Biometric-Based Frista Application And Outpatient Satisfaction At Darkuthni Primary Clinic
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Keywords

Patient Satisfaction
Biometric Identification
Digital Health Services
Outpatient Services
Health Information Systems

How to Cite

Adriansyah, A., Latu, S., Satrianegara, F., Handayani, R., & Haji Saeni, R. (2026). Biometric-Based Frista Application And Outpatient Satisfaction At Darkuthni Primary Clinic. Jurnal Kesehatan Manarang, 12(2), 251–260. https://doi.org/10.33490/jkm.v12i2.2328

Abstract

Outpatient care requires accurate, timely, convenient, and secure patient identification. However, problems related to patient identification, administrative efficiency, and data security may affect patients’ experiences and satisfaction. FRISTA is a biometric authentication system designed to support automated patient identification. Nevertheless, the association between FRISTA use and outpatient satisfaction in primary healthcare settings in Indonesia remains insufficiently evaluated. This study aimed to examine the association between the use of the FRISTA application and outpatient satisfaction at Darkuthni Primary Clinic, Tojo Una-Una Regency, Central Sulawesi, Indonesia. A quantitative approach with a cross-sectional design was employed, involving 150 outpatients selected using stratified random sampling from the Obstetrics and Gynecology, Internal Medicine, and Neurology Clinics. Data were analyzed using the Chi-square test and multivariate binary logistic regression, with results expressed as odds ratios (OR) and 95% confidence intervals (CI). The Chi-square test showed that ease of service access, service speed, patient identification accuracy, and personal data security were significantly associated with patient satisfaction (p < 0.05). Multivariate binary logistic regression showed that patient identification accuracy (OR = 2.226; 95% CI: 1.019–4.861; p = 0.045) and personal data security (OR = 1.748; 95% CI: 1.028–2.972; p = 0.039) remained significantly associated with patient satisfaction, whereas ease of service access and service speed were not independently associated with patient satisfaction. The multivariate binary logistic regression model yielded a Nagelkerke R² of 0.897. The use of the FRISTA biometric application was significantly associated with outpatient satisfaction. Therefore, improving patient identification accuracy and strengthening personal data security should be prioritized in implementing biometric-based digital health systems in primary healthcare settings to enhance patient satisfaction.

https://doi.org/10.33490/jkm.v12i2.2328
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References

Ampamya, S., Kitayimbwa, J. M., & Were, M. C. (2020). International Journal of Medical Informatics Performance of an open source facial recognition system for unique patient matching in a resource-limited setting ⋆. International Journal of Medical Informatics, 141(May). https://doi.org/https://doi.org/10.1016/j.ijmedinf.2020.104180

Belfrage, S., Helgesson, G., & Lynøe, N. (2022). Trust and digital privacy in healthcare : a cross ‑ sectional descriptive study of trust and attitudes towards uses of electronic health data among the general public in Sweden. BMC Medical Ethics, 23(19), 1–8. https://doi.org/https://doi.org/10.1186/s12910-022-00758-z

BPJS Kesehatan. (2020). Peraturan Badan Penyelenggara Jaminan Sosial Kesehatan Nomor 6 Tahun 2020 Tentang Sistem Pencegahan Kecurangan Dalam Pelaksanaan Program Jaminan Kesehatan. https://jdih.bpjs-kesehatan.go.id/

Creswell, J. ., & Ceswell, J. . (2023). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches Research methods. SAGE Publications.

Farias, M. A., Badino, M., Jose, M., & Apocada, F. De. (2024). Patient satisfaction with telemedicine for substance-related disorders. Digital Health, 10, 1–7. https://doi.org/10.1177/20552076241240974

Field, A. (2024). Discovering statistics using IBM SPSS statistics (6th ed.). SAGE Publications. https://us2.sagepub.com/en-us/nam/discovering-statistics-using-ibm-spss-statistics/book285130

Hair, J. F., Black, W. C., Babin, B. Ja., & Erson, R. E. (2021). Multivariate data analysis (8th ed.). Cengage Learning.

Handayani, R., & Saeni, R. H. (2024). Metode Penelitian dan Statistik. Bintang Semesta Media.

Hege, I., Tolks, D., Kuhn, S., & Shiozawa, T. (2020). Digital skills in healthcare. GMS Journal for Medical Education 2020, 37(6), 4–9. https://doi.org/10.3205/zma001356

Kodobo, U., Baso, S., & Hutauruk, M. V. R. . (2022). Hubungan Identifikasi Pasien Secara Benar Dengan Kepuasan Pasien Di Instalasi Gawat Darurat UPTD Rumah Sakit Menembo-Nembo Bitung. Jurnal Rumpun Ilmu Kesehatan, 2(1), 1–6. https://ejurnal.politeknikpratama.ac.id/index.php/JRIK/article/view/527

Kortli, Y., Jridi, M., Falou, A. Al, & Atri, M. (2020). Face Recognition Systems : A Survey. MDPI, 20(342). https://doi.org/https://doi.org/10.3390/s20020342

Liu, H., Gonzales, R., & Martinez, O. S. (2020). Enhancing Privacy and Data Security across Healthcare Applications Using Blockchain and. Healthcare (MDPI), 8, 243. https://doi.org/doi:10.3390/healthcare8030243

Meegada, S. R. (2025). Biometric technology in healthcare : Balancing security benefits with implementation challenges. World Journal of Advanced Research and Reviews, 26(01), 1864–1870. https://doi.org/https://doi.org/10.30574/wjarr.2025.26.1.1239

O.Navarro-Martinez, Igual-Garcia, J., & Traver-Salcedo, V. (2023). Bridging the educational gap in terms of digital competences between healthcare institutions ’ demands and professionals ’ needs. BMC Nursing, 22(144), 1–8. https://doi.org/10.1186/s12912-023-01284-y

Wells, A., & Usman, A. B. (2024). Privacy and biometrics for smart healthcare systems : attacks , and techniques. Information Security Journal: A Global Perspective, 33(3), 307–331. https://doi.org/10.1080/19393555.2023.2260818

Yuliati. (2024). Relationship Between Waiting Time and Patient Satisfaction at the Surgery Polyclinic of Bekasi District Hospital. Comprehensive Nursing Journal, 10, 397–402. https://doi.org/http://doi.org/10.33755/jkk

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Copyright (c) 2026 Adriansyah Adriansyah, Saparuddin Latu, Fais Satrianegara, Rika Handayani, Rahmat Haji Saeni