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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.

How e-Prescribing Features Improve Your Practice Life

Posted on July 9, 2018 I Written By

The following is a guest blog post by Dr. Tom Giannulli, CMIO at Kareo.

e-Prescribing, the process of electronically fulfilling a medication prescription directly from your practice, is far from new. In fact, this service has been around long enough that the majority of patients have come to expect the convenience that accompanies it.

Most private practices are using some type of medical software that aids in the e-Prescribing process. Some may have incorporated said software because they felt obligated, but others have realized that an integrated software solution can do more than help meet the requirements for the meaningful use electronic health record (EHR) initiative.

They recognize that it may also help to improve their practice.

As the clinical leader for an electronic health record (EHR) vendor serving independent practices, I can attest that Kareo’s cloud-based software is designed with the intent to improve the unique needs of the private practice. The changes in regulations and requirements might mean you should change the way you practice, but it doesn’t have to reduce the personal connection between patients and their providers.

Improve Upon Value-Based Care

Value-based care is driven by data and has required practices to become more efficient and effective in order to reduce overall healthcare costs.

Without the automated support that accompanies e-prescribing, compiling the number of required reports could become overwhelming and significantly reduce your efficiency. Our software can make compiling this data with accurate reports both simple and manageable, which saves you valuable time. It makes tracking the quality metrics related to drug compliance much easier, but it’s also tracking quality by:

  • Helping to reduce your liability with legible prescriptions
  • Improving upon prescription accuracy
  • Reducing medication errors
  • Improving upon patient compliance
  • Monitoring fraud and abuse from duplicate prescriptions

Having an automated perspective on drug interactions and prescription history at your fingertips allows you to focus on measures that improve preventative care. This global perspective on each patient’s individual treatment can potentially reduce abuse and readmissions.

Leverage a “Heads Up” Philosophy

You won’t hear many, if any, physicians state that they chose medicine for the abundance of paperwork.

The time EHR can save on administrative tasks provides the physician with more time to do what they enjoy—care for their patients. Patients often choose a practice because they want that personal connection with their physician. Someone who knows their story, and is aware of their health history. Most patients don’t enjoy waiting while the physician is writing notes, asking them to repeat their medical history, or trying to find the correct button on the computer. This won’t help to increase patient satisfaction, and gain patient loyalty. With the information right in front of you, you have more time to devote to quality communication, which gains your patient’s trust.

There are several secondary key benefits to practicing “Heads Up” Medicine with e-prescribing that help improve the patient experience by devoting your attention to your patient, not your computer. You’re still getting the essential information with an easy method of information collection by pointing and clicking.

  • Reviewing key points and a simple question and answer interview can help you build your narrative.
  • Your EHR is accessible on a mobile device, such an IPad, and not just on a website
  • You don’t have to spend the extra time typing the narrative in each time and starting from scratch.

Save Significant Time

Time is valuable to you, and your patients. The time saved with automated support does more than make your patients happy by getting them in and out of their visit quicker, it also shows that you respect their time.

Less time waiting and more time with their providers often results in better patient satisfaction. Word of mouth is often the most effective form of marketing and satisfied patients refer new patients to help you continue to grow your business.

Our software takes care of the bulk of your work with chart, bill and fill to reduce administrative tasks and improve your workflow. It helps you write the note, ensures that you get the billing codes correct and fills the prescription and orders lab work. This allows you to improve your workflow by:

  • Getting the billing done quickly and accurately to expedite payment
  • Allowing you to see more patients in the same amount of time
  • Helping you gain a better balance between your work and personal life to reduce the risk of burnout
  • Making sure your patients don’t leave because of extended wait times

Maintain a Personal Connection

Engaging more with your clients can foster patient satisfaction and loyalty to your practice. Your patients want compassionate care provided and human interaction, and you can leverage this “heads up” philosophy with the simple solutions offered in EHR software to manage the bulk of your administrative work.

Seek out technology and service solutions to improve your practice, increase patient satisfaction and provide you with more time to focus on priorities to aid in the growth of your practice, rather than being burdened with administrative tasks. Because you chose to work in private practice for the patients, not the paperwork.

About Tom Giannulli, MD, MS
Tom Giannulli, MD, MS, is the chief medical information officer at Kareo, a proud sponsor of Healthcare Scene. He is a respected innovator in the medical technology arena with more than 15 years of deep experience in mobile technology and medical software development. 

5 Steps to Ensure Revenue Integrity After Implementing a New EHR

Posted on June 18, 2018 I Written By

The following is a guest blog post by Lisa Eramo, a regular contributor to Kareo’s Go Practice Blog.

In the rush to implement EHRs for Meaningful Use incentives, many practices lost sight of what matters most for continued success—revenue integrity, says Joette Derricks, healthcare compliance and revenue integrity consultant in Baltimore, MD. Revenue integrity—the idea that practices must take proactive steps to capture and retain revenue—isn’t a novel concept. However, it’s becoming increasingly important for physician practices operating in a regulatory-driven environment, she adds.

Revenue integrity is also an important part of ensuring smooth cashflow during and after the transition to a new EHR, says Derricks. This is a time when revenue opportunities are easily overlooked as practices adjust to new navigation, templates, and more, she adds.

Revenue integrity is all about compliance, says Derricks. “It’s about taking a holistic approach to operational efficiency, regulatory compliance, and maximizing reimbursement,” she adds. “It’s about doing things the right way.”

Maximizing reimbursement isn’t about ‘gaming’ the system to upcode. Rather, it’s about implementing processes and procedures to ensure that practices are paid for all of the services they perform without leaving money on the table or generating revenue that payers will later recoup, she explains.

Derricks provides five simple steps practices can take to ensure revenue integrity following an EHR implementation:

1. Review EHR templates. Do templates include the most specific CPT and ICD-10-CM codes? And do physicians understand the importance of avoiding unspecified codes, when possible?

2. Examine the interface between the EHR and practice management system. Do the codes that physicians assign in the EHR feed correctly into the practice management system? For example, when a physician performs an E/M service in addition to a procedure, does the EHR map both codes to the practice management system for billing purposes? Does the practice management system correctly bundle and unbundle services, when appropriate?

3. Run your numbers frequently. Ideally, practices will perform a monthly data analysis to help gauge performance and identify potential missed revenue opportunities, says Derricks. For example, she suggests running a report of the practice’s top 20 billing codes in a particular month. Then, compare those codes with the top 20 codes the practice billed that same month in the previous year. What has changed, and why? And have these changes benefited or hurt the practice? For example, practices may see new codes in that list because they added chronic care or transitional care management, both of which provide additional revenue. Or practices may discover a system glitch that incorrectly bundled services that are separately payable, thus causing a revenue loss.

“Everybody can play the ‘I’m too busy’ game, but this is too important to fall into that trap,” says Derricks. “I applaud the office manager or practice administrator who recognizes the value of constantly being on the lookout for system-wide improvements and analyzing their own numbers.”

Some practice management systems provide robust billing analytics that can help practices identify the root cause of billing errors and omissions. Working with a consultant is another option, says Derricks. Consultants provide unbiased input regarding inefficiencies and vulnerabilities and can provide a ‘fresh set of eyes’ necessary to effect change. They also often have access to benchmarking tools and other resources that can help practices identify revenue gaps and delays, she adds.

For example, Derricks suggests performing an assessment for revenue gaps and roadblocks to reduce the workflow process errors that delay revenue. Download the assessment.

4. Provide physician training. Physicians need thorough training on how to use the EHR properly so as to avoid data omissions, says Derricks. They also need annual training on new CPT and ICD-10-CM codes as well as new documentation requirements, she adds.

5. Create an environment that promotes compliance. This requires a top-down approach from physicians and practice managers, says Derricks. “Everyone should have their eyes open and feel comfortable being able to address concerns,” she says. “It should be an open-door policy in terms of looking at processes versus putting your head down.”

About Lisa Eramo
Lisa Eramo is a regular contributor to Kareo’s Go Practice Blog, as well as other healthcare publications, websites and blogs, including the AHIMA Journal. Her focus areas are medical coding, clinical documentation improvement and healthcare quality/efficiency.  Kareo is a proud sponsor of Healthcare Scene.

Designing for the Whole Patient Journey: Lumeon Enters the US Health Provider Market

Posted on April 23, 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.

Lots of companies strive to unshackle health IT’s potential to make the health care industry more engaging, more adaptable, and more efficient. Lumeon intrigues me in this space because they have a holistic approach that seems to be producing good results in the UK and Europe–and recently they have entered the US market.

Superficially, the elements of the Lumeon platform echo advances made by many other health IT applications. Alerts and reminders? Check. Workflow automation? Check. Integration with a variety of EHRs? Of course! But there is something more to Lumeon’s approach to design that makes it a significant player. I had the opportunity to talk to Andrew Wyatt, Chief Operating Officer, to hear what he felt were Lumeon’s unique strengths.

Before discussing the platform itself, we have to understand Lumeon’s devotion to understanding the patient’s end-to-end experience, also sometimes known as the patient journey. Lumeon is not so idealistic as to ask providers to consider a patient’s needs from womb to tomb–although that would certainly help. But they ask such questions as: can the patient physically get to appointments? Can she navigate her apartment building’s stairs and her apartment after discharge from surgery? Can she get her medication?

Lumeon workflow view

*Lumeon workflow view

Such questions are the beginning of good user experience design (UX), and are critical to successful treatment. This is why I covered the HxRefactored conference in Boston in 2016 and 2017. Such questions were central to the conference.

It’s also intriguing that criminal justice reformers focus attention on the whole sequence of punishment and rehabilitation, including reentry into mainstream society.

Thinking about every step of the patient experience, before and after treatments as well as when she enters the office, is called a longitudinal view. Even in countries with national health care systems, less than half the institutions take such a view, and adoption of the view is growing only slowly.

Another trait of longitudinal thinking Wyatt looks for is coordinated care with strong involvement from the family. The main problem he ascribed to current health IT systems is that they serve the clinician. (I think many doctors would dispute this, saying that the systems serve only administrators and payers–not the clinician or the patient.)

Here are a couple success stories from Wyatt. After summarizing them, I’ll look at the platform that made them possible.

Alliance Medical, a major provider of MRI scans and other imaging services, used Lumeon to streamline the entire patient journey, from initial referral to delivery of final image and report. For instance, an online form asks patients during the intake process whether the patient has metal in his body, which would indicate the use of an alternative test instead of an MRI. The next question then becomes what test would meet the current diagnostic needs and be reimbursed by the payer. Lumeon automates these logistical tasks. After the test, automation provided by the Lumeon platform can make sure that a clinician reviews the image within the required time and that the image gets to the people who need it.

Another large provider in ophthalmology looked for a way to improve efficiency and outcomes in the common disease of glaucoma, by putting images of the eye in a cloud and providing a preliminary, automated diagnosis that the doctor would check. None of the cloud and telemedicine solutions covered ophthalmology, so the practice used the Lumeon platform to create one. The design process functioned as a discipline allowing them to put a robust process for processing patients in place, leading to better outcomes. From the patient’s point of view, the change was even more dramatic: they could come in to the office just once instead of four times to get their diagnosis.

An imaging provider found that they wasted 5 to 10 minutes each time they moved a machine between an upper body position and a lower body position. They saved many hours–and therefore millions of dollars–simply by scheduling all the upper body scans for one part of the day and all lower body scans for another. Lumeon made this planning possible.

In most of the US, value-based care is still in its infancy. The longitudinal view is not found widely in health care. But Wyatt says his service can help businesses stuck in the fee-for-service model too. For example, one surgical practice suffered lots of delays and cancellations because the necessary paperwork wasn’t complete the day before surgery. Lumeon helped them build a system that knew what tests were needed before each surgery and that prompted staff to get them done on time. The system required coordination of many physicians and labs.

Another example of a solution that is valuable in fee-for-service contexts is creating a reminder for calling colonoscopy patients when they need to repeat the procedure. Each patient has to be called at a different time interval, which can be years in the future.

Lumeon has been in business 12 years and serves about 60 providers in the UK and Europe, some very large. They provide the service on a SaaS basis, running on a HIPAA-compliant AWS cloud except in the UK, where they run their own data center in order to interact with legacy National Health Service systems.

The company has encountered along the way an enormous range of health care disciplines, with organizations ranging from small to huge in size, and some needing only a simple alerting service while others re-imagined the whole patient journey. Wyatt says that their design process helps the care provider articulate the care pathway they want to support and then automate it. Certainly, a powerful and flexible platform is needed to support so many services. As Wyatt said, “Health care is not linear.” He describes three key parts to the Lumeon system:

  1. Integration engine. This is what allows them to interact with the EHR, as well as with other IT systems such as Salesforce. Often, the unique workflow system developed by Lumeon for the site can pop up inside the EHR interface, which is important because doctors hate to exit a workflow and start up another.

    Any new system they encounter–for instance, some institutions have unique IT systems they created in-house–can be plugged in by developing a driver for it. Wyatt made this seem like a small job, which underscores that a lack of data exchange among hospitals is due to business and organizational factors, not technical EHR problems. Web services and a growing support for FHIR make integration easier

  2. Communications. Like the integration engine, this has a common substrate and a multiplicity of interfaces so doctors, patients, and all those involved in the health care journey can use text, email, web forms, and mobile apps as they choose.

  3. Workflow or content engine. Once they learn the system, clinicians can develop pathways without going back to Lumeon for support. The body scan solution mentioned earlier is an example of a solution designed and implemented entirely by the clinical service on its own.

  4. Transparency is another benefit of a good workflow design. In most environments, staff must remember complex sequences of events that vary from patient to patient (ordering labs, making referrals, etc.). The sequence is usually opaque to the patient herself. A typical Lumeon design will show the milestones in a visual form so everybody knows what steps took place and what remain to be done.

Wyatt describes Lumeon as a big step beyond most current workflow and messaging solutions. It will be interesting to watch the company’s growth, and to see which of its traits are adopted by other health IT firms.

Moving from “Reporting on” to “Leading” Healthcare – A Conversation with Dr. Halee Fischer-Wright, President & CEO of MGMA

Posted on October 11, 2017 I Written By

Colin Hung is the co-founder of the #hcldr (healthcare leadership) tweetchat one of the most popular and active healthcare social media communities on Twitter. Colin speaks, tweets and blogs regularly about healthcare, technology, marketing and leadership. He is currently an independent marketing consultant working with leading healthIT companies. Colin is a member of #TheWalkingGallery. His Twitter handle is: @Colin_Hung.

In Chapter 3 of Dr. Halee Fischer-Wright’s new book Back to Balance, she writes: “People are increasingly being treated as if they are the same. Science and data are being used to decrease variability in an attempt to get doctors to treat patients in predictable ways.” This statement is Fischer-Wright’s way of saying that the current focus on standardization of healthcare processes in the quest to reduce costs and increase quality may not be the brass ring we should be striving for. She believes that a balance is needed between healthcare standardization and the fact that each patient is a unique individual.

As president of the Medical Group Management Association (MGMA), a role Fischer-Wright has held since 2015, she is uniquely positioned to see first-hand the impact standardization (from both legislative and technological forces) has had on the medical profession. With over 40,000 members, MGMA represents many of America’s physician practices – a group particularly hard hit over the past few years by the technology compliance requirements of Meaningful Use and changes to reimbursements.

For many physician practices Meaningful Use has turned out to be more of a compliance program rather than an incentive program. To meet the program’s requirements, physicians have had to alter their workflows and documentation approaches. Complying with the program and satisfying the reporting requirements became the focus, which Fischer-Wright believes is a terrible unintended consequence.

“We have been so focused on standardizing the way doctors work that we have taken our eyes off the real goal,” said Fischer-Wright in and interview with HealthcareScene. “As physicians our focus needs to be on patient outcomes not whether we documented the encounter in a certain way. In our drive to mass standardization, we are in danger of ingraining the false belief that populations of patients behave in the same way and can be treated through a single standardized treatment regimen. That’s simply not the case. Patients are unique.”

Achieving a balance in healthcare will not be easy – a sentiment that permeates Back to Balance, but Fischer-Wright is certain that healthcare technology will play a key role: “We need HealthIT companies to stop focusing just on what can be done and start working on enabling what needs to be done. Physicians want to leverage technology to deliver better care to patient at a lower cost, but not at the expense of the patient/physician relationship. Let’s stop building tools that force doctors to stare at the computer screen instead of making eye contact with their patients.”

To that end, Fischer-Wright issued a friendly challenge to the vendors in the MGMA17 exhibit hall: “Create products and services that physicians actually enjoy using. Help reduce barriers between physician, patients and between healthcare organizations. Empower care don’t detract from it.”

She went on to say that MGMA itself will be stepping up to help champion the cause of better HealthIT for patients AND physicians. In fact, Fischer-Wright was excited to talk about the new direction for MGMA as an organization. For most of its history, MGMA has reported on the healthcare industry from a physician practice perspective. Over the past year with the help of a supportive Board of Directors and active members, the MGMA leadership team has begun to shift the organization to a more prominent leadership role.

“We are going to take a much more active role in healthcare. We are going to focus on fixing healthcare from the ground up –  from providers & patients upwards. In the next few years MGMA will be much bigger, much strong and even more relevant to physician practices. We are forging partnerships with other key players in healthcare, federal/state/local governments and other associations/societies.“

Members should expect more conferences, more educational opportunities and more publications on a more frequent basis from MGMA going forward. Fischer-Wright also hinted at several new technology-related offerings but opted not to provide details. Looking at the latest news from MGMA on their revamped data-gathering/analytics, however, it would not be surprising if their new offerings were data related. MGMA is one of the few organizations that regularly collects information on and provides context on the state of physician practices in the US.

It will be exciting to watch MGMA evolve in the years ahead.

Exchange Value: A Review of Our Bodies, Our Data by Adam Tanner (Part 3 of 3)

Posted on January 27, 2017 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 raised the question of whether data brokering in health care is responsible for raising or lower costs. My argument that it increases costs looks at three common targets for marketing:

  • Patients, who are targeted by clinicians for treatments they may not need or have thought of

  • Doctors, who are directed by pharma companies toward expensive drugs that might not pay off in effectiveness

  • Payers, who pay more for diagnoses and procedures because analytics help doctors maximize charges

Tanner flags the pharma industry for selling drugs that perform no better than cheaper alternatives (Chapter 13, page 146), and even drugs that are barely effective at all despite having undergone clinical trials. Anyway, Tanner cites Hong Kong and Europe as places far more protective of personal data than the United States (Chapter 14, page 152), and they don’t suffer higher health care costs–quite the contrary.

Strangely, there is no real evidence so far that data sales have produced either harm to patients or treatment breakthroughs (Conclusion, 163). But the supermarket analogy does open up the possibility that patients could be induced to share anonymized data voluntarily by being reimbursed for it (Chapter 14, page 157). I have heard this idea aired many times, and it fits with the larger movement called Vendor Relationship Management. The problem with such ideas is the close horizon limiting our vision in a fast-moving technological world. People can probably understand and agree to share data for particular research projects, with or without financial reimbursement. But many researchers keep data for decades and recombine it with other data sets for unanticipated projects. If patients are to sign open-ended, long-term agreements, how can they judge the potential benefits and potential risks of releasing their data?

Data for sale, but not for treatment

In Chapter 11, Tanner takes up the perennial question of patient activists: why can drug companies get detailed reports on patient conditions and medications, but my specialist has to repeat a test on me because she can’t get my records from the doctor who referred me to her? Tanner mercifully shields here from the technical arguments behind this question–sparing us, for instance, a detailed discussion of vagaries in HL7 specifications or workflow issues in the use of Health Information Exchanges–but strongly suggests that the problem lies with the motivations of health care providers, not with technical interoperability.

And this makes sense. Doctors do not have to engage in explicit “blocking” (a slippery term) to keep data away from fellow practitioners. For a long time they were used to just saying “no” to requests for data, even after that was made illegal by HIPAA. But their obstruction is facilitated by vendors equally uninterested in data exchange. Here Tanner discards his usual pugilistic journalism and gives Judy Faulkner an easy time of it (perhaps because she was a rare CEO polite enough to talk to him, and also because she expressed an ethical aversion to sharing patient data) and doesn’t air such facts as the incompatibilities between different Epic installations, Epic’s tendency to exchange records only with other Epic installations, and the difficulties it introduces toward companies that want to interconnect.

Tanner does not address a revolution in data storage that many patient advocates have called for, which would at one stroke address both the Chapter 11 problem of patient access to data and the book’s larger critique of data selling: storing the data at a site controlled by the patient. If the patient determined who got access to data, she would simply open it to each new specialist or team she encounters. She could also grant access to researchers and even, if she chooses, to marketers.

What we can learn from Chapter 9 (although Tanner does not tell us this) is that health care organizations are poorly prepared to protect data. In this woeful weakness they are just like TJX (owner of the T.J. Maxx stores), major financial institutions, and the Democratic National Committee. All of these leading institutions have suffered breaches enabled by weak computer security. Patients and doctors may feel reluctant to put data online in the current environment of vulnerability, but there is nothing special about the health care field that makes it more vulnerable than other institutions. Here again, storing the data with the individual patient may break it into smaller components and therefore make it harder for attackers to find.

Patient health records present new challenges, but the technology is in place and the industry can develop consent mechanisms to smooth out the processes for data exchange. Furthermore, some data will still remain with the labs and pharmacies that have to collect it for financial reasons, and the Supreme Court has given them the right to market that data.

So we are left with ambiguities throughout the area of health data collection. There are few clear paths forward and many trade-offs to make. In this I agree ultimately with Tanner. He said that his book was meant to open a discussion. Among many of us, the discussion has already started, and Tanner provides valuable input.

Exchange Value: A Review of Our Bodies, Our Data by Adam Tanner (Part 2 of 3)

Posted on January 26, 2017 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 summarized the evolution of data brokering in patient information and how it was justified ethically and legally, partly because most data is de-identified. Now we’ll take a look at just what that means.

The identified patient

Although doctors can be individually and precisely identified when they prescribe medicines, patient data is supposedly de-identified so that none of us can be stigmatized when trying to buy insurance, rent an apartment, or apply for a job. The effectiveness of anonymization or de-identification is one of the most hotly debated topics in health IT, and in the computer field more generally.

I have found a disturbing split between experts on this subject. Computer science experts don’t just criticize de-identification, but speak of it as something of a joke, assuming that it can easily be overcome by those with a will to do so. But those who know de-identification best (such as the authors of a book I edited, Anonymizing Health Data) point out that intelligent, well-designed de-identification databases have been resistant to cracking, and that the highly publicized successes in re-identification have used databases that were de-identified unprofessionally and poorly. That said, many entities (including the South Korean institutions whose practices are described in Chapter 10, page 110 of Tanner’s book) don’t call on the relatively rare experts in de-identification to do things right, and therefore fall into the category of unprofessional and poor de-identification.

Tanner accurately pinpoints specific vulnerabilities in patient data, such as the inclusion of genetic information (Chapter 9, page 96). A couple of companies promise de-identified genetic data (Chapter 12, page 130, and Conclusion, page 162), which all the experts agree is impossible due to the wide availability of identified genomes out in the field for comparison (Conclusion, page 162).

Tanner has come down on the side of easy re-identification, having done research in many unconventional areas lacking professional de-identification. However, he occasionally misses a nuance, as when describing the re-identification of people in the Personal Genome Project (Chapter 8 page 92). The PGP is a uniquely idealistic initiative. People who join this project relinquish interest in anonymity (Chapter 9, page 96), declaring their willingness to risk identification in pursuit of the greater good of finding new cures.

In the US, no legal requirement for anonymization interferes with selling personal data collected on social media sites, from retailers, from fitness devices, or from genetic testing labs. For most brokers, no ethical barriers to selling data exist either, although Apple HealthKit bars it (Chapter 14 page 155). So more and more data about our health is circulating widely.

With all these data sets floating around–some supposedly anonymized, some tightly tied to your identity–is anonymization dead? Every anonymized data set already contains a few individuals who can be theoretically re-identified; determining this number is part of the technical process of de-identification? Will more and more of us fall into this category as time goes on, victims of advanced data mining and the “mosaic effect” (combining records from different data sets)? This is a distinct possibility for the future, but in the present, there are no examples of re-identifying data that is anonymized properly–the last word properly being all important here. (The authors of Anonymizing Health Data talk of defensible anonymization, meaning you can show you used research-vetted processes.) Even Latanya Sweeney, whom Tanner tries to portray in Chapter 9 as a relentless attacker who strips away the protections of supposedly de-identified data, believes that data can be shared safely and anonymously.

To address people’s fretting over anonymization, I invoke the analogy of encryption. We know that our secret keys can be broken, given enough computing power. Over the decades, as Moore’s Law and the growth of large computing clusters have increased computing power, the recommended size of keys has also grown. But someday, someone will assemble the power (or find a new algorithm) that cracks our keys. We know this, yet we haven’t stopped using encryption. Why give up the benefits of sharing anonymized data, then? What hurts us is the illegal data breaches that happen on average more than once a day, not the hypothetical re-identification of patients.

To me, the more pressing question is what the data is being used for. No technology can be assessed outside of its economic and social context.

Almighty capitalism

One lesson I take from the creation of a patient data market, but which Tanner doesn’t discuss, is its existence as a side effect of high costs and large inefficiencies in health care generally. In countries that put more controls on doctors’ leeway to order drugs, tests, and other treatments, there is less wiggle room for the marketing of unnecessary or ineffective products.

Tanner does touch on the tendency of the data broker market toward monopoly or oligopoly. Once a company such as IMS Health builds up an enormous historical record, competing is hard. Although Tanner does not explore the affect of size on costs, it is reasonable to expect that low competition fosters padding in the prices of data.

Thus, I believe the inflated health care market leaves lots of room for marketing, and generally props up the companies selling data. The use of data for marketing may actually hinder its use for research, because marketers are willing to pay so much more than research facilities (Conclusion, pages 163-164).

Not everybody sells the data they collect. In Chapter 13, Tanner documents a complicated spectrum for anonymized data, ranging from unpublicized sales to requiring patient consent to forgoing all data sales (for instance, footnote 6 to Chapter 13 lists claims by Salesforce.com and Surescripts not to sell patient information). Tenuous as trust in reputation may seem, it does offer some protection to patients. Companies that want to be reputable make sure not to re-identify individual patients (Chapter 7, page 72, Chapter 9, pages 88-90, and Chapter 9, page 99). But data is so valuable that even companies reluctant to enter that market struggle with that decision.

The medical field has also pushed data collectors to make data into a market for all comers. The popular online EHR, Practice Fusion, began with a stable business model offering its service for a monthly fee (Chapter 13, page 140). But it couldn’t persuade doctors to use the service until it moved to an advertising and data-sharing model, giving away the service supposedly for free. The American Medical Association, characteristically, has also found a way to extract profit from sale of patient data, and therefore has colluded in marketing to doctors (Chapter 5, page 41, and Chapter 6, page 54).

Thus, a Medivo executive makes a good argument (Chapter 13, page 147) that the medical field benefits from research without paying for the dissemination of data that makes research possible. Until doctors pony up for this effort, another source of funds has to support the collection and research use of data. And if you believe that valuable research insights come from this data (Chapter 14, page 154, and Conclusion, page 166), you are likely to develop some appreciation for the market they have created. Another obvious option is government support for the collection and provision of data for research, as is done in Britain and some Nordic countries, and to a lesser extent in the US (Chapter 14, pages 158-159).

But another common claim, aired in this book by a Cerner executive (Chapter 13, page 143) is that giving health data to marketers reduces costs across the system, similarly to how supermarkets grant discounts to shoppers willing to have their purchases tracked. I am not convinced that costs are reduced in either case. In the case of supermarkets, their discounts may persuade shoppers to spend more money on expensive items than they would have otherwise. In health care, the data goes to very questionable practices. These become the topic of the last part of this article.

Exchange Value: A Review of Our Bodies, Our Data by Adam Tanner (Part 1 of 3)

Posted on January 25, 2017 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.

A lot of people are feeling that major institutions of our time have been compromised, hijacked, or perverted in some way: journalism, social media, even politics. Readers of Adam Tanner’s new book, Our Bodies, Our Data: How Companies Make Billions Selling Our Medical Records, might well add health care data to that list.

Companies collecting our data–when they are not ruthlessly trying to keep their practices secret–hammer us with claims that this data will improve care and lower costs. Anecdotal evidence suggests it does. But the way this data is used now, it serves the business agendas of drug companies and health care providers who want to sell us treatments we don’t need. When you add up the waste of unnecessary tests and treatments along with the money spent on marketing, as well as the data collection that facilitates that marketing, I’d bet it dwarfs any savings we currently get from data collection.

How we got to our current data collection practices

Tanner provides a bit of history of data brokering in health care, along with some intriguing personalities who pushed the industry forward. At first, there was no economic incentive to collect data–even though visionary clinicians realized it could help find new diagnoses and treatments. Tanner says that the beginnings of data collection came with the miracle drugs developed after World War II. Now that pharmaceutical companies had a compelling story to tell, ground-breaking companies such as IMS Health (still a major player in the industry) started to help them target physicians who had both the means of using their drugs–that is, patients with the target disease–and an openness to persuasion.

Lots of data collection initiatives started with good intentions, some of which paid off. Tanner mentions, as one example, a computer program in the early 1970s that collected pharmacy data in the pursuit of two laudable goals (Chapter 2, page 13): preventing patients from getting multiple prescriptions for the same drug, and preventing adverse interactions between drugs. But the collection of pharmacy data soon found its way to the current dominant use: a way to help drug companies market high-profit medicines to physicians.

The dual role of data collection–improving care but taking advantage of patients, doctors, and payers–persists over the decades. For instance, Tanner mentions a project by IMS Health (which he treats pretty harshly in Chapter 5) collecting personal data from AIDS patients in 1997 (Chapter 7, page 70). Tanner doesn’t follow through to say what IMS did with the AIDS data, but I am guessing that AIDS patients don’t offer juicy marketing opportunities, and that this initiative was aimed at improving the use and effectiveness of treatments for this very needy population. And Chapter 7 ends with a list of true contributions to patient health and safety created by collecting patient data.

Chapter 6 covers the important legal battles fought by several New England states (including the scrappy little outpost known for its worship of independent thinking, New Hampshire) to prevent pharmacies from selling data on what doctors are prescribing. These attempts were quashed by the well-known 2011 Supreme Court ruling on Vermont’s law. All questions of privacy and fairness were submerged by considering the sale of data to be a matter of free speech. As we have seen during several decisions related to campaign financing, the current Supreme Court has a particularly expansive notion of what the First Amendment covers. I just wonder what they will say when someone who breaks into the records of an insurer or hospital and steals several million patient records pleads free speech to override the Computer Fraud and Abuse Act.

Tanner has become intrigued, and even enamored, by the organization Patient Privacy Rights and its founder, Deborah Peel. I am closely associated with this organization and with Peel as well, working on some of their privacy summits and bringing other people into their circle. Because Tanner airs some criticisms of Peel, I’d like to proffer my own observation that she has made exaggerated and unfair criticisms of health IT in the past, but has moderated her views a great deal. Working with experts in health IT sympathetic to patient privacy, she has established Patient Privacy Rights during the 2010 decade as a responsible and respected factor in the health care field. So I counter Tanner’s repeated quotes regarding Peel as “crazy” (Chapter 8, page 83) by hailing her as a reputable and crucial force in modern health IT.

Coincidentally, Tanner refers (Chapter 8, page 79) to a debate that I moderated between IMS representative Kim Gray and Michelle De Mooy (available in a YouTube video). The discussion started off quite tame but turned up valuable insights during the question-and-answer period (starting at 38:33 in the video) about data sharing and the role of de-identification.

While the Supreme Court ruling stripped doctors of control over data about their practices–a bit of poetic irony, perhaps, if you consider their storage of patient data over the decades as an unjust taking–the question of patient rights was treated as irrelevant. The lawyer for the data miners said, “The patients have nothing to do with this” (Chapter 6, page 57) and apparently went unchallenged. How can patients’ interest in their own data be of no concern? For that question we need to look at data anonymization, also known as de-identification. This will begin the next section of our article.