Capturing and Making Use of Consumer Generated Data: A Strategy for Population Health Management

Presented at Askesis’ 13th Annual User Conference by Ellen Beckjord, PhD, MPH Director, Population Health Program Design and Engagement Optimization-UPMC Health Plan

HealthIT.gov defines patient generated health data (PGHD) as health related data created, recorded or gathered by or from patients, including family members or caregivers, to help address a health concern.  PGHD is different from data collected through clinical encounters, since patients are the source of the collection and the recording of the data. Patients are also in control of how, when and to whom the data is distributed.

PGHD is important because it can be used in conjunction with information gathered in more traditional settings to fill in the gaps between services, which help to generate a more complete picture of a patient’s health.  More specifically, this data can:

  • Be captured between visits and on a continuous basis
  • Help to provide information to better address prevention and chronic care management
  • Be used to improve quality and coordination of care, cost savings, and patient safety

Dr. Beckjord made clear that consumer generated data (CGD) is not new, but current technology has improved our ability to capture and utilize it.  She pointed out that the shift from volume based to value based health care is bringing increased attention to CGD. 

CGD is collected in many ways including claims data, internet searches, wearable devices, smartphones, social media activity, and purchased data.  Dr. Beckjord cited various studies indicating that the majority of consumers have smartphones, many with health apps, and most consumers were very or somewhat willing to share vitals, behavioral information and/or symptoms with their healthcare provider. 

The following two examples of CGD usage were cited:

  1. A Depression study where mobile phones were used to collect data to indicate when experiencing symptoms of depression and predict when interventions were needed to help improve mood. 
  • Mobilyze!, a context-aware mobile intervention was paired with a website for participants
  • Based on the data, the technology was able to predict location and mood accurately close to 60% of the time
  1. Schizophrenia – create a platform to collect smartphone raw sensor and usage data with the goal to develop a methodology to extract biomedical and clinical insights.
  • Could the presence of paranoia be detected by altered patterns of movement?
  • Could call logs be used to indicate decreased social activity?
  • Could Bluetooth be used to determine the presence of other individuals?
  • Can voice data be used to infer a change in symptoms?

The incorporation of CGD is being proposed as a requirement for reimbursement in the new MACRA program, which focuses on value based care and shared risk for providers.  Dr. Beckjord indicated there are many challenges that need to be addressed:  strategic, technologic and ethical, as well as consumer privacy and security.  However, if successful, CGD could be a method for providing the right care, at the right time, in the right way, to the right consumer.