Evidence map›Paper›PMID 26208595›Full record

ArticleJournal of medical systems2015

Development and User Research of a Smart Bedside Station System toward Patient-Centered Healthcare System.

Sooyoung Yoo, Kee-Hyuck Lee, Hyunyoung Baek, Borim Ryu, Eunja Chung, Kidong Kim, Jay Chaeyong Yi, Soo Beom Park, Hee Hwang

Abstract read
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In one paragraph

Article in Journal of medical systems, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

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

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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

9 authors.

Sooyoung YooCenter for Medical Informatics, Seoul National University Bundang Hospital, Seongnam-si, South Korea.
Kee-Hyuck Lee
Hyunyoung Baek
Borim Ryu
Eunja Chung
Kidong Kim
Jay Chaeyong Yi
Soo Beom Park
Hee Hwang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

User experience design that reflects real-world application and aims to support suitable service solutions has arisen as one of the current issues in the medical informatics research domain. The Smart Bedside Station (SBS) is a screen that is installed on the bedside for the personal use and provides a variety of convenient services for the patients. Recently, bedside terminal systems have been increasingly adopted in hospitals due to the rapid growth of advanced technology in healthcare at the point of care. We designed user experience (UX) research to derive users' unmet needs and major functions that are frequently used in the field. To develop the SBS service, a service design methodology, the Double Diamond Design Process Model, was undertaken. The problems or directions of the complex clinical workflow of the hospital, the requirements of stakeholders, and environmental factors were identified through the study. The SBS system services provided to patients were linked to the hospital's main services or to related electronic medical record (EMR) data. Seven key services were derived from the results of the study. The primary services were as follows: Bedside Check In and Out, Bedside Room Service, Bedside Scheduler, Ready for Rounds, My Medical Chart, Featured Healthcare Content, and Bedside Community. This research developed a patient-centered SBS system with improved UX using service design methodology applied to complex and technical medical services, providing insights to improve the current healthcare system.

Indexed as

User-Computer InterfaceElectronic Health RecordsHumansInformation SystemsPatient-Centered CarePatient SatisfactionPoint-of-Care SystemsSoftware Design

Identifiers

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.