Abstract:
Proper management of medical device is mandatory for sustaining high quality patient care,
proper clinical and financial governance, and reducing the risk of adverse effect. However, due
to several reasons such as lack of operator training, maintenance capacity and inadequate
knowledge regarding complex and sophisticated equipment, the employment of proper
maintenance and disinvestment are at substandard level, especially in Ethiopia. Consequently,
serious health risks and huge economic deficit are being observed. To solve this, different
multicriteria decision analysis based maintenance management approach were proposed in the
literature. However, to our knowledge the existing literature did not incorporate inclusive and
optimum selection, and prioritizing criteria. In addition, most of the studies didn’t consider
uncertainty and vague information gathered from the expert’s. Failure mode prioritization is
mostly implemented in industrial and manufacturing field; but it is not yet been implemented for
medical device. Thus, compressive and well organized model that incorporates maintenance
strategy selection, medical device prioritization, failure prioritization and medical device
disinvestment is required for proper medical device management.
In this thesis, a hybrid multicriteria decision analysis model is proposed for selecting suitable
maintenance strategies and medical device and failure mode prioritization. In order to execute
the model, suitable criteria and attributes required for maintenance strategy, device and failure
prioritization were identified from literatures and situational analysis. The identified criteria
were examined by selected experts, meanwhile; the consistency of each expert was checked.
Then, the weights of the criteria were calculated using Fuzzy analytical hierarchy process (AHP
).To prioritize medical devices, criteria -based device assessment result and computed criteria
weights were used. The alternatives such as maintenance strategy and failure modes were
ranked by implementing Fuzzy technique for order preference by similarity to ideal solution
(TOPSIS). The rank of calculated weight and alternatives were compared and found to be in line
with the literature findings. In addition, medical device disinvestment decision support system
was also developed. Finally, web-based application was developed for ease of use for the
developed models and to facilitate the models applicability to a clinical setting.
