Evidence map›Paper›PMID 35415420›Full record

ArticleJournal of healthcare informatics research2019

What Happened to Me while I Was in the Hospital? Challenges and Opportunities for Generating Patient-Friendly Hospitalization Summaries.

Sabita Acharya, Andrew D Boyd, Richard Cameron, Karen Dunn Lopez, Pamela Martyn-Nemeth, Carolyn Dickens, Amer Ardati, Jose D Flores, Matt Baumann, Betty Welland and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of healthcare informatics research, 2019. 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.

Sabita AcharyaDepartment of Computer Science, College of Engineering, University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607 USA.ORCID 0000-0003-1825-3623
Andrew D BoydDepartment of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, 1919 W Taylor St., Chicago, IL 60612 USA.
Richard CameronDepartment of Linguistics, College of Liberal Arts and Sciences, University of Illinois at Chicago, 601 South Morgan Street, Chicago, IL 60607 USA.
Karen Dunn LopezDepartment of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, 1919 W Taylor St., Chicago, IL 60612 USA.
Pamela Martyn-NemethDepartment of Biobehavioral Health Science, College of Nursing, University of Illinois at Chicago, 845 South Damen Ave, Chicago, IL 60612 USA.
Carolyn DickensDepartment of Biobehavioral Health Science, College of Nursing, University of Illinois at Chicago, 845 South Damen Ave, Chicago, IL 60612 USA.
Amer ArdatiDivision of Cardiology, College of Medicine, University of Illinois at Chicago, 840 South Wood Street, Chicago, IL 60612 USA.
Jose D FloresCardiology patient advisors, College of Applied Health Sciences, University of Illinois at Chicago, 1919 W Taylor St., Chicago, IL 60612 USA.
Matt BaumannCardiology patient advisors, College of Applied Health Sciences, University of Illinois at Chicago, 1919 W Taylor St., Chicago, IL 60612 USA.
Betty WellandCardiology patient advisors, College of Applied Health Sciences, University of Illinois at Chicago, 1919 W Taylor St., Chicago, IL 60612 USA.
Barbara Di EugenioDepartment of Computer Science, College of Engineering, University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607 USA.

Funding

SCH: INT: MyPHA: Automatically generating personalized accounts of in-patient hospitalizationR01CA225446 · NCI · UNIVERSITY OF ILLINOIS AT CHICAGO · PI DI EUGENIO, BARBARA · 2018 to 2021
$1.5M
NCI NIH HHS R01 CA225446
6 · The paper itself

Abstract

Comprehending medical information is a challenging task, especially for people who have not received formal medical education. When patients are discharged from the hospital, they are provided with lengthy medical documents that contain intricate terminologies. Studies have shown that if people do not understand the content of their health documents, they will neither look for new information regarding their illness nor will they take actions to prevent or recover from their health issue. In this article, we highlight the need for generating personalized hospital-stay summaries and several research challenges associated with this task. The proposed directions are directly informed by our ongoing work in generating concise and comprehensible hospitalization summaries that are tailored to suit the patient's understanding of medical terminologies and level of engagement in improving their own health. Our preliminary evaluation shows that our summaries effectively present required medical concepts.

Indexed as

Discharge summariesNatural language generationPatient-centric informationPersonalizationSimplification

Identifiers

PMID35415420
PMCPMC8982693

What OpenQuestion holds

Textmetadata
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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.