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I’m going to go on a rant tonight. I’m not even in a bad mood. However, something reminded me of something, and I want to go off of it.

Healthcare, we need to talk

When it comes to the business and financial side of healthcare, it varies a little bit depending on the organization’s size. Suppose I think broadly of what people think of it like physicians, physician offices, even large provider groups with 15-25 MDs or mid-levels, and things like that. In that case, I’m astonished at how they are not typically run using a lot of data.

That doesn’t mean that data doesn’t exist in the business. That doesn’t mean that nobody looks at these things. The leaders of the organization, the people making the primary decisions, are not using data as one of their critical tools in terms of helping them set the direction for the company, make crucial decisions, and so on.

It’s not that nobody is. But, I think that we would benefit more from doing that. Indeed, we would make more money. Certainly, suppose we’re thinking about the push and pull between insurance companies and providers. In that case, we might have the weight come down a little bit better on the providers’ side and extract more money out of the insurance companies. Of course, this would make all of us happier if we were more adept at using data. It’s so wide-ranging.

Embrace the value of data

It actually makes me think of Guy Kawasaki. One time, he gave a model for how to value a startup. For those who may not know who Guy Kawasaki is, he’s been around the venture capital and startup community for decades. He was there at Apple computer early on. Guy Kawasaki was, I think, the key person for the Macintosh launch back in 1984. He calls himself an evangelist. He’s been around for decades now, talking about things and investing and so on.

His model for valuing a startup, which is slightly tongue-in-cheek, takes the number of engineers or software developers you have in the organization and multiply that times a million dollars. If you’ve got five engineers, $5 million. Then, take the number of MBAs you have in the organization and multiply that times $500,000 but subtracted. I’m not trying to hit on MBAs because I’ve got an MBA, and I think there’s value to the MBA. However, I think he’s got a point, which is that not all functions are created equal.

Use data for healthcare finance

Suppose I think of healthcare organizations, particularly when we think of revenue cycle management, which is really finance, which is really numbers, which is really data. In that case, we should really, really, really be living in that data. Not living in some simple sort of information in terms of what I call the typical finance but really more the ability to go from descriptive to predictive analytics, to prescriptive analytics. We’ll do all of that another day in terms of what that is and so on.

We really need to have a much more data-centric methodology, data-centric mindset regarding the healthcare business. I’m not commenting on the clinical side. I have very little knowledge of that whatsoever. Indeed, when it comes to healthcare, what I’ve seen over decades now in this business is that we could use more data analysis.

How data runs business

I think, in smaller organizations, whether it’s a solo provider, whether it’s a 10 or 25 doc group, there’s a lot of challenges in terms of getting access to data. It’s harder for a small organization to be that data-centric.

Larger organizations, hospitals, hospital systems, and so on, in my experience, have all kinds of other problems. Even if they have many IT systems, they run into a whole slew of other things that make CFOs and other top executives often really discouraged. In particular, in terms of their ability to lead and manage with data. Even though there is tons of data, they cannot get the answers that they want. That’s sort of a consistent theme.

To make a similar analogy to how to value a revenue cycle management department or a revenue cycle management company:

  1. Take the number of data scientists you have in the organization and multiply a couple of million times.
  2. Take the number of high-level data analysts, Excel guru kind of folks, multiply it times half a million, or something like that.
  3. If we’re talking revenue cycle management, take the number of times you’ve had consultants or other “experts” come in. Next, try to tell them what to do based on their experience as opposed to data and subtract a million dollars.”

Make decisions based on data

We need to make decisions based on data, not based on what we’ve done before, what’s worked for somebody else, or all those kinds of things. That doesn’t mean there’s no value to that, but that should be an overlay applied to the data based on what is currently happening in the business. What we forecast happening in the future as opposed to just “We should go revamp the eligibility and the intake process because it needs work, we’re having problems.” Anecdotal isn’t a good way to run a business.

That’s my rant for tonight. Go off and have fun! Go crunch some data. Data’s sexy.


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