Enhanced, Personalized and Integrated Care for Infection Management at the Point-Of-Care

NCT ID: NCT04013737

Last Updated: 2021-08-31

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 33 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2017-02-28
• Study Completion Date: 2019-08-08

Brief Summary

Antimicrobials (drugs that kill or stop the growth of microorganisms including bacteria, thereby treating infections) commonly used to treat patients with infections are becoming less effective over time as bacteria develop resistance to them. Antimicrobial usage itself can lead to development and spread of antimicrobial resistance. Antimicrobial resistance is now a major threat to patient safety. To conserve the effectiveness of antimicrobials the investigator need to develop ways to use them more sensibly healthcare professionals who diagnose and treat infections must be able to access antimicrobial guidelines and test results at the patient bedside. This needs to be provided rapidly and with support to make sure that the decisions on prescribing antimicrobials are the best that can be made.

Detailed Description

Prototype software to achieve this has been developed through collaboration between healthcare professionals and biomedical engineers. This prototype software (run on a mobile device) retrieves patient results from various laboratory and clinical databases (securely within the Trust firewall) and displays this to the clinician making the prescribing decision. Furthermore a machine learning algorithm is applied to the data, and similar anonymised historical cases (and the antimicrobials prescribed and the clinical outcomes) are also displayed to the clinician to further inform their decision making. The prototype has been designed for use in intensive care, where the risk of infection is high, but through the research project detailed here, the software will be developed and validated across other areas of hospital patient care. Furthermore there is a key need to engage patients with how decisions are made around antimicrobial prescribing. The investigator propose to adapt the prototype to meet these needs. This system should improve patient safety and help preserve the effectiveness of existing antimicrobials

Conditions

Antibiotic Resistant Infection; Infection

Study Design

• Observational Model Type: OTHER
• Study Time Perspective: PROSPECTIVE

Study Groups

Patients and Public

Exploration of patient and public engagement with antibiotic decision making in secondary care. Prospective evaluation of a co-designed intervention to support enhanced knowledge and understanding of infections and their management.

EPIC IMPOC

Intervention Type: DEVICE

Clinical Decision Support System for antibiotic prescribing.

Prescribers

Quantitative evaluation of the impact of using a clinical decision support system to support antibiotic decision making.

EPIC IMPOC

Intervention Type: DEVICE

Clinical Decision Support System for antibiotic prescribing.

Interventions

EPIC IMPOC

Clinical Decision Support System for antibiotic prescribing.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

(i) healthcare professionals for evaluation phases: Have read the PIL and consent to participate in the study

(ii) patients for whom the clinician chooses to use the POC DSS as a resource when prescribing antimicrobials: Adult patients > 18 years old Being managed for infection outside of the critical care setting in Imperial College Healthcare NHS Trust Deemed appropriate for management with POC DSS by attending physician Prescribed antimicrobial agents outside of the critical care setting in last 5 days

(iii) Prescriber / healthcare professional for using POC DSS: Trained Healthcare Professional Working within wards under assessment Deemed suitable for recruitment by senior member of their team

Exclusion Criteria

(i) healthcare professionals: Do not wish to participate in the study Working across wards which is acting as a control ward Deemed no suitable for recruitment by a senior member of their team Non-permanent member of the Trust Information governance training not up-to-date

(ii) patients recruits Critical care patients Paediatric patients < 18 years old Deemed not suitable for management using POC DSS by attending physician On palliative care, end of life pathway Prisoners / young offenders in custody of HM Prison Service Involved in current research or have recently been involved in any research prior to recruitment (last 3 months)

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Imperial College London

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Alison Holmes

Role: PRINCIPAL_INVESTIGATOR

Professor

Locations

Imperial College London

London, , United Kingdom

Countries

United Kingdom

Provided Documents

Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

16HH3526

Identifier Type: -

Identifier Source: org_study_id