Work

Operationalizing preventive care: the preventive health logistics ecosystem framework for aging societies

Year: 2025

Type: article

Abstract: PopulaDons across the globe are ageing at an unprecedented pace. By 2050, one in four people 1 in the region is projected to be over 60 years old, creaDng escalaDng demands on health and social care systems. In response, governments have increasingly emphasised prevenDve health and primary care as cornerstones of sustainable health reform, aiming to reduce the burden of chronic disease and promote healthy longevity.Singapore has long been preparing itself for these shiYs through the launch of various primary care reforms, including the recent implementaDon of Healthier SG (HSG) 2 , a naDonal strategy that reorients the health system towards prevenDve, primary, and communitybased care. Central to this strategy is an ecosystem that promotes enrolment with family physicians 3 , designed around a vision that encourages healthier lifestyles, proacDve screening for common preventable chronic diseases, strengthening of community support networks and leveraging digital health technologies. While prioriDes represent a criDcal policy advance [4][5][6] , implementaDon science in healthcare oYen neglects the 'last-mile' logisDcs of prevenDve care. Indeed, in healthcare supply chain literature, logisDcs is argued to be underdeveloped and underuDlised compared to commercial sectors 7 , with limited coordinaDon between suppliers and providers 8 .For clarity, we define several key terms we use in this paper. "PrevenDve care" refers to organised efforts to reduce disease burden through early detecDon, behavioural intervenDons, and proacDve management of risk factors. OperaDonalising said prevenDve care denotes the translaDon of these strategies into implementable workflows. We use "logisDcs ecosystem" to describe the coordinated movement of people, resources and informaDon required to deliver prevenDve care effecDvely. Consistent with WHO convenDons, "older adults" are defined as persons aged 60 years and above, while "aging socieDes" refer to populaDon with rising proporDons of older adults resulDng in increased demand on health and social systems.LogisDcs in prevenDve care encompasses the end-to-end design and management delivery, from forecasDng to last-mile execuDon, including capacity, scheduling, data flows and workforce deployment. Put simply, prevenDve health strategies must contend not only with what intervenDons to deliver, but also with how, when, and where they are delivered -and to whom. HSG culDvates the partnership across different levels of care and between private and public healthcare providers, adding a further dimension to be explored 5 .NeglecDng these operaDonal consideraDons risks entrenching inequiDes and undermining the effecDveness of otherwise well-designed policies. Older adults, for example, oYen face barriers in mobility 9 , digital literacy 10 , and conDnuity of care across the healthcare system. Providers also face business model pressures when policy requirements constrain profit margins, especially when the vast majority of primary care providers enrolled in HSG are private standalone commercial enDDes 11 . Addressing these challenges requires a logisDcs environment that ensures Dmely, accessible and integrated prevenDve intervenDons. Yet, the "last mile" of prevenDve care delivery remains under-theorised and insufficiently embedded in health policy design. This paper introduces the concept of the PrevenDve Health LogisDcs Ecosystem (PHLE), a framework for operaDonalising prevenDve care in aging socieDes. We examine Healthier SG through the PHLE lens, drawing on three crucial insDtuDons. Singapore's naDonal healthcare supply-chain agency, the Agency for LogisDcs and Procurement Services (ALPS), provides the logisDcs backbone beyond hospitals, including vendor management and kifng for community nodes. The Agency for Integrated Care's (AIC) integraDon mandate operates a shared schedule and data backbone through lead social service agencies, pooling resources and aligning incenDves. While examples in this paper draw on the roles of three Singapore insDtuDons, these serve as funcDonal archetypes rather than fixed requirements. The PHLE components (decentralised nodes, health triggers, service flows, integraDon layers, and metrics) can be operaDonalised by varying combinaDons of governmental, private, or community actors depending on local governance structures. PHLE provides a blueprint for how decentralised care nodes, proacDve health triggers, and community-integrated logisDcs can close systemic gaps in service delivery. By situaDng logisDcs experDse alongside clinical and policy reforms, the framework aims to render prevenDve health not only aspiraDonal but acDonable, providing a model for resilient, equitable, people-centred health systems. Although grounded in Singapore's context, the PHLE framework is designed to be applicable across ageing socieDes that share common demographic pressures, including rising mulDmorbidity, constrained primary-care capacity, uneven geographical access, and fragmentaDon between clinical and social-care providers. These shared system characterisDcs provide a basis for adapDng the framework beyond Singapore.The PHLE framework (see Figure 1 below) is anchored in an integraDon of established theories from supply chain management, logisDcs sciences, and health systems design. At its core, PHLE adapts the Supply Chain OperaDons Reference (SCOR) model 12 , which is widely recognised in commercial sectors for driving end-to-end performance through standardised metrics such as reliability, responsiveness, and flexibility. In this context, SCOR provides a blueprint for orchestraDng the enDre conDnuum from risk idenDficaDon to intervenDon follow-up, ensuring that each stage is opDmally sequenced and resourced. This perspecDve highlights that prevenDve intervenDons require carefully orchestrated flows of people, informaDon, and resources. The framework also leverages queueing theory, parDcularly Lihle's Law 13 , to address the perennial challenge of service-delivery bohlenecks. By explicitly modelling the relaDonship between paDent arrival rates, service Dmes, and work-in-process, PHLE enables health systems to anDcipate and dynamically manage demand surges.Central to PHLE's design is Donabedian's structure-process-outcome model 14 , which provides a systemaDc lens for linking logisDcs infrastructure (structure), operaDonal workflows (process), and populaDon health results (outcome). The addiDon of equity straDficaDon ensures that logisDcs soluDons are not only efficient but also just, prioriDsing access for underserved and high-risk groups. This mulDdimensional theoreDcal foundaDon elevates logisDcs from a technical aYerthought to a strategic lever, compelling measurable accountability in prevenDve health delivery.1. Decentralised Care Nodes Decentralised care nodes are designed using principles of network opDmisaDon and the "5 A's" of access (availability, accessibility, accommodaDon, affordability, and acceptability) 15 . By bringing prevenDve services closer to where people live, these nodes reduce reliance on centralised faciliDes, shorten the Dme from risk idenDficaDon to first contact, and improve equity across neighbourhoods. Convenience and proximity are criDcal determinants of uptake, parDcularly among older adults and disadvantaged groups, making decentralised nodes essenDal to ensuring that prevenDve intervenDons and follow-up long-term chronic disease management by General PracDDoners (GPs) are both accessible and uDlised. Being decentralised also enables individual care nodes to operate efficiently according to their operaDonal requirements while retrofifng their protocols to the wider PHLE ecosystem.Health triggers refer to predefined clinical, behavioural, or contextual indicators that automaDcally prompt prevenDve or follow-up acDons within a health system. These may include biometric thresholds (e.g. elevated blood pressure), missed appointments, or changes in risk profiles detected through digital monitoring 16 . Health triggers translate latent risk into scheduled demand and, hence, into anDcipatory demand by applying queuing theory, parDcularly Lihle's Law, which links arrival rates, service Dmes, and work-in-process. Clearly defined triggers for acDon stabilise otherwise volaDle demand paherns, especially among high-risk populaDons. By smoothing paDent flow, these mechanisms reduce backlog and waiDng Dmes while enabling Dmely intervenDon on upstream determinants of health, ulDmately improving both efficiency and equity in prevenDve care delivery. Keying in the required clinical and paraclinical parameters will iniDate workflows, including next-episode screening, referral to higher levels of care, or social prescribing acDviDes. At the populaDon level, mobile applicaDons can also be synchronised with health status consolidated across various care interfaces and trigger alerts for future healthcare visits, lifestyle events, or changes in blood invesDgaDon results.Service flows in the PHLE uDlise the SCOR model to manage prevenDve pathways as an integrated, end-to-end chain, rather than fragmented steps. This approach prevents bohlenecks from merely shiYing between silos, increases compleDon rates across the conDnuum of care, and safeguards scarce capacity by ensuring that each stage of the prevenDve process is coordinated and aligned. This should be assisted by an interoperable IT system that integrates basic health informaDon across all care interfaces, so that a lack of paDent informaDon does not inhibit prompt service delivery and enables providers to know which services are required for the paDent.The integraDon layer provides the structural backbone of the PHLE, drawing on Donabedian's model. A shared logisDcs plajorm enables conDnuity of care across mulDple actors by pooling resources, standardising workflows, and aligning incenDves. Embedding logisDcs funcDons directly into regional health planning ensures that operaDonal consideraDons are treated as core components of prevenDve strategies rather than aYerthoughts, thereby promoDng both feasibility and equity in delivery. An integrated layer that enables services required and delivered at all care nodes can also promote transparency and meet agreed service obligaDons. Having a bird's-eye view of all logisDcal needs and their respecDve deliverables can also open the door to efficient policy and systems evaluaDon.PHLE evaluaDon links operaDonal design to outcomes also using Donabedian's model while aligning with the SCOR framework's performance categories for comparability and control. The proposed metrics extend beyond clinical results to capture logisDcal effecDveness, including equity of access across socioeconomic groups, Dme-to-care from risk idenDficaDon to intervenDon, and reducDons in avoidable hospitalisaDons. By making the operaDonal "health" of prevenDve care visible, these indicators provide policymakers and system leaders with acDonable insights for conDnuous improvement and accountability.Singapore's HSG strategy offers a Dmely test case for how prevenDve health reform can be translated from policy into pracDce. Yet without a robust logisDcal backbone, even welldesigned strategies risk remaining aspiraDonal. PrevenDve services in Singapore conDnue to be predominantly anchored within clinic-and hospital-based sefngs, with persistent dispariDes in the geographical accessibility of CHAS-accredited general pracDDoners across housing estates 17 . Among older adults, mobility constraints, limited digital literacy, and reliance on caregivers further impede engagement with prevenDve care, while fragmentaDon across service providers (GPs, community partners, and hospital outreach teams) creates duplicaDon and inefficiencies.The framework explicitly addresses several gaps that exisDng soluDons have struggled to resolve. First, clearly defined health-trigger systems can reduce missed opportuniDes for screening and follow-up, especially among older adults with fluctuaDng ahendance paherns. Second, decentralised care nodes miDgate mobility and digital-access barriers by bringing services closer to neighbourhoods where older residents live. Third, the integraDon layer helps prevent duplicaDon (such as repeated assessment by different agencies) by enabling shared scheduling, informaDon flows, and logisDcs coordinaDon. CollecDvely, these mechanisms provide acDonable pathways for strengthening the last-mile delivery of prevenDve services.Elements of the PHLE, however, are already visible within Singapore's health system. The introducDon of mulDdisciplinary 'Healthier SG Teams' 18 embodies the decentralised care node principle by linking clinical and community actors at the precinct level. Likewise, Delivery on Target Primary Care Networks (DOT PCN) 19 demonstrate how independent GP pracDces can be networked to pool resources, standardise workflows, and coordinate chronic-disease management. The Agency for Integrated Care (AIC) has further advanced integraDon by designaDng lead social service agencies to coordinate health and social services within regions, aligning incenDves and logisDcs across sectors. Together, these iniDaDves illustrate the early applicaDon of PHLE principles in operaDonal sefngs.To achieve scale, Healthier SG must now consolidate these efforts through a deliberate logisDcs infrastructure. A shared integraDon layer anchoring scheduling, informaDon flows, and service obligaDons across care nodes would ensure that bohlenecks are managed system-wide rather than shiYed between silos. Financing mechanisms should explicitly recognise the logisDcal work inherent in prevenDon, including mobile deployment, coordinaDon Dme, and transport operaDons, rather than remuneraDng only clinic encounters. Digital soluDons such as HealthHub 20 can funcDon as populaDon-level healthtrigger systems, but must be complemented by analogue pathways for digitally marginalised seniors.Anchored in PHLE principles, we idenDfy the following five recommendaDons.PrevenDve health planning should explicitly integrate logisDcs and operaDons specialists alongside clinicians and policymakers. Professionals experienced in supply chain management, flow design, and last-mile distribuDon (tradiDonally confined to hospital procurement) can enhance demand forecasDng, capacity planning across care nodes, and coordinate service flows in primary and community care. Embedding such experDse within Ministry of Health transformaDon teams, Regional Health Offices, and Healthier SG implementaDon units would ensure intervenDons are designed with operaDonal feasibility from the outset.Decentralised nodes and mobile models, such as neighbourhood health pods and mobile outreach units, require dedicated and recurrent funding to sustain operaDons. Ad-hoc or pilot-based funding cycles undermine scalability. Financing frameworks should treat the logisDcs infrastructure (such as vehicles, coordinaDon teams, community spaces, and scheduling systems) as long-term system investments, comparable to hospitals or polyclinics.Performance management must evolve beyond clinical outcomes to place greater emphasis on accountability through logisDcs-related system metrics and Key Performance Indicators (KPIs). These should encompass Dme-to-care (from risk idenDficaDon to intervenDon), equity of access across socioeconomic groups, and the avoidance of duplicaDon across providers. Such metrics make the operaDonal "health" of prevenDve systems visible, enabling policymakers to detect bohlenecks early and drive conDnuous improvement.PrevenDve logisDcs must reflect the lived realiDes of seniors and caregivers. Co-designing service flows -such as offering accessible venues, flexible appointment Dming , and analogue alternaDves to digital enrolment 21 -enhances parDcipaDon and sustainability. IntegraDng caregiver engagement and feedback loops ensures logisDcal efficiency translates into meaningful user experience, promoDng equity and trust.Sustainable implementaDon depends on aligning payment models with the logisDcal realiDes of prevenDon. Under capitaDon or risk-pooling arrangements, acDviDes such as transport, coordinaDon, and mobile deployment should be recognised as cost-saving investments. Funding should follow paDents across sefngs, supported by outcome-based payments Ded to successful navigaDon of high-risk individuals through the prevenDve pathway.By embedding these enablers, HSG could evolve from an enrolment-driven strategy into a dependable, neighbourhood-based delivery model. Strengthening the logisDcs infrastructure (alongside clinical, digital, and financial reforms) would operaDonalise the PHLE framework in pracDce, ensuring that prevenDve care becomes accessible, coordinated, and sustainably delivered for Singapore's ageing populaDon.The challenges observed in Singapore's experience with prevenDve health reform are mirrored across ageing socieDes such as China, Japan, South Korea, and much of Europe 22,23 , where over-reliance on facility-based delivery, fragmented provider networks, and digital or social exclusion persist as barriers to equitable care. As populaDons age and health systems pivot toward prevenDon, how services are delivered will become as criDcal as what is delivered.The PHLE framework offers a transferable response. By conceptualising prevenDon as a logisDcs ecosystem, it provides adaptable principles for diverse contexts. Decentralised care nodes may take the form of rural outreach teams in China 24 or municipality-led community centres in Europe 25 , but the underlying logic (bringing prevenDve services closer to populaDons) remains constant. Similarly, health triggers, service flows, integraDon plajorms, and performance metrics can be adapted to varying governance and resource environments while maintaining system coherence. Rather than prescribing a fixed model, the PHLE serves as a scalable architecture that health systems can selecDvely layer to align with exisDng strategies in digital health, primary care, and social services, thereby strengthening operaDonal readiness for populaDon ageing.UlDmately, the PHLE reframes prevenDve care as an operaDonal discipline rather than a purely policy or behavioural endeavour. Embedding logisDcs science into system design links prevenDve strategies to measurable flows, performance indicators, and resource allocaDon, transforming intent into implementaDon. LogisDcs should therefore be recognised not as an auxiliary support, but as a foundaDonal pillar of prevenDve health reform, on par with clinical quality and financial stewardship. The experience of HSG and comparable iniDaDves globally demonstrates that success hinges on integraDng logisDcal planning across policy, financing, and operaDonal domains. Doing so will enable health systems to move from aspiraDon to execuDon, fostering resilience and ensuring that prevenDve care remains accessible, coordinated, and people-centred.

Source: Frontiers in Public Health

DOI: 10.3389/fpubh.2025.1740511

Authors: Hao Yi Tan, Elizabeth Skylar Loo, Chuan De Foo, Huay Ling Tay, Ken Wah Teo, Lian Leng Low