systems were enhanced.

Population choice and variable selection in the estimation and application of risk models.

This paper shows that risk adjustment models based on demographic and employment variables are not easily transferable from one population to the next, and that administrative variables are not useful in predicting medical expenditures. We found statistically significant differences between models built on populations of employees from a single employer enrolled in two different health plans, and between models built on populations of enrollees from a single health plan employed at two different companies. Employment-based variables (e.g., length of employment) had little predictive power in any of these risk models. We conclude that policymakers should be careful in applying risk models across populations, and that future versions of risk models for use within large employers need not include employment-based variables.

Managed care and children: an overview.

This article lays the foundation for the other articles in this journal issue, which examine the effect of managed health care arrangements on a particular population: children. Although managed care has been used to finance and deliver health care services for decades, the meaning of this term often has been unclear to health care consumers and practitioners because new forms of managed care have evolved rapidly. The one consistent and unifying concept across all managed care arrangements is that enrollees obtain care from a network of participating health care providers who contract with the managed care organization and abide by the organization's rules. The uncertainty of what managed care is has made it difficult to measure the effect of these arrangements on health service delivery and health outcomes, especially in the pediatric population, where the development of outcome and quality measures lags behind that for adults. The incentives posed by managed care suggest both potential advantages and disadvantages to these arrangements for children. On the positive side, managed care enrollment may offer a "medical home" for primary care services to children who otherwise would obtain only episodic care; improve the coordination of health care services; and encourage more preventive health services. On the negative side, under capitated reimbursement, health plans have an incentive to enroll only healthy children with the lowest expected health care expenditures, and providers have an incentive to offer fewer services than may be appropriate. Managed care also may limit enrollees' choice of providers, particularly for specialty care. Despite the paucity of information about the effect of managed care on the delivery of pediatric health services and on child health outcomes, children are disproportionately being enrolled in managed care plans.

Medicare and managed care.

Medicare offers nearly universal, but limited, coverage for the elderly. The vast majority of beneficiaries therefore obtain supplemental coverage, or they enroll in HMOs to gain extra benefits at substantially lower or zero cost. This is possible because of reduced utilization and costs, as well as favorable selection of lower-risk enrollees into HMOs. Competition from HMOs may lower local fee-for-service costs as well. Quality and satisfaction measures are quite balanced, with some results showing better HMO performance and some worse. The absence of adequate risk-adjusted payments to HMOs, however, gives them little incentive to develop high-quality programs for the sickest enrollees.

The costs and outcomes of restricting public access to poison control centers. Results from a natural experiment.

OBJECTIVES: The authors examined the costs and outcomes resulting from a natural experiment during which direct public access to poison control centers was restricted and then restored. METHODS: Both societal and health care purchaser perspectives were used. Probability data were obtained from a natural experiment during which public callers from a large county in California were electronically blocked from directly accessing the poison control center. Callers were referred to 911, which had direct access to the poison control center, if they thought they had a poisoning emergency. We conducted telephone interviews of: (a) persons who attempted to call the poison control center for a child's poisoning exposure but who did not have direct access (n = 270) and (b) persons who called the poison control center after direct access was restored (n = 279). Cost data were obtained from primary data collection and from other sources. The outcome measure was the appropriateness of the treatment location (at home or at a health care facility). Caller-reported outcomes were also examined. RESULTS: The average additional cost per blocked call was $10.89 from a societal perspective, or $33.14 from a health care purchaser perspective. Fourteen percent of callers with restricted access were treated at an inappropriate location, compared with only 2% of callers with direct poison control center access. Also, 14% did not obtain any professional advice after they attempted to call the poison control center, although 66% of these cases involved potentially toxic substances. Results were robust across a range of sensitivity analyses. CONCLUSION: Restricting direct public access to poison control centers created additional costs to society, the health care sector, and callers.

The impact of financial incentives on quality of health care.

Purchasers of health care could offer financial incentives to plans or providers in order to increase quality. Unfortunately, the current health care market, in which quality is rarely measured and there is no risk adjustment, actively discourages both plans and providers from maximizing quality, resulting in a poor overall level of quality, both in fee-for-service arrangements and health maintenance organizations. Health plans and providers will not focus on quality until mechanisms to correct for risk differences among enrollees can be developed. Although such risk adjustment will be the most important stimulus for quality, it should also be linked to improvements in information systems and agreement on a minimum benefits package, quality reporting standards, and financial solvency requirements.

The policy implications of using hospital and physician volumes as "indicators" of quality of care in a changing health care environment.

There is growing interest in the quality of health care and in using quality measures to direct patients to hospitals and providers offering high quality, low cost health care. The dilemma is that, while there is an increasing need for quality indicators as a result of a changing health care environment, this changing environment has important implications for the use of some of these measures. Since the 1970s, a growing body of research in the U.S. has addressed the empirical relationship between the number of patients with a specific diagnosis of surgical procedure and their outcomes after treatment in a particular hospital or by a particular physician ("volume-outcome" studies). In this paper, we examine the policy implications of using hospital and physician volume information as an "indicator" of quality in a rapidly changing health care environment with new players and new incentives. We begin by describing the evolution of the use of volumes within both regulatory and market-oriented contexts in the U.S. We then discuss policy considerations and cautions in using volumes, along with suggestions for future research. Our purpose is to point out potential problems and clarify confusions about the use of volumes, so that policymakers and practitioners can be sensitive to the potential minefields they are traversing.

Does managed care lead to better or worse quality of care?

We analyzed evidence on managed care plan (mostly health maintenance organization, or HMO) performance from thirty-seven recently published peer-reviewed studies. Quality-of-care evidence from fifteen studies showed an equal number of significantly better and worse HMO results, compared with non-HMO plans. However, in several instances, Medicare HMO enrollees with chronic conditions showed worse quality of care. Evidence comparing hospital and physician resource use showed no clear pattern, whereas evidence on enrollee satisfaction varied by measure and enrollee type. Although recent research provides useful findings, interpreting and generalizing from these relatively few studies is difficult. Fears that HMOs uniformly lead to worse quality of care are not supported by the evidence, although all quality data were collected prior to the recent round of cost cutting that started in 1992. Hopes that HMOs would improve overall quality also are not supported, in part because of slow clinical practice change, lack of risk-adjusted capitation rates, and inadequate quality measurement and reporting.