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ePoster Presentations

EP-156 - Beyond Falls: Reasons Why Older Adults Use a Personal Emergency Response System

Tuesday, May 1
11:35 AM - 11:50 AM
Location: Education Zone, Booth 2416, Screen 5

Background

Individuals in the United States are living longer than ever before, yet this is often associated with increased risk for chronic illness. Managing age-related chronic conditions is crucial for enabling older adults to remain independent. The Personal Emergency Response System (PERS) enables older adults living at home to signal for help in emergency medical situations. Traditionally, the PERS service is used after a fall to alert caregivers or medical professionals and prevent further injury due to lying on the floor for an extended time. Beyond fall notification, the PERS service may help older adults during acute medical situations such as COPD exacerbation, acute decompensated heart failure, or severe diabetic hypoglycemia [1]. We hypothesize that, beyond a fall notification service, PERS benefit patients with chronic conditions. Specifically, here we investigated: 1) the medical reasons for enrolling in a PERS service, 2) the situations of PERS help-needed calls resulting in ambulance transport, and 3) the primary diagnoses for emergency hospital stays in PERS users.

Methods

A retrospective, longitudinal analysis was conducted utilizing data from patients who a) received care through the Partners HealthCare at Home (PHH) program and b) were enrolled in Philips Lifeline commercial PERS service between 2011-2015. Electronic medical record (EMR) data included demographic, hospital utilization and medication information. These clinical data were combined with PERS data, which included demographics, self-reported medical conditions, and electronic case information gathered during subscribers' help-needed calls. Data from 1,156 individuals were aligned to analyze healthcare utilization before and after PERS enrollment.

Results

PERS users were, on average, 78 years old at service enrollment, the majority (76%) were female, and nearly a third were widowed. 80% of PERS enrollment was immediately preceded by a healthcare encounter, 35% of which were emergency hospital visits. Chronic conditions were the principal reason for more than 50% of those visits, while fractures due to falls accounted for only 12%. At PERS enrollment, 90% of individuals self-reported having one or more medical conditions, where COPD, CHF and diabetes were most common.
Per 1,000 PERS users, 380 ambulance transports were requested annually. 46% of emergency transports were classified as "physical or psychological symptoms", with reasons including respiratory problems, chest and other pain, illness and dizziness, whereas only 23% of emergency transports were due to a fall or fracture. Further, the most common principal diagnoses for unplanned hospital admissions after these transports were CHF, COPD, urinary tract infection, pneumonia and septicemia.

Conclusion

Our results demonstrate that, in addition to falls alerts, the PERS service is broadly used to signal for help in situations often related to underlying chronic conditions such as respiratory distress, chest pain and other acute symptoms. Early referral to a PERS service for patients with chronic conditions and high fall risk may facilitate timely interventions leading to reduced costly emergency admission, better clinical outcomes, and improved well-being of patients and their families. Moreover, combining the PERS service with predictive analytics to monitor patients' risk for needing emergency hospital transport has the potential to provide valuable insights to significantly improve chronic disease management and support independent living for older adults.

Learning Objectives:

Jennifer Felsted

Program Manager, Data Science & Analytics
Connected Health Innovation, Partners Healthcare

Jennifer Felsted, PhD is passionate about leveraging technology to bridge gaps in healthcare delivery and improve the lives of patients managing chronic conditions. As a Research Fellow at Harvard Medical School and Program Manager in Data Science & Analytics at Partners Connected Health Innovation, Dr. Felsted is involved in designing and conducting rigorous clinical and data analytic studies evaluating novel connected health technologies. Dr. Felsted earned her PhD in Biochemical & Molecular Nutrition, with a concentration in Neuroscience, from Tufts University and BS in Neurobiology and Psychology from the University of Connecticut.

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Jorn Op den Buijs

Senior Scientist
Philips Research

Jorn op den Buijs, PhD, is a senior data scientist with Philips Research. Jorn’s passion is to identify trends, uncover patterns and predict the future from large data sets. At Philips he is involved in research for CareSage, a predictive analytics engine that aims to help older adults remain independent for longer. Jorn earned his PhD degree in Biomedical Engineering from the Mayo Clinic Graduate School, Minnesota, and his MSc degree in Biomedical Engineering from Eindhoven University of Technology, the Netherlands.

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