Evidence map›Paper›PMID 27500285›Full record

ArticleProceedings of the SIGCHI conference on human factors in computing systems. CHI Conference2016

Closing the Gap: Supporting Patients' Transition to Self-Management after Hospitalization.

Ari H Pollack, Uba Backonja, Andrew D Miller, Sonali R Mishra, Maher Khelifi, Logan Kendall, Wanda Pratt

Abstract read
In one paragraph

Article in Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 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

33 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. A qualitative exploration of patient perspectives regarding patient education during their colorectal surgical experience.Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland · 2026
    Article
  5. Exploring Collaboration Breakdowns Between Provider Teams and Patients in Post-Surgery Care.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Informing the Design of Individualized Self-Management Regimens from the Human, Data, and Machine Learning Perspectives.ACM transactions on computer-human interaction : a publication of the Association for Computing Machinery · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Self-Management of Medication on a Cardiology Ward: Feasibility and Safety of the SelfMED Intervention.International journal of environmental research and public health · 2022
    Article
  18. Article
  19. Articulation of postsurgical patient discharges: coordinating care transitions from hospital to home.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  20. Observational
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

7 authors.

Ari H PollackDepartment of Pediatrics, School of Medicine, University of Washington, Seattle, WA, USA; Division of Nephrology, Seattle Children's Hospital, Seattle, WA, USA.
Uba BackonjaBiomedical and Health Informatics, University of Washington, Seattle, WA, USA.
Andrew D MillerBiomedical and Health Informatics, University of Washington, Seattle, WA, USA.
Sonali R MishraThe Information School, University of Washington, Seattle, WA, USA.
Maher KhelifiBiomedical and Health Informatics, University of Washington, Seattle, WA, USA.
Logan KendallBiomedical and Health Informatics, University of Washington, Seattle, WA, USA.
Wanda PrattThe Information School, University of Washington, Seattle, WA, USA.

Funding

University of Washington Biomedical Informatics and Data Science Research Training ProgramT15LM007442 · NLM · UNIVERSITY OF WASHINGTON · PI JOHN H. GENNARI, Andrea L. Hartzler · 2002 to 2026
$19.6M
Patients as safeguards: Understanding the information needs of hospitalized patieR01HS022894 · AHRQ · UNIVERSITY OF WASHINGTON · PI PRATT, WANDA · 2014 to 2018
$2.3M
Managing Health Information in Your LifeR01LM009143 · NLM · UNIVERSITY OF WASHINGTON · PI PRATT, WANDA · 2007 to 2009
$1.5M
AHRQ HHS R01 HS022894NLM NIH HHS R01 LM009143NLM NIH HHS T15 LM007442
6 · The paper itself

Abstract

Patients going home after a hospitalization face many challenges. This transition period exposes patients to unnecessary risks related to inadequate preparation prior to leaving the hospital, potentially leading to errors and patient harm. Although patients engaging in self-management have better health outcomes and increased self-efficacy, little is known about the processes in place to support and develop these skills for patients leaving the hospital. Through qualitative interviews and observations of 28 patients during and after their hospitalizations, we explore the challenges they face transitioning from hospital care to self-management. We identify three key elements in this process: knowledge, resources, and self-efficacy. We describe how both system and individual factors contribute to breakdowns leading to ineffective patient management. This work expands our understanding of the unique challenges faced by patients during this difficult transition and uncovers important design opportunities for supporting crucial yet unmet patient needs.

Indexed as

dischargeH.5.m. Information interfaces and presentationHealthHealth informaticshospitalJ.3 Life and Medical Sciencesmedical informaticsMedical Information Systemspediatricself-efficacyself-management

Identifiers

PMID27500285
PMCPMC4973626

What OpenQuestion holds

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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.