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EmPowering a data-driven approach to personalized healthcare for people who don't (usually) use technology
How can we care for people who live alone and have high risk medical conditions?
Mollie's health care provider saw a steep drop-off in visits from patients like Mollie during the pandemic. They are now providing telehealth services to manage patients with chronic care needs, and to maintain revenue.
The Lyfeome(R) core sensor set gives care providers a numerical and visual summary of Mollie's daily life activities. If Mollie takes medical device readings, the system is reimbursable with Remote Patient Monitoring codes. A healthcare provider can then ensure that a chronic care patient like Mollie is monitored for her ability to live independently and follow a care plan. Lyfeome(R) has 22 alerts that tell her medical care team and family when a normal event is missing or a possible bad event occurred so they can check on her.
Dementia care - people who do not remember instructions can be monitored without them having to do anything differently than usual.
Low energy or low interest patients - people who don't feel well enough to respond to surveys, or take medical device readings, will have daily life data collected automatically.
Complex chronic conditions - people who need help tracking and organizing data before clinical visits have a continuous record of their home data that their medical team can review anytime.
Making data collection automatic and effortless generates a complete dataset for as long as the system is in place. Passive monitoring solves the problem of data gaps when patients lose interest in taking medical device readings, and forget to charge or wear devices like special watches and wristbands.
Eldercare and frailty monitoring - people who are nearing the edge of their ability to care for themselves, and still live independently in the community, would benefit from monitoring to ensure their safety.
Older adults are susceptible to hearing loss (nearly 2 out of 3 people over age 70), and impaired vision (13% over age 65), which limits their ability to engage with most technologies. Also, in the US, there are 7.7 million people over age 75 who live alone in the community and could be a frailty and fall risk.
Social Determinants of Health (SDOH) includes life circumstances that affect health, like income, housing, food security, and social support. However, comparing people in different circumstances can lead to bias and false conclusions. The Lyfeome(R) analytics reduce bias by comparing each person to his / her / their own history of what is normal rather than comparing people to a population that may not represent them.
Immunocompromised patients are more likely to get sick than people with a strong immune system. People with conditions like cancer, rheumatoid arthritis, diabetes, multiple sclerosis, celiac disease, etc, can reduce their exposure to circulating diseases and stay home more safely where their caregivers can check in with them at a distance.
People who need help to move around - people who are homebound or require significant help to leave the home can stay in place with supporting technologies.
Low technology settings - Many telehealth services can use regular telephones so people who do not use smartphones or have broadband can still stay in contact. But healthcare providers often have to rely on patient descriptions that are often inaccurate or missing important information. The Lyfeome(R) service gives healthcare teams and families complete daily information and works wherever cellphone texting works.
Rural care - Patients and healthcare providers both need access to digital technology to keep local relationships strong and provide revenue to maintain local clinics. Telehealth tools like Lyfeome(R) can reduce patient burdens related to data gathering and transportation, while giving medical teams important information for discussing care decisions with the patients.
Post-acute care - Some types of patients, like cancer and heart patients, return to the hospital frequently. Some monitoring technologies have significantly reduced the number of patients going back to the Emergency Room and hospital by catching problems early enough to be treated at home - a win for everyone. An automatic system that scans to be sure a person who lives alone and has recently gone home from the hospital, is eating, sleeping through the night, getting out of bed in the morning, and moving around during the day, will alert medical and family care teams when these essential things are not happening. 8M US adults over age 75 live alone, and more than 40% of people over age 65 have 4+ chronic conditions with complicated care arrangements, and could benefit from monitoring.
Cancer treatment - Chemotherapy drains energy and makes it hard for people to care for themselves at home. Setbacks are common. Cancer patients could use automated oversight to communicate with their families and medical care teams about how they are doing and if they need help.
Primary care, Lifestyle Medicine, and Care Management practices - integrated care and chronic care teams can get information about the whole person, including how all their chronic conditions together impact the person's life. Assessing the whole person improves care management and coordination.
Counseling and Health Coaching - Authorized therapists and counselors could see their patient's daily life patterns and discuss the ways those habits affect the person's wellbeing.
Understanding what works - Patients may say they feel better, but what does that mean? By breaking down daily life into patterns, then measuring them, Lyfeome(R) analytics can clearly communicate the effect of treatments immediately and over time. More stable sleep, more activity around the home, and more effort spent cooking are much better indicators of recovery and health than when a person says 'I'm fine'.