The Four Keys to Increasing Hospital Capacity Without Construction

hospital capacityEditor’s Note: This report is based on a 2018 Healthcare Analytics Summit presentation given by Yohan Vetteth, MBA, CAO, and Rudy Arthofer, RN, BSN, MHA, Administrative Director of the Hospital Operations Center, both at Stanford HealthCare, entitled, “Adding Capacity Without Construction: A Collaboration of Analytics and Frontline Operations.”

Many health systems are facing a hospital capacity problem. The demand for patient beds is greater than the number of beds available. This can lead to several negative effects, such as surgery cancellations, increased length of stay, and declining patient and staff satisfaction. While building capacity is vital to meeting demand, construction is costly and time consuming, and it isn’t always an option. This leaves health systems with the challenge of adding capacity without construction, and many are looking to healthcare analytics to help address this challenge and get ahead of demand while maintaining or improving patient outcomes and satisfaction.

Impacts of Limited Hospital Capacity

The impacts of a bed capacity problem can be significant. Some academic medical centers are turning away transfer patients because there aren’t any available beds, which means patients who need specialized care cannot get it or have to travel farther to get it. Surgeries are cancelled as well—sometimes even at the last minute—putting patient satisfaction and health at risk. Surgery cancellations also interrupt workflow, which can decrease staff satisfaction. Another risk of limited capacity is an increase in emergency department boarding hours. Interestingly, some hospitals see an increased length of stay for all patients in the ED (not just those awaiting an inpatient bed) when there aren’t enough available beds.

As the population ages and grows, bed capacity will continue to be an issue unless health systems can find a viable solution.

Developing a Hospital Capacity Management Process

The most important part of developing a process to manage bed capacity is creating a plan based on a collaboration of leaders and staff throughout the hospital. Having daily interdepartmental huddles is key to understanding the root of the problem and how to best address it. Solutions must focus on maintaining or improving quality and outcomes. Patient safety and patient experience need to be top of mind when initiating any change.

Using Data Analytics to Guide Resource Allocation

Data analysis can help organizations increase capacity without construction. Using available data, organizations can understand how past decisions and actions contributed to the capacity problem before they try to address it. They can also identify key process and outcome metrics across departments to inform the interventions chosen to address the dearth of beds. This can help increase transparency and measure impact.

Health systems can leverage data by creating an interactive dashboard that allows staff to dig deep into the data. This gives staff an opportunity to look at capacity constraints and understand the root of the problem in their respective areas. A dashboard also removes some pressure from the analytics team because it provides basic information staff can access without submitting a request. While a dashboard is an effective and necessary tool, it’s just part of the process because it only provides historical data, looking backward rather than forward.

Next, organizations can develop forward-looking tools that leverage the power of data science and take advantage of predictive analysis capabilities:

  • A hospital operations center daily report can provide accurate, timely data about current and future bed availability and provide leadership a view of the entire organization. It can also provide a tool to gather data and predict whether capacity demands can be met and, if so, how.
  • A 24/48-hour discharge dashboard can show the patient discharge plan throughout the hospital. This type of report uses predictive analysis to provide a picture of what bed availability will look like throughout the day so staff can develop countermeasures if necessary. The report uses advanced analytics to reprioritize frontline workflow by integrating system needs into the decision process. It uses data to help the team identify which patients are most likely to be discharged, which in turn informs next steps. This isn’t a clinical decision-making tool, but rather a predictive modeling tool for support services that helps align resources so patients ready for discharge aren’t taking up beds.
  • An annual capacity management assessment can help analyze the effectiveness of interventions, which helps with future resource allocation. This can also help organizations understand whether there is a year-long capacity problem or whether there are seasonal spikes.

These tools and others like them help move organizations from the theory of problem solving through the actions that increase capacity.

Roadmap to Increase Hospital Capacity

Health systems that have successfully increased capacity without building new spaces follow four guidelines:

  1. Successful organizations start with the problem and the ideal solution. Before an organization can develop a plan to address a capacity problem, it must map out what the problem is and agree upon an ideal solution. Fully understanding the problem and the changes that need to take place should be the foundation of any problem-solving mission.
  2. The analytics team works with teams throughout the organization—including leadership. A successful, efficient data analytics team cannot operate in a vacuum. They should be interacting with departments throughout the organization to fully understand the problem and how to best address it. Leadership should make it a priority to ensure the data analytics team is included in the entire process, from the initial planning stage through successful intervention.
  3. Leaders spend time with the operations team to understand workflow. The entire process must integrate the operations team and other vital departments. One of the best ways to get across-the-board buy-in for any change initiative is to get everyone together in a room to talk about solutions.
  4. Successful organizations focus on impact, not the tool. The data analytics tools are only as good as the impact they have, and organizations should strive for balance between using tools already available in the EMR and solutions beyond the EMR. The ability to effectively leverage data to assess interventions is vital.

The Value of Solving the Bed Capacity Problem

When capacity is a problem, hospital executives and other leaders can spend two to three hours per day addressing capacity management issues. When that problem is addressed through an effective capacity management process, leaders get their time back. This is a real benefit that can’t be accurately measured. Staff efficiency will also increase, as they aren’t burdened with trying to manage a lack of bed space. Instead, staff can spend their time focusing on patient care. And when patients have beds, they are more likely to feel valued and cared for—a positive effect on patient satisfaction and outcomes.

Additional Reading

Would you like to learn more about this topic? Here are some articles we suggest:

  1. Streamlining Radiology Operations and Care Delivery through Analytics
  2. The Healthcare Analytics Ecosystem: A Must-Have in Today’s Transformation
  3. The Practical Use of the Healthcare Analytics Adoption Model
  4. How Clinical Analytics Will Improve the Cost and Quality of Healthcare Delivery
  5. Emergency Department Triage Redesign Dramatically Reduces Wait Times, LOS, and Left Without Being Seen Rates

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