Evidence-based medical equipment management: a convenient implementation

Abstract

Maintenance is a crucial subject in medical equipment life cycle management. Evidence-based maintenance consists of the continuous performance monitoring of equipment, starting from the evidence—the current state in terms of failure history—and improvement of its effectiveness by making the required changes. This process is very important for optimizing the use and allocation of the available resources by clinical engineering departments. Medical equipment maintenance is composed of two basic activities: scheduled maintenance and corrective maintenance. Both are needed for the management of the entire set of medical equipment in a hospital. Because the classification of maintenance service work orders reveals specific issues related to frequent problems and failures, specific codes have been applied to classify the corrective and scheduled maintenance work orders at Careggi University Hospital (Florence, Italy). In this study, a novel set of key performance indicators is also proposed for evaluating medical equipment maintenance performance. The purpose of this research is to combine these two evidence-based methods to assess every aspect of the maintenance process and provide an objective and standardized approach that will support and enhance clinical engineering activities. Starting from the evidence (i.e. failures), the results show that the combination of these two methods can provide a periodical cross-analysis of maintenance performance that indicates the most appropriate procedures. Graphical abstractThe left side shows a block diagram of the process needed to calculate the proposed set of KPIs, starting from technological, organizational and financial data. On the upper right it is shown an example of scheduled maintenance analysis for a specific class of equipment (legend in the article body). The bottom right part shows how the KPIs can be implemented in a business intelligence dashboard.

Case Studies on the Use of Sentiment Analysis to Assess the Effectiveness and Safety of Health Technologies: A Scoping Review

“…One of the goals of our preliminary study is to design a method to analyze the performances of medical devices starting from data that are extracted from electronic medical records. A similar application can involve the analysis of technical reports after scheduled and corrective maintenance that are aimed to implement an evidence-based maintenance [30], [31], [32]. In addition, SA can play an important role in the post-market evaluation of medical devices as a feedback loop that consumers can use to express their satisfaction directly to the company [19].…”

Clinical needs and technical requirements for ventilators for COVID-19 treatment critical patients: an evidence-based comparison for adult and pediatric age

“…Historically, clinical engineering has been based on best practices and clinical engineers have been less involved in research activities as well as in publishing their activities’ results in peer reviewed journals. However, in the past 10 years, clinical engineering has been growing globally [ 15 ], with the first peer reviewed journal papers on evidence-based being published in 2019 [ 16 , 17 ]. Similarly to what Pecchia et al did for personal protective equipment [ 18 ], starting from the clinical indications spread by WHO and the Italian Ministry of Health, we joined our efforts to conscientiously share the minimum technical requirements that an ICU ventilator might meet to be considered acceptable for treating COVID-19 patients in severe to critical illnesses, comparing and, at the same time, combining in an easily readable way, all the indications publicly available in order to provide a unified and global vision.…”

Medical devices nomenclature systems: a scoping review

“…Henschke's aim is to develop a taxonomic model in which devices are evaluated according to their risk class in a logic of HTA [35]. The model structure is a 9 × 6 matrix; to develop the model the authors used:…”

“…We found five articles dealing with UDI nomenclature framework [30][31][32][33][34], and one with GMDN [35]. In Sherwin's work [34], the authors examine some of the key problems in managing MD inventory tracking.…”

“…In the work from Henschke et al [35], the aim is to develop a taxonomy model that provides researchers and policy makers with an orientation tool to approach the assessment of different use and regulations of MDs. Drozda et al [32] report the Food and Drug Administration (FDA) strategy defined for the MDs post-market surveillance, in 2012.…”