Optimalisasi Potensi Sistem Penjadwalan Janji Temu Online di Rumah Sakit

Eufrasia Victa Swastika Anggriasti, Purnawan Junadi

Abstract


Salah satu penyebab utama ketidakpuasan pasien dalam penjadwalan layanan rawat jalan adalah waktu tunggu yang terlalu lama, sehingga diperlukan penjadwalan yang adil berdasarkan kompetensi klinis. Penelitian ini bertujuan untuk menganalisis jurnal-jurnal terkait dengan optimalisasi penjadwalan janji temu dalam konteks rawat jalan. Dengan melakukan tinjauan komprehensif terhadap artikel-artikel yang diterbitkan antara 20s hingga 2024. Metode penelitian yang digunakan adalah dengan melakukan pencarian sistematis dan terarah menggunakan basis data akademik yang relevan, seperti Science Direct. Sebanyak 100 artikel diidentifikasi awalnya, namun hanya 14 yang paling relevan yang dipilih untuk analisis mendalam. Jurnal-jurnal tersebut dievaluasi untuk menilai berbagai metode optimalisasi yang digunakan, termasuk algoritma pembelajaran mesin, simulasi, dan teknologi IoT. Hasil analisis menunjukkan bahwa berbagai metode tersebut telah berhasil meningkatkan efisiensi penjadwalan dan kepuasan pasien. Penelitian literatur yang di temukan menekankan pentingnya penggunaan berbagai pendekatan optimalisasi untuk meningkatkan efisiensi dan kepuasan pasien dalam layanan kesehatan. Temuan ini menunjukkan potensi besar teknologi seperti pembelajaran mesin, simulasi, dan IoT dalam memperbaiki kualitas layanan kesehatan. Dapat disimpulkan bahwa temuan ini menegaskan pentingnya terus mengembangkan dan menerapkan strategi optimalisasi yang sesuai dengan kebutuhan spesifik dari masing-masing konteks layanan kesehatan untuk meningkatkan kualitas, aksesibilitas, dan kepuasan pasien.

Keywords


Optimalisasi; Janji Temu Online; Efisiensi; Kepuasan Pasien.

Full Text:

PDF

References


Abreu, P., Santos, D., & Barbosa-Povoa, A. (2023). Data-driven forecasting for operational planning of emergency medical services. Socio-Economic Planning Sciences, 86, 101492. https://doi.org/https://doi.org/10.1016/j.seps.2022.101492

Agnihothri, S., Cappanera, P., Nonato, M., & Visintin, F. (2024). Appointment scheduling in surgery pre-admission testing clinics. Omega, 123, 102994. https://doi.org/https://doi.org/10.1016/j.omega.2023.102994

Ahmadi-Javid, A., Jalali, Z., & Klassen, K. J. (2017). Outpatient appointment systems in healthcare: A review of optimization studies. European Journal of Operational Research, 258(1), 3–34. https://doi.org/https://doi.org/10.1016/j.ejor.2016.06.064

Anil, A., Saravanan, A., Singh, S., Shamim, M. A., Tiwari, K., Lal, H., Seshatri, S., Gomaz, S. B., Karat, T. P., Dwivedi, P., Varthya, S. B., Kaur, R. J., Satapathy, P., Padhi, B. K., Gaidhane, S., Patil, M., Khatib, M. N., Barboza, J. J., & Sah, R. (2023). Are paid tools worth the cost? A prospective cross-over study to find the right tool for plagiarism detection. Heliyon, 9(9), e19194. https://doi.org/10.1016/j.heliyon.2023.e19194

Apergi, L. A., Baras, J. S., Golden, B. L., & Wood, K. E. (2020). An optimization model for multi-appointment scheduling in an outpatient cardiology setting. Operations Research for Health Care, 26, 100267. https://doi.org/https://doi.org/10.1016/j.orhc.2020.100267

Cai, Y., Song, H., & Wang, S. (2024). Managing appointment-based services with electronic visits. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2024.01.012

Eminoğlu, A., & Çelikkanat, Ş. (2024). Assessment of the relationship between executive Nurses’ leadership Self-Efficacy and medical artificial intelligence readiness. International Journal of Medical Informatics, 184, 105386. https://doi.org/https://doi.org/10.1016/j.ijmedinf.2024.105386

Fan, G., Deng, Z., Ye, Q., & Wang, B. (2021). Machine learning-based prediction models for patients no-show in online outpatient appointments. Data Science and Management, 2, 45–52. https://doi.org/10.1016/j.dsm.2021.06.002

Farage, M., Miller, K. W., Elsner, P., & Maibach, H. (2008). Intrinsic and extrinsic factors in skin ageing: A review. International Journal of Cosmetic Science, 30, 87–95. https://doi.org/10.1111/j.1468-2494.2007.00415.x

Guo, H., Xie, Y., Jiang, B., & Tang, J. (2024). When outpatient appointment meets online consultation: A joint scheduling optimization framework. Omega, 127, 103101. https://doi.org/https://doi.org/10.1016/j.omega.2024.103101

Hadid, M., Elomri, A., Jouini, O., Kerbache, L., Saleh, A., & Hamad, A. (2022). Multi-Objective Simulation-Based Optimization for Effective Management of the Outpatient Chemotherapy Process. IFAC-PapersOnLine, 55(10), 1639–1644. https://doi.org/https://doi.org/10.1016/j.ifacol.2022.09.632

Küçük, A., Demirci, M., Kerman, G., & Soner Özsoy, V. (2021). Evaluating of hospital appointment systems in Turkey: Challenges and opportunities. Health Policy and Technology, 10(1), 69–74. https://doi.org/https://doi.org/10.1016/j.hlpt.2020.11.008

Legato, P., Mazza, R. M., & Fortino, G. (2022). A multi-level simulation-based optimization framework for IoT-enabled elderly care systems. Simulation Modelling Practice and Theory, 114, 102420. https://doi.org/https://doi.org/10.1016/j.simpat.2021.102420

Namakshenas, M., Mazdeh, M. M., Braaksma, A., & Heydari, M. (2023). Appointment scheduling for medical diagnostic centers considering time-sensitive pharmaceuticals: A dynamic robust optimization approach. European Journal of Operational Research, 305(3), 1018–1031. https://doi.org/https://doi.org/10.1016/j.ejor.2022.06.037

Srinivas, S., & Ravindran, A. R. (2018). Optimizing outpatient appointment system using machine learning algorithms and scheduling rules: A prescriptive analytics framework. Expert Systems with Applications, 102, 245–261. https://doi.org/https://doi.org/10.1016/j.eswa.2018.02.022

Sugiyono. (2013). Metode Peneltian Pendidikan Pendekatan Kuantitatif, Kualitatif, dan R&D. Bandung: Alfabeta.

Wan, M., Shukla, N., Li, J., & Pradhan, B. (2023). Optimization of teleconsultation appointment scheduling in National Telemedicine Center of China. Computers & Industrial Engineering, 183, 109492. https://doi.org/https://doi.org/10.1016/j.cie.2023.109492

Wang, J., Chen, Y. (Frank), & Xu, M. (2018). Optimization and approximation methods for dynamic appointment scheduling with patient choices. Computers & Operations Research, 92, 65–76. https://doi.org/https://doi.org/10.1016/j.cor.2017.12.009

Wynn, S. G., & Fougère, B. J. B. T.-V. H. M. (Eds.). (2007). Materia Medica (pp. 459–672). Mosby. https://doi.org/https://doi.org/10.1016/B978-0-323-02998-8.50028-7




DOI: https://doi.org/10.51849/j-p3k.v5i3.428

Refbacks

  • There are currently no refbacks.


slot dana

slot