Unveiling Efficiency: A Research Inquiry into Technical Staff Utilization in South Indian Clinical Laboratory using Workload Indicators Staffing Need (WSN) Analysis.

Introduction

Efficient healthcare relies heavily on the valuable contributions of clinical laboratory personnel. These skilled professionals help diagnose illnesses and effectively monitor treatments. Their expertise is genuinely indispensable for making informed decisions and delivering top-notch care. The effective use of clinical laboratory services improves doctors’ capacity to use the least resources possible while reducing total healthcare costs by helping them make evidence-based diagnostic and treatment decisions for their patients. Clinical laboratory services are the least intrusive and economical source of objective health information for preventing and diagnosing diseases, enhancing patient outcomes, guaranteeing patient safety, and carrying out crucial public health monitoring tasks (Swanson et al., 2018). A crucial component of health care is clinical laboratory services. As a result, adequate staff capacity is required to ensure patient satisfaction and improve patient and clinical staff outcomes (Tripković et al., 2020). Human resources for health are essential for providing healthcare services to the population (Nandan & Agarwal, 2012).

The World Health Organization (WHO) developed Workload Indicators of Staffing Need (WISN), a human resource planning and management tool that gives health managers a mechanism to assess and determine the ideal staffing levels in healthcare facilities (Shipp & WHO, 1998; Pandey et al., 2013). The WISN method is a tool for human resource management that calculates the number of health workers needed to meet the demands of a specific healthcare institution and evaluates the workload pressure experienced by those workers. This method has several advantages, including being easy to use and applicable in any healthcare setup and other institutions that may not be medical (WISN: user’s Manual, second edition-2023, Asres & Gessesse, 2024).

Health planners and policymakers must ensure that workers with the necessary skills are available appropriately. Policymakers should contribute critical insights to developing guidelines for healthcare facilities’ staffing standards in the context of resource constraints (Stankovic & Santric Milicevic, 2022). The acknowledgement of the importance of clinical labs for patient welfare remains the most valuable attribute for any healthcare worker, despite the ongoing problems they encounter. Even if the public and patients are unaware of its existence, clinical laboratories’ primary purpose is to provide superior laboratory diagnostic tests (Bayot et al., 2023). The need for more human resources to match the needs of their communities is posing a problem for healthcare management everywhere. The significance of health professionals’ accessibility in attaining universal health coverage and sustainable development objectives has been emphasized by the global health human resources strategy, Workforce 2030 (Gupta et al., 2023).

Diagnosis and treatment these days are primarily driven by evidence-based; the hematology and Clinical Pathology Laboratory is one of the most supporting medical units, and this functional unit plays a significant role in supporting hospital operations by testing the cause of the disease. Scarce research is available in the staffing and utilization of clinical laboratory staff. This exploration aids in assessing the effective use of technical staff in the context of workload, work pressure, and staff requirements in the laboratory.

Methods

The study was initiated after obtaining approval from the Institutional Ethics Committee, Kasturba Medical College (KMC) and Kasturba Hospital (KH) (IEC2-345/2023) (approved on 22 July 2023), Institutional Research Committee (IRC- MCHP-Mpl/IRC/PG/2023/150, 18 April 2023). The Workload Indicator Staffing Need (WISN) software is accessible upon registering with the WHO, making it an efficient and valuable tool for our research endeavors.

As human participants not included, no consent required for the performed study. However, data was collected with permission from laboratory in charge and head of the hospital while obtaining IRC and IEC approval.

The study was conducted in the Clinical Laboratory of a tertiary care hospital., operating 24/7 with a staff of 33 technicians. The data on workload, distribution of activity time, staff Available Work Time (AWT), time spent by staff for the supportive activities (such as training, meetings, sample pre examination procedures and equipment maintenance) were collected over a period of two years, from June 2021 to May 2023.

Results

Conclusions/Discussion

The clinical laboratory’s technical staff’s efficiency is critical for ensuring high-quality patient care and efficient diagnostics (Ebubekir et al., 2017). The WISN analysis applied to clinical laboratory work was evaluated in the current study. The goal of this analysis was to evaluate the level of staffing in this area of healthcare, making sure that the available human resources are adequately equipped to provide support. Considering the rapidly evolving healthcare landscape, no other medical specialities alone can fully meet the complex needs of patients. As such, laboratory technicians should play a critical role in driving clinical effectiveness and improving patient care (Ferraro et al., 2016). Clinical laboratory technicians and technologists are essential members of the healthcare team, playing a crucial role in the workforce. Without their valuable expertise, the time and cost of providing quality care would significantly escalate. Their accurate diagnoses and efficient treatment support are integral to ensuring optimal patient outcomes (Cortelyou-Ward et al., 2011).

A study highlights the critical role of human resource planning and management in the healthcare sector, particularly within clinical laboratory environments. Research involved a large group of health laboratory workers, medical laboratory technicians, and medical biochemists, illustrating the diverse personnel involved in such services (Stankovic & Santric Milicevic 2022).

In a District Hospital of Madhya Pradesh, the laboratory technicians were constantly under pressure to match the existing workload due to shortage of 10 manpower. Hence, it indicates an urgent need for improved human resource management in the healthcare facility (Pandey et al., 2013). In the current study, the clinical laboratory conducts a significant number of tests annually, indicating a substantial workload. Despite this high volume, the laboratory efficiently manages its operations with a relatively small team of 33 technical staff. This emphasizes the crucial role of efficient resource allocation and management strategies within clinical laboratory settings to ensure optimal productivity and service quality.

The field of medical laboratory science is overwhelmingly female, with women comprising 88.99% of medical laboratory technicians and 81.8% of medical biochemists, with an average age of 50 (Stankovic & Santric Milicevic 2022). This trend is further reflected in the current study, where 94% of the technical staff are women. The age range (24 to 56 years) of these technicians highlights their extensive experience, varying from recent graduates to seasoned professionals with over 30 years of service. This diversity highlights the strong expertise within the team.

A scarcity of technical staff, an ageing workforce, and ticking demographic time bombs of pension-related issues all threaten to compound the situation. The impact of these challenges is evident in delayed diagnoses and errors, directly impacting patient care quality (Cortelyou-Ward et al., 2011; Yenice, 2020; Strain & Sullivan, 2019). To combat these challenges head-on, it is crucial to diversify the technical staff by appointing individuals across different age groups and experience levels (Green et al., 2002). In the current study, the diverse team of technical staff serves as the backbone for sustaining top-notch service quality and keeping the clinical laboratory up to speed amidst the fast-paced evolution of cutting-edge technologies.

The midwives at Asrade Zewude Memorial Hospital worked five working days with an actual working time of 1030 hours annually. 58.4% of hours were spent on health service activity, additional activities, 36.6% hours, and supporting activities, 5% hours (Asres, 2023). The time that laboratory personnel spent on main activities was 70%. Per core activities took 0.25 to 180 minutes (Tripković et al., 2020). In the current study, the total available working time was 112320 minutes/year and 1872 hours/year, and the technical staff spent 68 to 84% of the time on main activities and 1.19 to 1.46% on supporting activities, individual allowance factor (IAF) for additional activities only to specific staff members 0.03 to 0.34. The inpatient medical record data update personnel were granted an allowance of 286 hours/year and a standard allowance of 0.17 hours per year (Prihadi et al., 2021). In the current study, the allowance for technical staff is 358.8 hours/per year, and the standard allowance is 0.19 hours/per year.

In a study in the RSU Anutapura Palu laboratory, reveals that the productive time used for activities was 88.6%, and the working hours was 114,240 minutes/year. The workload standard was 5817.32 annually, and the allowance was 0.4% annually. Employee in laboratory unit distribution has been successful; tasks and activities divided into productive, unproductive, and personal pursuits. Each employee has a 0.4 annual leeway factor, almost 40%. The laboratory has a deficit of 8 technicians. Qualification and competence are important for manpower planning. Understanding the optimal staffing levels can help hospital management make informed decisions regarding recruitment, training, and retention of staff members, ensuring that the workforce is adequate and competent to handle the workload (Napirah & Sulistiani, 2015).

The WISN difference shows a 20% and 14% Full-Time Equivalent (FTE) medical biochemist and medical laboratory technician shortfall, respectively, as well as a highly inconsistent workload pressure/WISN ratio of 0.4 to 1.0 (Stankovic & Santric Milicevic 2022). In a similar study by Tripković et al., there was a shortage of 22.22% laboratory analysts and 20.63% laboratory technicians and moderate to high workload pressure. Laboratory personnel levels required 8 FTE analysts and 13 FTE technicians to balance workloads with a pressure of 0.86 to 0.50. Both light and heavy workloads can undermine a laboratory’s competencies and work ethic. Thus, having adequately qualified employees for the workload is essential (Tripković et al., 2020). In the current study, the variation in WISN difference for technical staff requirements across sections of the clinical laboratory is striking, ranging from a mere 4.9% to a staggering 37.8%. However, two sections stand out with an ample supply of technical staff, showcasing a commendable balance in workforce allocation.

There was a significant difference between the number of employees currently employed and the number calculated by WISN. 25% of the employees were accessible to meet their needs, and 75% were shortfalls (Shivam et al., 2014). Three dialysis technicians needed to give patient care, and the hospital hired two of them (Gupta et al., 2023). There was a severe shortage in the Nurse/Midwife category, and there were just nine staff available where 45 were needed (Oaiya et al., 2022). In the current study, the WISN calculation has determined that the laboratory needs a total of 46.33 staff to handle the influx of samples and effectively manage the workload. However, with only 33 (71.7%) technical staff currently employed, there is a notable deficit of 13.33 additional staff. This represents a significant 28.3% increase required to ensure the smooth functioning of the clinical laboratory and to manage the workload adequately.

A moderate to high workload is shown on the WISN ratio, which ranges from 0.86 to 0.50 for laboratory workers (Tripković et al., 2020). A staff difference of 0 and a WISN ratio of 1, indicating that there were just enough personnel on hand to provide the facility’s services by national professional standards. Therefore, maintaining the services was the only necessary activity (Dimiri et al., 2022). In a few sections of the current study, the difference in technical staff runs from 1.1 to 8.5, showing a technical staff deficit. The WISN ratio ranges from 1 to 1.6, suggesting minimal workload pressure, and from 0.2 to 0.7, exposing moderate to high workload pressure. When a diagnosis is delayed or a mistake occurs, it lowers the quality and optimal treatment that the patient receives, which is when the effects of insufficient laboratory workers become evident (Cortelyou-Ward et al., 2011).

Despite encountering a heavier workload, the present study indicates that the reporting turnaround time was commendable. This was achieved through the redistribution of tasks among sections and the delegation of activities to graduates and students under supervision. This approach not only benefited patient care but also provided valuable training opportunities for future laboratory professionals. Considering the significant workload, this strategy played a pivotal role in reducing the turnaround time. It provided students with a unique opportunity to enhance their skills and become proficient laboratory technicians equipped with the education and experience necessary for success in their field of work.

The WISN approach serves as a valuable tool for HRM planners, assisting in the determination of whether there is an excess or deficit of human resources due to work-related stress. The establishment of suitable HRM policies requires consideration of current labour market analysis based on reliable data (Najafpour et al., 2023), and can help improve the distribution and equity of health workers within regions or similar healthcare facilities nationwide (Satish Kumar et al., 2016). Although the current study shows that workload pressure among technical staff is moderate to high pressure and there is a technical staff shortage, the management of the hospital has considered the clinical laboratory and updated the number of technical staff.

Using non-parametric Kruskal–Wallis one-way ANOVA (analysis of variance), facility-specific raw (unrounded) WISN values for all cadres were evaluated for a cross-state differences to investigate data heterogeneity. Since the count data produced by the WISN rounding technique caused problems with saturation raw numbers, a better fit was used in the ANOVA model. A non-parametric test was selected because of the data’s apparent skewness (Nair et al., 2022). In the current study, the Shapiro-Wilk test was utilized to assess the normality of the data. A p-value <0.01 indicated that the data originated from a non-normal distribution. Consequently, a non-parametric Kruskal-Wallis test was conducted. A p-value < 0.01 indicated a notable disparity in the demand for Technical Staff and workload across each section of the clinical laboratory.

Conclusion

The dedicated technological tool provided by the WHO for the WISN Software process facilitated the measurement of workload and the evaluation of technical staff utilization and needs. Based on the WISN, this study’s computation reveals a significant discrepancy between the actual workforce 33 and the WISN-calculated demand 46.33. The WISN results proved that staffing minimum and maximum standards and technical staff are optimally utilized in clinical laboratories. The WISN ratio is < 1, and the required number of laboratory staff is 13.33, indicating the workload pressure. This study focuses on staffing needs in modern clinical laboratories, which are increasingly automated compared to traditional facilities. This unique approach can inform policies for developing workforce requirements in future laboratories and healthcare settings.

Limitations

The calculations for staffing requirements are based on data from previous financial years and focused on a single clinical laboratory, limiting the generalizability of the findings. However, adjustments may be required to account for the current year’s workload and staffing needs. The WISN tool is helpful, but it has limitations. It may not fully consider facilities that operate all day and night or cases where different staff groups do similar tasks. Also, incorrect workload data could make the system suggest too few staff members. Despite its limitations, the WISN tool remains a valuable resource for healthcare staffing decisions. It works best in combination with other approaches.

Ethics and consent

The study was initiated after obtaining approval from the Institutional Ethics Committee, Kasturba Medical College (KMC) and Kasturba Hospital (KH) (IEC2-345/2023) (approved on 22 July 2023). The Workload Indicator Staffing Need (WISN) software is accessible upon registering with the WHO, making it an efficient and valuable tool for our research endeavors. As human participants were not included, no consent was required for the performed study. However, data was collected with permission from laboratory in charge and head of the hospital while obtaining IEC approval.