Envisioning a learning health care system: the electronic primary care research network, a case study

Abstract

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 U.S. 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 U.S. 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.

Figure 1

The learning health care system. RCT = randomized controlled trial.

Figure 2

The electronic Primary Care Research Network (ePCRN). eCRF = electronic case report form. Note: The ePCRN system functions in a modular fashion. A researcher is able to create a standardized computable representation of their study eligibility criteria using a Web-based workbench and a terminology service. With permission from the network, the system creates a search tailored for the target clinical data, referred to as a gateway. The gateway can be a copy of a single health record system or an aggregate data repository. It holds records that are potentially identifiable, however, either directly or via pseudoanonymization. The search reports counts of eligible subjects to the researcher, and then tags the identified subjects for local recruitment by practice staff.