Evidence map›Paper›PMID 42519594›Full record

ArticleJAMIA open2026

Challenges implementing treatment guidelines in electronic health records: the American Diabetes Association Standards of Care as a case example.

Irene Demarie, Michael E Bowen, Shubham Agarwal, Christine Mai, Kelsea Marble, Jonathan Pak, Daniel F Heitjan, Zichang Xiang, Christoph U Lehmann, Ildiko Lingvay and 1 more

Abstract read
In one paragraph

Article in JAMIA open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Irene DemarieClinical Informatics Center, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.ORCID https://orcid.org/0009-0006-7022-9961
Michael E BowenDivision of General Internal Medicine, Department of Internal Medicine and Peter O'Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.
Shubham AgarwalDivision of Endocrinology, Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.
Christine MaiClinical Informatics Center, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.
Kelsea MarbleClinical Informatics Center, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.
Jonathan PakBoehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT 06877, United States.
Daniel F HeitjanDepartment of Health Data Science and Biostatistics, Peter O'Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.
Zichang XiangDepartment of Statistics and Data Science, Southern Methodist University, Dallas, TX 75275, United States.
Christoph U LehmannDepartment of Pediatrics and Clinical Informatics Center, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.
Ildiko LingvayDivision of Endocrinology, Department of Internal Medicine and Peter O'Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.ORCID https://orcid.org/0000-0001-7006-7401
Mujeeb A BasitDivision of Cardiology, Department of Internal Medicine and Clinical Informatics Center, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.ORCID https://orcid.org/0000-0002-4948-6158

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Treatment guidelines can improve population health; however, their implementation within electronic health records (EHRs) can be challenging. We aimed to create an implementable framework using the American Diabetes Association (ADA) Standards of Care (SOC) for people with type 2 diabetes and cardiovascular or renal disease as an example. Materials and Methods: A multidisciplinary team used agile methods to translate the text-based ADA SOC into structured elements within the EHR, including logic-driven algorithms and ontology groupers for diagnoses, laboratory values, and medications, leveraging standard terminologies such as SNOMED CT, LOINC, and RxNorm. Results: The structured elements were used to implement 3 tools in the EHR: a real-time patient registry and 2 clinical decision support (CDS) instruments. The real-time registry enables dynamic, ongoing identification of patients eligible for guideline-directed medical therapy, supports more advanced analytics, and can be filtered to evaluate treatment gaps at the population and individual provider levels. The CDS tools allow clinicians to address these gaps directly within their EHR workflows. Discussion: Transforming clinical guidelines into executable constructs within the EHR is feasible but remains complex and labor-intensive. Broader and more consistent implementation could be achieved if guideline organizations provided technical frameworks, regular updates (through addenda or shared interfaces), and collaborated with EHR vendors to support the distribution and maintenance of implementable algorithms. Conclusion: The integration of executable logic into clinical guidelines, using deterministic frameworks such as Unified Modeling Language and standardized ontologies, would simplify guideline implementation across EHR platforms.

Indexed as

diabetes mellituselectronic health recordsglucagon-like peptide-1 receptor agonistsguideline adherencesodium-glucose transporter 2 inhibitorstype 2

Identifiers

PMID42519594
PMCPMC13384065

What OpenQuestion holds

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LicenceCC BY-NC
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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.