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Forecasting inpatient glycemic control: extension of damped trend methods to subpopulations

AIM: Evaluate forecasting models applied to smaller geographic locations within the hospital. MATERIALS & METHODS: Damped trend models were applied to blood glucose measurements of progressively smaller inpatient geographic subpopulations. Mean absolute percentage error (MAPE) and 95% prediction...

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Detalles Bibliográficos
Autores principales: Saulnier, George E, Castro, Janna C, Cook, Curtiss B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Future Science Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720372/
http://dx.doi.org/10.2144/fsoa-2020-0096
Descripción
Sumario:AIM: Evaluate forecasting models applied to smaller geographic locations within the hospital. MATERIALS & METHODS: Damped trend models were applied to blood glucose measurements of progressively smaller inpatient geographic subpopulations. Mean absolute percentage error (MAPE) and 95% prediction intervals (PIs) assessed validity of the models to forecasts 48 weeks into the future. RESULTS: MAPE values increased, and 95% PIs widened, when data from progressively smaller geographic areas were analyzed. MAPE values were highest and 95% PIs were broadest with the smallest geographic areas. In contrast, observations missed at larger geographical locations were more evident with smaller subpopulations. CONCLUSION: The utility of damped trend models to forecast inpatient glucose control diminished when applied to smaller geographic areas within the hospital.