Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Mar 18;25(1):400.
doi: 10.1186/s12913-025-12473-7.

A web-based platform for optimizing healthcare resource allocation and workload management using agile methodology and WISN theory

Akash Gajanan Prabhune  1 , P S Karpaga Priya  2 , Rohit Chandra  1 , Ankur Thakur  1 , Viany R Srihari  1 , Sachin S Bhat  1
Affiliations

A web-based platform for optimizing healthcare resource allocation and workload management using agile methodology and WISN theory

Akash Gajanan Prabhune et al. BMC Health Serv Res. .

Abstract

Background: Effective healthcare workforce management is critical for ensuring quality care delivery, particularly in resource-constrained settings. The World Health Organization's (WHO) Workload Indicators of Staffing Need (WISN) methodology provides an evidence-based framework for optimizing staffing levels. However, manual implementation of the WISN methodology is labour-intensive, error-prone, and time-consuming. To address these challenges, the Platform for Resource Allocation and Optimization for Healthcare Facilities (PRAYOJN) platform was developed as a web-based tool to automate WISN calculations, streamline data analysis, and improve workforce planning.

Objective: To develop and validate a web-based system that automates the WISN methodology for healthcare workforce planning.

Methods: The PRAYOJN platform was developed using an agile methodology, structured over five iterative sprints. These sprints incorporated stakeholder feedback to refine system functionalities, ensuring adaptability to real-world healthcare needs. The platform integrates data for principal, supporting, and ancillary tasks to calculate staffing requirements. Key functionalities include automated computation of Available Work Time (AWT), Standard Workload (SW), Category Allowance Factor (CAF), and Individual Allowance Factor (IAF). Alpha testing validated usability and accuracy, while beta testing in a clinical phlebotomy department assessed real-world performance.

Results: The platform calculated an ideal staffing requirement of 15.53 Full-Time Equivalent (FTE) for the phlebotomy department, aligning closely with the current staff strength of 15 FTE. Agile development ensured iterative improvements, enhancing user interface (UI) and user experience (UX). Feedback highlighted the platform's user-friendly design, with dynamic visualizations such as pie charts and bar graphs aiding workload interpretation. Users praised its efficiency, adaptability, and role in reducing calculation complexity.

Conclusion: PRAYOJN modernizes and enhances WISN-based workforce planning by automating workload calculations, improving data visualization, and supporting real-time decision-making. Its scalability and intuitive interface position it as a valuable tool for optimizing staffing efficiency across diverse healthcare environments.

Keywords: Agile development in healthcare; Healthcare resource allocation; Healthcare workforce optimization; PRAYOJN platform; Staffing automation; Workforce planning tool; Workload indicators of staffing need (WISN).

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethics approval and consent to participate: Since the study was mainly on software designing and the operational study was based on observations and interaction with management team (did not involve human data) the study was exempted from IRB approval by the Institutional Ethical Review Board of the Institute of Health Management Research, Bangalore (IIHMR-B). Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
A tailored data flow diagram for workload and resource allocation calculator
Fig. 2
Fig. 2
The User Interface of the PRAYOJN developed using HTML
Fig. 3
Fig. 3
Prerequisite Data Inputs Interface for Calculating Available Work Hours/Year Using PRAYOJN Platform
Fig. 4
Fig. 4
PRAYOJN Platform Interface for Calculating Principal Task Staff Requirements with Visual Distribution of Task Weightage
Fig. 5
Fig. 5
PRAYOJN Platform Interface for Calculating Category Allowance Standard (CAS) and Category Allowance Factor (CAF) for Supporting Tasks
Fig. 6
Fig. 6
PRAYOJN Platform Interface for Calculating Individual Allowance Factor (IAF) for Ancillary Tasks
Fig. 7
Fig. 7
PRAYOJN Platform Interface for Calculating WISN-Based Staff Requirements with Visual Task Weightage Breakdown
See this image and copyright information in PMC

References

    1. Kruk ME, Gage AD, Arsenault C, Jordan K, Leslie HH, Roder-DeWan S, et al. High-quality health systems in the sustainable development goals era: time for a revolution. Lancet Glob Health. 2018;6:e1196–252. - DOI - PMC - PubMed
    1. Bhati D, Deogade MS, Kanyal D. Improving patient outcomes through effective hospital administration: a comprehensive review. Cureus 2023;15(10):e47731. - PMC - PubMed
    1. Figueroa CA, Harrison R, Chauhan A, Meyer L. Priorities and challenges for health leadership and workforce management globally: a rapid review. BMC Health Serv Res. 2019;19(1):239. - DOI - PMC - PubMed
    1. Nguyen TTH, Phung HT, Bui ATM. Applying the workload indicators of staffing needs method in nursing health workforce planning: evidences from four hospitals in Vietnam. Hum Resour Health. 2022;19(Suppl 1):124. - DOI - PMC - PubMed
    1. Asres GD, Gessesse YK. Workload indicators of staffing need (WISN) method for health workforce planning at health facility: A scoping review. Hum Factors Healthc. 2024;6:100078. - DOI

LinkOut - more resources