Document Type

Final Project

Graduation Date

Spring 5-4-2024

Degree Name

Doctor of Nursing Practice

First Advisor

Catherine Carithers

Abstract

Urinary tract infections, UTIs, are among the most common reasons college-aged women seek medical care. The selected University clinic has a difficult time triaging walk-in UTI patients promptly. Long patient wait times have a negative effect on patient and employee satisfaction scores. An algorithm was created to assist the University clinic in triaging walk-in UTI patients using guidelines from the American Academy of Family Physicians updated with the most current clinical practice recommendations. The algorithm includes the utilization of a point-of-care urine analyzer which provides urinalysis results in 120 seconds. With the algorithm and point-of-care urine analyzer, the student health clinic can improve wait times for patients seeking treatment for UTIs. Improving the diagnosis and treatment process for the large number of female patients seeking medical care for UTI symptoms will facilitate patient and provider satisfaction. Validation of reliable methods that accurately diagnose UTIs without overuse of valuable clinic time and resources is necessary.

This study is a retrospective observational study on wait times and the effectiveness of diagnosing patients using the proposed algorithm. Data were collected over two three-month periods, each separated by a year pre- and post-intervention, and a total of 220 charts were collected. The study took place at a university campus student health center in the front range area of Colorado. Inclusion criteria for participants in the quality improvement project included college-aged women who were assigned female gender at birth and are aged 18 years and older who walk into the health clinic, presenting with UTI symptoms of dysuria, frequency, and/or urgency. Exclusion criteria included pregnant women, those assigned male gender at birth, and participants with scheduled appointments.

The study results showed that implementing the algorithm to reduce patient wait times was not statistically significant. The mean wait time for patients pre-intervention was 70.44 minutes, while the post-intervention cohort had an average wait time of 68.04 minutes. This reduction was not statistically significant. However, the algorithm did not have a negative effect on the effectiveness of diagnosing female patients with UTIs based on return follow-up visits.

This study did not prove that the algorithm helped reduce patient wait times. In future studies, barriers impacting patient wait times must be identified and managed. Future studies to identify when POC urinalysis testing is appropriate, how POC testing affects patient wait times, and the effectiveness of diagnosing UTIs with POC testing versus laboratory-run urinalysis could all help to make this research study more effective in reducing patient wait times in future attempts. Implications of this study could translate to other ambulatory healthcare settings in helping these clinics assess where their barriers lie in reducing patient wait times and how they can manage these barriers.

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