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Tag: Connected Health

Research Bites Dog

Screen Shot 2016-04-03 at 10.42.56 AMWe live in a headline/hyperlinked world.  A couple of years back, I learned through happenstance that my most popular blog posts all had catchy titles.  I’m pretty confident that people who read this blog do more than scan the titles, but there is so much information coming at us these days, it’s often difficult to get much beyond the headline.  Another phenomenon of information overload is that we naturally apply heuristics or short cuts in our thinking to avoid dealing with a high degree of complexity.  Let’s face it: it’s work to think!

In this context, I thought it would be worth talking about two recent headlines that seem to be set backs for the inexorable forward march of connected health.  These come in the form of peer reviewed studies, so our instinct is to pay close attention.

In fact, one comes from an undisputed leader in the field, Dr. Eric Topol.  His group recently published a paper where they examined the utility of a series of medical/health tracking devices as tools for health improvement in a cohort of folks with chronic illness.  In our parlance, they put a feedback loop into these patients’ lives.  It’s hard to say for sure from the study description, but it sounds like the intervention was mostly about giving patients insights from their own data.  I don’t see much in the paper about coaching, motivation, etc.

If it is true that the interactivity/coaching/motivation component was light, that may explain the lackluster results.  We find that the feedback loops alone are relatively weak motivators.  It is also possible that, because the sample included a mix of chronic illnesses, it would be harder to see a positive effect.  One principle of clinical trial design is to try to minimize all variables between the comparison groups, except the intervention.  Having a group with varying diseases makes it harder to say for sure that any effects (or lack of effects) were due to the intervention itself.

Dr. Topol is an experienced researcher and academician.  When they designed the study, I am confident they had the right intentions in mind.  My guess is they felt like they were studying the effect of mobile health and wearable technology on health (more on that at the end of the post). But you can see that, in retrospect, the likelihood of teasing out a positive effect was relatively low.

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Health Insurance Exchanges Will Transform Health Care. Magically Increase Transparency. Improve Access. And Maybe Even Lower Costs. But Only if We Get it Right …

NPR ran a story recently about how some retailers are retooling efforts to appeal to consumers in light of increased competition, particularly from online vendors.

Many are striving to be more “customer friendly”; Kohl’s department store was mentioned for adopting a “no questions asked” return policy with the idea that customer loyalty could be enhanced as the retailer made itself easier to do business with.

Comparisons between health care and retail abound, and while we say it is ideal for the consumer experience to be the same in both industries, in fact they are much different. The gap between the two industries was well-illustrated in this video of a shopper in a grocery store. We see them at the counter having their items rung up. But they aren’t told the prices and when they are given the receipt at the end, they’re told the final amount due may actually differ from what they see on the receipt.

Let’s take the analogy a step further: what if the customer expected the same “no questions asked” return policy from Kohl’s? Or a money back guarantee? In health care, only recently has the federal government taken steps to impose financial penalties in instances of poor care (which is the health care system’s equivalent of a “return policy” from providers).

When our team was at Subimo we initially focused on cost and quality (outcomes) information on hospitals. It was clear that – for the same procedures – there were both low cost and high quality providers as well as high cost and poor quality providers. Our efforts with transparency were designed to help people sort through the information so they could make more informed decisions and understand what quality outcomes might mean to them. We knew there was much variation in outcomes with certain procedures (e.g. aortic aneurysm repair) and less variation with others (e.g. normal vaginal delivery). Helping people understand when a poor outcome was more likely to occur helped them with their decisions (and presumably made them better shoppers).

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