Evidence map›Paper›PMID 31983680›Full record

ArticleJournal of medical Internet research2020

Deploying Patient-Facing Application Programming Interfaces: Thematic Analysis of Health System Experiences.

Aaron Neinstein, Crishyashi Thao, Mark Savage, Julia Adler-Milstein

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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  3. The role of artificial intelligence for the application of integrating electronic health records and patient-generated data in clinical decision support.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024
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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

4 authors.

Aaron Neinstein *Department of Medicine, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0002-9774-7180
Crishyashi Thao *Center for Clinical Informatics and Improvement Research, Department of Medicine, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0001-9739-7136
Mark Savage *Center for Digital Health Innovation, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0001-8104-765X
Julia Adler-Milstein *Department of Medicine, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0002-0262-6491

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth systems have recently started to activate patient-facing application programming interfaces (APIs) to facilitate patient access to health data and other interactions.

objectiveThis study sought to ascertain health systems' understanding, strategies, governance, and organizational infrastructure around patient-facing APIs, as well as their business drivers and barriers, to facilitate national learning, policy, and progress toward adoption.

methodsWe performed a content analysis of semistructured interviews with a convenience sample of 10 health systems known to be leading adopters of health technology, having either implemented or planning to implement patient-facing APIs.

resultsOf the 10 health systems, eight had operational patient-facing APIs, with organizational strategy driven most by federal policy, the emergence of Health Records on iPhone, and feelings of ethical obligation. The two priority use cases identified were enablement of a patient's longitudinal health record and digital interactions with the health system. The themes most frequently cited as barriers to the increased use of patient-facing APIs were security concerns, an immature app ecosystem that does not currently offer superior functionality compared with widely adopted electronic health record (EHR)-tethered portals, a lack of business drivers, EHR vendor hesitation toward data sharing, and immature technology and standards.

conclusionsOur findings reveal heterogeneity in health system understanding and approaches to the implementation and use of patient-facing APIs. Ongoing study, targeted policy interventions, and sharing of best practices appear necessary to achieve successful national implementation.

Indexed as

Electronic Health RecordsHealth Systems PlansHumansLongitudinal Studiesapplication programming interfaceconsumer health informationelectronic health recordhealth information exchangehealth policypatient engagement

Identifiers

PMID31983680
PMCPMC7165308

What OpenQuestion holds

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LicenceCC BY
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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.