SAĞLIK İŞLETMELERİNDE İLAÇ TÜKETİMİ İÇİN UYGUN TAHMİN YÖNTEMİNİN BELİRLENMESİ VE UYGULANMASI

Yıl 2024, , 235 - 241, 25.07.2024

Gökçen Çeliker , Nazife Öztürk , Rabia Nilüfer Ersoyoğlu

https://doi.org/10.34108/eujhs.1353450

Öz

Bu araştırmanın amacı, bir devlet hastanesinde seçilen bir ilacın tüketiminin en uygun tahmin yöntemi seçilerek gelecek 1 yıllık dönem için tahmin edilmesidir. Araştırmada, 2018 yılı Ocak ayından, 2022 yılı Aralık ayına uzanan süreçteki 60 aylık Kaptoril 5 mg tablet için ilaç tüketim verileri incelenmiştir. Araştırmada Minitab18 programı kullanılarak mevcut verilere zaman serisi yöntemleri uygulanmıştır. Araştırmada talep tahmin yöntemlerinden hareketli ortalama, üstel düzeltme, Holt-Winters yöntemleri kullanılmıştır. Yöntemlerin karşılaştırılmasında ortalama mutlak hata, ortalama mutlak hata yüzdesi ve hata karelerinin ortalaması gibi hata ölçütleri kullanılmıştır. Kaptoril 5 mg için hata ölçütlerine göre en uygun talep tahmini yöntemi ÇarpımsalHolt-Winters yöntemidir. Bu yönteme göre ortalama mutlak yüzde hata değeri 37.23’dür. ÇarpımsalHolt-Winters modeline göre 2023 yılında toplam ilaç tüketiminin 145 olacağı bulunmuştur. Bu araştırma, bir devlet hastanesinde, seçilen bir ilaç üzerinde örnek uygulama yapılarak, ilaçların stok yönetiminde güvenilir olarak karar vermeye yardımcı olacak zaman serisi tahmin yöntemlerinin uygulanabileceğini göstermektedir.

Anahtar Kelimeler

malzeme yönetimi, eczacılıkla ilgili ürünler, zaman serisi

DETERMINATION AND APPLICATION OF FORECASTING METHOD FOR MEDICINE CONSUMPTION IN HEALTHCARE ORGANIZATION

Öz

The aim of this research is to estimate the consumption of a selected medicine in a public hospital for the next 1-year period by choosing the most appropriate fore casting method. Kaptoril 5-mg tablets from January 2018 to December 2022 were examined. In this research, time series methods were applied to the existing data using the Minitab 18 program. Moving average, exponentials moothing, and Holt-Winters fore casting methods were used in this study. Error measures such as mean absolute error, mean absolute percent age error, and mean squared error were used to compare the methods. For Kaptoril 5 mg, the most appropriatedem and fore casting method according to error measures is the Multiplicative Holt-Winters Method. According to this method, the mean absolute percent age error is 37.23. According to the multiplic ative Holt-Winters model, the total medicine consumption in 2023 was found to be 145 tablets. This research shows that time series fore casting methods can be applied to help reliable decision making in stock management of medicines by making a sample application on a selected medicine in a public hospital.

Anahtar Kelimeler

materials management, pharmaceutical products, time series

Kaynakça

• Ağırbaş İ. Financial managementandcostanalysis in healthinstitutions. (3.ed). Ankara: Siyasal Press;2022.p.277
• Tengilimoğlu D, Yiğit V. SupplyChainandMaterial Management in Health Enterprises. Ankara: Nobel Publications;2013.
• Yıldırım K. Materialmanagement in hospitals: publichospitalexample. Sakarya University, Ph.D. Thesis, Sakarya, Turkey, 2015.
• Ucakkus P, Kocyigit SC. DemandForecasting in HealthInstitutions: Application on SurgicalGauze. JBusRes. 2019;11(4):3421-3429.doi:10.20491/isarder.2019.818
• Yıldırım C, Yıldırım S, Arı HO. DemandForecastingMethods in HealthInstitutions. J PerformQualHealth. 2014;8(2):77-92.
• Dedeoğlu T, Çetin O. Fore castingpf Patient Demand In Health Sector. Trakya University E-Journal of theFaculty of Economics and Administrative Sciences, 2021;10(1):25-38.doi: 10.47934/tife.10.01.03
• Esen H, Kaya Ü. Estimated Number of Patients Applied to a Training Research Hospital Emergency Department. Journal of Productivity. 2021;(3):129-145.doi: 10.51551/verimlilik.736855
• Karakaş E. Estimating Demand for Pediatric Intensive Care Unitby Time Series Methods. EJOSAT. 2019;(17):454-462. doi: 10.31590/ejosat.624407
• Sarıyer G. Time Series Modelling for Forecasting Demand in the Emergency. IJERD, 2018;10(1):66-77.doi: 10.29137/umagd.419661
• Yiğit V. Forecasting Demand of Medical Material at Hospıtals: An Example Application of Consumption on Serum Set. Manas Journal of Social Studies, 2016;5(4):207-222.
• Engin D, Işıkçelik F, Akyürek ÇE. DemandForecasting in Health Institutions: an Application Example. 4. International Health Sciences and Management Conference 2019 e-Proceeding. June 20-23, 2019, İstanbul, Turkey.
• Özüdoğru AG, Görener A. An application on demand fore casting in the health sector. Istanbul Commerce University Journal of Social Sciences. 2015;14(27):37-53.
• Pharmaceutical Manufacturers Association of Turkey (PMAT). Short Product Information. Available from: https://www.titck.gov.tr/kubkt (AccessedJuly 3,2023).
• Calegari R, Fogliatto FS, Lucini FR, Neyeloff J, Kuchenbecker RS, Schaan BD. Fore casting daily volume and acuity of patients in the emergency department. Comput Math Methods Med.2016.doi: 10.1155/2016/3863268
• Lewis CD. Industrial and business fore casting methods: A practical guide to exponentials moothing and curvefitting. 1982.
• Biçer İ, Ömürgönülşen M. Determination of Supply Chain Management Perceptions of Health Institutions Managers. Hacettepe Journal of Health Administration. 2019;22(3):599-618.
• Eren B. Material Management in Hospital Services. Availablefrom: https://www. academia. edu/5394565/Hastane_Hizmetlerde_Malzeme_Y% C3% B6netimi. 2016. (AccessedJuly 3, 2023).
• Sarı T, Gül BS. Demand Fore casting with Integrated Time Series Analysis: An Case Studyin Pharmaceutical Supply Chain. Journal of Productivity. 2022;(4),597-610. doi: 10.51551/verimlilik.1091150
• Bon AT, Ng TK. Optimization of inventory demand fore casting in the university health care center. In IOP Conference Series: Materials Science and Engineering (Vol. 166, No. 1, p. 012035). 2017; IOP Publishing.
• Mbonyinshuti F, Nkurunziza J, Niyobuhungiro J, Kayitare E. The prediction of essential medicines demand: a machine learning approachusing consumption data in Rwanda. Processes. 2021;10(1):26. doi: 10.3390/pr10010026
• Gimbach S, Vogel D, Fried R, Faraone SV, Banaschewski T, Buitelaar J, Döpfner M, Ammer R. The impact of the COVID-19 pandemic on ADHD medicine consumption in 47 countries and regions. Eur Neuropsychopharmacol. 2023;73:24-35.doi: 10.1016/j.euroneuro.2023.04.008
• Vukićević T, Draganić P, Škribulja M, Puljak L, DošenovićS..Consumption of psychotropic drugs in Croatia before and during the COVID-19 pandemic: a 10-year longitudinal study (2012–2021). Soc Psychiatry Psychiatr Epidemiol. 2023;1-13.doi: 10.1007/s00127-023-02574-1
• Barrett R, Hodgkinson J. Impact of the COVID-19 pandemic on cardiovascular heart disease medication use: time-series analysis of England’s prescription data during the COVID-19 pandemic (January 2019 to October 2020). Ther Adv Cardiovasc Dis. 2022;16, 17539447221137170.doi: 10.1177/17539447221137
• Mathieu C, Pambrun E, Bénard-Laribière A, Noize P, Faillie JL, Bezin J, Pariente A. Impact of the COVID-19 pandemic and its control measures on cardiovascular and antidiabetic drugs use in France in 2020: a nation widerepeated cohort study. Eur J Epidemiol. 2022;37(10):1049-1059.doi: 10.1007/s10654-022-00912-2