Risk Management and Healthcare Policy (Feb 2024)
The Impact of Age Group in Hierarchical Forecasting of Monthly Blood Donations in Zimbabwe
Abstract
Coster Chideme, Delson Chikobvu, Tendai Makoni Department of Mathematical Statistics and Actuarial Sciences, University of the Free State, Bloemfontein, South AfricaCorrespondence: Coster Chideme, Tel +263 777 098 263, Email [email protected]; [email protected]: To meet the blood requirements for transfusion therapy, blood banks need to ensure that blood inventories are maintained at desirable levels. There is a rising global need for optimal ways to manage blood supply and demand using statistical models in blood inventory planning and management. Thus, blood donation forecasting using donor-specific characteristics such as donor type and age is critical in managing the blood bank inventory.Methods: The monthly blood donation data covering the period 2007 to 2018, collected from the National Blood Service Zimbabwe (NBSZ) was used in this study. The data is first disaggregated based on donor age, and further disaggregation is performed for each age group based on donor type. The hierarchical forecasting approaches, namely the bottom-up, top-down and the optimal combination methods were used in the data analysis. The Error-Trend-Seasonality (ETS) and Autoregressive Integrated Moving Average (ARIMA) methods are used in the hierarchical forecasting approaches to generate the forecasts.Results: New blood donors account for more than 55% of blood donations in Zimbabwe. The younger donors (16– 29 years) dominate the blood donations, accounting for 89.2% of the donations. Young and new donors account for nearly 50% of the donations. The middle-aged and older donors have lower blood donations. The bottom-up approach under the ARIMA model outperformed all the other approaches. The future projections show that new and young donors will increase in blood donations, regular donations will decline slightly while the occasional donations are projected to remain constant.Conclusion: Hierarchical forecasting is a unique approach in that the different aggregation levels reveal important features of the blood donation data. The lower percentage of regular donations is worrisome to blood authorities as it points to new blood donors not returning for further donations. Blood authorities need to develop policies that will encourage new and young donor categories to become regular donors.Keywords: hierarchical forecasting, blood donation, top-down, bottom-up, optimal combinations, forecasting accuracy
