?United States healthcare is embroiled in a crisis of inconsistent quality and overwhelming cost. Through two administrations, the national healthcare strategy has focused on using data and technology to control costs and improve care. Congress has enacted legislation to encourage measurement of quality, sharing of data, payment based on quality of care, and transparency within the healthcare system. While these goals are bipartisan and lofty, implementation requires both hard work from health systems and robust technology. Industry has developed technologies that incrementally further the national agenda, including electronic health records, computer assisted coding, and population health analytics. Each of these supports workflow within the healthcare system and improves profit margin for healthcare organizations. But, approaches that go beyond workflow, using data to better understand clinical care, are lacking. With newly available electronic health data and a massive increase in processing power, data-driven personalized medicine is just now becoming possible. It will require advanced semantic technologies to understand clinical care strategies that have been tried in the past, but that have unknown efficacy. It will pose informatics challenges in inferring inclusion criteria, interventions, and outcomes from incomplete and poorly structured data. It will require deep clinical understanding to run real-time pragmatic clinical trials based on real world data to understand complex patients. The goal, dependent on Phase I success, is to create the first commercial system to support healthcare in running real-time pragmatic clinical trials using full clinical data. This will augment the standard of care defined by randomized controlled trials to actually tailor therapy for those complex patients that account for the majority of healthcare spends, but for whom complexity precludes tailored randomized trials.
Public Health Relevance Statement: Public Health Relevance: If successful, the Phase I effort will represent a first step toward a revolutionary approach to leverage newly collected clinical data, rapidly evolving semantic technologies, and cutting edge clinical informatics to define best practices in healthcare. The overall project will target the complex patients that are poorly served by generalization of the randomized trial and currently account for the majority of healthcare spend. The goal is to leverage the national investment in clinical data to not just improve clinical workflow, but to actually transform medicine to achieve national goals of reducing costs and improving outcomes.
NIH Spending Category: Bioengineering; Clinical Research; Clinical Trials and Supportive Activities; Health Services; Networking and Information Technology R&D
Project Terms: Accounting; base; Caring; Clinical; clinical care; Clinical Data; Clinical Informatics; clinical phenotype; Clinical Trials; Code; cohort; commercialization; Complex; Computer Assisted; Congresses; cost; Cost Control; Data; Data Element; Electronic Health Record; Electronics; Exclusion Criteria; Goals; Health; health data; Health system; Healthcare; Healthcare Systems; improved; inclusion criteria; Industry; Informatics; Intervention; Investments; Label; Maps; Measurement; Medicine; meetings; Modeling; Natural Language Processing; Outcome; Pathway interactions; Patients; payment; personalized medicine; Pharmacologic Substance; Phase; population health; Process; public health relevance; Quality of Care; Randomized Controlled Trials; randomized trial; Rest; Running; Semantics; sharing data; Small Business Innovation Research Grant; standard of care; Statutes and Laws; Structure; Subgroup; success; System; Technology; Time; United States; Work; World Health
