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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Future Science Ltd
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720372/ http://dx.doi.org/10.2144/fsoa-2020-0096 |
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. |
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