Objectives: We examined patient-specific predictors of high cost for endovascular (EVAR) and open (OPEN) repair of abdominal aortic aneurysm (AAA).
Methods: Vascular Study Group of Northern New England data specific to Fletcher Allen Health Care were merged with cost data from the same source. We retrospectively analyzed 389 elective AAA repairs (230 EVAR, 159 OPEN) between 2003 and 2011 to determine clinical characteristics that contribute to membership in the upper quartile of cost (UQC) versus the remaining three quartiles. For the purpose of this exercise, it was assumed that clinical outcomes were equally good with EVAR versus OPEN repair.
Results: Significant predictors of UQC for OPEN repair procedures were: history of treated chronic obstructive pulmonary disease (COPD), previous bypass surgery, transfer from hospital and age >70 (area under receiver operating curve [ROC] = 0.726). Predictors of UQC for EVAR were: presence of iliac aneurysm(s), coronary artery bypass graft surgery or percutaneous transluminal coronary angioplasty within the past 5 years, ejection fraction ≤30%, absence of beta blockers, creatinine ≥1.5mg/dL, and current use of tobacco (area under ROC = 0.784). The mean length of stay for EVAR and OPEN repair were 2.22 and 8.55 days, respectively. Costs for EVAR and OPEN repair were $32,656 (standard error of the mean [SEM] $591) and $28,183 (SEM $1,571), respectively.
Conclusions: Certain risk factors at the individual patient level are predictive of UQC. Under such circumstances, it is our expectation that such algorithms may be used to select the most cost-efficient treatment.
surveillance data collection. Such are defined as an aircraft without a human pilot on board, operated either autonomously by computer or under remote control by a human pilot. Methods: We performed a targeted literature search for medical applications of UAS and rank-ordered strengths and weaknesses according to emerging applications and corresponding difficulty, feasibility and cost. Results: Based on secondary sources, we report conceptual factors that can contribute to the practicality and efficiency of UAS in emergency medical situations. These were 1) frequency of occurrence, 2) time-sensitivity of occurrence, 3) rurality and complex terrain, 4) financial impact and 5) cultural acceptance. The results of our matrix point to a gradation of accepted uses for UAS with the variance in geographical location and urgency directly relating to an increase in operation costs. It is well known that natural disasters are increasing in frequency and intensity. Salient platforms for using UAS in medical delivery would be in the areas of natural and combative disaster relief. During these occurrences the use of UAS to aid in the medical relief could be a great asset. ConClusion: Our model illustrates how Big Data can be leveraged to improve ongoing quality and efficiency of UAS-delivered medical supplies, reduce time for delivery of supplies during times of natural disasters, and thus eschew our reliance on manned aircraft to assist in critical and non-critical medical operations.objeCtive: We propose a paradigm and ranking system for potential medical applications of unmanned aircraft systems (collectively UAS). Over the past three decades, UAS have become a vital component to our armed forces, used notably for combat but also commonly used for work in intelligence, reconnaissance and
switching to a combination therapy from monotherapy, regardless of medical conditions. Further research is required to evaluate the possible negative aspects of FDC drugs.
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