Data analysis has earned buzzword status, and healthcare isn’t exempt. Unfortunately, healthcare professionals face numerous hurdles when it comes to gathering, integrating and digesting data. Part of the issue lies with the disparate systems in which data is housed, while another is the lag time between various data sets such as clinical data versus payer data. During Modern Healthcare’s recent Virtual Patient Safety and Quality Conference, Conduent sponsored an expert panel with leaders of quality and risk management to uncover how they’ve integrated data and analytics to produce actionable insights for better outcomes.
The below panelists discussed how they use data to develop quality improvement measures that benefit the patient care their facilities provide. Our panel also covered how they integrate data and analytics into the daily lives of those serving their patients.
Daniel Gell. In his role as Market Director of Care Management at Adventist Health at Simi Valley & Adventist Health White Memorial, Daniel leads the performance improvement initiatives. Prior to Adventist, Daniel served as the Senior System Director of Population Health & Care Management at Central Maine Healthcare.
Clark Wheeler. As Director of Quality Management at St. Elizabeth Healthcare in Northern Kentucky, Clark oversees physician quality reporting, required regulatory reporting, best practice registries, service line-specific quality reporting, award program monitoring and reporting, and general quality data analytics.
Anna Daly. As Vice President of Data Analytics and Innovation at Conduent, Anna focuses on the expansion of clinical data management and business intelligence strategies to help clients understand the value of the clinical data and how this asset can drive change across the healthcare continuum.
Top 5 panel takeaways
Here are five best practices shared during the panel to help drive a culture of quality and safety across your organization. To get more insights, watch the full panel discussion.
1) Stay true to your organization’s mission. Use it as a guidepost to drive focus. For instance, St. Elizabeth Healthcare aims to provide the highest quality of care in its region, creating one of the healthiest communities in America. Clark shared that earning the CMS 5-Star Organization designation aligns with St. Elizabeth’s mission, so his team uses those parameters to guide its focus.
Each time a prospective project arises, they use a scoring system and methodology to discern whether each improvement will help their vision. If they determine that a project will drive better performance against CMS 5-Star rankings, then it ranks higher on their priorities list.
“One of the biggest issues is having too many priorities,” he explained. So, they set expectations and orient processes to overcome competing priorities and stay focused on those at a high level.
2) Report the same information on several levels. Clark discussed how his team reports as close to individual clinicians as possible, then at unit-, division- and facility-levels. Despite being monitored at various levels, however, each measure is prioritized and tracked in the same way. By sharing this data at every level of the organization, they’re able to highlight relevant outcomes to all. This aligns with one of Anna’s main pieces of advice: “Know your data and the audience you’re delivering it to. Find the right level of data to accelerate your objectives – whittle it down to the appropriate level for each audience.”
3) Use meaningful dashboards. Dan argued that doing so not only makes it easier to engage with frontline staff and get physician buy-in, but also to uncover gaps in patient care. One way he suggests making data more meaningful is to share both health and financial outcomes via dashboards. This is why his organization’s dashboards align payer and clinical data. By sharing prevented readmissions, for instance, they help frontline workers understand how their work not only supports positive patient outcomes, but also their organization overall.
Clark suggests creating dashboards that allow physicians to compare their own performance on any set of measures to a wider data set within their specialty. “Surgeons can learn from others’ outcome data which empowers the sharing of best practices and improvements in performance and patient care,” he explained.
4) Consider multiple perspectives and meet stakeholders where they are. Dan recommends taking a multi-generational approach to data education, reaching those from the resident level up to long-time nurses and providers. The most tenured and experienced ones, for instance, may be particularly skeptical about tracking and using data.
“They’ve dealt with changing requirements, regulations and reporting procedures multiple times, and many don’t think that it affects the quality of care,” he said. “Make it clear that all we do from a regulatory level and from the corporate structure down to frontline staff – all knowledge and understanding – still leads back to the better outcomes for the patients.”
5) Take a long-term view of data. Building data sets takes time – as much 60-120 days before you can see actual ROI on specific outcomes. And, as Dan noted, for ROI on a population health program, you may even need three to five years. This is partially due to clinical data being current while payer data comes later.
“Integrating those two data sets within at least several 6-month periods, while also aligning attribution, is tricky,” Dan said. He suggests focusing KPIs at a practice level rather than the provider level. The other critical element he pointed out was integrating those data elements with health information exchanges (HIEs).
“The potential and value [of HIEs] is absolutely amazing to health organizations and the patients they serve,” Anna agreed. “That sharing of data will be more important to all our organizations as we move forward.”
To get more insights from Clark, Dan and Anna, including Clark’s take on how to best partner with IT and collaborate with physicians to enable trust, watch the full panel discussion.