MEDBRIDGE: AI-Driven Risk Stratification and Care Transition Intervention to Improve Diabetes Medication Management
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 45
- 试验地点
- 2
研究概览
简要总结
This study tests whether a support program led by a nurse case manager and community health worker can help patients with type 2 diabetes manage their medications after leaving the hospital. Many patients with diabetes take multiple medications, and changes to these medications during hospital stays can cause confusion and lead to missed doses or incorrect use. This is especially common in communities with limited access to healthcare.
The study uses a computer-based tool called MEDBRIDGE (MEDication BRIDGE) to identify patients who may be at higher risk for problems after discharge, such as worsening blood sugar control or return visits to the emergency department. Patients identified as high-risk will receive 3 months of support from a nurse case manager and community health worker team, who will help with medication questions, coordinate with their doctor, and provide follow-up check-ins.
The main goal is to find out whether this type of support program is practical to deliver and acceptable to patients. The study will also track changes in blood sugar levels and emergency department visits. Forty-five patients will be enrolled over 6 months at the University of Alabama at Birmingham and Cooper Green Mercy Health Services in Jefferson County, Alabama.
详细描述
This single-arm feasibility pilot evaluates a MEDBRIDGE-guided nurse case manager (NCM) and community health worker (CHW) post-discharge support intervention for high-risk patients with type 2 diabetes (T2D). MEDBRIDGE is an AI-driven risk stratification tool that integrates medication data, clinical factors, and social determinants of health from electronic health records to identify patients at elevated risk of HbA1c elevation, diabetes-related emergency department visits, and hospitalizations within 3 months post-discharge.
The intervention follows a four-phase workflow: (1) Risk Assessment, where the NCM reviews the daily MEDBRIDGE-generated high-risk patient list; (2) Initial Patient Contact, where the NCM/CHW team initiates contact after discharge to review medications and identify discrepancies; (3) Ongoing Support, where the CHW provides monthly check-ins to monitor adherence, address barriers, and coordinate with primary care providers; and (4) Transition to Routine Care, where the team facilitates handoff to the patient's primary care provider with a summary of activities and recommendations.
Primary outcomes include feasibility (recruitment rate, retention rate), patient acceptability (Acceptability of Intervention Measure), and intervention fidelity (NCM/CHW contact log adherence). Secondary outcomes include HbA1c change, diabetes-related emergency department visits, and diabetes-related hospitalizations within 3 months post-discharge, analyzed descriptively and compared with non-intervention high-risk patients identified by MEDBRIDGE.
The study is conducted at the University of Alabama at Birmingham (UAB) Hospital and Cooper Green Mercy Health Services, a county-owned safety-net facility serving predominantly low-income and uninsured residents of Jefferson County, Alabama. The patient population is characterized by higher rates of medication complexity, limited health literacy, and social vulnerability. Approximately 20 UAB hospitalizations involve Cooper Green patients with T2D each month, providing a sufficient recruitment base for the target enrollment of 45 patients over a 6-month recruitment window.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Treatment
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Adults aged 18 years or older
- •Diagnosis of type 2 diabetes (HbA1c of 6.5% or higher or relevant ICD-10 codes including E11, E13, E14, R73, L97.509, K31.84)
- •Discharged from UAB Hospital or its emergency departments
- •Receiving primary care at Cooper Green Mercy Health Services or UAB Post Discharge Clinic
- •Identified as high risk by the MEDBRIDGE prediction tool based on elevated risk of HbA1c elevation, diabetes-related emergency department visits, or diabetes-related hospitalizations within 3 months post-discharge
排除标准
- •Under age 18
- •No indication of type 2 diabetes
- •Not affiliated with Cooper Green Mercy Health Services or UAB Post Discharge Clinic for primary care
- •Unable to provide informed consent
- •Currently enrolled in another post-discharge intervention study
研究者
Seung-Yup Lee
Assistant Professor
University of Alabama at Birmingham