Healthcare Data Silos: From Medical Tragedy to Opportunity of Accelerating Returns
A Forbes article on data sharing called the lack of it in healthcare “a medical tragedy of underappreciated dimension.” Certainly, many hospitals and healthcare organizations are working hard to integrate their various healthcare data silos into meaningful tools for improved patient care, cost efficiencies and business decision making – no easy task! Earlier this year, we wrote about closing healthcare data silos as a trend for 2017, a prediction we hope to see come to fruition, or at least begin to move a bit more quickly.
Within healthcare organizations, data resides in many different silos often organized by function or purpose, including:
Strategic planning silos
Market development silos
Service line management silos
Claims data silos
Various clinical data silos, including EMR data
Data Aggregation and Accelerating Returns
Metcalfe’s Law – a key principle underlying the concept and power of networks – states that the value of a network is proportional to the square of the number of participants (i.e. adding more people to a network increases value not linearly, but exponentially). Physician and informaticist John Mattison developed a variant to Metcalfe’s Law called Matticalfe’s Law. According to Mattison and Matticalfe’s Law, the value of data silos is very limited. Yet, when deployed in aggregate data silos yield a law of accelerating returns rather than a law of diminishing returns like the network effect of Metcalfe’s law.
Sounds like a pretty good idea for healthcare, right?
As those of us who’ve been working in data analytics for some time now know, data sharing in healthcare moves slowly. Healthcare systems are large entities with layers of cultural norms and systems. Change does happen, but only with focused and dedicated effort.
Barriers to Healthcare Data Sharing
There are many barriers to data sharing, and we’re sure you’re aware of them. Among the more common challenges are:
Privacy: Protecting patients’ health information is important. Sharing clinical data housed in various silos does pose risks and challenges to ensure privacy regulations are followed. However, it is possible to connect data silos for improved information sharing and data analytics.
Competition: Data is, justifiably, a competitive asset for a healthcare organization. From this perspective, sharing data across the healthcare ecosystem can be complex. Tools like public and private health information exchanges are helping to close this gap, albeit slowly. Healthcare organizations will need to look for ways to both share data for improved patient care within their communities and explore innovative ways to maintain competitive advantages such as strategies that align with healthcare consumerism.
Workflow: While you might often hear that technology is a barrier to integrating data silos, Soon-Shiong, a South African-born surgeon, medical researcher, businessman, philanthropist and UCLA professor who holds dozens of patents and is regarded as an influential healthcare entrepreneur stated, “The barriers [to improving healthcare with data] technologically don’t exist any longer…healthcare is falling behind other industries like banking and entertainment because it isn’t using the technology properly – and that’s a workflow management problem.
Culture: The biggest challenge we see with integrating data silos in healthcare is culture. This goes along with workflow, but is a larger issue. To some extent, it’s human nature to think that holding data will create more value. However, within a healthcare system, data silos result in less value for the organization’s bottom line, the patient and healthcare providers.
Benefits of Healthcare Data Sharing
The benefits to addressing the barriers to data siloes for improved data sharing across a healthcare system are numerous:
Patient care: First and foremost, the ability to have as complete a picture of a patient’s clinical data as possible is of great value to providers. From a macro perspective, having access to competitor data around a procedure can shed insights into how a healthcare organization might make improvements for better patient care and costs.
Business decision making: Data sharing can yield significant value when it comes to strategic business decision making. One example includes the ability to flag readmissions among data sets to work on strategies to reduce readmission rates, which hospitals are now penalized for by CMS.
Closing Data Silos: It Comes Down to Commitment
In the end, integrating data silos comes down to how much a healthcare organization is willing to:
Commit to the process of data integration, including major culture shifts and change management.
Invest in tools and technology for meaningful data integration and data analytics.
Address personnel issues related to data sharing.
Create a culture of transparency around data sharing.
Look for ways to collaborate around data within their healthcare ecosystems and innovate in new ways beyond data ownership for competitive advantage.
Gene Koch serves as INTELLIMED’s Chief Operating Officer and is a member of the INTELLIMED leadership team. In his free time, he loves to play golf, travel for pleasure and mentor students in several MBA business classes.
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