Evidence map›Paper›PMID 39622048›Full record

ArticleJournal of medical Internet research2024

Digital Information Ecosystems in Modern Care Coordination and Patient Care Pathways and the Challenges and Opportunities for AI Solutions.

You Chen, Christoph U Lehmann, Bradley Malin

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Observational
  4. Digital Transformation in Health Care: Are We on the Right Track?Journal of medical Internet research · 2026
    Article
  5. Article
  6. Review
  7. The future of follow-up: technology-enabled medical and developmental follow-up care for NICU graduates.Journal of perinatology : official journal of the California Perinatal Association · 2026
    Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Digital Psychiatry with Chatbot: Recent Advances and Limitations.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2025
    Review
  20. 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

3 authors.

You ChenDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States.ORCID 0000-0001-8232-8840
Christoph U LehmannClinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, TX, United States.ORCID 0000-0001-9559-4646
Bradley MalinDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States.ORCID 0000-0003-3040-5175

Funding

AIM-AHEAD Coordinating Center - All Four CoresOT2OD032581 · OD · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI Paul Avillach, Bettina M. Beech · 2021 to 2026
$168.7M
Ethics Core (FABRIC)U54HG012510 · NHGRI · YALE UNIVERSITY · PI MALIN, BRADLEY A. · 2022 to 2025
$11.2M
Discovering Care Coordination Practice Patterns in the EMR: Interpretation and Impact on Patient OutcomesR01LM012854 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CHEN, YOU · 2019 to 2022
$1.5M
NHGRI NIH HHS U54 HG012510NIH HHS OT2 OD032581NLM NIH HHS R01 LM012854
6 · The paper itself

Abstract

The integration of digital technologies into health care has significantly enhanced the efficiency and effectiveness of care coordination. Our perspective paper explores the digital information ecosystems in modern care coordination, focusing on the processes of information generation, updating, transmission, and exchange along a patient's care pathway. We identify several challenges within this ecosystem, including interoperability issues, information silos, hard-to-map patient care journeys, increased workload on health care professionals, coordination and communication gaps, and compliance with privacy regulations. These challenges are often associated with inefficiencies and diminished care quality. We also examine how emerging artificial intelligence (AI) tools have the potential to enhance the management of patient information flow. Specifically, AI can boost interoperability across diverse health systems; optimize and monitor patient care pathways; improve information retrieval and care transitions; humanize health care by integrating patients' desired outcomes and patient-reported outcome measures; and optimize clinical workflows, resource allocation, and digital tool usability and user experiences. By strategically leveraging AI, health care systems can establish a more robust and responsive digital information ecosystem, improving care coordination and patient outcomes. This perspective underscores the importance of continued research and investment in AI technologies in patient care pathways. We advocate for a thoughtful integration of AI into health care practices to fully realize its potential in revolutionizing care coordination.

Indexed as

Artificial IntelligenceCritical PathwaysDigital TechnologyHumansartificial intelligencecare coordinationcare journeycare transitionsclinical workflowdigital information ecosystemdigital technologieshealth care information systemsinformation interoperabilityinformation retrievalinformation silosnetworks of health care professionalspatient care pathwaypatient information flowpatient-reported outcome measuresusabilityuser experience workflowworkload

Identifiers

PMID39622048
PMCPMC11650087

What OpenQuestion 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 OpenQuestion graph.