Application of a Prediction Model for Directing Antibiotic Use in the Treatment of Urinary Tract Infection in an Ambulatory Setting

NCT ID: NCT06976125

Last Updated: 2026-01-27

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 47 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2026-03-01
• Study Completion Date: 2026-06-01

Brief Summary

Urinary tract infection (UTI) is when bacteria enter the urinary system and cause an infection. UTIs cause symptoms including burning when peeing, a feeling of an increased urge to pee, and cloudy or strong-smelling urine. Sometimes, severe UTIs can also cause fever, abdominal pain, and/or lower back pain.

In the emergency department (ED), healthcare providers rely on symptoms, along with a urine analysis and a urine culture to diagnose a UTI. A urine analysis involves taking a sample of urine and analyzing different factors like color, acidity, presence of blood cells, presence of bacteria. An abnormal urine analysis increases the likelihood that patients might have a UTI, but it does not confirm it. A positive urine analysis will lead to provider's sending a sample of urine for a urine culture. A urine culture is used to grow whatever bacteria is in the collected urine. If growth is seen on the culture, then this confirms a patient has a UTI. This also specifies which bacteria grew on the culture. The lab can also take it a step further and do an antibiotic test to check which antibiotic the bacteria is sensitive to.

When a urine analysis comes back abnormal in an ER setting, patients are prescribed an antibiotic before the culture and antibiotic sensitivity tests come back. If a patients condition is not critical, they will be discharged home before the culture results come back. If the culture comes back positive, the pharmacists will evaluate the culture and antibiotic sensitivity tests, then call patients to inform them whether they are taking a suitable antibiotic.

This study aims to decrease the unnecessary use of antibiotics because this contributes to antibiotic resistance which is considered a global public health issue. Antibiotic resistance occurs when bacteria develop the ability to withstand certain antibiotics that used to be effective against them, which makes it difficult to treat the infection. One of the factors that increase the risk of antibiotic resistance is the overuse of antibiotics.

In this study, investigators will be incorporating a prediction model and a negative callback system to decrease unnecessary antibiotic use.

Conditions

Urinary Tract Infections

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: PREVENTION
• Blinding Strategy: NONE

Study Groups

Presenting to ER for Urinary Tract Infection (UTI)

Patients presenting to the a UH ER location for UTI symptoms.

Group Type: EXPERIMENTAL

Decision Aid-prediction model

Intervention Type: DEVICE

ER physician will input the necessary de-identified data into the decision aid application.

The decision aid determines if the patient has a high or low likelihood of having a positive urine culture. The patient with high likelihood of positive culture, will be prescribed empiric antibiotics per the UH guidelines for treating UTI in the ambulatory setting. Patients with a low likelihood of having a positive culture, will be discharged without antibiotics.

Study team members will give the patient a handout describing what will happen in the event of a positive or negative culture.

The culture call-back team, consisting of clinical pharmacists, will be notified.

Interventions

Decision Aid-prediction model

ER physician will input the necessary de-identified data into the decision aid application.

The decision aid determines if the patient has a high or low likelihood of having a positive urine culture. The patient with high likelihood of positive culture, will be prescribed empiric antibiotics per the UH guidelines for treating UTI in the ambulatory setting. Patients with a low likelihood of having a positive culture, will be discharged without antibiotics.

Study team members will give the patient a handout describing what will happen in the event of a positive or negative culture.

The culture call-back team, consisting of clinical pharmacists, will be notified.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

• Female sex
• Age >18 years old
• Discharged from the hospital after ER visit
• Discharge ICD code consistent with a UTI diagnosis
• Antibiotic prescribed for UTI at the time of discharge

Exclusion Criteria

• Male sex
• Necessity for chronic bladder catheterization or discharge with a urinary catheter
• Patients who have an Emergency Severity Index (ESI) of 1 and 2
• Patients who verbalize to the study team member that their pain is a 6 or higher
• Patient set to be transferred to inpatient care
• History of bladder augmentation
• Pregnancy (this will be confirmed with a negative pregnancy test which is ordered in the ER)

• Minimum Eligible Age: 18 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: No

Sponsors

University Hospitals Cleveland Medical Center

OTHER

Sponsor Role: lead

Responsible Party

David Sheyn

Physician

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

David Sheyn, MD

Role: PRINCIPAL_INVESTIGATOR

University Hospitals Cleveland Medical Center

Locations

University Hospitals Cleveland Medical Center

Cleveland, Ohio, United States

Countries

United States

Central Contacts

Jessica Abou Zeki

Role: CONTACT

Jessica.AbouZeki@UHhospitals.org

216-286-0603

Facility Contacts

Mofetoluwa Abraham Oluwasanmi

Role: primary

mofetoluwa.oluwasanmi@uhhospitals.org

440-317-2777

Other Identifiers

STUDY20250812

Identifier Type: -

Identifier Source: org_study_id