When Registries Aren’t Fast Enough: How Real-time Feedback Helps with Rapid Leaps & Hairpin Turns

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Megan S. Berlinger, MHA

When implementing new technologies, success sometimes hinges on how quickly and efficiently we collect, analyze and react to data.

In cardiology, new technology is key to both patient care and achieving a competitive edge. The cardiovascular leadership team must support pre-adoption decision-making, implementation and post-adoption assessment.

Pre-adoption

Industry often offers modeling resources that use the hospital’s own data to predict the financial impact of implementing a new technology. Practice leaders can use these tools in discussions with the C-suite about capital, human resource and operations needs. From a reimbursement perspective, the newer the technology, the greater the financial risk.

Implementation

The implementation phase includes a number of activities around training and operations. Often this period does not include proactive reporting because the priorities are supply/equipment acquisition, education and proctoring. The steps taken to ensure quality outcomes and accurate billing lay the foundation for post-adoption analysis.

Post-adoption

During the post-adoption phase, data analysis needs to transition from obtaining approvals to a glide path or impact analysis. Data tools are essential for updating the team on the impact of implementation compared with early projections and for ensuring quality outcomes. At Wake Forest, we use population definitions to help us cut the data to address different questions, often tailored to the technology. We typically focus on the following areas:

  • Clinical quality, including mortality, adverse events and other indicators applicable to the technology
  • Process/throughput quality, such as readmissions, lengths of stay, home healthcare utilization and time from identification to procedure
  • Accurate coding with CPT, diagnosis-related groups and so on, to optimize reimbursement
  • Denials: Reviewing denied claims confirms the revenue cycle is accurate and optimized
  • Financial impact, particularly the technology’s contribution to the margin and net margin to better understand its direct and total impact on the institution, including relevance to downstream patients (e.g., referrals to cardiothoracic surgery)

Hours every month could be invested in studying and sharing the impact of new technologies; each could have a dedicated dashboard. The sweet spot is efficient analysis that supports optimized operations.

Carrie Redick, RN, MSN, CCRN, talked with me about how the team at Atlantic Health System’s Morristown Medical Center, in New Jersey, found the sweet spot with post-adoption assessment of their transcatheter aortic valve replacement (TAVR) program. As the manager of the invasive cardiology, electrophysiology and structural heart care departments, Carrie was instrumental in executing “a hairpin turn” to reduce Morristown Medical Center’s TAVR length of stay from 8.6 days to next-day discharge. Carrie and her team figured out how to address the challenges of information lag that so many of us struggle with.

Source: Carrie Redick, RN, MSN, CCRN.
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Carrie Redick, RN, MSN, CCRNMorristown Medical Center, Atlantic Health SystemMorristown, N.J.
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Carrie, how do you approach post-implementation analysis for new technologies?

We have a comprehensive data department and traditionally have relied heavily on registries, which are a strong long-term tool for managing the post-implementation period. However, we found that registries weren’t providing the information we needed to impact operations in the short term. We needed a way to reduce the information lag inherent with registries, especially with our TAVR program.

Though we’re one of the highest-volume TAVR programs in the country, we recognized that we could improve our quality and financial outcomes. Specifically, we wanted to improve our lengths of stay. Rather than wait for registry data to make changes, we took two steps. First, we created intra- and post-procedural data-collection tools to help us know, immediately, if there was a complication or other factor requiring a longer length of stay. We wanted as close to real-time feedback as possible so we could make quick changes. And, second, with the help of an industry partner, we performed a financial analysis on our 2016 TAVR patient data. This drill-down allowed us to see trends. The results were clear—our lengths of stay needed to be improved.

Which data do you collect with the intra- and post-procedural tools?

With the intraoperative tool, we collect data on the team, the approach they used, safety as well as complications and any interventions deployed to address them. There is space for staff comments.

The post-procedure feedback tool is completed by critical care and/or the floor team. It focuses on vital signs, complications, interventions and the status of patient goals. This form led us to a key finding, namely that there were barriers to getting patients out of bed.

What was the impact, and how quickly did it happen?

It truly was a hairpin turn. In addition to moving from an average of over a week-long length of stay to discharging the next day, we are now below the national average on mortality and pacemaker implementation rates. Every data element that previously was above the national average is now below it.

What were the key variables to success?

One important decision was adding a physician leader, Philippe Généreux, MD, to help make the case for data collection to improve the TAVR program. We also networked with others who had been successful about their best practices. Sandra Lauck, PhD, RN, of St. Paul’s Hospital in Vancouver, came for a site visit and recommended the 3M [multi-minimalist modality] approach. We were able to tweak 3M to meet our needs and create a clinical pathway with expectations to meet goals in structured six-hour increments. Another key was having clear guidelines to measure against during data analysis. Our TAVR checklist includes specific data points.

It helps that our physicians and staff are extremely onboard with the process and that we added a clinical nurse specialist whose focus is on education for the service line. She took on the project, helped implement the operationalized pathway and collects real-time data from daily rounds.

Where did the initiative come from? Does your institution require post-implementation review, or do you drive it within your leadership?

We worked closely with Finance and Administration to reduce our lengths of stay. Meanwhile, I was taking a leadership development course and approached the chief financial officer of our system to mentor me. This opened the door for one-to-one discussions around TAVR finances. The first analysis was fairly discouraging; it was clear our lengths of stay had to improve. With TAVR (and other expensive new technologies), length of stay is a large opportunity for overall financial impact.

Beyond length of stay, are there other measures you tend to focus on during post-adoption analysis?

For us, the key to any measure is whether we can get real-time data. We monitored all of our measures but especially those that affected length of stay, such as complications. That focus led to interventions that improved our workflows and helped us identify educational opportunities and stakeholder context—what the front-line caregivers face in caring for TAVR patients.

For example, we found that a measure around getting patients out of bed post-procedure was lagging. When we looked into the reasons, we found that the ICU staff were concerned about groin site drainage and oozing, so we partnered with educators on the floor and in the ICU to make ambulation routine within six hours of the procedure.

How do you measure the so-called downstream impact of new technology?

We work closely with other departments to project volumes and partner with them on department budgets. We have manually collected these data at times but do not review it on a regular basis.

Based on your experience with TAVR, what lessons would you share?

The majority of our successes came from collecting real-time data. We had to shift our mentality from registry data with its inherent delay to internal data review. This required physician and staff buy-in and investment in the process.

We also try to hardwire the important items, such as a care team goal like getting patients out of bed or holding every charge before it goes out the door. These items must become routine and expected. The relationships with stakeholders are what make hardwiring and data collection possible, and they allow us to evaluate expected vs. achieved.

Last, celebrate your wins as a team. When we achieve goals, we all are proud together.

Megan S. Berlinger, MHA, is the business administrator for the Heart and Vascular Center at Wake Forest Baptist Medical Center in Winston-Salem, N.C.