Using cost-effectiveness league tables to compare interventions to prevent sexual transmission of HIV

Abstract

Cost-effectiveness information is needed to help public health decision makers choose between competing HIV prevention programs. One way to organize this information is in a 'league table' that lists cost-effectiveness ratios for different interventions and which facilitates comparisons across interventions. Herein we propose a common outcome measure for use in HIV prevention league tables and present a preliminary league table of interventions to reduce sexual transmission of HIV in the US. Fifteen studies encompassing 29 intervention for different population groups are included in the table. Approximately half of the interventions are cost-saving (i.e. save society money, in the long run), and three-quarters are cost-effective by conventional standards. We discuss the utility of such a table for informing the HIV prevention resource allocation process and delineate some of the difficulties associated with the league table approach, especially as applied to HIV prevention cost-effectiveness analysis.

What Works, and What Remains to Be Done, in Hiv Prevention in the United States

“…As of August 2004, the literature on economic evaluation of HIV prevention had grown to over 140 articles. Many types of HIV prevention interventions discussed above have now been subjected to cost-effectiveness analyses and have been found to be either cost-saving or cost-effective relative to other life-saving interventions in public health and medicine [for reviews see (44,50)]. Cost-saving interventions are those for which the costs-often medical costs-averted by a prevention program outweigh the cost of prevention service delivery; cost-effective interventions do not actually save public money but the cost-per-quality-adjust-life-year-saved is considered reasonable relative to other readily accepted medical and public health interventions.…”

When there is too much to do

“…Formal cost-effectiveness analyses have sometimes been used in an attempt to identify clinical priorities; 16,23 however, conducting explicit cost-effectiveness analyses is time consuming and sometimes is not feasible (because of deficiencies in the available evidence). Further, when the results of cost-effectiveness analyses vary substantially with sensitivity analyses, there is no established way to simultaneously convey the importance of the estimated absolute risk reduction (if true) and our confidence that the estimate is true.…”

“…However, in the short run, we need to understand, and in some cases modify, the priorities that providers bring to clinical encounters so as to ensure that the most important interventions are not lost amid the blizzard of demands on patients' and providers' time and energy. There have been numerous attempts to develop prioritization schemes for health interventions, usually using economic cost-effectiveness models, as part of population-level resource allocation decisions, [16][17][18][19][20][21][22][23] perhaps most famously the controversial Oregon Basic Health Services Act. 24,25 Despite the controversy that surrounds some of these efforts, Coffield et al argue that while all of interventions supported by evidence might be desirable, prioritization can allow for efficient step-by-step improvement in population health by devoting quality improvement resources to those interventions that have the greatest impact and value.…”

The Role of Quantitative Policy Analysis in HIV Prevention Technology Transfer

“…[15][16][17][18][19][20][21] Examples of these analytic techniques include research synthesis and meta-analysis, 21 decision analysis, 19,20 multi-attribute utility analysis (a decision analytic tool that incorporates consideration of multiple dimensions within one decision analysis), 20 and economic evaluation methods (including cost, cost-effectiveness-especially costutility analysis-and threshold analysis). 11,16,18,19 The solid gray arrow in the Figure represents an important bi-directional dialogue between scientists and policy analysts (of course, policy analysis is a branch of science but we use the terms "scientists" and "policy analysts" distinctly here solely for ease of exposition). This dialogue fosters the conduct of research and the packaging of scientific information suitable for inclusion in policy analyses.…”

“…15,16 This is likely due, in part, to the fact that there is no published framework for incorporating policy analytic information (including cost and cost-effectiveness analytic) in technology transfer efforts.…”