Automatic Feedback Indicator to Enhance the Hospital Discharge Communication Between Acute Care and Primary Care: a Randomized Controlled Cluster Trial
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 132,000
- 试验地点
- 1
- 主要终点
- Proportion of Discharge Letters Generated on the Day of Discharge
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Health Services Research
- 盲法
- Single (Outcomes Assessor)
盲法说明
The statistician in charge of the data analyses will be blinded to the allocation of hospital services to the intervention or control group to prevent bias in the statistical evaluation of outcomes. This includes the primary outcome (proportion of discharge letters validated on the day of discharge) and secondary outcomes.
Outcomes assessors and the statistician will work with anonymized datasets without group allocation information. However, participants (hospital services), care providers, and investigators managing the intervention are not masked due to the need to deliver feedback in real-time and monitor its implementation.
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients hospitalized for at least 24 hours in participating services.
- •Patients discharged alive directly from participating services.
排除标准
- •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).
研究组 & 干预措施
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.
干预措施: Monthly Performance Feedback with Dashboards (Automated Audit and Feedback) (Other)
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.
结局指标
主要结局
Proportion of Discharge Letters Generated on the Day of Discharge
时间窗: 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.
次要结局
- Median Time to Validate Discharge Letters(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(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)(Collected monthly during the 12-month intervention period (February 2025 to February 2026).)
- Rate of Unplanned 30-Day Readmissions(Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.)
- Proportion of Discharge Letters Validated on the Day of Discharge(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(Measured monthly over the study period (January 2024 to February 2026), comparing a 12-month pre-implementation period to a 12-month intervention period.)