Applying the Workload Indicators of Staffing Need (WISN) methodology for health workforce planning in Singapore's public polyclinics: a pilot study to support the Healthier SG reform

In Singapore, the Healthier SG (HSG) reform is broadening the healthcare system’s focus beyond clinical care to include preventive and promotive primary healthcare, which is expected to significantly increase the workload of family physicians (FPs). Traditional staffing models fail to capture actual workloads, creating a need for evidence-based planning tools. This study, the first of its kind in a Singaporean polyclinic, applies the World Health Organization’s (WHO) Workload Indicators of Staffing Need (WISN) methodology to determine optimal FP staffing levels needed under the new HSG model. A single-site, mixed-methods pilot study was conducted at a public primary care clinic in Singapore. The WHO’s WISN methodology was used to quantify physician staffing requirements based on 2024 workload data, incorporating health services, support and additional activities. Activity standards were determined through electronic health records, clinic statistics and expert consensus. The WISN software was used to calculate the total staff required and the WISN ratio. In-depth interviews with five FPs were conducted to contextualise and triangulate quantitative findings. WISN analysis found a staffing requirement of 28 full-time equivalent (FTE) FPs, compared to the current staffing of 22 FTEs, resulting in a WISN ratio of 0.79. This indicates that the FP workforce is overworked, operating at 79% of the required capacity, with a staffing shortfall of 6 FTEs. Routine support activities required a Category Allowance Factor (CAF) of 1.26 (representing a 26% greater requirement for clinical and support activities), and additional duties required an Individual Allowance Factor (IAF) equivalent to 2.21 FTEs. HSG-related tasks alone accounted for 1.5 FTEs. Qualitative interviews highlighted high workload pressure, substantial administrative burden due to HSG, and challenges in balancing under-recognised teaching and supervision with clinical duties. This study demonstrates misalignment between the current FP workforce and the future workload demands of Singapore’s PHC under current reforms. The findings provide evidence-based justification for increasing staffing and reveal the extensive, often-overlooked “invisible workload” of non-clinical duties. Policymakers should adopt workload-based planning models like WISN, make non-clinical work visible in rosters, and accelerate task-shifting within team-based care to ensure HSG’s long-term success and prevent physician burnout.

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Publication Details

Journal
Human Resources for Health
Published
2026-08-14
DOI
https://doi.org/10.1186/s12960-026-01094-8
Primary Topic
Primary Care and Health Outcomes
Type
article
Field-Weighted Citation Impact
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article

Applying the Workload Indicators of Staffing Need (WISN) methodology for health workforce planning in Singapore's public polyclinics: a pilot study to support the Healthier SG reform

Yang Chang, Taufique Joarder, Harshini Suresh, Yii Jen Lew et al.
Human Resources for Health
Primary Care and Health Outcomes
article

Applying the Workload Indicators of Staffing Need (WISN) methodology for health workforce planning in Singapore's public polyclinics: a pilot study to support the Healthier SG reform

Yang Chang, Taufique Joarder, Harshini Suresh, Yii Jen Lew, David B. Hipgrave, Ying Xian Chua
article en

Abstract

In Singapore, the Healthier SG (HSG) reform is broadening the healthcare system’s focus beyond clinical care to include preventive and promotive primary healthcare, which is expected to significantly increase the workload of family physicians (FPs). Traditional staffing models fail to capture actual workloads, creating a need for evidence-based planning tools. This study, the first of its kind in a Singaporean polyclinic, applies the World Health Organization’s (WHO) Workload Indicators of Staffing Need (WISN) methodology to determine optimal FP staffing levels needed under the new HSG model. A single-site, mixed-methods pilot study was conducted at a public primary care clinic in Singapore. The WHO’s WISN methodology was used to quantify physician staffing requirements based on 2024 workload data, incorporating health services, support and additional activities. Activity standards were determined through electronic health records, clinic statistics and expert consensus. The WISN software was used to calculate the total staff required and the WISN ratio. In-depth interviews with five FPs were conducted to contextualise and triangulate quantitative findings. WISN analysis found a staffing requirement of 28 full-time equivalent (FTE) FPs, compared to the current staffing of 22 FTEs, resulting in a WISN ratio of 0.79. This indicates that the FP workforce is overworked, operating at 79% of the required capacity, with a staffing shortfall of 6 FTEs. Routine support activities required a Category Allowance Factor (CAF) of 1.26 (representing a 26% greater requirement for clinical and support activities), and additional duties required an Individual Allowance Factor (IAF) equivalent to 2.21 FTEs. HSG-related tasks alone accounted for 1.5 FTEs. Qualitative interviews highlighted high workload pressure, substantial administrative burden due to HSG, and challenges in balancing under-recognised teaching and supervision with clinical duties. This study demonstrates misalignment between the current FP workforce and the future workload demands of Singapore’s PHC under current reforms. The findings provide evidence-based justification for increasing staffing and reveal the extensive, often-overlooked “invisible workload” of non-clinical duties. Policymakers should adopt workload-based planning models like WISN, make non-clinical work visible in rosters, and accelerate task-shifting within team-based care to ensure HSG’s long-term success and prevent physician burnout.

Human Resources for Health
SingHealth Duke-NUS Academic Medical Centre (SG)
Partnerships for the goals
Openalex Percentile: Top 5%
Primary Care and Health Outcomes
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