Digital maturity index instrument development for primary health care in Indonesia: a sequential exploratory mixed-methods approach

BACKGROUND: Digital health transformation in Indonesia is a comprehensive digitalization strategy aimed at improving health services, particularly in primary health care (PHC). There are no digital maturity instrument tools available to measure the digitalization level in PHC yet. This study aims to develop a particular digital maturity index (DMI) instrument to measure the digital maturity in the PHC. METHOD: The research design employed a Sequential Exploratory Mixed-Methods Approach. First phase, A qualitative data collection conducted through a Focused Group Discussion. Forty-one health care workers in PHCs from South Sulawesi and West Java provinces were involved as participants. Participants were selected using criterion-based purposive sampling. Qualitative data were processed using the ScreenQ software, and content analysis was conducted. Afterward, two quantitative research instrument prototypes were built using a predetermined theory. The quantitative phase of the survey involved 30 health care workers in the same provinces, with one respondent representing one PHC. The data obtained is transformed and analyzed using Rasch modeling. The maturity levels are categorized into “Basic”, “Utilization”, “Development”, “Coordination”, and “Sustainable”. A comparison of the two prototypes was then analyzed to determine the most significant one based on the most valid and reliable result. RESULT: Qualitative analysis generated five dimensions of the digital maturity index: Stewardship, Human Resources, Infrastructure, Information System, and Health Facility. The reliability, index separation, and Cronbach’s alpha for prototype version 1 are 0.91, 3.10, and 0.95, respectively. The reliability, index separation, and Cronbach’s alpha for prototype version 2 are 0.76, 1.79, and 0.98, respectively. The maturity index based on both prototypes showed that 87% of total PHCs are in the development level. CONCLUSION: The Digital Maturity Instrument version 1 demonstrates promising preliminary psychometric properties and is suitable for further large-scale validation.