Clinical trial NCT06835153: Automatic Feedback Indicator to Enhance the Hospital Discharge Communication Between Acute Care and Primary Care.
Official title: Automatic Feedback Indicator to Enhance the Hospital Discharge Communication Between Acute Care and Primary Care: a Randomized Controlled Cluster Trial
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
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
Electronic Health Records (EHR)
Lead sponsor: University Hospital, Grenoble
Sponsor class: OTHER
First posted: 2025-02-19
Enrollment: 132000
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention 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.
Primary purpose: HEALTH_SERVICES_RESEARCH

Brief 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. 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.

Eligibility criteria: Inclusion Criteria:

* Patients hospitalized for at least 24 hours in participating services.
* Patients discharged alive directly from participating services.

Exclusion Criteria:

* 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).

Primary outcomes:
measure: Proportion of Discharge Letters Generated on the Day of Discharge
timeFrame: 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:
measure: Proportion of Discharge Letters Validated on the Day of Discharge
timeFrame: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
measure: Median Time to Generate Discharge Letters
timeFrame: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
measure: Median Time to Validate Discharge Letters
timeFrame: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
measure: Time from Patient Discharge to Electronic Submission of Discharge Letter to Primary Care Physicians
timeFrame: Measured monthly during the study period (January 2024 to February 2026), comparing the 12-month pre-implementation period to the 12-month intervention period.
measure: Patient Satisfaction with Discharge Process (e-Satis Survey)
timeFrame: Collected monthly during the 12-month intervention period (February 2025 to February 2026).
measure: Rate of Unplanned 30-Day Readmissions
timeFrame: Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.
Other outcomes:
measure: Completeness of Required Fields in Discharge Letters
timeFrame: Measured monthly during the 12-month intervention period (February 2025 to February 2026), comparing intervention and control groups.
measure: Documentation of Organizational Changes in Intervention Services
timeFrame: Ongoing during the 12-month intervention period (February 2025 to February 2026).
Locations:
city: Grenoble
country: France
facility: Centre hospitalier de Grenoble Alpes
Study officials:
affiliation: Grenoble Alps University, Faculty of Medicine.
name: Bastien Boussat, MD PhD
role: PRINCIPAL_INVESTIGATOR
References: