The ‘So What’ Interface – a Prescriptive Layer

When we see a calendar, we know what the information means, and readily map this to potential action-taking. This is not as clear with data displayed from the new era of the Health Internet of Things - the increasingly ubiquitous information climate of consumer biophysical monitoring and quantified self-tracking that surrounds us.

So far the main focus has been on Apple-y/iOS-y design and data visualization in health data streams such as 23andMe genomic data, Fitbit data, the Eatery food diary summarization data, or EKG data tracking across a smartphone screen when held up to the chest. However, we are all still scratching our heads as to what to do as a result of seeing the information.

The Prescriptive Interface
A whole new conceptual category of ‘what to do with this data’ needs to be articulated, named, and implemented – an intuitively-apparent prescriptive layer of suggested action-taking as a result of viewing the data. The two biggest challenges are first, these data streams are only nascently available and therefore meaning has not yet been determined in many cases, and second, there is little effort in determining and implementing a core set of principles for behavior influence and ambient suggestioning. Having these challenges solved could help constitute what is missing in the health data streams but not the calendar – knowing what the information means and what action to take as a result.

The Rapid Approach of the Health Internet of Things

The efforts of the eHealth movement have been quietly gathering steam for the last five years and are finally fulminating into what could be a significant transformation in the management of health and health care. The most encouraging sign of change is that it consists of not just the usual shiny new technology solutions, but more importantly, structural changes in the public health system:

The 80% slim-down of the doctor’s office visit…

• Telemedicine reimbursement: As of March 2011, only 12 states offered reimbursement for telemedicine services (e.g.; telephone, email, video consultation), and at lower rates than in-office visits. Now more payers and states are starting to approve telemedicine reimbursement, which could be a huge cost savings for the industry as it is estimated that 70% of physician consultations could be handled by phone.

• Majority of diagnosis is straightforward: It is estimated that in 18/20 cases (per Singularity University FutureMed), diagnosis is straightforward, and could be accomplished via telemedicine.

• Trend to higher deductible plans: many programs are underway to transfer employees to higher-deductible plans which both reduces costs and puts more of an emphasis on preventive medicine.

Significant progress could be made with these structural changes acting in concert with the new generation of healthtech tools in areas such as:

• Health sensors, examples: continuous glucose monitoring patches, EEG sensors, ambient assisted living
  

• Quantified self-tracking devices, examples: Fitbit, Zeo sleep tracking, Body Media, Pebble Watch, Nike Fuel Band, Basis Watch

• mHealth (mobile health) apps, examples: The Eatery, MoodPanda, Map My Run, Cardio Trainer