Using AI to build the foundation of better capacity management
Abstract
Operating at optimal capacity is more critical than ever for hospitals and health systems. Sophisticated capacity management allows healthcare organisations to create the right availability in intensive care units (ICU) and floor units, meet demand for elective surgeries and infusion treatments in a timely way, and adjust staff and nursing rosters nimbly to avoid burnout. But why are health systems so challenged to address these issues now, let alone during crises? In healthcare, the foundational math of capacity management, matching supply with demand and linking multiple services, is largely broken. This paper discusses how the healthcare industry can learn much from the successes other industries have achieved in these areas. It will, however, require fundamentally revamping existing tools and processes for health systems not only to overcome capacity shocks like future COVID-19 surges but also to maximise the use of existing assets and create value for patients and the organisation. Essential to delivering value-based care in today’s dynamic environment is deploying proven and scalable AI-driven, virtual and distributed systems and creating an organisational culture of innovation that embraces the change. Hundreds of health systems across the USA have already adopted digital transformation solutions that empower them to make real-time capacity optimisation decisions. Results include an 8 per cent decrease in opportunity days (difference between Med/Surg LOS & CMS LOS), US$500,000 more revenue earned per operating room (OR) per year, and significantly decreased patient wait times and increased patient volumes for infusion centres.
The full article is available to subscribers to the journal.
Author's Biography
Sanjeev Agrawal Sanjeev serves as the President and Chief Operating Officer of LeanTaaS, the leading artificial intelligence/machine learning (AI/ML) analytics company in healthcare operations. LeanTaaS’ predictive analytics software powers 176 health systems and 605 hospitals to improve access and lower costs. Sanjeev is also the co-author of the book Better Healthcare Through Math. Before Sanjeev joined LeanTaaS, he was Google’s first Head of Product Marketing and led three successful start-ups — CEO at Aloqa (acquired by Motorola), VP Products & Marketing at Tellme Networks (acquired by Microsoft) and Founder and CEO at Collegefeed (acquired by AfterCollege). Sanjeev graduated with BS and MS degrees in electrical engineering and computer science from MIT. He started his career at McKinsey & Company and Cisco Systems before joining Google. Sanjeev has been named by Becker’s Hospital Review as one of the top entrepreneurs innovating in healthcare.
Jonathan Turner Jonathan is a Product Implementation Manager for LeanTaaS’ iQueue for Operating Rooms (ORs) product. Prior to his career at LeanTaaS, he held a number of positions at Northwestern Medicine in Chicago, IL, and University Health Care System in Augusta, GA, where he ran ORs, led employed physicians, chaired readmission and length of stay committees, wrote community needs assessments, built clinical guidelines into order sets, led capital projects and published and refereed papers in both engineering and healthcare journals. Prior to his career in healthcare, Jonathan optimised frozen chicken inventory levels at Tyson Foods, corn syrup delivery routes at Carry Transit, spare parts quantities for mobile US Army warehouses in Iraq and Afghanistan at RAND, and physical plant layouts at Lockheed Martin. Jonathan earned a PhD in engineering from Northwestern University and an MBA from Augusta University. He is a Fellow of the American College of Healthcare Executives.
Citation
Agrawal, Sanjeev and Turner, Jonathan (2023, March 1). Using AI to build the foundation of better capacity management. In the Management in Healthcare: A Peer-Reviewed Journal, Volume 7, Issue 3. https://doi.org/10.69554/QUDR5310.
Publications LLP