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Completed

NCT Number: NCT05923983

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

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.

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Key information

Conditions

Patient Acceptance of Health Care Acute Kidney Injury Acute Renal Failure Behavior Female Urogenital Diseases Female Urogenital Diseases and Pregnancy Complications Health Behavior Kidney Diseases Male Urogenital Diseases Renal Insufficiency Treatment Adherence and Compliance Urogenital Diseases Urologic Diseases

Age range

65 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Institut Cœur-Poumon - Médecine aiguë gériatrique

Lille, France

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

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

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

Primary outcomes

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

    Time frame: through study completion, an average of 20 days

Secondary outcomes

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

    Time frame: through study completion, an average of 20 days

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

    Time frame: through study completion, an average of 15 days

    Therapeutic changes within 72 hours of a CDSS alert for acute renal failure or hyperkalemia. Therapeutic changes include discontinuation of drug therapy, introduction of a new drug, dose reduction or change of drug

  3. Relevance of CDSS alerts

    Time frame: through study completion, an average of 20 days

    Relevance of CDSS alerts is defined in a standard way. Each CDSS alert is evaluated by a clinical pharmacist according to their own expertise and data available in the EHR. If the alert was deemed not relevant, the clinical pharmacist did not perform any pharmaceutical intervention. The CDSS software register the classification of the alert as "not relevant". This approach was used the last 4 years in our hospital and as been published in an article published in the International Journal of Medical Informatics: Cuvelier E, Robert L, Musy E, Rousselière C, Marcilly R, Gautier S, Odou P, Beuscart JB, Décaudin B. The clinical pharmacist's role in enhancing the relevance of a clinical decision support system. Int J Med Inform. 2021 Nov;155:104568. doi: 10.1016/j.ijmedinf.2021.104568. Epub 2021 Sep 2. PMID: 34537687

  4. Number of pharmaceutical interventions accepted

    Time frame: through study completion, an average of 20 days

    When an alert is received by the pharmacist, it is analyzed and the pharmacist forwards a pharmaceutical intervention to the physician in charge of the patient to propose a modification of the treatment (dosage, dose, stop

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

    Time frame: Through study completion, an average of 20 days

    Changes in the work system are identified through a comparison of its elements (tools, tasks, organization, interactions, work environment, professionals), before and after the introduction of alerts, using qualitative system engineering methods.

  6. Cost-effectiveness of the pharmaceutical intervention

    Time frame: through study completion, an average of 20 days

    Use medico-economic data such as time spent treating an alert, cost of treating an adverse drug reaction to estimate the cost-effectiveness of the intervention

Sponsors and collaborators

Lead sponsor

University Hospital, Lille

Other

Collaborators

  • OméDIT (Observatory of Medicines, Medical Devices and Therapeutic Innovations
  • Regional Agency of Sante Nord Pas-de-Calais

Registry information

Official study title

Reduction of Acute Renal Failure and/or Hyperkaliemia Adverse Drug Events in Older Inpatients by Incorporating Specific Rules Into a Computerized Support System and Dedicated Procedures: a Randomized Trial.

Acronym: DETECT-IP:

Important dates

Study start
2023
Primary completion
2024
Study completion
2024
First posted
Jun 29, 2023
Registry last updated
Dec 26, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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