Evidence map›Paper›PMID 38414827›Full record

ArticleFrontiers in digital health2023

Electronic medical record systems data use in decision-making and associated factors among health managers at public primary health facilities, Dodoma region: a cross-sectional analytical study.

Eusebi Cornelius Kessy, Stephen Mathew Kibusi, Julius Edward Ntwenya

Abstract read
In one paragraph

Article in Frontiers in digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

3 authors.

Eusebi Cornelius KessySchool of Nursing and Public Health, The University of Dodoma, Dodoma, Tanzania.
Stephen Mathew KibusiSchool of Nursing and Public Health, The University of Dodoma, Dodoma, Tanzania.
Julius Edward NtwenyaSchool of Nursing and Public Health, The University of Dodoma, Dodoma, Tanzania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tanzania has shown some improvements in the adoption of electronic medical record (EMR) systems in public health facilities; however, the rate of utilization of data generated from EMRs among health managers is not well documented. This study aims to assess the use of electronic medical record systems data in decision-making among health managers at public primary health facilities in Dodoma Region, Central Tanzania. Methods: A facility-based quantitative cross-sectional analytical study was conducted among 308 randomly selected health managers. A self-administered questionnaire supplemented with documentary review was used. Descriptive summary statistics and bivariable and multivariable logistic regression analyses (crude and adjusted odds ratios) were used. A Results: Overall, more than a third (40.6%) of the health managers, that is 174 of the 308 included in the study, reported using data generated by EMR systems in decision-making. One-third (33.4%) of the health managers were adequately using data generated by EMR systems, of which 39.3% used data to support continuous quality improvement initiatives. Among the facilities visited, only nine (30%) had good documented EMR systems data use. Access to computers [adjusted odds ratio (AOR) = 4.72, 95% confidence interval (CI): 1.65, 13.48, Conclusions: The findings of this study indicate that utilization of EMR system data in decision-making among health managers was optimal. It was found that training in itself is insufficient to improve use of EMR, which points to more organizational aspects of work routine as a challenge. Hence, a comprehensive approach that addresses these factors is essential for maximizing EMR system data use in decision-making.

Indexed as

cross-sectional analytical studydata usedecision-makingelectronic medical recordshealth managerspublic primary health facilities

Identifiers

PMID38414827
PMCPMC10897969

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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.