Free EMR Newsletter Want to receive the latest news on EMR, Meaningful Use, ARRA and Healthcare IT sent straight to your email? Join thousands of healthcare pros who subscribe to EMR and HIPAA for FREE!!

Three Words That Health Care Should Stop Using: Insurance, Market, and Quality (Part 2 of 2)

Posted on August 23, 2016 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

The previous part of this article ripped apart the use of the words “insurance” and “market” to characterize healthcare. Not let’s turn to another concept even more fundamental to our thinking about care.

Quality

The final element of this three-card Monte is the slippery notion of quality. Health care is often compared to the airlines (when we’re not being compared to the Cheesecake Factory), an exercise guaranteed to make health care look bad. Airlines and restaurants offer relatively homogeneous experiences to all their clients and can easily determine whether their service succeeded or failed. Even at a mechanical level, the airlines have been able to quantify safety.

Endless organizations such as the National Association for Healthcare Quality (NAHQ) and the Agency for Healthcare Research and Quality (AHRQ) collect quality measures, and CMS has tried strenuously to include quality measures in Meaningful Use and the new MACRA program. We actually have not a dearth of quality measures, but a surfeit. Doctors feel overwhelmed with these measures. They are difficult to collect, and we don’t know how to combine them to create easy reports that patients can act on. There is a difference between completing a successful surgery, caring for things such as pain and infection prevention after surgery, and creating a follow-up plan that minimizes the chance of readmission. All those things (and many more) are elements of quality.

Worst of all, despite efforts to rank patients by their conditions and risk, hospitals repeatedly warn that quality measures underestimate risky patients and therefore penalize the hospitals that do the most difficult and important work–caring for the sickest. Many hospitals are throwing away donor organs instead of doing transplants, because the organs are slightly inferior and therefore might contribute to lower quality ratings–even if the patients are desperate to give them a try.

The concept of quality in health care thus needs a fresh look, and probably a different term. The first, simple thing we can do is remove patient ratings from assessments of quality. The patient knows whether the nurse smiled at her or whether she was discharged promptly, but can’t tell how good the actual treatment was after the event. One nurse has suggested that staff turnover is a better indication of hospital quality than patient satisfaction surveys. Given our fascination with airline quality, it’s worth noting that the airline industry separates safety ratings from passenger experience. The health care industry can similarly leverage patient ratings to denote clients’ satisfaction, but that’s separate from quality.

As for the safety and effectiveness of treatment, we could try a fairer rating system, such as one that explicitly balances risk and reward. Agencies would have to take the effort to understand all the elements of differences in patients that contribute to risk, and make sure they are tallied. Perhaps we could learn how to assess the success of each treatment in relation to the condition in which the patient entered the office. Even better, we could try to assess longitudinal results instead evaluating each office visit or hospital admission in isolation.

These are complex activities, but we have lots of data and powerful tools to analyze it. Together with a focus on changing behavior and environments, we should be able to make a real difference in quality–and I mean quality of life. Is there anything an ordinary member of the health professions can do till then? Well, try issuing Bronx cheers and catcalls at any meeting or conference presentation where someone uses one of the three misleading terms.

Three Words That Health Care Should Stop Using: Insurance, Market, and Quality (Part 1 of 2)

Posted on August 22, 2016 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

Reading the daily papers, I have gotten increasingly frustrated at the misunderstandings that journalists and the public bring to the debates of over health expansion, costs, and reform. But you can’t blame them–our own industry has created the confusion by misusing terms and concepts that work in other places but not in health. Worse still, the health care industry has let policy-makers embed the incorrect impressions into laws and regulations.

So in this article I’ll promote the long process of correcting the public’s impressions of health care–by purging three dangerous words from health care vocabulary.

Insurance

The health care insurance industry looks like no other insurance industry in the world. When we think of insurance, we think of paying semi-annually into a fund we hope we never need to use. But perhaps every twenty years or so, we suffer damage to our car, our house, or our business, and the insurance kicks in. That may have been true for health care 70 years ago, when you wouldn’t see the doctor unless you fell into a pit or came down with some illness they likely couldn’t cure anyway. The insurance model is totally unsuited for health care today.

The Affordable Care Act made some symbolic gestures toward a recognition that modern health care should embrace prevention and wellness. For instance, it eliminated copays for preventative visits. The insurance companies took that wording very literally: if you dare to bring up an actual medical problem during your preventative visit, they charge you a copay. Yet the “preventative” part of the visit usually consists of a lecture to stop smoking and go on the Mediterranean diet.

Effective wellness programs jettison the notion of insurance (although patients need separate insurance for catastrophic problems). They keep in regular contact with clients, provide coaching, and sometimes use intelligent digital interventions such as described by Dr. Joseph Kvedar in The Internet of Healthy Things (which I reviewed shortly after its release). There are scattered indications that these programs do their job. As they spread, the system set up to deal with catastrophic health events will have to adapt and take a modest role within a behavioral health model.

The term “insurance” is so widely applied to our healh funding model that we can’t make it go away. Perhaps we should put the word in quotation marks wherever it must be used.

Market

This term is less ubiquitous than “insurance” but may be even more harmful. Numerous commenters have pointed out the difference between health care and actual markets:

  • In a market, you can walk away and refuse to pay for a good that is too expensive. If the price of beef goes through the roof, you can switch to beans (and probably should, for your own health). So the best time to argue with someone who promotes a health care market may be right after he’s fallen from a ladder and is clutching at his leg in agony. Ask him, “Do you feel you can walk away from an offer of health care?” Cruel, but a lesson he won’t forget.

  • A market serves people who can afford it. It’s hard to find a stylish hair dresser in a poor neighborhood because no one can pay $200 for a cut. But here’s the rub: the people who need health care the most can’t afford it. Someone with serious mental or physical problems is less likely to find work or be able to attend a college with health insurance. Parents of seriously ill children have to take time off from work to care for them. And so on. It’s what economists–who have trouble discarding the market way of thinking–call a market failure.

  • In a market, you know what you’re going to pay for a service and what your options are. Enough said.

  • In a market, you can evaluate the quality of a service and judge (at least in retrospect) whether it was worth the cost. I’ll deal with quality in the next section.

The misconception of health care as a market came to a head in the implementation of the Affordable Care Act. Presumably, millions of “young invincibles” were avoiding health insurance because of the cost. The individual mandate, combined with affordable plans on health care exchanges, would bring them flooding into the insurance system, lowering costs for everyone and balancing the burden created by the many sick people who we knew would join. And yet now we have stubbornly rising health care rates, deductibles, and caps, along with new costs in the states where Medicaid expanded Where did this all fall apart?

Part of the problem is certainly the recession, which caused incomes to decline or stagnate and exacerbated people’s health care needs. Also, there was a pent-up need for treatment among people who had lacked health insurance and avoided treatment for some time. This comes through in a study of prescription medication use. Furthermore, people don’t change habits overnight: many continue to over-rely on the emergency room (perhaps because of a shortage of primary care providers).

But there’s another unanticipated factor: the “young invincibles” actually start using health care once they get access to it. An analysis showed that mental health needs among the young are much higher than expected. In particular, they suffer widely from depression and anxiety, which is entirely reasonable given the state of our world. (I know that these conditions are connected to genetics and biology, but environment must also play a role.)

Ultimately, until we get behavioral health in place for everybody, health care costs will continue to rise and we won’t realize the promise of near-universal coverage. Many health care activists–especially during the recent political primary season–call for a single-payer system, which certainly would introduce many efficiencies. But it doesn’t solve the problems of chronic conditions and unhealthy lifestyles–that will require policy action on levels ranging from improvements in air cleanliness to new opportunities for isolated individuals to socialize. Meanwhile, we still have to look at the notion of quality in tomorrow’s post.

How Precision Medicine Can Save More Lives and Waste Less Money (Part 2 of 2)

Posted on August 10, 2016 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

The previous section of this article looked at how little help we get from genetic testing. Admittedly, when treatments have been associated with genetic factors, testing has often been the difference between life and death. Sometimes doctors can hone in with laser accuracy on a treatment that works for someone because a genetic test shows that he or she will respond to that treatment. Hopefully, the number of treatments that we can associate with tests will grow over time.

So genetics holds promise, but behavioral and environmental data are what we can use right now. One sees stories in the trade press all the time such as these:

These studies usually depend on straightforward combinations of data that are easy to get, either from the health care system (clinical or billing data) or from the patient (reports of medication adherence, pain level, etc.).

And we’ve only scratched the surface of the data available to us. Fitness devices, sensors in our neighborhoods, and other input will give us much more. We can also find new applications for data: for instance, to determine whether one institution is overprescribing certain high-cost drugs, or whether an asthma victim is using an inhaler too often, meaning the medication isn’t strong enough. We know that social factors, notably poverty (LGBTQ status is not mentioned in the article, but is another a huge contributor to negative health outcomes, due to discrimination and clinician ignorance) must be incorporated into models for diagnosis, prediction, and care.

President Obama promises that Precision Medicine features both genetics and personal information. One million volunteers are sought for DNA samples and information on age, race, income, education, sexual orientation, and gender identity.

There are other issues that critics have brought up with the Precision Medicine initiative. For instance, its focus on cure instead of prevention weakens its value for long-term public health improvements. We must also remember the large chasm between knowing what’s good for you and doing it. People don’t change notoriously unhealthy behaviors, such as smoking, even when told they are at increased risk. Some experts think people shouldn’t be told their DNA results.

Meanwhile, those genetic database can be used against you. But let’s consider our context, once again, in order to assess the situation responsibly. The data is being mined by police, but it’s probably not very useful because the DNA segments collected are different from what the police are looking for. Behavioral data, if abused, is probably more damning than genetic data.

Just as there are powerful economic forces biasing us toward genetics, social and political considerations weigh against behavioral and environmental data. We all know the weaknesses in the government’s dietary guidelines, heavily skewed by the food industry. And the water disaster in Flint, Michigan showed how cowardice and resistance by the guardians of public health to admitting changes raised the costs in public health measures. Industry lobbying and bureaucratic inertia work together to undermine the simplest and most effective ways of improving health. But let’s get behavioral and environmental measures on the right track before splurging on genetic testing.

How Precision Medicine Can Save More Lives and Waste Less Money (Part 1 of 2)

Posted on August 9, 2016 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

We all have by now seen the hype around the Obama Administration’s high-profile Precision Medicine Initiative and the related Cancer Moonshot, both of which plan to cull behavioral and genomic data on huge numbers of people in a secure manner for health research. Major companies have rushed to take advantage of the funds and spotlight what these initiatives offer. I think they’re a good idea so long as they focus on behavioral and environmental factors. (Scandalously, the Moonshot avoids environmental factors, which are probably the strongest contributors to cancer) . What I see is an unadvised over-emphasis on the genetic aspect of health analytics. This can be seen in announcements health IT vendors, incubators, and the trade press.

I can see why the big analytics firms are excited about increasing the health care field’s reliance on genomics: that’s where the big bucks are. Sequencing (especially full sequencing) is still expensive, despite dramatic cost reductions over the past decade. And after sequencing, analysis requires highly specialized expertise that relatively few firms possess. I wouldn’t say that genomics is the F-35 of health care, but is definitely an expensive path to our ultimate goals: reducing the incidence of disease and improving life quality.

Genomics offer incredible promise, but we’re still waiting to see just how it will help us. The problems that testing turns up, such as Huntington’s, usually lack solutions. One study states, “Despite the success of genome-wide association and whole-exome and whole-genome sequencing (WES/WGS) studies in revealing the DNA variants that underlie the genetic basis of disease, the development of effective treatments for most diseases has remained a challenge.” Another says, “Despite much progress in defining the genetic basis of asthma and atopy [predisposition to getting asthma] in the last decade, further research is required.”

When we think about the value of knowing a gene or a genetic deviation, we are asking: “How much does this help predict the likelihood that I’ll get the disease, or that a particular treatment will work on me?” The most impressive “yes” is probably in this regard to the famous BRCA1 and BRCA2 genes. If you are unlucky enough to have certain mutations of these gene, you have a 70% lifetime risk for developing breast or ovarian cancer. This is why testing for the gene is so popular (as well as contentious from an intellectual property standpoint), and why so may women act on the results.

However–this is my key point–only a small percentage of women who get these cancers have these genetic mutations. Most are not helped by testing for the genes, and a negative result on such a test gives them only a slight extra feeling of relief that they might not get cancer. Still, because the incidence of cancer is so high among the unfortunate women with the mutations, testing is worthwhile. Most of the time, though, testing is not worth much, because the genetic component of the disease is small in relation to lifestyle choices, environmental factors, or other things we might know nothing about.

So, although it’s hard enough already to say with any assurance that a particular gene or combination of genes is associated with a disease, it’s even harder to say that testing will make a big difference. Maybe, as with breast or ovarian cancer, a lot of people will get the disease for reasons unrelated to the gene.

In short, several factors go into determining the value of testing: how often a positive test guarantees a result, how often a negative test guarantees a result, how common the disease is, and more. Is there some way to wrap all these factors up into a single number? Yes, there is: it’s called the odds ratio. The higher an odds ratio, the more helpful (using all the criteria I mentioned) an association is between gene and disease, or gene and treatment. For instance, one study found that certain genes have a significant association with asthma. But the odds ratios were modest: 3.203 and 5.328. One would want something an order of magnitude higher to show running a test for the genes would have a really strong value.

This reality check can explain why doctors don’t tend to recommend genetic testing. Many sense that the tests can’t help or aren’t good at predicting most things.

The next section of this article will turn to behavioral and environmental factors.

Communal Themes Between Behavioral Health and General Healthcare – #NatCon16

Posted on March 7, 2016 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

Instead of getting a break after HIMSS, I’m doing back to back conferences as I attend the National Council for Behavioral Health’s NatCon Conference in Las Vegas. If you’re following along at home, the twitter stream for the event is #NatCon16 and is full of a ton of gems from the conference.
Chris Matthews and John Lynn at NatCon
Today I got the chance to hear and meet two of the keynote speakers: Chris Matthews and @KevinMD. Chris Matthews provided a lot of great insights into the political environment and a lot of amazing insider stories. My biggest takeaway from his talk is that we’re stuck in a massive quagmire and I don’t see much of that changing in the future. Presidential candidates can make all the promises they want, but they mean nothing if they don’t have the political support and finances to pay for it. @KevinMD was great to meet and hear talk about the benefits of using social media. Of course, he was mostly preaching to the choir for me. However, I’m sure that his comments were extremely eye opening for many in the audience.
KevinMD and John Lynn
Besides these two keynotes, I attended a few different sessions in the tech track of the conference. The most surprising thing to me was how similar these sessions were to any sessions you might have in any healthcare IT conference. This wasn’t really shocking, but it was a surprise that the messages and challenges were so much the same. Here are a few examples:

Third Party App Integration with EHRs
In one session, the vendors were talking about their inability to integrate their behavioral health apps into the various EHR software. They all said it was on the roadmap, but that there wasn’t an easy way for them to make it a reality. One of them appropriately called for EMR customers to start demanding that their EHR vendors open up their systems to be able to integrate with these third party apps.

Fear of Social Media
I usually find at conferences that this breaks out into two groups. One group loves social media, embraces it and benefits from it. The other group is totally afraid of the repercussions of using it. @KevinMD offered some great insights on how to overcome this fear. First, don’t say anything on social media that you wouldn’t say in a crowded hospital hallway. Second, start by using something like LinkedIn or Doximity which is a more private type of social media and are both professional networks. The real key I’d suggest is that you should own your brand. Don’t leave your brand image up to other people.

Business Models
There was a lot of discussion around various uses of technology in behavioral health and the need for the business models to catch up with the technology. Many would love to use all these technological advances, but they aren’t sure how they’re going to get paid for doing so.

I’m sure I could go on and on. I know that many in the general medical field look at behavioral health as a totally different beast. No doubt there are some differences in behavioral health, but I think that we’re more alike than we are different. Looking forward to learning even more over the next two days.