With the increase in information derived from clinical research and technology, many in clinical medicine have adopted an evidence-based approach to inform treatment decisionmaking. Such a process forces the physician to obtain relevant scientific information (evidence) from a variety of sources including the patient, and to evaluate continually decisions made against patient health outcomes. Among the various proposed community-based health programs, how do foundations or health care systems decide which programs to fund? Can the evidence-based decisionmaking paradigm adopted by the clinical community support decisionmaking concerning community-based health programs? A literature review was conducted to ascertain what types of evidence concerning community-based health program effectiveness and costs were available. Focus groups and telephone interviews were conducted with persons involved in community-based health program funding decisions to learn how decisions were made and what types of information were used to support those decisions. While there was general support for using more evidence regarding program effectiveness and costs in making funding decisions about community-based programs, there was consensus that little evidence was readily available. There was also a widely held belief that funding decisions could (and should) also take into consideration issues beyond that which can be expressed as evidence. The report concludes with some suggestions regarding how health care systems and private funders can move toward an evidence-based approach to community-based program decisionmaking.
Table of Contents
An Evidence-Based Approach to Decisionmaking for Community Health Interventions
Is There Enough Evidence to Support an Evidence-Based Approach?
The View from Health Care Systems and Funders: Focus Groups
The View from Health Care Systems and Funders: Telephone Interviews
Toward an Evidence-Based Approach to Community Health Interventions
Focus Group Protocol: Funders
Telephone Interviews: Suggested Questions for Health Systems