In a data-rich world, Help at Home converts data to action

By Marek Bako, Vice President, Business Intelligence

The ability of organizations to gather, assemble, sort and present data has never been greater – but all of that work is meaningless if the data isn’t actionable.  That’s why Help at Home’s Business Intelligence and Analytics team works to get the right data into the right hands, so that we can make a real difference in the lives of our clients.  

Every single day, my team creates and publishes hundreds, if not thousands, of data reports, putting information directly into the hands of the people who use it to make important decisions. In fact, we recently created a data science department geared toward finding better ways to put the data to use, especially around care coordination.  

Too often, organizations collect massive amounts of data, but then don’t take the necessary steps to convert that data into formats that are timely, relevant and easy-to-use.  At Help at Home, our data team is energized by seeing the work we do immediately used to improve lives.  

Natalie Hodson, senior director of Business Intelligence, recently described the satisfaction of our work this way: “It’s really cool to see how data-driven our business is.  They’re using the data to make better decisions. There’s definitely a thirst for data or insight that is really awesome.” 

Many people may not initially see the value of data-collection to a company like ours. We are the nation’s largest provider of personal care services – and that may not sound like its data-dependent. We aren’t doing blood work or analyzing medical tests. Instead, we are performing vital daily tasks that allow people to live at home as they age. In other words, we do things like laundry, meal prep, and personal hygiene help.   

But while that’s a big part of the work, that’s only a small part of the value of what our caregivers are doing. The most valuable data we collect is based on the observations and knowledge of our caregivers as they work closely with clients.  

Our caregivers may be the first to notice subtle shifts in a client’s mood, health or behavior. For example, a caregiver may notice a client seems dizzy – or that they are becoming winded more easily. Follow-up evaluations after these kinds of observations can lead to a change in medication or other treatments that will improve health – and can help avoid dangerous falls or health scares.  

By collecting these observations, we are making Help at Home’s caregivers front-line workers in care coordination efforts. We are now able to use advanced analytics to sort and prioritize the observations, directing the care coordination team to clients who most urgently need follow-ups. In fact, we are even getting real time alerts on some data points – such as emergency room visits. This puts information in front of the care coordination team right when they need it so they can ensure that when the client returns home, they have the support and care they need as they recover.  

I know the data we gather is useful. How can I tell? Every day, we have more and more people using the reports and dashboards. That means they see the value. Also, our clients receiving this kind of care coordination are able to stay at home longer.

We are looking for ways to make every aspect of our work more effective.  For example, one of the first things we do for a client is match them with a caregiver. This involves some concrete, skill-based factors. For example, if a client needs rides to doctors’ appointments, the caregiver needs a driver’s license.  But successful matches also sometimes rely on a less tangible quality – whether the caregiver and client “click.”  

Right now, our care supervisors make matches based on their own knowledge and instincts. They know the client and the available pool of caregivers and make their best judgment on who would be a good fit. Sometimes the first match is a success. Other times, we have to try again. 

Increasingly, we are looking at the most successful matches and working to determine what datapoints may be relevant to why that relationship works – so that we can make more informed decisions.  

If we can reduce the trial-and-error aspect of matching, so that every client finds the right caregiver quickly, we can set the stage for a long relationship.  

That means steady, satisfying work for the caregiver – and personalized, knowledgeable care for the client. Everyone benefits!