Prediction of workload for hospital departments is a forecasting problem. Most forecasting techniques use time series methods. However, the unpredictability of hospital utilization which occurs because of environmental turbulence requires that predictions be based on strategic plans. Regression models developed from cross-sectional data can provide a methodology for linking predictions of service workload to strategic plans. The methodology is illustrated and evaluated in a pilot study, which produced models predicting measures of workload such as laboratory tests (R: =.85), doses of medication given to inpatients (R2 =.43), outpatient prescriptions (R3 =.79), and x-rays (R3 =.86).
Bibliographical noteFunding Information:
James E. Rohrer and John N p a n are arii-l.i.a te- d- wit-n 1 1 1 u rauualc rrugxam 111 Hospital and Health Administration, and the Center for Health Se University of Iowa, Iowa City, IA 52242. The authors wish to thank Andrew Hogan or rne ~.*.l.Ic n.-~ g arnare unr Office of Medical Education Research and Developrn ent for h )is many 1 suggestions on the conduct of this analysis. This research was partially supported by the Vezere Ins Admin The views expressed here are the authors ,own .ana 1, ao *. nor . represenr . tne - rnnu--- cies or opiniort s of the V 'eterans At jministration or any agency of 31 gov- ernn lent.
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