Envisioning a Learning Health Care System: The Electronic Primary Care Research Network, A Case Study
Research output: Contribution to journal › Article
Colleges, School and Institutes
PURPOSE The learning health care system refers to the cycle of turning health care data into knowledge, translating that knowledge into practice, and creating new data by means of advanced information technology. The electronic Primary Care Research Network (ePCRN) was a project, funded by the US National Institutes of Health, with the aim to facilitate clinical research using primary care electronic health records (EHRs). METHODS We identified the requirements necessary to deliver clinical studies via a distributed electronic network linked to EHRs. After we explored a variety of informatics solutions, we constructed a functional prototype of the software. We then explored the barriers to adoption of the prototype software within US practice-based research networks. RESULTS We developed a system to assist in the identification of eligible cohorts from EHR data. To preserve privacy, counts and flagging were performed remotely, and no data were transferred out of the EHR. A lack of batch export facilities from EHR systems and ambiguities in the coding of clinical data, such as blood pressure, have so far prevented a full-scale deployment. We created an international consortium and a model for sharing further ePCRN development across a variety of ongoing projects in the United States and Europe. CONCLUSIONS A means of accessing health care data for research is not sufficient in itself to deliver a learning health care system. EHR systems need to use sophisticated tools to capture and preserve rich clinical context in coded data, and business models need to be developed that incentivize all stakeholders from clinicians to vendors to participate in the system.
|Number of pages||6|
|Journal||Annals of family medicine|
|Publication status||Published - 1 Jan 2012|
- electronic health records, Information management/informatics, randomized clinical trials, research capacity building, quantitative methods