Time to SMAC the Healthcare Consumer

SMAC – Social, Mobile, Analytics, Cloud – is a popular framework for optimizing business performance through IT. The basic idea is that these four elements all play key roles in generating value from data through capture, storage, and application.

• Social refers to the consumer or end-user level, where data is created and collected
• Mobile describes the shift to smartphone and tablet-driven computing
• Analytics speaks to the growing ability and need to interpret and understand data big and small
• Cloud refers to the advent of virtual computing through untethered storage and access to data, applications, services, and more

Compelling visions are emerging about how SMAC might be applied to improve the delivery of care. These generally describe a connected patient population that is actively and passively generating new health and behavioral data that are captured through an array of apps and sensors. These data are funneled and blended into algorithms that can suggest trends or predict medical needs, which can then inform appropriate patient engagement. A wide range of specific clinical applications also bubble up from this process, from care alerts and medication reconciliation, to rules authoring and risk scoring.

In theory this sounds great. But of course, there are several obstacles to making it work.

Lately, a different vision of SMAC seems to be emerging in healthcare, focused on the consumer rather than the patient, and the marketing rather than the clinical. Some of these business-oriented applications may look something like this:

• Social: Advanced use of social media as an interactive brand and rich source of insight on consumer preferences and trends.
• Mobile: Tools to help consumers navigate the healthcare system the same way we look for movie tickets or deposit checks: with our phones.
• Analytics: Using population data to understand linkages between people (make of car, marital status, education, vocation, social media presence) and their tendencies (paying for a wellness visit, missing appointments, using digital tools, writing online reviews).
• Cloud: Virtually everything that everyone does is captured and sent into a cloud, from web searches and click patterns to credit card purchases and retail behavior.

If this seems more like futuristic fiction than reality, consider what your smartphone is tracking. After a recent trip to the local coffeeshop, my phone sent me a note of exactly where I had parked, based on Google’s ability to interpret patterns of passively generated geolocation and accelerometer data.

Are We There Yet?

An article about the digital dust left behind by consumers recently made the rounds online, generating excitement about some of the potential applications of all of this non-health data. It pointed out ideas such as clinical trials eligibility, or public health surveillance. Such uses read well in the press, but others don’t, as MedSeek found out in June. The article also goes into detail about how such use cases are being built at UPMC. The Pittsburgh health system has mined, bought, and mixed census records, claims, prescriptions, utilization, household incomes, education levels, marital status, race, number of children, number of cars, and more. They have created correlations to predict people’s use of services, though they claim not to use those correlations to alter care delivery today. Since UPMC has rolled out its own narrow network plan, does the collection of this information cross a line – will it be used to determine the relative risk of a patient and his or her family when signing up for insurance?

Has Data Ethics Caught up with Data Collection?
The elephant in the room here is if we are ready to openly acknowledge and condone these practices, or if there are still some questions that need answering. To name just a few: If these correlations lead to differential treatment based on disease or age, is this just a watered down, post-reform version of pre-existing conditions? What are repercussions of a company acting based on correlations to someone’s race or gender? Are some of these data falling through a HIPAA loophole? Does it make sense to develop a disclosure or data consent policy here, or even to set rules on which data can be collected and how they can be used? Finally, while efficiencies are needed in healthcare, is it worth feeding giants like UPMC, a non-profit with $10.2B operating revenue, at the potential cost of consumer privacy and autonomy?

While the debate about civil rights continues, consumers may be past the point of outrage, thanks to a rolling banner of stories about how much data about us is being used without our permission. NSA’s surveillance and Facebook’s mood manipulation are treated with a headshake and a shrug. Even if this attitudinal shift serves as a weak thumbs up from consumers, HCOs may still be wary of losing their brand standing in a fiercely competitive marketplace. UPMC and Highmark’s turf war, for example, is so entrenched it has generated its own About.com page. Perhaps too there is a correlation between a person’s likelihood of voting with their feet after a PR crisis, and their education, affluence, and level of health.

Data Talks, But Who’s Listening?
While HCOs have shown some reluctance to SMAC their consumers to shift their operations, others have moved forward. Pharma and medical device manufacturers have been studying us for decades, trying to understand our preferences, what we watch on TV, and where we eat. Now they follow what we’re doing online. Digital agency and social media analytics firm WCG has become adept at monitoring and analyzing data on millions of individuals on behalf of their industry clients, with the end goal of connecting the dots between what people are saying online and what they may be doing in real life.

“We can map patient journeys through various therapeutic areas, based strictly on the social exhaust we are picking up on people,” said Greg Matthews, a managing director at WCG and creator of the MDigitalLife project. Referring to a recent project to track online discussions of cancer, he explained further, “What we’re able to do is look deeply at conversations online, related to a diagnosis, ascertain language using NLP, and understand where they are in the patient journey, from pre-diagnosis to post-treatment.” Matthews also noted that while doctors and individual providers have been active in these conversations, hospitals and health systems have been missing thus far.

While some applications of SMAC may appear controversial, others are simply convenient. Thanks to innovative tech companies, HCOs are able to subtly leverage consumer data to help business, without compromising their integrity. iTriage and Axial Exchange can leverage GPS to define geographic boundaries for lists of providers and facilities. Virtuwell and AskMD are proving that people are willing to divulge their PHI straight into a computer (and pay for it out of pocket) if it gives them better access to care. HCOs are paying all four of these companies to help them rein in patients by giving them something useful.

With tight market competition and a macro shift towards value-based care, the value proposition for using consumer data intelligently has become clear. HCOs now have the means to capture, understand, and act on data about people based on the digital footprints they leave behind. Early applications have been limited to tighter network management and customer retention through apps like iTriage. The next wave of applications is right around the corner, led by systems like UPMC and vendors like MedSeek: selective marketing of services and programs, more sophisticated utilization management, and some degree demographic/socioeconomic targeting. As we collectively become accustomed to this new normal, look for HCOs to begin taking on consumer engagement with an all out SMAC.