Louise B. Russell

Cost-effectiveness in health and medicine

1. Cost-Effectiveness Analysis as a Guide to Resource Allocation in Health: Roles and Limitations 2. Theoretical Foundations of Cost-Effectiveness Analysis 3. Framing and Designing the Cost-Effectiveness Analysis 4. Identifying and Valuing Outcomes 5. Assessing the Effectiveness of Health Interventions 6. Estimating Costs in Cost-Effectiveness Analysis 7. Time Preference 8. Reflecting Uncertainty in Cost-Effectiveness Analysis 9. Reporting Cost-Effectiveness Studies and Results Appendix A: Summary of Recommendations for the Reference Case Appendix B: Cost-Effectiveness of Strategies to Prevent Neural Tube Defects Appendix C: The Cost-Effectiveness of Dietary and Pharmacologic Therapy for Cholesterol Reduction in Adults

Guidelines for Pharmacoeconomic Studies

SummaryThis article reports the recommendations of the Panel on Cost Effectiveness in Health and Medicine, sponsored by the US Public Health Service, on standardised methods for conducting cost-effectiveness analyses. Although not expressly directed at analyses of pharmaceutical agents, the Panel’s recommendations are relevant to pharmacoeconomic studies.The Panel outlines a ‘Reference Case’ set of methodological practices to improve quality and comparability of analyses. Designed for studies that inform resource-allocation decisions, the Reference Case includes recommendations for study framing and scope, components of the numerator and denominator of cost-effectiveness ratios, discounting, handling uncertainty and reporting.The Reference Case analysis is conducted from the societal perspective, and includes all effects of interventions on resource use and health. Resource use includes ‘time’ resources, such as for caregiving or undergoing an intervention. The quality-adjusted life-year (QALY) is the common measure of health effect across Reference Case studies. Although the Panel does not endorse a measure for obtaining quality-of-life weights, several recommendations address the QALY. The Panel recommends a 3% discount rate for costs and health effects.Pharmacoeconomic studies have burgeoned in recent years. The Reference Case analysis will improve study quality and usability, and permit comparison of pharmaceuticals with other health interventions.

Conceptualizing a Model A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force–2

The appropriate development of a model begins with understanding the problem that is being represented. The aim of this article is to provide a series of consensus-based best practices regarding the process of model conceptualization. For the purpose of this series of papers, the authors consider the development of models whose purpose is to inform medical decisions and health-related resource allocation questions. They specifically divide the conceptualization process into two distinct components: the conceptualization of the problem, which converts knowledge of the health care process or decision into a representation of the problem, followed by the conceptualization of the model itself, which matches the attributes and characteristics of a particular modeling type to the needs of the problem being represented. Recommendations are made regarding the structure of the modeling team, agreement on the statement of the problem, the structure, perspective and target population of the model, and the interventions and outcomes represented. Best practices relating to the specific characteristics of model structure, and which characteristics of the problem might be most easily represented in a specific modeling method, are presented. Each section contains a number of recommendations that were iterated among the authors, as well as the wider modeling taskforce, jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.

Preventing Chronic Disease: An Important Investment, But Don’t Count On Cost Savings

Over the four decades since cost-effectiveness analysis was first applied to health and medicine, hundreds of studies have shown that prevention usually adds to medical costs instead of reducing them. Medications for hypertension and elevated cholesterol, diet and exercise to prevent diabetes, and screening and early treatment for cancer all add more to medical costs than they save. Careful choices about frequency, groups to target, and component costs can increase the likelihood that interventions will be highly cost-effective or even cost-saving.

The cost-effectiveness of autologous transfusion revisited : implications of an increased risk of bacterialinfection with allogeneic transfusion

BACKGROUND: Previous analyses have found autologous transfusion to be very expensive but have not considered avoidance of postoperative bacterial infections as one of its benefits.

Conceptualizing a Model: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-2

The appropriate development of a model begins with understanding the problem that is being represented. The aim of this article was to provide a series of consensus-based best practices regarding the process of model conceptualization. For the purpose of this series of articles, we consider the development of models whose purpose is to inform medical decisions and health-related resource allocation questions. We specifically divide the conceptualization process into two distinct components: the conceptualization of the problem, which converts knowledge of the health care process or decision into a representation of the problem, followed by the conceptualization of the model itself, which matches the attributes and characteristics of a particular modeling type with the needs of the problem being represented. Recommendations are made regarding the structure of the modeling team, agreement on the statement of the problem, the structure, perspective, and target population of the model, and the interventions and outcomes represented. Best practices relating to the specific characteristics of model structure and which characteristics of the problem might be most easily represented in a specific modeling method are presented. Each section contains a number of recommendations that were iterated among the authors, as well as among the wider modeling taskforce, jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.

The Effect of Prospective Payment on Medicare Expenditures

Medicares prospective payment system was introduced in 1983 to slow the growth of expenditures for hospital care, which from the bulk of Medicare costs. Instead of reimbursing hospitals for the actual costs of patient care, the system pays them at fixed rates for each admission. In this study, we estimated the savings to Medicare from the use of prospective payment. We analyzed the expenditure projections published in 10 successive annual reports (1979 to 1988) by the trustees of the federal Hospital Insurance Trust Fund, which pays hospital bills for Medicare beneficiaries. To show the effect of prospective payment, these projections were adjusted to correct for the different assumptions about inflation and admissions made in each report. We also examined trends in expenditures from the Supplementary Medical Insurance Trust Fund, which pays for outpatient services, to see whether the savings in hospital expenses were offset by higher spending for out-of-hospital services. We found that prospective payment has reduced Medicares hospital costs substantially. Expenditures from the Hospital Insurance Trust Fund for 1990 are expected to be +12 billion less in 1980 dollars, and +18 billion in 1990 dollars, than was expected shortly before prospective payment went into effect--the equivalent of a savings of approximately 20 percent. By contrast, the effect of prospective payment on the supplementary fund has not been great. We conclude that the prospective payment system is having a major impact on Medicares hospital expenditures and that the savings is not offset by an increase in outpatient expenditures.

Assessing the effectiveness of health interventions for cost-effectiveness analysis

Cost-effectiveness analysis (CEA) is an analytic tool in which the costs and effects of an intervention designed to prevent, diagnose, or treat disease are calculated and compared with an alternative strategy to achieve the same goals. The results of a CEA are presented as a ratio of costs to effects, where the effects are health outcomes such as cases of disease prevented, years of life gained, or quality-adjusted life years gained, rather than monetary measures, as in cost-benefit analysis. Conducting a CEA requires a framework for portraying the cascade of events that occur as a consequence of the decision to intervene, for describing the probability that each event will occur, for accounting how long each event will last, and describing how much each event costs and is valued by the population or individuals targeted by the intervention. Mathematical models are well suited to these purposes. The purpose of this article is to provide an overview of modeling to estimate net effectiveness in a CEA (the difference in effectiveness between an intervention and the alternative to which it is being compared). Many of the principles described for estimating effectiveness apply equally to determining costs in a CEA. The main difference is that health events are weighted by costs in the numerator of the cost-effectiveness ratio, while they are often weighted by preference values in the denominator. Preference values, or utilities, reflect the fact that individuals or populations with similar ability (or disability) to function may regard that level of functioning differently. When preferences are incorporated into CEAs, the results are generally expressed as costs per quality-adjusted life years.1,2 A discussion of measurement of costs and valuing outcomes is beyond the scope of this article; for further information on these, and other components of a CEA, the reader is referred elsewhere.3–5 Following some definitions of terms, this article is organized into two sections describing the process of estimating effectiveness in a CEA: the first presents a review of the sources of event probabilities, and the second describes the use of modeling to estimate effectiveness.

Patient time requirements for screening colonoscopy

OBJECTIVE:To measure the amount of time patients spend in the screening colonoscopy process.METHODS:We recruited patients from a university endoscopy center scheduled to undergo screening colonoscopy. Participants completed a time diary for the screening colonoscopy process to account for time spent in preparation, travel, waiting, colonoscopy, and recovery.RESULTS:A total of 110 subjects completed the study. The sample was 57% female, 85% white, and 90% insured (40% Medicare, 4% Medicaid). Patients spent a median of about 21 h in the screening colonoscopy process for preparation, travel, waiting, colonoscopy, and onsite recovery. They invested a median of 16.5 h in preparation, 1.1 h traveling, 1.4 h waiting, 12 minutes for sedation, and 20 minutes for colonoscopy. Median time spent at the endoscopy center was 2.8 h. Median onsite recovery time was 47 minutes. Median time from the completion of the colonoscopy procedure until returning to routine activities was 17.7 h. Median time from the completion of the colonoscopy procedure until feeling completely back to normal was 19.9 h. Patient time requirements were sensitive to having a history of depression, type of person accompanying the patient, income, and employment status.CONCLUSIONS: Screening colonoscopy requires a substantial commitment of time. A small portion of that time is spent at the endoscopy center or having the colonoscopy. The majority of that time is spent in preparation and recovery. Time is a potential barrier to screening, but advances in preparation and sedation practices could reduce the time required for patients.

Completing Costs Patients' Time

Objectives:To show the importance of patients’ time as a cost of health and medical care and to explain how to include it in costing studies without greatly increasing the work required for such studies. Background:Despite the decade-old recommendation of the Panel on Cost-Effectiveness in Health and Medicine, patients’ time is rarely included in costing or cost-effectiveness analyses (CEAs). Studies of cancer care, smoking cessation, and diabetes self-management show that it can be a large part of an intervention’s costs, sometimes larger than direct medical costs, and can potentially affect patients’ willingness to undertake the intervention. Measuring and Valuing Time:Good costing practice follows 2 principles: measure all important uses of a resource; and value it appropriately and in a way that is consistent with the valuation of other resources. Counts of formal medical services, already measured in most studies, can serve as the starting point for valuing patients’ time, and would be a major step toward recognizing time costs, even when analysts cannot measure other uses of time. The concept of opportunity cost, often approximated by a market price, is the basis for valuing all resources. The reasons why the wage is a reasonable proxy for the value patients place on their own time are explained. Wage data are well measured and readily available. Conclusions:Ignoring patients’ time underestimates disease burden and biases cost-effectiveness results toward interventions that use more time. The tools and data to include patients’ time are available and will improve if they are routinely used.