ArticleF1000Research2024
Workload Assessment of Technical Staff in a Clinical Laboratory in South India.
Article in F1000Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: 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. Methods: 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. Result: 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. Conclusion: 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.
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Registered trials
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