Continuity of CareFIAQLSNCT06835153
Automatic Feedback Indicator to Enhance the Hospital Discharge Communication Between Acute Care and Primary Care.
A study testing Monthly Performance Feedback with Dashboards (Automated Audit and Feedback) in people with Continuity of Care and Patient Safety, run by University Hospital, Grenoble at 1 site in France.
Trial summary
This study, titled "Automated Indicator Feedback for Improving the Quality of Discharge Letters: A Cluster-Randomized Controlled Trial" (FIAQ-LS), aims to evaluate whether continuous real-time feedback to hospital teams can improve the quality of discharge letters. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Continuity of Care, Patient Safety, Hospital Discharge Communication Processes
- What is being tested?
- Monthly Performance Feedback with Dashboards (Automated Audit and Feedback)
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 132,000 participants
- Where
- 1 siteFrance
- Study dates
- 1 Mar 2025to 1 Feb 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Who may be able to join
- Patients hospitalized for at least 24 hours in participating services.
- Patients discharged alive directly from participating services.
Who cannot join
- Patients hospitalized for less than 24 hours.
- Patients who died during hospitalization.
- Stays in services not meeting inclusion criteria (e.g., psychiatry, long-term care, emergency services with rare direct discharges, or critical care units).
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
France1 site
Centre hospitalier de Grenoble Alpes
Grenoble, 38000
Cyrielle Vicier, PhD, +33476767900, cvicier@chu-grenoble.fr
About this study
Official title: Automatic Feedback Indicator to Enhance the Hospital Discharge Communication Between Acute Care and Primary Care: a Randomized Controlled Cluster Trial
This study, titled "Automated Indicator Feedback for Improving the Quality of Discharge Letters: A Cluster-Randomized Controlled Trial" (FIAQ-LS), aims to evaluate whether continuous real-time feedback to hospital teams can improve the quality of discharge letters. Discharge letters are critical for ensuring continuity of care and reducing adverse events by providing detailed information about a patient's hospital stay to both the patient and their primary care physician.
The study will be conducted at Grenoble Alpes University Hospital and involve 40 hospital services across three campuses. The trial design includes two parallel arms: an intervention group receiving monthly performance feedback through automated dashboards and a control group with no additional intervention. Services are randomized into these groups using a stratified cluster approach.
Read more
The primary objective is to assess whether this intervention increases the proportion of discharge letters validated on the day of discharge compared to usual care. Secondary objectives include evaluating patient satisfaction, rates of unplanned 30-day readmissions, and completeness of discharge letter content.
The study will include data from approximately 132,000 patient stays over two phases: a pre-implementation observational period (12 months) and an intervention phase (12 months). All data will be collected and analyzed anonymously, with findings expected to inform the broader implementation of quality improvement strategies in French hospitals.
Read the detailed description
Detailed Description Effective communication at hospital discharge is vital for continuity of care and patient safety. Discharge letters summarize the hospital stay, outlining diagnoses, treatments, and follow-up care. Despite national guidelines mandating that discharge letters be validated and provided to patients on the day of discharge, compliance remains suboptimal in France, with average performance scores well below targets.
This study seeks to address this gap through an automated feedback mechanism. Using the hospital's electronic health record (EHR) system, the study will generate monthly dashboards for each participating service in the intervention group. These dashboards will provide a real-time view of performance metrics, including the proportion of discharge letters validated on the day of discharge and the completeness of required content fields.
The trial employs a cluster-randomized controlled design with 40 hospital services as the unit of randomization. Services are stratified by activity type (medicine, surgery/obstetrics) and baseline performance. The study is divided into two phases:
Pre-implementation Phase (January 2024 - January 2025): A 12-month observational period to collect baseline data and stratify services for randomization.
Implementation Phase (February 2025 - February 2026): Intervention services receive monthly performance feedback, while control services continue with standard care practices.
The primary endpoint is the proportion of hospital stays where discharge letters are validated on the day of discharge. Secondary outcomes include:
Patient satisfaction, measured through the national "e-Satis" survey. Rates of unplanned readmissions within 30 days of discharge. Completeness of discharge letters, evaluated across mandated content fields (e.g., patient identification, discharge summary, follow-up plan).
This study will enroll all eligible patient stays within the 40 participating services, excluding stays of less than 24 hours or cases where the patient died during hospitalization. The anticipated sample size is 132,000 stays.
Data collection will rely on routine administrative data from the EHR system, anonymized at the patient level. Statistical analyses will adopt a "difference-in-differences" approach, comparing changes in outcomes between the intervention and control groups over time. A mixed-effects logistic regression model will account for intra-cluster correlations.
The results of this study aim to demonstrate the effectiveness of automated feedback in driving quality improvements in hospital discharge processes. If successful, the approach could be scaled across other hospitals in France, contributing to better continuity of care and patient outcomes.
- Conditions
- Continuity of Care, Patient Safety, Hospital Discharge Communication Processes, Communication, Quality Indicators, Health Care, Electronic Health Records
- Being tested
- Monthly Performance Feedback with Dashboards (Automated Audit and Feedback)
- Keywords
- Discharge Summary, Patient Handover, Quality Improvement, Cluster Randomized Trial, Healthcare Outcomes, Patient Satisfaction, Quality Indicators, Real-Time Feedback, Electronic Health Records (EHR)
- Medical subject headings
- Communication, Patient Satisfaction
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Monthly Performance Feedback with Dashboards (Automated Audit and Feedback)Other
Hospital services in the intervention group will receive monthly automated dashboards that provide detailed performance metrics. These include:
The proportion of patients with a discharge letter generated on the day of discharge, The proportion of discharge letters validated on the day of discharge, Median delays for generating discharge letters, Median delays for validating discharge letters. The dashboards are shared with all physicians, nurse managers, and secretarial staff in each service. A designated quality improvement officer is available to assist teams in interpreting the data and implementing organizational changes based on the feedback. The intervention uses real-time data extraction from the hospital's electronic health record system to generate these insights.
| Study group | Role | What they receive |
|---|---|---|
| Intervention Group | Experimental | Hospital services in this group will receive monthly performance feedback through automated dashboards, provided electronically to the entire service team, including all physicians, nurse managers, and secretarial staff. These dashboards will display data on the proportion of discharge letters validated on the day of discharge and the completeness of required content fields. The intervention also includes support from a designated quality improvement officer, who will assist teams in implementing organizational changes as needed to improve performance. Receives: Other: Monthly Performance Feedback with Dashboards (Automated Audit and Feedback) |
| Control Group with Usual Care | No intervention | Hospital services in this group will continue with usual care practices and may access routine support from institutional departments, such as quality management and IT services, upon request. However, no automated feedback on discharge letter performance will be provided or proposed. This setup ensures the control group reflects the typical resources and support available in standard practice. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Proportion of Discharge Letters Generated on the Day of Discharge
The proportion of hospital stays where discharge letters are generated electronically on the same day as the patient's discharge. This measure evaluates the timeliness of generating discharge communication, a critical factor for continuity of care and patient engagement. Data will be extracted from the hospital's electronic health record system (EHR) and aggregated at the service level for analysis.
Measured: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
Secondary outcomes (6)
Proportion of Discharge Letters Validated on the Day of Discharge
The proportion of hospital stays where discharge letters are validated electronically on the day of discharge. This measure assesses the quality and timeliness of the validation process, ensuring that discharge letters are ready for patient handover and communication with primary care providers. Data will be extracted from the hospital's electronic health record system and analyzed at the service level.
Measured: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
Median Time to Generate Discharge Letters
The median time (in hours) from the patient's discharge to the generation of the discharge letter. This measure evaluates process efficiency and timeliness, critical for improving discharge workflows and patient communication. Data will be extracted from the hospital's electronic health record system.
Measured: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
Median Time to Validate Discharge Letters
The median time (in hours) from the generation of a discharge letter to its validation. This outcome assesses the efficiency of the validation process, a key step in finalizing discharge communication for patients and primary care providers.
Measured: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
Time from Patient Discharge to Electronic Submission of Discharge Letter to Primary Care Physicians
The median time (in days) from the patient's discharge to the electronic transmission of the discharge letter to the external primary care physician (e.g., general practitioner). This outcome assesses the timeliness of communication between hospital services and external care providers, a key factor in ensuring continuity of care after hospitalization.
Measured: Measured monthly during the study period (January 2024 to February 2026), comparing the 12-month pre-implementation period to the 12-month intervention period.
Patient Satisfaction with Discharge Process (e-Satis Survey)
Scores from the national e-Satis survey evaluating patient satisfaction with their hospital discharge process. Aggregate scores and specific sub-scores for "organization of discharge" and "interaction with physicians" will be compared between intervention and control groups.
Measured: Collected monthly during the 12-month intervention period (February 2025 to February 2026).
Rate of Unplanned 30-Day Readmissions
The proportion of hospital stays followed by unplanned readmissions within 30 days of discharge, measured via emergency admissions. This measure evaluates the impact of improved discharge communication on post-hospitalization outcomes.
Measured: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Feb 2025
- Study start1 Mar 2025 (estimated)
- Primary completion1 Feb 2026 (estimated)
- Study completion1 Feb 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Continuity of 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
- Parallel groups
- Model description
- This study is a cluster-randomized controlled trial with two parallel arms. The unit of randomization is the hospital service, with 40 services participating across three campuses of Grenoble Alpes University Hospital. Services are stratified by activity type (medicine vs. surgery/obstetrics) and baseline performance on the primary outcome. The intervention arm will receive monthly feedback via automated performance dashboards, highlighting the proportion of discharge letters validated on the day of discharge and the completeness of required content fields. The control arm will not receive any feedback but will continue routine care practices. Outcomes will be assessed over two phases: a 12-month pre-implementation observational phase and a 12-month intervention phase. The analysis uses a "difference-in-differences" approach to compare changes in outcomes between the two groups, accounting for intra-cluster correlations using mixed-effects logistic regression models.
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 132,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Hospital, Grenoble
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Bastien Boussat, MD PhD, Principal investigator, Grenoble Alps University, Faculty of Medicine.
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06835153
- Sponsor's protocol ID
- PREPS-20-0195
- Acronym
- FIAQLS
- Status last verified
- Feb 2025
- First submitted
- 13 Jan 2025
- Last updated
- 19 Feb 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: The study plans to share de-identified individual participant data (IPD) with other researchers upon request, after the publication of primary results. The shared data will include: Anonymized patient-level data for all outcomes (e.g., discharge letter generation and validation times, patient satisfaction scores, readmission rates). Aggregated service-level performance data. Access to IPD will be granted under a data-sharing agreement to ensure proper use and compliance with ethical guidelines. Requests for data must be submitted to the corresponding investigator and approved by the study's oversight committee.
Study at a glance
From the registry record, last updated by the sponsor on 19 Feb 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Automatic Feedback Indicator to Enhance the Hospital Discharge Communication Between Acute Care and Primary Care: a Randomized Controlled Cluster Trial
- ClinicalTrials.gov ID
- NCT06835153
- Acronym / sponsor ID
- FIAQLS / PREPS-20-0195
- Conditions
- Continuity of Care, Patient Safety, Hospital Discharge Communication Processes, Communication, Quality Indicators, Health Care, Electronic Health Records
- Keywords
- Discharge Summary, Patient Handover, Quality Improvement, Cluster Randomized Trial, Healthcare Outcomes, Patient Satisfaction, Quality Indicators, Real-Time Feedback
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 132,000 participants (estimated)
- Lead sponsor
- University Hospital, GrenobleUniversity, hospital or other
- Study start
- 1 Mar 2025 (estimated)
- Primary completion
- 1 Feb 2026 (estimated)
- Study completion
- 1 Feb 2026 (estimated)
- First posted
- 19 Feb 2025 (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.
This study, titled "Automated Indicator Feedback for Improving the Quality of Discharge Letters: A Cluster-Randomized Controlled Trial" (FIAQ-LS), aims to evaluate whether continuous real-time feedback to hospital teams can improve the quality of discharge letters. Discharge letters are critical for ensuring continuity of care and reducing adverse events by providing detailed information about a patient's hospital stay to both the patient and their primary care physician.
The study will be conducted at Grenoble Alpes University Hospital and involve 40 hospital services across three campuses. The trial design includes two parallel arms: an intervention group receiving monthly performance feedback through automated dashboards and a control group with no additional intervention. Services are randomized into these groups using a stratified cluster approach.
The primary objective is to assess whether this intervention increases the proportion of discharge letters validated on the day of discharge compared to usual care. Secondary objectives include evaluating patient satisfaction, rates of unplanned 30-day readmissions, and completeness of discharge letter content.
The study will include data from approximately 132,000 patient stays over two phases: a pre-implementation observational period (12 months) and an intervention phase (12 months). All data will be collected and analyzed anonymously, with findings expected to inform the broader implementation of quality improvement strategies in French hospitals.
Detailed description
Detailed Description Effective communication at hospital discharge is vital for continuity of care and patient safety. Discharge letters summarize the hospital stay, outlining diagnoses, treatments, and follow-up care. Despite national guidelines mandating that discharge letters be validated and provided to patients on the day of discharge, compliance remains suboptimal in France, with average performance scores well below targets.
This study seeks to address this gap through an automated feedback mechanism. Using the hospital's electronic health record (EHR) system, the study will generate monthly dashboards for each participating service in the intervention group. These dashboards will provide a real-time view of performance metrics, including the proportion of discharge letters validated on the day of discharge and the completeness of required content fields.
The trial employs a cluster-randomized controlled design with 40 hospital services as the unit of randomization. Services are stratified by activity type (medicine, surgery/obstetrics) and baseline performance. The study is divided into two phases:
Pre-implementation Phase (January 2024 - January 2025): A 12-month observational period to collect baseline data and stratify services for randomization.
Implementation Phase (February 2025 - February 2026): Intervention services receive monthly performance feedback, while control services continue with standard care practices.
The primary endpoint is the proportion of hospital stays where discharge letters are validated on the day of discharge. Secondary outcomes include:
Patient satisfaction, measured through the national "e-Satis" survey. Rates of unplanned readmissions within 30 days of discharge. Completeness of discharge letters, evaluated across mandated content fields (e.g., patient identification, discharge summary, follow-up plan).
This study will enroll all eligible patient stays within the 40 participating services, excluding stays of less than 24 hours or cases where the patient died during hospitalization. The anticipated sample size is 132,000 stays.
Data collection will rely on routine administrative data from the EHR system, anonymized at the patient level. Statistical analyses will adopt a "difference-in-differences" approach, comparing changes in outcomes between the intervention and control groups over time. A mixed-effects logistic regression model will account for intra-cluster correlations.
The results of this study aim to demonstrate the effectiveness of automated feedback in driving quality improvements in hospital discharge processes. If successful, the approach could be scaled across other hospitals in France, contributing to better continuity of care and patient outcomes.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- Model description
- This study is a cluster-randomized controlled trial with two parallel arms. The unit of randomization is the hospital service, with 40 services participating across three campuses of Grenoble Alpes University Hospital. Services are stratified by activity type (medicine vs. surgery/obstetrics) and baseline performance on the primary outcome. The intervention arm will receive monthly feedback via automated performance dashboards, highlighting the proportion of discharge letters validated on the day of discharge and the completeness of required content fields. The control arm will not receive any feedback but will continue routine care practices. Outcomes will be assessed over two phases: a 12-month pre-implementation observational phase and a 12-month intervention phase. The analysis uses a "difference-in-differences" approach to compare changes in outcomes between the two groups, accounting for intra-cluster correlations using mixed-effects logistic regression models.
| Arm | Type | Receives |
|---|---|---|
| Intervention Group | Experimental | Other: Monthly Performance Feedback with Dashboards (Automated Audit and Feedback)Hospital services in this group will receive monthly performance feedback through automated dashboards, provided electronically to the entire service team, including all physicians, nurse managers, and secretarial staff. These dashboards will display data on the proportion of discharge letters validated on the day of discharge and the completeness of required content fields. The intervention also includes support from a designated quality improvement officer, who will assist teams in implementing organizational changes as needed to improve performance. |
| Control Group with Usual Care | No intervention | –Hospital services in this group will continue with usual care practices and may access routine support from institutional departments, such as quality management and IT services, upon request. However, no automated feedback on discharge letter performance will be provided or proposed. This setup ensures the control group reflects the typical resources and support available in standard practice. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (2 listed)
- Patients hospitalized for at least 24 hours in participating services.
- Patients discharged alive directly from participating services.
Key exclusion criteria (3 listed)
- Patients hospitalized for less than 24 hours.
- Patients who died during hospitalization.
- Stays in services not meeting inclusion criteria (e.g., psychiatry, long-term care, emergency services with rare direct discharges, or critical care units).
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 |
|---|---|---|
| Monthly Performance Feedback with Dashboards (Automated Audit and Feedback)Hospital services in the intervention group will receive monthly automated dashboards that provide detailed performance metrics. These include: The proportion of patients with a discharge letter generated on the day of discharge, The proportion of discharge letters validated on the day of discharge, Median delays for generating discharge letters, Median delays for validating discharge letters. The dashboards are shared with all physicians, nurse managers, and secretarial staff in each service. A designated quality improvement officer is available to assist teams in interpreting the data and implementing organizational changes based on the feedback. The intervention uses real-time data extraction from the hospital's electronic health record system to generate these insights. | Other | Intervention Group |
Primary outcome
Proportion of Discharge Letters Generated on the Day of Discharge
Time frame: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
The proportion of hospital stays where discharge letters are generated electronically on the same day as the patient's discharge. This measure evaluates the timeliness of generating discharge communication, a critical factor for continuity of care and patient engagement. Data will be extracted from the hospital's electronic health record system (EHR) and aggregated at the service level for analysis.
6 secondary outcomes
Proportion of Discharge Letters Validated on the Day of Discharge
Time frame: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
Median Time to Generate Discharge Letters
Time frame: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
Median Time to Validate Discharge Letters
Time frame: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
Time from Patient Discharge to Electronic Submission of Discharge Letter to Primary Care Physicians
Time frame: Measured monthly during the study period (January 2024 to February 2026), comparing the 12-month pre-implementation period to the 12-month intervention period.
Patient Satisfaction with Discharge Process (e-Satis Survey)
Time frame: Collected monthly during the 12-month intervention period (February 2025 to February 2026).
Rate of Unplanned 30-Day Readmissions
Time frame: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Feb 2025.
- Individual participant dataSharing planned: Yes. The study plans to share de-identified individual participant data (IPD) with other researchers upon request, after the publication of primary results. The shared data will include: Anonymized patient-level data for all outcomes (e.g., discharge letter generation and validation times, patient satisfaction scores, readmission rates). Aggregated service-level performance data. Access to IPD will be granted under a data-sharing agreement to ensure proper use and compliance with ethical guidelines. Requests for data must be submitted to the corresponding investigator and approved by the study's oversight committee.
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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.
Bastien Boussat, MD PhD principal investigator
Grenoble Alps University, Faculty of Medicine.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Monthly Performance Feedback with Dashboards (Automated Audit and Feedback) in people with Continuity of Care and Patient Safety, run by University Hospital, Grenoble 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 2 inclusion and 3 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: opening soon, as of the sponsor's last update on 19 Feb 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Bastien Boussat, MD PhD (334476767575, bboussat@chu-grenoble.fr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Proportion of Discharge Letters Generated on the Day of Discharge (time frame: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 19 Feb 2025.