From the Health Catalyst summit, some lessons learned to help make big data actionable for improved outcomes and better economics.
This past week in Salt Lake City, I spent some time at Health Catalyst’s Healthcare Analytics Summit. Why should an executive attend this conference? Not only is Salt Lake City
a beautiful location, but the conference offers a comprehensive view into how organizations are currently leveraging data and analytics, and how these use cases will mature and evolve to improve outcomes and enable true care coordination.
Many themes from the conference also align with the industry’s adoption of team-based care as the foundation for value-based care delivery models. I think this is because at this point in time healthcare organizations are struggling to bridge the gap between team-based care and population health. Ask any healthcare organization trying to apply analytics to explain what they need to change outcomes and performance, and they will tell you that above all else, the data needs to be accurate and actionable. For team-based care to succeed, we need to get the right data to the right players at the right time. Here are the key principles I took away from the Healthcare Analytics Summit that we need to embrace in order to make that happen.
Simplicity Drives Action
New technologies and algorithms offer administrators and clinicians new insights into care delivery, variation in protocols, and cohort comparative analysis. But for too many healthcare organizations, more data means more complexity. These data sets and their “outputs” can become overwhelming, requiring leaders to invest more and more resources to synthesize this data into its most direct and simple elements. Multi-variable equations are powerful, but stakeholders must target the data in the simplest form for it to be actionable. At our company, we’ve found that data-driven workflows must be patient-centered and focused on the job all stakeholders are trying to get done. We’ve always summarized this job simply: “How are we working as a team to help this individual get better?” This is the critical success factor for any population health initiative.
Right Player, Right Place, Right Time
Another challenge we see with the emergence of big data in healthcare is the inability to get data into the right hands. For example, we see all the time that provider organizations are given a claims data set, or that the organization has an electronic data warehouse (EDW). Provider organizations use these tools to see patient care delivery or protocol performance at the aggregate view. It’s not uncommon for this data to only be available to a handful of leaders or presented out of context to the provider teams and administrators. The data is valuable, but how does the organization get data-driven insights into the hands of clinicians and executives in real-time and in contexts where that data is most valuable? We’ve seen repeatedly that the most powerful use of population health data is real-time in the context of patient care, available to all stakeholders working to deliver care. Team members delivering care in different organizations and disparate settings need a meaningful way to coordinate, communicate, and measure their performance together.
A Deep-dive Into Specialty Pharma
A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.
Small Fire Before Big Shots
We think this evolution to actionable data is necessary but difficult. What can we learn from other industries where big data is being used? Best-selling business author and Fortune 500 consultant Jim Collins talks about looking for opportunities to take small, manageable shots before an organization makes a big bet – and especially before an organization is forced to take that big bet for its own survival. Taking small shots enables business leaders to calibrate their organization’s abilities with easy targets and make incremental progress before they make a risky commitment to a big shot. The lesson for healthcare? First, seek to gain a better understanding of your care delivery situation with simple, targeted solutions before you make big shots that require extreme investment, implementation and integration.
Find The Right Pace
For all this talk about big data, we need to acknowledge the reality of an organization’s readiness, and how quickly its employees can understand and execute on new information. Initiatives designed to present new care delivery models must recognize the “pace” with which the organization can adapt and move to a new paradigm. In healthcare, we know this cycle can be long due to security, privacy, technical, and clinical workflow considerations. Prior experience is a good indicator of current and future performance – which is further proof why taking small shots before big shots is so important.
Think “Action”
In my work supporting team-based care, I’m always looking to understand the state of play in the market, calibrate to our targets and identify the key differentiators for our solution. Big data’s potential is exciting, but we must ensure that data drives action in order to deliver the intended value of improved outcomes and economics. I found these themes to be useful principles from the talented speakers and participants at the HASummit. Well done, Health Catalyst!
