Data Capacity for Patient-Centered Outcomes Research through Creation of an Electronic Care Plan for People with Multiple Chronic Conditions 2.0: Development of the Patient-Facing Application

01/27/2021

Improve Data Capacity to Conduct Pragmatic, Patient Centered Outcomes Research through Development and Refinement of Interoperable Electronic (eCare) Plans
Agency
  • National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
  • Agency for Healthcare Research and Quality (AHRQ)
Start Date
  • NIDDK: 4/23/2020
  • AHRQ: 5/15/2020
Functionality
  • Use of Clinical Data for Research
  • Standardized Collection of Standardized Clinical Data
  • Collection of Patient-Provided Information
  • Linking of Clinical and Other Data for Research

 

STATUS: Active Project

BACKGROUND

The research community recognizes the need for pragmatic, applicable health research, expanding beyond traditional randomized trials and toward the generation of “real-world” evidence that will more readily translate to point-of-care settings. Pragmatic trials and other research designs using “real-world” data offer a research approach that uses health information technology (health IT) systems such as electronic health records (EHRs) to expedite use of point-of-care data to inform our knowledge on the effectiveness of health interventions in practice. However, lack of interoperability across systems is a barrier to pragmatic patient-centered outcomes research (PCOR). EHRs often are missing essential data on patient-reported outcomes, social determinants of health and patient goals and preferences. Additionally, because most people—especially people living with multiple chronic conditions (MCC)—seek care in multiple settings with distinct EHR systems, key clinical, patient-centered outcomes and risk factor data are often incomplete in a single data source, and merging data across diverse settings can be cumbersome due to inconsistent data and poor interoperability.

The electronic care (eCare) plan 2.0 project continues the work of AHRQ and NIDDK’s 2019 OS-PCORTF eCare plan 1.0 project. The goals of the original project include data capacity improvements for pragmatic PCOR through the development an open source clinician-facing eCare plan application. The application and corresponding implementation guide (IG) supports research efforts and clinical care delivery for individuals living with MCC. This project will develop an analogous patient-facing eCare plan application capable of coordination with the clinician-facing application to facilitate collection and the exchange of vital data on patients living with chronic kidney disease (CKD), cardiovascular disease (CVD), diabetes, and/or chronic pain with or without opioid use disorder (OUD). By working in concert with the clinician-facing eCare plan application, the patient tool will enrich current understanding of the complex care requirements and outcomes of high-need patients.

PROJECT PURPOSE & GOALS

Leveraging previous OS-PCORTF electronic eCare plan 1.0 project work, the eCare plan 2.0 aims to develop additional resources for patient use and expand upon the original capabilities of the first eCare plan application by incorporating feedback from pilot findings.

The NIDDK project objectives are to:

  • Create a Fast Healthcare Interoperability Resources (FHIR®)-based, mobile eCare plan software application specifically for patients.

  • Build upon the eCare 1.0 IG for the clinician-facing application by incorporating patient-facing components and considerations.

  • Retool the patient-facing eCare plan application and IG to address feedback from pilot implementation and integrate findings.

  • Ballot the revised IG with Health Level 7 (HL7®) to increase uptake and long-term use.

The AHRQ project objectives are to:

  • Implement and evaluate the patient-facing eCare plan software application in clinical settings in patients living with MCC, including chronic CKD, assessing the feasibility and usability of the application in collecting data across clinical and research settings using FHIR.