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SENSI-STEPS:
USING PATIENT-GENERATED DATA TO PREVENT POST-STROKE FALLS

 

This project was completed as part of the American Medical Informatics Association (AMIA) Annual Symposium's Student Design Challenge in 2017. Our team proudly won second place. 
Team members: Angela Smith, Eleanor Burgess, Jennifer Pacheco, Noah Weingarten, Ada Ng

SUMMARY

We created an integrated suite of sensors and mobile applications that can administer a digital fall-risk assessment and track the user's score over time. The clinically validated Timed Up and Go (TUG) test is typically administered at a physical therapist's office which would require the post-stroke patient to a) have a physical therapist and b) transport themselves to the office regularly. Our system enables patients to keep track of their fall risk score regularly within the safety of their own home and transfer the information to their care provider through the electronic health record (EHR). 

 
  This provides an overview of the design process.

This provides an overview of the design process.

NEEDS ASSESSMENT

CLINICIAN

  • Lack of visibility into patient's recovery status

  • Difficulty assessing actionable fall risk assessment

PATIENT

  • Lack of support, information, and therapy after discharge

  • Lack of awareness of issues that warrant immediate medical attention

  Clinician view of Timed Up and Go test results within the electronic medical record.

Clinician view of Timed Up and Go test results within the electronic medical record.

STUDENT DESIGN CHALLENGE PROMPT

The Student Design Challenge invited submissions that focused on leveraging Patient Generated Data for improving patient care. Patient-Generated Data (PGD) has become a focus of increasing attention for both healthcare providers and patients. There is a growing recognition of its potential to provide new insights into individuals’ lives and health outside of the traditional clinical encounters. However, there remain considerable barriers to integrating PGD with Electronic Health Record (EHR) systems, and to using these data to improve patient care. In this challenge, the committee invited teams of students to envision new ways for integrating PGD with EHR and for using these data to improve clinical decision-making, patient care, and patient-provider communication.

 
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