The sets of technologies people use are now so integrated into their lives that they have become a part of their identities. Data captured in the digital and physical worlds, along with related data sets (e.g. demographics, sociographics), can converge to create a technology identity for an individual. Healthcare leaders can use people’s technology identities to create a new generation of offerings and experiences.
The digital revolution introduced technology identities as part of an emerging feedback loop, one that first began to show potential via personalization efforts. Thanks to ecosystem connections, healthcare organizations are increasingly using these identities to deliver more personalized and individualized services. For instance, Kinsa’sconnected thermometers let customers track their fevers via a smartphone app; Clorox paid to license the information, using it to direct ads to US ZIP codes where people had more fevers (and potentially more need for disinfecting wipes). No personally identifying information was ever shared.1 Now, in the post-digital era, organizations have greater opportunity to use technology identities and insights to shift from one-off transactions to ongoing customized relationships with individualized experiences.
Healthcare leaders can use people’s technology identities to create a new generation of offerings and experiences.
When healthcare organizations gain the ability to create one-to-one relationships with individual healthcare consumers, they become each individual person’s ongoing, trusted healthcare partner. Organizations will achieve this by understanding the technology people use and how they use it, creating the insights needed to integrate seamlessly into the person’s life.
Who are we serving?
Healthcare has an ongoing data stream from medical records, technology devices, claims, past preferences for services, biology and more. This data is the cornerstone of delivering personalized healthcare on a person’s own terms.
Imagine if a healthcare provider has a “digital phenotype” for every patient3—one snapshot that captures indirect healthcare data from technology-based interactions (e.g. online search history, app usage, social posts) and correlates it with health events. The digital phenotype has the potential to help providers predict health-related behaviors and risks and also diseases for that person and others like them.
For example, a multinational technology company partnered with an academic medical center to examine the health relatedness of searches in the remote past and within seven days of an emergency room visit. Interestingly, more than half of those who participated in the study had searched online for content related to their chief complaint within the week prior to their emergency room visit.4 By tapping into people’s digital phenotypes, providers and other allied health organizations can anticipate needs and intervene with care at the time of need, potentially preventing an emergency room visit.
The digital phenotype has the potential to help providers predict health-related behaviors and risks and also diseases for that person and others like them.
Imagine if providers could use a person’s digital identity to deliver care in context—even beyond traditional location-dependent care settings. When shopping, an app could tell a person with chronic lung disease (i.e. COPD) that it’s time to sit down and take a break. When walking into a restaurant, a mobile alert would inform the individual of healthy meal selections to consider on the menu. Each environment provides an opportunity to use those moments that occur to add value in context of health.
Clearly technology identity presents amazing potential for detecting the need for care at home (or on the go) and delivering care where and when people need it, but it also has some pitfalls when it comes to capturing information while maintaining individual privacy.
Clearly technology identity presents amazing potential for detecting the need for care at home (or on the go) and delivering care where and when people need it.
Trust is the foundation
There is a gap in expectation between how healthcare is delivered today and how patients think it should be.6 People want their needs met, but they also want control over their privacy preferences. And as healthcare organizations strive to meet these needs, they must understand that the line between “useful” and “creepy” will vary for each person.
Technology can allow healthcare enterprises to maintain ongoing, experience-driven relationships with individual consumers in ways that were impossible before. But the possibilities come with new ambiguity and complexity—tailoring offerings and experiences to the individual also means figuring out just how much tailoring to do in the first place.
Among them, healthcare organizations must recognize that there are times when consumers want more technology in their lives, but also times when they do not want it at all. Understanding this dynamic is critical to successfully creating ongoing, intensely individualized relationships with consumers.
Healthcare organizations across the ecosystem must proactively take steps to earn trust with consumers by being clear about their intentions related to data privacy, data stewardship and consent. These steps include making sure data is clean and its origin is known. Physical devices must have proper security embedded. Products and services must be designed with privacy in mind. When organizations make privacy a priority and communicate the actions taken, they will build trust and loyalty among increasingly discerning healthcare consumers.
of healthcare IT and business executives believe that digital demographics give their organization a new way to identify market opportunities for unmet customer needs.
of healthcare executives believe that consumers’ digital demographics (vs. traditional demographics) are increasingly becoming a more powerful way to understand their organization’s customers.
Mental health care meets smartphone
Mindstrong uses artificial intelligence and remote monitoring to continuously measure cognitive function and mood, allowing providers to detect changes and intervene at critical times. Digital phenotyping collects data from a user’s smartphone to provide measures of cognition and emotion. Mindstrong uses machine learning to identify which digital phenotyping features might be most useful to clinical assessment. The company has a patient-facing app that allows users to access help through their smartphones, and a provider-facing app that augments care models.