Automatic Feedback Indicator to Enhance the Hospital Discharge Communication Between Acute Care and Primary Care.

NCT ID: NCT06835153

Last Updated: 2025-02-19

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 132000 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2025-03-01
• Study Completion Date: 2026-02-01

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.

Conditions

Continuity of Care; Patient Safety; Hospital Discharge Communication Processes; Communication; Quality Indicators, Health Care; Electronic Health Records

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: HEALTH_SERVICES_RESEARCH
• Blinding Strategy: SINGLE

Study Groups

Intervention Group

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.

Group Type: EXPERIMENTAL

Monthly Performance Feedback with Dashboards (Automated Audit and Feedback)

Intervention Type: 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.

Control Group with Usual Care

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.

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

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.

Intervention Type: OTHER

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.

• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

University Hospital, Grenoble

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Bastien Boussat, MD PhD

Role: PRINCIPAL_INVESTIGATOR

Grenoble Alps University, Faculty of Medicine.

Locations

Centre hospitalier de Grenoble Alpes

Grenoble, , France

Countries

France

Central Contacts

Bastien Boussat, MD PhD

Role: CONTACT

bboussat@chu-grenoble.fr

334476767575

Facility Contacts

Cyrielle Vicier, PhD

Role: primary

cvicier@chu-grenoble.fr

+33476767900

Other Identifiers

PREPS-20-0195

Identifier Type: -

Identifier Source: org_study_id