Evidence map›Paper›PMID 38907738›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2024

Patient-centered clinical decision support challenges and opportunities identified from workflow execution models.

Dean F Sittig, Aziz Boxwala, Adam Wright, Courtney Zott, Nicole A Gauthreaux, James Swiger, Edwin A Lomotan, Prashila Dullabh

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Materials and System Design for Self-Decision Bioelectronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  4. Review
  5. Article
  6. Article
  7. 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

8 authors.

Dean F SittigDepartment of Clinical and Health Informatics, University of Texas Health Science Center, Houston, TX 77030, United States.ORCID 0000-0001-5811-8915
Aziz BoxwalaElimu Informatics, El Cerrito, CA 94530, United States.
Adam WrightDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, United States.ORCID 0000-0001-6844-145X
Courtney ZottNORC at the University of Chicago, Bethesda, MD 20814, United States.
Nicole A GauthreauxNORC at the University of Chicago, Bethesda, MD 20814, United States.ORCID 0000-0001-5743-0640
James SwigerCenter for Evidence and Practice Improvement, Agency for Healthcare Research and Quality, Rockville, MD 20857, United States.
Edwin A LomotanCenter for Evidence and Practice Improvement, Agency for Healthcare Research and Quality, Rockville, MD 20857, United States.
Prashila DullabhNORC at the University of Chicago, Bethesda, MD 20814, United States.

Funding

AHRQ HHS 75Q80120D00018
6 · The paper itself

Abstract

objectiveTo use workflow execution models to highlight new considerations for patient-centered clinical decision support policies (PC CDS), processes, procedures, technology, and expertise required to support new workflows.

methodsTo generate and refine models, we used (1) targeted literature reviews; (2) key informant interviews with 6 external PC CDS experts; (3) model refinement based on authors' experience; and (4) validation of the models by a 26-member steering committee. RESULTS AND DISCUSSION: We identified 7 major issues that provide significant challenges and opportunities for healthcare systems, researchers, administrators, and health IT and app developers. Overcoming these challenges presents opportunities for new or modified policies, processes, procedures, technology, and expertise to: (1) Ensure patient-generated health data (PGHD), including patient-reported outcomes (PROs), are documented, reviewed, and managed by appropriately trained clinicians, between visits and after regular working hours. (2) Educate patients to use connected medical devices and handle technical issues. (3) Facilitate collection and incorporation of PGHD, PROs, patient preferences, and social determinants of health into existing electronic health records. (4) Troubleshoot erroneous data received from devices. (5) Develop dashboards to display longitudinal patient-reported data. (6) Provide reimbursement to support new models of care. (7) Support patient engagement with remote devices.

conclusionSeveral new policies, processes, technologies, and expertise are required to ensure safe and effective implementation and use of PC CDS. As we gain more experience implementing and working with PC CDS, we should be able to begin realizing the long-term positive impact on patient health that the patient-centered movement in healthcare promises.

Indexed as

Decision Support Systems, ClinicalPatient-Centered CareWorkflowElectronic Health RecordsHumansModels, TheoreticalPatient Generated Health DataPatient Reported Outcome Measuresclinicaldecision support systemspatient-generated health datapatient-reported outcome measuresworkflow

Identifiers

PMID38907738
PMCPMC11258405

What OpenQuestion holds

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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 OpenQuestion graph.