Evidence map›Paper›PMID 29237579›Full record

ArticleJMIR mHealth and uHealth2017

Usage Pattern Differences and Similarities of Mobile Electronic Medical Records Among Health Care Providers.

Yura Lee, Yu Rang Park, Junetae Kim, Jeong Hoon Kim, Woo Sung Kim, Jae-Ho Lee

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. 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

6 authors.

Yura Lee *Department of Biomedical Informatics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0003-2048-3727
Yu Rang Park *Department of Biomedical Informatics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-4210-2094
Junetae KimSchool of Management Engineering, Korea Advanced Institute of Science and Technology, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-4278-3491
Jeong Hoon KimMedical Information Office, Asan Medical Center, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-2338-9827
Woo Sung KimDepartment of Biomedical Informatics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-4396-4403
Jae-Ho LeeDepartment of Biomedical Informatics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0003-2619-1231

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecently, many hospitals have introduced mobile electronic medical records (mEMRs). Although numerous studies have been published on the usability or usage patterns of mEMRs through user surveys, investigations based on the real data usage are lacking.

objectiveAsan Medical Center, a tertiary hospital in Seoul, Korea, implemented an mEMR program in 2010. On the basis of the mEMR usage log data collected over a period of 4.5 years, we aimed to identify a usage pattern and trends in accordance with user occupation and to disseminate the factors that make the mEMR more effective and efficient.

methodsThe mEMR log data were collected from March 2012 to August 2016. Descriptive analyses were completed according to user occupation, access time, services, and wireless network type. Specifically, analyses targeted were as follows: (1) the status of the mEMR usage and distribution of users, (2) trends in the number of users and usage amount, (3) 24-hour usage patterns, and (4) trends in service usage based on user occupations. Linear regressions were performed to model the relationship between the time, access frequency, and the number of users. The differences between the user occupations were examined using Student t tests for categorical variables.

resultsApproximately two-thirds of the doctors and nurses used the mEMR. The number of logs studied was 7,144,459. Among 3859 users, 2333 (60.46%) users were nurses and 1102 (28.56%) users were doctors. On average, the mEMR was used 1044 times by 438 users per day. The number of users and amount of access logs have significantly increased since 2012 (P<.001). Nurses used the mEMR 3 times more often than doctors. The use of mEMR by nurses increased by an annual average of 51.5%, but use by doctors decreased by an annual average of 7.7%. For doctors, the peak usage periods were observed during 08:00 to 09:00 and 17:00 to 18:00, which were coincident with the beginning of ward rounds. Conversely, the peak usage periods for the nurses were observed during 05:00 to 06:00, 12:00 to 13:00, and 20:00 to 21:00, which effectively occurred 1 or 2 hours before handover. In more than 80% of all cases, the mEMR was accessed via a nonhospital wireless network.

conclusionsThe usage patterns of the mEMR differed between doctors and nurses according to their different workflows. In both occupations, mEMR was highly used when personal computer access was limited and the need for patient information was high, such as during ward rounds or handover periods.

Indexed as

communicationelectronic health recordsmobile applicationsnursespatient handoffphysiciansrounds

Identifiers

PMID29237579
PMCPMC5745350

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.