Wearable Activity Tracking to Curb Hospitalizations

This study is being done to collect patient generated health data to predict the risk of patients needing emergency department visits or hospitalization before, during. and after receiving radiation therapy.

PRIMARY OBJECTIVE:

1. Validate a previously developed step-count model for predicting all-cause acute care (pooled across all devices).

SECONDARY OBJECTIVES:

1. Validate a previously developed model for predicting each ED visits or hospitalizations during external beam RT using continuous step counts before, during, and after treatment.

II. Validate the previously developed step-count model for predicting all-cause acute care for each of the two different device platforms.

III. Validate concordance of step counts across each of the device's platforms in the Apple group.

IV. Validate the previously developed SHIELD-RT Electronic health record (EHR)-based model for predicting unplanned acute care (ED visit or hospitalization).

EXPLORATORY OBJECTIVES:

1. Refinement of the pre-existing models(step count and SHIELD-RT). II. Evaluate association between wearables collected parameters, EHR-based variables, and acute care events.

III. Develop and validate a multi-modal predictive model for predicting acute care.

OUTLINE: This is an observational study. Participants are assigned to 1 of 2 groups.

• GROUP I: Participants receive Fitbit device and undergo non-interventional, standard of care, radiation therapy.
• GROUP II: Participants receive Fitbit device and utilize their own personal Apple HealthKit-based device and undergo non-interventional, standard of care, radiation therapy.