TDWI Upside - Where Data Means Business

Q&A: How Analytics May Improve Healthcare Outcomes

An attorney specializing in healthcare efficiency and compliance explains how analytics can lead to healthier populations and better outcomes at lower cost.

"The U.S. often falls dead last in quality of care in almost any measure except cancer care," says healthcare attorney Harry Nelson. "We're also the most expensive. The question is, using analytics, how can we catch up with countries that are spending much less than we are but seem to have much better health outcomes and healthier populations?"

Nelson is cofounder and a managing partner at Nelson Hardiman LLP, a Los Angeles-based law firm specializing in medical technology law, HIPAA compliance, Medicare laws, and medical practice law. He has launched three companies that advise clients in the healthcare industry about streamlining efficiency, including how better to store and secure data to ensure compliance with the law.

This is part one of a two-part series detailing our conversation about current trends in healthcare technology.

Upside: What is your background and interest in healthcare and technology?

Harry Nelson: I started in healthcare regulatory compliance and strategy in 1994, after getting my law degree in 1992 ... My timing was perfect in terms of working with large healthcare centers at that time, first in Chicago and then California, in that it all coincided with HIPAA and the beginning of the focus on health data privacy, and the fact that our healthcare system was beginning to be transformed by electronic records and electronic payments. Until the 90s, data privacy and electronic records weren't big issues in healthcare.

I've been blessed with chances to work with both very large institutional healthcare providers and many small physician-owned practices ... Those perspectives, large and small, have helped me see where healthcare has gone wrong and also where analytics can and has helped to catch mistakes.

We saw this transformation in healthcare in the late 90s and early 2000s in which the government began to use healthcare data in a new way -- for example, to catch those at the epicenter of the over-prescription of opioids. That's just one example, but since that time, there's been a significant advance in how quickly data can be mined, organized, and analyzed to address issues.

I see actionable data as a chance to improve healthcare -- a way to catch things that are going wrong.

What was behind Compliagent, the healthcare consulting firm you started in 2009?

I started Compliagent as a way of using analytics as a compliance tool. It's been quite successful, particularly in the nursing home industry and the behavioral health industry.

Part of the goal was to help healthcare providers leverage analytical data for their own compliance. ... Providers needed a way to demonstrate that they were doing good work by providing really good documentation. They needed to shift to quantitative analysis. By that I mean the ability to prove that they were actually delivering good care and complying with the law. They needed metrics to show what was going right as well as errors and problems.

My focus has always been on middle-market healthcare because so few people are looking in that area. The largest healthcare providers tend to have enormous resources and can hire the best companies and consultants. Much of the middle market doesn't have those resources -- they need to find really efficient, value-oriented solutions, and there's not much out there. In almost everything I've done, that's been my focus -- to serve the middle market with value-based solutions.

How do you define the healthcare middle market?

Not so much by revenue or income, rather I think of it as privately held healthcare, as distinguished from large nonprofits, academic medical centers, and publically traded companies. The midmarket is generally privately held, often family-owned and founder-led, and can be almost anywhere in terms of revenue, even up to a billion dollars. Generally, I tend to think of them as a second tier of healthcare providers who are struggling to find value in the tools they buy to support their organizations.

How can healthcare companies of any size use technology better?

That's a good question. I think there is a lot of work to do on developing systematic, evidence-based approaches to using analytics -- both to really figure out what's working and to do root-cause analysis.

In general, there's still a bias toward letting individual doctors and health providers make their own choices. There's still an idea of medicine as something that calls for individual expertise specific to a case and a reluctance to develop both positive and negative protocols. By positive protocols, I mean the ability to extract the data and say, OK, our patients who come in with this particular condition clearly do best when we follow these protocols. Negative protocols might mean, OK, when the following happens, it's a clear warning sign that we're about to enter an expensive episode and we have to intervene.

What's an example of an area where technology could be used better?

Medicare recently came out with a mega-rule on nursing homes and acute care. It's focused on payment models for heart attacks, joint replacements, and hip fractures. Part of the reason for that focus is that these have been really expensive areas of care and it's clear that there could be enormous savings in these areas.

Unfortunately, most facilities have not used analytics to develop good, evidence-based protocols. The fact is the quality of care and the experience of an elderly person who suffers a heart attack or hip fracture could be just as good with a lot less money spent. Healthcare providers haven't been developing protocols on their own about how to manage quality and cost in these areas, so the government is forcing the issue with these payment pilots, starting with a set of about 100 hospitals nationally.

You could extend that example to how we treat any number of conditions. It's such a huge opportunity. We could, with the use of analytics, develop a standardized protocol for how each instance should be treated -- by physicians, in the hospital, and post-hospital. On their own, most organizations are not using analytics to develop protocols. They are letting physicians drive care decisions, with huge variances based on the physician involved. There are only a handful of procedures where objective data is actually being collected on how physicians are doing.

Why is that?

First, doctors and providers don't want to be in the glare of publicity that sometimes happens if statistics show that some are doing better than others. Second, doctors simply don't want to be hemmed in by protocol. They don't want medicine to go from a craft practiced by artists to a streamlined process.

The Checklist Manifesto, a great book by Atul Gawande, talks about the power of checklist protocols in healthcare and how much healthcare could learn from the airline industry, from the construction industry, and many other places with lots of complex data. Processes have been streamlined there so that errors are less likely to happen. Yet healthcare has somehow been immune to that process.

The book talks about autonomy, which is a huge value for physicians but isn't a great value for pilots or engineers. With doctors, it sometimes seems that autonomy wins at the cost of accuracy. It has a profound impact on the way our healthcare system runs.

It sounds like we don't lack the technology to implement healthcare fixes. Rather, we lack the cultural will to implement them.

Right, I think it's the latter. In 2002, I was struck that the level of technology in the federal government was so primitive that it was revolutionary to be able to pull up a list of drug prescribers. We've made enormous advances from there. Technology is not the main issue any longer, although healthcare is still trailing some fields ... In terms of misuse, for example, companies such as American Express and MasterCard are much further ahead of Medicare or Blue Cross/Blue Shield in real-time detection of unusual claims. There's definitely some catch-up regarding technology compared to other industries, but the bigger problem is culture, absolutely.

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The conversation continues in Part 2.

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