Development and validation of an instrument for measuring competencies on public health informatics of primary health care worker (PHIC4PHC) in Indonesia. (6th July 2020)

• Record Type: Journal Article
• Authors: Rachmani, Enny; Hsu, Chien-Yeh; Chang, Peter WuShou; Fuad, Anis; Nurjanah, Nurjanah; Shidik, Guruh Fajar; Ningrum, Dina Nur Anggraini; Lin, Ming-Chin
• Is Part Of: Primary health care research & development. Volume 21(2020)
• Publication Date: 2020-07-06
• Subjects: computer literacy, -- developing countries, -- health information system, -- primary health care, -- public health informatics; Family medicine -- Great Britain -- Periodicals; Primary care (Medicine) -- Great Britain -- Periodicals; 362.1094105
• DOI: 10.1017/S1463423620000018
• Languages: English
• ISSNs: 1463-4236

Abstract

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.