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UCHealth’s new success in directing patient flow, part 1: a data-driven approach to hospital bed management

  • Pallabi Sanyal-Dey, MD, FHM
    Pallabi Sanyal-Dey, MD, FHM

    Director Client Services, iQueue for Inpatient Flow, Associate Clinical Professor, UCSF School of Medicine

In many hospitals, the ongoing inability to place the right patients in the right bed at the right time is both a burden and source of frustration for clinicians and staff. Patients are impacted by barriers to inpatient beds as well. Along with their families, they grow tired waiting hours when it comes to admissions, internal transfers, and finally discharges. 

To mitigate these effects on providers, patients, and staff, hospitals have historically relied on manually-prepared tools and processes, such as lists, spreadsheets, or dashboards, to report on patient flow and unit capacity data. However, these reports are labor intensive and error prone. Even as staff must constantly update them throughout the day, they are still often unable to provide managers and frontline workers with the patient placement information they truly need. Further, staff sometimes mistrust the information the tools do offer, as they may not be updated on time or with the correct data. These tactics can introduce even more chaos, confusion, and frustration when trying to ensure patients are placed in appropriate beds.  

UCHealth University of Colorado Hospital experienced this very problem with hospital inpatient capacity management. Throughout the 2010s, all 12 hospitals in the clinically diverse health system had access to an extensive amount of patient data, and a range of reports, dashboards, and worklists on which to view it. Though these efforts helped in grasping some of the current and historical state, there were no predictive analytics nor prescriptive actions for operational teams to use. To enable staff to act quickly, decisively, and with true impact on patient experience, UCHealth needed a single source of truth for inpatient capacity management that could be shared in real-time across departments, clinical disciplines, and the health system as a whole. 

This two-part series discusses the successes UCHealth saw after implementing LeanTaaS’ iQueue for Inpatient Beds in 2020. The inpatient bed capacity solution provides real-time data displays plus predictive and prescriptive analytics that enable operational teams to move away from reactive capacity planning and toward proactive problem-solving. Using iQueue also improves patient flow by reducing wait times at key steps along the patient journey and mitigates the chaos historically inherent in managing bed capacity. UCHealth deployed the solution to address several critical points that impacted patient throughput, including one of the biggest patient discharge barriers, communication.

Hospital bed management key issue 1: Time to admit  a waiting game

The complex journey of patient flow begins upon admission to the hospital. Many times, patients must wait to be admitted to an inpatient unit as staff try to locate an available bed wherever possible. As they rely on manually updated reports distributed via email, staff may not have the most up-to-date information for bed placement decisions. This is a root cause of the above-described frustration and dissatisfaction among patients, their families, providers, and hospital staff overall. One of the reasons UCHealth adopted iQueue for Inpatient Beds was to change how staff accessed and distributed the information they needed to admit, transfer, and discharge patients in a timely way. 

UCHealth’s 665-bed hospital at University of Colorado Anschutz Medical Campus implemented iQueue for Inpatient Beds in February 2020 to help run daily bed meetings, perform hourly administrative management, and drive capacity protocol standardization, including surge planning. Despite an 18+% increase in census (due to COVID-19), UCHealth noted a 10% decrease in time to admit patients from the Emergency Department and an overall 16% decrease in time to admit.  

Using the analytics-powered dashboards in iQueue for Inpatient Beds, which show up-to-the-minute capacity statuses across the health system as well as likely future trends based on historical data, UCHealth staff are able to predict future admissions and discharges, balance beds across the network, hospital, and unit, and confidently make strategic decisions to ensure the right patient is in the right bed at the right time. UCHealth adopted iQueue for Inpatient Beds as the primary information source throughout the organization regarding any questions or concerns pertaining to patient throughput, thereby helping to increase efficient communication among the healthcare team.  

An upcoming post will explore the challenges of another key step in hospital bed management, efficiently transferring patients between units, and how UCHealth realized a 65% reduction in time to complete intensive care unit transfers.

*UCHealth is an integrated health care delivery system serving Colorado, southern Wyoming, and areas of Nebraska. The network, which utilizes Epic, consists of 12 hospitals with a total of 1,997 inpatient hospital beds and had over 141,000 inpatient admissions and observation visits in FY2021.

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