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Variance analysis. Using standards to predict nurse staffing patterns.

J D Suver, E B Oppermann, F T Helmer

Healthcare Financial Management : Journal of the Healthcare Financial Management Association

|August 8, 1984

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This study refines nurse staffing prediction models by analyzing variances between standard and actual hours. It enhances accuracy for better hospital resource management and cost control.

Area of Science:

Healthcare Management
Nursing Administration
Health Informatics

Background:

Healthcare cost containment and revenue limitations necessitate efficient nurse staffing.
Standardized systems are increasingly used to predict and manage nursing labor hours.
Data availability supports the development of sophisticated staffing prediction models.

Purpose of the Study:

To further analyze variance between standard and actual nursing hours.
To refine previously developed nurse staffing prediction models.
To improve the accuracy of predicting required nurse staffing patterns.

Main Methods:

Utilized data from a 220-bed short-term hospital.
Performed variance analysis comparing standard hours to actual hours.

Related Experiment Videos

Adjusted predictions for patient case mix and volume changes.

Main Results:

Identified key factors contributing to variances in nurse staffing.
Quantified the differences between predicted and actual nursing hours.
Provided insights into the reliability of the developed prediction models.

Conclusions:

Variance analysis is crucial for refining nurse staffing models.
Accurate staffing predictions support effective resource allocation and cost management.
Continued model development is essential for adapting to healthcare dynamics.