Evidence map›Paper›PMID 41938604›Full record

ArticleFrontiers in digital health2026

Structuring integration for patient-centered care: a review-informed ontology-driven modular front-end framework for digital health innovation.

Radha Ambalavanan, R Sterling Snead, Julia Marczika, Gideon Towett, Alex Malioukis, Mercy Mbogori-Kairichi

Abstract read
In one paragraph

Article in Frontiers in digital health, 2026. 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. Review
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

6 authors.

Radha AmbalavananResearch Department, The Self Research Institute, Broken Arrow, OK, United States.
R Sterling SneadResearch Department, The Self Research Institute, Broken Arrow, OK, United States.
Julia MarczikaResearch Department, The Self Research Institute, Broken Arrow, OK, United States.
Gideon TowettResearch Department, The Self Research Institute, Broken Arrow, OK, United States.
Alex MalioukisResearch Department, The Self Research Institute, Broken Arrow, OK, United States.
Mercy Mbogori-KairichiResearch Department, The Self Research Institute, Broken Arrow, OK, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Semantic interoperability remains a significant barrier in healthcare, particularly when integrating patient-reported, clinical, and genomic data to enable personalized care. Existing models rarely focus on patient-centered, ontology-driven front-end architectures based on widely adopted standardized medical ontologies and terminologies. Within broader Personal Health Data Space (PHDS) initiatives, such integration increasingly depends on front-end frameworks that enable semantic consistency and patient-centered usability across heterogeneous clinical domains and systems. Objective: This analysis presents a review-informed framework to support semantic integration, data governance, user experience, and patient engagement. The objective is to present a front-end, standards-aligned, ontology-driven model grounded in established healthcare standards. Methods: Based on our previously published systematic review and thematic synthesis, this paper presents a review-informed conceptual framework. It outlines a modular front-end architecture for semantic healthcare data integration. The framework was developed through a reproducible synthesis-to-design process, consistent with design science principles of treatment design, thereby ensuring conceptual rigor and alignment with evidence. Using a knowledge-based modeling approach, we designed a six-layer architecture comprising User Experience, Security and Compliance, Data Management, Interoperability and Integration, Advanced Analytics, and Support and Scalability. Each layer is aligned with established standards including Health Level Seven-Fast Healthcare Interoperability Resources (HL7 FHIR), Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), and Logical Observation Identifiers Names and Codes (LOINC), compliance with privacy and security regulations such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA). Results: The framework illustrates how ontologies and health IT standards can be conceptually incorporated within front-end system design to unify structured and unstructured data, providing a foundation for secure sharing and standards-aligned integration with existing health information systems. Conclusions: This review-informed analysis introduces the Self Data Atlas Front-End Framework (SDA-FEF), an ontology-driven, standards-aligned Electronic Health Record (EHR) front-end architecture designed to support patient-centered care. By promoting semantic interoperability, structured data integration, and user-centered design, the framework conceptually advances the development of healthcare systems that may enhance continuity of care and overall quality of life.

Indexed as

conceptual frameworkdata integrationEHR usabilityfront-end frameworkHL7 FHIRmedical ontologypatient-centered caresemantic interoperability

Identifiers

PMID41938604
PMCPMC13044035

What Socratic holds

Textmetadata
LicenceCC BY
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.