Thinking inside the box: Resourceful innovation helps solve a growing data challenge

By Q-Centrix | December 3, 2021

What makes solving a critical customer need even better? When success is the product of resourceful innovation.

Some business leaders have likened resourceful innovation to thinking inside, rather than outside, the box. It’s the idea that using what you already have fosters greater creativity for problem-solving and may work better than creating something new. At Q-Centrix, we simply view it as using the best approach for the challenge at hand—and sometimes leveraging existing resources in new ways is superior to creating novel technologies and processes.

“I think we can all agree that health care is ever-changing. So, we must constantly adapt to remain at our best,” asserts Connie Cook, Q-Centrix Director of Customer Success. “When there is no manual for what you are trying to do, which is often the case in clinical data management, innovation and resourcefulness go hand-in-hand, and are arguably necessary for ongoing problem-solving and sustainable improvement.”

But resourceful innovation doesn’t happen by chance. And Connie notes that the inspiration often comes from the customer—or partner, as we say at Q-Centrix.

“It all starts with active listening to truly understand the problem the partner is facing,” explains Connie. “This includes homing in on specific challenges and the changes they want to see occur. It then becomes about focusing our creativity and experience on coming up with the best possible solution.”

When a Q-Centrix partner, one of the largest health systems in the U.S., came to Connie asking for help improving stroke care quality at several of its facilities, Connie had a hunch she’d need to get creative.

With a diverse background in health care—having worked as a nurse for more than 25 years, a coordinator of clinical trials of various experimental drug treatments, and a stroke program director for Nashville-based HCA Healthcare prior to arriving at Q-Centrix—Connie possesses first-hand care delivery experience and a firm grasp on evaluating what is and isn’t working.

“One issue that many facilities face is that case data collected for stroke center accreditation maintenance is reviewed retrospectively,” Connie points out. “In other words, performance insights can be weeks or months old by the time clinicians are trying to act on them. Concurrent review, on the other hand, can have a greater and more-immediate positive impact on clinical performance.

Several studies, like this large investigation of measures compliance and stroke center certification using data from more than 29,500 stroke cases at nearly 50 North Carolina hospitals, have concluded that continuous, real-time monitoring of care is critical to ongoing clinical performance improvement.

“From working with a partner community of more than 1,200 hospitals, we know that the quicker the data can be interpreted, the more valuable it will be to the facility and the more confidence the clinical team will have in it,” adds Connie.

For the partner with the sites underperforming in stroke care, the limitations of retrospective data review were thwarting top performance. Specifically, data collection occurred one to two months after the patient was discharged from the hospital. A lack of timely visibility into performance hindered the partner’s efforts to recruit physicians and grow these stroke programs. Also, the stroke coordinators were spending most of their time managing data for quality reporting, and therefore had difficulty focusing on process improvements.

The “light-bulb” realization for Connie and her team followed several conversations with the partner’s divisional VP and a thorough review of the underperforming facilities’ stroke data processes: The status quo in stroke data management and quality improvement was widely lacking a more-current approach.

However, retrospective data review was the predominant model used by the partner health system’s stroke programs at the time. Supplanting it with a concurrent model or adding concurrent review as a parallel process would be logistically and economically prohibitive due to the resulting significant operational disruption. Connie foresaw an alternative that would combine the models.

“At Q-Centrix, we have the team and technology for concurrent review, and we perform it within particular service lines and for many of our partners,” notes Connie. “At the same time, since retrospective review is used for reporting in most regulatory and voluntary quality reporting programs, the majority of our data abstraction services employ a retrospective model. For the system with the underperforming stroke programs, we said, why not combine the two approaches into a workable, cost-effective hybrid model?”

Since the concurrent-retrospective hybrid model would be an innovative approach, Connie vetted the idea internally first. Among the key questions she sought to answer:
• Could the Q-Centrix concurrent workflow be adapted for stroke care?
• Is there enough expertise on the Q-Centrix team from a data management and stroke service line standpoint to design an effective hybrid model?
• Would the hybrid model offer enough efficiencies and return on investment to be cost-effective?

The answer to all the above was an enthusiastic yes. Connie went back to the partner with a hybrid model proposal. This included an overview of the adjusted data management workflow and use of the Q-Centrix core technology for immediate visibility into facility performance.

Connie notes that the efficiency of the hybrid model is most obvious in the workflow. When the abstraction team performs the concurrent review, they also enter the data for retrospective analysis instead of entering it separately for each, saving up to two hours in data management for every stroke case. Some of the underperforming facilities saw as many as 350 stroke cases a year, which translates to more than 700 hours saved annually. This proved to be the proverbial panacea that made the solution feasible for the partner.

The following are distinct characteristics of the Q-Centrix hybrid model:
• A concurrent review workflow for real-time performance-data capture.
• Reporting capabilities for immediate performance assessment and visibility of improvement opportunities.
• Highly skilled abstraction with a focus on complete and accurate data collection.
• Alleviation of data management burdens on stroke program coordinators so they can focus on frontline support and education to enable the highest standard of care.

Connie describes the hybrid model as the best of both worlds. The concurrent component provides real-time performance review that allows the program coordinator to ensure best practices are met while the patient is still in the hospital, such as confirming an antithrombotic is delivered at the appropriate time, and a statin is prescribed before discharge. The enhanced retrospective capabilities like exception reporting helps attribute missed care measures, or fallouts, to a particular unit or clinician—which is a distinct feature of the Q-Centrix platform.”

In less than two months following the launch of the hybrid model, the partner began reporting saved fallouts and expressing delight with the outcomes.

Doubling down on her team’s resourceful innovation, Connie poses the question: If the hybrid model can work in stroke, why can’t it for other areas, like trauma and cardiovascular lines? Hearing of similar struggles from hospitals and systems that partner with Q-Centrix in these other areas, consideration of additional hybrid models is already underway.