Policy makers in the United States have increasingly recognized the deficiencies in information related to technology assessment and quality assessment. This growing consensus resulted in the passage of legislation in 1989 to create a new Agency for Health Care Policy and Research and to expand substantially funding for assessment activities.

The use of large data bases in technology assessment offers a number of attractive possibilities for the future. This article outlines the major approaches to technology assessment and how data bases can be used to enhance each approach.

This article describes the findings of an ongoing assessment of prostatectomy that relied on the use of administrative data bases. Examples of the use of claims data for monitoring outcomes and treatment comparisons are provided, as well as a discussion of the strengths and limitations of administrative data for technology assessment.

Large registries have been used by the National Heart, Lung, and Blood Institute to evaluate a number of medical procedures. Two of these, the Coronary Artery Surgery Study (CASS) and the Balloon Valvuloplasty Registry (BVR), are described to illustrate potential problems in using registry data to compare medical procedures.

Large data sets are an attractive source of information for outcome assessment, but their use involves certain problems and risks. Data base evaluations are retrospective and unblinded; they often represent the result of multiple analyses of multiple endpoints, and it is difficult to identify the procedures used and analytic choices made because critical details are often omitted. While data bases can suggest problems and offer answers, they cannot prove them; data base analyses must be followed by trials.

Modeling death rates has been suggested as a potential method to screen hospitals and identify superior and substandard providers. This article begins with a review of one hospital death rate study and focuses upon its findings and limitations. It also explores the inherent limitations in the use of large data sets to assess quality of care.

This article examines how large data sets can be used for evaluating the effects of health policy changes and for flagging providers with potential quality problems. An example is presented, illustrating how three risk-adjusted measures of hospital performance were developed using patient discharge abstracts. Advantages and disadvantage of this approach are discussed.

Numerous recent studies use risk-adjusted patient mortality rates to measure hospital performance, focusing on such hospital characteristics as volume of patients, teaching status, and ownership. This article summarizes the empirical findings of these studies, critiques their methods and models, and offers recommendations for overcoming several obstacles to meaningful correlation of patient outcomes and provider performance.

This review of the advantages (peaks) and problems (pits) of large data bases to study quality contrasts their suitability with randomized control trials. Researchers need to advise policymakers and others about when statistically significant differences in quality are also politically and socially significant and deserve responsible reactions.

This article discusses data that might be used for measuring quality of care, for health care administrative purposes, and for tracking the use of technologies. The advantages and limitations of administrative data banks for research purposes and some process-of-care and outcome analysis are noted. Three important obstacles to their use—reliability of diagnosis and service information, unique patient identifiers, and provider identifiers—are discussed briefly.

Diagnostic information within administrative data bases is generally in the form of lnternational Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. The purpose of this article is to introduce ICD-9-CM, to review its strengths and limitations, and to suggest ways that it can be used through administrative files for assessing the quality of hospital care.

Despite their potential utility, clinicians are skeptical about claims data as a substrate for clinical research. Clinicians' concerns are centered on two issues—the quality of the data and the fairness of comparisons that are made. To increase the impact of claims data research on clinical practice, several strategies should be pursued.

The implications of effectiveness research are far-reaching. Thus, the specification of a broad research agenda and the soundness of the underlying research methodologies and data bases are critical. This article discusses the quality of administrative data and the infrastructure supporting an ongoing effectiveness research effort.

The discussion of the effectiveness of the use of large bases for technology and quality assessments in health care is important to policy makers because of their increasing concern about the value of the dollars spent on health care. The focus on value is particularly acute for those policy makers having responsibility for the Medicare program. Recognizing that knowledge regarding medical outcomes will be imperfact, nevertheless, they have put the wheels in motion to empand research in this area beyond clinical trials.

As prefigured in the Greek tragedy Antigone, one of the primary conflicts in contemporary health care is that between humane concern for the individual and concern for society at large and administrative rules. The computerization of the health care system and development of large data bases will create new forms of this conflict that will challenge the self-definition of health care and health care professionals.

Ernest Amory Codman, M.D., was one of the most important figures in the history of outcomes research in medicine. While his contemporaries scorned his efforts to create systematic procedures to evaluate the end results of medical care, his work foreshadowed many of today's most pressing issues in technology assessment. This arti traces Codman's career as an innovator and political gadfly at the Massachusetts General Hospital during the first three decades of this century, and examines the development and demise of his end-result system.

The focus of this article is on contemporary roots of medical care quality measurement, while it also examines some of the most important historical precedents. Specifically, it singles out Dr. Ernest Avery Codman and his early 20th-century work emphasizing the assessment of outcome as the paramount indicator of medical care quality. The standard that he set for himself and others is the one that late 20th-century researchers must uphold, and to which we must answer.

Health outcome assessment may be used for a variety of purposes: to evaluate the effectiveness of medical practices: to assess the quality of services provided; to educate providers, purchasers, and users of health services about the sequelae of treated and untreated disease; to guide reimbursement and regulatory policy; and to characterize the health status of a population. This article focuses on the use of health outcomes to evaluate the effectiveness of medical practices and to assess the quality of services provided.