The role of performance measures for improving quality in managed care organizations.

OBJECTIVES: To understand how managed care plans use performance measures for quality improvement and to identify the strengths and weaknesses of currently used standardized performance measures such as the Health Plan Employer Data and Information Set (HEDIS) and the Consumer Assessment of Health Plans (CAHPS) survey. DATA SOURCES/STUDY SETTING: Representatives (chief executive officers, medical directors, and quality-improvement directors) from 24 health plans in four states were surveyed. The overall response rate was 58.3 percent, with a mean of 1.8 respondents per plan. STUDY DESIGN: This exploratory qualitative research used a purposive sample of respondents. Two study authors conducted separate one-hour tape-recorded telephone interviews with multiple respondents from each health plan. PRINCIPAL FINDINGS: All managed care organizations interviewed use performance measures for quality improvement but the degree and sophistication of use varies. Many of our respondent plans use performance measures to target quality-improvement initiatives, evaluate current performance, establish goals for quality improvement, identify the root cause of problems, and monitor performance. CONCLUSION: Performance measures are used for quality improvement in addition to informing external constituents, but additional research is needed to understand how the benefits of measurement can be maximized.

Are managed care plans organizing for quality?

This article examines the degree to which managed care organizations (MCOs) are reorganizing to take responsibility for the quality of care and service they provide. Specifically, factors prompting plans to focus on quality improvement (QI) and how they may be building the capacity to improve quality are considered. The authors' analysis is based on executive interviews with the plan medical directors, QI directors, and chief executive officers (CEOs) in a sample of 24 health plans. The overall response rate was 58.3 percent (medical director = 62.5 percent, QI director = 79.2 percent, CEO = 33.3 percent). The authors queried respondents about (1) perceived drivers and obstacles to the development of an effective QI program, (2) plan organizational structure for QI, and (3) technical capacities for data collection, management, and performance measurement. The results suggest that MCOs are responding to outside pressures to engage in QI. They are reorganizing their management structures and more slowly and tentatively are building technical capacity for QI.

HEDIS measures and managed care enrollment.

This article examines the relationship between 1996 health plan enrollment and both HEDIS-based plan performance ratings and individual HEDIS measures. Data were obtained from a large firm that collected, aggregated, and disseminated plan performance ratings to its employees. Plan market share regressions are estimated controlling for out-of-pocket price and model type in addition to the plan ratings and HEDIS measures. The results suggests that employees did not respond strongly to the provided ratings. There are several potential explanations for the lack of response, including difficulty understanding the ratings and never having seen them. In addition, employees may base their plan choices on information that is obtained from their own past experience, friends, family, and colleagues. The pattern of results suggests that such information is important. Counterintuitive signs most likely reflect an inverse correlation between some HEDIS ratings (or measures) and attributes employees observe informally.

Health plan report cards and insurance choice.

This paper examines the relationship between consumers' health plan choices and health plan performance ratings. We make use of an initiative at a large firm to collect, aggregate, and disseminate to employees plan performance ratings. We estimate several statistical models, including share equations--which allow for the presence of important unobserved plan attributes--and logit models. Although report card ratings appear to be related to enrollment choices, the relationship is not uniform. For some dimensions of performance, the results are consistent with the hypothesis that employees respond to the performance ratings. For other dimensions, the ratings seem less influential than other plan attributes that employees likely observed without the data release.

Health plan report cards: exploring differences in plan ratings.

BACKGROUND: Despite the considerable attention paid to the collection of data and the publication of health plan report cards, there is no available study on the comparability of published report cards. Ratings from seven health plan report cards publicly available in fall 1996 were compared--including those produced by major periodicals, a large national employer, a nonprofit consumer group, a health maintenance organization accreditation agency, and a consortium of employers. METHODS: Dimensions of plan performance common to the seven report cards were identified. Spearman rank correlation coefficients were computed for each pair of report cards for each of the three dimensions that were evaluated. COMPARABILITY OF REPORT CARDS: Although plan ratings tended to be positively correlated as hypothesized, the magnitude of the estimated correlation coefficients varied. For example, the estimated correlation coefficient between two periodicals' overall plan ratings was 0.48. The ranges of estimated correlations were 0.18-0.70 for preventive care (among four report cards) and 0.19-0.73 for enrollee satisfaction (among three report cards). DISCUSSION: Discrepancies in ratings may reflect methodologic issues pertaining to the sample of health plans used, plan performance measures included, and the processes by which individual measures were aggregated to construct indices and ratings. Health plan report cards may be sending mixed signals to consumers. These inconsistencies may explain why focus group studies have found that despite the widespread indication that plan performance measures would be useful, relatively few of those who had seen such information report using it in making their plan choice. Future efforts to evaluate health plans should clearly identify assumptions, methods, normative judgments, and limitations.

Health plan accreditation: NCQA, JCAHO, or both?

Currently the National Committee for Quality Assurance (NCQA) and the Joint Commission on the Accreditation of Healthcare Organizations (the Joint Commission) accredit managed care organizations (MCOs), but is competition in the market for plan accreditation beneficial or counterproductive? This paper presents the results from two surveys that were administered to a group of large public and private purchasers, and representatives from the American Association of Health Plans and the Centers for Disease Control, who attended the Lovelace Health System (LHS) "Accreditation Experience" program. The LHS program was designed to inform purchasers about the NCQA and Joint Commission accreditation processes. The surveys captured purchaser views about the advantages and disadvantages of both accreditation processes, the value of accreditation, and the use of plan performance measures.

Consumer health plan choice: current knowledge and future directions.

A keystone of the competitive strategy in health insurance markets is the assumption that "consumers" can make informed choices based on the costs and quality of competing health plans, and that selection effects are not large. However, little is known about how individuals use information other than price in the decision making process. This review summarizes the state of knowledge about how individuals make choices among health plans and outlines an agenda for future research. We find that the existing literature on health plan choice is no longer sufficient given the widespread growth and acceptance of managed care, and the increased proportion of consumers' income now going toward the purchase of health plans. Instead, today's environment of health plan choice requires better understanding of how plan attributes other than price influence plan choice, how other variables such as health status interact with plan attributes in the decision making process, and how specific populations differ from one another in terms of the sensitivity of their health plan choices to these different types of variables.