Design and Implementation of an Agile-Based Electronic Prescription System for Neurological Medications

Authors

  • Denny Jean Cross Sihombing Information System Study Program, Atma Jaya Catholic University of Indonesia

Keywords:

Electronic Prescription, Agile Methodology, Neurology Clinics

Abstract

This study addresses the complexity of managing neurological medication prescriptions by implementing an Agile-based electronic prescription system. The main issues faced in neurological medical practice are complex drug dosages, drug interactions, and effective patient monitoring. To tackle these problems, this research employs qualitative and quantitative methods, including user needs analysis, application development, and user acceptance evaluation. The study's findings indicate that implementing the Agile-based electronic prescription system enhances neuro-logical medical practice efficiency, safety, and service quality. This system provides flexibility and certainty in patient care by its ability to adapt to changes in patient conditions and treatment protocols. The primary contribution of this research is the development of an Agile-based electronic prescription system capable of addressing the complexity of managing neurological medication prescriptions. This study offers a new perspective on paradigm shifts in prescription management through technology-driven approaches, thereby contributing to advancing more targeted and improved healthcare services in the future.

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References

Alami, A., Krancher, O., & Paasivaara, M. (2022). The journey to technical excel-lence in agile software development. Information and Software Technology, 150. https://doi.org/10.1016/j.infsof.2022.106959

Al-Hassan, M., & AlQahtani, S. (2019). Preparedness of dental clinics for medical emergencies in Riyadh, Saudi Arabia. Saudi Dental Journal, 31(1), 115–121. https://doi.org/10.1016/j.sdentj.2018.11.006

Almeida, F., Simões, J., & Lopes, S. (2022). Exploring the Benefits of Combining DevOps and Agile. Future Internet, 14(2). https://doi.org/10.3390/fi14020063

Bhat, S., Birajdar, G. K., & Patil, M. D. (2023). A comprehensive survey of deep learning algorithms and applications in dental radiograph analysis. In Healthcare Analytics (Vol. 4). Elsevier Inc. https://doi.org/10.1016/j.health.2023.100282

Bin, K. J., Higa, N., da Silva, J. H., Quagliano, D. A., Hangai, R. K., Cobello-Júnior, V., Pereira, A. J. R., Carneiro-D’albuquerque, L. A., Carrilho, F. J., Wen, C. L., & Ono, S. K. (2021). Building an outpatient telemedicine care pilot using scrum-like framework within a medical residency program. Clinics, 76. https://doi.org/10.6061/CLINICS/2021/E2795

Chan, K., Sepassi, A., Saunders, I. M., Goodman, A., & Watanabe, J. H. (2022). Ef-fects of financial toxicity on prescription drug use and mental well-being in cancer patients. Exploratory Research in Clinical and Social Pharmacy, 6. https://doi.org/10.1016/j.rcsop.2022.100136

Das, A. K., Islam, M. N., Billah, M. M., & Sarker, A. (2021). COVID-19 pandemic and healthcare solid waste management strategy – A mini-review. In Science of the Total Environment (Vol. 778). Elsevier B.V. https://doi.org/10.1016/j.scitotenv.2021.146220

Hasan, R., Ta, A.-, & Razali, R. (2013). Prioritizing Requirements in Agile Devel-opment : A Conceptual Framework. Procedia Technology, 11(Iceei), 733–739. https://doi.org/10.1016/j.protcy.2013.12.252

Hatta, T., Ide, K., Fujita, M., & Ikka, T. (2022). Financial risks posed by unproven cell interventions: Estimation of refunds from medical expense deductions in Ja-pan. In Stem Cell Reports (Vol. 17, Issue 5, pp. 1016–1018). Cell Press. https://doi.org/10.1016/j.stemcr.2022.03.015

Horita, H. M., Friesen, T. L., Cahill, G., Brigger, H., Rao, A., Kumar, S., Duong, T. E., Morris, K., Horvay, L., Floco, V., & Brigger, M. T. (2023). Development of a Medical Complexity Score for Pediatric Aerodigestive Patients. Journal of Pe-diatrics, 261. https://doi.org/10.1016/j.jpeds.2023.113549

Kolabas, Z. I., Kuemmerle, L. B., Perneczky, R., Förstera, B., Ulukaya, S., Ali, M., Kapoor, S., Bartos, L. M., Büttner, M., Caliskan, O. S., Rong, Z., Mai, H., Höher, L., Jeridi, D., Molbay, M., Khalin, I., Deligiannis, I. K., Negwer, M., Roberts, K., … Erturk, A. (2023). Distinct molecular profiles of skull bone marrow in health and neurological disorders. Cell, 186(17), 3706-3725.e29. https://doi.org/10.1016/j.cell.2023.07.009

Kumar, G., & R.S., R. (2022). Availability of public health facilities and utilization of maternal and child health services in districts of India. Clinical Epidemiology and Global Health, 15. https://doi.org/10.1016/j.cegh.2022.101070

Mahdavi, A., Atlasi, R., Ebrahimi, M., Azimian, E., & Naemi, R. (2023). Human re-source management (HRM) strategies of medical staff during the COVID-19 pandemic. In Heliyon (Vol. 9, Issue 10). Elsevier Ltd. https://doi.org/10.1016/j.heliyon.2023.e20355

Mahdi, S. S., Battineni, G., Khawaja, M., Allana, R., Siddiqui, M. K., & Agha, D. (2023). How does artificial intelligence impact digital healthcare initiatives? A review of AI applications in dental healthcare. In International Journal of In-formation Management Data Insights (Vol. 3, Issue 1). Elsevier B.V. https://doi.org/10.1016/j.jjimei.2022.100144

Meiliana, Daniella, G., Wijaya, N., Putra, N. G. E., & Efata, R. (2023). Agile Soft-ware Development Effort Estimation based on Product Backlog Items. Proce-dia Computer Science, 227, 186–193. https://doi.org/10.1016/j.procs.2023.10.516

Miller, M. I., Shih, L. C., & Kolachalama, V. B. (2023). Machine Learning in Clinical Trials: A Primer with Applications to Neurology. Neurotherapeutics, 20(4), 1066–1080. https://doi.org/10.1007/s13311-023-01384-2

Mishra, A., & Alzoubi, Y. I. (2023). Structured software development versus agile software development: a comparative analysis. International Journal of Sys-tem Assurance Engineering and Management. https://doi.org/10.1007/s13198-023-01958-5

Najihi, S., Elhadi, S., Abdelouahid, R. A., & Marzak, A. (2022). Software Testing from an Agile and Traditional view. Procedia Computer Science, 203, 775–782. https://doi.org/10.1016/j.procs.2022.07.116

Rindell, K., Ruohonen, J., Holvitie, J., Hyrynsalmi, S., & Leppänen, V. (2021). Securi-ty in agile software development: A practitioner survey. Information and Soft-ware Technology, 131. https://doi.org/10.1016/j.infsof.2020.106488

Roulet Perez, E. (2023). Precision or narrative medicine? Child neurology needs both! Archives de Pediatrie, 30(6), 415–419. https://doi.org/10.1016/j.arcped.2023.06.007

Samadbeik, M., Aslani, N., Maleki, M., & Garavand, A. (2023). Acceptance of mo-bile health in medical sciences students: Applying technology acceptance model. Informatics in Medicine Unlocked, 40. https://doi.org/10.1016/j.imu.2023.101290

St Louis, E. K., & Videnovic, A. (2021). Sleep Neurology’s Toolkit at the Cross-roads: Challenges and Opportunities in Neurotherapeutics Lost and Found in Translation. In Neurotherapeutics (Vol. 18, Issue 1). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/s13311-021-01032-7

Tan, Z. C., Tan, C. E., & Choong, Y. O. (2023). Occupational Safety & Health Man-agement and Corporate Sustainability: The Mediating Role of Affective Com-mitment. Safety and Health at Work. https://doi.org/10.1016/j.shaw.2023.10.006

Wang, J., & Conwell, J. (2022). Higher education and health at midlife: Evaluating the role of college quality. SSM - Population Health, 19. https://doi.org/10.1016/j.ssmph.2022.101228

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Published

2024-04-22

How to Cite

Sihombing, D. J. C. (2024). Design and Implementation of an Agile-Based Electronic Prescription System for Neurological Medications. Jurnal Ekonomi, 13(02), 245–256. Retrieved from https://ejournal.seaninstitute.or.id/index.php/Ekonomi/article/view/4384

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