Custom Enterprise Data Platform

Challenge

In the hospital setting, suboptimal bed utilization can cascade into a multitude of unpleasant or even unsafe experiences for patients — not to mention wasted resources and revenue loss for hospitals.

Our client, a for-profit hospital system, was having trouble determining the right number of staff to schedule for servicing (or “turning around”) beds in any given ward of the hospital. As a result, the client had been experiencing many of these “cascading issues” firsthand. 

In wards with too few staff scheduled, staff members could become very stressed while rushing around to prepare rooms. This prompted some to worry about patient safety.

“When beds aren’t ready and staff feels tension and pressure to complete their tasks in a hurry, patient safety can be compromised,” the client explained. 

“It’s a very stressful way to work,” she said. “During high-capacity hours, it’s like Grand Central Station. We have to work quickly to clean the rooms, make sure each room has the right equipment, and then get our patients into beds.”

Meanwhile, other wards of the hospital might have too many service staff scheduled for turning around a much smaller number of beds.

Our client knew there were times when beds would be empty, but they couldn’t predict when those times would be or anticipate bed usage and turnaround times with accuracy.

When hospital administrators learned data analytics could provide a solution, they were interested in pursuing it. 

Unfortunately, the data needed to conduct a proper predictive analysis existed within several disparate systems throughout the hospital. The hospital’s own IT department had no easy way of collecting or using their data. Stretched to capacity with the daily operational tasks, the hospital’s IT experts didn’t have the bandwidth to build a new solution.

That’s when the hospital decided to hire a data and analytics partner to help them streamline and use their data to unlock insights into optimizing staffing and anticipating hospital bed utilization.

Solution

Wimmer’s data and analytics expert met with hospital administrators and listened carefully, asking a number of questions to understand exactly what the hospital hoped to resolve with their data and analytics initiative. 

More specifically, administrators hoped their data would help them:

• Improve patient safety and satisfaction 
• Serve a greater number of patients
• Increase revenue

The expert from Wimmer then developed an action plan and assembled a team of experienced data professionals, including a data scientist, data analysts, data architects and modelers, and dashboard architects. 

The hospital also dedicated one of their own system administrators to work with the team and guide them to the right systems and data sources, namely:

• Historical patient profile data, including diagnoses 
• Hospital resource data, including: 
• Types of beds
• Equipment and supplies required for specific rooms and wards 
• Room schedules 
• Staff schedules

Using Azure Data Factory, MySQL, and Python, the team developed pipelines for collecting and integrating the data, then cleaned, organized, and centralized it.

Next, the team modeled data using MS Power BI. This would set a standard for using the data to achieve the hospital’s stated objective going forward. 

After data was modeled, dashboard architects constructed easy-to-use, predictive analytic visual dashboards so hospital staff could view real-time data, forecast future bed utilization, and recommend staff schedule adjustments, as needed. 

Finally, the team went the extra mile by creating dashboard “alerts” to notify floor managers when beds in certain wards needed to be serviced. The alerts gave managers time to readjust staff schedules. 

Innovation & Impact

By providing technical skills, expertise in business problem-solving, and program management experience to guide the project to completion, the team from Wimmer Solutions built a custom platform that enabled hospital staff to analyze relevant data and make informed choices on efficiently allocating and utilizing hospital resources.

The client was able to discover deep insights into improving: 

• Patient safety and satisfaction
• Bed utilization and revenue flow 
• Staff productivity and operating costs

In addition, the client achieved the following goals:

• Improved Patient Safety and Satisfaction: The custom data platform improved bed utilization, reducing stress on staff and ensuring timely patient care, which led to better patient safety and satisfaction.
• Boosted Business Revenue: By optimizing bed utilization, the hospital saw a significant increase in revenue, with a potential annual increase of $87.6 million.
• Increased Staff Productivity: The platform allowed for better staff scheduling, reducing stress and improving productivity, leading to a more positive working environment.
• Operational Growth: The integration and centralization of data enabled real-time insights and predictive analytics, allowing the hospital to make informed decisions and improve overall operational efficiency.