DETECT-IP: a Clinical Decision Support System and Intelligent Procedures to Counter Some Adverse Drug Events in Older Hospital Patients

NCT05923983 | Completed

• 3 other identifiers: 2019_10302021-A03211-40AAP PREPS 2019
• Study Type: interventional
• Target: 783
• Locations: 1 country
• Sites: 1

Brief Summary

Current evidence shows that computerized decision support systems (CDSS) have shown to be insufficiently effective to prevent adverse drug reactions (ADRs) at large scale (e.g. whole hospital). Several barriers for successful implementation of CDSS have been identified: over-alerting, lack of specificity of rules, and physician interruption during prescription. The effectiveness of CDSS could be increased in two ways. Firstly, by creating rules that are more specific to a given adverse drug reaction: the current study focuses on acute renal failure and hyperkalemia (two serious and frequent ADR in older hospitalized patients). Secondly, by involving the pharmacist in the review of the alerts so that he/she can transmit, if deemed necessary, a pharmaceutical recommendation to the clinician. This procedure will reduce over-alerting and prevent task interruption. The hypothesis is that the use of specific rules created by a multidisciplinary team and implemented in a CDSS, combined with a strategy for managing and transmitting alerts, can reduce specific ADRs such as hyperkalemia and acute renal failure.

Conditions

Patient Acceptance of Health Care; Acute Renal Failure

Keywords

Acute renal failure; hyperkaliemia; older people; computerized decision support system; stepped-wedge

Outcome Measures

Primary Outcomes (1)

• Number of adverse drug events such as acute renal failure and/or hyperkalemia in older hospitalized patients.

  through study completion, an average of 20 days

Secondary Outcomes (6)

• Presence of an adverse event related to the intervention provided ("change of prescription", "discontinuation of drug")

  through study completion, an average of 20 days

• Therapeutic adaptations implemented in case of acute renal failure (ARF) or hyperkalemia upon hospital admission

  through study completion, an average of 15 days

• Relevance of CDSS alerts

  through study completion, an average of 20 days

• Number of pharmaceutical interventions accepted

  through study completion, an average of 20 days

• Changes in ADEs (Adverse Drug Event) prevention/management work process induced by the introduction of alerts

  Through study completion, an average of 20 days

Study Arms (2)

Intervention Group

EXPERIMENTAL

Other: Clinical decision support

Control Group

OTHER

Other: Will not receive Clinical Decision Support

Interventions

Clinical decision support OTHER

In the intervention group, the pharmaceutical validation will be based on routine care, often on entry to a ward and by analysis of all the alerts produced by the CDSS. Some alerts will result in a pharmaceutical intervention being provided to the medical team

Intervention Group

Will not receive Clinical Decision Support OTHER

In the control group, the pharmaceutical validation will be based on routine care, often on entry to a ward or in a particular situation

Control Group

Eligibility Criteria

• Age: 65 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Older Adult (65+)

You may qualify if:

• Hospitalized for 3 days or more in an MCO (medicine surgery obstetrics) department participating in the study
• Patient who gave oral consent to participate in the study
• Socially insured patient

You may not qualify if:

• Patient discharged or died before D3 of hospitalization
• Patient in palliative care or end of life on entry to the service
• Person under legal protection (curatorship)
• Lack of coverage by the social security system, Failure to obtain oral consent to participate in the study

Sponsors & Collaborators

• University Hospital, Lille: lead
• OméDIT (Observatory of Medicines, Medical Devices and Therapeutic Innovations: collaborator
• Regional Agency of Sante Nord Pas-de-Calais: collaborator

Study Sites (1)

Institut Cœur-Poumon - Médecine aiguë gériatrique

Lille, France

Location

Related Publications (1)

• Payen A, Tlili NE, Cousein E, Ferret L, Le Bozec A, Lenglet A, Marcilly R, Pilven P, Potier A, Rousseliere C, Soula J, Robert L, Beuscart JB. Can the integration of new rules into a clinical decision support system reduce the incidence of acute kidney injury and hyperkalemia among hospitalized older adults: a protocol for a stepped-wedge, cluster-randomized trial (DETECT-IP). Trials. 2024 Nov 18;25(1):779. doi: 10.1186/s13063-024-08569-w.

  PMID: 39558377 BACKGROUND

MeSH Terms

Conditions

Patient Acceptance of Health Care; Acute Kidney Injury

Condition Hierarchy (Ancestors)

Treatment Adherence and Compliance; Health Behavior; Behavior; Renal Insufficiency; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases

Study Officials

• Jean-Bapstiste Beuscart, MD

  University Hospital, Lille

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: SEQUENTIAL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: Prospective, multicentre, controlled, single-blind, randomised cluster study with stepped-wedge permutations. The centres (hospitals) will be the clusters.

Study Record Dates

• First Submitted: February 9, 2023
• First Posted: June 29, 2023
• Study Start: October 2, 2023
• Primary Completion: October 3, 2024
• Study Completion: October 3, 2024
• Last Updated: December 26, 2025

Record last verified: 2025-12

Locations

FR (1)