Deborah W. Garnick

Unhealthy Drinking Patterns in Older Adults: Prevalence and Associated Characteristics

OBJECTIVES: To examine the prevalence of unhealthy drinking patterns in community‐dwelling older adults and its association with sociodemographic and health characteristics.

Developing Performance Measures for Alcohol and Other Drug Services in Managed Care Plans

BACKGROUND Monitoring the quality and availability of alcohol and other drug (AOD) services must be a central tenet of any health-related performance measurement system. The Washington Circle Group (WCG), which was convened by the Center for Substance Abuse Treatment Office of Managed Care in March 1998, has developed a core set of performance measures for AOD services for public- and private-sector health plans. It is also collaborating with a broad range of stakeholders to ensure widespread adoption of these performance measures by health plans, private employers, public payers, and accrediting organizations. CORE PERFORMANCE MEASURES Four domains were identified, with specific measures developed for each domain: (1) prevention/education, (2) recognition, (3) treatment (including initiation of alcohol and other plan services, linkage of detoxification and AOD plan services, treatment engagement, and interventions for family members/significant others), and (4) maintenance of treatment effects. CONTINUING EFFORTS Four measures that are based on administrative information from health plans and two measures that require a consumer survey of behavioral health care are undergoing extensive pilot testing. The WCG has reached out to a broad range of stakeholders in performance measurement and managed care to acquaint them with the measures and to promote their investigation and adoption. As results of pilot testing become available, these outreach efforts will continue. CONCLUSIONS Performance measures for AOD services need to become an integral part of a comprehensive set of behavioral and physical health performance measures for managed care plans.

Adapting Washington Circle performance measures for public sector substance abuse treatment systems

The Washington Circle, a group focused on developing and disseminating performance measures for substance abuse services, developed three such measures for private health plans. In this article, we explore whether these measures are appropriate for meeting measurement goals in the public sector and feasible to calculate in the public sector using data collected for administrative purposes by state and local substance abuse and/or mental health agencies. Working collaboratively, 12 states specified revised measures and 6 states pilot tested them. Two measures were retained from the original specifications: initiation of treatment and treatment engagement. Additional measures were focused on continuity of care after assessment, detoxification, residential or inpatient care. These data demonstrate that state agencies can calculate performance measures from routinely available information and that there is wide variability in these indicators. Ongoing research is needed to examine the reasons for these results, which might include lack of patient interest or commitment, need for quality improvement efforts, or financial issues.

Hospital volume and patient outcomes. The case of hip fracture patients.

Patients achieve better outcomes at hospitals that treat larger numbers of patients with certain diagnoses or who are undergoing particular procedures. However, the causal direction underlying this relationship is less well understood. Do patients treated at institutions with higher volumes of patients achieve better outcomes because the hospital staff and physicians have gained expertise by practice (the “practice makes perfect” hypothesis)? Do hospitals with a community reputation for excellent results attract higher volumes of patients because primary care physicians refer patients to specialists who practice there (the “selective referral” hypothesis)? Or, are both explanations important? This article addresses this question through a detailed analysis of patients with a particular diagnosis: hip fracture. In addition, two measures of patient outcomes are compared: long hospital stays as a proxy for in-hospital complications and in-hospital death.

The sensitivity of conditional choice models for hospital care to estimation technique.

It is plausible that distance, quality, and hospital charges all influence which hospital patients (and their referring physicians) choose. Several researchers have estimated conditional choice models that explicitly incorporate the existence of competing hospitals. To be useful for hospital administrators, health planners and insurers, however, estimates must be made for specific types of patients and include entire market areas. Data sets meeting these requirements have many combinations of hospitals and locations with zero patients. This raises computational difficulties with the linear estimation techniques used previously. In this paper, we use data on patients undergoing cardiac catheterization in several market areas to assess alternative estimation techniques. First, we estimate the conditional choice model with the two techniques used previously to transform the non-linear choice model. These involve using as a reference (1) a single hospital, or (2) the geometric mean of all the hospitals in the market. When there are many zeros, these techniques require extensive adjustments to the data which may lead to biased estimators. We then compare these results with maximum likelihood estimates. The latter results are substantively and significantly different from those using traditional techniques. More importantly, the linear estimates are much more sensitive to the proportion of zeros. We thus conclude that maximum likelihood estimates are preferable when there are many zeros.

Market and Regulatory Influences on the Availability of Coronary Angioplasty and Bypass Surgery in U.S. Hospitals

Using 1983 data on 3720 nonfederal short-term hospitals, we analyzed the influence of local market competition and state regulatory programs on the availability of percutaneous transluminal coronary angioplasty and coronary-artery bypass surgery. The degree of competition for patients with heart disease was measured in terms of the number of hospitals in the local market area that maintained a cardiac catheterization laboratory or facility for open-heart surgery. When the patient case mix and the hospitals teaching role were controlled for, institutions with more than 20 competitors in the local area were 166 percent more likely to offer coronary angioplasty (P less than 0.0001) and 147 percent more likely to offer bypass surgery (P less than 0.0001) than hospitals with no competitors in the local market. Four fifths of the hospitals performing bypass surgery whose annual volume was less than 200 had one or more neighboring hospitals with a facility for open-heart surgery. State rate-regulation programs in New York, New Jersey, Connecticut, Massachusetts, and Maryland significantly reduced the availability of both procedures, with the greatest regulatory effects being observed in the most competitive hospital markets. We conclude that in the period under consideration, competition encouraged and regulation discouraged the proliferation of these cardiac services.

Developing and evaluating performance measures for ambulatory care quality: a preliminary report of the DEMPAQ project.

Because of the focus on technical quality, the content of the DEMPAQ performance measures is clinically detailed and oriented toward processes of care relevant to the everyday practice of medicine in the ambulatory setting. This emphasis is crucial if the performance measures are to be useful to practicing physicians.

Selecting data sources for substance abuse services research.

In this article we discuss the strengths and weaknesses of using different types of data sources for alcohol and drug abuse services research. To do this, we describe four types of data sources used in substance abuse services research: surveys of organizations, medical records, claim and encounter data and program-level administrative data. For each, we outline where to obtain data, how each type has been used, and the advantages and challenges. This overview should allow investigators to think more critically about the datasets they now use; providers to understand the types of data sources most appropriate for specific research questions so as to participate more fully in research; and policy makers to interpret correctly results based on different types of data. Moreover, it should foster better communication among these stakeholders in collaborative projects to improve the effectiveness of services for people with addictions.

Designing and using measures of quality based on physician office records

This article presents our principles for developing performance measures to assess the quality of ambulatory care. The measures were developed as part of a project for developing and evaluating methods to promote ambulatory care quality (DEMPAQ). We describe our design for the performance measures, present examples of the DEMPAQ review criteria, and show the formats we used to feed back information to physicians. We conclude by presenting the results of our appralsal of the performance measures showing how evaluation can aid in the interpretation of measurement findings.

Developing a Quality Improvement Database Using Health Insurance Data: A Guided Tour with Application to Medicare's National Claims History File

Health policy researchers are increasingly turning to insurance claims to provide timely information on cost, utilization, and quality trends in health care markets. This research offers an in-depth description of how to systematically transform raw inpatient and ambulatory claims data into useful information for health care management and research using the Health Care Financing Administrations National Claims History file as an example. The topics covered include: (a) understanding the contents and architecture of claims data, (b) creating analytic files from raw claims, (c) technical innovations for health policy studies, (d) assessing data accuracy, (d) the costs of using claims data, and (e) ensuring confidentiality. In summary, claims data are found to have great potential for quality of care analysis. As in any analysis, careful development of a database is required for scientific research. The methods outlined in this study offer health data novices as well as experienced analysts a series of strategies to maximize the value of claims data for health policy analysis.