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

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 optimizi...

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Main Authors: Akash Gajanan Prabhune, P S Karpaga Priya, Rohit Chandra, Ankur Thakur, Viany R Srihari, Sachin S Bhat
Format: Article
Language:English
Published: BMC 2025-03-01
Series:BMC Health Services Research
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Online Access:https://doi.org/10.1186/s12913-025-12473-7
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author Akash Gajanan Prabhune
P S Karpaga Priya
Rohit Chandra
Ankur Thakur
Viany R Srihari
Sachin S Bhat
author_facet Akash Gajanan Prabhune
P S Karpaga Priya
Rohit Chandra
Ankur Thakur
Viany R Srihari
Sachin S Bhat
author_sort Akash Gajanan Prabhune
collection DOAJ
description 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.
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spelling doaj-art-5ceb1eff8ac74c238dd94683a4c0c4072025-08-20T03:41:41ZengBMCBMC Health Services Research1472-69632025-03-0125111710.1186/s12913-025-12473-7A web-based platform for optimizing healthcare resource allocation and workload management using agile methodology and WISN theoryAkash Gajanan Prabhune0P S Karpaga Priya1Rohit Chandra2Ankur Thakur3Viany R Srihari4Sachin S Bhat5ADMIRE Centre for Advancing Digital Health, Institute of Health Management Research, Bangalore (IIHMR-B)ADMIRE Centre for Advancing Digital Health, Institute of Health Management Research, Bangalore (IIHMR-B)ADMIRE Centre for Advancing Digital Health, Institute of Health Management Research, Bangalore (IIHMR-B)ADMIRE Centre for Advancing Digital Health, Institute of Health Management Research, Bangalore (IIHMR-B)ADMIRE Centre for Advancing Digital Health, Institute of Health Management Research, Bangalore (IIHMR-B)ADMIRE Centre for Advancing Digital Health, Institute of Health Management Research, Bangalore (IIHMR-B)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.https://doi.org/10.1186/s12913-025-12473-7Healthcare workforce optimizationWorkload indicators of staffing need (WISN)PRAYOJN platformStaffing automationAgile development in healthcareWorkforce planning tool
spellingShingle Akash Gajanan Prabhune
P S Karpaga Priya
Rohit Chandra
Ankur Thakur
Viany R Srihari
Sachin S Bhat
A web-based platform for optimizing healthcare resource allocation and workload management using agile methodology and WISN theory
BMC Health Services Research
Healthcare workforce optimization
Workload indicators of staffing need (WISN)
PRAYOJN platform
Staffing automation
Agile development in healthcare
Workforce planning tool
title A web-based platform for optimizing healthcare resource allocation and workload management using agile methodology and WISN theory
title_full A web-based platform for optimizing healthcare resource allocation and workload management using agile methodology and WISN theory
title_fullStr A web-based platform for optimizing healthcare resource allocation and workload management using agile methodology and WISN theory
title_full_unstemmed A web-based platform for optimizing healthcare resource allocation and workload management using agile methodology and WISN theory
title_short A web-based platform for optimizing healthcare resource allocation and workload management using agile methodology and WISN theory
title_sort web based platform for optimizing healthcare resource allocation and workload management using agile methodology and wisn theory
topic Healthcare workforce optimization
Workload indicators of staffing need (WISN)
PRAYOJN platform
Staffing automation
Agile development in healthcare
Workforce planning tool
url https://doi.org/10.1186/s12913-025-12473-7
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