Evidence map›Paper›PMID 37940130›Full record

ArticleApplied clinical informatics2023

Social and Health Information Platform: Piloting a Standards-Based, Digital Platform Linking Social Determinants of Health Data into Clinical Workflows for Community-Wide Use.

Anjum Khurshid, Matti Hautala, Eliel Oliveira, Vidya Lakshminarayanan, Vishal Abrol, Joshua Collier, Justin Rosseau, Linda Granado, Shreya Nallaparaju, Kanishka Mitra and 1 more

Abstract read
In one paragraph

Article in Applied clinical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

11 authors.

Anjum KhurshidDepartment of Population Medicine, Harvard Medical School, Boston, Massachusetts.
Matti HautalaDepartment of Population Health, Dell Medical School at The University of Texas at Austin, Texas.
Eliel OliveiraDepartment of Population Health, Dell Medical School at The University of Texas at Austin, Texas.
Vidya LakshminarayananDepartment of Population Health, Dell Medical School at The University of Texas at Austin, Texas.
Vishal AbrolDepartment of Population Health, Dell Medical School at The University of Texas at Austin, Texas.
Joshua CollierDepartment of Population Health, Dell Medical School at The University of Texas at Austin, Texas.
Justin RosseauDepartment of Population Health, Dell Medical School at The University of Texas at Austin, Texas.
Linda GranadoDepartment of Population Health, Dell Medical School at The University of Texas at Austin, Texas.
Shreya NallaparajuDepartment of Population Health, Dell Medical School at The University of Texas at Austin, Texas.
Kanishka MitraDepartment of Population Health, Dell Medical School at The University of Texas at Austin, Texas.
Rania SohailDepartment of Population Health, Dell Medical School at The University of Texas at Austin, Texas.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial determinants of health (SDoH)a are increasingly recognized as a main contributor to clinical health outcomes, but the technologies and workflows within clinics make it difficult for health care providers to address SDoH needs during routine clinical visits.

objectivesOur objectives were to pilot a digital platform that matches, links, and visualizes patient-level information and community-level deidentified data from across sectors; establish a technical infrastructure that is scalable, generalizable, and interoperable with new datasets or technologies; employ user-centered codesign principles to refine the platform's visualizations, dashboards, and alerts with community health workers, clinicians, and clinic administrators.

methodsWe used privacy-preserving record linkage (PPRL) tools to ensure that all identifiable patient data were encrypted, only matched and displayed with consent, and never accessed or stored by the data intermediary. We used limited data sets (LDS) to share nonidentifiable patient data with the data intermediary through a health information exchange (HIE) to take advantage of existing partner agreements, technical infrastructure, and community clinical data.

resultsThe platform was successfully piloted in two Federally Qualified Health Clinics by 26 clinic staff. SDoH and demographic data from findhelp were successfully linked, matched, and displayed with clinical and demographic data from the HIE, Connxus. Pilot users tested the platform using real-patient data, guiding the refinement of the social and health information platform's visualizations and alerts. Users emphasized the importance of visuals and alerts that gave quick insights into individual patient SDoH needs, survey responses, and clinic-level trends in SDoH service referrals.

conclusionThis pilot shows the importance of PPRL, LDS, and HIE-based data intermediaries in sharing data across sectors and service providers for scalable patient-level care coordination and community-level insights. Clinic staff are integral in designing, developing, and adopting health technologies that will enhance their ability to address SDoH needs within existing workflows without adding undue burdens or additional stress.

Indexed as

Health Information ExchangeSocial Determinants of HealthAmbulatory Care FacilitiesHumansReferral and ConsultationWorkflow

Identifiers

PMID37940130
PMCPMC10632068

What OpenQuestion holds

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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.