Last time on our blog, we shared our vision of a new destination for healthcare – a place where proactive, data-rich relationships enable access to precise and personalized services at the patient’s convenience. We identified three key challenges along the journey, including prior authorizations, the emerging use of telehealth, and shortfalls in addressing the social determinants of health.
All of these issues have something in common. They are strongly correlated with the provision of low-value care that is either inappropriate, delayed, inaccessible, or too expensive.
But why? If we go one level deeper, we can uncover the true root of the problem: a fragmented and disjointed healthcare knowledge supply chain.
Just like the supply chains that put products on shelves and packages on doorsteps, the mechanisms that move healthcare insights are crucial for keeping payers, providers, and patients connected and informed.
When this chain is not functioning correctly, healthcare breaks down, resulting in higher costs, worse outcomes, frustrating experiences for everyone involved…and no further progress toward the new destination for our industry. Data is our fuel, after all, and we cannot move forward without it.
Fortunately, we do have the tools and capabilities to keep the knowledge supply chain up and running. But we need to reevaluate our current data delivery pathways and make the tweaks and changes required to make sure we are delivering comprehensive, appropriate, high-quality care everywhere it needs to go.
What is the healthcare knowledge supply chain?
During a recent industry roundtable, a group of pioneering healthcare leaders discussed the modern healthcare knowledge supply chain. It is the entire series of events surrounding the generation and application of any given piece of data.
Data travels through the supply chain as it is created, exchanged and aggregated, retrieved, curated, presented to the end user, and applied to a clinical decision. New data is then generated based on the results of that decision. That data flows through the same cycle, providing new insights to inform future actions, and so on and so on.
For example, routine A1C readings are fundamental for managing the health of diabetic individuals. A1C readings are typically created at a lab, sent to the EHR and/or a care management platform, retrieved by a clinical user, and presented to that user in a way that should enable them to care for their patient.
But sometimes data gets stuck along the way.
The latest information might not be pulled into the EHR in a timely manner, leaving the provider with outdated values to discuss during their next appointment. Or the analytics might not be sophisticated enough to put an A1C reading in context with the patient’s elevated blood pressure and recent weight gain to indicate a rising risk.
And even if that information is available, it might be buried somewhere in the interface – or there’s no good way to communicate with the patient once they’ve left the office – and the clinician misses out on something helpful before the patient ends up in the ED.
Connecting up the knowledge supply chain for comprehensive, appropriate care
Overcoming these challenges won’t be easy. Some of these chokepoints are deeply entrenched in our health IT infrastructure and care processes. It will require a continuation of concerted effort from payers, providers, technology companies, and regulators to remove the barriers and set the stage for robust, resilient data pathways.
The effort will be worthwhile. Instead of knowing that we have information without being able to use it, providers and patients will be able to seamlessly and proactively communicate to achieve better health anywhere and everywhere it’s needed.
Let’s go back to that diabetic patient with a recent A1C test. Keeping “better health anywhere and everywhere” in mind, we can even start the process at the patient’s home instead of a lab. The patient could use test their A1C at home with a smart monitor. The standardized data is uploaded directly into the provider’s EHR, where automated sensors identify an addition to the patient’s chart.
The provider doesn’t need to open the chart just to view the new information and figure out what it means. Instead, the new A1C reading is automatically synthesized and analyzed in context with the patient’s existing history.
If the reading is out of range or otherwise clinically significant, the clinician or case manager gets an alert that something might be wrong. They would also get a tailored suggestion about what clinical action might be most appropriate based on that specific patient’s history and care plan.
Providers using an integrated care management platform could easily use that touchpoint to send a message to the patient or schedule a quick telehealth check-in. Patients can view the changes to their own charts and prepare for the consult, keeping them informed and engaged. And none of it requires the patients to leave their own homes.
How do we build a better knowledge delivery system?
The solution will be a mix of technical, cultural, financial, and administrative improvements – many of which are already underway.
The movement toward value-based care has been steady and promising, successfully aligning healthcare providers and payers under the same set of patient-centered incentives. We will need to continue our momentum toward value-based care to provide the motivation and structure that make proactive, comprehensive, preventive care possible.
Next, we can take aim at administrative and systemic issues that often slow the delivery of care, including burdensome prior authorizations, restrictive telehealth rules, and poor integration of non-clinical socioeconomic services into the traditional care environment.
The last major piece of the puzzle is the technology to support a newly liberated knowledge delivery landscape.
Remote patient monitoring (RPM) devices and other home-based technologies can keep patients connected whenever and wherever they need to be. Providers, in turn, must adopt standardized and interoperable clinical platforms to accept, synthesize, and surface these new data points appropriately. And they need the analytics tools to help them continuously learn from their actions through meaningful quality reporting and performance reviews.
As we work together to solve these problems, picturing a proactive, highly automated, comprehensive healthcare knowledge supply chain will help us focus our efforts. With contextualized and accessible data fueling our journey forward, we will be able to achieve our shared goals and improve experiences and outcomes for all.
Download the roundtable white paper on the healthcare knowledge supply chain today!