Technology in healthcare: A case study of healthcare supply chain management models in a general hospital in Singapore

Mittal Chikul, Hsann Yin Maw, Yang Kok Soong


Objective: To simulate and compare a manual hospital supply chain management model versus a process that is technologically integrated (either by Radio Frequency Identification [RFID] technology or automated guided vehicles [AGVs]), in a general hospital in Singapore.
Methods: Design: Deterministic modelling of hospital supply chain management for manual and technologically integrated processes as part of the institutional quality improvement exercise. Setting: Study was conceptualised during re-location of a 355-bed general hospital to newer premises within Singapore with an increased capacity of 700 beds. Study duration was 1.5 years and data collection was performed from Sep 2014 to Sep 2015.
Results: Automating the inventory check and use of automated guided vehicles for medical supplies can improve business and operational performance by saving time on no-value added activities that can be transferred to patient care. RFID intervention requires least number of man-hours per day reducing the total manpower requirements by about one third as compared to the manual process while improving productivity by about 40%, it also provides cost savings of about 25% over a period of 10 years. Sensitivity analysis shows that extent of these cost savings are dependent on overall staff utilisation. Although use of AGV alone is expensive in our model, combining AGVs with RFID technology provides the least manpower dependence among the different interventions studied, it also gives a positive return on investment as compared to manual process beyond 3 years of operations.
Conclusions: Optimising supply chains within healthcare helps minimise manpower dependency and costs. However, prior to adopting a specific intervention, the unique characteristics of each healthcare setting should be considered. There is need for similar research into healthcare supply chains to identify key determinants to cost savings and improving productivity, both locally and regionally.

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Journal of Hospital Administration

ISSN 1927-6990(Print)   ISSN 1927-7008(Online)

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