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Pandemic Prompts Predictive Analytics to Optimize Hospital Resources

Analysis  |  By Scott Mace  
   January 26, 2021

Elective surgery backlog calculator and other new tools help University of Colorado Hospital.

Time was, that optimizing capacity management of operating rooms, hospital beds, and infusion stations required combing through EHR reports or spreadsheets built in Excel or visual analytics created in Tableau. Thanks to innovative advancements, that's no longer necessary. LeanTaaS employs predictive analytics technology to simplify such optimizations. Among the 300 U.S. hospitals that use its products are Dignity Health, Penn Medicine, and UCSF Health.

Recently, LeanTaaS founder and CEO Mohan Giridharadas and one of his customers, Jamie Nordhagen, MS, RN, NEA-BC, director of capacity management at the UCHealth University of Colorado Hospital, answered some questions about the challenge of better utilizing these resources.

HealthLeaders: How has your company leveraged technologies like artificial intelligence, machine learning, and predictive analytics to support customers during the pandemic?

Mohan Giridharadas: Our solutions ingest electronic healthcare record data and apply operational constraints (e.g., operating hours, number of operating rooms, special requirements such as robotic surgery, staffing) to derive the most efficient allocation of the resource under consideration. When it became apparent that COVID-19 was going to have a dramatic impact, we worked closely with our customers to introduce new constraints caused by the pandemic into the platform. We also rapidly developed tools such as an elective surgery backlog calculator, a staff survey template, and a nursing hours calculator that we made available at no cost to any hospital or health system. We also conducted several webinars to enable some of our leading customers to share best practices on responding to the crisis with hundreds of participants from across the country.

HL: Heading into 2021, how do you expect hospitals to lean on technology even more? What are some lessons learned from COVID-19 or predictions for the year ahead, when it comes to technology?

Giridharadas: Patient throughput and capacity management remain mission-critical initiatives for hospitals and health systems. What was viewed as a “nice to have” in terms of data-driven decision support tools is now imperative for providers large and small with the agility and resilience needed to meet the challenges of each new wave. In addition, as vaccines roll out over the next two years, hospitals and health systems will need help restoring their patient volumes as quickly and efficiently as possible.

HL: At a time when ICU capacity is strained to the limit, how is this technology helping to manage supply and demand of ICU beds?

Jamie Nordhagen: The LeanTaaS tool has been instrumental in automating patient flow through our Intensive Care Units and opening space for more critical COVID patients. Historically, our bed management system required nurses to manually enter when patients were "ready to move" after physicians wrote downgrade orders for transfer to lower level of care. LeanTaaS has allowed us to leverage a "pull" versus "push" strategy for lower acuity patients in our ICUs and offloaded some of the administrative burden for our bedside nurses.

HL: With so many systems deployed in hospitals (EHRs, ERPs, etc.), what does the single source of truth look like for managing and leveraging hospital resources?

Nordhagen: It has become our single source of truth across departments and clinical disciplines. We utilize the LeanTaaS tool and their predictive modeling to drive our patient flow operations. We have established triggers to open and close our surge areas, staff emergency department boarders, and open and close COVID-dedicated units.

Scott Mace is a contributing writer for HealthLeaders.

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