Weekly Hospital Workforce Data: A Data Visualisation Exercise.

Area of Science:

• Health Services Research
• Hospital Management
• Health Informatics

Background:

• Accurate quantification of the health workforce is crucial for effective hospital service delivery policy.
• Traditional methods like audits and surveys suffer from time-dependence and recall biases.
• Existing methods for obtaining staffing data are often prone to inaccuracies and limitations.

Purpose of the Study:

• To derive reliable workforce metrics from routine hospital financial and clinical information systems.
• To overcome the biases associated with traditional staffing data collection methods.
• To gain insights into spatial and temporal variations in hospital staffing and workload.

Main Methods:

• Utilized routine hospital financial and clinical information systems for data extraction.
• Aggregated and visualized staffing data, linking it to patient demand.
• Analyzed staff-to-patient and staff-to-staff ratios to understand workforce dynamics.

Main Results:

• Demonstrated a method to derive workforce metrics from existing hospital data systems.
• Identified significant variations in hospital staff resourcing across a weekly cycle.
• Observed reduced staff numbers and staff-to-patient ratios during nights and weekends.

Conclusions:

• Routine hospital data can be effectively leveraged to generate accurate health workforce metrics.
• Hospital staffing levels and patient ratios exhibit notable temporal variations.
• Analysis of staff-to-staff ratios provides insights into supervision dynamics and workforce patterns.