Open-source software for demand forecasting of clinical laboratory test volumes using time-series analysis

摘要: Background: Demand forecasting is the area of predictive analytics devoted to predicting future volumes services or consumables. Fair understanding and estimation how demand will vary facilitates optimal utilization resources. In a medical laboratory, accurate demand, that is, test volumes, can increase efficiency facilitate long-term laboratory planning. Importantly, in an era management initiatives, accurately predicted compared realized form precise way evaluate initiatives. Laboratory are often highly amenable by time-series models; however, statistical software needed do this generally either expensive technical. Method: paper, we describe open-source web-based tool for explain use it as clinical laboratories estimate volumes. Results: This has three different models, Holt-Winters multiplicative, additive, simple linear regression. Moreover, these models ranked best one highlighted. Conclusion: allow anyone with historic volume data model demand.