Explaining the 17% Meaningful Use Dropout Rate

It's been widely reported that 17% of eligible providers dropped out of the meaningful use program after 1 year of participation. There are hundreds of reasons one can point to in order to explain this statistic. But there's only one reason that matters: poorly designed incentives. With better-designed incentives, all of the other issues would have worked themselves out, and providers would've begrudgingly jumped through the meaningful use hoops.

Incentives matter. Our nation's healthcare cost problem is the result of decades of misaligned incentives (fee-for-service). Wall street collapsed in 2008 because bankers were structuring securities based on shortsighted, greedy, poorly designed incentives. People will act to maximize the clearly defined financial incentives laid out for them.

The problem with the meaningful use payout program is that the financial rewards decrease over time:

Year 1: $18,000

Year 2: $12,000

Year 3: $8,000

Year 4: $4,000

Year 5: $2,000

As the meaningful use program progresses and gets more complicated and rigorous, providers are given less incentive to stay the course.  Year 1 only requires 90 days of attestation (aka headache). Year 2 requires 360 days (aka 4x the headache). On the other hand, consider an alternative payment structure:

Year 1: $5,000

Year 2: $8,000

Year 3: $9,000

Year 4: $10,000

Year 5: $16,000

In this scenario, if after one year a provider got sick of the government's bullshit, they would have only recouped $5,000 of the $30,000+ they probably spent on an EHR. They probably would've felt compelled to stay the course to recoup their initial capital outlay. Initial adoption may have been a bit slower than it actually was, but in the long run, that wouldn't have mattered much anyways. There're three distinct classes of providers: those that accept EHRs, those that reject EHRs, and those that avoid EHRs because they don't accept Medicare or Medicaid. There's nothing the government can do to change the minds of the providers in the latter two groups, so instead they should've aimed to maximize the success and participation of those in the first group.

Glass <3 FDA + HIPAA

This post was originally featured on HIStalk. 

Lots of people ask me about FDA and HIPAA compliance for Glass. There’s nothing in either of these regulatory frameworks that has unique implications for Glass, even in the most delicate clinical environments such as surgery.

Glass is a computer, just like a smartphone, tablet, laptop, or desktop. It’s not special except that it looks funny. It runs Android, the fastest-growing, widely-used, flexible, extensible operating system known to mankind.

There will be Glass apps that require FDA regulation, but those apps will only require FDA regulation if the same function warranted FDA regulation on smartphones or tablets. Most of the Glass apps being developed inside universities are extensions of the EHR.

As an example, every idea listed by John Halamka, MD, CIO at BIDMC, is an EHR extension. As such, none of these apps will require FDA approval.

Glass isn’t unique within the HIPAA regulatory framework, either. Glass is just another Android device on the network. All data storage and transmissions to and from Glass must adhere to HIPAA protocols, but that’s not unique to Glass.

Moreover, because Glass runs Android, CIOs already know how to manage Glass within their existing IT infrastructure. My company has tested Glass with existing mobile device management (MDM) tools such as AirWatch and it works. MDMs simply recognize Glass as another Android device on the network.

Many have stated that the first-person camera will be the bane of Glass’s existence in hospitals. The camera is a non-issue. Hospitals are already recording everything 24 / 7. In surgery, this is especially true, where hospitals will spend north of $100,000 to install cameras in the OR lights. In fact, most hospitals already give patients waivers (that they don’t read) stating that the hospital has a right to record everyone inside.

In many ways, Glass is more regulation-friendly than traditional computers and smartphones because:

1. Glass doesn’t have a cellular chip, meaning it doesn’t support texting.
2. Glass’s proximity sensor can detect when the device is taken on and off. Unlike traditional computers, which can be physically hijacked within 2-3 minutes of last use if the user forgets to lock / logout, Glass is physically un-high jackable.
3. Glass won’t store any personal information, contacts, or connections. At Pristine, we’re removing the consumer-centric timeline user interface and replacing it with our own that’s hospital-centric. As such, users won’t have access to anything except hospital-specific functions. That means no texting, no Gmail, no Twitter, no SnapChat, no Instagram, etc.

Lots of people are trying to understand how Glass will reshape healthcare. Quite a few universities and hospitals are already testing Glass internally. A handful of venture-backed startups in addition to mine that are trying to reshape healthcare on Glass.

Surprisingly, I’ve seen little Glass activity out of the older healthcare IT vendors. I guess I shouldn’t have been so surprised. After all, this is healthcare IT.

Understanding the ACO Pioneers Successes and Failures

First year pilot numbers are out for the first ACOs. They're a mixed bag. About 1/3 performed well, 1/3 did mediocre, and 1/3 are anxiously leaving the ACO pioneer program.

People like to yell and scream as the healthcare system changes. It's difficult. A lot of legacy healthcare pundits were happy with the results of the ACO pioneer program because the data didn't appear to be overwhelmingly supportive of ACOs. But the data is actually extremely supportive of ACOs.

The hardest thing to do in a startup is prove product viability (I haven't; I still sell dreams). Similarly, paradigm shifting payment structures must prove viability. The leading 1/3 of ACOs did in their first year trying. 1/3 is phenomenal.

But what about the 2/3 that failed? Well...

How many companies with thousands of employees across dozens of physical locations with a broad base of skills in a very rigid hierarchy have successfully inverted their revenue models and associated cost structures in 1-2 years utilizing mostly unproven technologies? 2/3, if not 9/10, were destined to fail. No amount of normalization of data can account for inadequate and unprepared management in a radically new revenue and cost structure. ACOs will disrupt fee-for-service (FFS) providers because ACOs employ a disruptive business model that solves Clayton Christensen's jobs to be done theory. FFS providers job is to administer more care. ACOs job is to keep you healthy and out of clinic / hospital. ACOs are fundamentally aligned with patients health needs, FFS providers are not. As such, in the long run, they will deliver the best care at the lowest prices. These first batch of successful ACOs are a harbinger of what's to come.

Now all that's left to be done is to propagate the management practices of the best to the rest.

A Day in the Life of a Startup CEO

5:30 AM: wake up using Sleep Cycle, check Mailbox in bed. I want folks to know that I'm up early working.

5:55 AM: begin 1.5 mile run, always in Vibrams

6:30 AM: setup rings on a tree, workout, drink post workout shake, shower, shave, etc

7:30 AM: on the road to Capital Factory

8:00 AM: begin working. Here are some pictures of the views of and from Capital Factory (here and here and here and here and here). Work consists of:

emails

emails

emails

emails

phone calls

phone calls

begging for money

interviews

meetings

blogging

I take most of my phone calls on this bean bag, or in one of these phone booths.

6:30 PM: Attend a developer event, usually conveniently located at Capital Factory or on 6th Street

8:00 PM: go home

8:30 PM: work from home

12:00 AM: sleep

Interview: Paris Wallace, Founder, CEO, Ovuline

This interview was originally featured on HIStalk. I forgot to post the last 5 interviews when they were originally published on HIStalk, so they're here all in one big chunk. Moving forward, I'll make sure to post interviews as they're published.

Paris Wallace is founder and CEO of Ovuline of Boston, MA. 

What does Ovuline do?

Ovuline uses data to help women conceive and have healthier pregnancies. Women share their key health information with us,  both from what they observe as well as data they gather from wearable health tracking devices. We take that data and analyze it with machine learning algorithms and clinical guidelines to help them achieve their fertility and pregnancy health goals.

Is your system an expert system, a data-driven system, or some combination of the two?

Some combination of the two, but we’re mainly data-driven. Our systems use machine learning algorithms that analyze a large set of data based on all of the information Ovuline users share about their key health indicators. This is coupled with an analysis of their own personalized health information that comes from quantified self devices such as FitBit or Withings. Users also share their fertility symptoms with us, so we can further analyze that data using our proprietary technology.

All of that information is processed along with clinical guidelines to make accurate and personalized predictions about their fertility cycles. 

It’s a three-step data process: quantified self devices, what women observe about their own symptoms, and what our machine learning analyzes from the millions of data points of women who are also trying to get pregnant. I suppose you could say the big data combined with the small data –personal information — and clinical guidelines are what make up our system.

Ovuline is intended for pre-conception and post-conception.

That’s correct.  We launched our pre-conception – SmartFertility — product in September 2012 . We’re launching our pregnancy module in fall 2013.

What are some the tips and suggestions you give women?

We collect a variety of information from health and wellness data points, including menstrual cycle, cervical fluid, basal body temperature, nutrition, weight, sleep activity, and so on. All of this information — again, coupled with the large sets of data we’re analyzed in the “baby cloud” as I like to call it — allows us to recommend the best time for women to have intercourse to conceive. The women who’re actively using Ovuline conceive three times faster than the national average, two months versus 4-6 months.

Do you have different pricing plans for pre-conception, post-conception, and monitoring?

Although we sell fertility kits and quantified self devices to help our users record their data more accurately, right now we’re really focused on customer and data acquisition. We’re ultimately a data company.  We find and build preparatory algorithms based upon the data that users share with us that improve the user’s experience. 

Right now we don’t have anything – including charging for our service – that’s going to block people from sharing their data with us, because we ultimately think it’s going to be good for us and good for them.  We are exploring opportunities with various partners that will help us monetize, but right now we’re just trying to create amazing user experience and demonstrate the medical efficacy of what we’re doing.

How do you acquire customers?

Word of month is the #1 way we acquire customers. They’re also finding us on the Web because so many women are looking for a solution to this problem and until now there was no way to provide this in-depth level of analysis. The technology didn’t exist, and even as it emerged, this is the first time anyone has applied it to the fertility and pregnancy space. We’ve also been around for long enough that now we’re getting a lot of organic traffic, in addition to app store downloads.

Have you looked at any of the healthcare app store prescription platforms, such as Happtique?

We’re aware of them and exploring partnerships that make sense.

Do you have interesting insights about your data?

Fifty percent of fertility treatments are not needed.  Conceiving is often an issue of timing, as 30 percent of women have irregular cycles. One of the big public health issues around infertility is that it is almost taboo to talk about it. In general, I think any insights related to this space should be shared. We need to talk more about the tools and resources to help women conceive more quickly that don’t cost thousands of dollars.

Is there any other part of your business that you’d like to share?

We’re on the vanguard of supporting the Fitbit and Withings APIs to integrate their data into our database. We’re taking quantified self to the next level and trying to answer the question: what does all of this data mean to me as an individual, and how can I act upon it?

How did you get into this business?

This is my second company.  My first company was a molecular diagnostic company called GoodStart Genetics. GoodStart creates fertility diagnostic so parents can foresee if their children are at risk of being born with a recessive genetic disorder. I started GoodStart in 2008 during my last year of business school. I built GoodStart for four years. I designed the product, launched it nationally, grew the team, raised venture funding, and hired the former CEO of LabCorp to run it. GoodStart is doing incredibly well and continues to grow.

The experience at GoodStart ultimately gave me a pretty deep passion for women’s health, specifically fertility.  It’s a unique place in medicine where you have an acute issue with a positive outcome, so there is positive reinforcement to do an action as opposed to negative reinforcement. It’s incredibly rewarding to able to help people achieve their dreams of starting a family.