Fig 2.

Case study—inpatient vs. outpatient models. The following case study presents the integration of mobile health (mHealth) data into the inpatient and outpatient settings. The initial steps for data collection and analytics are similar to those in Fig 1 for the proposed mHealth integration model. The summarized and processed data can be provided for different stakeholders in the clinical or community care team based on pre-specified use-case scenarios. For example, the inpatient setting will require short term monitoring of patient’s state by collecting data on physical activity (PA) to implement acute interventions for faster recovery and improvement [i.e., integrating early ambulation markers into early recovery after surgery (ERAS) protocols for improved outcomes]. The data are specified and analyzed based on the patient’s clinical status and PA needs. Once the patient is discharged, the outpatient provider can continue to monitor PA and health status of the patient through the integrated mHealth system. For prevention-oriented outpatient care (preventive cardiology, lifestyle medicine, and primary care clinics) the mHealth integration model follows the same initial flow. In this model, after the healthcare provider initiates PA assessment and counseling, a referral to the community care team (i.e., certified fitness professionals) is recommended. These teams deliver evidence-based interventions and work closely with each patient or small groups of patients based on their clinical needs and goals. However, the challenge is to track and analyze not only PA data but also behavioral change precursors that will lead to the adoption of improved PA and lifestyle and reduced CVD risk. The community care team is able to use mHealth data for increased engagement and real-time monitoring in order to implement clinician’s recommendations and relay summary behavior change outcome data as the clinician follows-up with the patient.