Evidence map›Paper›PMID 41169633›Full record

ArticleLearning health systems2025

Multi-site research using electronic health record data: Lessons learned from a case study.

Brittany Garcia, Michael Hogarth, Yu Wang, Xi Zhu, Shin-Ping Tu

Abstract read
In one paragraph

Article in Learning health systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Brittany GarciaDepartment of Internal Medicine University of California, Davis Sacramento California USA.ORCID https://orcid.org/0000-0001-5351-3545
Michael HogarthDepartment of Medicine University of California, San Diego San Diego California USA.
Yu WangDepartment of Internal Medicine University of California, Davis Sacramento California USA.
Xi ZhuDepartment of Health Policy and Management University of California, Los Angeles Los Angeles California USA.
Shin-Ping TuDepartment of Internal Medicine University of California, Davis Sacramento California USA.

Funding

SMART Cancer Care Teams: Enhancing EHR Communication to Improve Interprofessional Teamwork - Diversity SupplementR01CA273058 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Kwan-Liu Ma, Daniel Sewell · 2022 to 2026
$3.6M
NCI NIH HHS R01 CA273058
6 · The paper itself

Abstract

Introduction: Multi-site research collaboration is necessary to increase generalizability, diversity, and innovation; however, there are complexities and challenges surrounding research processes, including regulatory oversight, data management, and data sharing activities. This report highlights the specific challenges of collaborative research identified in the conduct of a federally funded multi-site study and presents lessons learned to inform ways to overcome these challenges. The purpose of our current research project is to determine how interprofessional teamwork affects quality outcomes and develop tools to improve teamwork in cancer care. Methods: Our research team is comprised of 23 members across five academic institutions. Our study cohort includes approximately 20 000 adult patients with breast, colorectal, and non-small cell lung cancers diagnosed at the respective sites between January 1, 2016, and December 31, 2021. Electronic health record (EHR) access log data was extracted 12 months pre- and 24 months post-diagnosis for each patient, and outcome data of potentially preventable emergency department visits and unplanned hospitalizations was extracted from the California state All-Payer Claims database. Results: Major challenges experienced related to single institutional review board processes, establishment of contract agreements, and data management, analysis, acquisition, and transfer. Lessons learned included: (1) start research planning as early as possible, including engaging with information technology and compliance teams to identify processes and develop and share data dictionaries; (2) work closely with the institution contracting team to identify the most optimal timing and ordering for multiple data use agreement (DUA) contracts; and (3) ensure that research team members are abreast of current Health Insurance Portability and Accountability Act and institutional guidelines as they pertain to research and data practices. Conclusions: Multi-site research involving big data from the EHR requires ample planning and execution time. Adopting a single standardized DUA and developing data dictionaries that can be shared for research will improve the data acquisition phase of multi-site research studies.

Indexed as

access log datadata use agreementselectronic health record (EHR)multi‐site researchresearch challenges

Identifiers

PMID41169633
PMCPMC12569463

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.