Why Lifeline’s AutoAlert Fall Detection Is Right for Your Loved One

It’s scary, but true: Falls are the leading cause of injuries and deaths from injury for seniors.1 And that figure includes all older adults — even those who are very active. That’s why a medical alert system with automatic fall detection is a must-have for every senior.

Use this information when buying a medical alert device with fall detection to determine the features that best suit your loved one’s lifestyle, and consider sharing this information to help get his or her buy-in:

Active Seniors

People in this group are 55+, live independently, are in good health, and engage in regular social, physical, and other activities.

Low-profile wearable: Philips Lifeline medical alert devices with AutoAlert fall detection are discreet pendants that fit neatly under clothes from activewear to business attire and beyond. They’re waterproof, so they can be worn in the tub — plus GoSafe, which features AutoAlert, offers on-the-go protection1 for those frequently out of the house.

Low rate of false alarms: The last things active seniors want are unnecessary interruptions and distractions. Some other companies’ fall detectors produce 8 to 20 false alarms a month. Our AutoAlert fall detection uses velocity and barometric sensors and a sophisticated algorithm to more accurately detect true falls and reduce false alarms to only one every two months.2

Seniors Living Alone

82% of people who fall are alone, and 54% are found lying on the floor, which can impact recovery time and (in some cases) survival rates.4

Assistance whether your loved one can press the button or not: It can be scary to fall and not be able to get up — and even scarier for someone who’s alone and can’t activate the medical alert device. AutoAlert fall detection calls for help when it detects a fall, whether the button’s pressed or not5, capturing 30% more falls that required EMS assistance than a standard device.6

24/7/365 availability: Lifeline with AutoAlert is reliable with 99.99% uptime, and multiple call centers fully equipped to stay online even during power outages or bad weather. The pendant also features a long-lasting battery that only needs to be replaced every 18 months.

Cardiac Patients

People with cardiovascular conditions fall and need hospital transport 29% more often than people with healthy hearts.7

Rapid response time: Once the AutoAlert service detects a fall or the help button is pushed, Philips Response Center staff answers in just 21 seconds.Help can be on the way faster than if you dial 9-1-1 yourself.

Faster access to life-saving treatments: Studies show that doctors have about 90 minutes to restore blood flow after a heart attack – otherwise a patient faces worsening heart damage and a swift slide toward death.9 Stroke patients need to receive tPA treatments within 3 hours to improve the chances of recovery.

Seniors with Multiple Health Conditions

Seniors with 5 or more chronic conditions (including diabetes, COPD or osteoporosis) report 40% more falls requiring medical attention than those without.10

Qualified call center staff: When seniors fall, they want to reach qualified response personnel who can provide the correct assistance quickly. Our U.S.-based call center staff is extensively trained in gerontology, stress management, and emergency response.

Better fall prevention: The AutoAlert service captures data on every fall, even if the senior gets up and declines assistance from the Response Center. Many seniors do not tell their doctors or families about falls they can get up from, but that doesn’t mean the falls aren’t indicative of a problem. Our CareSage predictive analytics solution accesses this and other patient data to help clinicians in an organization understand when a patient is at risk of hospital transport in an upcoming 30-day period. Clinicians can intervene early and help prevent potentially more serious spills and incidents. Ask your loved ones’ doctors if their affiliated healthcare organizations use Philips CareSage.

Seniors with Cognitive Impairment or Parkinson’s Disease

Older adults with Parkinson’s are twice as like to fall and require a hospital visit; those with cognitive impairment are 1.5 times more likely.11

Fall detection: Seniors with cognitive challenges may not be able to call for help or forget to push their button. AutoAlert will call help for them after it detects a fall.

Constant contact: Lifeline with AutoAlert fall detection connects with our call centers that stay online when the power’s off or there’s bad weather, so someone’s always there for you. Philips Response Center staff can respond to calls in 21 seconds when a button is pressed or fall is detected.12

This information should help you and your loved one to feel more confident about choosing a medical alert system with automatic fall detection that helps people stay active and safer.

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http://www.cdc.gov/media/releases/2016/p0922-older-adult-falls.html
2 Coverage outside the home provided where AT&T wireless network coverage is available.
AutoAlert Webinar FINAL052016
http://dx.doi.org/10.1136/bmj.a2227
AutoAlert does not detect 100% of falls. If able, the user should always push their button when they need help.
Personal Emergency Response System with Optimized Automatic Fall Detection Shows Greater Effectiveness than PERS alone, Philips Research
www.lifeline.philips.com/resources/fall-risk
According to results from an analysis of Philips Home Monitoring internal data collected from Aug. 2015 through Aug. 2016. All data is reported with a +/- 95% confidence interval.
http://www.cleveland.com/healthfit/index.ssf/2016/03/university_hospitals_ems_work_to_improve_heart_attack_response_time_critical_moments.html
10 Personal Emergency Response System with Optimized Automatic Fall Detection Shows Greater Effectiveness than PERS alone, Philips Research
11 Personal Emergency Response System with Optimized Automatic Fall Detection Shows Greater Effectiveness than PERS alone, Philips Research
12 According to results from an analysis of Philips Home Monitoring internal data collected from Aug. 2015 through Aug. 2016. All data is reported with a +/- 95% confidence interval.

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