Developing Enhanced Prediction Models

NCT ID: NCT02983812

Last Updated: 2020-02-06

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

500 participants

Study Classification

OBSERVATIONAL

Study Start Date

2017-01-23

Study Completion Date

2019-12-07

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.

Conditions

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

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Activity Monitoring - Smartphone

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.

No interventions assigned to this group

Activity Monitoring - Wearable

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.

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

1. Be 18 years or older
2. Be able to provide informed consent
3. Be admitted to the Hospital of the University of Pennsylvania or Penn Presbyterian Medical Center
4. Have a smartphone or tablet compatible with activity tracking devices
5. 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.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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University of Pennsylvania

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Mitesh Patel

Role: PRINCIPAL_INVESTIGATOR

University of Pennsylvania

Locations

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Penn Medicine

Philadelphia, Pennsylvania, United States

Site Status

Countries

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United States

References

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Patel MS, Polsky D, Kennedy EH, Small DS, Evans CN, Rareshide CAL, Volpp KG. Smartphones vs Wearable Devices for Remotely Monitoring Physical Activity After Hospital Discharge: A Secondary Analysis of a Randomized Clinical Trial. JAMA Netw Open. 2020 Feb 5;3(2):e1920677. doi: 10.1001/jamanetworkopen.2019.20677. No abstract available.

Reference Type DERIVED
PMID: 32031643 (View on PubMed)

Evans CN, Volpp KG, Polsky D, Small DS, Kennedy EH, Karpink K, Djaraher R, Mansi N, Rareshide CAL, Patel MS. Prediction using a randomized evaluation of data collection integrated through connected technologies (PREDICT): Design and rationale of a randomized trial of patients discharged from the hospital to home. Contemp Clin Trials. 2019 Aug;83:53-56. doi: 10.1016/j.cct.2019.06.018. Epub 2019 Jun 29.

Reference Type DERIVED
PMID: 31265915 (View on PubMed)

Other Identifiers

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825189

Identifier Type: -

Identifier Source: org_study_id

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