Dr. Darlene Tad-y stepped into her capacity management and patient flow roles at UCHealth in September 2022, assuming these as part of the effort to streamline the operations of a health system whose efficiency was critical to delivering care across the entire state of Colorado.
UCHealth comprises 12 hospitals spanning the whole state from north to south along a major interstate corridor. With 2,000 inpatient beds across the system, UCHealth also has 5,000 employed and affiliated providers and 26,000 employees and staff. Each year the system sees over 140,000 inpatient admissions and observation visits.
Also an Associate Professor at University of Colorado School of Medicine and an academic hospitalist at the University of Colorado Hospital, UCHealth’s academic medical center, Dr. Tad-y oversees efforts to optimize operational efficiency and ensure patients receive the right care, at the right time, in the right setting by the right team. She will speak further on these efforts at the Transform Virtual Hospital Operations Summit on June 6-7, 2023.
Question 1: Can you begin by talking about UCHealth, and the particular challenges you were experiencing with inpatient flow? Why was this “chaotic”?
Darlene Tad-y: UCHealth is nationally and locally recognized for our accomplishments in the quality and safety realm. We work to maintain this standard and provide equitable access for all in our region. Doing so can be challenging, as we have such a large footprint over an expansive geography, with many patients who must be matched to many resources. Before I took on this role and started working with my colleagues on process improvement efforts, and especially before we implemented new technology in 2020, we struggled to efficiently manage inpatient flow.
Within each of our hospitals, we would activate Code Yellow when we reached high capacity, or had high inflow from the emergency department (ED) or transfer requests from other hospitals. When Code Yellow was called, administration held crisis meetings in a boardroom while our frontline providers scrambled to discharge eligible patients safely. Due to the lack of real-time communication between those two groups, people did not have insight into the processes that were happening in other areas. No one had a good grasp on what was happening with our beds, how many bed requests came in through our ED or operating rooms (ORs), or how many requests were coming from outside hospitals.
Administrators and providers struggled to improve patient flow without knowing what barriers existed nor what interventions were taking place, which ultimately jeopardized access to hospital care, surgical services, and emergency services during the times that we were at Code Yellow capacity. To preserve access, we had to change how we created and enacted our processes across our teams.
Q2: How did you assess what solutions to put in place to begin addressing these communication and decision making issues?
DT: We realized that whether we faced a crisis or not, we needed real-time insight into patient flow at our fingertips to enable informed decisions that were aligned across administration and the frontline. We needed technology that would provide a single source of updated truth for all, accurately predict admissions and discharge barriers, and flag upcoming capacity issues so that we could address them together before they became emergencies.
Prior to February 2020, our frontline teams relied on traditional methods of reporting like dashboards, paper, and spreadsheet-based reports for decision making in their daily huddles. These methods caused undue stress to our teams, as they had to be manually prepared and updated, relying on team members’ instincts to predict future patient flow. These methods also did not provide the common source of truth needed to effectively manage patient flow within one hospital and across sites in our system. We needed powerful intelligent technology to synthesize the many factors that direct patient flow.
To become a high reliability organization that ran on informed decisions, UCHealth needed high powered analytics and automated workflows, as well as a new patient flow strategy to drive decisions in real time. In February 2020, we deployed the AI-based iQueue for Inpatient Flow solution at our main academic medical center, University of Colorado Hospital, then rolled the solution out across the rest of the system in October. We saw rapid improvement in the management of inpatient flow, which we continue to build on today.
Q3: How does the AI technology UCHealth adopted work specifically to support your frontline staff, as well as leadership, in creating better patient flow?
DT: First, iQueue provides our administration and frontline teams with reliable, easy to access data. Everyone can make decisions based on the information and have confidence it is accurate and up-to-date. This supports efficient and confident daily huddles on the floor, empowering our teams to determine and take immediate action, while giving performance metrics to help administration drive high-level decisions that reflect the capacity situation as it truly is.
iQueue also offers specific levers to direct patient flow throughout the day. The discharges and admissions tool, because it runs on machine learning and AI, gets smarter over time. In using it, our care teams have become extremely accurate at predicting patient discharge dates as a team, so they can work toward these goals together.
The predictive capabilities takes the guesswork out of admissions volume for the day, so iQueue users can see patients are likely to get admitted from the emergency department and other areas. For insight into the present situation, iQueue shows a real-time overview of bed capacity in every unit, including the number of open beds and where bottlenecks might potentially occur. Every department has to report out on this, which promotes transparency and collaboration. iQueue’s transfer toolkit further shows bed availability across hospitals, so care teams can make the best choices on when and where to transfer,
avoiding blind requests that cause capacity problems on other sites.
We can also use iQueue to see our predicted bed balance across care units, so we can choose to open a surge space for a certain level of care only when it’s likely to be needed and used. Now when we reach a certain capacity level, iQueue automatically informs us which action to take, based on what’s worked best previously. We no longer need to make in-the-moment, individual decisions based on limited information, which removes much of the chaos that came with Code Yellows in the past.
Q4: UCHealth found a technology solution to address particular issues that impacted patient flow. What other steps did you take to align your people and processes to ensure this technology succeeded?
DT: Besides adding a technology solution, we’ve looked carefully at our patient flow processes, so that we had the right people in the right place with the most effective assigned roles and responsibilities. Our philosophy for aligning our people and processes toward one unified goal, while ensuring individuals can take action that makes sense in their given location, is “central discipline, local control.” The data iQueue provides helps us operate in this structure successfully.
We now have a senior executive group that sits over the patient flow governance structure that operates system wide, then a Patient Care Continuum Council that oversees the activities surrounding patient needs and phases of the care journey in different locations. At the local level, we built infrastructure among our physician leaders.
We start by putting structures in place at the system level, then build processes at the local level on our units and in our facilities. About a year ago, we began training our frontline to understand the concept that every patient's care journey has specific milestones. Noting these milestones helps us ensure, together, that patients get to the right place in our system at the time they need their care.
The iQueue technology gives us universal visibility into patient journeys and provides the insight to act on it. We operate on a checklist of all clinical and nonclinical needs an admitted patient may have while they're in the hospital with us; issues our system causes that may delay that patient's care journey; and potentially unavoidable discharge barriers, such as a patient having nowhere to go post-discharge. To surface and solve these problems, we conduct multidisciplinary rounds every day with all of our teams, as well as twice-daily inpatient flow huddles where we escalate delays so we can address them in real time and keep patients moving safely on their recovery journeys. This way, we can reduce unnecessary length of stay, open beds in a timely way, and maintain access to care for our communities.
Q5: What are some results of UCHealth’s inpatient flow transformation?
DT: In this past year, we have decreased our length of stay by 0.4 days, which translates into the creation of 35 inpatient beds. We also have had a 6.8% increase in our inpatient admission volume, which enabled us to care for almost 1,400 more patients this year to date than last year.
As another result, we note the confidence and clarity felt by our teams. When our frontline teams use their new insights, they can know what's going on and feel that they’re as important a part of the process as they truly are. When we administrators can use our insights to geographically cohort team members to join the same patient care teams consistently, they can bond and collaborate together. Creating that joy and wellness at work among our people is a priority for us, and we look forward to continuing to do so.
To hear more from Dr. Tad-y and see UCHealth’s patient flow strategy in-depth, register for the Transform Virtual Hospital Operations Summit, happening June 6-7, 2023.