Technology-enabled Platform for Proactive Regular Senior-Centric Health Assessments

About the project

Caregivers were asked to train on, and use technology - a mobile app, called PITCH to proactively monitor seniors’ health, during routine care, for risk factors that could predict hospitalizations or other negative health outcomes. Seniors completed regular health assessments with their caregiver. Caregivers entered the results into the app, for analysis. The assessments could involve physical health (like weight and blood pressure) and cognitive/mental health (like word recall and quality of life). All equipment was provided in a kit that was stored in the senior’s home. 

Goals included:

  • Train the caregivers on, and to use the mobile app, PITCH, and evaluate the feasibility of caregiver-driven home health assessments.
  • Train caregivers to administer health assessments with provided home kits and determine if changes are significant for health.
  • Identify and understand the factors that may predict changes in a senior’s ability to stay at home.

Conclusions and lessons learned

At the end of this study, not enough data was gathered to determine the impacts on participants’ health. Additionally, assessments were not passed on to care providers, so their usefulness in assessing health changes was not determined.

  • Caregivers can be trained on, and to use the app.
  • The app and the assessments were accepted and appreciated by both caregivers and client participants.
  • It is believed that the app could be used to predict health changes before a possible negative health event occurs.

Recommendations

  • All caregivers could be upskilled to give assessments using this app and monitor their clients on a regular basis.
  • Routine health assessments should become a standard for in-home care to detect trends in individual senior’s health, this could lead to earlier interventions.
  • A larger research project should be completed to include a larger sample size and allow for more data collection, analysis, and the development of a statistical, predictive model to predict future adverse health events.
  • With further research and a sustainability/scale plan (with adaptations), this model could be used for other cohorts in the future, such as those who have had a stroke, spinal cord injury, other mobility-related disadvantages, those recovering from surgery.

To learn more read the complete project findings (PDF 165 KB)

Knowledge transfer