Lisa Arthur, who wrote the book “Big Data Marketing,” defines big data as “a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis.”
In this article I will focus on the undeveloped opportunity to use “Big Data” to capture dining habits of Seniors in Long Term Care, using Point of Sale (POS),
In Continuing Care Retirement Communities (CCRC), or Life Plan Communities (LPC), Residents often move in somewhere in their late 60’s. This is different than Assisted Living (AL) or Skilled Nursing (SNF) facilities where residents may often be admitted in their late 70’s or early 80’s.
In AL and SNF facilities this Big Data is already on its way to being captured. There is a plethora of nutritional software used to create recipes, plan cycle menus, tailor special diets, like and dislikes, physicians orders, and allergies. There is the ability to track consumption, and then, use this data to plan care and to improve outcomes for these residents. The missing piece is what do we know about the resident before they arrive? The current answer is: almost nothing.
In LPC’s, there is an unrecognized opportunity to capture Big Data in the dining habits of residents. As the LPC industry evolves, dining within them is transitioning from a managed hospital style cycle dining to a more free and flexible Restaurant model. As cooking goes from batch production to cook to order, I am seeing the need to communicate these orders remotely to a kitchen using a Kitchen Display System or printer. Dining has evolved from count based meal plans to declining point, or declining dollar plans. Having the new need to communicate on a per order basis with the kitchen, coupled with the need to manage these new robust dining plans ,has opened the door to POS technology, as these communities can no longer manage their operations with pen and paper.
We know in the near future that reimbursement rates in AL and SNF facilities will be tied to outcomes. Can we use POS as a window to wellness? There is an “aha”… Yes.
Currently the nutritional software used in Hospitals, AL, and SNF facilities is already being integrated to allow for flow of Cycle Menus and nutritional information into the Point of Sale. The unrealized part we all are missing is the flow of dining information from the POS back to the nutritional software. What would it mean if we could capture the dining history of a resident in an LPC for 10 to 20 years prior to them transitioning into AL, SNF, or Memory Care facilities?
I think the value is twofold. It exists as both internal and external value for Residents, the communities in which they reside, business, and society.
Internal Value:
If we could capture the unique dining habits of a resident, over a long period of time, we could manage better wellness outcomes now and into the future. If you are anything like me, we are constantly at battle with the the ever expanding pant size and the health affects that come in tow. When talking with friends and relatives, we talk with confidence, about how we are fine specimens of healthy eating and have trouble explaining why we have weight gain, and health issues, related to diet. How many of us have ever really kept a food journal? The POS could function, with integration back to nutritional software, as just that.
If a resident was feeling unwell and went to the doctor, explained their symptoms, had a blood test, and it was determined they had prediabetes, a doctor could be able to request dining history over a long range of time to get to the root cause. Currently, the approach would be to ask the resident about their dining habits, for which the resident might feel they are eating healthy and convey misleading information. Could the POS software provide this healthcare information back to the nutritional software for immediately assess wellness? Of course!
The doctor might determine that a resident often skips breakfast, eats a larger, higher calorie, higher carbohydrate lunch, then eats a somewhat healthy dinner. The physician might then prescribe a special diet that would flow through the nutritional software, relaying the information to the server taking their order in one of the various dining venues.
Taking it a step further, now that we know when, and what, the resident is eating over the last decade perhaps we can integrate fitness tracking devices back into the nutritional software to monitor activity as a variable. Maybe all of these tracking points can be feed back into the POS to use as a tool to suggest tailored options while the server is standing table side using the tablet ordering I spoke of in a previous article. Maybe the nutritional software, through a personalized in room closed circuit channel, can suggest appropriate dining selections that will be available later that day in the dining venues. Using these tools could provide a better value to the residents measured in overall wellness outcomes.
What about the resident who is not unwell? As wellness becomes a factor in determining future rates, perhaps that dining history can help get a better grasp on more realistic actuary tables. It would allow communities to remain more fair, balanced, and competitive in overall pricing.
In no other industry can we capture the extreme length of dining history on an individual person as we can in the LPC environment. Taking a macro look at demo graphical data, not resident specific data, could help with forecasting overall meal service. If we know a majority of residents dined the night before and choose richer, higher caloric foods, we might have the system automatically change breakfast offerings to entice participation with lighter fare. Understanding dining flavor and texture preferences as communities transition from one generation to the next would be more manageable and less of a guessing game. The generational shift will be a curve as new admissions replace those aging out, and managing resident choices can lead to less prepared food waste, and overall reduced cost to a facility, on a per plate basis. In a profit based model there is more flow through to the bottom line. In NPO’s this efficiency can be passed back to the residents through reduced room and board creating a more competitive pricing structure, required by the market, as the pension dollars start to dry out with new generations that wont receive them.
External Value:
What is the value of this non-resident specific Big demographical Data outside of the community?
Dining trends would not be theoretical but actual. What price would food service providers pay for that data to help them create new products? How many new healthcare technologies could be introduced to sell back into these markets?
More importantly, what is the value to the research and regulatory sector?
As an example, The Dietary Guidelines for Americans, published by the USDA in 2010, recommends no more than 8 ounces of seafood per week to avoid Mercury accumulation. What if demographic data, taken from a population of millions, across thousands of communities, over dozens of years, showed more, or less, measured values than than the recommended weekly consumption of seafood? If Mercury levels were measured upon admission to the AL, SNF, and Memory Care facilities, what if it do not correlate to those USDA recommendations? How much would regulatory researchers pay for that extremely valuable, non-resident specific, Big Data they would have no way to collect on their own?
This could create an immense amount of sell able analytical data. This could be so disruptive and revolutionary that it may outweigh charging for the software all together. The POS model in Senior Care could one day resemble the model of Microsoft, Facebook, Google, and Amazon, whereas, contractually the POS provider would have demographic access to that Big Data.
Today, obviously, we are not there. As the market demands this enhanced technology, more POS software and Nutritional software partners, either fully integrated, or coming online through more universal API’s will get more involved. I think we are looking at a high upfront development cost, with a pretty long wait for rewards. When those rewards come, they will come like a flood, benefiting the residents, the communities, the software providers, and society.
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