Implementation Study With Decision Support Based on Data

May 26, 2020 updated by: Tn Bonten, Leiden University Medical Center

Implementation Study With Machine Learning Based Decision Support Software for Treatment of Urinary Tract Infections in General Practice.

This study evaluates the implementation of a machine learning based clinical decision support system for treatment of patients presenting with an urinary tract infection in general practice. The software was developed to support general practitioners in the choice of antibiotic regimen.

Study Overview

Status

Completed

Conditions

Study Type

Observational

Enrollment (Actual)

16824

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

      • Utrecht, Netherlands
        • Netherlands Institute for Health Services Research

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

12 years and older (Child, Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Patients with a urinary tract infection diagnosed by the general practitioner

Description

Inclusion Criteria:

  • Patients with a urinary tract infection in general practice
  • Age > 12 years.

Exclusion Criteria:

  • No.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Software practices
Patients with urinary tract infection in practices using the clinical decision support software
Control practices
Patients with urinary tract infection in practices not using the clinical decision support software

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Non-recurrent UTI
Time Frame: 28 days
A subsequent period of time after treatment, in which no new UTI treatment was needed
28 days

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Collaborators

Investigators

  • Study Director: Willem Herter, Leiden University Medical Center
  • Principal Investigator: Tobias Bonten, Leiden University Medical Center

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

November 13, 2017

Primary Completion (Actual)

May 16, 2018

Study Completion (Actual)

May 16, 2018

Study Registration Dates

First Submitted

May 26, 2020

First Submitted That Met QC Criteria

May 26, 2020

First Posted (Actual)

June 1, 2020

Study Record Updates

Last Update Posted (Actual)

June 1, 2020

Last Update Submitted That Met QC Criteria

May 26, 2020

Last Verified

May 1, 2020

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • P1746

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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