By Emily Griese, PhD, Director, Population Health, Sanford Health & Associate Scientist, Population Health, Sanford Research
Technology continues to propel the healthcare sector forward. Consider the advents within healthcare data: long gone are paper charts filled with unintelligible provider notes, instead our EMRs and various data sources backfill warehouses with terabytes of healthcare data. Data mining techniques and the introduction of artificial intelligence provide the capability of developing not only predictive but prescriptive models – with algorithms capable of near certain (data-based) prediction of patient risk and optimal pathways to mitigate those risks.
These technological advances are pivotal for providing direction and innovation in the midst of a shifting healthcare sector, from volume (per click reimbursement) to value (population-based reimbursement). Yet, in the advent of disruptive technology, including our capabilities in data-driven healthcare, we have yet to experience a subsequent disruption in patient and community health outcomes. That is, while technological advances including the next best predictive algorithm are growing in specificity and applicability, these advances seem to be outpacing healthcare’s ability to leverage them effectively and impact fully, with measurable population-based health outcomes.
As healthcare continues to shift from volume to value – the need to identify outcomes early is crucial.
This should not come as a surprise to those of us engulfed in the day-to-day of healthcare. We’ve all been there, having dreamt up the next best advancement for our organization, working tirelessly to bolster the right support to push it forward with urgency and impact. Then the real challenge, integration into operations. How does the next best idea become integrated within the broader clinical flow of everyday health care delivery? This becomes even more difficult when we set out to effectively evaluate and to build sustainable, scalable processes around it. Similar to most tech vendors or forward organizational thinkers who appear to have the “solution”, the difficult work comes in putting it all into action. There is no shortage of ideas for predictive models, best practice alerts, or the next best machine learning algorithm. However, in standing up new technology, we often miss the mark in shifting the culture behind the tool – to make it effective, meaningful, and impactful for our patients.
The Institute of Medicine (IoM) defines a learning healthcare system as one where, “science, informatics, incentives, and culture are aligned for continuous improvement and innovation, with best practices seamlessly embedded in the delivery process and new knowledge captured as an integral by-product of the delivery experience.” Unfortunately, building a culture that collaborates early and often in the development, implementation, alignment and testing of new technology is a mountain most healthcare systems continue to face. Yet, in my experience working alongside healthcare administration, technology leaders, data analysts, researchers, and providers, there do seem to be effective ways of overcoming these barriers. The approaches are not earth-shattering, yet if done with intention as part of the early strategy, they may assist in breaking down the barriers for uptake and impact – those standing in the way of truly impactful technological advancement and a radical impact on the health outcomes of our patients and communities.
Communicate and collaborate. Bringing together multiple champions and perspectives not only to the technical build of an algorithm, for example, but for the potential application and ultimate goals of the tool needs to occur early in the process and consistently thereafter. Not everyone is a data scientist or tech expert, but everyone brings a unique perspective to the complex issues facing healthcare delivery. There needs to be a purposeful openness to recognizing and listening to other’s points of view very early on in the process. We’ve all been there, it’s difficult to bring in various stakeholders with impossible calendars and workplace dynamics that stand in the way, however, the upfront work is pivotal for success in backend implementation and impact. I’ve learned in more failures than I can count that identifying champions early on, long before your first data model, and keeping them close through consistent and appropriate communication is pivotal. Your executives and C-suite may not need to see the code behind the model, but they do need to be bought in early on around the need and ultimate goal. Building a tool for a perceived problem only to find out providers or healthcare leadership don’t perceive the same issue and need sets both sides up for failure.
Measure meaningful impact. Gone are the days of starting a project or employing a new tool with the assumption it will work with no outcomes backing it (at least I hope!). We have a responsibility with technology and tools built to measure impact. Technology for technology sake has come and gone, very few organizations can move innovation forward without impactful ROI– and not just dollar signs, the patient outcomes associated with it. Early on, work to identify leading indicators – those that show long before the often lagging outcomes that this solution might be working. As healthcare continues to shift from volume to value – the need to identify outcomes early is crucial.
Build alignment. Technology built for alignment – with the capability to be communicated and utilized across payers, providers, and patients – will be ahead of the game in a shifting healthcare environment. Coordination underlies healthcare success of value-based care; unfortunately, it’s still difficult to find technology solutions that assist in meeting this need. From benefit design to payer coverage to physician communication, all levers work together to move patients along with their health continuum. Tools and technology that recognize these multifaceted environments surrounding healthcare will be leaps and bounds ahead of those in silos, with singular approaches.
As the idea of value over volume inundates the healthcare sector, the success of disruptive technology hinges on its ability to provide direction and impact in the value shift. Unfortunately, we can miss the boat on leveraging technology for meaningful impact because we overlook foundational steps: collaboration and communication, measuring meaningful impact and building alignment across multiple facets of healthcare. Technology has the potential to be the catalyst for much larger cultural shifts to occur. Because of that, healthcare’s ability to leverage technology will always rely on leaders – administrators, providers, and innovators – to build a meaningful foundation to thoughtfully bring technological advances into action and impact.