Health risk assessment using real time clinical data

描述（由申请人提供）：卫生信息技术的进步通过更准确、及时和临床相关的措施，显著提高了我们识别基于人群的健康状况和临床需求的能力。私人和公共保险赞助商以及其他对调整财务或临床质量和业绩数据感兴趣的人现在最常使用的工具和手段依赖于健康状况的代理措施，如诊断、药房数据或程序，通常从索赔或其他行政数据源获取。这些工具及其衍生的风险评估用于调整健康计划或提供者付款和医生简介，以进行质量评估和其他用途。每个模型的基础是，从索赔或管理数据生成的诊断或药房配药作为潜在健康状况的信号，可用于解释当前或预测未来的医疗保健使用情况。依赖这些数据的模型之所以被开发出来，是因为直到最近，从人群的临床记录中获取实际临床状态的标记是不切实际的，或者成本太高。然而，采用电子医疗记录，其中包括以前无法为大量人口提供的临床数据，有可能改变我们评估基于人口的风险的方式，并将这些评估应用于调整临床表现、健康计划和提供者付款。我们建议开发和测试一种风险评估模型，该模型使用来自电子病历的实时临床数据。我们将检验这样一个假设，即使用医疗需求的临床表达来评估人群风险的能力将比纯粹从诊断或药房数据中得出的措施更准确，并且在指导临床实践方面更相关。

DESCRIPTION (provided by applicant): Advances in health information technology significantly improve our ability to identify population based health status and clinical need through more accurate, timely and clinically relevant measures. The tools and instruments that are now used most often by private and public insurance sponsors and others interested in adjusting financial or clinical quality and performance data rely on proxy measures of health status such as diagnoses, pharmacy data or procedures, usually captured from claims or other administrative data sources. These instruments and the risk assessments derived from them are used to adjust health plan or provider payments and physician profiles for quality assessments among other uses. The foundation of each model is that diagnoses or pharmacy dispenses generated from claims or administrative data serve as a signal of underlying health status and can be used to explain current or predict future health care use. Models that rely on these data were developed because until recently it has been impractical or too costly to capture markers of actual clinical status from clinical records on a population basis. However adoption of electronic medical records, which include clinical data previously not available for large populations has the potential to change the ways we assess population based risk and apply these assessment to adjusting clinical performance and health plan and provider payments. We propose to develop and test a risk assessment model that uses real time clinical data from an electronic medical record. We will test the hypothesis that the ability to assess population risk using clinical expressions of medical need will be more accurate than measures derived purely from diagnostic or pharmacy data and be more relevant in guiding clinical practice. PUBLIC HEALTH RELEVANCE: We propose to develop, test, and validate a population based risk assessment model using primarily real time clinical and diagnostic data obtained from electronic medical records, supplemented with self reported information on health behaviors. Advances in health information technology create opportunities to estimate population based risk using more complete data on health status and health outcomes. Risk models based on real time clinical data will be more accurate with respect to their ability to explain and predict medical care need as well as more closely aligned with clinical practice.