Results Summary

What was the project about?

Electronic health records, or EHRs, have information about a patient’s health such as test results, diagnoses, and treatments. EHRs also have clinical notes that doctors and patients can use to track goals and decisions.

Clinical notes may be useful for research or to help improve care. But it’s hard to get information from these notes across large groups of patients. The notes may use different ways to describe the same thing. For example, high blood pressure may be called hypertension. Also, the notes may use abbreviations or have spelling mistakes.

In this project, the research team designed and built a search engine to make EHR notes easier to search and use for patient care and research.

What did the research team do?

To develop a new method for searching clinical notes in EHRs, the research team used 66 million clinical notes from patient visits at Nationwide Children’s Hospital in Ohio from 2006 to 2016. Using the new method, the team built a search engine called QREK. QREK stands for Query Refinement by word Embedding and Knowledge base. QREK finds and pulls out EHR notes that are related to keywords entered into it. It can also suggest other relevant keywords and common alternatives.

The research team tested QREK in two ways. First, they asked three doctors to rate the relevance of terms suggested by QREK across 11 searches. Second, the team looked at how often QREK correctly suggested a synonym for a known medical term.

The research team tested the final version of QREK under nine different scenarios with people at Nationwide Children’s Hospital to get feedback about its usefulness. For example, some people used QREK to do research; others used QREK to help improve care.

Patients, hospital administrators, health insurers, health information technology specialists, researchers, and clinicians provided input during the study.

What were the results?

The research team found that about 72 percent of the terms suggested by QREK were relevant to the original search term. Also, of the first 60 terms suggested by QREK, 54 percent matched synonyms on a standard list of known medical terms.

In the nine scenarios tested, people reported that QREK improved their use of EHR notes.

What were the limits of the project?

Testing occurred at a children’s hospital using keywords for children’s care.

Future research could continue to refine QREK and test QREK with EHR notes from adult care settings.

How can people use the results?

Researchers and hospital staff can use QREK to search and use notes in EHRs. QREK is available free of charge.

How this project fits under PCORI’s Research Priorities
The research reported in this results summary was conducted using PCORnet®, the National Patient-Centered Clinical Research Network. PCORnet® is intended to improve the nation’s capacity to conduct health research, particularly comparative effectiveness research (CER), efficiently by creating a large, highly representative network for conducting clinical outcomes research. PCORnet® has been developed with funding from the Patient-Centered Outcomes Research Institute® (PCORI®).

Final Research Report

This project's final research report is expected to be available by July 2023.

Peer-Review Summary

The Peer-Review Summary for this project will be posted here soon.

Conflict of Interest Disclosures

Project Information

Yungui Huang, PhD, MBA
Huan Sun, PhD
Nationwide Children's Hospital/The Ohio State University
$1,060,000
Unlocking Clinical Text in EMR by Query Refinement Using Both Knowledge Bases and Word Embedding

Key Dates

November 2017
December 2022
2017
2022

Study Registration Information

Tags

Has Results
Award Type
State State The state where the project originates, or where the primary institution or organization is located. View Glossary
Last updated: November 10, 2022