I read a really interesting article this past week that was published a few years ago on Senior Housing News. The article discusses how senior living communities’ dining programs are closely tied to move-ins, especially as it relates to memory care communities. What I found particularly interesting about this article was its focus on generational differences when it comes to reliance on data for making senior living decisions.
Senior living decision-maker vs. senior living resident
Importantly, the article notes the potential distinction between the “senior living decision-maker” and the “senior living resident.” In some cases, this person is one in the same — an older person who is proactively making the choice to move to a senior living community, such as a continuing care retirement community (CCRC, or “life plan” community) or some other type of retirement community.
In other cases, however, the senior living decision-maker might be the adult child of a senior who requires some level of care services. In many cases, this type of decision-maker might be in a more reactive situation. Consider these common scenarios where an adult child might be the one who is taking the lead on a senior living decision:
- A senior has some challenges related to normal age-related decline, needs help with certain activities of daily living (ADLs), and requires the assistance of a full- or part-time caregiver. This care might be provided by an unpaid family member, a paid in-home caregiver, or within an assisted living community.
- An older person has a degenerative memory issue such as dementia and can no longer safely remain in their home, necessitating a move to a memory care community.
- A person has experienced an acute health event such as a stroke that requires extensive or even full-time nursing care. The family might try to handle the care themselves, pay for in-home nursing care, or move their loved one to a skilled nursing facility (also referred to as a nursing home).
Data-driven senior living programs
Whatever a family’s particular circumstances may be, this article notes that younger generations — such as so-called Gen X, Gen Y, and the Millennials — rely heavily on concrete, objective data to make many of their life decisions, including those related to senior living. By contrast, older generations, such as the Baby Boomers or the World War II-era Silent Generation, are often content with anecdotal evidence or even word-of-mouth when making a senior living decision.
This article goes on to discuss how senior living communities, and memory care communities in particular, must change the way they develop their dining programs and menus as well as other resident programming. They must learn to apply quantitative metrics to the process to properly market themselves to the data-focused adult children who are often making the decision about which memory care community to move their parent to.
To this end, Morrison Living, which provides food services to hundreds of senior living communities around the country, has taken the initiative to create their own in-house data analytics group. They examine the data they collect from communities to develop innovative culinary experiences for community residents based on needs and preferences. They also analyze the information to make informed choices about facility design and even staffing decisions.
>> Related: 5-Stars: Dining Options Evolve at Many CCRCs
Gathering and sharing more data
This concept of quantitative data analysis and application could easily be extrapolated to encompass numerous aspects of life within senior living communities beyond food service. It is this type of data that decision-makers from younger generations will rely upon to make informed choices about senior living — for their loved one and eventually for themselves.
For example, what if CCRCs consistently gathered — and importantly, shared — data on things like participation rates for community social and educational programs, demographic makeup of the community, the percentage or average age of residents who eventually move to assisted living or the healthcare facility, utilization rates of the fitness facilities, or even anonymized data on the percentage of residents with high blood pressure (which speaks to both the community’s wellness programs and menu planning).
This is the type of measurable analytics that may well appeal to data-driven senior living decision-makers, now and in the future.
The data trend of the future
The bottom line is that those generations that rely upon measurable data to make their decisions are fast-approaching retirement age. And indeed, in some cases, they are already making senior living decisions for their aging parents. What are CCRCs and other senior living communities doing to collect that hard and fast data that those consumers are going to require to make their selections? And are communities making business decisions informed by data or simply relying on anecdotal evidence or the status quo?
I don’t think it is overstating the importance of this issue to say that the future of the senior living industry could very well depend on how well it shifts to a more fact-based model for its operations and management.
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