Karamarie Fecho, Charity G. Moore, Anne T. Lunney, Peter Rock, Edward A. Norfleet and Philip G. Boysen
This paper aims to determine the one‐year incidence of, and risk factors for, perioperative adverse events during in‐patient and out‐patient anesthesia‐assisted procedures.
Abstract
Purpose
This paper aims to determine the one‐year incidence of, and risk factors for, perioperative adverse events during in‐patient and out‐patient anesthesia‐assisted procedures.
Design/methodology/approach
A quality assurance database was the primary data source. Outcome variables were death and the occurrence of any adverse event. Risk factors were ASA physical status (PS), age, duration and type of anesthesia care, number of operating rooms running, concurrency level and medical staff. Data were stratified by in‐patient or out‐patient, surgical (e.g. thoracotomy) or non‐surgical (e.g. electroconvulsive therapy), and were analyzed using Chi square, Fisher's exact test and generalized estimating equations.
Findings
Of 27,970 procedures, 49.8 percent were out‐patient and greater than 80 percent were surgical. For surgical procedures, adverse event rates were higher for in‐patient than out‐patient procedures (2.11 percent vs. 1.45 percent; p<0.001). For non‐surgical procedures, adverse event rates were similar for in‐patients and out‐patients (0.54 percent vs. 0.36 percent). The types of adverse events differed for in‐patient and out‐patient surgical procedures (p<0.001), but not for non‐surgical procedures. ASA PS, age, duration of anesthesia care, anesthesia type and medical staff assigned to the case were each associated with adverse event rates, but the association depended on the type of procedure.
Practical implications
In‐patient and out‐patient surgical procedures differ in the incidence of perioperative adverse events, and in risk factors, suggesting a need to develop separate monitoring strategies.
Originality/value
The paper is the first to assess perioperative adverse events amongst in‐patient and out‐patient procedures.
Details
Keywords
Ozan Okudan, Murat Cevikbas and Zeynep Işık
The purpose of this paper is to propose a decision support framework that can be used by decision-makers to identify the most convenient disruption analysis (DA) methods for…
Abstract
Purpose
The purpose of this paper is to propose a decision support framework that can be used by decision-makers to identify the most convenient disruption analysis (DA) methods for megaprojects and their stakeholders.
Design/methodology/approach
The framework was initially developed by conducting a comprehensive literature review to obtain extensive knowledge about disruption management and megaprojects. Focus group discussion (FGD) sessions with the participation of the construction practitioners were then organized to validate and strengthen the findings of the literature review. Consequently, 17 selection factors were identified and categorized as requirement, ability and outcome. Lastly, the most convenient DA methods for megaprojects were identified by performing integrated fuzzy analytical hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) analysis. Additionally, consistency analysis was also conducted to verify the reliability of the results.
Findings
The results revealed that the measured mile method is the most appropriate DA method for megaprojects. In case the measured mile method cannot be adopted due to various technical and contractual reasons, the decision-makers are proposed to consider program analysis, work or trade sampling, earned value analysis and control chart method, respectively. Second, the selection factors such as “Comprehensible analysis procedure,” “Existing knowledge and experience about a particular DA method,” “Ability to resolve greater number of disruption events,” “Ability to resolve complex disruption events,” “Ability to exclude factors that are not under the owner's responsibility” and “General acceptance by practitioners, courts, and arbitration, etc.” were given the top priority by the experts, highlighting the critical aspects of the DA methods.
Originality/value
Disruption claims in megaprojects are very critical for the contractors to compensate for the losses stemming from disruption events. Although the effective use of DA methods maximizes the accuracy and reliability of disruption claims, decision-makers can barely implement these methods adequately since past studies neglect to present extensive knowledge about the most convenient DA methods for megaprojects. Thus, developing a decision support framework for the selection of DA methods, this study is the earliest attempt that examines the mechanisms and inherent differences of DA methods. Additionally, owing to the robustness and versatility of this research approach, the research approach could be replicated also for future studies focusing on other project-based industries since disruption is also a challenging issue for many other industries.