The moments leading up to surgery are often emotional for patients and their families. Waiting for the doctor can be a nerve-wracking experience, one that’s compounded if complications throw a schedule or operating room availability into disarray.
“Delays cascade, and patient anxiety increases with waiting, so their experience is much better when things run on time,” says Cara Martino, RN, enterprise business intelligence manager for Jefferson Health, which operates 14 hospitals, as well as outpatient, urgent care, rehabilitation and imaging facilities, in Pennsylvania and New Jersey. “Every minute in the OR is very costly, so saving time saves money for both the hospital and, ultimately, the patient.”
Looking to get in front of the problem, early last year, the Philadelphia-based organization started tracking data on the factors that impact on-time starts for the first case of the day in its operating rooms. It implemented Qlik Sense analytics and visualization solutions, which help to capture clinical and financial data from electronic systems throughout the organization, including its new Epic electronic health record and its legacy EHR.
Today, more and more provider organizations are turning to data analytics and visualization tools to get a better sense for how, where, when and why resources are deployed, with an eye on improving operations management, workflow, and patient care and satisfaction.
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Start Hospital Off on the Right Foot with Data Tools
Getting clinicians involved early is vital to the success of any analytics project, says Cynthia Burghard, a research director at IDC Health Insights. IT needs to know what practitioners want to accomplish with the data and the best way for them to receive it.
“What I hear most often from people who have worked on analytics initiatives is, ‘It was really hard to get the right data in place and figure out the right output,’” Burghard says. “Get everybody at the table as soon as possible.”
Likewise, Martino says that definitions need to be standardized from department to department, key metrics must be identified, and users need education to get the most out of such efforts.
“There’s a steep learning curve for users, but we help them climb it,” she says. “We have the analytics tools that will help them change what they do for the better, and they all want that.”
Interactive dashboards are helping clinicians and staff hone their processes in the OR. As a result, Jefferson Health has increased on-time starts by 25 percent, improved patient satisfaction and realized savings of nearly $300,000 a month.
The tools have also helped the organization reduce the time that patients spend on ventilators in intensive care units, lowering the risk of ventilator-associated pneumonias, Martino says. The healthcare system also uses Qlik Sense on its EHR to aggregate and track opioid orders and provide clinicians with interactive reports to help them control overprescription of the addictive drugs.
“Using analytics, hospitals are finding out who does it best, whatever the procedure or treatment, and making that the standard, improving care across the institution,” Burghard says.
Data Improves Emergency Flow at CHRISTUS Health
Similar to Jefferson Health, Dallas-based CHRISTUS Health turned to analytics to better manage patient care flow. Using a robust analytics setup that included Informatica solutions such as B2B Data Exchange, Data Quality, Master Data Management and Power Exchange, CHRISTUS has reduced average patient stays in its emergency rooms up to 60 percent, says Lauren Bui, vice president for data management and analytics.
“We were able to provide a full view of patient throughput and quality of service,” Bui says. “Through the dashboard, clinicians and administrators not only saw historical data, but also could drill down to individual patients and how they were doing hourly.”
CHRISTUS is still involved in the substantial groundwork necessary to use its analytics tools to their full potential, Bui says. The task is complicated by the fact that CHRISTUS has grown through mergers and acquisitions, bringing together many disparate systems.
To that end, CHRISTUS staff currently spend more time cleansing data than working on data visualizations, she says. “But these steps are essential if you want the analytics to be right in the end,” Bui says. “The view provided by analytics translates into more continuity of care, which is going to mean better care and outcomes for our patients.”
Massachusetts General Taps a More Transparent Culture with Data
At Massachusetts General Hospital in Boston, data analytics is all about boosting performance, says Andrea Tull, director of reporting and analytics, quality and safety management.
“The technology has definitely helped us up our game in quality improvement,” she says. “Mass General has always been a data-driven institution, but analytics allows us to leverage the data to answer more targeted questions.” The organization has a robust data infrastructure based on information from its SQL databases. Tableau software provides another layer of analytics and interactive visualization.
“The technology has helped people see how they’re doing against specific metrics,” Tull says. “It’s created a more transparent culture and started conversations about best practices.”
The Clinical Impact of Data Analytics
Until recently, data analytics had been chiefly deployed to create reports on electronic clinical quality measures, Tull says. That enabled healthcare institutions to meet federal regulatory requirements around EHR use, but resulted in months-long delays before the analysis was shared with clinicians. As such tools shift toward more real-time reporting, the impact on clinical decisions will grow, she says.
“With enough data and artificial intelligence in your analytics, you can tell individual patients, ‘For someone like you, these are the most likely outcomes,’” Tull says. “As we develop more ways to quantify and measure health and healthcare, we’ll see better outcomes.”
The impact of data analytics on healthcare will only increase as the technology adds capabilities, she says. At present, analytics applications only offer ways to explore structured data, but tools on the horizon that work with natural language will support more focus on patient-reported outcomes, Tull believes. “AI applications will not only support the decision-making of clinicians but also allow patients a clearer view of their choices,” she says.
IDC’s Burghard agrees. “Since most data is retrospective, analytic tools always looked through a rear-view mirror,” she says. “New predictive tools create models that let clinicians intervene to prevent things like sepsis, morbidity and readmissions.”