Although inpatient admissions to hospitals appear to be a random process, identifying and understanding any underlying patterns and drivers could have a significant impact on medical staffing and organizational planning.
The number of daily admissions to the medical service of an academic medical center was analyzed using the wavelet transform, a method of deconstructing signals as a compilation of stretched and shifted versions of a basic pattern, the mother wavelet. For any given day, the relative strength of all underlying periodicities can be computed and displayed as a topographic map. Patterns whose strength were greater than that expected for a purely random process were extracted for further deterministic analysis.
The wavelet transform identified locally significant trends of 2‐, 4‐, 7‐, and 30‐day periodicities/delays throughout the admission data set. A 2‐day delay was seen immediately after Martin Luther King Day, suggesting a postholiday effect on admissions. The 7‐ and 30‐day cycles stimulated exploration of day‐of‐week and time‐of‐month effects on admissions. Indeed, in a univariate analysis, Sunday, Monday, Tuesday, Thursday, Saturday, ends of the month, and day after holiday were significantly correlated with inpatient admissions. A simple multivariate linear model based entirely on binary variables could explain 26% of the variance in patient admissions.
Wavelet analysis systematically uncovered the effects of societal schedules on patient behavior. It is a powerful and robust tool for understanding some of the forces driving complex processes.
T. Chau, none.
Figure 1. (a) Plot of daily admissions by date. (b) Wavelet power spectrum using the Morlet 6 mother wavelet. Hatched region is the cone of influence, which is susceptible to edge effects. Black contours denote the 5% significance level compared to a random white‐noise background spectrum. Courtesy of http://www.researchsystems.com
To cite this abstract:Chau T. Visualizing Drivers of Inpatient Admissions Using Wavelet Analysis. Abstract published at Hospital Medicine 2008, April 3-5, San Diego, Calif. Abstract 11. Journal of Hospital Medicine. 2008; 3 (suppl 1). https://www.shmabstracts.com/abstract/visualizing-drivers-of-inpatient-admissions-using-wavelet-analysis/. Accessed January 19, 2020.