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

University Hospital, Lille

Status: Completed

Conditions: Patient Acceptance of Health Care; Acute Renal Failure

Treatments: Other: Will not receive Clinical Decision Support; Other: Clinical decision support

Study type: Interventional

Funder types: Other

Identifiers

NCT05923983

2021-A03211-40 (Other Identifier)

AAP PREPS 2019 (Other Identifier)

2019_1030

Details and patient eligibility

About

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.

Enrollment: 783 patients

Sex: All

Ages: 65+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• 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

Exclusion criteria

• 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

Trial design

Primary purpose: Health Services Research

Allocation: Randomized

Interventional model: Sequential Assignment

Masking: Single Blind

---

783 participants in 2 patient groups

Intervention Group

Experimental group

Treatment:

Other: Clinical decision support

Control Group

Other group

Treatment:

Other: Will not receive Clinical Decision Support