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!!

Conference on Drug Pricing Inject New Statistics Into Debate, Few New Insights (Part 2 of 2)

Posted on November 9, 2018 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 first part of this article described the upward pressures on costs and some of the philosophical debates over remedies. This section continues the discussion with several different angles on costs.

Universal access and innovation

It’s easy to call health care a human right. But consider an analogy: housing could also be considered a human right, yet no one has the right to a twenty-room mansion. Modern drug and genetic research are creating the equivalents of many twenty-room mansions, and taking up residence means the difference between life and death for someone, or perhaps between a long productive life and one of pain and deformity.

Universal access, often through a single-payer system, is in widespread use in every developed country except the United States. Both universal access and single payer are credited with keeping down the costs of health care, including drugs. It makes sense to link single-payer with lower drug costs, because of the basic rules of economics: size gives a buyer clout, as we can see in the ways Walmart lords it over their suppliers (documented in a 2006 book, The Wal-Mart Effect, by Charles Fishman). At the conference, Sean Dickson from the Pew Charitable Trusts gave what he called an “economics 101 course” of health care and how the industry diverges from an ideal market. (He did not come out in favor of single-payer, though.)

How much fat can be cut from pharma? My guess is a lot. As we saw in the previous section, profits from pharmaceuticals tower above profits in most industries. But we don’t have to stop by simply shaving payments to shareholders, or even management compensation. I know from attending extravagent health care conferences that there’s a lot of free cash floating around the health care industry in general, although it’s unevenly distributed. (Many hospitals, nursing homes, and other institutions are struggling to maintain adequate staffing.) In industries possessing such easy money, it does trickle down somewhat. Gaudino pointed out ruefully that health care is one of the few fields left that can give ordinary people a middle-class income, something we don’t want to lose even as employment continues to rise in that space. But easy money also leads to bloat, and this is almost certainly true throughout health care, including pharma.

Even so, projections of the cost of universal access are dizzyingly high, placing pressure on the historic universal access model in Massachusetts and forcing Vermont to give up single-payer. The pressures that could be applied to the health care field by the US government would certainly outweigh the negligible impact that Vermont–with its population of a mere 600,000–could exert. But it’s unlikely that the easy wins falling out of single-payer (squeezing drug companies, eliminating the administrative overhead of handling health insurance) could make up for the staggering costs of adding whole new swaths of a high-need, difficult population to government rolls.

What we need to lower health costs is an overhaul of the way health care systems conceive of patients, taking them from conception to the grave and revamping to treat chronic conditions. T.R. Reid, in his book The Healing of America, says that universal access must come first and that all the rest will gradually follow. I would like to have at least a strong concept throughout the health care system of what the new paradigm will be, before we adopt single-payer. And in theory, adopting that paradigm will fix our cost problems without the wrenching and contentious move to single-payer.

What non-profits can teach us

So how do we recompense manufacturers while getting drugs to low-income people who need them? Some interesting insights did turn up here at the conference, through a panel titled From Development to Delivery Globally. All three speakers operate outside the normal market. One is a representative of Gilead Sciences (mentioned earlier), whereas the other two represent leading non-profits in international health care, Partners in Health and the Bill & Melinda Gates Foundation. Nevertheless, their successes teach us something about how to bend the cost curve in traditional markets.

Flood said that Gilead Sciences made an early commitment to get its AIDS drug to all who needed it, without regard to profit. At first it manufactured the drug and distributed it in sub-Saharan Africa at cost. That failed partly because the cost was still out of reach for most patients, but also because the distribution pipeline was inadequate: logistics and government support were lacking.

So Gilead took a new tack: it licensed the drug to Indian manufacturers who not only could produce it at a very low cost (while maintaining quality), but understood the sub-Saharan areas and had infrastructure there for distributing the drug. This proved highly successful. I’m betting we’ll find more drugs manufactured in India over time.

Hannah Kettler of the Gates Foundation described how they set 50 cents as an affordble price for a meningitis vaccination, then went on to obtain that price in a sustainable manner. The key was to hook up potential buyers and manufacturers in advance. The buyers guaranteed a certain number of bulk purchases if the manufacturers could achieve the desired price. And armed with a huge guaranteed market, the manufacturers scaled up production so as to reduce costs and meet the price goal.

The Gates model looks valuable for a number of drugs: guarantee an advance market and start out manufacturing at a large scale to reduce costs. This will not help with orphan diseases, of course.

More generally, in my opinion, developed countries have to define their incentive to provide aid of any kind–medicine, education, microloans, or whatever. Is it enough of an incentive to empower women and keep population growth under control? To avoid social conflicts that turn into civil wars? To avoid mass emigration and refugee crises? What are solutions worth to us?

The contributions of artificial intelligence

Aside from brief mentions of advanced analytics by Gaudino and Taylor, the promise of computer technology came up mainly in the final panel of the conference, where Petrie-Flom research fellow Sara Gerke offered some examples of massive costs savings that AI has created at various points in the drug development chain. These tend to be isolated success stories, but illustrate a trend that could relieve pressure on prices.

I have reported on the use of AI in drug development in other articles over the years. This section consolidates what I’ve seen: although AI can potentially help at any point in an industry’s business, it seems particularly fertile in two parts of drug development.

The first area is the initial discovery of compounds. Traditional research can be supercharged by analyses of patient genes, simulations of molecule behaviors, and other ways of extracting needles from haystacks.

The second area is the conduct of the clinical trial. Here, techniques being tried by drug companies are variants of what clinicians are doing to engage and monitor patients. For instance, clinical subjects can wear devices with minimal disruption to their lives, and report vital signs back to researchers on an ongoing basis instead of having to come into the researcher’s office. AI can also find suitable subjects, increasing the potential pool. Analytics may reveal early whether a clinical trial is not working, allowing the company to save money by shutting it down early, and avoiding harm to subjects.

Of course, we all look forward to some marvelous breakthrough–the penicillin of the 21st century–that will suddenly open up miracle treatments at low cost for a myriad of illnesses. Current research is pushing this medical eschaton further and further off into the unforeseeable future. We are learning that the genome and human molecules interact in ways that are much more complex than we thought, that a lot is dependent on the larger biome, and that diseases are also cleverer than we thought and able to work around many of our attacks.

Analytics will certainly accelerate medical discoveries. In doing so, it could drastically reduce the costs of drug discovery, and therefore reduce risk and ultimately prices. But stunning new drugs for rare diseases could also vastly increase prices.

Baby steps

I’ll end with a few suggestions made by conference participants to create a more competitive market or reduce prices. Outside of explicit price setting (on which participants were deeply split), the proposals looked like small contributions to a situation that requires something big and bold.

  • Price transparency came up several times.
  • Grogan would like Congress to re-examine reimbursement for Medicare Part D (especially the donut hole and catastrophic coverage) to give both PBMs and vendors incentives to lower costs.
  • Gaudino said that Australia does a much better job than the US of collecting data on the outcomes of using drugs, which they can use to determine whether to approve the drugs. The U.S. payment system is more privatized and fragmented, making it impossible to collect the necessary data.
  • Caljouw praises the efforts of the Massachusetts Health Policy Commission, which has no power to set costs but meets with providers and asks them to reconsider the factors that lead to jacked-up prices.
  • Caljouw also mentioned laws requiring price transparency from PBMs.
  • Several participants suggested reversing the decision that allowed companies to air advertisements directly to consumers. (I’m afraid that if all the misleading drug ads disappeared from the air, a bunch of television networks would go out of business.)
  • Taylor cited pressure by Wall Street on drug companies to maximize prices without regard for the social impacts–an intense kind of pressure felt by no other industry except fossil fuels–and called for the extension of socially responsible investment to drug companies.

I’d like to suggest, in conclusion, that we may be focusing too much on manufacturers, who are taking enormous risks to cure difficult diseases. A University of Southern California study found that 41% of the price is absorbed by intermediaries: wholesalers, pharmacies, PBMs, and insurers. Whether through single-payer or through other changes to the health care system, we can do a lot without constricting innovators.

Conference on Drug Pricing Injects New Statistics Into Debate, Few New Insights (Part 1 of 2)

Posted on November 8, 2018 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 price of medications has become a leading social issue, distorting economies around the world and providing easy talking points to politicians of all parties (not that they know how to solve the problem). Last week I attended a conference on the topic at the Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School.

On one level, the increasing role that drugs play in health care is salutary. Wouldn’t you rather swallow a pill than go in for surgery, with the attendant risks of anesthesia, postoperative pain opiates, and exposure to the increasingly scary bacteria that lurk in hospitals? Wouldn’t you rather put up with a few (usually) minor side effects of medication than the protracted recovery and discomfort of invasive operations? And even when priced in the tens of thousands, drugs are usually cheaper than the therapies they replace.

But drug costs are also deeply disrupting society. They are more and more dominant in the health care costs that take up nearly a fifth of the total output of the U.S., and the outsized demands that medications put on both private and public pocketbooks lead to drug pricing being a rare bipartisan issue.

Michael Caljouw from Blue Cross Blue Shield of Massachusetts pointed out at the conference that in Massachusetts, health care has skyrocketed from 20% to 45% of entire state budget in 20 years, and similar trends are found in other states. He says that an expensive new drug can “blow through” budgets set a year in advance. Bach cited statistics showing the prices for cancer drugs are rising exponentially, while the drugs get only slightly more effective over time.

Drug costs also eat into the limited savings of the elderly, dragging many into bankruptcy or poverty. As reported at the conference by Peter Bach of the Memorial Sloan Kettering Cancer Center, high costs drive away many patients who would benefit from the medications, thus leading to worse health care conditions down the line.

Similar problems can be seen internationally as well.

Petrie-Flom drew together a stellar roster of speakers and panelists for its one-day conference. However, when one shakes out all the statistics and recommendations, the experts turn out to lack answers. Their suggestions look like tinkering around the edges, just as the federal government did over the past year with new rules such as citing prices in drug ads and tweaking the Medicare Part D reimbursement formulas. Thus, I will not tediously cover all the discussions at the conference. I will instead raise some key issues while tapping into these discussions for fodder.

The loudest statement at the conference was the silence of the pharma industry. Representatives of everyone you could imagine with skin in this game appeared on the podium–insurers, clinicians, pharmacy benefit managers, the finance industry, regulators, patent activists, think tanks, and of course lawyers–with one glaring exception: drug manufacturers. I’m sure these companies were invited. But the only biopharmaceutical firm to show up was Gilead Sciences, and the talk given by Amy Flood, senior vice president of public affairs, was not about normal drug development but about the company’s commendable efforts to disseminate an HIV drug through sub-Sahara Afica. Given the intense political, social, and geographic contention over AIDS, her inspiring story had little in the way of models and lessons to offer mainstream drug development. I will cover it later in the section ‘What non-profits can teach us.”

Failure by the vast bulk of the pharma industry to take up the sterling opportunity represented by this conference to present their point of view, to me, comes across as an admission of guilt. Why can’t they face questions from an educated public?

The oncoming sucker punch

A couple days before the conference, Stat published a heart-warming human interest story about a six-year old being treated successfully for a debilitating rare condition, Batten disease. Rather than giving in to genetic fate, the parents pulled together funding and doctors from around the country, pushed the experimental treatment through an extremely fast-track FDA approval, and saw positive results within a year.

The tears tend to dry from one’s eyes–or to flow for different reasons–when one reads the means used to achieve this miracle. The child’s mother is a marketing professional who raised nearly three million dollars through crowdfunding. An article in the November/December issue of MIT Tech Review describes six other families who raised money for personalized genetic treatments. Another article in the same issue–which is devoted to big data and genetic research in medicine–discusses personalized vaccines against cancers, while a third lays out the expenses of in vitro genetic testing. This is not a course of action open to poor, marginalized, uneducated people. Nor is such money likely to turn up for every orphan disease suffered somewhere in the world.

I hope that this six-year-old recovers. And I hope the three-million-dollar research produces advances in gene science that redound to the benefit of other sufferers. But we must all consider how much society can spend on the way to an envisioned utopia where cures are available to all for previously untreatable conditions. As conference speakers pointed out, genetic treatments assume an “N of 1” where each patient gets a unique regimen. This doesn’t scale at all, and certainly doesn’t fit the hoary old pharmaceutical paradigm of giving a monopoly over a treatment for a decade or so in exchange for low-cost generic imitations for all eternity afterward.

Yet government needs to keep funding biotech research, and creating a positive regulatory environment when venture capitalists and other investors will fund the research. Joe Grogan of the Office of Management and Budget, keynoting at the conference, claimed that Germany used to have the pre-eminent biotech industry and let it shrivel up through poor policies. In the same way, biotech could leave the United States for some other country that proves welcoming, probably China.

Dueling models

Some panelists enthusiastically promoted what they openly and officially called Willingness To Pay (WTP) or “what the market will bear” pricing, but which I call “stick it to ’em” pricing. Others called for the price controls that are found in almost every developed country outside the U.S. Various schemes being promoted under the umbrella of “value-based pricing” were generally rejected, probably because they would allow the companies to inflate their prices. However, Jami Taylor of Stanton Park Capital suggested that modern data collection and analytics could support micropricing, matching payment to the outcome for each patient.

Interestingly, nobody believed that drug prices should reflect the costs of producing them. But everybody understood that drug producers must be adequately reimbursed. That is why people from many different perspectives came out in opposition to “charity” and “compassionate” discounts or rebates offered by many pharma companies, sometimes reaching 10% of their total expenditures. In a typical sequence of events, a company enjoying a breakthrough for a serious condition announces some enormous price in the tens or hundreds of thousands of dollars. After public outcry (or to ward off such outcry) they start awarding deep discounts or rebates.

Why are discounts and rebates poor policy? First, they bind the recipients to dependence on the company. This is why, according to Annette Gaudino of the Treatment Action Group, Médecins Sans Frontières rejected a donation from a manufacture of a vaccine.

More subtly, high list prices set a bar for future prices. They allow the companies to jack up prices for brand-name drugs by double digits each year (as shown in a chart by Surya Singh of CVS Health) and to introduce new drugs at inflated prices–only to take off the edge through more discounts and rebates.

Grogan would like Europeans to pay higher prices, following the common perception that US consumers are subsidizing the rest of the world. But other speakers contended that Europeans offer fair compensation that can keep drug companies sustainable. A recent administration proposal to force manufacturers to match foreign drug prices seems to take the same attitude.

Aaron Kesselheim of Harvard Medical School participated in a study that demonstrated the robustness of European price controls in a clever manner. He and colleagues simply examined which drugs were withdrawn from the German market by manufacturers who didn’t want to undergo their rigorous price-setting regime, run by the Institute for Quality and Efficiency in Health Care (IQWiG). The 20% of drugs that were withdrawn were those demonstrated to be ineffective or to be no better than lower-priced alternatives.

Gaudino also tried to slay the opponents of price controls with an onslaught of statistics. She cited a JAMA study finding that bringing a cancer drug to market costs well under one million dollars, less than half of the billions often cited. The non-profit Drugs for Neglected Diseases initiative (DNDi) can produce a new medicine for a total cost of just 110 to 170 million dollars. And the average profit for pharma companies has stayed level at around 20% for decades, far above most industries.

With all these endorsements for price controls, the shadow of possible negative effects on innovation hover over them. In the next part of this article, I’ll examine technical advances that might lower costs.

Nurses and Patient Loads: The Solution Lies in Process Change, Not Maximums

Posted on November 1, 2018 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.

Shortages of clinical staff plague communities around the world. Even my state of Massachusetts, a medical Mecca, has a shocking dearth of professionals in mental health. Health care reformers understand that shortages much be addressed through a careful and deep investigation into the hospital and clinic processes and practices. Streamlining processes through data analytics and the deft application of new technologies for monitoring and recording information will probably help.

Nurses probably experience the crunch of patient loads more than other staff. Unfortunately, some of them try to force a quick fix on their institutions through mandatory maximums. They ignore process, ignore holistic systems thinking, and ignore the potential of technology. Massachusetts is facing just such an ill-planned effort right now in a ballot question that would fix arbitrary patient loads. The public is being asked to regulate an area that can’t possibly understand. (The inscrutable text of this ballot question, number 1 on the ballot, is available about one-quarter of the way down this web page.) But Massachusetts was not the first to face this choice, and will probably not be the last.

In 2003, California passed limits on patient loads that are somewhat of a model for the Massachusetts law, and whose effects are hotly debated. Texas apparently considered a similar law, but I assume it went nowhere because I could find no other reference to it. Massachusetts has a law applying narrowly to emergency rooms, and every state has regulations for nursing homes.

Nurses don’t have it easy; that’s clear. But the solutions must be systemic. Opponents of Massachusetts ballot question 1 point to all kinds of negative effects that the proponents refuse to consider, such as the loss of non-nursing staff who are crucial to helping the nurses get their jobs done. The basic problem is that hospitals and other facilities are not making use of the computing advances, and related process improvements, available in this year 2018.

Health care giant Kaiser Permanente found that clinicians were spending 15 to 40 percent of their doing “hunting and gathering” for supplies before the company optimized its supply chains. The Boston Globe cites numerous management techniques that free up clinicians’ time, some right in Boston. A 2011 NIH report found that nurses spend only 37% of their time taking direct care of patients. Of course, other activities such as administration and documentation are important, but they are begging for process improvement. Partners Health Care has embarked on a large-scale effort to automate repetitive, “soul-crushing” work, and have found that staff are much happier and are spending more time using the skills they were trained to use in handling people issues. Currently, the effort affects HR, finance, and operations. I’m sure nursing would turn up opportunities for improvement when it comes their turn.

We shouldn’t have to spend 35% of nurses’ time on documentation, using systems that are notoriously inefficient and poorly automated. A recent survey showed that most doctors believe that automating common tasks such as documentation could improve clinicians’ efficiency. Nurses use the same systems, so their workloads could probably be reduced through similar improvements in technology.

Some nurses tell me, “Much of our job involves a human touch; it can’t be automated.” The NIH study shows that plenty of tasks that are amenable to computerization, and doing so will give nurses more time to apply their human touch–or as health care workers like to say, “work at the top of their license.”

The proponents of the Massachusetts ballot question count on a knee-jerk distrust of corporations (or at least of large health-care institutions). They have succeeded in winning over many people who call themselves political “progressives,” but a large segment of the Massachusetts public–according to polls, a slightly larger segment–intrinsically sense the ballot question’s flaws, so the polls are running against its passing.

We cannot improve health care and reduce costs if institutions take the status quo for granted. Voting “yes” on question 1 in Massachusetts would accept and perpetuate the assumptions behind our nursing practices. It’s hard to accept that profound systemic problems will take time and data to ameliorate, but the sooner we face that realization, the better we can deal with our clinical staffing problems.

Key Articles in Health IT from 2017 (Part 1 of 2)

Posted on January 2, 2018 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.

This article provides a retrospective of 2017 in Health It–but a retrospective from an unusual perspective. I will highlight interesting articles I’ve read from the year as pointers to trends we should follow up on in the upcoming years.

Indubitably, 2017 is a unique year due to political events that threw the field of health care into wild uncertainty and speculation, exemplified most recently by the attempts to censor the use of precise and accurate language at the Centers for Disease Control (an act of political interference that could not be disguised even by those who tried to explain it away). Threats to replace the Affordable Care Act (another banned phrase) drove many institutions, which had formerly focused on improving communications or implementing risk sharing health care costs, to fall back into a lower level of Maslow’s hierarchy of needs, obsessing over whether insurance payments would cease and patients would stop coming. News about health IT was also drowned out by more general health topics such as drug pricing, the opiate crisis, and revenue pressures that close hospitals.

Key issues

But let’s start our retrospective on an upbeat note. A brief study summary from January 4 reported lower costs for some surgeries when hospitals participated in a modest bundled payment program sponsored by CMS. This suggests that fee-for-value could be required more widely by payers, even in the absence of sophisticated analytics and care coordination. Because only a small percentage of clinicians choose bold risk-sharing reimbursement models, this news is important.

Next, a note on security. Maybe we should reprioritize clinicians’ defenses against the electronic record breaches we’ve been hearing so much about. An analysis found that the most common reason for an unauthorized release of data was an attack by an insiders (43 percent). This contrasts with 26.8 percent from outside intruders. (The article doesn’t say how many records were compromised by each breach, though–if they had, the importance of outside intruders might have skyrocketed.) In any case, watch your audit logs and don’t trust your employees.

In a bracing and rare moment of candor, President Obama and Vice President Biden (remember them?) sharply criticized current EHRs for lack of interoperability. Other articles during the year showed that the political leaders were on target, as interoperability–an odd health care term for what other industries call “data exchange”–continues to be just as elusive as ever. Only 30% of hospitals were able to exchange data (although the situation has probably improved since the 2015 data used in the study). Advances in interoperability were called “theoretical” and the problem was placed into larger issues of poor communication. The Harvard Business Review weighed in too, chiding doctors for spending so much money on systems that don’t communicate.

The controversy sharpened as fraud charges were brought against a major EHR vendor for gaming the certification for Meaningful Use. A couple months later, strangely, the ONC weakened its certification process and announced it would rely more on the vendors to police themselves.

A long article provided some historical background on the reasons for incompatibility among EHRS.

Patients, as always, are left out of the loop: an ONC report finds improvements but many remaining barriers to attempts by patients to obtain the medical records that are theirs by law. And should the manufacturers of medical devices share the data they collect with patients? One would think it an elementary right of patients, but guidance released this year by the FDA was remarkably timid, pointing out the benefits of sharing but leaving it as merely a recommendation and offering big loopholes.

The continued failure to exchange data–which frustrates all attempts to improve treatments and cut costs–has led to the question: do EHR vendors and clinicians deliberately introduce technical measures for “information blocking”? Many leading health IT experts say no. But a study found that explicit information blocking measures are real.

Failures in interoperability and patient engagement were cited in another paper.

And we can’t leave interoperability without acknowledging the hope provided by FHIR. A paper on the use of FHIR with the older Direct-based interoperability protocols was released.

We’ll make our way through the rest of year and look at some specific technologies in the next part of the article.

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.

How Will the Coming Election Year Impact Healthcare IT?

Posted on November 10, 2015 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.

It seems like the Presidential election should be closer since we’ve been hearing about possible Presidential candidates for the past year. However, we still have a whole year before the next Presidential election. Does anyone else think we’re going to be tired of this process a year from now? (But I digress)

In past years, there was certainly a lot to talk about when it comes to the impact a new president would have on healthcare IT. However, I don’t think that this presidential election will be the same. I think that’s true for healthcare in general as well.

On the healthcare IT side, meaningful use has basically run its course. Sure, Jeb Bush has asked to eliminate meaningful use and government mandates and penalties for EHR use. Although, John Halamka and Marc Probst have both recently asked for the same. We’ve written previously about how getting rid of meaningful use wouldn’t do much of anything to alter the current course of EHR and healthcare IT. It just wouldn’t change much of anything.

What could a presidential candidate do to impact healthcare IT? I really don’t see them having an interest in doing much of anything to impact the current course of healthcare IT. If you think otherwise, I’d love to hear why.

On the healthcare side of things we might see more changes. Certainly the topic of healthcare costing the US too much money is a very big an important topic for the president. However, I think Obamacare and those healthcare reform efforts are too far gone to be able to really go back and change them now. Sure, we could see some changes here and there, but I think it’s too late for a new President to really drastically change what’s already been done.

Related to this is the move away from fee for service to a value based reimbursement environment. Would any President condone this direction? Would any President advocate for a return to the old fee for service environment? I don’t see it happening. As many people have told me, the shift to value based care has left the building. There’s no coming back. Could they modify the approach and some of the details. Certainly! However, they’re not likely going to change the trajectory.

Long story short, I’m not sure any Presidential candidate will do anything that will drastically impact healthcare IT and healthcare as we know it. Sure there will be some tweaks that will have some impact, but nothing major like Obamacare or the HITECH Act.

Do you agree or disagree? I always love to hear other perspectives.

Fun Friday Healthcare Humor

Posted on November 6, 2015 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.

It’s Friday and I came across this cartoon which is funny and sad at the same time (the best kind of humor). However, I think it reflects the major challenge and a lot of the discontent many feel towards health care today.
The advances in Health-Care seems to be putting some distance between the doctor and patient.

I recently asked some people where all this physician discontent is going to lead. They didn’t have a good answer and I don’t either.

Since it’s Friday, I thought this graphic was worth sharing as well:
Friday Doctor Humor

Thanks to all the hundreds of thousands of doctors who work hard every day and don’t mail it in because it’s Friday, a weekend, late at night, etc etc. You’re true heroes.