How Hospitals Use Analytics to Staff Up Before a Rush

Jennifer D’Angelo, CIO of Bergen New Bridge Medical Center, says the center is becoming a more data-driven healthcare provider. Photography by Colin Lenton

It’s why Tiwari has built a model that analyzes up to a year’s worth of historical surgery data and compares it to scheduled elective surgeries for each of the next 30 days. It also accounts for potential last-minute emergency surgeries because VUMC, located in Nashville, Tenn., is a Level I trauma center.

Through predictive analytics, Tiwari is able to estimate daily demand for surgery to within seven cases of the actual number 80 percent of the time. Operating room managers automatically receive reports each morning that show the latest surgical caseload projections for the next 14 to 30 days, which enables them to make staffing adjustments as needed.

If the model predicts that the case- load is below expectations for a few days during the next two weeks, managers can reduce staffing levels on those days, Tiwari says. 

MORE FROM HEALTHTECH: Discover how predictive analytics applications are changing oncology.

Data Analytics Predicts Number of Daily ER Visits 

Envision Physician Services, a Nashville, Tenn.-based multispecialty medical group providing care in more than 900 facilities nationwide, has built a web-based application that can accurately predict the number of expected daily emergency room visits with an accuracy rate of 80 percent to 85 percent.

The tool can also forecast what time patients are expected to arrive, what ailments they will have and what services they will need, says Dr. Kirk Jensen, Envision’s chief innovation officer.

Housed in the public cloud, the app automatically grabs patient data from the company’s billing system and physicians’ schedules from the company’s scheduling software and stores the data in a Microsoft SQL Server ­database. The app uses Microsoft’s Power BI software to run reports. 

“Physician and operational leaders have the ability to make sure our capacity is matched against patients’ needs,” Jensen says. 

Executives can review the reports to validate their current schedules and shift budgets if necessary. During the year, if something changes, such as significant population growth, a demand spike from flu season or a desire to change hospital processes, they can run the model again to see how capacity and workflow are affected.

Envision released the app in early 2019, and about 50 to 100 emergency department partners now use it to forecast physician staffing needs. In the coming years, Envision intends to share the app with the several hundred other emergency departments it supports. 

For now, the app makes a big difference. “We can schedule the right type of clinician and the right number of ­clinicians to match incoming workflow needs,” Jensen says. “It ensures that ­­clinical quality remains high. It improves flow, and we avoid long wait times.”

MORE FROM HEALTHTECH: Find out how AI Is helping predict and prevent senior falls.

Bergen New Bridge Invests in IT Modernization

In New Jersey, a $20 million IT modernization effort has allowed Bergen New Bridge Medical Center to become a more data-driven healthcare provider, D’Angelo says.

In 2017, Bergen deployed Dell EMC’s VxBlock converged infrastructure, which features Dell EMC Unity all-flash storage, Cisco UCS B-Series servers and switches, and VMware software. The hospital also upgraded its network with Cisco Nexus switches, wireless controllers and access points, and Palo Alto Networks firewalls.

The facility, which used to have spotty wireless access, now has full Wi-Fi coverage throughout. The company also invested in new Lenovo desktops and notebook computers and new applications, including a major electronic health record upgrade, to support the hospital’s data analytics goals.

“Stabilizing and modernizing our network created the foundation we needed to move forward, to go beyond looking at data and move toward creating effective ways of analyzing it,” D’Angelo says. That progress, she adds, is critical for advancing interoperability.

During the past year, Bergen has integrated its EHR with the New Jersey Health Information Network, which provides access to patient health records from other healthcare providers. Now, when patients are admitted to Bergen’s emergency room, clinicians can quickly see patients’ medical histories.

The hospital will invest in a data warehouse in 2020 to pool data to bolster its predictive analytics efforts, including the ability to predict staffing needs in advance.

“We’re not quite there yet with the data automation,” D’Angelo says. “But access to data and real-time decision-making and having that predictive analytics component is in our future.