# Multiple Chronic COnditions: MultiPle dAta SouRcEs (MC COMPARE)

> **NIH NIH R01** · OREGON HEALTH & SCIENCE UNIVERSITY · 2024 · $1,228,970

## Abstract

MC COMPARE Multiple Chronic COnditions: MultiPle dAta SouRcEs Project Summary
The evidence to guide risk-benefit decisions for patients living with multiple chronic conditions (MCCs) is
limited. For example, patients with chronic kidney disease can benefit from tight blood pressure control but are
also at risk of adverse events – hypotension, falls, acute kidney injury (AKI) – making treatment difficult. Trials
exploring how best to treat patients with MCC including high blood pressure are being performed: A
collaborative approach to managing hypertension (HTN): COACH Collaboration-Oriented Approach to
Controlling High blood pressure (Dorr and Koopman) and Electronic Tools to Increase Recognition and
Improve Primary Care Management for Hypertension in Chronic Kidney Disease (CKD; Samal and Dykes).
In this proposal, we will aggregate EHR data from multiple institutions into the eCarePlan, an application
intended to bring multiple data sources together for care planning using Fast Healthcare Interoperable
Resources (FHIR). These enhanced data sets will help us to quantify the ways that aggregating fragmented
data can improve clinical trial results and personalized decision making for older adults. We will then use this
dataset to better understand the risk of adverse events in these studies, like falls and AKI, as well as poor
clinical outcomes, like strokes and worsening cognitive function. We will proceed in accordance with
established steps of data harmonization. First, we will adapt and implement the eCarePlan tool to automatically
extract data needed for the two partner studies on HTN and CKD. We will focus on unrecognized chronic
conditions, partner study variables, partner study outcomes, health behaviors, social determinants of health,
and adverse event outcomes. We will use optical character recognition (OCR) and natural language
processing (NLP) to extract and harmonize data from electronic free text notes and scanned
documents.Second, we will harmonize data and refine the integration process using
Findability/Accessibility/Interoperability/Reusability (FAIR) and data readiness frameworks and engage patients
and providers to understand how these integrated studies can be matched to patient prognosis and needs.
Third, we will replicate measurement of study criteria and outcomes for both studies. We will provide the
resulting interoperable infrastructure openly for all.

## Key facts

- **NIH application ID:** 10913569
- **Project number:** 5R01AG082931-02
- **Recipient organization:** OREGON HEALTH & SCIENCE UNIVERSITY
- **Principal Investigator:** DAVID A. DORR
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,228,970
- **Award type:** 5
- **Project period:** 2023-09-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10913569

## Citation

> US National Institutes of Health, RePORTER application 10913569, Multiple Chronic COnditions: MultiPle dAta SouRcEs (MC COMPARE) (5R01AG082931-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10913569. Licensed CC0.

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