BIG Data & Aging in Place

As I arrive in Chicago for the American Society on Aging conference and What’s Next? Boomer Business Summit…………

All the talk about Big DATA, brought to my mind’s eye by Joel Shapira forwarding this Forbes article about IBM , leads me to discuss the impact big data will (can?) have on aging in place.

Currently most aging in place management and decisions are not based on data at all. People wake up daily hoping not to face a crisis. Caregiver adult children also hope not to have a crisis today not only because they want mom and dad to be well, but because they know the cost to their day, their lives and their work when care plans need adjustment…and they do all the time. Management and decisions are made on a put out the fire basis. That is the nature of the beast.

Similarly, providers show up to work every day hoping some things run smoothly knowing most don’t. That is the nature of the beast. Clients’ health changes so the care level and mix needs to change with it. New clients are in turmoil. There is little in between.

How can big data change the nature of the beast.

In most fields Big Data is about predictability. Retailers, insurers and so forth put a particular client in the context of other clients who have similar buying habits or interests to predict what they may buy or what risk they represent.

Most aging in place tech is about small data. The recent McKinsey report suggests it is not catching on because the data is not actionable, does not provide value.  A report on mom’s sleep last night, for example, goes to her daughter or maybe to a monitoring station. So what? Someone has to call or visit mom and see what is up.  Mom may not be a good reporter so no actionable info is gathered. What makes this better than a routine daily call? People- consumers and tech companies – are frustrated.

To make individual aging in place data actionable it must be in the context of much more health data so predictions can be made. That is not hard to grasp. If client A has three health conditions and monitoring info is available for 65 days prior to today’s real time report, and all that info is placed in the context of 10,000 others with similar health and monitoring data, the real time data for client A can help predict changes and the matching care needs. That can be actionable.

I say can because this is only half the equation. Consumers are just half.  Data captured from clients, put in a larger context of similar clients, can be used to predict client needs – not so much for the individual client– that is small data’s province. Big data applies to the community of clients. Providers -business, non-profit or government agency -must be equally adept at using the data – acting on the predications- to improve performance.  Improving the customer experience and business operations. Providers use it to match expected needs to staffing and product inventories. That means better service and smoother, more economical operations. That is what businesses do.

So we need a sea change in how we view and use the data we collect. Some of us should redirect our focus from serving individual clients to serving coordinated providers. Then big data has a chance to show her stuff.

Talk to me about it.