Using predictive analytics to boost operational efficiency: 4 experts weigh in

With the rise of value-based care, population health management and other market challenges, operational efficiency is becoming increasingly important for hospitals to survive and thrive in today's healthcare environment.

During a panel discussion at the Becker's Hospital Review 3rd Annual Health IT and Revenue Cycle Conference in Chicago, four healthcare technology leaders shared their thoughts on the importance of operational efficiency and how hospitals can use predictive analytics to improve processes.

Panelists included:

  • Sameer Badlandi, MD, vice president and chief health information officer at Sacramento, Calif.-based Sutter Health
  • Karim Botros, senior vice president and chief strategy and innovation officer at The MetroHealth System in Cleveland
  • Mudit Garg, founder and CEO of Mountain View, Calif.-based Qventus
  • Todd Stewart, MD, vice president of clinical integrated solutions and clinical informatics at St. Louis-based Mercy Technology Services

Here are the top soundbites from their discussion, lightly edited for clarity.

On the importance of operational efficiency in healthcare:

Dr. Stewart said, "Hospitals can no longer expect to have decent margins by just providing a service, billing for the service and collecting. The days of healthcare having decent margins are over. Everyone is out of money, so you have to focus on these efficiencies. Strong management and efficiency are survival mechanisms for hospitals that must adapt or die."

Mr. Botros addressed operational efficiency from a population health perspective. "Our system has spent a fair amount of time focusing on call centers, scheduling, population health and referral management. If you don't drive operational efficiency at the same speed, you run yourself into a challenge. You can keep on growing, but if you can't do it efficiently, growth doesn't always translate to bottom dollar."

Dr. Badlandi said, "Operational efficiency is important because there are significant peer pressures in the market. Most organizations do not make any money on Medicaid. Most people also end up losing money on Medicare, so the imperative of fee-for-service and value-based care only kicks in when you're making your margins. To serve our populations, put up a new hospital building and provide millions in charity care every year, we have to be an efficient business."

Mr. Garg said, "The first time I walked into a hospital to improve operations, I was shocked. We have access to world-class clinicians, equipment and therapies in our healthcare system. But if you asked any average patient, we weren't providing world-class medicine. I realized it wasn't the medicine, but everything else around it that was behind the times."

On using real-time analytics in healthcare:

Mr. Botros said analytics comes into play a lot with load balancing and predicting patient surges. "If we have an ED that gets busy at a given period of time, but we haven't adjusted our staffing to fit that load, that's inefficient" he said. "We're taking that methodology and driving it across the hospital from the cafeteria to transportation to clinical settings."

Dr. Stewart said a predictive analytics program designed to forecast surges helped one Mercy hospital achieve a 30 percent reduction in the number of people who left the ED without being seen. "This reduction buys us a lot of credibility for the other things we want to do. It's a quick win — a substantial win — that demonstrates our cultural capability and a lot of credibility for change."

Dr. Badlandi said, "UPS has this amazing software that makes their drivers always turn right. What is the most amazing part of the strategy? That they came up with the idea? That they used predictive analytics to figure out where to turn? No and no. The most amazing part is they're able to make their drivers do that on a consistent basis. Figuring out how to make your people really stick to the plan and do standard work — that's where the magic is."

Mr. Garg said predictive analytics is really about "taking the data, processing it, understanding it and bringing the insight to the clinician in a way they can act … I genuinely believe adoption is most likely — and a lot of value exists — for using analytics to make simple changes to existing processes."

More articles on data analytics and precision medicine:

3 actions to get a data analytics project off the ground
NIH launches online 'toolkit' to help nurses bring genomics into patient care
Synthetic Genomics facing gender discrimination lawsuit

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