By MARIE COPOULOS
I have been fortunate to spend a significant portion of my career working at the intersection of health care innovation and the foundational data that fuels new models. For those of us who have worked in this field for a long time, there is a certain pattern recognition that comes with this work, often in terms of exciting developments as well as common pitfalls. The challenge lies in the fact that these stumbling blocks, often apparent to those with experience in health tech, may not be readily apparent in the business and can even be met with resistance.
I will focus on pattern recognition, with the goal of identifying common stumbling blocks and, importantly, ways to address them if encountered.
Pattern #1: Lacking a Clear-Eyed View of Market Data Gaps
Key Question: Do you understand how the market you’re in informs your ability to measure your work and use data to drive insight?
For those developing models that aim to change the status quo, it’s essential to recognize that these innovations break from existing care and financial models with the goal of improvement. However, it’s common to overlook the fact that breaking from the status quo also breaks from the ways in which health data is captured and utilized. Therefore, understanding the availability and quality of data in your market space is crucial. It’s important to consider if the necessary data is available, or if adjustments need to be made to align with what’s accessible. Designing with intention is key.
Pattern #2: Accumulating Non-Technical Roadblocks
Key Question: Do you have a good handle on the non-technical challenges impacting your data business?
Today, business challenges are more likely to slow down technical progress than the other way around. Stumbling blocks such as data acquisition, partnerships, and strategic vendor choices can increase technical debt that hinders productivity. When working with new models and approaches, having good governance to address these issues together is crucial. Early consideration of who will tackle these challenges and make decisions is necessary.
Pattern #3: Lack of Focus
Key Question: Do you know what pieces of information provide disproportionate value?
Identifying the pieces of information that are disproportionately valuable for your business is crucial in the healthcare industry. This focus allows for consistent improvement in patient and clinician experience, in turn driving better outcomes. Until healthcare data becomes less inconsistent and messy, knowing what information is most valuable for your business is essential for effective resource allocation.
Pattern #4: Short-Term Wins that Don’t Build
Key Question: Do you feel comfortable with the tension between short-term wins and long-term wins and do you have an open conversation with your team on this topic?
Look for ways to build in small, additive steps to avoid short-term wins that don’t contribute to long-term progress. It’s important to consider if small projects will serve future efforts and to build partnerships that scale. Additive steps build momentum and capacity over time.
Pattern #5: Siloed Technical Teams
Key Question: Do you have a good sense of what motivates your team to solve hard problems for you?
Connecting with the mission and fostering a sense of belonging within the team can motivate technical team members helping to solve difficult problems in healthcare data. Understanding what drives and informs the team can make it easier to collectively address challenging issues.
Marie Copoulos, MS, is a public health professional and long-time health executive working at the intersection of analytics, population health, and climate. (She previously published on THCB under the name Marie Dunn).
