Health IT is booming, or so they say. The hotly debated and highly politicized health care reform, a.k.a. Obamacare, has been shining bright lights on a segment of our economy that is quickly approaching $3 trillion per year, and is in dire need of improvement, or so they say. Depending on who you ask, some say that health care resources must be redistributed in a more equitable manner, while others contend that health care must be made more parsimonious, or both. But regardless of nuances and variations, all seem to agree that health care must cost less in aggregate.
Somewhere around the turn of the 19th century, give or take a few decades, we figured out how to make things cost less in aggregate, and we have been applying the same principles to an ever increasing array of things that went from being luxuries reserved for kings and magnates, to being household items taken for granted by every pauper. And we’re not done yet, not by a longshot, but our cost reducing tools have changed from the chemical fumes and big iron of the early 19th century to the clean and minuscule silicon chip. Computers will make health care cost less in aggregate. We just need to figure out how.
Fortunately, the cost of making people is pretty much zero, because people are a renewable resource. Unfortunately, we have very little ability at this point in time to enforce some sort of quality control on an entirely spontaneous production system, so we are stuck for now with high variability in our inputs. Health care is the part that deals with maintenance for all these non-standard people, and hence the high aggregate costs.
Exacerbating the problem is that in a fragmented system, those who provide health maintenance services and products are on an innovation spree of their own, with new and expensive products coming to market every day. We could tinker with controlling prices of health maintenance providers, like other developed countries are doing, but frankly that’s just a band aid on the fundamental problem of aggregate costs of health care, which are growing by leaps and bounds all over the world.
To reduce maintenance costs, we need to reduce the need for expensive services, and we need to devise service paradigms that are cheaper to deliver. Since the factory floor is the entire planet, or at least the entire nation, the former requires incredible amounts of computable data, and the latter requires ability to control all aspects of service delivery under one roof.
And this in a nutshell is health care reform, not to be confused with health insurance reform and its poster goal of providing “coverage” for the poor and the sick through exchanges, subsidies and expansions. The vertical and horizontal consolidation of health maintenance services has been going on for quite some time, but is now accelerating to the point where there is hardly a day when health corporations merging and buying each other are not in the news. The servicing of these consolidated entities and all other cost reduction tasks fall to health IT.
Just like master craftsmen in the 18th century did not lead the transformation of their respective industries, and just like more recently butchers, bakers and candlestick makers did not build Amazon.com, clinicians will not be leading health care reform. Those who make, and program the machines, always did and will do so now. Health IT will dictate how health maintenance is provided in the future.
So what’s health IT up to? Health IT is lagging behind IT in other industries, because until now health IT did not recognize its own strength. Like young superheroes in blockbuster movies, health IT is blowing things up randomly, while trying to understand how it should apply these newfound powers. But health IT is not a single minded monolithic being. There are factions, competing ideologies, politicking, and lots and lots of money flowing in, both from customers and more recently venture capital. Generally speaking though, health IT, as the leader of transformation, has two immediate jobs to do.
This is absolutely necessary if we are going to reduce the need for expensive maintenance services, and a two prong approach is emerging. First, if we have enough information, we can stop people from using their bodies (and minds) in ways that are known to lead to disease, and we can have people engage in early and continuous self-maintenance. Here you find all the little health and fitness tracking apps and gizmos, supported by an emerging common wisdom that the medical profession should play its part in nudging people to hook themselves up to these devices, because it’s about staying healthy and a doctor’s job should be to keep people healthy, not to treat sickness. Who needs yucky sickness anyway?
Sure, for a while, we will have to contend with legacy people that are already sick, or on a path to sickness, so for them we have slightly different tracking apps that will help minimize the damage (and costs), one way or another, depending on a variety of factors. These are the feeders, or data suppliers, and in this category we also have involuntary data collectors, such as social media data collectors, shopping/leisure data collectors, financial data collectors, communications data collectors, and even electronic medical records collectors.
Second, we have the large (and not so large) aggregators of big data, which are now sprouting like mushrooms after the rain. These applications go by the name of population management or analytics software, and here is where the magic occurs. By combining all data streams, these software programs can identify need for preemptive maintenance. For example, did you know that people that like minivans tend to be obese? If we can combine car purchasing data with food store data and maybe entertainment data, we can red flag people for wellness interventions. And just so we don’t waste our precious resources, we can add health risk assessment data to eliminate those who are not amenable to intervention (why throw good money at lost causes?).
No, this is not an Orwellian futuristic state, because nothing is more important than health, and being healthy is the wish of every person in their right mind. As the revolutionary generation used to say, “Give me health, or give me death!” We can finally make this yearning a reality.
But all this big data collection and analysis cannot really work because most people are too stupid to voluntarily see the brightness of a healthy future. So we need to enforce prevention of escalating maintenance costs for the public good, and as always, compliance in a free society, can only be enforced by someone that is bigger, stronger and better armed. If a mom and pop doc tells you to buy and use a Nike+ FuelBand and in your infinite pedestrian idiocy, you decide not to spend money on that, you can always avoid the doctor by simply going to a different one next time your diabetes “flares up.”
But, if all doctors in town work for the same outfit, and every single one of them is aware of your obstinacy, because it’s in your permanent medical record, you’re out of luck. And just buying the thing and tossing it in a kitchen drawer won’t work either, because the doctor-employing outfit will be expecting your data from Nike soon enough.
Consolidation of the entire continuum of health maintenance services is therefore a must, and since we are now talking about huge businesses, health IT must come up with enterprise software, which is a far cry from little consumer apps, and even from medium size population management applications. Here we are running into the most hotly debated health IT issue — large integrated software systems vs. little interoperable apps. The common wisdom (have you noticed how all wisdom is now common?) argues that the big iron enterprise systems are expensive, horrible for users and not given to selfless data sharing (interoperability).
Yeah, they are, so what? Have you by any chance seen the horrendous software used by bank employees? Not the cute web/mobile apps for bank customers, but the grey 1950s model used inside the bank, that freezes and crashes and has more boxes and screens than anything I’ve ever seen in health IT. Does anybody give a damn that the “financial advisor” hates the computer? Nope. And when we have our health equivalents of Citibank, JP Morgan and Bank of America, nobody will care about physician dissatisfaction or productivity or burnout or any other feelings reserved for upper management.
How about interoperability, the battle cry of small apps builders wishing to get into the game? There’ll be plenty of interoperability, but not the kind people think they need. Enterprise health IT will open the gates for all the little data feeders to come in, and all the population management analyzers to come and do their thing, but nothing of substance will ever get out. A corporation cannot honestly provide efficient health maintenance to people floating around specialists and hospitals whenever they want to, and health IT will be erecting the electronic portion of the barriers to changing health maintenance providers.
Yes, we will have health IT ATMs where we can get a little information when stranded in a strange city, but when was the last time you walked into a Chase bank and cashed a Bank of America check? And when was the last time your Fidelity financial advisor was able to peruse your various accounts at your current bank and all banks you used in the past, to better advise you on saving for retirement? Come to think of it, when was the last time you switched banks? And how much transactional history was interoperated between your old bank and your new bank?
Health IT is hot and health IT will be leading the revolution and health IT will transform itself and health care. The big (and rather comfortable) enterprise health IT will just get stronger and bigger to better support industry consolidation. The little data feeder and analytics health IT will service the big health IT. It is very possible that some of these new consumer apps will gain huge market share and become big health IT (just big, not enterprise), and most likely this is why venture capital is investing. Take home lesson for little health IT: you can’t beat them, so the best strategy is to join them. And if you think something is missing from this (too) long dissertation, like patient empowerment for example, think again.