Patient Age: A Determining Factor in Mobile JKN Adoption

Abstract

The Mobile JKN application represents a significant national initiative to modernize health insurance services in Indonesia, yet adoption rates remain suboptimal despite near-universal population coverage. This study examined the influence of patient demographic characteristics on Mobile JKN utilization for outpatient registration at RSUD Sejiran Setason, a regional hospital in Bangka Belitung. A quantitative cross-sectional study was conducted with 345 respondents selected through accidental sampling. Data were collected using a structured questionnaire measuring four demographic variables (age, gender, education, occupation) and Mobile JKN usage status. Binary logistic regression analysis was employed to determine predictor effects on adoption behavior. Mobile JKN adoption was 38.60%, indicating substantial underutilization. Among demographic predictors, only age demonstrated significant positive influence (p = 0.006, Exp(B) = 1.023), with each additional year increasing adoption likelihood by 2.3%. Gender (p = 0.633), education (p = 0.947), and occupation (p = 0.449) showed no significant effects. The demographic model explained merely 4.4% of variance (Nagelkerke R² = 0.044), suggesting that unmeasured factors substantially determine adoption behavior. Age positively predicts Mobile JKN adoption, contradicting conventional digital divide assumptions, while other demographic characteristics prove insufficient for predicting digital health platform utilization. Implementation strategies should transcend demographic targeting and address systemic, psychological, and technological determinants to achieve equitable digital health transformation in regional Indonesian healthcare settings.

Keywords

JKN Mobile Adoption; Demographic Characteristics; Digital Health Transformation