How UCHealth's EHR became key to its COVID-19 response: 6 insights on optimization capacity

EHRs are a critical components of a health system's COVID-19 response, offering a trove of data insights that support capacity predictions and optimizations.

During Becker's Health IT + RCM Virtual Forum Feb. 9, industry experts discussed how EHR platforms can be outfitted to better support hospitals' real-time decision making, both during and after the pandemic, in areas such as staffing, medical equipment and more.

The presenters were:

  • Steve Hess, CIO at UCHealth in Aurora, Colo.
  • Mohan Giridharadas, founder and CEO of LeanTaaS

Six key takeaways from the presentation:

1. The EHR is critical for a successful response to COVID-19. UCHealth went live on its enterprise Epic EHR in 2011 and has rolled out several optimizations in partnership with LeanTaaS since 2015.

"If we didn't have that enterprise EHR and the capability to produce analytics and intelligence, I don't know how we would have successfully responded to the pandemic," Mr. Hess said. "We're obviously still fighting the battle, but the key to our response has been our EHR, where we could actually grab data in real-time, analyze it and predict what's going to happen tomorrow, next week, next month."

2. UCHealth taps into knowledge from IT platforms to help with census prediction and make real-time decisions about staffing, setting up surge areas and getting more medical and IT equipment.

"We actually looked at external models coming from not only Colorado but also across the nation and world. We layered multiple models on top of our data to really look at where we were heading into the future," Mr. Hess said. "So, not only the descriptive analytics that would happen yesterday, last week, last month, but also what do we think's going to happen? And then that'll allow us to make those real-time decisions."

3. LeanTaaS' iQueue tool lets UCHealth manage daily capacity by pulling in data from direct admissions from the emergency department and operating room. The tool analyzes what the health system's demand will be for its limited supply of beds by looking at its predicted discharges.

"This helps our capacity managers, nursing leaders and physician leaders manage the daily capacity. But again, without the EHR and these advanced intelligence analytics tools it would be extremely difficult to manage an ever-changing capacity platform," Mr. Hess said. 

4. Optimizing capacity relies on two main concepts: Matching, or how to match supply and demand minute for minute every day of every week; and linking, which involves stringing together a series of disconnected service deliveries, according to Mr. Giriharadas.

5. Matching supply and demand patterns is crucial in healthcare; on the supply/capacity side, hospitals must ensure that when delivering any health service that the staff, equipment and facilities are all available at the same place and at the same time to accommodate the demand, Mr. Giriharadas said. Conversely, on the demand side, the health system must have an accurate understanding of the number and type of patients they are providing the service, when they will show up and how long each visit will take. 

6. UCHealth since 2016 has been using LeanTaaS' predictive analytics tools to boost operation capacity across its infusion centers, operating rooms, ambulatory clinics and inpatient beds.

Mr. Hess described some of the results as "UCHealth has seen impressive results across the board from the LeanTaaS implementations. Infusion centers have been able to decrease wait times even as we experienced double-digit growth in volume, excluding COVID period. OR utilization has improved significantly by creating an active 'marketplace'; Quality of in-patient bed capacity decision making has improved from 60 percent to nearly 100 percent."


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