Elad Walach

Stop the Healthcare Scavenger Hunt

Sarah is a 45-year-old woman visiting her primary care physician with concerning symptoms. Her family history includes a list of devastating medical issues, so understandably, she’s anxious. Her physician suspects an underlying condition and refers her to a specialist. 

Sounds simple, right? Get an appointment with the specialist and a comprehensive care plan will be coordinated for Sarah. However, Sarah’s experience won’t be so cut and dry. Why? 

Healthcare fragmentation – the result of healthcare being provided across disconnected care systems, technologies and specialists. 

Sarah’s PCP sends her records to the specialist, but crucial details are lost in translation. Lab results are missing. The imaging reports are delayed. The specialist doesn’t have a complete picture of Sarah’s health.

As her diagnostics continue, each test and procedure generates its own set of results and reports. Yet these pieces of information remain scattered and inaccessible to her full care team. 

Sarah’s situation is by no means unique. One study found that Medicare patients alone “see a median of seven providers (two primary care providers and five specialists)” across four practices each year. Add onto that the fact that “the typical primary care physician has 229 other physicians in 117 practices with whom to coordinate care.”

The Scavenger Hunt: A Symptom of Fragmentation

The fragmentation of healthcare data and, subsequently, care delivery, isn’t a matter of information coming from disparate sources: it happens as a result of disconnected platforms that aren’t working together. The impact then trickles down throughout the health system. Technology systems, data and people are all fragmented in multiple places. 

This fragmentation, felt by both physicians and patients, takes us to an unnecessary and burdensome space for practitioners: the healthcare scavenger hunt. Due to a myriad of factors, primarily increased patient volumes and administrative burdens, clinicians are strapped for time, leaving little to no luxury for them to comb through mountains of patient notes and radiology reports to find information. This can manifest in many ways, but here are two I found staggering:

So how can technology bridge the gap?

How Enterprise-Wide AI Can Alleviate Fragmentation

AI represents the potential for improvement in healthcare delivery, aiming to help address the care fragmentation cycle that patients often experience. A big challenge is that we’ve been having the wrong conversations about clinical AI, utilizing its abilities as a single problem solution-solver rather than an architect that weaves disparate threads together to make data actionable, leading to increased interventions and improved patient outcomes.

Clinical AI has the ability to integrate disparate data sources, streamline communication channels and provide actionable insights at the point of care. This approach creates a one-stop shop to alleviate some of the problems that come with the fragmentation of healthcare delivery. AI has taken various approaches from single point solutions that address a single issue to marketplaces that provide a range of solutions under one umbrella. While there are still instances of success with the use case adoption method, a platform approach is all-encompassing for health systems looking to scale AI across the enterprise, empowering clinicians with all the information needed about patients, making treatments more accurate and the health system as a whole more efficient and connected while mitigating some of the risks associated with large-scale technology shifts in a health system. 

Take an example from Yale New Haven Health, in which a retrospective study revealed a 40% increase in administration of advanced therapies for PE patients at a spoke facility. This was made possible thanks to an all-encompassing AI platform that:

  • Notifies relevant PERT members of intermediate to high-risk PE patients, contingent on multivariable analysis (suspected presence on imaging, RV/LV ratio)
  • Secure text communications for care teams, including notifications about CT scans in real time
  • Streamlined communications between members of the PERT and increased collaboration between hospitals

The Health System Incentive

AI is becoming the nexus of information, empowering physicians to stop hunting and to work smarter and faster while, more significantly, enabling health systems to act promptly on powerful clinical signals.

With a clinical AI platform, a health system has the prerogative to choose how these problems are streamlined in a way that best suits them, including:

  • Which physicians should be alerted for a pathology
  • The timing of such alerts based on additional patient information 
  • The parameters underpinning the risk stratification
  • Interoperability. In other words, how AI integrates within native workflows and IT infrastructure (including PACS, EHR and scheduling, for example), not the other way around
  • Monitoring algorithm performance, capturing real-world data during its clinical use

In this, the AI platform would shoulder the responsibility of data aggregation, analysis, clinical signal identification and the activation of requisite interfaces. This symbiotic relationship underscores a division of labor that capitalizes on the strength of each entity; health systems steer the clinical direction while AI platforms provide the technological muscle to actualize these directives. This collaborative paradigm fosters a conducive environment for leveraging AI in healthcare, ensuring that the theoretical promises of AI translate into tangible improvements in patient care and systemic efficiency.

Reducing Fragmentation

Healthcare’s long standing fragmentation problem poses critical challenges, resulting in inefficient care delivery and potentially harming patient outcomes.

The fragmented nature of healthcare information poses significant challenges for physicians, leading to wasted time, increased administrative burden and a heightened risk of diagnostic errors. The deployment of a clinical AI platform offers a beacon of hope in this regard. 

Enterprise-wide AI represents a transformative solution that aims to integrate disparate data sources, streamline communication channels and provide actionable insights at the point of care. The promise of a better tomorrow in care delivery lies in embracing solutions that empower physicians and health systems to work more efficiently. 

Imagine Sarah’s journey through the healthcare labyrinth, but this time all of the physicians, facilities and systems are sufficiently connected, exchanging all crucial information. Her PCP and specialist would be synchronized with access to the latest information, ensuring that each step of her care journey is transparent and accessible. Sarah’s physicians all have a comprehensive view of her health and are now able to make the most informed next step possible. 

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Elad Walach