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Health risk assessment using real time clinical data

使用实时临床数据进行健康风险评估

基本信息

批准号：
8082820
负责人：
PAUL A FISHMAN
金额：
$ 16.4万
依托单位：
KAISER FOUNDATION HEALTH PLAN OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-09-01 至 2013-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8082820
关键词：
Adoption Attention Caring Clinic Clinical Clinical Data Clinical Management Code Computerized Medical Record Data Data Collection Data Sources Development Diagnosis Diagnostic Diagnostic Procedure Foundations Future Health Health Personnel Health Planning Health Services Accessibility Health Status Health behavior Healthcare ICD-9 Incentives Individual Information Systems Injury Insurance Integrated Health Care Systems Internet Investments Joints Lead Link Literature Measurement Measures Medical Medical Records Modeling Outcome Patient Self-Report Performance Pharmaceutical Preparations Pharmacy facility Physicians Population Procedures Process Provider Proxy Records Research Research Personnel Resources Risk Risk Adjustment Risk Assessment Self-Administered Signal Transduction Testing Time Translating Update Writing base clinical practice clinically relevant cost design health information technology improved instrument interest payment population based population health programs tool

项目摘要

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.

描述（由申请人提供）：卫生信息技术的进步显著提高了我们通过更准确、及时和临床相关的措施确定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有兴趣调整财务或临床质量和绩效数据的人现在最常使用的工具和手段依赖于健康状况的替代指标，如诊断、药房数据或程序，通常从索赔或其他行政数据来源获取。这些工具和由此得出的风险评估用于调整保健计划或提供者付款和医生概况，以进行质量评估等。每个模型的基础是，从索赔或管理数据中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。开发依赖于这些数据的模型是因为直到最近，从基于人群的临床记录中捕获实际临床状态的标记物是不切实际的或成本太高。然而，采用电子病历（包括以前无法用于大规模人群的临床数据）有可能改变我们评估基于人群的风险的方式，并将这些评估应用于调整临床表现和健康计划以及提供者支付。我们建议开发和测试一个风险评估模型，该模型使用电子病历中的真实的临床数据。我们将检验以下假设，即使用医疗需求的临床表达评估人群风险的能力将比纯粹从诊断或药学数据得出的措施更准确，并且在指导临床实践方面更相关。公共卫生关系：我们建议开发、测试和验证一个基于人群的风险评估模型，该模型主要使用从电子病历中获得的真实的临床和诊断数据，并辅以自我报告的健康行为信息。卫生信息技术的进步创造了利用更完整的健康状况和健康结果数据估计基于人口的风险的机会。基于真实的时间临床数据的风险模型在解释和预测医疗护理需求的能力方面将更加准确，并且与临床实践更加一致。