Industry First Activity of Daily Living Scoring Uncovers Results in Level of Care Needed



As more and more members of the American family went into the workforce, the psychological and physical demands of caring for an elderly loved one at home, proved to be complicated. Families began to realize the obligations of work and managing a household significantly limits the amount of time that can be spent caring for an elderly person. And while the family may face physical and emotional stress, without proper supervision, older adults that have issues such as dementia, incontinence and restricted mobility are at risk for injury or more serious illness. A person deciding to act as a caregiver doesn’t always understand the demands of managing medications, coping with changes in behavior, and lifting and moving an older person.

Several solutions to family care have become popular in the past decades. Nursing homes gained in popularity in the 1960s, the 1990s saw an upswing in assisted living, and more recently, many seniors are choosing independent living facilities with moderate assistance. Today, the elderly population is increasing rapidly. Every day, 8,000 Americans join the 40 million Americans who are already 65 and older. This boom in the aging population has prompted more types of senior care to expand across the United States; one popular option is home care. Home care offers assistance from a professional helper, that is knowledgeable about a variety of medical conditions while letting an elderly person live in the comfort of their own home. But with living at home, assistance is often needed by others and must have a standard of care and way to evaluate daily activities. These basic daily functions are known in the industry as Activities of Daily Living (ADLs).

In the 1950s, Dr. Sidney Katz, a specialist in gerontology, and his team at Benjamin Rose Hospital in Cleveland, Ohio, developed a chart for standards of living, called the Activities of Daily Living (ADL) index, which is used to assess the functional abilities of older adults living with chronic conditions that require long-term services and support from others. Medical and health professionals use an older person’s ability or inability to perform ADLs as a measurement of their ability to function properly on a daily basis.

While ADLs have gone through some minor changes, the ADLs that Dr. Katz created are nationally classified and recognized by all healthcare professionals as eating, bathing/grooming, toilet hygiene, dressing, and mobility, also called transferring.


THB’s mission is to provide personalized in-home assistance to elderly or disabled care-recipients, as well as carefully measure and track the amount of care that is needed. This care typically involves assisting with one or more ADLs per visit. Along with providing home care, THB licenses their mobile app technology (at no charge to the caregiver) to help managing home care visit tracking. As a result of this rich dataset, THB implemented an analytical program that measures both the level of care needed to perform the ADL as well as the number of hours spent at each independent visit. Capturing data from each visit identifies how much care is needed in terms of intensity and the hours needed at that level of intensity with each ADL. Hands-on-assistance or HOA is the most severe or most intense level of care needed and when reported indicates that this person needs the most assistance with performing that particular ADL.

At each visit, a caregiver records the ADL level of care needed for that caregivers individual visit (based on score ratings of 0 to 3) and logs the number of hours spent at the visit into the THB mobile app. This ability to capture data at each visit is crucial in helping to identify how many hours of care each care recipient needs based on the severity of their ADL score. The higher the score, the more hands-on assistance (HOA), a care recipient needs from a caregiver.

Through The Helper Bee’s analytics program a consistent pattern has emerged that demonstrates: if a claimant needs more hands-on assistance with ADL tasks at home, then that claimant also needs (and the data shows) more total hours of care. This is a non-trivial observation as it validates the ADL scoring methodology as an accurate mechanism for tracking care changes.


Each visit was registered into their system by the assigned helper creating a timesheet that captured the level of care needed for each ADL at each visit. The majority of data was recorded by submitting the information from The Helper Bee’s ‘Helper Hive’ mobile app. Each visit only has one submission and one score. If a single timesheet spanned over 24 hours, it was removed from the analysis. This occurs when a helper submits one timesheet for multiple days. The proper process would have been to split into two timesheets, and the data was eliminated as it would have been redundant.

During the visit, the helpers use The Helper Bees’ proprietary scoring system that assigns ADLs with a value from 0–3 depending on the severity of care provided. A score of 0 (NP or None Provided) indicated that no help is needed or requested. A score of 1 (CUE, cueing) meant a client needed a reminder or nudge about a behavior, but they did not need assistance or require monitoring during the activity. A score of 2 (SBA or stand by assistance) signified that the helper needed to be in the same room and stand by to assist with the task as required. Finally, a score of 3 (HOA or hands-on assistance) denoted full hands-on assistance was needed from the helper to perform a task.

For each unique visit, an average of all recorded ADL scores are tallied and submitted with the timesheet. The possible score can range from 0 to 15, where 0 is NP or not provided on all ADLs and 15 is Hands-on-assistance on all ADLs. A score of 15 would indicate a person needed maximum help for each ADL. After the data is submitted, the results are averaged on both a daily and weekly basis.

Of 290 claimants analyzed, 63 claimants need help with 2 ADLs or less. Over the course of a year, those claimants only needed an average of 4.9 hours of care per visit and 23 hours per week. The other 227 claimants needed between 2 and 4 ADLs per visit — those claimants, on average, required around 7.5 hours per day, and 42 hours per week.


The two other groupings are claimants who received between 10–40 hours and claimants who receive 41–120 hours of care per week. The 10–40 group had an average ADL score of 7.8 whereas the 41–120 scored 9.2. The 10–40 group needed an average of 24.9 hours of care per week, but the 41–120 showed significant increase in weekly hours at an average of 66.9 hours per week.

The below chart represents the percent difference in each groupings. Noting a similar trend as discussed above, a greater percentage increase is seen as the ADL score increases as well as the number of weekly visits and their length.


As with all care, a claimant’s needs may change during the course of their care. They may cross into different care level groups as they progress or digress in their condition, and some leave home to care for various reasons. Comparing data from active and inactive claimants still demonstrates the same breakdown in need levels versus hours of care.

Looking at our group categories we can estimate the weekly care hours need — what could be the appropriate amount of care for a person based on their ADL grouping.

The dashed lines represent the average trend within a group. The solid line reflects the actual data of each cohort. What is noticeable is that the Medium group has the most variability within the cohort, hence the greater deviation from the average line.


With this analysis, when a claim is initially filed, insurance companies can utilize THB benchmark data to ensure that the claimant’s plan of care and approved hours of care match up to the expected care needs. These benchmarks are also highly valuable because it provides insurance companies with reliable data to make a case for approving more hours of care for a high-needs claimant or to help mitigate the chance of a claimant suffering an acute injury or further debilitating themselves while on claim. Confidence in approving additional hours of care lowers the risk of further injury to the claimant, which in turn lowers the need to file a new claim, and can reduce the amount of money spent by both the insurer and the claimant (potentially out of pocket) on additional care. In the long run, through predictive analysis, this data can help insurers and care providers better assess risk for this group, allowing them to update policies and rates to match a claimant’s needs better.

It is also beneficial to the overall healthcare system. Claimants receiving the appropriate amount of care can reduce accidents otherwise preventable; and in-doing so reduce the spike in higher cost claims such as hospital stays or nursing home admissions. This lowers the need to use emergency rooms, urgent care clinics, and have extended hospital stays, as well as pay for expensive medications or labs and equipment for testing. Using fewer medical resources, outside of in-house care, poses a very favorable long-term outcome for both claimants and insurance companies. Insurance companies need not pay high cost, lengthy hospital stays if a claimant is able to receive the care they need in their own home.

Finally, the claimant benefits in this case as well. 90% of older adults wish to remain at home. This reality is possible when care can be delivered, monitored, and successful tracked. And, claimants can preserve their benefits, as home care is a substantially lower cost (and claim cost) than hospital or facility-based care. Beyond the financial benefit, being at home often contributes to a better emotional outlook for the claimant. Remaining independent can be critical to maintaining health, limiting further injury, and overall satisfaction of living in their own home.


While this may seem like a simple concept — the more activities of daily living assistance needed, the more care required by a caregiver — this data is groundbreaking. The Helper Bees demonstrate a positive correlation between claimants with high activities of daily living needs and the hours of hands-on-assistance care needed by a caregiver.


Contributors to this paper:

  • Data analysis by Jessica Faulk
  • Copy editing by Christina Newbrough

#Insurtech #AgingTechnology #InHomeCare #Thinker CEO of The Helper Bees @thehelperbees and founder of Georgetown Living @georgetownalf

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