Evidence map›Paper›PMID 32624060›Full record

ArticlePrimary health care research & development2020

Development and validation of an instrument for measuring competencies on public health informatics of primary health care worker (PHIC4PHC) in Indonesia.

Enny Rachmani, Chien-Yeh Hsu, Peter WuShou Chang, Anis Fuad, Nurjanah Nurjanah, Guruh Fajar Shidik, Dina Nur Anggraini Ningrum, Ming-Chin Lin

Abstract read
In one paragraph

Article in Primary health care research & development, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

8 authors.

Enny RachmaniCollege of Medical Science and Technology, Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei City, Taiwan.ORCID 0000-0002-4582-288X
Chien-Yeh HsuDepartment of Information Management, National Taipei University of Nursing and Health Science, Taipei City, Taiwan.
Peter WuShou ChangTUFTS University Medical School, Chung Shan Medical University, Taichung, Taiwan.
Anis FuadCollege of Medical Science and Technology, Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei City, Taiwan.
Nurjanah NurjanahDepartment of Public Health, Faculty of Health Science, Universitas Dian Nuswantoro, Kota Semarang, Jawa Tengah, Indonesia.
Guruh Fajar ShidikDepartment of Health Information Management, Faculty of Health Science, Universitas Dian Nuswantoro, Semarang, Jawa Tengah, Indonesia.
Dina Nur Anggraini NingrumDepartment of Public Health, Semarang State University, Kota Semarang, Jawa Tengah, Indonesia.
Ming-Chin LinCollege of Medical Science and Technology, Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei City, Taiwan.ORCID 0000-0001-9624-9705

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Because of the increasing adoption and use of technology in primary health care (PHC), public health informatics competencies (PHIC) are becoming essential for public health workers. Unfortunately, no studies have measured PHIC in resource-limited setting. This paper describes the process of developing and validating Public Health Informatics Competencies for Primary Health Care (PHIC4PHC), an instrument for measuring PHC workers' competencies in public health informatics. Method: This study developed a questionnaire that had three stages: the Delphi technique, a pretest, and field test. Eleven academicians from a university and 13 PHC workers joined 2 rounds of group discussion in the first stage. The second stage comprised two pilot studies with 75 PHC workers in Semarang Municipality. The third stage involved validating the questionnaire with 462 PHC workers in Kendal District. This study used Pearson's product-moment correlation for the validity check and Cronbach's alpha coefficient for determining the internal consistency. This study used the K-means algorithm for clustering the results of the PHIC4PHC questionnaire. Results and Conclusion: PHIC4PHC is the first comprehensive PHIC questionnaire administered in a resource-limited setting, consisting of 11 indicators and 42 measurement items concerning knowledge of health information systems, skills required for health data management, ethical aspects of data sharing and health information literacy. The final results of PHIC4PHC were clustered into three classes based on the K-means algorithm. Overall, 45.7% PHC workers achieved medium competency, whereas 25.6% and 27.7% achieved low and high competency, respectively. Men had higher competency than women. The higher the worker's level of education, the higher the PHIC level; the longer the worker's work experience, the lower the PHIC score; and the greater the worker's age, the lower the PHIC score. Measuring and monitoring PHIC is vital to support successful health IT adoption in PHC.

Indexed as

Primary Health CarePublic Health InformaticsAdultFemaleHealth PersonnelHumansIndonesiaMaleMiddle AgedPilot Projectscomputer literacydeveloping countrieshealth information systemprimary health carepublic health informatics

Identifiers

PMID32624060
PMCPMC7372181

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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.