Antibiotic Prescription Relevance Indicators: Calculation From Electronic Health Records (ARIPPA)

Automatisation du Recueil d'Indicateurs de Pertinence de Prescription d'Antibiotiques : Développement, Validation et efficacité d'un Outil Utilisant Les systèmes d'Information d'un Groupement Hospitalier de Territoire

This research focuses on the development and validation of indicators on the relevance of antibiotic prescriptions. The investigators want to propose transferable tools to other healthcare institutions to allow automated construction of quality indicators as part of a structured approach to improve future practices. The main objective of the study is to develop indicators on the appropriateness of antibiotic prescriptions and on surgical prophylaxis automated from the hospital information system and to assess their criterion validity.

Study Overview

• Status: Recruiting
• Conditions: Surgery; Antibiotic
• Intervention / Treatment: Other: Automatic tool to identify inappropriate antibiotic prescriptions

Detailed Description

According to the national program to control Antimicrobial resistance, hospitals are required to report two indicators on antibiotic prescriptions appropriateness: 1/the percentage of inappropriate treatment among treatments lasting more than 7 days; 2/the percentage of surgical antibiotic prophylaxis lasting more than 24 hours.

These indicators are collected via practice audits that are time-consuming and cover a limited number of patient records.

The main objective of ARIPPA project is to assess the ability of an automatic tool to detect inappropriate antibiotic prescriptions directly from the electronic health records (sensitivity). Secondary objectives are 1) to assess the specificity, positive predictive value and negative predictive value of the tool for automatically calculating indicators of the relevance of antibiotic prescriptions from information systems, 2) to assess the impact of individual and collective feedbacks on antibiotic prescription appropriateness 3) to explore acceptability of this automated tool by prescribers.

This observational study consists in 4 steps: 1/ development of the automatic tool to detect inappropriate antibiotic prescriptions directly from the electronic health records - for treatments lasting more than 7 days, the study will focus on respiratory infections and urinary tract infections which are the most common infections in hospitals; 2/ assessment of metrologic performance of the tool by comparison to practice audits as the gold standard; 3/ feedback of the indicators to the prescribers and 4/ evaluation of the impact of this feedback on appropriateness of antibiotic prescriptions.

This project will be piloted at Bordeaux University hospital and then implemented in other public hospitals belonging to a same territorial organization. As each hospital information system is different, the investigators will propose transposable tools to other healthcare institutions to allow an automated construction of these indicators.

• Study Type: Observational
• Enrollment (Anticipated): 2115

Contacts and Locations

• Study Contact: Name: Frantz THIESSARD, MD, PhD; Phone Number: + 33 557 574 522; Email: frantz.thiessard@u-bordeaux.fr ; frantz.thiessard@chu-bordeaux.fr
• Study Contact Backup: Name: Catherine DUMARTIN, PharmD; PhD; Phone Number: + 33 556 796 058; Email: catherine.dumartin@chu-bordeaux.fr

Study Locations

• France
  • Arcachon, France, 33120
    • Not yet recruiting
    • Arcachon Hospital
    • Contact: Stéphanie Bez, MD; Email: stephanie.bez@ch-arcachon.fr
    • Principal Investigator: Stéphanie Bez, MD
    • Sub-Investigator: Pierre Labadens, MD
    • Sub-Investigator: Martha Videcoq, MD
    • Sub-Investigator: Fabien Giroux, MD
    • Sub-Investigator: Catherine De Montaudouin, MD
    • Sub-Investigator: Mélanie Gautier, PharmD
  • Blaye, France, 33390
    • Not yet recruiting
    • Blaye Hospital
    • Contact: Cathy Rakotomalala, MD; Email: rakotomalala@chblaye.fr
    • Principal Investigator: Cathy Rakotomalala, MD
    • Sub-Investigator: Elodie Arnaud, PharmD
  • Bordeaux, France, 33000
    • Recruiting
    • Bordeaux university hospital
    • Sub-Investigator: Romain Griffier, MD
    • Contact: Anne-Marie Rogues, MD PhD; Email: anne-marie.rogues@chu-bordeaux.fr
    • Principal Investigator: Anne-Marie Rogues, MD PhD
    • Sub-Investigator: Vianney Jouhet, MD PhD
    • Sub-Investigator: Charles Cazanave, MD PhD
    • Sub-Investigator: Arnaud Desclaux, MD PhD
    • Sub-Investigator: Stephane Pedeboscq, PharmD PhD
    • Sub-Investigator: Véronique Gilleron, MD
    • Sub-Investigator: Eric Ouattara, MD
    • Sub-Investigator: Maider Coppry, PharmD PhD
  • Bordeaux, France, 33000
    • Not yet recruiting
    • Charles Perrens Hospital
    • Contact: Françoise Obeniche, MD; Email: fobeniche@ch-perrens.fr
    • Principal Investigator: Françoise Obeniche, MD
    • Sub-Investigator: Anne Colombe, PharmD
    • Sub-Investigator: Anne-Laure Debruyne, PharmD
    • Sub-Investigator: Elisabeth Goumard, MD
  • Cadillac, France, 33410
    • Not yet recruiting
    • Cadillac Hospital
    • Contact: Laurence Parneix-Sediey, PharmD; Email: laurence.parneix@ch-cadillac.fr
    • Principal Investigator: Laurence Parneix-Sediey, PharmD
    • Sub-Investigator: Bérénice Bréchat-Huet, MD
  • Langon, France, 33210
    • Not yet recruiting
    • Sud-Gironde Hospital
    • Contact: Philippe Cormier, MD; Email: Philippe.cormier@ch-sudgironde.fr
    • Principal Investigator: Philippe Cormier, MD
    • Sub-Investigator: Bernard Caumont, MD
    • Sub-Investigator: Dominique Gauthier, MD
    • Sub-Investigator: Thierry Dufoir, PharmD
  • Libourne, France
    • Not yet recruiting
    • Libourne Hospital
    • Contact: Caroline Fondrinier, PharmD; Email: Caroline.fondrinier@ch-libourne.fr
    • Principal Investigator: Caroline Fondrinier, PharmD
  • Sainte Foy la Grande, France, 33220
    • Not yet recruiting
    • Sainte Foy la Grande Hospital
    • Contact: Corinne Thé, PharmD; Email: Corinne.The@ch-sudgironde.fr
    • Principal Investigator: Corinne Thé, PharmD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Patients whose medical and administrative data are available in an electronic format in the hospital information system, Adult patients aged over 18.

Description

Inclusion Criteria:

• Patients whose medical and administrative data are available in an electronic format in the hospital information system
• Adult patients aged over 18;
• Patients hospitalized at the Bordeaux University Hospital or one of the hospital of the territorial organization ;
• Patients hospitalized between 01/01/2022 and 31/12/2024 ;

• Indicator 1: "antibiotic treatments of more than 7 days without justifications"

  • Patients with of a hospitalization of more than 24 hours;
  • Patients with urinary or respiratory infections on admission or during the hospitalization (including sepsis related to urinary or respiratory infection);
  • Patients with a prescription for at least one antibiotic, initiated on admission or during the hospitalization, for more than 7 days including the hospital prescription AND the discharge prescription

• Indicator 2: "surgical antibiotic prophylaxis lasting more than 24 hours"

  • Patients with surgery requiring an antibiotic prophylaxis
  • Patients having received antibiotic prophylaxis

Exclusion Criteria:

• Patients not hospitalized at the Bordeaux University Hospital or one of the hospital of the territorial organization.
• Patients whose medical and administrative data are not available in an electronic format in the hospital information system;
• Patients who have refused the secondary use of their data for research purpose

• Indicator 1: "Indicator of antibiotic treatments of more than 7 days without justifications"

  • Patients with another concomitant infectious pathology
  • Patient with pulmonary or urinary tuberculosis

• Indicator 2: "surgical antibiotic prophylaxis lasting more than 24 hours"

  • Patients without any surgery or with surgery for which antibiotic prophylaxis is not required
  • Patients without antibiotic prophylaxis

Study Plan

How is the study designed?

Design Details

• Observational Models: Other
• Time Perspectives: Retrospective

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Patient who received antibiotic prophylaxis; Patient who received antibiotic prophylaxis to assess appropriateness and consumption of treatment.	Other: Automatic tool to identify inappropriate antibiotic prescriptions; The system will identify inappropriate antibiotic prescriptions.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Sensitivity of the automatic tool to identify inappropriate antibiotic prescriptions compared to classical practices audits (gold standard).	Indicator "inappropriate treatment lasting more than 7 days": antibiotic treatment initiated or continued more than 7 days in clinical situations (urinary and respiratory infections) where a shorter treatment is recommended Indicator "surgical antibiotic prophylaxis lasting more than 24 hours": antibiotic given for a more than 24 hours for a surgical procedure requiring antibiotic prophylaxis The gold standard is the judgement of prescription appropriateness by infectious diseases experts. The gold standard will be measured independently from the automatic tool. Data will be manually extracted from patient electronic health record and assessed, independently, by two infectious diseases specialists to identify inappropriate prescriptions. In case of disagreement, an expert committee will be convened.	Between January 2021 and December 2024

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Metrological performances of each indicator	specificity , positive and negative predictive values to identify inappropriate prescriptions will be compared to gold standard (practices audits)	Between January 2021 and December 2023
Number of responses done by the system	The number and the content of responses: acknowledgment of inappropriateness or justification of the prescription The number of alerts without responses from the prescriber.	Between December 2022 and December 2024
Number of response with justification of the prescription	The number and the content of responses: acknowledgment of inappropriateness or justification of the prescription The number of alerts without responses from the prescriber.	Between December 2022 and December 2024
Number of alerts without responses from the prescriber	The number and the content of responses: acknowledgment of inappropriateness or justification of the prescription The number of alerts without responses from the prescriber.	Between December 2022 and December 2024
Evaluate the score with scale MAUQ_E	The usability of the tool will be assessed with the mHealth App Usability Questionnaire ( Zhou L, Bao J, Setiawan A, Saptono A, Parmanto B, (2019), "The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study", JMIR mHealth and uHealth, 7(4):e11500. DOI: 10.2196/11500. PMID: 30973342). This score evaluate the ease of use of Interface Items of Scale are from 1 to 7 : 1 - strongly disagree, 2 - disagree, 3 - somewhat disagree, 4 - neither , agree nor disagree, 5 - somewhat agree, 6 - agree, 7 - strongly agree.	Between June 2023 and December 2024
Evaluate the score with scale MAUQ_I	The usability of the tool will be assessed with the mHealth App Usability Questionnaire ( Zhou L, Bao J, Setiawan A, Saptono A, Parmanto B, (2019), "The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study", JMIR mHealth and uHealth, 7(4):e11500. DOI: 10.2196/11500. PMID: 30973342). This score evaluate the satisfaction use of Interface Items of Scale are from 1 to 7 : 1 - strongly disagree, 2 - disagree, 3 - somewhat disagree, 4 - neither , agree nor disagree, 5 - somewhat agree, 6 - agree, 7 - strongly agree.	Between June 2023 and December 2024
Evaluate the score with scale MAUQ_U	The usability of the tool will be assessed with the mHealth App Usability Questionnaire ( Zhou L, Bao J, Setiawan A, Saptono A, Parmanto B, (2019), "The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study", JMIR mHealth and uHealth, 7(4):e11500. DOI: 10.2196/11500. PMID: 30973342). This score evaluate the usefulness. Items of Scale are from 1 to 7 : 1 - strongly disagree, 2 - disagree, 3 - somewhat disagree, 4 - neither , agree nor disagree, 5 - somewhat agree, 6 - agree, 7 - strongly agree.	Between June 2023 and December 2024
Number of inappropriate antibiotic prescriptions	Changes in the proportion of inappropriate prescriptions will be assessed 4 months after implementation of the automatic tool and compared with the pre-implementation period	Between April 2023 and December 2024

Collaborators and Investigators

• Sponsor: University Hospital, Bordeaux
• Collaborators: University of Bordeaux
• Investigators: Principal Investigator: Frantz THIESSARD, MD, PhD, University Hospital, Bordeaux

Study record dates

Study Major Dates

• Study Start (Actual): January 2, 2021
• Primary Completion (Anticipated): December 31, 2024
• Study Completion (Anticipated): December 31, 2024

Study Registration Dates

• First Submitted: May 24, 2022
• First Submitted That Met QC Criteria: June 14, 2022
• First Posted (Actual): June 15, 2022

Study Record Updates

• Last Update Posted (Actual): June 15, 2022
• Last Update Submitted That Met QC Criteria: June 14, 2022
• Last Verified: April 1, 2022

More Information

Terms related to this study

• Keywords: Antibiotic; Relevance; Antibioprophylaxis; Indicators
• Additional Relevant MeSH Terms: Anti-Infective Agents; Anti-Bacterial Agents
• Other Study ID Numbers: CHUBX 2018/69

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