Evidence map›Paper›PMID 41032388›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2025

A standards-based approach to digital health research: implementing the people heart study.

Raheel Sayeed, David Kreda, Joshua C Mandel, Bryan Larson, William Gordon, Kenneth D Mandl, Isaac Kohane

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 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

7 authors.

Raheel SayeedDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.ORCID 0000-0001-8810-2471
David KredaDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.
Joshua C MandelDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.
Bryan LarsonDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.
William GordonDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.
Kenneth D MandlDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.
Isaac KohaneDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.

Funding

Department of Biomedical Informatics, Harvard Medical School
6 · The paper itself

Abstract

objectiveTo assess whether HL7 Fast Healthcare Interoperability Resources (FHIR) can underpin a fully standards-based, end-to-end digital research architecture, demonstrate it in a live study, and quantify its benefits for interoperability and development efficiency. MATERIALS AND

methodsWe designed a generalizable standards-based architecture to accelerate digital health research relying on FHIR as the sole transactional model throughout a participant research lifecycle starting from API-based study discovery to results. It was instantiated for People Heart Study, a real-world digital health cardiovascular-risk assessment study with its protocol transformed into FHIR resources (eligibility, consent, tasks, and results). Evaluation examined workflow coverage, validator conformance across independent servers, and points requiring custom extensions or app logic.

resultsThe architecture was implemented using cloud managed FHIR stores including an illustrative public research discovery API for first-/third-party apps. A participant-facing iOS app was published on the App Store. Our evaluation reveals that 6 of 10 research app workflows could be executed entirely from FHIR artifacts; 2 were partially standards-driven and 2 remained limited requiring custom development. All FHIR resources passed structural, semantic validation with minimal custom extension usage and terminology integrity issues. DISCUSSION: Our approach addresses persistent challenges in digital health research by enhancing data interoperability, minimizing redundant development, and supporting the full research lifecycle. The architecture aligns with national priorities and complements healthcare standardization efforts.

conclusionBy leveraging FHIR, our architecture enables generalizability, interoperability, and reuse across diverse digital health research contexts, transforming study design into data modeling rather than software development, and fostering a more inclusive and agile digital health ecosystem.

Indexed as

Biomedical ResearchHealth Information InteroperabilityHealth Level SevenCardiovascular DiseasesDigital HealthHumansMobile ApplicationsWorkflowdigital healthhealth IT standardsmobile healthresearch on FHIRtranslational medical research

Identifiers

PMID41032388
PMCPMC12646378

What Socratic 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 Socratic graph.