Monday, August 9, 2010

eHealth Disparities Segmentation by Meaningful Access

Many of the same populations that suffer from health disparities also have lower Internet usage. How can we use the Web and mobile technologies to close the gap between the haves and have-nots, rather than increasing the gap?

As always, we need to start by understanding the people involved.


There are many ways to describe the people likely to get the short end of the stick in terms of health, healthcare, and technology. The most obvious are:


  • Demographics (e.g., ethnicity, age, language, socioeconomic status)
  • Psychographics (e.g., those deeply engaged in their health vs. those who don’t pay much attention to their health, or those who love the latest gadget vs. those who fear computers)
  • Access to Technology (e.g., those with desktop broadband vs. those with dial-up, vs. those with smart phones, vs. those with cell phones & SMS, vs. those with none of these)

The problem I keep bumping into is that these factors overlap in very complex ways, and all simple approaches to segmentation seem to oversimplify way too much. For example, Hispanics are more likely to have adverse health outcomes than whites, and they’re also less likely to have broadband, but they’re more likely to access the Internet on their phones. Does this mean we can use smartphones to decrease health disparities for Hispanics? Not necessarily—I'd guess that the Hispanics suffering most from health disparities are those least likely to have smartphones.


Four years ago, in the report Expanding the Reach and Impact of Consumer eHealth Tools, Cynthia Bauer and colleagues at the Dept. of Health and Human Services did an impress job of researching, analyzing, and organizing the field of eHealth Disparities. One of their main conclusions was that we needed more data at the subpopulation level. That gap in our understanding has closed a little in the last four years, but we're still struggling to understand the individuals most at risk of being caught between health disparities and digital disparities.


That said, I think we're close to having a practical starting point.


As we think about strategies to address eHealth Disparities, we might find it helpful to start segmenting in terms of meaningful access to technology. “Meaningful Access” refers to the need to have more than just a computer. Meaningful access requires:


  • hardware
  • Internet connection
  • skills to use them
  • ongoing technical support
  • relevant useful content and functionality

If we take the people most vulnerable to health disparities and subsegment them by meaningful access, then some high-level strategies start to emerge:


The “haves”

Those who already have meaningful access, or those who will gain meaningful access in the next few years with or without our efforts.

Strategies:

Promote existing content and functionality to them

Enhance current content and functionality to be more useful to them

Create new content and functionality for them


The “could haves”

Those who don’t have meaningful access, but who could gain meaningful access as a result of our efforts.

Strategies:

Use the same strategies as for the “haves” above, and also…

Support public access points (libraries, medical centers, shopping malls, etc.)

Support simple and inexpensive access on devices they already own, e.g., SMS texting, including paying the per-message fee

Support public policies and funding that increase access for the underserved (e.g., community-wide wi-fi, extend universal access programs to cover not just phone but also Internet)


The “won’t haves”

Those who don’t have meaningful access, and who still won’t have meaningful access 3 years from now regardless of our efforts.

Strategies:

Support “infomediaries” such as family members who use the Web and mobile devices on behalf of those who don’t

Maintain and enhance non-technology-based services



This might be a starting point. The next step would be to gather more information about each of these groups to understand whether these groups are homogeneous enough to have similar needs that can be addressed with similar efforts.

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