The Healthy Middle

Who Is The “Healthy Middle?”

You, quite likely. I am. The healthy middle is the large portion of the population who feel generally healthy, but don’t really know what’s going on inside their bodies. We aren’t facing an acute or chronic illness and we aren’t high performance athletes. As we get older, we start to feel tweaks and twinges, but that’s just life, right?

Maybe. Maybe not. The healthy middle is already on its path from general wellness into ill-health. Healthcare traditionally hasn’t focused on exploring this quiet path of the healthy middle. Between wearables and AI, we’re understanding better what’s happening in our bodies and the early, undetectable – to human senses – indicators of a growing health risk. Yet the healthcare industry doesn’t know how to work with us during this long, critical stage where high impact prevention can prevent cellular degeneration, keeping us healthy longer.

If we invest in proactively managing the health of the healthy middle, we can reduce the volume and proportion of healthcare spending needed late in life. We might even need to reimagine what healthy aging looks like.

Why Healthcare Overlooks the Healthy Middle

The existing healthcare framework encourages delay on addressing health issues in this middle stage. Doctors concentrate on people already in a sick phase. If something doesn’t feel right but you’re not past the threshold of what qualifies as “sick,” the common response from the doctor is “Let’s keep an eye on this and see if it gets worse.”

But something is happening inside your body now. What if we had better insight into what that is and what its potential impact could be as we “wait and see?”

Doctors take this approach because they only have treatment protocols for the sick phase. Because there’s relatively little scientific examination into the potential or non emergent phase of illness, we don’t have the benchmarks for diagnosis and related treatment protocols.

Healthcare professionals are trained to look at data points, not continuous states. For example, they can run a test on your ketone levels and, based on the number, they can make clinical decisions. What the healthcare industry, research and clinical, doesn’t look at is how ketone levels in a patient’s body fluctuate over days. Without research identifying benchmarks touching on when changes will occur and what their impact could be, they can’t establish preventative protocols.

A healthy middle state isn’t getting researched to develop diagnostic tools and protocols for these interim stages. Without the data and analysis, the healthcare profession really can’t do much more for the healthy middle than wait and see until the illness becomes acute, and more dangerous and expensive to address.

Now, we need to take our share of responsibility. We play “wait and see” with our health too.

How often do we feel some foot pain or excessive tiredness and think, “Well, I can walk it off. I’ll be fine.” Nobody enjoys going to the doctor. We’re all eager to push that off. The appointment is inconvenient and possibly costly. If there really is something wrong, that will be even more inconvenient and costly – and now scary. So we wait until we can’t put any weight on that foot or until the fatigue causes an accident.

Because we avoid the healthcare environment if we can and keep our low-level aches and pains to ourselves, we may use home remedies or seek alternative treatments. We often do nothing. I get it. Most healthcare clinics, offices, and hospitals aren’t very hospitable. But we have to admit, our lack of participation in understanding and managing our personal state of health also contributes to why the healthcare industry overlooks us.

Fortunately, that mindset is changing. People in the healthy middle are interested in using the health devices available to them. We’re getting more curious about what’s happening inside our bodies that we can’t discern for ourselves. As the tools and technology improve, we all – individually and within the healthcare system – can work together to maintain a healthy state longer and slow down degeneration.

The HealthTech Tools We Have and Where They Could Go

The range of HealthTech devices is wide and of varying utility. Apps for Apple Watches can track many things, like heart and respiratory rates. But it’s just more data points that aren’t really put to use meaningfully. Activity tracker devices are popular, but don’t seem to have much impact in helping people lose weight.

At the other end of the spectrum are tech tools originally designed to help people manage their chronic illness, like continuous glucose monitoring (CGM) for people with diabetes. They’re built to help people manage living with a disease they already have, but are these tools the healthy middle can use to learn more about themselves?

Right now, we don’t use the HealthTech tools that collect medical grade data as diagnostic tools for the healthy middle. If understanding patterns of glucose fluctuations in our bodies could identify triggers and benchmarks that show when someone might slide towards a state of ill health – don’t we want to have that data and analytical understanding to prevent disease?

Healthcare Artificial intelligence (AI) used to analyze medical data sets is filling in these benchmark gaps between pre-diagnosis, diagnosis, and treatment. It’s building our knowledge of how to identify inflection points on the journey from healthy to sick. Because continuous glucose monitoring (CGM) has been around for a while, the industry has already had more than a decade to develop benchmarks on how to understand glucose fluctuations. For example, we now know that the amount of time and time of day that a person’s blood glucose is too high means something; it’s not just a point-in-time blood glucose unit number that’s important.

The more we use AI analysis on these data sets, the better it gets at predicting when someone’s glucose might spike. We now know that the amount of time a person spends each day with healthy blood glucose levels is critical, which makes being able to prevent a predicted spike incredibly important to maintaining long-term health.

AI’s help in identifying triggers and benchmarks is a necessary piece to convert personal health devices from tools that regurgitate simple data to tools that provide timely, actionable guidance. This idea is trickling down to some devices connected to our home networks. Mattresses that can self-adjust if the sleeper’s body temperature gets too high or low. Smart mirrors that track our skin and facial characteristics to offer nutritional recommendations.

This trend should lead to a state where we can each monitor our body’s well-being with the same precision that our cars can monitor their systems. Really, think about how much we rely on our cars’ ability to gauge for itself the earliest moment when one of its systems starts to function sub-optimally. That little red light on the dashboard lights up and we’re on it. We’re on it because we want to keep our cars running smoothly. We’d rather take small, reasonable action now to avoid catastrophic failure and paying astronomical prices for a major system overhaul in the future.