Google engineering too slow? Facebook too invested in the wrong data model to adapt? Are you kidding me?

Few things in my work life are better than finding mind-blowing information from other industries and figuring out the implications for healthcare.

I recently read a set of slides by Paul Adams, a user experience designer that worked at Google and Facebook.  Although Adams’ presentation had 224 slides, the main thesis was relatively simple and obvious. The best insights usually are. Adams pointed out that online social media applications create a single category of relationships, called “friends.” They put every social relationship in that one bucket.  Wife, college sweetheart, boss, party friends, kids …  all just “friends.”  In contrast, real-world social networks — the kind that humans have cultivated for millions of years — are characterized by various groupings of people representing different roles, life-stages and social contexts, with different levels of strength and trust.

Diagram from Paul Adams' presentation on Real World Social Networks

He described the research that shows that people typically have 4-6 different groupings of friends.  People typically have fewer than 10 strong ties that consume most of their communication attention.  They typically don’t have more than 150 weak ties.  They have many “temporary ties” that may influence their behaviors for relatively short periods of time.  He points out that existing social media applications create problems for their users because the users publish information intended for one group of people that ends up being received by others.  Like wild party pictures being viewed by your prospective employer.

I came across Adams’ presentation through a link from a CNN article by Dhanji Prasanna that tells the story of how Adams developed these ideas when he was part of a team at Google that was developing Google’s response to Facebook.  The CNN article explains that Google had an engineering culture and a technology infrastructure that made them too slow to develop an application that took Adams’ insights to heart.  Adams then left Google to join Facebook.  But, Facebook was deeply invested in the simplified one-big-bucket social graph at the heart of the system that now has 750 million users.  So, despite Facebook’s “hacker” engineering culture that allows it to develop applications rapidly, they were unable to solve their fundamental problem.  They eventually launched Facebook Groups, which is a superficial answer to the insight that people have multiple groups of relationships.  But, Facebook’s central “one-big-bucket” friends model was apparently deemed too risky to touch.

My eyes rolled.  Google’s culture makes them too slow?  Facebook can’t innovate?  Are you kidding me?  If only we could experience a tenth of the agility shown by those two companies in health care, which has long suffered from a powerful aversion to risk and change in both care delivery and information technology.

But, there are deeper connections between Adams’ insights about social networks and our challenges in transforming our health care system.

First, the health behaviors of patients are strongly influenced by their social networks. For years, health care providers, health plans and vendors of wellness and care management services have attempted to promote smoking cessation, exercise, healthy diet, compliance with medication orders, and other health and lifestyle behaviors by designing “interventions” that target individual patients.  A whole industry of “health risk assessment” and “predictive modeling” was built up to try to identify which individual patients to target.  But, such an approach has produced unimpressive results.  That should not have been surprising.  Decades old research about the diffusion of innovations has shown that lifestyle behaviors in a population change through social networks.  People follow the lead of the people around them.  Therefore, to be effective, wellness and care management programs need to be designed to work through those existing social networks.  We need to be targeting groups of people that are already connected, rather than just reaching out to individuals.  We need to be designing our communications and incentive approaches so as to augment and leverage our patients’ social networks.  To support such social-network-oriented clinical programs, we need information systems that capture information about those social networks and that are designed to interact with them.   But, when we examine the fundamental data model and features of the market-leading electronic health record (EHR) systems, such capabilities are nowhere to be found.  Those vendors, blessed with a large installed base, may be unable to make such fundamental changes to their systems.  Like Google and Facebook, the leading  EHR vendors may not be agile enough to address our emerging understanding of the importance of social networks that exist among our patients.

Second, the relationships between patients and care providers are types of social network relationships.  I call these care relationships.  When we talk about “accountable care,” we mean that some provider organization is taking responsibility for the quality and cost of care for a population of patients. When we talk about a “patient-centered medical home,” we mean a team of primary care physicians, nurses and other care providers proactively taking care of a group of patients. But, who exactly are those patients? We have developed some very crude primary care “attribution” logic that tries to derive care relationships from claims data.  But, we do a very poor job of validating such derived care relationships or proactively declaring new care relationships.  And we don’t keep track of changes in care relationships.  We don’t have established processes to inform the participants in those relationships when one of the parties determines that they don’t intend for the relationship to exist.  We don’t distinguish between different types of care relationships.  If a patient has heart failure and sees both a primary care physician and a cardiologist, we don’t explicitly declare which physician has the care responsibility for that patient problem.

Furthermore, the referral relationships among providers are also types of social network relationships.  As with Adams’ real-world social networks, these relationships among patients, primary care doctors, specialists, hospitals, home health care nurses, pharmacists, and others are complex and dynamic.   Yet, when you examine the systems we use to keep track of these relationships, they are primitive or non-existent.  Just as over-simplification of social network relationships has reeked havoc for social media users, so has over-simplification of care relationships, care responsibilities and referral relationships harmed clinical communications and accountabilities.  This deficiency ultimately reduces the effectiveness of care. As a result, patients are harmed.

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