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Int J Colorectal Dis ; 39(1): 91, 2024 Jun 13.
Article in English | MEDLINE | ID: mdl-38867089

ABSTRACT

PURPOSE: Surgery wait times after diagnosis of appendicitis are an important factor influencing the success of a patient's treatment. The proposed study will be a quantitative multicenter retrospective cohort design with the primary aim of assessing the difference between appendicectomy wait times between rural and urban hospitals in Western Australia and the effect of this on operative outcomes. Selected outcome measures will be examined by time from initial presentation at an emergency department to the patient being diagnosed and then time of diagnosis to surgery being performed. The secondary aim is to compare rates of negative appendicectomies between hospitals. METHODS: Appendicectomy patients will be identified from operating room register by medical student data collectors; then, each respective hospital's emergency room data collection will subsequently be accessed to complete case report forms based on demographics and clinical findings, pre-operative investigations, and management and follow-up. Case report forms with > 95% completeness will be accepted for pooled analysis. The expected duration of retrospective data collection will be 8 months. This study RGS6483 has received HREC approval by the Royal Perth Hospital HREC Ethics Committee, with a waiver of consent obtained and the HREC was notified of amendments to the protocol made on April 21, 2024. Dissemination of results. Data will be collected and stored online through a secure server running the Research Electronic Data Capture (REDCap) web application. No patient-identifiable data will be entered into the system. Results will subsequently be shared via scientific journal publication and presentation at relevant meetings.


Subject(s)
Appendectomy , Humans , Appendectomy/statistics & numerical data , Western Australia , Treatment Outcome , Appendicitis/surgery , Geography , Waiting Lists , Time Factors , Time-to-Treatment/statistics & numerical data , Rural Population/statistics & numerical data , Hospitals, Urban/statistics & numerical data , Retrospective Studies
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