Evidence map›Paper›PMID 23423776›Full record

ArticleJournal of medical systems2013

An architecture model for multiple disease management information systems.

Lichin Chen, Hui-Chu Yu, Hao-Chun Li, Yi-Van Wang, Huang-Jen Chen, I-Ching Wang, Chiou-Shiang Wang, Hui-Yu Peng, Yu-Ling Hsu, Chi-Huang Chen and 4 more

Abstract readEvaluation Study
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In one paragraph

Article in Journal of medical systems, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Lichin ChenGraduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 10617, Taiwan, d98945012@ntu.edu.tw.
Hui-Chu Yu
Hao-Chun Li
Yi-Van Wang
Huang-Jen Chen
I-Ching Wang
Chiou-Shiang Wang
Hui-Yu Peng
Yu-Ling Hsu
Chi-Huang Chen
Lee-Ming Chuang
Hung-Chang Lee
Yufang Chung
Feipei Lai

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disease management is a program which attempts to overcome the fragmentation of healthcare system and improve the quality of care. Many studies have proven the effectiveness of disease management. However, the case managers were spending the majority of time in documentation, coordinating the members of the care team. They need a tool to support them with daily practice and optimizing the inefficient workflow. Several discussions have indicated that information technology plays an important role in the era of disease management. Whereas applications have been developed, it is inefficient to develop information system for each disease management program individually. The aim of this research is to support the work of disease management, reform the inefficient workflow, and propose an architecture model that enhance on the reusability and time saving of information system development. The proposed architecture model had been successfully implemented into two disease management information system, and the result was evaluated through reusability analysis, time consumed analysis, pre- and post-implement workflow analysis, and user questionnaire survey. The reusability of the proposed model was high, less than half of the time was consumed, and the workflow had been improved. The overall user aspect is positive. The supportiveness during daily workflow is high. The system empowers the case managers with better information and leads to better decision making.

Indexed as

Disease ManagementSoftwareSystems IntegrationAdultCase ManagementComputer SystemsFemaleHumansInformation SystemsMaleMedical InformaticsMiddle AgedQuality Assurance, Health CareSurveys and Questionnaires

Identifiers

What OpenQuestion holds

Textmetadata
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.