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...

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Detalles Bibliográficos
Autores principales: Watson, Linda, Qi, Siwei, DeIure, Andrea, Link, Claire, Chmielewski, Lindsi, Hildebrand, April, Rawson, Krista, Ruether, Dean
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
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

Internet

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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