Using the Human Error Assessment and Reduction Technique to predict and prevent catheter associated urinary tract infections

dc.contributor.authorFaucett, Courtney Michelle
dc.date.accessioned2017-11-17T19:10:51Z
dc.date.available2017-11-17T19:10:51Z
dc.date.graduationmonthDecemberen_US
dc.date.issued2017-12-01en_US
dc.date.published2017en_US
dc.description.abstractAccording to the Centers for Disease Control and Prevention (2015), urinary tract infections (UTIs) are the most commonly reported healthcare-associated infection (HAI), of which approximately 75% of infections are attributed to the presence of a urinary catheter. Urinary catheters are commonplace within hospitals as approximately 15-25% of patients receive a urinary catheter during their hospitalization, introducing the risk of a catheter associated urinary tract infection (CAUTI) during their stay (CDC, 2015). In recent years there have been efforts to reduce CAUTI in U.S. hospitals; however, despite these efforts, CAUTI rates indicate the need to continue prevention efforts. Researchers have investigated the use of human reliability analysis (HRA) techniques to predict and prevent CAUTI (Griebel, 2016), and this research builds on that topic by applying the Human Error Assessment and Reduction Technique (HEART) to develop a model for a patient’s probability of CAUTI. HEART considers 40 different error-producing conditions (EPCs) present while performing a task, and evaluates the extent to which each EPC affects the probability of an error. This research considers the task of inserting a Foley catheter, where an error in the process could potentially lead to a CAUTI. Significant patient factors that increase a patient’s probability of CAUTI (diabetes, female gender, and catheter days) are also considered, along with obesity which is examined from a process reliability perspective. Under the HEART process, human reliability knowledge and the knowledge of eight expert healthcare professionals are combined to evaluate the probability that a patient will acquire a CAUTI. In addition to predicting the probability of CAUTI, HEART also provides a systematic way to prioritize patient safety improvement efforts by examining the most significant EPCs or process steps. The proposed CAUTI model suggests that 7 of the 26 steps in the catheter insertion process contribute to 95% of the unreliability of the process. Three of the steps are related to cleaning the patient prior to inserting the catheter, two of the steps are directly related to actually inserting the catheter, and two steps are related to maintaining the collection bag below the patient’s bladder. An analysis of the EPCs evaluated also revealed that the most significant factors affecting the process are unfamiliarity, or the possibility of novel events, personal psychological factors, shortage of time, and inexperience. By targeting reliability improvements in these steps and factors, healthcare organizations can have the greatest impact on preventing CAUTI.en_US
dc.description.advisorMalgorzata J. Rysen_US
dc.description.degreeMaster of Scienceen_US
dc.description.departmentDepartment of Industrial & Manufacturing Systems Engineeringen_US
dc.description.levelMastersen_US
dc.identifier.urihttp://hdl.handle.net/2097/38242
dc.language.isoen_USen_US
dc.publisherKansas State Universityen
dc.subjectHuman reliability assessmenten_US
dc.subjectHuman Error Assessment and Reduction Technqiueen_US
dc.subjectCatheter associated urinary tract infectionen_US
dc.titleUsing the Human Error Assessment and Reduction Technique to predict and prevent catheter associated urinary tract infectionsen_US
dc.typeThesisen_US

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