Spurred by demands for data from employer-purchasers and accreditation agencies and the adoption of strategies for disease management and outcome-based quality assurance, managed care organizations have recognized the need for rapid, convenient access to clinical information. Large investments in administrative and clinical data systems have also produced unprecedented opportunities for research on health care and epidemiology in large, defined populations. There is a long history of contributions to research by investigators who are based in the older nonprofit group and staff models of health maintenance organizations (HMOs). Many of these organizations maintain research units that are primarily funded by outside sources. Research includes descriptive and etiologic studies of epidemiology, randomized and observational studies of the effectiveness of treatment regimens, studies of disease costs and estimation of cost-effectiveness, investigations of risk predictions in populations, of risk and changes in organizational behavior, and evaluations of interventions to alter physician and patient behavior. The work is often conducted in collaboration with academic researchers. The HMO Research Network has recently been established to foster a scientific exchange among HMO-based researchers. As managed care organizations come to provide health care coverage to most U.S. citizens, research conducted by these organizations increasingly overlaps with public health research. Collaboration between HMO-based research centers and researchers from academia and government will undoubtedly continue to increase.

Administrative policies and programs play an important and growing role as determinants of the use of medical care. Although some policies and programs may be harmful or ineffectual, randomized, controlled trials or prospective evaluations are rarely done for political or logistic reasons. Most evaluations are retrospective and often use administrative databases. Major problems with such evaluations include poor data quality, lack of concurrent controls, inability to ascertain important study outcomes, and incomplete data on case mix. This article uses published evaluations to illustrate these problems and suggests strategies that can minimize their impact. Such strategies include thorough assessment of data quality, interrupted time-series or policy gradient analysis, restriction of studies to those clinical outcomes that reliably result in medical care, and use of data on medical encounters as surrogates for determining case mix. However, even when these strategies are used, adequate evaluation of the effects of many policies and programs may continue to be impossible. Prospective evaluations need to be used more frequently to ensure that changes are held to the same standard used for other therapeutic interventions.

Simulation models that support decision and cost-effectiveness analysis can further the goals of evidence-based medicine by facilitating the synthesis of information from several sources into a single comprehensive structure. The Stroke Prevention Policy Model (SPPM) performs this function for the clinical and policy questions that surround stroke prevention. This paper first describes the basic structure and functions of the SPPM, concentrating on the role of large databases (broadly defined as any database that contains many patients, regardless of study design) in providing the SPPM inputs. Next, recognizing that the use of modeling continues to be a source of some controversy in the medical community, it discusses the philosophical underpinnings of the SPPM. Finally, it discusses conclusions in the context of both stroke prevention and other complex medical decisions. We conclude that despite the difficulties in developing comprehensive models (for example, the length and complexity of model development and validation processes, the proprietary nature of data sources, and the necessity for developing new software), the benefits of such models exceed the costs of continuing to rely on more conventional methods. Although they should not replace the clinician in decision making, comprehensive models based on the best available evidence from large databases can support decision making in medicine.

Physicians must decide when the evidence is sufficient to adopt a new clinical policy. Analysis of large clinical and administrative databases is becoming an important source of evidence for changing clinical policies. Because such analysis cannot control for the effects of all potential confounding variables, physicians risk drawing the wrong conclusion about the cause-and-effect relation between a change in clinical policy and outcomes. Randomized studies offer protection against drawing a conclusion that would lead to adoption of an inferior policy. However, a randomized study may be difficult to justify because of the extra costs of collecting data for a randomized study and concerns that a study will not directly benefit the patients enrolled in the study. This article reviews the advantages and disadvantages of basing clinical policy on analysis of large databases compared with conducting a randomized study. A technique is described and illustrated for accessing the potential costs and benefits of conducting such a study. This type of analysis formed the basis for a physician-managed health care organization deciding to sponsor a randomized study among patients with end-stage renal disease as part of a quality-improvement initiative.

Administrative records from the Medicare Program of the Health Care Financing Administration provide a valuable source of information for research on medical and public policy issues. This administrative database contains information on utilization of covered medical services, diagnoses, episodes of illness, and Medicare-covered costs of health care. Combining such data with information from national surveys on health status, demographics, and socioeconomic attributes substantially expands the scope of potential research questions that can be addressed. This article discusses the benefits and difficulties of linking Medicare administrative data with survey data and provides brief summaries of five national surveys of elderly U.S. citizens. These surveys can be valuable resources for examining the health status and life experiences of the Medicare population.

During the early 1990s, the U.S. government addressed the issue of providing universal health care to all its citizens. Although this issue has not been completely resolved, centralization of electronic data and sharing of health care information among insurers and providers have been pursued. The emergence of electronic data banks in health care has raised another issue: each citizen's right to privacy compared with the collective benefit to society when critical data on quality assurance and scientific research are shared by an array of network users. The choices we face are difficult, and the solution may necessarily reflect a compromise that alters traditional beliefs in the right to personal privacy. However, Congress can take the initiative by enacting statutes to ensure that sensitive information contained in electronic patient records is not divulged without a patient's consent and is protected against fraudulent access and abuse.

Administrative data result from administering health care delivery, enrolling members into health insurance plans, and reimbursing for services. The primary producers of administrative data are the federal government, state governments, and private health care insurers. Although the clinical content of administrative data includes only the demographic characteristics and diagnoses of patients and codes for procedures, these data are often used to evaluate the quality of health care. Administrative data are readily available, are inexpensive to acquire, are computer readable, and typically encompass large populations. They have identified startling practice variations across small geographic areas and-supported research about outcomes of care. Many hospital report cards (which compare patient mortality rates) and physician profiles (which compare resource consumption) are derived from administrative data. However, gaps in clinical information and the billing context compromise the ability to derive valid quality appraisals from administrative data. With some exceptions, administrative data allow limited insight into the quality of processes of care, errors of omission or commission, and the appropriateness of care. In addition, questions about the accuracy and completeness of administrative data abound. Current administrative data are probably most useful as screening tools that highlight areas in which quality should be investigated in greater depth. The growing availability of electronic clinical information will change the nature of administrative data in the future, enhancing opportunities for quality measurement.

A single point mutation in the gene coding for coagulation factor V results in a form of factor Va that is resistant to degradation by activated protein C and leads to a relative hypercoagulable state. This mutation, factor V Leiden, is found in 4% to 6% of the U.S. population.

Chronic hepatitis C is a major cause of illness and death in the United States. Interferon-alpha 2b can induce clinical, biochemical, and virologic remission in some patients with chronic hepatitis C, but the long-term cost-effectiveness of this treatment, particularly in patients with histologically mild disease, is unknown.

To review the available data on the treatment of chronic stable angina and formulate a rational approach to the use of pharmacologic therapy, percutaneous transluminal coronary angioplasty (PTCA), and coronary artery bypass graft surgery (CABG).

Stroke is a leading cause of death in the industrialized world, and hypercholesterolemia may be a risk factor for stroke.

Interleukin-6, an inflammatory cytokine, is characterized by pleiotropy and redundancy of action. Apart from its hematologic, immune, and hepatic effects, it has many endocrine and metabolic actions. Specifically, it is a potent stimulator of the hypothalamic-pituitary-adrenal axis and is under the tonic negative control of glucocorticoids. It acutely stimulates the secretion of growth hormone, inhibits thyroid-stimulating hormone secretion, and decreases serum lipid concentrations. Furthermore, it is secreted during stress and is positively controlled by catecholamines. Administration of interleukin-6 results in fever, anorexia, and fatigue. Elevated levels of circulating interleukin-6 have been seen in the steroid withdrawal syndrome and in the severe inflammatory, infectious, and traumatic states potentially associated with the inappropriate secretion of vasopressin. Levels of circulating interleukin-6 are also elevated in several inflammatory diseases, such as rheumatoid arthritis. Interleukin-6 is negatively controlled by estrogens and androgens, and it plays a central role in the pathogenesis of the osteoporosis seen in conditions characterized by increased bone resorption, such as sex-steroid deficiency and hyperparathyroidism. Overproduction of interleukin-6 may contribute to illness during aging and chronic stress. Finally, administration of recombinant human interleukin-6 may serve as a stimulation test for the integrity of the hypothalamic-pituitary-adrenal axis.

Hydroxyurea is an antineoplastic agent commonly used to treat myeloproliferative disorders and other nonneoplastic conditions.

Clinical software systems are becoming ubiquitous. A growing literature documents how these systems can improve health care delivery, but concerns about patient safety must now be formally addressed. In 1996, the U.S. Food and Drug Administration (FDA) called for discussions on regulation of software programs as medical devices. In response, a consortium of organizations dedicated to improving health care through information technology developed recommendations for the responsible regulation and monitoring of clinical software systems by users, vendors, and regulatory agencies. These recommendations were revised and approved by the American Medical informatics Association Public Policy Committee and Board. Other organizations reviewed, modified, and approved the recommendations, and the Boards of Directors of most of the organizations in the consortium endorsed the guidelines. The consortium proposes four categories of clinical system risk and four classes of monitoring and regulatory action that can be applied on the basis of the risk level. The consortium recommends that most clinical software systems be supervised locally and that developers of health care information systems adopt a code of good business practices. Budgetary and other constraints limit the type and number of systems that the FDA can regulate effectively; therefore, the FDA should exempt most clinical software systems and focus on systems that pose high clinical risk and provide limited opportunity for competent human intervention.

To determine the efficacy of somatostatin or octreotide for the treatment of acute nonvariceal upper gastrointestinal hemorrhage.

The increasing incidence and biological heterogeneity of ductal carcinoma in situ (DCIS) of the breast have made the management of this entity challenging and controversial. This paper reviews data on the natural history of the disease and results obtained with various management approaches.