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Using Autoregressive Integrated Moving Average (ARIMA) Modelling to Forecast Symptom Complexity in an Ambulatory Oncology Clinic: Harnessing Predictive Analytics and Patient-Reported Outcomes
An increasing incidence of cancer has led to high patient volumes and time challenges in ambulatory oncology clinics. By knowing how many patients are experiencing complex care needs in advance, clinic scheduling and staff allocation adjustments could be made to provide patients with longer or short...
Autores principales: | Watson, Linda, Qi, Siwei, DeIure, Andrea, Link, Claire, Chmielewski, Lindsi, Hildebrand, April, Rawson, Krista, Ruether, Dean |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8394538/ https://www.ncbi.nlm.nih.gov/pubmed/34444115 http://dx.doi.org/10.3390/ijerph18168365 |
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