Abstract
Developing a forecasting tool for patient census allows for improved staffing, better resource utilization and mobilization, and improved timing of educational campaigns around the disease control process. Using a neural network approach we evaluated several different models and variables for predicting patient census prospectively. These initial studies enabled selection of a subset of predictor variables and show that different network models, and variables must be used based on the season.
Original language | English (US) |
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Pages (from-to) | 1147 |
Number of pages | 1 |
Journal | AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium |
State | Published - 2007 |
Externally published | Yes |
ASJC Scopus subject areas
- General Medicine