NATIONWIDE PATHOLOGY SERVICES NETWORK STUDY ON DISINVESTMENT AND INVESTMENT STRATEGIES: A STUDY PROTOCOL

Author(s)

LOW E. VIEN, RPh, PhD1, Tengku Norita Tengku Yazid, MBBS, MPath2, Yui Ping Tan, RPh, MSC1, Wan Hayati Mohd Yaakob, MD, MPath3, Sahlawati Mustakim, MBBChBAO, MPath4, Hanisah Abd Hamid, MD, MPath3, Sharifah Khairul Atikah Syed Kamaruddin, MD, MPath4, Marhaini Mostapha, PhD1, Mohd Shaiful Jefri Mohd Nur Sham Kunusegaran, MD1, Farhana Aminuddin, PhD1, Sivaraj Raman, RPh, MSC1, Nur Amalina Zaimi, BDS1, Jabrullah Ab Hamid, PhD1, Olivia Yen Ping Tan, MD, MPH5, Huzaifah Hussin, MD, DrPH6, Syful Azlie, MS6, Iylia Raihana Semsudin, MS6, Nor Zam Azihan Mohd Hassan, MD, DrPH1;
1Institute for Health Systems Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam, Malaysia, 2Selayang Hospital, Department of Pathology, Kuala Lumpur, Malaysia, 3Tengku Ampuan Rahimah Hospital, Department of Pathology, Klang, Malaysia, 4Sungai Buloh Hospital, Department of Pathology, Sungai Buloh, Malaysia, 5Medical Development Division, Ministry of Health Malaysia, Putrajaya, Malaysia, 6Family Health Development Division, Ministry of Health Malaysia, Putrajaya, Malaysia
OBJECTIVES: Pathology services underpin clinical and public health decision-making, yet national laboratory systems in middle-income countries are frequently fragmented, cost-inefficient, and weakly coordinated. This study aims to identify existing infrastructure and system configurations and to model disinvestment and investment strategies for redesigning laboratory services at a whole-system level.
METHODS: This is a cross-sectional, retrospective study of pathology service coverage, resource utilization, and logistics network delivery within the Ministry of Health (MOH) Malaysia. The study applies a three-phase, system-level methodological framework. Phase 1 establishes a nationwide census of all public hospitals and primary health clinics (n = 929) providing pathology services. Standardized primary data are collected on test volumes, costs, workforce, equipment, logistics, laboratory information systems, and turnaround time. Phase 2 applies top-down costing and multivariable regression analyses to identify key drivers of cost per test and laboratory turnaround time across facility types, disciplines, and referral modalities. Phase 3 will use dynamic network modelling (DNO) to model optimal laboratory network designs. Unlike single-facility or discipline-specific studies, DNO applies geospatial modelling to simulate alternative laboratory network configurations, explicitly quantifying trade-offs between cost, access, and turnaround time. A baseline model will be developed using the census data. Based on the data from Phase 2 and expert input, future scenarios incorporating projected testing demands, equipment placements and its potential impact on turnaround time and costs will be constructed. DNO look at the impact of costs and outcomes, beyond individual laboratories, adopting a whole system perspective.
RESULTS: Our study framework enables systematic identification of low-value activities suitable for disinvestment (e.g., laboratory consolidation or lab tests redistribution) and priority domains for targeted investment (e.g., high-performance analysers in high-volume settings).
CONCLUSIONS: This framework supports data-driven decision-making to improve patient outcomes through efficient laboratory services while reducing overall healthcare costs and is applicable to other health systems pursuing universal health coverage.

Conference/Value in Health Info

2026-05, ISPOR 2026, Philadelphia, PA, USA

Value in Health, Volume 29, Issue S6

Code

HSD50

Topic

Health Service Delivery & Process of Care

Disease

No Additional Disease & Conditions/Specialized Treatment Areas

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