Workload Assessment of Technical Staff in a Clinical Laboratory in South India

Clinical laboratories play a significant role in healthcare, providing tests for diagnosis and treatment monitoring. Having skilled and adequate staffing is crucial for clinical laboratories to operate efficiently, manage their workload effectively, and deliver timely results. Despite being critical for healthcare delivery, ensuring adequate staffing levels in clinical laboratories remains a complex challenge for healthcare providers worldwide due to resource constraints and workforce shortages.

This study evaluates the workload in clinical laboratory staff using Workload Indicators of Staffing Need (WISN) method, focusing on workload, work pressure, and staffing requirements to optimize staffing levels and ensure an efficient clinical laboratory environment. Annual clinical laboratory data from June 2021 to May 2023 were collected to calculate the average number of days (234) worked annually, percentage of workload, distribution of activity time measurement units, and the ratio of needed, surplus, and existing staff (n=33, complete enumeration) from the laboratory registers and hospital statistics. WISN software was used to calculate staffing requirements, workload pressure, and WISN ratio. The Shapiro-Wilk test assessed normality and the Kruskal-Wallis test evaluated differences across clinical laboratory sections.

A total of 33 technical staff employed, performed approximately 3.7 million tests across hematology and clinical pathology during the study period, WISN ratios ranged from 0.2 to 0.7, indicating the existing 33 staff members face a high workload burden. The calculated ideal staffing level was 46.33 personnel, indicating a shortfall of 13.3 staff (28.3%). A p < 0.01 confirmed a significant disparity in workload distribution.

The results highlight the importance of optimizing staffing levels in clinical laboratories to ensure quality service delivery. The WISN methodology can be a useful tool in healthcare facilities for making evidence-based staff allocation, maximizing the utilization of employee skill sets, and establishing standard staffing benchmarks tailored to the needs of clinical laboratories.