The effect of maintenance on the survival of medical equipment

Abstract

Purpose -Studying the availability of medical equipment based on various maintenance types has been a major concern for hospitals. Most of the methodologies used are empirical and few are based on mathematical modelling. The objective of this paper is to present a mathematical maintenance model that analyses the effect of maintenance on the survival probability of medical equipment based on maintenance history and age of that equipment. Design/methodology/approach -A global model is proposed to measure the probability of equipment being available using real data extracted from maintenance history of infusion pumps and ventilators and analysed using Matlab. To confirm the validity of the developed model, the survival analysis approach is used to develop a model that measures the survival of equipment as a function of maintenance and age of equipment. The method is first tested using simulated data and the findings confirm the validity of the proposed approach. Findings -The analysis using survival approach reveals that conducting preventive maintenance (PM) on the selected medical equipment had an impact on survival of equipment. However, the manufacturer's recommended PM intervals do not correlate to the failure rate encountered. This will contribute to the debate on PM manufacturer's recommended intervals and might lead to the revision of maintenance strategies implemented by hospitals and clinical engineering (CE) practitioners. Research limitations/implications -Although the data collected for the infusion pumps were quite sufficient, that collected for the ventilators were more limited. The major difficulty is that of the availability of historical maintenance data and the effect of user errors may cause uncertainty in the analysis. A closer collaboration with the medical professional should facilitate the recording and access to such information. Practical implications -The use of mathematical modelling to analyse the effect of maintenance on the survival of medical equipment is a beneficial tool that is not exploited in the medical equipment industry. It will provide CE practitioners with scientific tool to analyse the effect of PM on the survival of medical equipment. Originality/value -This paper presents a mathematical approach to analyse the effect of maintenance on the survival of medical equipment, which is crucial in the assessment of maintenance strategies implemented in the medical equipment industry.

Maintenance Strategies and Failure‐Cost Model for Medical Equipment

“…Ridgway noted that because of the current regulatory pressures to perform PM in accordance with manufacturer's recommendations, there are currently no reliable statistics available on what increase in failure rates is expected if no PM at all was performed on various types of medical equipment. This challenge was addressed by using a global mathematical model to analyse the effect of PM on MTTF and failure rates of infusion pumps, ventilators and anaesthesia machines …”

Preventive Maintenance Optimization in Healthcare Domain: Status of Research and Perspective

“…Ridgway [31] debates the question and stresses the importance of streamlining the current maintenance policies by analyzing the operational reliability of MD. The paper [32] evaluated and analyzed maintenance strategies effect on the survival probability of some MD using exponential distribution approach. The foremost finding of this study is that the equipment flowing strictly the manufacturer's recommended interval for PM is less reliable than the one of the same model with less preventive interventions.…”

“…In [48] mathematical optimization model of periodic inspections was founded on the same simple assumption of perfect maintenance (AGAN). Later, [32] presented an age-dependent model to evaluate and analyze maintenance strategies (PM, CM) effect on the survival probability of some MD using exponential distribution approach. The purpose of this study is to counter the credibility of manufacturer's recommended interval.…”

“…He concluded that the power-law process is the most convenient for the survival models and the best fitted for repairable devices. Likewise, [32] evaluated and analyzed maintenance strategies effect on the survival probability of some MD using exponential distribution approach. Later, [67] proposes a statistical analysis of MD soft and hard failure data flowing Nonhomogenous Poisson process (NHPP) with a power-law intensity function.…”

“…The author used a recursive algorithm to find the solution, which makes the model computationally hard and time consuming. The paper [32] suggested a mixed-integer linear programming to solve an MD maintenance scheduling problem using greedy algorithms.…”