ABSTRACT
Although the healthcare technology management (HTM) community has decades of accumulated medical device-related maintenance data, little knowledge has been gleaned from these data. Finding and extracting such knowledge requires the use of the well-established, but admittedly somewhat foreign to HTM, application of inferential statistics. This article sought to provide a basic background on inferential statistics and describe a case study of their application, limitations, and proper interpretation. The research question associated with this case study involved examining the effects of ventilator preventive maintenance (PM) labor hours, age, and manufacturer on needed unscheduled corrective maintenance (CM) labor hours. The study sample included more than 21,000 combined PM inspections and CM work orders on 2,045 ventilators from 26 manufacturers during a five-year period (2012-16). A multiple regression analysis revealed that device age, manufacturer, and accumulated PM inspection labor hours all influenced the amount of CM labor significantly (P < 0.001). In essence, CM labor hours increased with increasing PM labor. However, and despite the statistical significance of these predictors, the regression analysis also indicated that ventilator age, manufacturer, and PM labor hours only explained approximately 16% of all variability in CM labor, with the remainder (84%) caused by other factors that were not included in the study. As such, the regression model obtained here is not suitable for predicting ventilator CM labor hours.
Subject(s)
Biomedical Engineering/methods , Data Mining/methods , Databases, Factual , Maintenance , Software , Animals , Models, StatisticalSubject(s)
Biomedical Technology , Maintenance , Materials Management, Hospital , Biomedical Technology/methods , Biomedical Technology/organization & administration , Biomedical Technology/standards , Humans , Information Dissemination , Maintenance/methods , Maintenance/organization & administration , Maintenance/standards , Materials Management, Hospital/methods , Materials Management, Hospital/organization & administration , Materials Management, Hospital/standardsABSTRACT
This paper gives sample ethical case vignettes and discussions that will be presented at the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'14) special session of the Ethics and Professional Responsibility Committee. The session includes additional cases with audience participation and panel discussions.
Subject(s)
Biomedical Technology/ethics , Biomedical Technology/legislation & jurisprudence , HumansSubject(s)
Cognition , Ergonomics/methods , Man-Machine Systems , Software , User-Computer Interface , Visual Perception , Humans , Software DesignSubject(s)
Decision Support Techniques , Ergonomics/methods , Facility Design and Construction/methods , Man-Machine Systems , Medical Errors/prevention & control , Process Assessment, Health Care/methods , Risk Assessment/methods , Equipment Design/methods , Mandatory Reporting , Risk Factors , United StatesABSTRACT
In order for vacuum-assisted venous return (VAVR) to be used safely and efficiently during cardiopulmonary bypass (CPB), a full understanding of venous return is necessary. The focus of this work was to use the concepts of energy conservation and viscous energy dissipation in the development of a theoretical model of venous return utilizing vacuum assist. The effectiveness and accuracy of this model has been verified through in vitro laboratory investigations and statistical analysis. Although VAVR can provide higher flows through smaller venous cannula, vacuum assist may lead to increased levels of wall shear stress as shown in this work. The clinical implications of VAVR have yet to be investigated, but may lead to an exacerbation of the detrimental effects of CPB during cardiac surgery.
