Patient acuity indicators as predictors of pharmacy workload

Area of Science:

• Healthcare Management
• Pharmacy Practice
• Nursing Administration

Background:

• Accurate prediction of pharmacy workload is crucial for effective resource allocation and staffing.
• Existing methods for workload prediction may not fully capture the dynamic nature of patient care demands.
• Integrating nursing workload data offers a novel approach to enhance pharmacy workload forecasting.

Purpose of the Study:

• To evaluate the feasibility of using nursing patient-classification system workload indicators to predict pharmacy workload.
• To determine the correlation between nursing workload metrics (patient acuity, nursing care hours) and pharmacy activities.
• To assess the predictive power of nursing workload on same-day and next-day pharmacy workload.

Main Methods:

• A 28-day observational study recorded frequency data for 13 pharmacy activities across nine nursing units.
• Linear regression analysis was employed to assess the association between pharmacy workload and nursing workload indicators.
• Both same-day and one-day-lagged analyses were conducted to evaluate predictive relationships.

Main Results:

• A strong correlation was observed between pharmacy workload and same-day nursing care hours.
• Nursing workload indicators explained at least 73% of the variance in pharmacy workload.
• Both patient acuity and nursing care hours demonstrated significant predictive capability for pharmacy workload.

Conclusions:

• Nursing workload indicators, specifically patient acuity and standard nursing care hours, are robust predictors of pharmacy workload.
• These nursing workload metrics can reliably forecast pharmacy workload for the same day and the following day.
• The study supports the use of nursing workload data for optimizing pharmacy staffing decisions and improving operational efficiency.