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Why Does Risk Adjustment Need Technology?

This is the first in a 4-part series called Intro to Risk Adjustment Technology.

Cognitive computing. Machine learning. Natural language processing. Two years ago, few people in the risk adjustment world had ever heard of these terms, and yet today they are becoming synonymous with risk adjustment. What are these technologies? Why do we even need them in risk adjustment?

Traditional risk adjustment just isn’t efficient

Traditionally, risk adjustment has been done manually: Coders comb through thousands of pages of patient charts and look for documented chronic conditions. But this isn’t the most effective or efficient process. It is time consuming and costly, and it doesn’t make good use of coders’ expertise. When I coded this way, It was frustrating that I had to spend so much time organizing my work before I could actually start doing it. Additionally, coders are often beholden to the slow and disruptive chart retrieval process.

Manual risk adjustment is also difficult for coder managers. With a manual process, it’s tough to QA 100% of documents, because there are just too many to review and not enough time to do it. And without electronic oversight, it’s difficult to have more than anecdotal insight into how your risk adjustment process is performing overall and identify ways to improve as an organization. This is critical from a management perspective if they need to manage their coders and other resources effectively.

Providers and payers face special challenges here. Providers may not receive or have access to all their patient’s health information, which leads to missing critical information in the medical decision making process. For payers, in order to get charts, they have to bother providers, creating a big disruption in the providers workday and unnecessary friction that will affect their relationship.

Risk adjustment will get bigger and the stakes will increase

All of this would be concerning in an ordinary moment, but we are in an extraordinary one. Currently, only five percent of Medicare Advantage plans are audited every year, and whatever money is recouped from the audit sample is not extrapolated to all the plan’s charts. CMS is considering audit changes in 2017 that would entail 100% of plans being audited and audit findings being extrapolated to all charts. Given this, and the fact that Medicare Advantage enrollment is increasing by about a million patients a year, we can hardly afford for risk adjustment to continue to be this difficult and time consuming.

Risk adjustment is ripe for a technological revolution

In the past decade, technology has made our lives easier in many ways. Take, for example, shopping. Just a couple years ago, shopping for a household meant driving around to four different stores in your area. You might go to Kohl’s to get a couple shirts for yourself, Sports Authority to pick up sneakers for your kids, the hardware store to get a can of paint, and finally the grocery store for dinner ingredients. Now, if you choose, you can buy all these things in a couple clicks, from the comfort of your home, with Amazon, while easily comparing price, specs, and even reviews. Think about what a huge transformation that is: We went from physically collecting objects at stores, to clicking on pictures of objects and then getting them delivered to your door. Technology has fundamentally improved the experience.

Just like Amazon has done for shopping, technology is improving the risk adjustment process. It has made risk adjustment coding more productive, accurate, efficient, transparent, and predictive.

Wondering what this new technology is and what it means? Stay tuned for Part II, III and IV of our Intro to Risk Adjustment Technology series.

To learn more, see the rest of the Intro to Risk Adjustment Technology series.

Part II: How We Use Technology to Get Risk Adjustment Data out of EHRs

Part III: How We Use Machine Learning to Analyze Patient Data in Medical Records

Part IV: How New Risk Adjustment Technology Affects Coders

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