Merlin Tracy L, Hiller Janet E, Ryan Philip
Adelaide Health Technology Assessment, School of Public Health, University of Adelaide, Adelaide, South Australia, Australia (TLM).
Faculty of Health Sciences, Swinburne University, Melbourne, Victoria, Australia (JEH).
MDM Policy Pract. 2016 Oct 6;1(1):2381468316672465. doi: 10.1177/2381468316672465. eCollection 2016 Jul-Dec.
The linked evidence approach (LEA) is used in health technology assessment (HTA) to evaluate the clinical utility of new medical tests in the absence of direct trial evidence. To determine whether use of LEA affects decisions to publicly fund medical tests. Australian HTAs that evaluated medical tests before and after LEA was mandated (in 2005) were screened for eligibility. Data were extracted and the impact of LEA and other possible clinical predictors (selected a priori) on funding decisions was modelled. Regression diagnostics were performed to estimate model fit, model specification, and to inform model selection. The unit of analysis was per clinical indication for each new test, so analyses were adjusted for clustering. 83 HTAs (for 173 clinical indications) were eligible from the 259 screened. When health policy was compared before and after 2005, there was an 11% reduction in overall positive funding decisions, including a 25% decrease in "interim" (coverage with evidence development) funding decisions. The odds of obtaining interim funding reduced by 98% (odds ratio = 0.02, 95% confidence interval = 0.0005, 0.17), but there was no change in the direction of funding decisions (odds ratio = 1.36, 95% confidence interval = 0.62, 3.01). Across both time periods, when LEA was used there was a very strong likelihood that the medical test would not receive interim funding (χ = 12.63, df = 1, P = 0.001). For positive funding decisions, the strongest predictors were whether or not the new test would replace an existing test and whether the available evidence was limited. The use of LEA did not predict the direction of funding decisions. Application of the method did predict that a "coverage with evidence development" decision was unlikely. This suggests that LEA may reduce decision-maker uncertainty.
在卫生技术评估（HTA）中，当缺乏直接的试验证据时，会采用关联证据法（LEA）来评估新医学检测的临床效用。以确定使用LEA是否会影响公共资助医学检测的决策。对澳大利亚在LEA被强制要求使用（2005年）前后评估医学检测的HTA进行资格筛选。提取数据，并对LEA和其他可能的临床预测因素（事先选定）对资助决策的影响进行建模。进行回归诊断以估计模型拟合度、模型规范，并为模型选择提供依据。分析单位是每项新检测的每个临床适应症，因此分析针对聚类进行了调整。从筛选的259项中，有83项HTA（针对173个临床适应症）符合条件。比较2005年前后的卫生政策时，总体阳性资助决策减少了11%，包括“临时”（证据开发覆盖）资助决策减少了25%。获得临时资助的几率降低了98%（优势比=0.02，95%置信区间=0.0005，0.17），但资助决策的方向没有变化（优势比=1.36，95%置信区间=0.62，3.01）。在两个时间段内，使用LEA时，医学检测极有可能不会获得临时资助（χ=12.63，自由度=1，P=0.001）。对于阳性资助决策，最强的预测因素是新检测是否会取代现有检测以及现有证据是否有限。LEA的使用并不能预测资助决策的方向。该方法的应用确实预测到“证据开发覆盖”决策不太可能。这表明LEA可能会降低决策者的不确定性。
