{"title":"确定目标人群,以满足决策者的需求。","authors":"Jennifer L Lund, Anthony A Matthews","doi":"10.1093/aje/kwae129","DOIUrl":null,"url":null,"abstract":"<p><p>Randomized trials estimate the average treatment effect within individuals who are eligible, invited, and agree to enroll. However, decision-makers often require evidence that extends beyond the trial's enrolled population to inform policy or actions for their specific target population. Each decision-maker has distinct target populations, the composition of which may not often align with that of the trial population. As researchers, we should identify a decision-maker for whom we aim to generate evidence early in the research process. We can then specify a target population of their interest and determine if a policy or action can be informed using results from a trial alone, or if additional complementary real-world data and analysis are required. In this commentary, we outline 5 key groupings of decision-makers: policymakers, payers, purchasers, providers, and patients. We then specify relevant target populations for decision-makers interested in the effectiveness of beta-blockers after a myocardial infarction with preserved ejection fraction. Finally, we summarize the scenarios in which results from a randomized trial may or may not apply to these target populations and suggest relevant analytic approaches that can generate evidence to better align with a decision-maker's needs. This article is part of a Special Collection on Pharmacoepidemiology.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":null,"pages":null},"PeriodicalIF":5.0000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11538562/pdf/","citationCount":"0","resultStr":"{\"title\":\"Identifying target populations to align with decision-makers' needs.\",\"authors\":\"Jennifer L Lund, Anthony A Matthews\",\"doi\":\"10.1093/aje/kwae129\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Randomized trials estimate the average treatment effect within individuals who are eligible, invited, and agree to enroll. However, decision-makers often require evidence that extends beyond the trial's enrolled population to inform policy or actions for their specific target population. Each decision-maker has distinct target populations, the composition of which may not often align with that of the trial population. As researchers, we should identify a decision-maker for whom we aim to generate evidence early in the research process. We can then specify a target population of their interest and determine if a policy or action can be informed using results from a trial alone, or if additional complementary real-world data and analysis are required. In this commentary, we outline 5 key groupings of decision-makers: policymakers, payers, purchasers, providers, and patients. We then specify relevant target populations for decision-makers interested in the effectiveness of beta-blockers after a myocardial infarction with preserved ejection fraction. Finally, we summarize the scenarios in which results from a randomized trial may or may not apply to these target populations and suggest relevant analytic approaches that can generate evidence to better align with a decision-maker's needs. This article is part of a Special Collection on Pharmacoepidemiology.</p>\",\"PeriodicalId\":7472,\"journal\":{\"name\":\"American journal of epidemiology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2024-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11538562/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American journal of epidemiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/aje/kwae129\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of epidemiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/aje/kwae129","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Identifying target populations to align with decision-makers' needs.
Randomized trials estimate the average treatment effect within individuals who are eligible, invited, and agree to enroll. However, decision-makers often require evidence that extends beyond the trial's enrolled population to inform policy or actions for their specific target population. Each decision-maker has distinct target populations, the composition of which may not often align with that of the trial population. As researchers, we should identify a decision-maker for whom we aim to generate evidence early in the research process. We can then specify a target population of their interest and determine if a policy or action can be informed using results from a trial alone, or if additional complementary real-world data and analysis are required. In this commentary, we outline 5 key groupings of decision-makers: policymakers, payers, purchasers, providers, and patients. We then specify relevant target populations for decision-makers interested in the effectiveness of beta-blockers after a myocardial infarction with preserved ejection fraction. Finally, we summarize the scenarios in which results from a randomized trial may or may not apply to these target populations and suggest relevant analytic approaches that can generate evidence to better align with a decision-maker's needs. This article is part of a Special Collection on Pharmacoepidemiology.
期刊介绍:
The American Journal of Epidemiology is the oldest and one of the premier epidemiologic journals devoted to the publication of empirical research findings, opinion pieces, and methodological developments in the field of epidemiologic research.
It is a peer-reviewed journal aimed at both fellow epidemiologists and those who use epidemiologic data, including public health workers and clinicians.