Evidence map›Paper›PMID 39994604›Full record

ArticleBMC medical informatics and decision making2025

Evolution of clinical Health Information Exchanges to population health resources: a case study of the Indiana network for patient care.

Karmen S Williams, Saurabh Rahurkar, Shaun J Grannis, Titus K Schleyer, Brian E Dixon

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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.

Karmen S WilliamsGraduate School of Public Health and Health Policy, City University of New York, New York, NY, USA. Karmen.Williams@sph.cuny.edu.
Saurabh RahurkarDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
Shaun J GrannisCenter for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA.
Titus K SchleyerCenter for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA.
Brian E DixonCenter for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA.

Funding

Quality Assurance and Quality Control Project Management: Improving Submissions and Study Conduct in the Human Subjects Research Prior Approval ProcessUL1TR002529 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI MOE, SHARON M, WIEHE, SARAH ELIZABETH · 2018 to 2022
$27.2M
The Indiana Training Program in Public & Population Health InformaticsT15LM012502 · NLM · INDIANA UNIVERSITY INDIANAPOLIS · PI Brian E. Dixon, William F Fadel · 2017 to 2026
$4.7M
AHRQ HHS R21 HS025502AHRQ HHS R21HS025502NCATS NIH HHS UL1 TR002529NCATS NIH HHS ULI TR002529NLM NIH HHS T15 LM012502U.S. National Library of Medicine T15LM012502
6 · The paper itself

Abstract

backgroundMotivated by the Triple Aim, US health care policy is expanding its focus from individual patient care to include population health management. Health Information Exchanges are positioned to play an important role in that expansion.

objectiveThe objective is to describe the evolution of the Indiana Network for Patient Care (INPC) and discuss examples of its innovations that support both population health and clinical applications.

methodsA descriptive analytical approach was used to gather information on the INPC. This included a literature review of recent systematic and scoping reviews, collection of research that used INPC data as a resource, and data abstracted by Regenstrief Data Services to understand the breadth of uses for the INPC as a data resource.

resultsAlthough INPC data are primarily gathered from and used in healthcare settings, their use for population health management and research has increased. By December 2023, the INPC contained nearly 25 million patients, a significant growth from 3.5 million in 2004. This growth was a result of the use of INPC data for population health surveillance, clinical applications for data, disease registries, Patient-Centered Data Homes, non-clinical population health advancements, and accountable care organization connections with Health Information Exchanges.

conclusionBy structuring services on the fundamental building blocks, expanding the focus to population health, and ensuring value in the services provided to the stakeholders, Health Information Exchanges are uniquely positioned to support both population health and clinical applications.

Indexed as

Health Information ExchangePopulation HealthHumansIndianaCommunicable disease controlCOVID-19 pandemicInfectious disease transmissionPublic health surveillanceSARS-CoV-2 virus

Identifiers

PMID39994604
PMCPMC11849299

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LicenceCC BY-NC-ND
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Registered trials

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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.