Patient Acceptance of Health CareDETECT-IP:NCT05923983
DETECT-IP: a Clinical Decision Support System and Intelligent Procedures to Counter Some Adverse Drug Events in Older Hospital Patients
A study testing Clinical decision support and Will not receive Clinical Decision Support in people with Patient Acceptance of Health Care and Acute Renal Failure, run by University Hospital, Lille at 1 site in France.
Trial 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). Read more about this study
- Who is it for?
- Ages 65 years and older
- Conditions the study is for
- Patient Acceptance of Health Care, Acute Renal Failure
- What is being tested?
- Clinical decision support and Will not receive Clinical Decision Support
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 783 participants
- Where
- 1 siteFrance
- Study dates
- 2 Oct 2023to 3 Oct 2024
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 65 years and older
- All sexes
- No healthy volunteers
- Older adult
Who may be able to join
- 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
Who cannot join
- 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 locations and contacts
1 site in 1 country.
About this study
Official 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.
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.
- Being tested
- Clinical decision support, Will not receive Clinical Decision Support
- Keywords
- Acute renal failure, hyperkaliemia, older people, computerized decision support system, stepped-wedge
- Medical subject headings
- Patient Acceptance of Health Care, Acute Kidney Injury
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Clinical decision supportOther
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 SupportOther
In the control group, the pharmaceutical validation will be based on routine care, often on entry to a ward or in a particular situation
| Study group | Role | What they receive |
|---|---|---|
| Intervention Group | Experimental | Not described Receives: Other: Clinical decision support |
| Control Group | Other | Not described Receives: Other: Will not receive Clinical Decision Support |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of adverse drug events such as acute renal failure and/or hyperkalemia in older hospitalized patients.
Measured: 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")
Measured: through study completion, an average of 20 days
Therapeutic adaptations implemented in case of acute renal failure (ARF) or hyperkalemia upon hospital admission
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
Measured: through study completion, an average of 15 days
Relevance of CDSS alerts
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
Measured: through study completion, an average of 20 days
Number of pharmaceutical interventions accepted
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
Measured: through study completion, an average of 20 days
Changes in ADEs (Adverse Drug Event) prevention/management work process induced by the introduction of alerts
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.
Measured: Through study completion, an average of 20 days
Cost-effectiveness of the pharmaceutical intervention
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
Measured: through study completion, an average of 20 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Jun 2023
- Study start2 Oct 2023
- Primary completion3 Oct 2024
- Study completion3 Oct 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Patient Acceptance of Health CareStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Sequential
- Model description
- Prospective, multicentre, controlled, single-blind, randomised cluster study with stepped-wedge permutations. The centres (hospitals) will be the clusters.
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 783 participants (actual)
Sponsor and investigators
- Lead sponsor
- University Hospital, Lille
- Sponsor type
- University, hospital or other
- Collaborators
- OméDIT (Observatory of Medicines, Medical Devices and Therapeutic Innovations, Regional Agency of Sante Nord Pas-de-Calais
- Responsible party
- Sponsor
- Investigators
- Jean-Bapstiste Beuscart, MD, Principal investigator, University Hospital, Lille
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05923983
- Sponsor's protocol ID
- 2019_1030
- Other IDs
- 2021-A03211-40, AAP PREPS 2019
- Acronym
- DETECT-IP:
- Status last verified
- Dec 2025
- First submitted
- 9 Feb 2023
- Last updated
- 26 Dec 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
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.
PubMed 39558377
Study at a glance
From the registry record, last updated by the sponsor on 26 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official 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.
- ClinicalTrials.gov ID
- NCT05923983
- Acronym / sponsor ID
- DETECT-IP: / 2019_1030
- Keywords
- Acute renal failure, hyperkaliemia, older people, computerized decision support system, stepped-wedge
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 783 participants (actual)
- Lead sponsor
- University Hospital, LilleUniversity, hospital or other
- Collaborators
- OméDIT (Observatory of Medicines, Medical Devices and Therapeutic Innovations, Regional Agency of Sante Nord Pas-de-Calais
- Study start
- 2 Oct 2023 (actual)
- Primary completion
- 3 Oct 2024 (actual)
- Study completion
- 3 Oct 2024 (actual)
- First posted
- 29 Jun 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Sequential
- Masking
- Single blind (participant)
- Number of arms
- 2
- Model description
- Prospective, multicentre, controlled, single-blind, randomised cluster study with stepped-wedge permutations. The centres (hospitals) will be the clusters.
| Arm | Type | Receives |
|---|---|---|
| Intervention Group | Experimental | Other: Clinical decision support |
| Control Group | Other | Other: Will not receive Clinical Decision Support |
Who may qualify
- Ages
- 65 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Older adult
Key inclusion criteria (3 listed)
- 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
Key exclusion criteria (4 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Clinical decision supportIn 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 | Other | Intervention Group |
| Will not receive Clinical Decision SupportIn the control group, the pharmaceutical validation will be based on routine care, often on entry to a ward or in a particular situation | Other | Control Group |
Primary outcome
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
6 secondary outcomes
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
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
Relevance of CDSS alerts
Time frame: through study completion, an average of 20 days
Number of pharmaceutical interventions accepted
Time frame: through study completion, an average of 20 days
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
Cost-effectiveness of the pharmaceutical intervention
Time frame: through study completion, an average of 20 days
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Dec 2025.
- Background: PubMed 39558377Payen 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Jean-Bapstiste Beuscart, MD principal investigator
University Hospital, Lille
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Clinical decision support and Will not receive Clinical Decision Support in people with Patient Acceptance of Health Care and Acute Renal Failure, run by University Hospital, Lille at 1 site in France.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 26 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05923983, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Dec 2025; AzTrials last refreshed its copy on 29 Oct 2026.