Developing Enhanced Prediction Models

Study Overview
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Brief Summary
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In this study, patients will be prospectively enrolled for data collection to design prediction models that integrate claims data (inpatient, outpatient, and pharmacy), electronic health record data (on clinical, social, and behavioral indicators), and patient-generated activity data. Patients will be randomized to use either a smartphone or a wearable activity tracking device to capture patient-generated health data.

Detailed Description
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Many hospital readmissions could be prevented if higher risk patients were identified and effective interventions then targeted towards these individuals. However, most existing claims-based predictive models perform poorly and do not provide timely and actionable information. In this study, researchers will prospectively enroll patients for data collection to design prediction models that integrate claims data (inpatient, outpatient, and pharmacy), electronic health record data (on clinical, social, and behavioral indicators), and use wearable devices or smartphones to collect patient-generated data (physical activity and sleep patterns). Patients will be randomized to use either a smartphone or a wearable activity tracking device to capture patient-generated health data.

Official Title
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Developing Enhanced Prediction Models to Identify Patients at Risk for Hospital Readmission by Collecting Patient-Generated Health Data

Conditions
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Acute Myocardial Infraction or Chest Pain, Chronic Obstructive Pulmonary Disease (COPD), Congestive Heart Failure (CHF), Diabetes, Pneumonia

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Be 18 years or older Be able to provide informed consent Be admitted to the Hospital of the University of Pennsylvania or Penn Presbyterian Medical Center Have a smartphone or tablet compatible with activity tracking devices Plan to be discharged to home Exclusion Criteria: Have no medical condition which prohibits them from ambulating or plan for any medical procedure over the next 6 months that would prohibit them from ambulating.

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Activity Monitoring - Smartphone<br>Patients in the activity monitoring - smartphone group will be randomly assigned to track their data using a smartphone app (which collects step counts) for 6 months. There will be no intervention for either group, both are being passively monitored. | |
| Activity Monitoring - Wearable<br>Patients in the activity monitoring - wearable device group will be randomly assigned to track their data using a wearable activity tracker (which collects step counts and sleep patterns/duration). There will be no intervention for either group, both are being passively monitored. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Hospital readmission within 30 days of discharge | Patient readmission within 30 days of initial discharge | 30 days | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The secondary outcome measures include re-hospitalization within 90 days of discharge. | Patient readmission within 90 days of initial discharge | 90 days | 
| Re-hospitalization within 6 months of discharge | Patient readmission within 6 months of initial discharge | 6 months | 
| Emergency department visits within 6 months of discharge | Patient visit to the emergency department within 6 months of initial discharge | 6 months | 
| Total health care cost utilization in 6 months after discharge | The cost of health care services for patient within 6 months of initial discharge | 6 months |