Doctor of Philosophy (PhD) in Health Science
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College of Health Care Sciences – Health Science Department
Publication Date / Copyright Date
Nova Southeastern University. College of Health Care Sciences.
Wei Chao Chang. 2015. Impact of Preoperative Patient Profiles on Elective Open Intestinal Resection Outcomes. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, College of Health Care Sciences – Health Science Department. (2)
There are a myriad of risk factors for surgical mortality, intraoperative and postoperative complications, and prolonged length of stay. Effectively identifying possible risk factors in the preoperative patient profiles that may impact the outcome of elective open intestinal resection has significant implications on the quality of care, the safe delivery of surgical care, and the speedy recovery of patients undergoing elective open intestinal resection. Few studies specifically focused on the construction of individual preoperative patient risk profile used only preoperative patient profiles in elective open intestinal resection. A retrospective cohort predictive study was conducted to assess the impact of preoperative patient profiles on surgical outcomes in patients undergoing elective open intestinal resection using 2009-2011 Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) databases. This study aimed to identify independent predictors in the preoperative patient profiles for the development of preoperative patient risk profiling tool for the construction of an individual preoperative patient risk profile for risk stratification, surgical planning, and care coordination for patients undergoing elective open intestinal resection. The results of this study showed that independent predictors in the preoperative patient profiles could predict the risks of increased adverse surgical outcomes in terms of in-hospital mortality, in-hospital complications, and prolonged length of stay in patients undergoing elective open intestinal resection. Independent predictors of increased adverse surgical outcomes were identified in the personal domain, the social history domain, and the comorbidity domain of preoperative patient profiles. In the personal domain profile, advanced age was an independent predictor of increased in-hospital mortality, prolonged length of stay (LOS), and six of the eight categories of in-hospital complications studied, except mechanical wound complications and infection complications. The 18 to 39 age group was more likely to develop the latter two complications. Male gender was an independent predictor of in-hospital mortality, prolonged LOS, and six of the eight in-hospital complications except intraoperative complication and systemic complications. Asian/Pacific Islanders were more likely to have intraoperative bleeding complication while black patients were more likely to have gastrointestinal complications and prolonged LOS compared to white patients. In the social history domain profile, patients with alcohol abuse were more likely to suffer pulmonary complications and have prolonged LOS. Patients with illicit drug abuse were more likely to have prolonged LOS as well. Four comorbidities, fluid and electrolyte disorders, weight loss, coagulopathy, and congestive heart failure, were identified as the strongest independent predictors of increased adverse surgical outcomes overall, except in the cardiovascular complications. Pulmonary circulation disorders were the strongest independent predictors of cardiovascular complications. Other comorbidities that were statistically significant and unique predictors of adverse outcomes were also identified. Patients without comorbidity were less likely to have increased in-hospital mortality, prolonged LOS, and in-hospital complications. These findings have significant implications in developing preoperative patient risk profiling tools for the construction of an individual preoperative patient risk profile for risk stratification, surgical planning, and care coordination in patients undergoing elective open intestinal resection.
Medicine and Health Sciences
Health and environmental sciences, Predictors, Preoperative patient profiles, Preoperative patient risk profile, Preoperative patient risk profiling