Using AI to build the foundation of better capacity management

Sanjeev Agrawal and Jonathan Turner
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Sanjeev Agrawal: LeanTaaS, USA
Jonathan Turner: LeanTaaS, USA

Management in Healthcare: A Peer-Reviewed Journal, 2023, vol. 7, issue 3, 194-205

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.

Keywords: Digital healthcare; healthcare delivery and systems; transformation; administration and operations; capacity management; throughput; lean (search for similar items in EconPapers)
JEL-codes: I1 I10 (search for similar items in EconPapers)
Date: 2023
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