Modeling for health care and other policy decisions: uses, roles, and validity.

The role of models to support recommendations on the cost-effective use of medical technologies and pharmaceuticals is controversial. At the heart of the controversy is the degree to which experimental or other empirical evidence should be required prior to model use. The controversy stems in part from a misconception that the role of models is to establish truth rather than to guide clinical and policy decisions. In other domains of public policy that involve human life and health, such as environmental protection and defense strategy, models are generally accepted as decision aids, and many models have been formally incorporated into regulatory processes and governmental decision making. We formulate an analytical framework for evaluating the role of models as aids to decision making. Implications for the implementation of Section 114 of the Food and Drug Administration Modernization Act (FDAMA) are derived from this framework.

An off-the-shelf help list: a comprehensive catalog of preference scores from published cost-utility analyses.

PURPOSE: The Panel on Cost-Effectiveness in Health and Medicine recommends an organized collection of preference measure values for health states that can be used in costutility analyses (CUAs). The authors sought to construct a catalog of preference scores from published CUAs, organize the catalog by clinical categories, and identify methods of preference score assessment. METHOD: The authors systematically searched Medline and other databases to identify original CUAs published through 1997. Information was abstracted on the health state descriptions, corresponding preference scores, method of preference score elicitation, and the source of the estimate. RESULTS: Two hundred twenty-eight CUAs were appraised. The authors found 949 health states and corresponding preference scores. Most frequently, health states pertained to the circulatory system (21.7%), health states were valued by experts (35.8%), and values were derived through community-based preference scores (23.5%). CONCLUSION: A catalog of preference scores for health states can be constructed. The catalog (http://www.hsph.harvard.edu/organizations/hcra/cuadatabase/ intro.html) may provide a useful reference tool for producers and consumers of CUAs but also underscores the methodologic variation and inconsistencies present in the field.

A comparison of HUI2 and HUI3 utility scores in Alzheimer's disease.

PURPOSE: The Health Utilities Index (HUI) is a generic, multiattribute, preference-based health-status classification system. The HUI Mark 3 (HUI3) differs from the earlier HUI2 by modifying attributes and allowing more flexibility for capturing high levels of impairment. The authors compared HUI2 and HUI3 scores of patients with Alzheimer's disease (AD) and caregivers, and contrasted results of a cost-effectiveness analysis of new drugs for AD using the two systems. METHODS: In a cross-sectional study of 679 AD patient/caregiver pairs, stratified by patient's disease stage (questionable/mild/moderate/severe/profound/terminal) and setting (community/assisted living/nursing home), caregivers completed the combined HUI2/HUI3 questionnaire as proxy respondents for patients and for themselves. RESULTS: Mean (SD) global utility scores for patients were lower on the HUI3 (0.22[0.26]) than on the HUI2 (0.53 [0.21]). Patient HUI3 utility scores ranged from 0.47(0.24) for questionable AD to -0.23 (0.08) for terminal AD, compared with a range of 0.73 (0.15) to 0.14 (0.07) for the HUI2. Among the 203 patients in the severe, profound, and terminal stages, 96 (48%) had negative global HUI3 utility scores, while none had a negative HUI2 score. The utility scores for caregivers were similar on the HUI3 (0.87 [0.14]) and HUI2 (0.87 [0.11]). Cost-effectiveness analysis of a new medication to treat AD showed somewhat more favorable results using the HUI3. CONCLUSIONS: The HUI2 and HUI3 discriminate well across AD stages. Compared with the HUI2, the HUI3 yields lower global utility scores for patients with AD, and more scores for states judged worse than dead. The HUI3 may yield substantially different results from the HUI2, particularly for persons who have serious cognitive impairments such as AD.

A comprehensive league table of cost-utility ratios and a sub-table of "panel-worthy" studies.

OBJECTIVES: The authors compiled a comprehensive league table of cost/QALY ratios, and a standardized table of analyses satisfying selected Reference Case criteria from the USPHS Panel on Cost-Effectiveness in Health and Medicine. METHODS: They identified 228 cost-utility analyses (CUAs) through literature searches, and abstracted data on methods and cost-utility ratios. The subset of "Panel-worthy" analyses used: a societal or broad health-care perspective, community or patient preference weights, net costs, incremental comparisons, and discounting of costs and QALYs. RESULTS: The 228 CUAs included ratios for 647 interventions, ranging from cost-saving to $52,000,000/QALY (median = $12,000/QALY). The standardized table presents 112 ratios that met the "Panel-worthy" criteria, with articles published in recent years more likely to meet all of the criteria. CONCLUSIONS: The comprehensive league table (available on the Web) provides a useful reference, but ratios may not be comparable because of methodologic variations. The standardized table focuses on studies meeting basic methodologic criteria, potentially allowing for better comparison with future Reference Case analyses. Future studies should investigate the quality of analyses' underlying assumptions in addition to whether certain key procedural protocols were met.

Systematic overview of cost-utility assessments in oncology.

PURPOSE: Cost-utility analyses (CUAs) present the value of an intervention as the ratio of its incremental cost divided by its incremental survival benefit, with survival weighted by utilities to produce quality-adjusted life years (QALYs). We critically reviewed the CUA literature and its role in informing clinical oncology practice, research priorities, and policy. METHODS: The English-language literature was searched between 1975 and1997 for CUAs. Two readers abstracted from each article descriptions of the clinical situation and patients, the methods used, study perspective, the measures of effectiveness, costs included, discounting, and whether sensitivity analyses were performed. The readers then made subjective quality assessments. We also extracted utility values from the reviewed papers, along with information on how and from whom utilities were measured. RESULTS: Our search yielded 40 studies, which described 263 health states and presented 89 cost-utility ratios. Both the number and quality of studies increased over time. However, many studies are at variance with current standards. Only 20% of studies took a societal perspective, more than a third failed to discount both the costs and QALYs, and utilities were often simply estimates from the investigators or other physicians. CONCLUSION: The cost-utility literature in oncology is not large but is rapidly expanding. There remains much room for improvement in the methodological rigor with which utilities are measured. Considering quality-of-life effects by incorporating utilities into economic studies is particularly important in oncology, where many therapies obtain modest improvements in response or survival at the expense of nontrivial toxicity.

The quality of reporting in published cost-utility analyses, 1976-1997.

PURPOSE: Cost-utility analysis is a type of cost-effectiveness analysis in which health effects are measured in terms of quality-adjusted life-years (QALYs) gained. Such analyses have become popular for examining the health and economic consequences of health and medical interventions, and they have been recommended by leaders in the field. These recommendations emphasize the importance of good reporting practices. This study determined 1) the quality of reporting in published cost-utility analyses through 1997 and 2) whether reporting practices have improved over time. We examined quality of reporting by journal type and number of cost-utility analyses a journal has published. DATA SOURCES: Computerized databases were searched through 1997 for the Medical Subject Headings or text keywords quality-adjusted, QALY, and cost-utility analysis. Published bibliographies of the field were also searched. STUDY SELECTION: Original cost-utility analyses written in English were included. Cost-effectiveness analyses that measured health effects in units other than QALYs and review, editorial, or methodologic articles were excluded. DATA EXTRACTION: Each of the 228 articles found was audited independently by two trained readers who used a standard data collection form to determine the quality of reporting in several categories: disclosure of funding, framing, reporting of costs, reporting of preference weights, reporting of results, and discussion. RESULTS: The number of cost-utility analyses in the medical literature increased greatly between 1976 and 1997. Analyses covered a wide range of diseases and interventions. Most studies listed modeling assumptions (82%), described the comparator intervention (83%), reported sensitivity analysis (89%), and noted study limitations (84%). Only 52% clearly stated the study perspective; 34% did not disclose the funding source. Methods of reporting costs and preference weights varied widely. The quality of published analyses improved slightly over time and was higher in general clinical journals and in journals that published more of these analyses. CONCLUSIONS: The study results reveal an active and evolving field but also underscore the need for more consistency and clarity in reporting. Better peer review and independent, third-party audits may help in this regard. Future investigations should examine the quality of clinical and economic assumptions used in cost-utility analyses, in addition to whether analysts followed recommended protocols for performance and reporting.

Measuring costs in cost-utility analyses. Variations in the literature.

OBJECTIVES: Although cost-utility analysis (CUA) has been recommended by some experts as the preferred technique for economic evaluation, there is controversy regarding what costs should be included and how they should be measured. The purpose of this study was to: a) identify the cost components that have been included in published CUAs; b) catalogue the sources of valuation used; c) examine the methods employed for estimating costs; and d) explore whether methods have changed over time. METHODS: We conducted a comprehensive search of the published literature and systematically collected data on the cost estimation of CUAs. We audited the cost estimates in 228 CUAs. RESULTS: In most studies (99%), analysts included some direct healthcare costs. However, the inclusion of direct non-healthcare and time costs (17%) was generally lacking, as was productivity costs (8%). Only 6% of studies considered future costs in added life-years. In general, we found little evidence of change in methods over time. The most frequently used source for valuation of healthcare services was published estimates (73%). Few studies obtained utilization data from RCTs (10%) or relied on other primary data (23%). About two-thirds of studies conducted sensitivity analyses on cost estimates. CONCLUSIONS: We found wide variations in the estimation of costs in published CUAs. The study underscores the need for more uniformity and transparency in the field, and continued vigilance over cost estimates in CUAs on the part of analysts, reviewers, and journal editors.

Are pharmaceuticals cost-effective? A review of the evidence.

The argument that prescription drugs are cost-effective has been made both by the pharmaceutical industry to support rising drug prices and expenditures, and by advocates of expanded drug coverage for elderly and low-income persons. A new database of 228 published cost-utility analyses sheds light on the issue. According to published data, some drugs do save money or are cost-effective, but the issue depends critically on the context in which the drug is used and the intervention with which it is compared. Cost-utility analyses funded by the drug industry tend to report more favorable results than do those funded by nonindustry sources. Cost-effectiveness analysis can help policymakers to determine whether drugs and other interventions offer value for money.