Data Mining of Enterprise Resource Planning System to Support Effective and Efficient Equipment Repair Monitoring and Reference for Future Procurement

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Abstract Description
Abstract ID :
HAC5841
Submission Type
Authors (including presenting author) :
Cheung EYY, Cheung MHH, Leung KKL, Woo CW, Wong EYW, Chan JSP, Tsui AYY, LAU MHL, Chau RMW
Affiliation :
Physiotherapy Department, Kowloon Hospital
Introduction :
Therapeutic equipment constitutes one of the essential components in modern medicine. With over 2,000 equipment/gadgets in physiotherapy department, equipment maintenance & repair monitoring is vital to the safe and efficient service delivery. Environment Ambassadors Scheme was implemented since 2014 with system-in-place serving the function. With the implementation of the Enterprise Resource Planning(ERP) in HA, structured data on asset, request & maintenance details are captured providing user department with required information & data for systematic monitoring and further application of the “big data” such as future equipment procurement.
Objectives :
To apply the ERP based data for equipment maintenance/repair monitoring in ensuring safe and adequate usable equipment for effective & efficient physiotherapy services provision.
Methodology :
Malfunctioned equipment in Physiotherapy Department of Kowloon Hospital was identified by the corresponding environment ambassador of the venue with timely suspension of use and request for corrective maintenance made in ERP. The 2019 annual maintenance record of all repair request was extracted through ERP system and the characteristics of equipment was analyzed & categorized e.g. according to equipment type, manufacturer, model.
Result & Outcome :
There was a total of 188 entries in 2019. The most frequent malfunctioned equipment was aged mechanical wheelchair, neuromuscular electrical stimulators(NMES), exercisers, transcutaneous electrical nerve stimulators(TENS) and ultrasound(episode range: 11 to 16). There are various models of ultrasound therapy and NMES in the department. The NT-2LF model of aged NMES machine has the highest hit(7 episodes) as compared with other two models(1 & 4 episodes);SONOSTAT TOUCH for ultrasound(4 episodes) within 2-year of purchase, as compared with the other models(range 1 to 2 episodes). Readily available vital information on equipment model of frequent breakdown within usable life and check & balance of repair cost of aged equipment well beyond life cycle for economic repair, were derived. ERP information such as age(usable life), procured cost for calculation of depreciation cost(Sahu et al.,2016) also aided rational decision making for economic repair versus equipment replacement in uphold of accountability for resources utilization. Full compliance to equipment checking & repair arrangement process was detected. There was no equipment related patient or staff injury-on-duty incident in reviewed period. In conclusion, the ERP data together with the Environment Ambassadors Scheme provided seamless man-system interface for equipment maintenance/repair monitoring contributing to safe and adequate usable equipment for effective and efficient services provision at Physiotherapy Department. Reference Sahu AK, Narang HK, Sahu AK and Sahu NK. Machine economic life estimation based on depreciation-replacement model. Cogent Engineering (2016), 3: 1249225 http://dx.doi.org/10.1080/23311916.2016.1249225

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