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Modeling antecedents of electronic medical record system implementation success in low-resource setting hospitals

Overview of attention for article published in BMC Medical Informatics and Decision Making, August 2015
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Title
Modeling antecedents of electronic medical record system implementation success in low-resource setting hospitals
Published in
BMC Medical Informatics and Decision Making, August 2015
DOI 10.1186/s12911-015-0192-0
Pubmed ID
Authors

Binyam Tilahun, Fleur Fritz

Abstract

With the increasing implementation of Electronic Medical Record Systems (EMR) in developing countries, there is a growing need to identify antecedents of EMR success to measure and predict the level of adoption before costly implementation. However, less evidence is available about EMR success in the context of low-resource setting implementations. Therefore, this study aims to fill this gap by examining the constructs and relationships of the widely used DeLone and MacLean (D&M) information system success model to determine whether it can be applied to measure EMR success in those settings. A quantitative cross sectional study design using self-administered questionnaires was used to collect data from 384 health professionals working in five governmental hospitals in Ethiopia. The hospitals use a comprehensive EMR system since three years. Descriptive and structural equation modeling methods were applied to describe and validate the extent of relationship of constructs and mediating effects. The findings of the structural equation modeling shows that system quality has significant influence on EMR use (β = 0.32, P < 0.05) and user satisfaction (β = 0.53, P < 0.01); information quality has significant influence on EMR use (β = 0.44, P < 0.05) and user satisfaction (β = 0.48, P < 0.01) and service quality has strong significant influence on EMR use (β = 0.36, P < 0.05) and user satisfaction (β = 0.56, P < 0.01). User satisfaction has significant influence on EMR use (β = 0.41, P < 0.05) but the effect of EMR use on user satisfaction was not significant. Both EMR use and user satisfaction have significant influence on perceived net-benefit (β = 0.31, P < 0.01; β = 0.60, P < 0.01), respectively. Additionally, computer literacy was found to be a mediating factor in the relationship between service quality and EMR use (P < 0.05) as well as user satisfaction (P < 0.01). Among all the constructs, user satisfaction showed the strongest effect on perceived net-benefit of health professionals. EMR implementers and managers in developing countries are in urgent need of implementation models to design proper implementation strategies. In this study, the constructs and relationships depicted in the updated D&M model were found to be applicable to assess the success of EMR in low resource settings. Additionally, computer literacy was found to be a mediating factor in EMR use and user satisfaction of health professionals. Hence, EMR implementers and managers in those settings should give priority in improving service quality of the hospitals like technical support and infrastructure; providing continuous basic computer trainings to health professionals; and give attention to the system and information quality of the systems they want to implement.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 269 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
United Kingdom 1 <1%
Unknown 265 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 47 17%
Lecturer 21 8%
Student > Ph. D. Student 21 8%
Student > Bachelor 20 7%
Researcher 19 7%
Other 57 21%
Unknown 84 31%
Readers by discipline Count As %
Medicine and Dentistry 42 16%
Computer Science 37 14%
Nursing and Health Professions 25 9%
Social Sciences 19 7%
Business, Management and Accounting 16 6%
Other 38 14%
Unknown 92 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 August 2015.
All research outputs
#16,546,395
of 24,344,498 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,382
of 2,075 outputs
Outputs of similar age
#159,167
of 268,710 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#27
of 36 outputs
Altmetric has tracked 24,344,498 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,075 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 268,710 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.