Book Review: Redefining the Boundaries of Medicine

“Redefining the Boundaries of Medicine” is a Mayo Clinic Press book that was written by Paul Cerrato, MA (senior research analyst and communications specialist, Mayo Clinic) and John Halamka, MD, MS (president, Mayo Clinic Platform). The authors have collaborated previously on three books and several journal articles.

The book is written for readers who are knowledgeable about the “only in the US” healthcare mix of research, medical practice, consumerism, and hardcore capitalism where money has an outsized influence on both individual health and the business of healthcare. Its dense typography and layout is hardly inviting, but it provides an excellent history of how we got to where we are in healthcare (hint: often illogically, stubbornly, and parochially) and how healthcare can be improved.

The book delivers what its title promises. The authors are predictably precise in their citations and conclusions, and they are on the provider front lines rather than ivory tower academics. In addition, Mayo Clinic Platform is working actively to apply data science and technologies to healthcare.

I admit that I wasn’t aware of the previous books that these authors co-wrote and wasn’t exactly sure what Mayo Clinic Platform does or what happened with John Halamka after he left BIDMC three-plus years ago. But I think these authors might be the go-to-experts that the healthcare industry needs as it rushes headlong into artificial intelligence and re-examines itself with an opportunity (or requirement) to change dramatically.

Here are some of the notes I took.

Artificial Intelligence

The book leads off with a chapter on artificial intelligence, where the authors observe that the human brain cannot process the amount of new information from journals and conferences, much less apply it at the bedside, and can’t analyze all available information to arrive at an accurate diagnosis. AI is also better than humans in analyzing diagnostic images, although system training must be carefully designed in an environment that has never-ending changes in scanning technology, coding and terminology, EHR configuration, changed institutional practices or order sets, and a changing patient mix that may not be applicable elsewhere.

A fascinating idea is that all broad research, whether powered by AI or not, overgeneralizes to the entire population instead of digging into patient subgroups. For example, a large study on the effect of lifestyle modification on cardiovascular disease was abandoned when no differences were seen between the intervention and control groups, suggesting that lifestyle doesn’t matter. However, applying sophisticated analytical technique found that lifestyle intervention actually worked in two subgroups that were otherwise lost in the large numbers: patients whose diabetes is poorly controlled and in those with well-controlled diabetes who self-report their health as good.

They also note that FDA’s approval of AI devices is inconsistent and often involves retrospective and/or single-site studies.

The authors conclude AI algorithms need to be more equitable and better validated before being placed into clinical use.

Medical Knowledge

Medicine’s history in the US involves paternalistic physicians; diagnosis and treatment protocols that were based on GOBSAT (good old boys sat around the table); and slow acceptance of research findings in favor of personal experience, anecdotes, and opinions lacking evidence.

Randomized controlled trials, especially those that conclude that a therapy was not beneficial, have weaknesses such as too-small sample size and inclusion criteria that may introduce bias or reduce clinical usefulness. RCTs should be supplemented with real-world evidence and cohort studies. 

The “heterogeneity of treatment effect” acknowledges that treatment benefit and risk can vary widely among patients. Patients know their conditions and see the effects of treatments firsthand, so N-of-1 trials comparing active treatment with placebo are a good idea.

“Patients like mine” data can help support decisions in the absence of RCT or observational studies now that EHR data is widely available, although it may require experts to turn patient data into actionable evidence.

Rethinking Medical Expertise

The public questions the value of medical expertise. Experienced clinicians use Type 1 thinking, in which pattern recognition can lead to quick conclusions involving common conditions as “disease scripts.” But sometimes it fails dramatically when a patient’s symptoms fall outside the norm. Type 2 reasoning starts with a hypothesis that is refined via logic and critical thinking, which can be more accurate and avoid bias and thinking shortcuts, but takes too long to conduct in high-volume settings.

The authors cite previous studies that found that peer-reviewed journals often rejected research that turned out to be important, questioning whether that publishing process is the best way to gestate new ideas.

Replacing “One Size Fits All” with Personalized Medicine

Full genomic sequencing is increasingly useful. Some experts say it should be performed at birth, whereas now newborns are screened for a small number of genetic disorders.

Large studies on using the antiplatelet drug clopidogrel for blood clots found that the drug outperformed aspirin in just two of each 100 patients, but the real challenge is to identify those two instead of incurring the cost and risks of giving it to everyone.

“Normal” lab ranges are just a statistical convention, and each person’s “normal” may be different and deviation from it may not indicate the presence of disease. Insurance will often pay for only drugs and treatments that appear effective for broad segments of the population.

Researchers search for one or two primary causes of a disease, such as HIV as a cause of AIDS or striving to control the blood sugar of diabetics, and immediately refocus all research on those causes. The outliers are rarely studied, such as the people who are exposed to HIV but don’t develop AIDS and why that might be. Correcting the condition for a given patient doesn’t necessarily deliver the expected benefit.

Communication

Too many clinicians still practice the “doctor knows best” model when patients don’t agree with their evidence-based interventions. Policy decisions are rarely made on science alone since beliefs and core values will usually win.

FDA knows that most drugs that it approves offer only slight benefit, but consumers aren’t capable of analyzing studies, especially when faced with direct-to-consumer advertising. The public is easily confused by correlation versus causation and relative value versus absolute risk, such a miracle drug that reduces the risk of some disease by 50% that really means that one person instead of two out of 1,000 patients will get it, which is hardly impressive. Schools do not teach critical thinking skills and the US doesn’t follow the lead of other countries that teach media literacy.

Interdisciplinary Patient Care

Researchers and clinicians need to communicate better. Experts say that NIH-funded research focuses on silos for particular conditions of interest without looking at how they relate to, or are affected by, other factors, which is an outdated understanding of medicine. DARPA might offer a better model.

Clinician fragmentation increased with the growth of specialty medicine, medical group consolidation and insurance programs networks that separated people from their specific doctor.

More than three-fourths of chronic diseases are caused by or exacerbated by lifestyle choices that can’t be easily explained or encouraged in the allotted 15-minute office visit.

Patient-generated data should be fed into EHRs.

You will be stimulated by the ideas the authors express in this book if you are comfortable reading journal abstracts and understand clinical practice, especially if your specialty is informatics. It seems like a slim read at under 200 pages, but is packed with information in being free of self-aggrandizement and pontificating (and again, the typeface is pretty crammed, so it’s got more content than you might think). If you or your organization want to be considered disruptive in healthcare, the authors are giving you great ideas of where you might focus.

Book Review: The Algorithm Will See You Now

“The Algorithm Will See You Now” is the first novel written by JL Lycette. It is a remarkably polished and engaging thriller that delves into the promise and pitfalls of artificial intelligence, corporate medical greed, and the ever-increasing tension between the science and the humanity of medicine.

The author’s day job persona is hematologist-oncologist Jennifer Lycette, MD (UCSF undergrad, UW medical school), so the book’s medical and hospital details are accurate.

I admit that I bought this book purely because it sounded kind of interesting and the Kindle version was on sale for just $0.99. Cheap Kindle books are usually amateurishly self-published junk, but not this one — it’s a gem.

The story is set in 2035. Surgery resident Hope Kestrel, MD works for Seattle-based health system Prognostic Intelligent Medical Algorithms, where she has earned the official title of high resident, which PRIMA uses instead of chief resident, in its OASIS unit (Oncologic and Surgical Intervention Success.)

Medical technology has come a long way by 2035, as diagnosis and treatment is performed at PRIMA entirely with AI and a voice-powered chart assistant called Osler. The PRIMA health system’s AI determines upfront whether a patron (its word for “patient”) will benefit from a particular treatment or is instead likely to be a “non-responder.” The goal is to “optimize.” Or as Hope describes, “The AI frees both patients and doctors from the fallacy of choice. The algorithms are more trustworthy than people.”

An anonymous podcaster is critical of PRIMA, however. The algorithm is a mysterious black box. Patrons don’t pay deductibles or co-pays at PRIMA, but aren’t eligible for services for which AI predicts they will be non-responders, and rumor is that PRIMA licenses the technology to insurers who use it to deny coverage. The podcaster summarizes, “The most dangerous lies are the ones that use the truth to sell themselves.”

Hope is fully behind the AI system, declaring that any doctor who won’t embrace algorithm-directed care is as dangerous as surgeons in the 1800s who mocked sterile technique because they didn’t believe in germ theory.

The story continues with each key player, including the most vocal AI proponents, struggling with the health issues of loved ones and themselves, for which AI seems heartless and even wrong based on accidentally or intentionally flawed data training. They don’t face the patrons who are non-responders, but they can’t avoid seeing how the system works for those they love.

There’s also the business angle, as power-hungry PRIMA executives are working on the acquisition of Seattle’s biggest medical group, with plans to go regional, national, and then to be positioned to run a privatized Medicare system.

PRIMA’s medical residents are constantly scored, reassigned, and threatened for various transgressions, one of which is having non-responder patients for which blame must be assigned since nobody will admit that the algorithm could be wrong.

A recurring theme is the accuracy of the AI. Is it wrong one time out of 10,000, as PRIMA touts, or is only 95% accurate as behind-the-scenes data seems to suggest, leaving one patient in 20 to go untreated or to receive treatment unnecessarily that presents side effects and risks? And what are the clinical implications of overfitting, where the computer thinks it sees a pattern that doesn’t exist in the real world?

An uncomfortable moment ensues in a medical staff meeting of the practice that PRIMA hopes to acquire. A skeptical doctor expresses doubt about the AI’s accuracy, then when pressed to state his own accuracy rate, responds instead with a quote from Sir William Osler: “Medicine is a science of uncertainty and an art of probability.” It’s a valid point — doctors really don’t know their own accuracy, so to criticize that of the machine is a tenuous position.

The book is a compelling read that ricochets off the dangers of big data, corporate ambition, and what doctors are supposed to do when told that AI will be taking over their decision-making. It is really written like a movie screenplay, mostly “show don’t tell” scenes rather than exposition, playing for me like an episode of “Black Mirror.” I bail out early on most novels, including those of big-name authors, when I run out of patience for irritating writing style, sloppy editing, and inconsistent character behavior, but this one was remarkably well crafted and hard to put down.

The author wrote most of this book in the pre-2020 dark ages before COVID-19, ChatGPT, and health systems that are fueled by acquisitions racing each other to become national providers to compete with corporate giants such as Amazon and CVS Health. It is not preachy or prescriptive about any of the touchy healthcare topics that its characters are living through 10+ years in the future, which requires the reader to decide whether the tale it tells is entertaining or cautionary.

The author says the idea for the novel came when she saw IBM Watson touted for oncology before it fizzled. She practices as a rural community oncologist, and while she hopes to see the day when precision medicine’s abilities expand enough to cover more than a few patients, she worries about under-resourced systems and disparities in care. Her second book, due in November 2023, is a prequel to “The Algorithm Will See You Now.”

Book Review: “Big Med”

Authors David Dranove (Northwestern University strategy professor, PhD in economics, healthcare system antitrust expert) and Lawton R. Burns (Penn health care management professor, PhD in sociology, long-time analyst of physician-hospital integration) aren’t very cheery about the prospects of our profit-driven US healthcare system in their just-published “Big Med.” They repeatedly use the term“ depressing” to describe the mess we’re in. While they offer few optimistic solutions, they provide a valuable service in at least explaining how we got here.

Health system consolidation has resulted in poorly run, bigger organizations whose incentive is to maximize profit and business size rather than manage cost or improve health. Despite health system claims that their mega-mergers will result in efficiency, scale, and lower costs, that never actually happens. The only predictable result of such M&A activity is that newly enlarged health systems use their market clout to raise prices, to the point that they drive half to two-thirds of US healthcare spending. Yet only 5% of consumers blame hospitals and doctors for an expensive, broken health system, and nobody even notices that the revenue and executive compensation of big health systems exceed that of some major global brands

The magnitude of the problem keeps growing, but the problem itself goes back to the beginnings of health insurance. A government report from 1928 concluded that wasteful spending made healthcare inaccessible to most Americans. It called for universal health insurance, provider integration, payment reform, and a focus on prevention. The American Medical Association was a loud critic of all forms of health insurance, eventually including Medicare and Medicaid (they lumped all forms of health insurance together as being Communist), but they liked the idea of the prepaid hospital insurance plan that Baylor Hospital created in 1929 that eventually spread into a national Blue Cross umbrella. Insurance company board members were mostly hospital executives who made sure that the plans supported blank check spending – the insurer couldn’t question the amounts billed, hospitals were not forced to compete on price or quality, and the insurance plans did not require patient cost-sharing that would give them incentive to shop around or audit their own bills. Doctors kept their autonomy without hospital oversight and were immune from having their decisions questioned.

The rollout of Medicare and Medicaid dramatically increased the percentage of insured Americans, which then drove jumps in hospital bed count, physician numbers (many of them high-earning specialists), and overall healthcare spending. Hospitals started affiliating with medical schools to create academic medical centers. The jump in healthcare spending strained federal and state budgets, leading to these unsuccessful cost containment efforts:

• Prospective payment system. Hospitals learned to game the system.
• Capitation. Primary care doctors were unwilling to take on risk since they couldn’t control the expensive decisions made by specialists.
• Certificates of need to limit facility growth. Hospitals controlled the local politics involved with reviewing applications, legitimizing the megaprovider status quo. Only big health systems could afford the lawyers and consultants that were needed to successfully argue competitive issues.
• Ambulatory surgery centers. Hospitals simply stole the formula and built their own, as the percentage of hospitals with outpatient departments increased from 26% in 1975 to 77% in 1988. Hospitals insisted that insurers grant them exclusive rights to perform outpatient surgery, with the closed networks, raising ASC legal challenges that mostly failed because of the difficulty involved in defining the extent of the local market that in which competition would be limited.
• Antitrust laws. Hospitals used their political cloud and some creative defining of their markets (based on their multiple facilities and patient travel patterns to tertiary care facilities) to deflect legal challenges.

Hospitals faced multiple threats in the 1990s – reduced federal payments, ASC competition, and the proposed Clinton health plan that called for massive restructuring in payment and delivery. Urged on by consultants and trade magazines, they pursued vertical integration, in which everyone wanted to be Kaiser Permanente in owning physician practices and health plans and working with private equity-backed practice management firms. Models that were developed in California and Minnesota were copied even though PCPs were the only providers who were heavily capitated. The result was that health systems:

• Made their flagship hospital’s CEO the health system CEO.
• Pursued horizontal mergers with feeder institutions.
• Acquired primary care and specialist practices.
• Opened freestanding outpatient and diagnostic facilities.
• Ran therapy and home care services.
• Bought long-term care facilities.
• Launched their own insurance plans (sometimes).

The larger, more complex organizations favored executives whose approach was pure business rather than hospital administration. They focused on economies of scale, centralized management, systems building, and group purchasing. Health systems developed complex corporate structures and holding companies, some of them unrelated to healthcare, and moved to product line management in which unprofitable services were eliminated regardless of local need. Doctors were held accountable to economic credentialing.

Health systems competed to buy physician practices, paying $1 million or more upfront to acquire a PCP practice that was netting $150,000 while guaranteeing the income, hours, and freedom from oversight of the selling doctors. They ended up with the same doctors making the same number of referrals, except that they had spent fortunes buying their practices and watching physician productivity drop. Physician-hospital organizations mostly lost money as they generated no managed care contracts, much less risk-based contracts. IDNs allowed nearly all medical staff into their PHOs instead of choosing more cost-effective ones or trying to change practice patterns. Specialists who didn’t want to risk their high incomes beat the system by threatening to take their business to other health systems.

Physicians, meanwhile, formed their own integrated delivery networks, hoping to let someone else deal with EHRs and billing. They signed up with now-defunct but then high-flying national physician practice management firms such as PhyCor and MedPartners.

The end result of IDNs was no change in cost or quality, lots of money spent chasing scale, the emergence of highly paid health system executives who listened too closely to consultants, slow decision-making, and loss of connection with frontline staff and physicians.

Lack of EHR capability doomed integration in the 1990s. Health systems used EHRs to control the “physician’s pen” and turn those systems into billing machines, but patient documentation diverged from clinical reality in being cranked out solely to increase billing. Extracting clinical information was hard because most of it was in non-discrete form.

Hospital acquisition of practices picked up again due to hospital-friendly billing policies in which CMS, which allowed them to bill more for the same physician performing the same work in the same office. Cardiology and radiology practices were attractive targets.

The authors list a few solutions that haven been touted to help contain healthcare costs along with why they don’t think they will work.

• Accountable care organizations, aka “HMO lites.” They have not delivered cost savings, and even optimistic CMS estimates show a possible Medicare saving of just 0.04%, with providers spending twice as much to join run twice as much as the potential savings.
• Triple Aim (population health, per-capita cost, and patient experience). Hospitals have little influence over life expectancy and morbidity.
• Scaled-up medical practices. Scale economies usually taper off once a physician group is larger than 5-10 physicians, although the high cost of EHRs may have raised that optimal group size to 25-50 doctors. Mergers are not subject to antitrust review unless an insurer complains and expansion is usually piecemeal and hard to track as 1-2 doctors are added in each transaction, so regulatory oversight of acquisitions is minimal.
• Consumer activism. Most Americans don’t understand the cost and mortality of chronic disease. They don’t pay most of the cost, so avoiding low-value care isn’t important to them.
• Disruption. Doesn’t work in healthcare because lower quality at a lower price isn’t acceptable. Disruptors don’t bring new resources or capabilities, don’t understand healthcare, and mostly attempt to ride M&A activity to success.
• Smart technology and apps. The high-cost 20% of the population with expensive chronic conditions have little to gain from their use. Vendors usually bypass that market because it is hard to reach.
• Mergers, such as CVS-Aetna combining drugstores with in-store clinics. This type of combination hasn’t historically improved care coordination and didn’t accomplish much when megaproviders tried it. Their only asset is convenient store locations and the average clinic sees only 10-30 patients per day and loses money, which is why Walgreens dropped the idea and partnered with local health systems. Analytics and predictive modeling haven’t done much for insurers since at-risk members must be contacted, activated, and convinced to change behaviors.
• Digital health technologies. Little evidence exists that they have had any impact on access, cost, and quality. Transparency tools don’t translated into lower spending because their users are mostly young and healthy. People don’t worry about healthcare costs once they have reached their deductible because they aren’t the one paying.
• Artificial intelligence. Good at predicting health, but not good at advising physicians how to address it. AI doesn’t work well in the absence of rules, when information is lacking, or when decision-making isn’t clear cut.
• Telemedicine. Evidence of cost savings is minimal. It may be more widely used by the “worried well” than the chronically ill and thus may promote excessive use of screening tests that introduce their own risk.
• Genomics and personalized medicine. These are a breakthrough for only small patient populations. They explain only a small percentage of health status variation versus patient behaviors.

The authors make these recommendations:

• Change antitrust oversight to look at value chains. Reward those that use big data, develop treatment protocols, incent quality, and match patient needs. Savings should go beyond the 1-2% that having a competing hospital in a given market offers. Each market should have at least three competing value chains, at least one of them made up of independent providers, and make divestiture mandatory in smaller markers where megaproviders already dominate (or as an alternative, leave them alone if they agree to keep costs below Medicare reimbursement plus a small markup). Require all provider mergers to be pre-notified to the Federal Trade Commission, recognizing that most of them will be exempted because of low risk. Don’t try to regulate cross-market mergers.
• Recognize that fee-for-service isn’t all bad, especially when high-deductible insurance plans require patients to approve the cost.
• Put clinicians in charge of running health systems, no different than engineering firms, software companies, and law firms that are led by experts who members respect and follow.
• Improve EHR interoperability.
• Increase home-based care and improve care transitions.
• Improve communications among providers.
• Align bonuses. Simple metrics do not capture what any given doctor knows about the performance of their peers.

The takeaway of the book is that non-profit megaproviders are the biggest driver of healthcare costs and are using their local and regional goodwill to get away with competition-impeding mergers, indefensible pricing, and lack of operational and financial transparency. Market forces, technology, and consumerism won’t create price-lowering and quality-increasing competition as they have in other industries. The ever-increasing number of physicians who are employed by big health systems has blunted the potential physician pushback on the status quo, employer pressure has been mostly a bust, and consumers are still left being automatically enrolled in an “only in America” reverse lottery in which contracting a major illness is likely to leave them bankrupt while everybody else continues in the status quo happy that it didn’t happen to them.

Thanks to the HIStalk reader who asked me to review this book and to University of Chicago Press for providing an electronic copy.

Book Report: “UnHealthcare: A Manifesto for Health Assurance”

Spoiler alert: a technologist turned billionaire investor opines that healthcare can be saved only by technologists and billionaire investors.

Non-healthcare people who sell books or companies are always predicting the suddenly imminent rise of consumerism that will upend the deeply entrenched healthcare establishment. They say (and sometimes even believe) that our smart phones will empower us consumers to Uberize an industry of insurers, drug and device manufacturers, doctors, health systems, and politicians. Our discretionary healthcare spending and technology assets will force them to cower to our demands to be treated as individuals and choice-empowered customers.

Do you feel more empowered in your dealing with hospitals, doctors, pharmacies, and your insurance company? Has your phone disrupted the status quo and created a choice-laden healthcare environment of competition and price transparency? Has your armada of consumer technology made you healthier? You probably won’t like this book if not, because it is re-promising a brave new healthcare world in arguing that the old one can’t survive despite the fact that the entrenched players keep getting bigger, richer, and more influential.  

Hemant Taneja started and sold Livongo and other companies, making him a billionaire. Steve Klasko, MD, MBA runs Thomas Jefferson University and Jefferson Health, and while I guess he’s not quite in the billionaire category, he has augmented his generous Jefferson millions with lucrative board seats and participation in a freshly planned IPO of Teneja and other Livongo alumni. The world view of the authors isn’t necessarily yours or mine, either as industry participants or patients.

Both authors think that Livongo’s diabetes management technology was a game-changer, although last time I looked, we still have a few dozen million diabetics in the US, many of whom can’t afford insulin, much less Livongo. Livongo certainly did a good job in convincing employers to pay for its service and also convincing Teladoc Health to buy it for $18.5 billion so it could offer something that is synergistically sexier than selling plain old telehealth visits, but I’m not smart enough to determine whether it measurably improves the health of its users or the medical costs they incur, much less that it has revolutionized American healthcare as a whole.

The authors believe in the concept of “health assurance,” where people keep themselves healthy by being constantly wired up to sensors that pump out a continuous stream of real-time data that is dutifully and invisibly overseen by artificial intelligence. This, they predict, will “help us mostly forget about doctors, pills, hospitals, and insurance companies.” It will be consumer centric, data driven, cloud based, and built using open technology standard and empathetic user design (Taneja’s technologist identity comes out pretty strong here in focusing on the geek factor).

The key to reinventing healthcare, the authors insist, is bringing in tech startups, rewarding them with billion-dollar valuations, and then standing back while they disrupt everything in sight. I’m not opposed to that idea, but the track record of eager, naive outsiders hasn’t been pretty. Nobody knew healthcare could be so complicated.

Healthcare wasn’t built to be consumer friendly, the authors argue convincingly. It was built on the concept of mass production to address the scarcity of doctors, hospital beds, medical devices, and drugs that doesn’t really exist today. Baby boomer demographic changes, along with employer-provided health insurance, marginalized patients as a mostly powerless widget that was milked profitably by various healthcare fiefdoms who always blame everybody else for high cost and low quality. All of this is true.

Klasko explains that Jefferson Health paradoxically had to scale up (via acquiring competitors and starting new businesses) to allow it to eventually unscale sometime down the road. He claims Jefferson will then emerge butterfly-like as a wellness brand with no physical address, freed of the incentive to crank out profitable procedure volumes. Sounds great, but I haven’t seen many examples where the health system that was scaling up voluntarily took a less-profitable but more consumer-centric path down the other side. Expecting people or companies to do something that doesn’t pay them the most is usually cause for disappointment.

I can’t decide whether Klasko’s business dealings make him a better or worse advocate for a new business model for non-profit healthcare systems, but “non-profit” is more about accounting than mission for many health systems these days anyway. Still, both authors stand to make even larger fortunes if their tech company healthcare bets pay off, so maybe a bit of skepticism is warranted when their tech hammer is on the lookout for nails to pound.

Back to the healthcare assurance concept. You don’t need to have physicals or see your doctor until AI – which will be provided by a health system as part of a pre-primary care subscription — flags your data as unusual. Then you will complete a chatbot questionnaire and then see a doctor – probably virtually – and if something seems amiss, booking your appointment online, being updated with SMS messaging that eliminates the need for a waiting room, and spending time actually talking to the doctor since they don’t waste visit time taking measurements that the sensors have already sent them. That makes good sense, depending on the accuracy and completeness of the available sensor inventory (which is minimal at present).

I’m not sure I agree with the authors that the next logical step is that pricing will become transparent and insurance will return to its original form as being a hedge against risk, not a way to pay for routine services that are otherwise unaffordable. You would need more than 134 pages to explain how that could happen. UnitedHealth Group has more money that even Hemant Taneja and seems disinclined to make less of it.

Taneja is an investor in Ro and he loves their model of cranking out telehealth visits to sell ED and insomnia prescriptions online. Whether that is a consumer-friendly innovation or a lapse of professional responsibility by its doctors is beyond the scope of this discussion. The psychology of men who are embarrassed to tell their in-person doctor about their receding hairlines is probably different from someone who is facing a life-threatening condition that will never go away.

The authors also like the tech-heavy healthcare membership system of Forward, which uses biometrics, blood tests, genetic analysis as a baseline to then offer monitoring and unlimited visits for $149 per month, with no insurance accepted. They think that services like this could be targeted to subgroups such as those over 70, pregnant women, or young athletes as a form of unscaling. This seems perfectly logical and immediately achievable to me, although I’m sensitive to the fact that while many of us can afford these cash-only services, most Americans can’t and will still be staring at “The View” while being coughed on by the fellow occupants of whatever waiting rooms are left.

Health assurance would require fewer people in administration, but more in customer service, marketing, and technology. High-income proceduralists (dermatology, radiology, orthopedics) would become less valuable and thus paid less than family doctors and pediatricians. Medical schools would need to place less value on memorization skills and instead look for incoming students who exhibit empathy, creativity, and communication since they will need to treat the entire patient (sleep, diet, exercise, etc.) Hospitals will become the post office in the age of email, and insurers will be hurt most as the need for their middleman services is greatly reduced. If you want to disrupt those huge, highly profitable entities that will spend whatever it takes to keep the goose laying golden eggs, you’re going to need a bigger boat.

The authors posit that we’re at a tipping point (aren’t we always, according to authors?) because of the weaknesses COVID has exposed and the high premiums and deductibles of health insurance, which will turn most people cash payers against their will and encourage them to seek good experiences at good value.

From the regulatory point of view, the book calls for a single national medical license (agreed) and to redefine FDA’s role in safety and efficacy in regulating only the former and letting the market judge the latter (they say Livongo was held back by FDA’s efficacy requirements, wah).

As a curmudgeonly skeptic (or experienced realist, perhaps) I agree with some points of the book, but I would not predict a mass overhaul of a system that regularly lines lawmaker pockets to retain the status quo, especially if companies expect cash-strapped Americans to cough their own money to pay for gadgetry and services that mostly interest the worried well who are striving for data-powered immortality. In that regard, I would say this book’s emphasis on highly valued startups and profitable disruption makes it more of a business read than a balanced review of meeting society’s healthcare needs equitably and funding it as a public good. As a non-profit hospital lifer, I’m already uncomfortable with the idea of having a hospice owned by a private equity firm.

I’m also not convinced that today’s sensors and the invasive nature of wearing them can provide enough data to function like a car’s gauges and warning lights for a remote observer. The connection between DNA and health, or even medical treatments, has barely been touched, and has little impact on medical decisions. We haven’t asked doctors what information they would need to replace the traditional exam, assessed whether today’s sensors can provide that data, or proven that streams of patient data makes them healthier or avoids cost (and in fact, whether we should also ask them how they feel or have concerns that sensors can’t measure). Do you want your doctor to be a trusted life ally or a savvy mechanic, and what are you willing and able to pay for your vision of healthcare?

My review of “The Patient Will See You Now,” I realize, is similar to this one, although that review was funnier and snarkier. That book came out nearly six years ago – are we disrupted yet?

Book Review: It Shouldn’t Be This Hard to Serve Your Country

David Shulkin, MD, the ninth Secretary of Veterans Affairs, is the latest in the seemingly endless cavalcade of fired President Trump appointees whose tell-all books profitably pay penance for their participation in a divisive administration. The cash registers of websites, TV networks, newspapers, and booksellers everywhere can’t stop ringing from peddling controversy from both sides of the fence.  

I wasn’t going to read “It Shouldn’t Be This Hard to Serve Your Country,” to be honest. I’m wary of whitewashed stories told by humiliated former government officials and politicians who decide to bare their souls in a safe environment where only their own uncontested voice is heard. My experience with that kind of book is that the authors always claim to be misunderstood, selfless saints who just want to set the record straight in clearing their good name (as well as the path to future beneficial endeavors). An HIStalk reader sent me an Amazon gift card to cover the book’s cost and said he wanted to hear my take on it, so that guilted me into buying the Kindle version.

It’s a great title, by the way, referring to both veterans and to the author himself.

Shulkin is an internist who didn’t serve in the military, although much of his family did. He served in several medical school roles, was chief medical officer in an academic medical center, was president and CEO of Mount Sinai’s Beth Israel Medical Center in New York City for four years, and was then president of Morristown Medical Center (NJ) for five years before being tapped by President Obama to be the VA’s under secretary for health in 2015.

I generally believe Shulkin’s contention that he was a selfless advocate for the health of veterans, improving the VA system, and trying to protect the VA from the meddling of limelight-seeking members of Congress. Surely he could have found jobs that weren’t so soul-sucking if his goal was self-aggrandizement or lining his pockets.

Spoiler: Shulkin was fired because of the meddling of political appointees who want to see the VA system dismantled and by a president whose vanity requires him to distance himself from underlings who get bad press that interrupts the mandatory adulation.

The snips Shulkin mentions about President Trump suggest that the President has good intentions, values loyalty above all else, rules by executive order while refusing to talk to the other side, doesn’t have the attention span to analyze issues and relies on subordinates to form opinions for him, and is in far over his head in turning the government over to clueless power-grabbers who wage full-time war against career government workers who actually understand the issues. The Trump administration is dogged by infighting, revolving door cabinet members, and leaks of information that, whether factual or not, are often intended to discredit his legitimacy as President.

It’s also clear that the so-called Mar-a-Lago Three – Marvel Comics chairman Ike Perlmutter, physician Bruce Moskowitz, and lawyer Marc Sherman – had the President’s ear, represented themselves as his personal emissaries, and demanded full participation in all aspects of the VA’s operation. Perlmutter reminded Shulkin constantly that he was meeting with President Trump all the time and summoned Shulkin and others to the President’s Florida resort to tell them what to do, not just with regard to the VA’s EHR project, but in all aspects of the VA’s operation. Shulkin insisted that the three “counsel” him individually rather than as a group since the latter could have been interpreted as an illegally operating “federal advisory committee” that requires public oversight. Shulkin says he wasted a lot of his day dealing with them, with Perlmutter calling him several times a day with one naive idea after another.

Shulkin notes that, like President Trump, none of the three had ever even visited a VA facility and declined opportunities to do so. Only Perlmutter is a military veteran and that was in Israel, not the US.

Shulkin spends a lot of pages defending the travel expense controversy that helped get him fired, providing details that he says prove just how ridiculous the claims were that he was junketing around with his wife on the taxpayer’s dime (which was certainly true of other Cabinet members, but not Shulkin, according to Shulkin). I actually believe him here as well, and while I’m skeptical of the whole “fake news” excuse for unflattering exposes, it seems that the Trump-created 24×7 frantic news cycle where tweets earn headlines has roped even credible media outlets into running poorly vetted stories hoping to wrest eyeballs from equally lurid sites. Once Shulkin got on the wrong side of the headlines, the former Obama-Trump golden boy had to be sacrificed to protect the President’s thin skin, not to mention that cabinet member travel excesses stories were all the rage for newspapers back then thanks to former HHS Secretary and jet-chartering Tom Price.

Shulkin describes some of the improvements he made to the VA, often decisively and with little support – fixing the wait time problems, publishing operational statistics, trying to modernize its HR policies of basically firing nobody regardless of their level of incompetence, and addressing veteran suicide. He observed that the competitive innovation model rolled out by former Undersecretary for Health Ken Kizer, MD, MPH – especially a star ranking system — encouraged VA facilities to hoard best practices to keep other facilities from stealing their stars. Shulkin rolled out five priorities for improvement – care access, employee engagement, care coordination, veteran trust, and best practices sharing.

President Trump’s election brought in a flood of political appointees who knew nothing about their assigned areas of responsibility. The “politicals” ran off career professionals, leaked false information to the press, and stabbed each other in the back. Shulkin notes that not only did the President have zero government background, most of the cabinet secretaries he chose didn’t either, and some of them had spent their careers opposing the agencies they were empowered to oversee. Shulkin said he was told to find jobs for 30 people, which he thought was reasonable given the size of the VA. The person the White House had assigned to dole out the plum jobs was a 24-year-old former Trump campaign intern whose father was a “Fox and Friends” host. Shulkin was told that he had to accept any appointees the White House sent over and was given a direct order not to fire them. 

Shulkin had an obvious problem with some of the appointees who claimed to represent the White House or who wanted to oversee other appointees. One of them followed Shulkin’s staff meetings with his own sessions that included only the politicals, who would then be told to do something else in dividing the department between the “secretary’s team” and the “political team.” He was also getting beaten up by members of Congress who told him privately that he was doing a great job, but warned him that they would be grandstanding with bitterly negative criticism once the cameras started rolling. He assigned one of the politicals – who he names specifically – to serve on a White House committee who then leaked false information, threatened outside groups who didn’t support specific bills, and ran his own agenda in claiming to represent the President.

He also struggled with high-level VA positions that remained unfilled because the White House didn’t like some of his choices, including “a former CEO from one of the country’s largest public health systems” who was rejected because he had once served on a healthcare advisory committee for Hillary Clinton.

It was surprising to me how much influence that veterans service organizations such as American Legion and Disabled American Veterans wield. One of those that had been basically ignored as lobbying group a by the Obama administration – the Koch Brothers-funded Concerned Veterans of America – was welcomed by the White House despite its agenda of privatizing the VA. That issue kept Shulkin in trouble – nobody wants to admit to voting veterans that they want to shut down their healthcare system, so everybody accuses each other of having a hidden privatization agenda.

Shulkin says he made the right choice to replace the VA’s skunk works-developed VistA software. It made the VA paperless and was widely known because two-thirds of doctors trained in the US rotate through the VA, but Shulkin says the VA had made a mistake in allowing each of its 130 medical centers to create their own customized instance of it. He also noted the lack of interoperability with the Department of Defense’s systems, the high cost of maintenance, and the estimated $19 billion the VA would have spent to modernize VistA.

He admits, however, that he was naive in not realizing how his job would be threatened by his decision to bypass traditional contracting and to simply choose Cerner outright because “I was convinced that immediate action was necessary” because of a never-ending lack of DoD interoperability.

The VA engaged with Cerner under a little-used government contracting option called “determination of findings,” which allows a detailed vendor discussion without a formal commitment. He denies New York Times reports that cited a White House leak saying that Jared Kushner was advocating for Cerner. He says he was instead being pushed by former DoD employee John Windom and members of Congress to get moving with Cerner so the VA could align with DoD’s implementation schedule.

Shulkin says his main requirement was interoperability and Cerner wasn’t convincing in that area, offering only minor sharing of administrative data and the dataset used for government reporting. Or as he put it, “The Cerner team was in full sales mode.” He told Cerner’s then-President Zane Burke that he was ending negotiations until Cerner stepped up to the interoperability plate.

Shulkin worked with outside groups and with academic medical center CIOs to make sure the Cerner contract was solid. However, he was getting pushback from the political appointees, some of whom started showing up uninvited to EHR meetings and reporting back to the Mar-a-Lago Three with their concerns about the contract. One of the politicals was telling everyone that Shulkin was rushing to sign a flawed Cerner contract, urging that he be fired before he did so. Which, as it turns out, was exactly what happened.

In the last conversation Shulkin had with President Trump, the President told him, “You’re killing me with all the bad press coming out of the VA” and asked about the Cerner contract, “Can’t you find a cheaper alternative?” Later that afternoon, Shulkin – who had learned he was being hired as VA secretary only when he saw it on TV news — was fired by tweet. Access to government email and phones had already been turned off. He wasn’t allowed to return to the VA to pick up his personal items or to say goodbye to his team. He then was warned by a colleague that the politicals were making up a story that he had walked off with sensitive government information after being fired, so he returned all his electronic devices at 10 at night.

Shulkin notes that seven weeks after he was fired, “The political appointees apparently determined what I had known all along: the options for IT modernization were limited and the Cerner contract was the best option for the VA and for taxpayers. In the end, the right decision was made, and the VA was on its way to gaining a cutting-edge system to propel it into the future.” He also notes that the President took credit for the VA’s accomplishments at a White House event to which no Democrats or VA professionals had been invited. Shulkin was surprised that the press didn’t pick up on a published email in which one of the politicals laid out the firing of Shulkin, his deputy secretary, and his chief of staff, which was to be coordinated by Citizen Perlmutter to happen only after the President was able to take personal credit for completing several VA initiatives.

Shulkin had a lot of problems with the VA’s OIG, a 1,000-employee, much-feared organization that he accuses  of being “secret police” that aren’t always fair or thorough in their investigations.

He says he worries most about the clueless politicals who have run off qualified employees who could have overseen the Cerner project, explaining, “Getting a contract signed is one thing, but carrying out the real work involved is quite another. My years of experience with EHR implementations taught me that doing this well will require participants with real experience and knowledge that is unfortunately in short supply within the VA’s political leadership today.”

I found this book to be interesting, but depressing. Government is even more dysfunctional than we probably all suspect, and the motives of those involved can often be traced back to pettiness and personal gain (and the same can be said of the press, most likely). I don’t have a clue about how to fix that, but I do believe that David Shulkin was doing good for veterans until that opportunity was taken away by partisan politicians who accept incompetence as long as it is cloaked in political loyalty, just like the politicians who came before them and those who will follow.

As a cheap seats observer, I didn’t find Shulkin’s explanation of why he needed to rush into a no-bid Cerner contract to be convincing, but he’s right that he didn’t have any great alternatives. The Coast Guard’s struggle with Epic probably killed its chances, self-development was a non-starter, and not choosing Cerner when the DoD had already done would have been politically risky. He gives himself a convenient excuse should the project fail, warning in advance that incompetent VA politicals aren’t capable of implementing Cerner. 

The book was more interesting than I expected. Glimpses into how government works were fascinating, although not always encouraging. Maybe Shulkin is the self-sacrificing saint he describes in his book or maybe he isn’t, but regardless, I’m left with a more positive impression of him than before (and I was fairly positive about him before). He was unanimously confirmed twice for high-level VA jobs under wildly different administrations, developed consensus that crossed party lines, and as far as I can tell made veteran wellbeing his agency’s top priority. I think veterans were better off when he was in charge.

Book Review: Lethal Injection

A reader correctly predicted that I would like “Lethal Injection,” which he accurately described as an “informatics murder mystery” that came out in June 2019. That reader is a former colleague of the author and recognized in his book subtle references to the hospital and anesthesiology department in which they worked.

Author Perry Miller, MD, PhD is an anesthesia professor emeritus at Yale School of Medicine and founder and previous director of the Yale Center for Medical Informatics and its biomedical informatics research training program. He earned his medical degree at University of Miami , an MS at Cal Berkeley in electrical engineering and computer science, and a PhD in computer science from MIT.

It is remarkable that the book is Miller’s first foray into writing anything except research papers. The book is fast paced, flows perfectly, and contains few of the common flaws that often cause me to put a book down for good when the literary awkwardness distracts me from the story.

The book leads off with a flurry of action in which the CEO of academic health system Boston Central Hospital dies while undergoing cardiac surgery at Laurel Hill Community Hospital, which Boston Central is taking over.The anesthesiologist in the CEO’s surgery case is the wife of the protagonist, ED doc Gideon Lowell (the author has a lot of fun with his first name, which isn’t entirely random as he explains in the appendix). She is immediately targeted as a suspect when investigators find that a syringe that was labeled as vecuronium actually contained something else that killed the patient when she injected it. Lowell launches his own investigation, partly because of his patient safety background, but mostly because he wants to prove that his wife wasn’t responsible.

A good page-turning crime mystery starts by introducing several suspects with various motives, then keeps you guessing at who did it until the climactic end. Miller does a great job in weaving a tale of who might have wanted to see the CEO dead. Laurel Hill employees resent having Boston Central know-it-alls running around in preparation for the takeover. Partners in Laurel Hill’s contracted anesthesiology company stand to lose hundreds of thousands of dollars per year via lower academic salaries. Also present are the usual hospital soap opera issues of romantic entanglement, bullying, and doctor back-biting, not to mention hospital greed in performing questionable but lucrative surgeries. In other words, it is realistic.

Miller adds some fun IT flourishes that are vital to the story – spoofed hospital emails, intentional disclosure of EHR patient information, medical records tampering, and the fact that Laurel Hill was ripe for takeover because a botched billing system implementation caused revenue problems (that part of the book isn’t described believably, but it’s not crucial to the story). Then we meet an old friend of Lowell who is a cybersecurity expert who offers to help, a somewhat clueless risk management lawyer, a medical group programmer, a quality assurance manager, anesthesiologists whose character flaws range from laziness to hostility, and an investigative reporter who starts probing into Laurel Hill’s clinical problems.

This book flows really well, contains fun hospital insider knowledge, and probably scares laypeople who will wonder whether hospitals really are greedy and whether doctors could be so vain, insecure, and hostile to employees and to each other. Reading it is a pleasure, not a chore.

A few changes could have made the book better:

• It’s a relatively short read at 232 pages. That isn’t surprising since publishers aren’t going to allow first-time authors to ramble on for 500 pages like Stephen King since they can’t command his high cover price yet. Keeping it short when the book contains mostly dialog – which takes up more page space —  limits what we can learn about characters that can seem one-dimensional at times, and deprive of us what I’m certain would have been some funny details given a few that were included. But if someone wants to make a “Lethal Injection” movie, which isn’t a bad idea, the book already reads like a screenplay that mostly contains characters talking over a linear timeline.
• An editor should have caught that it’s vocal “cords,” not “chords,” and a data “breach,” not “breech.” Overuse of the term “sub rosa,” meaning done in secret, was a bit grating. Those are the only examples of questionable editing that I saw, and I usually see a ton, even with the books of best-selling authors. 
• One set of characters was probed in depth, which was good for calling them out as possible perpetrators, but then their seemingly incriminating act was left dangling as the story raced to its conclusion without them.

“Lethal Injection” grabs the reader’s attention in the first couple of paragraphs and doesn’t let it go until the end, demanding furiously fast reading to see how the story unfolds instead of easy savoring of carefully crafted details and back-stories. I can’t imagine that it’s easy for any author to create such a book, much less a first-time author. It’s quick-hit entertainment that won’t leave you thinking about the characters afterward, quoting new facts you learned, or pondering its hidden meaning or the meaning of life.

Perry Miller is an excellent writer and I’m awaiting his next work.

The Kindle version of “Lethal Injection” was a steal at $0.99. It would be the perfect read for traveling health IT folks who need something engrossing to read on planes or in hotel rooms, knowing that they can pick up where they left off easily if interrupted.

Book Review: HIT or Miss

Reading the third edition of “HIT or Miss” is like trying to reconcile memories of someone’s previously vibrant life with their coldly objective obituary. It contains dozens of examples in which the exuberance, high-fiving (especially by the vendor’s salesperson), and lofty goals of improving patient care via IT somehow ended up as flaming wreckage whose major contribution is to serve as a cautionary tale for the rest of us.

You may well chuckle at the naiveté and hubris of each (unnamed) hospital’s executive and IT teams for making some really bad decisions, but deep down you know your own organization isn’t any better even though its gaffes aren’t included. Hindsight is 20-20.

You also might question why this sort of HIT autopsy holds value and I see your point. The organizations that have yet to make such plus-sized IT mistakes aren’t likely to read the book like the Bible and declare themselves reborn. Every IT project is different and maybe the lessons belatedly learned by other hospitals either aren’t relevant or must be relearned by others.

Still, it’s made clear that the enthusiasm to “do this project right” – implicitly outperforming lesser-skilled peers whose cloak of invincible destiny turned out to be full of holes – can be crushed by a single, cancerous-like cell that metastasizes. Its genesis isn’t notable – a low-level decision made in an overcrowded conference room that smells of stale bagels, Type A executives who insist pushing on to recoup their eye-popping software investment by bringing it live at all costs so they can be photographed at the ribbon cutting, and leaders who allow the scope to creep to appease an influential department head or foot-stomping doctor. Any one of thousands of ever-moving parts can cause the whole machine to blow up once the big switch is pulled.

The biggest takeaway here – not surprising that AMIA was involved – is that hospitals should  listen to their CMIO, clinical IT folks, and patient care front-liners. I had “your vendor” on the list, but I’ll asterisk that – some vendors are determined to make their clients successful and possess the competence to do so, while others peak at getting the contract signed and may do more harm than good.

These examples, provided by and recounted by a stunning roster of industry luminaries and edited by Jonathan Leviss, MD, are representative:

• A hospital whose voluntary CPOE usage dropped from 60% during the pilot to 15% immediately afterward (and zero shortly after that) as the project team called it mission accomplished, took vacations, and shifted their attention to other priorities.
• Another (Hospital B) whose patient satisfaction dropped from the 70th percentile to the 5th as its health system parent tried to copy the successful ED implementation in its larger, newer, and more sophisticated Hospital B without involving Hospital B’s clinicians in the build and testing.
• A hospital that rolled out a legacy data viewer as it implemented a new EHR, but continued to send the viewer new data until its forced retirement three years later, at which time it was discovered that 40% of clinical users were still using it (instead of the new EHR) to look up lab results and clinical notes, after which staff complaints (mostly from surgeons) forced the hospital to reconfigure the new EHR’s screens to look like those of the legacy system.
• A decision to issue all drug interaction alerts to clinicians, with the intrusive pop-ups being overridden 95% of the time for drug-drug interactions and 87% of allergy warnings, wasting an estimated 12-18% of clinician time.
• A hospital that decided to implement a new medication reconciliation system and process across four hospitals without performing a pilot project, which had to be shut down two weeks later when the executive-estimated few seconds of pharmacist time required for each patient turned out to be 20-30 minutes.
• A barcode medication program that failed because IT and facilities engineering weren’t involved in choosing laptops, batteries, and carts and nobody had time to work the trouble tickets.
• A community hospital that slowly migrated from one ICU vital signs capture system to another as rooms were renovated, but each system interpreted and displayed information differently to the clinicians making decisions.
• The discovery that a newly implemented fetal monitoring system displayed information for the wrong patient because of a cable plug-in mix-up.

Each of the 48 case studies is interesting, even those that may now be mostly a historical curiosity now that integrated, single-vendor EHRs have eliminated some of the risk points of integration, upgrade timing, and multiple device use.

“HIT or Miss” was a lot more interesting and detailed than I expected. It recounts millions of dollars worth of bad decisions, unfortunate events, and vendor shortcomings that we wouldn’t have heard about otherwise. I’d like to think that no patients were harmed in the making of this book, but I’m certain that isn’t the case. And while IT sophistication grows linearly as health systems get bigger, complexity and thus the potential damage grow exponentially.

This is not my usual book review since it would be missing the point to focus on writing style or entertainment value (although both are excellent). Its value is to show what can go wrong when a project transitions from executive self-congratulation for choosing a bold IT path forward to their underlings trying to make it all work in an ever-changing environment full of self-interest landmines, competing pressures from all sides, and products whose shortcomings aren’t discovered until  analyst sleeves are rolled up.

Perhaps the takeaway is that it’s really tough to implement process change and ever-changing technology in meeting timeline and budget expectations while preserving the originally envisioned benefit to patients without harming them in the process. For that reason, IT leaders might want to stock up on copies to hand out to overconfident C-suiters and board members who feel that their executive insight justifies overriding the advice of those pessimistic, business-naive clinicians who won’t quite yapping about their “concerns” or the potential harm to patients that they can’t say with certainty will actually happen in standing in the way of lighting the candle. Worst is that they are right – you won’t know what you don’t know until you bring the system live and there’s never a perfect time to do that, so at some point you might was well just turn it on and be ready to fix what’s broken.

Thanks to attorney Henry W. “Hank” Jones, III, JD for sending me a copy of the book (he wrote Chapter 48 – “Explore HIT Contract Cadavers to Avoid HIT Managerial Malpractice.”) It’s $60 on Amazon.

Book Review: The 10 Principles of a Love-Based Culture

Industry long-timers Ivo Nelson and Dana Sellers hit a couple of massive health IT consulting company home runs. They created Healthlink and Encore Health Resources and then sold them to large companies in 2005 and 2014, respectively. Those brands have disappeared, existing only as a fond memory for the former employees who ended up working for companies (IBM an Quintiles as the original acquirers) whose corporate culture was considerably different than that of the “love-based” companies that are described in this book.

The Title

The title of this book will likely limit sales volume. It sounds pretty hokey, like those self-help books written by self-proclaimed gurus that can’t deliver on the title’s promise. I cringed every time I read “love” in the book because it doesn’t seem to fit what the book is actually saying. My observations:

• The principles described have little to do with the squishy, feel-good concept of “love” within the corporate walls. Offering a customer a refund for poorly done work isn’t really love. The authors never claim to love all of their former employees or to have been loved by them. “Compassion” or “trust” are more accurate. I don’t remember any part of the book stating that anyone loved someone else other than family, although it contains examples of compassionate executive behavior.
• I don’t think “love” and “business” share much common ground. I don’t expect to love my employer and I don’t expect them to love me. Our relationship is mutually beneficial, but I expect to get most of my emotional rewards elsewhere. My employers have admittedly operated far from the love-based culture described here and that makes me wonder whether any companies really follow the 10 principles.
• Most corporate executives would not read a book with this title because they would correctly realize that they can’t just flip a switch to turn on love that they don’t really feel. They probably also aren’t looking to retool their management style by reading business self-help books. They  aren’t likely to make a gazillion dollars just by using the book’s ideas to create the next Healthlink.

The book’s subtitle is better even though it’s no more actionable: “How authentic business leaders trust their employees to do the right thing.”

The Actual Book

A lot of health IT books are poorly produced. Authors use a vanity publisher or ghost writer, don’t hire a skilled editor, skip performing research in favor of just spitting out folksy non-wisdom, or scrimp on the physical production of the book. The result is embarrassing, or at least should be — a lazy way to check a resume box in hopes of finding a better job or adding “author” to join the questionable “speaker” or “thought leader” on business cards.  

This isn’t one of those books. It is well written, edited well, and designed and printed professionally. It’s a real book, in other words. It isn’t super long at just over 200 pages in the hardcover edition, but it has good, easy-to read stories and examples.  

The Intended Audience

I’m struggling to understand the intended and desired outcomes of this book. Ivo and Dana created two consulting companies that grew like crazy. Starting from scratch allowed them to hand-pick their co-workers and to intentionally create and maintain the culture they wanted.

Most of the book’s ideas don’t seem to fit well with larger organizations: companies whose culture isn’t easily changed (which I suspect is nearly all of them); those organizations that sell products rather than services or to consumers instead of to other businesses; and for employees who aren’t in a position to change culture.

I’m picturing the average reader wishing that they could have worked for Healthlink before IBM screwed it up or that they could quit their jobs and find the rare employer that embraces even some of the 10 principles. The biggest takeaway for many readers might be that their employer is not a great place to work.

The 10 Principles

1. Make every customer happy enough that they would offer a positive reference if asked.
2. Put employee needs first.
3. Make sure executives live the company’s core values.
4. Define a purpose that goes beyond profits.
5. Focus on long-term growth.
6. Reward employees based on the overall value they provide to the company, even though such value is subjective.
7. Create positive energy from company successes.
8. Develop company policies and processes based on trust.
9. Empower frontline employees to do what’s right for the customer.
10. Hire executives who demonstrate that they care.

The Credibility Factor

Healthlink is the example given through the book. Ivo sold that off to IBM in 2005, so a critic might question whether what he and Dana learned there 15 and more years ago is applicable and relevant now. They did it again with the more recently formed Encore, however, so that’s a plus even though it was still in the go-go industry years that have cooled off considerably since.

The book mentions that Healthlink spawned at least 15 CEOs who carried on with a love-based culture. Hearing their stories would have been enlightening. What kind of companies are involved? What cultures existed, if any? Which Healthlink principles did they find useful and which did they skip? Were any of them involved with larger companies and thus on the hook for delivering quarterly results and changing a culture at large scale? Did they apply what they had learned at Healthlink to a turnaround situation? What kind of personalities did they have and how did that affect their leadership style?

Ivo and Dana say in the book that Healthlink’s culture wasn’t necessarily designed up front – it happened on the fly as a by-product of the team they assembled. I’m not so sure that a CEO would read this book and suddenly vow to make personal and corporate changes that would make their company look like Healthlink, especially if they didn’t create the company in the first place. Nor am I sure that I would expect great things from a CEO who had to learn concepts such as empathy and employee satisfaction from reading this book.

In short, would any of theses ideas actually work if Ivo and Dana weren’t involved? I’m not so sure. They give themselves too little credit in the book. Consulting is a people business, Ivo and Dana have a long industry track record and a Rolodex full of contacts to earn services business, and they are obviously outstanding entrepreneurs.

Fear-Based Culture

Ivo says that the opposite of a love-based culture is a fear-based culture. That’s the type of employer that nearly all of us know. The book provides a checklist to determine whether your workplace is fear-based, which I can assure you is both enlightening and depressing. Your boss thinks they are smarter than everyone else, people are promoted and paid illogically, everybody is afraid to speak up, and corporate backstabbers play a zero-sum game in trying to diminish everybody else to improve their own standing.

The challenge is, what do you do having read the book? Send a copy to the CEO and hope for the best? Demand that the CEO change the culture? Find a new job working for a company whose culture is love-based? You’ve read this book and are thus enlightened — then what? I worry that readers will be able to recognize a fear-based culture while simultaneously realizing that it is unlikely to change.

What Would Have Made This Book Better?

• Provide examples that go beyond Healthlink to prove generalizable applicability.
• Identify a large company that follows most of the 10 principles and interview the CEO about that company’s culture.
• Interview the former Healthlink employees who are now CEOs to see how much of the company’s culture they carried over, especially for companies that aren’t in the consulting business.
• Describe how a company could start the slow turn toward the culture described, or how to assess where they stand and what they might expect along the way.
• Describe how a manager might use the principles even though they don’t have the power to change HR or financial processes.
• Expand the chapter on governance into its own book to help startup or small-company CEOs understand how to optimally work with their boards and the executive team. This is where I would want to pick Ivo’s brain, along with having him explain how and when to sell a company.

My Ivo Interview

I interviewed Ivo as he and Dana were getting Encore Health Resources off the ground. It’s one of my favorite interviews because Ivo is honest, reflective, and likeable (we would all love to have Ivo or Dana as our mentors, no doubt). Just about everything he said was worth considering and remembering, but this stuck with me most:

I’m perfectly happy with having an expectation that says we’re going to hire really good people and we’re going to do great work for our clients and the growth is going to be whatever the market has to give us. If this is a 30, 40, or 50-consultant company in five years and we’ve got 100% referenceability and we’re considered the place to work in the industry and every time I talk to a consultant they tell me how much they love working for Encore, I consider that to be a grand slam home run.

If it’s 500 people and we’re not providing great services to clients and we’ve got people quitting because they hate working for Encore but we’re making a ton of money, I’ll consider the company a huge failure. Dana and I, we really just want to build a really good company that clients can be proud that we’re working for them and our consultants can be proud to say that they work for Encore …

Having been acquired and watched other similar companies get acquired, too, I think it’s extremely difficult to take a people company like a consulting firm and have cultures meshed with a technology company that’s more asset-based …

This is nothing more than me doing what I love to do. If it leaves a legacy, I think that’s OK, but I’m not sure what you really get out of that. When I’m hopefully up in my 80s or 90s and I pass away, the people that are going to come to my funeral are going to be my family. It’s not going to be clients. It’s going to be people that are close to me personally in my personal life, my kids and my sisters and a handful of friends probably that I have. That’s a legacy.

I asked Ivo several questions about company culture, starting a company, and consulting vs. other businesses. It’s worth a read to get to know him better. His philosophy is simple, although I think his ability to strategize, execute, and sell is always understated and he is disarmingly unaffected in person.

My Final Points

• I enjoyed the book even if I can’t quite figure out how most readers who aren’t CEOs (me included) can actually use its concepts.
• I enjoyed every story from Ivo and Dana and I appreciate their use of them to illustrate concepts.
• This is a great book if you worked or Healthlink or admire its history, maybe less relevant or credible if not. Healthlink ceased to exist half a generation ago and people outside of healthcare IT have likely never heard of it.
• The book’s jacket makes the simplistic promise that companies that follow the 10 principles (the “no-brainer steps”) will have happy customers, energized employees, and high revenue growth. That’s a stretch.

I would have enjoyed reading a company history of Healthlink or autobiographies of Ivo and Dana and this book contains some of those elements. Still, I found myself wishing for a broader range of stories that weren’t necessarily chosen to back the questionable argument that the 10 specific principles can be easily implemented to guarantee business success. I don’t think it’s nearly that straightforward.

You now know the 10 principles. You know that the book contains a lot of Healthlink anecdotes. You understand that Ivo and Dana have created some great businesses in somewhat unconventional ways. You therefore have enough information to decide whether you are likely to get $15 worth of useful ideas or entertainment from “The 10 Principles of a Love-Based Culture.” My guess is that you probably will, even if you aren’t convinced that a company can just flip the switch on a nice, round number of love-based principles and find Healthlink-like success. It’s a fun read that contains enough information to be useful to nearly everyone in business.

Ivo and Dana need to write more books. Cover topics that distill a lot of practical knowledge that CEOs need. Write anonymized stories about mentoring CEOs and observing their boards and executive teams in action. Find a large company with a fear-based culture, help the CEO turn it into a love-based culture, and describe the process and results. This book proves without a doubt that Ivo and Dana have a lot of good information and are highly capable of presenting it well.

Book Review: Deep Medicine

Eric Topol is one of the highest-value of the few people I follow on Twitter. He consumes information voraciously and summarizes it well without talking down to his audience. He loves technology, hates EHRs, and weighs in on the practice of medicine even though I suspect his practice isn’t very much like that of the typical doctor or even the typical cardiologist. He is quick to point out those seemingly great ideas that have had zero real-world validation in a healthcare setting. He also holds researchers accountable for proving improvement in outcomes – just making a lab value move in a seemingly good way doesn’t cut it with ET.

I have mixed feelings about this book. Topol provides an exhaustive (and sometimes exhausting) review of all the work that’s being done with artificial intelligence in healthcare. Trust me, it’s a lot. The downside is that this book was nearly obsolete the moment the first copies rolled of the presses, meaning I had better get return on investment for my $20.69 quickly.

“Deep Medicine” is a firehose of who’s doing what with AI. By nature, a lot of that work is early-stage, experimental, and unlikely to see front-line use for a long time. Most of all, we have no idea of how it will integrate with the US healthcare industry (and make no mistake, it’s an industry). We’re not really that much different than other industries no matter what we would like to believe. 

I found the book somewhat of a chore to read. It has some personal stories, a bit about the history of medicine, background about companies, and of course who’s working on healthcare AI. I didn’t find it conclusive, but then again it really can’t be so early on.

Will AI Really Make Healthcare Human Again?

The subtitle “How artificial intelligence can make healthcare human again” sounds good and probably draws readers who are less interested in the nuts and bolts of AI. But to me, the book fails to deliver a convincing reason that Topol thinks that will actually happen.

I didn’t gain any confidence that healthcare will be even a little bit more human just because AI might save clinician time. If “making healthcare human again” was a business priority, we would have done it already, AI or not.

Topol expresses hope that doctors who are “given the gift of time” will be allowed to use that time to practice medicine the way they really want, to get personal with patients and to focus on their stories. That ignores the fact that most doctors these days are assembly line workers paid to treat ‘em and street ‘em in whatever way maximizes billing. It’s questionable whether the gift of time also offers the gift of higher income, and safe bets are always to assume that people do whatever it is that rewards them financially.

The other issue is that given Topol’s rigor in demanding that outcomes be proven, we don’t know that spending more time with patients in “deep medicine” actually improves outcomes. We don’t even know that patients want such attention. They seem happy with the urgent care model of dropping by with a problem and leaving with a prescription. AI could amplify the impersonal nature of those interactions, pushing patients to be triaged by chatbots or kiosk-based questionnaires. We don’t know whether that would make overall outcomes and quality of life issues better or worse.

I don’t recall any industry where the goal of automating the factories was to make workers happier or more self-actualized. Mostly it’s a reason to hire fewer of them or to restructure their work into something else that’s profitable. Assuming that healthcare is different is dangerously naive.

AI Hasn’t Been Tested on Humans

This is the most important reminder of the book. The AI work being done is interesting, but unproven. What works in a lab doesn’t necessarily work in an exam room. What works in analyzing heaps of data doesn’t necessary translate well to the frailties and idiosyncrasies of humans in their time of medical need.

It’s an easy leap to become overly exuberant when reading articles claiming that AI reads images better than radiologists, that somebody’s AI system passed a medical board exam, or that IBM Watson Health is smarter than an individual clinician. None of this has been studied and proven effective in the real world. Maybe it could improve outcomes or reduce cost,  but that’s just conjecture. A lot of those systems were rigged to do one thing, like Watson winning at “Jeopardy” only because it memorized Wikpedia, which is were the show’s staffers get most of the questions.

AI Is Good at Recognizing Patterns

Topol says properly trained AI can recognize patterns better than humans. Medical work that involves pattern recognition – diagnostic radiology and some aspects of dermatology and pathology – could perhaps be performed better by machines, leaving those doctors with time to perform other value-added services (if they can find them and if someone is willing to pay for them).

How Doctors Think

Topol has interesting thoughts on the Choosing Wisely initiative to get doctors to make better-informed decisions. He says it was a noble effort to get medical societies to define low-value tests and procedures, yet they are being ordered just as often even now. He gives these reasons:

• Doctors overestimate the benefit of what they do
• No mechanism exists to educate them
• Compliance can’t be measured
• No reward is offered for complying
• Doctors think it’s OK to perform questionably useful surgeries as long as they aren’t likely to be harmful

The book says that doctors are burned out by EHRs that contain inaccurate information and don’t share information. He gives those doctors a pass in simply blaming EHR vendors rather than those who select, implement, and use EHRs, often with the specific goal of not sharing information and not being willing to correct mistakes, especially those the patient could easily identify.

I’ll be honest in saying that I don’t trust the EHR commentary offered by authors like Topol and Bob Wachter, MD. They are often impatient in demanding an easy answer, like making EHRs as easy to use as Facebook, ignoring the fact that EHRs are designed to meet the requirements of our screwed-up health system.

I do like this idea from Topol – get the patient’s consent to make an audio recording of their visit, have it transcribed, and then turn that into an office note that doctor and patient review together. Key point – auto-delete the recording in 24 hours to minimize malpractice concerns.

Topol says doctors diagnose by reacting to a few patient descriptions and use internalized rules and experience to arrive at a conclusion. Their diagnostic accuracy rate is nearly perfect if they figure it out within five minutes, but it drops to 25 percent if they have to think longer. Topol also makes this point, which seems to conflict with the theme of the book – diagnostic accuracy doesn’t improve when doctors slow down and think more deeply. Clinicians who were “completely certain” about their diagnosis were wrong 40 percent of the time, based on an autopsy’s cause of death.

The #1 reason a diagnosis results in a malpractice lawsuit is that the doctor didn’t consider the diagnosis that was eventually found to be correct. Doctors say they could improve given better chart documentation.

The challenge for doctors is that they see a small number of patients, often of specific demographic composition. Personal experience can’t stack up to analyzing large patient data sets. This is an important point. Doctors don’t consistently incorporate evidence into their practice. They also can’t see their own deficiencies.

The assumption made here is that lack of accurate diagnosis is a big problem and AI can improve it. I’m not so sure from a public health perspective that it’s the most important problem to solve, although if AI can plow through the patient’s record, the literature, and data about similar patients to improve diagnostic accuracy under the doctor’s supervision, then that’s certainly a win.

Medicine versus Self-Driving Cars

I liked Topol’s comparison of self-driving cars to medicine. The steps are:

• Level 1 – driver assist, such as warnings to stay in the lane
• Level 2 – partial automation, such as automatic speed and steering control
• Level 3 – conditional automation, where the car drives itself but with human backup
• Level 4 – high automation, where human backup is not required, but it works only in limited circumstances
• Level 5 – full automation, where the car drives itself in all circumstances with no human involvement

Topol doesn’t expect medicine to get past Level 3. The clinician will always be personally involved to some degree.

Where AI Could Change Physician Roles

• To initially read radiology images and classify them as normal or abnormal, which given the large number of imaging studies, would save time and allow radiologists to change their role from being “the reader of scans.”
• To analyze surgical, cryopathology, and possibly dermatology images, where conformity across pathologists is lacking and error rates are high. The demand for “microscopists” should decrease.

In this regard, Topol suggests combining radiology and pathology into a single discipline of “information specialists” instead of “pattern recognizers.” That’s an interesting thought, although again tinkering with the lucrative incomes of doctors who are backed by politically astute societies usually doesn’t work.

The Economic Disparity Question

My overriding feeling in reading this book is that like much of healthcare, the benefits of AI won’t be spread evenly. You have the challenge of making sure that AI is trained given a broad set of demographics to avoid bias based on location, race, economic status, etc. but those people are already underrepresented in the healthcare system. AI can’t fix that.

AI could also be like self-monitoring tools such as the IPhone’s arrhythmia detection. Not everyone can afford an IPhone, is motivated to use it for self-monitoring, or has a clinician on standby to respond to the hypervigilant monitoring of the economically well off. On the other hand, we don’t have the research to know if those tools have any effect on outcomes or cost anyway. They sound inherently good, but so does robotic surgery, which Topol notes has done nothing to improve key outcomes.

My Conclusions

This is a fairly interesting book, assuming you like deep literature and news searches summarized loosely into a sometimes unconvincing narrative about AI in healthcare. Topol doesn’t follow the Silicon Valley mantra that AI will eliminate jobs, but instead lays out ways it could help rather than replace clinicians. That’s a compelling but simplistic view of how our healthcare system works.

The underlying assumptions are far from certain. We’re a profit-driven healthcare system, and attempts to wrest that profit back in the form of reduced costs rarely work. We also don’t know what patients want or what really moves the outcomes needle, so just throwing AI at interesting healthcare problems isn’t necessarily a huge step forward.

There’s also the question of who’s willing to pay for all this technology, which is being developed by startups and tech giants that expect hockey stick growth and endless profits. What they want may be directly at odds with what patients want.

Also in play is whether Eric Topol the exuberant futurist can represent the average frontline clinician whose day looks a lot different than Topol’s. It’s nice that he has the time and resources to write a book about AI and paint a picture of medicine that incorporates it, but I’m not so sure his worldview is accurate for the industry, especially the business aspects of it. He’s made himself an expert in this narrow AI niche that may or may not make him the best person to assess its use. People with hammers are always looking for nails.

We already have a lot of problems to fix. We’re probably not choosing medical school classes optimally or training doctors the right way. We are certainly not compensating them for doing the right things, and a fee-for-service system encourages practicing medicine that is clinically unsound but financially desirable. We don’t really know what patients want, or how they see the role of a PCP (if at all). We have ample evidence already and much of it isn’t being used on the front lines to make clinical decisions.

In short, while judiciously applied AI might provide some modest diagnostic and efficiency gains, I remain unconvinced that it will transform a healthcare system that desperately needs transforming.

Book Review: “Bad Blood”

I’ll save you the $13.99 Kindle price right now. Theranos was a fraud in every possible way. Elizabeth Holmes was its paranoid, money-fixated mastermind who was enabled by media that were enchanted with the crowd-pleasing and unfortunately rare story of a young, female Silicon Valley founder. Holmes didn’t care a bit that patients were endangered by the company’s entirely inaccurate blood testing system. She was a paper multi-billionaire until a series of exposes in the Wall Street Journal took the company down and put her on “healthcare’s most reviled” leaderboard ahead of Martin Shkreli. Thanks for coming out, I’m here all week, try the veal.

Or, maybe the $13.99 is worth it just to see how the company used its heavyweight legal team and connections to keep the scam alive. Or for the guilty pleasure of reading how Holmes sweated as the noose tightened, eventually going all Hitler in the bunker as she realized that at 34, she would never be trusted or taken seriously again.

You’ll like John Carreyrou’s book if you’re a fan of “All the President’s Men” or “Spotlight” and would enjoy the dramatic (and overly dramatic at times) account of how the reporter bagged the story of a lifetime and then got to double-dip his WSJ salary by repurposing his work into a bestseller. He’s probably worth a lot more than Holmes at this point.

Everything about the company was an elaborate hoax and so was Holmes, coached to ditch her thick glasses, speak in a creepily low register, wear black turtlenecks, and make lofty pronouncements about changing the world. She was like a lipsticked Steve Jobs except her fake voice was deeper, she was even better at milking the reality distortion field except to commit fraud instead of inspire achievement, and instead of kicking a dent in the universe, she was sent kicking and screaming into shame and ridicule (with a vacation behind bars a distinct future possibility).

Like Jobs, she was petulantly demanding, leaving a trail of fired employees and board members who dared question whether the empress was indeed wearing any clothes other than that ever-present turtleneck. Her 20-member armed security detail marched out employees who questioned the company’s patient-endangering technology that never worked. She oversaw her empire from an office she had designed as a replica of the White House’s Oval Office, which is about as weird as you can get.

The book opens with the company’s CFO playing his dutiful Silicon Valley role in inflating his already-inflated financial projection at Holmes’ insistence that she needed one of those hockey-stick growth charts like everybody else in Silicon Valley trots out while trying to keep a straight face. The CFO wasn’t too inquisitive about why Holmes refused to show him the drug company contracts on which his fantasy financials were based. His downfall came when he questioned Holmes about a demonstration of her blood testing machine that he knew didn’t actually work, charging Holmes (accurately) with simply faking the whole thing. She fired the CFO on the spot and the board didn’t press her for a reason (hello, clueless board). He was the company’s first and only CFO – despite heavy investment and a $9 billion paper company value, Theranos never had one again (hello, clueless investors).

Holmes dropped out of Stanford’s chemical engineering program after two semesters and wrote a patent application for an arm patch that would both diagnose and treat medical conditions. Her only fear in life was needles, which she vowed to eliminate for blood draws in favor of a finger stick, which sounds great to a 22-year-old college dropout who didn’t know or didn’t care that entire companies are filled with experts who have tried and failed to make that idea work. The sample size is too small, the dilution is too error-fraught, the repeated microfluidic flow through the testing machine is too complicated, and the skin material that is sucked up along with the blood always throws the results off.

Asked to describe how its product works, Holmes provided The New Yorker with a “comically vague” explanation:

A chemistry is performed so that a chemical reaction occurs and generates a signal from the chemical interaction with the sample, which is translated into a result, which is then reviewed by certified laboratory personnel.

Despite having no product, the business plan Holmes cooked up was brilliant. She envisioned drug companies paying her fortunes to perform home blood testing of clinical trials subjects, claiming that real-time reporting could save them 30 percent of their research costs and alert them to stop the therapy if patients experienced problems. Holmes was healthcare illiterate, but at least she knew that in search of health riches, you go where the money is (drug companies).

Holmes whipped employees into working crazy hours, spied on their email and telephone calls, hired private investigators to follow them, and didn’t allow company groups to interact with each other for fear of compromising her intellectual property. Her second-in-command was Sunny Balwani, her secret lover who was 18 years older than she. She marginalized the company’s board as “just a placeholder” that she charmed into giving her 99.7 percent of the voting rights, rendering the aged former heads of state and billionaires irrelevant as they joined the company’s investors in breaching their fiduciary duty. They treated her like a darling granddaughter who could do no wrong, smacking their lips approvingly at the inedible Easy-Bake Oven cake she proudly served them.

The blood testing technology didn’t work, so engineers jury-rigged a glue-dispensing robot to move pipettes around. Holmes immodestly named it the Edison. It was fraught with the same problems that plagued everything that Theranos ever designed – it could perform only a few tests, it wasn’t suitable for home use, and it ran only one sample at a time. Most importantly, it delivered inaccurate results. She had a very slick, Apple-looking case designed for it, though (it was not known to wear black turtlenecks).

Theranos ran an admirable “fear of missing out” scam on Walgreens, playing on that company’s fears that CVS would sign a deal first. Walgreens invested heavily even though Holmes refused to show them her lab and wouldn’t allow them to run side-by-side samples with commercial labs to verify the Edison’s accuracy (hello, clueless due diligencers).

Theranos avoided CMS and FDA oversight by claiming that its technology was “laboratory-developed tests” that fall between their respective jurisdictions, with the government predictably paying no attention. All Theranos had was a CLIA certificate and lab that was being run by a dermatologist with no lab experience. Holmes tried to work her connections to have the military use her product, only to become infuriated when a military expert said she would need an IRB-approved study and FDA approval. Holmes tried to get him fired. It didn’t matter anyway since she simply lied in claiming to anyone who would listen that the military was using Theranos in Afghanistan battlefields. She said it, so it must be true, and at some point she probably repeated it enough times to believe it herself.

Also scammed was the grocery chain Safeway, which envisioned a sexy future in wellness. It spent $350 million to add swanky Theranos testing stations to its stores somewhere back between the meat department and the rotisseried chickens.

Theranos started developing the MiniLab in 2010. Its only innovation over commercial machines was a smaller footprint for home and retail use. Holmes kept a straight face in calling it “the most important thing humanity has ever built.” She hired Apple’s former marketing company for $6 million to orchestrate a splashy product rollout and her own photo shoots.

Theranos couldn’t make its technology work in time to meet a Walgreens deadline, so Holmes simply bought a bunch of commercial blood testing machines and hacked them to try to make them work with the fingerstick samples. The friendly, fawning press asked no awkward questions. Her orchestrated fame emboldened her to fudge the numbers even more – she assured one investor that the company would make a $1 billion profit in 2015, while nearly simultaneously telling another investor that it would be $100 million. Her patient result numbers were equally all over the place, as the company performed untested processing on the modified commercial machines in its Phoenix-area rollout at Walgreens. They were just Fedexing samples back to California, which introduced another problem Theranos hadn’t thought of – the sweltering Phoenix summer sun was ruining the samples as they sat on hot Fedex planes. Doh!

The hoax started to unravel when a pathology blogger noticed that a paper Holmes co-authored had been published by a pay-for-play online journal in Italy and it involved a study of only six patients. The blogger contacted Wall Street Journal reporter John Carreyrou, who conducted his own test by having blood drawn at an Arizona Walgreens. He thought it was odd that it was a traditional needle draw rather than a finger stick, becoming even more puzzled when his same tests performed by LabCorp gave wildly different results.

While Carreyrou was investigating, the Theranos deception continued. The machines kept screwing up during demonstrations, so engineers rigged a “waiting” icon on display so the company could  blame connectivity problems and then run the samples later on commercial machines that actually worked. Holmes would encourage investors and reporters to have blood samples drawn in her offices and would show them the sample being inserted into the MiniLab, but as soon as they left, employees would pull out the sample and run it on a commercial lab machine.

In honor of a visit by Vice-President Joe Biden, Theranos built a fake lab in a conference room, stacking up non-functional MiniLabs and ordering employees to stay home in case anyone asked embarrassing questions.

Carryrou’s first article created a firestorm, although Business Insider’s Kevin Loria scooped him by a full six months in running a skeptical article quoting scientists in April 2015 – he really should get the credit. Many people defended Holmes, while others questioned how a medical company’s board and investors could have only healthcare-inexperienced people.

Holmes took to the airwaves to defend her company, proclaiming, “When you work to change things, first they think you’re crazy, then they fight you. And then all of a sudden you change the world.”

You know the rest. FDA declared the nanotainer to be an unapproved medical device. A surprise CMS inspection said Theranos was posing immediate jeopardy to patient health and safety. Holmes made Balwani her sacrificial lamb, firing him and breaking up with him. All Edison test results were voided, Walgreens and Safeway ended their Theranos partnership, Holmes was banned from the industry, and everybody involved sued Theranos, which had burned through $900 million of investor money and was rapidly going broke defending itself. As icing on the cake, the SEC began an investigation, declaring Theranos to have been a “massive fraud” from the beginning.

I’d like to think that most of us in healthcare eventually saw through the Theranos scam, or at least would have been skeptical enough to ask the questions that its investors and Holmes fanboys didn’t. The company made big claims without publishing peer-reviewed data. Its value proposition wandered – was the story the finger stick, the consumer access to blood tests, or the cost-lowering threat to LabCorp and Quest? Dropouts in their early 20s might well start technology companies like Facebook, but the Theranos board and leadership team were remarkably inexperienced and naive about healthcare and the huge players entrenched in it that had already already tried and failed to commercialize fingerstick testing. They also had the advantage that in terms of lab services, it’s all about draw-station locations and the economy of scale of running thousands of tests per minute through a highly automated factory, and Theranos would have needed to scale to thousands of times its volume to take even 1 percent of their market.

Theranos is a good reminder to healthcare dabblers. Your customer is the patient, not your investors or partners. You can’t just throw product at the wall and see what sticks when your technology is used to diagnose, treat, or manage disease. Your inevitable mistakes could kill someone. Your startup hubris isn’t welcome here and it will be recalled with great glee when you slink away with tail between legs. Have your self-proclaimed innovation and disruption reviewed by someone who knows what they’re talking about before trotting out your hockey-stick growth chart. And investors, company board members, and government officials, you might be the only thing standing between a patient in need and glitzy, profitable technology that might kill them even as a high-powered founder and an army of lawyers try to make you look the other way.

Book Review: “America’s Bitter Pill”

“America’s Bitter Pill” is not a feel-good book (pun intended). It’s not a fun read except for those folks who enjoy a maddening, blow-by-blow description of how legislative sausage is made. It tries to add drama and personal vignettes to events whose outcome is already known. Steven Brill tells us the obvious – the US healthcare system is a mess, the Affordable Care Act is a Band-Aid rather than major surgery, (and in fact made things worse in some ways), and there’s no resolution in sight.

The main message is that the Obama administration realized it had no chance of pushing through comprehensive healthcare reform given the presence of a strong healthcare lobby and rabid Republican opposition, so the ACA ended up being a Frankenstein law that was watered down with so many compromises that it did little except to expand the sales of medical insurance.

Political reality forced the administration to limit ACA to addressing coverage, not cost. Hospitals, drug companies, and device manufacturers stand to make even more money under ACA, which is why their powerful lobbyists – who practically sat at the table while the ACA was being negotiated – gave their required blessing.

Creating drama from politics requires characterizing people and organizations. President Obama is portrayed as well intentioned, but a bit detached and lazy in leaving the ACA details to others. White House staffers are seen as power-hungry and anxious to get Obama’s ear. CMS is a plodding, incompetent bureaucracy that vastly overestimated its ability to launch Healthcare.gov. Former US CTO Todd Park and HHS CTO Bryan Spivak are nice, geeky guys who weren’t invited to the Healthcare.gov table until it melted down. Insurance companies are low-margin businesses that are held hostage by greedy and ever-expanding hospitals that use their consumer brand identity to force high prices; insurance companies are also an easy but undeserving political target because that’s where the healthcare rubber meets the road for most consumers.

It’s interesting to read about how much influence data geeks have. An army of government number-crunchers has to to turn vaguely worded legalese into budget impact numbers that can make or break campaign promises, i.e. are new government ACA costs taxes or is the program budget neutral? Insurance companies have their own quant people whose insurance pool models determine their financial risk over many years. The stars of the book might just be the analysts whose numbers drove big political and business decisions.

The basis of Obamacare is the Romneycare three-legged stool: (a) a competitive insurance marketplace disentangled from employers; (b) a mandate that everyone buy medical insurance to avoid the self-selection in which healthy and young people opt out of subsidizing sicker and older ones by buying insurance; and (c) massive government welfare programs to help pay the medical insurance premiums for those who can’t afford them.

You can imagine the ugly details involved in rolling out this three-legged stool as a huge, complex law that even those legislators who passed it didn’t read in its entirety.

The book makes medical device makers as bad guys who escaped significant impact other than being charged a small medical device tax that they simply passed along to their customers. Their profit margins are extraordinary, their customers are hospitals who not only buy their products at high prices but then mark them up in selling them to patients, and they have positioned their products as a beacon of American medicine.

Drug manufacturers are bad guys, too, using their political influence to prevent importation of drugs from Canada (which like every other country, has much lower prices than here), to gain extended patent protection for biosimilar products, and to kill a provision that would have allowed Medicare to negotiate drug prices rather than paying made-up market prices.

Lobbyists had their fingers in the pie at every step, including those representing odd industries such as soft drink manufacturers, tanning bed groups, and ambulance services. Every member of Congress made sure to protect any back-home businesses that would have been negatively affected, including those that should have been targeted.

The author is sympathetic to physicians. He says Congress targeted them inappropriately in 1997 in its panic over rapidly increasing Medicare spending, implementing the Sustainable Growth Rate (SGR) payment cuts that have been overridden by Congress every year since. A fix was supposed to be in the ACA, but that, too didn’t make the final bill, and neither did tort reform.

CMS is characterized as just about as inept and bureaucratic as you would expect.They were afraid that Congress would de-fund some of their “offices” in their hatred of Obamacare, so they renamed them “centers” to make them an internal expense rather than a separately budgeted “office.” That bit of political sleight of hand came back to bite them, as the newly demoted “office” that was supposed to be overseeing Healthcare.gov was outranked by CMS’s procurement groups.

The result was a plodding bid process in which the same old government contractors made promises they couldn’t keep, with CMS deciding it would run the project internally. Literally nobody knew who was in charge – the author asked a bunch of people where the buck stopped and rarely got the same answer twice. Brill says the Beltway contractors “never met a botched product, cost overrun, or missed deadline they can’t pin on someone else.”

Still, the blow-by-blow on Healthcare.gov seems to be a distracting attempt at injecting drama and maybe selling a few more copies of the book. Government software failures, cozy contractor deals, and cost overruns are the rule more than the exception. The site was quickly implemented and horrendously complex, a massive integration effort involving other government systems run by the IRS, Homeland Security, and others. It failed, but it was fixed fairly quickly. Healthcare.gov is only a tiny part of the ACA. There were no particular lessons learned except perhaps that rushed, complex legislation that requires a rushed, complex technology solution is probably a bad idea all around.

Non-profit health systems are portrayed as somewhat well-intentioned monopolists unwilling to give up huge profits and executive salaries, using their hometown pride as big employers and their vague public threats of reduced quality from reduced payments to protect their huge incomes. The author mentions the complaints of the CEO of Montefiore Medical Center, who wailed about potential ACA-caused patient harm through lower margins just as the hospital turned a $197 million profit and that same CEO took home $4 million for the year. Brill talks about the cutthroat Pittsburgh market in which UPMC and Highmark hardballed each other and got into each other’s businesses trying to dominate the market.

Brill concludes that President Obama should be admired for pushing through broad healthcare reform even though he hadn’t expressed much interest as a candidate, but says that his failure to get involved with the details of ACA’s implementation will be be his unfortunate legacy. The backroom deals with profit-making entities ensured that the ACA fell far short of true reform and in fact will probably increase corporate profits as newly insured people consume their products and services as patients.

Brill says Obamacare won’t stand as a popular Democratic program such as Medicare and Social Security since it only helped the 20 percent of Americans without an insurance and another 10 percent or so who had been fooled into buying low-quality insurance whose benefits would run out after even a short hospitalization.

The end result is that most middle-class Americans continue to struggle to pay insurance premiums and inflated medical bills, the country still can’t afford the out-of-control medical spending that makes the US globally noncompetitive, and employers and hospitals got an easy out in blaming their ensuing self-serving actions on Obamacare.

Brill makes it clear that he would have preferred a single-payer health system, but he doesn’t notice the irony that in calling out CMS as inept bureaucrats, they run the closest thing we have to a single-payer system in the form of Medicare. He should have spent more time writing about that (and the VA’s government healthcare delivery system) than in trying to create TV moments in the form of Healthcare.gov war room arguments.

For all the problems recited, the book is short on solutions. Brill proposes:

• Let the big health systems get bigger and cut out the middleman by starting their own insurance companies, as long as each major metro area has as least two big players, but cap their profits.
• Limit hospital executive salaries to 60 times the salary paid to a first-year medical resident, or about $3 million in UPMC’s case (the CEO is making $5 million now). That’s not only a generous CEO salary cap, it also ensures an unintended consequence of raising resident salaries. Why not cap CEO salaries as a percentage of operating revenue instead?
• Pay doctors for quality. Sounds good, but the devil is (as was the case with ACA) in the details, which are missing.
• Encourage health systems to run urgent care centers and other less-expensive care venues. I think ACA is already doing that.
• Create an ombudsman appeals process for patients or doctors who think care is being compromised.
• Require health system CEOs to be licensed physicians with practice experience. He doesn’t provide reasoning for this argument, but he does express disdain for corporate types that move into running health systems. He also doesn’t say much of anything about for-profit chains, including publicly traded ones.
• Require health systems to insure a given percentage of Medicaid patients at a specific discount.
• Eliminate the chargemaster and require hospitals to charge uninsured patients no more than they charge insurance companies.

Steven Brill knew little about healthcare when he wrote his Time article and this book. In that regard, he comes across as a curious layperson outraged by what he learns, but perhaps too easily swayed by people and policies that he has filed away as “good” or “bad” in his populist outrage. 

The Affordable Care Act is a political lightning road and isn’t likely to be fine tuned by intelligent Congressional deliberation, so good or bad, it’s here to stay. Most of the people involved in creating it have already left government work and the Obama administration is counting down its remaining months. Meanwhile, the healthcare cash register keeps ringing for the same companies, organizations, politicians, and people who know how to make the system work for them. That’s what makes “America’s Bitter Pill’ unsatisfying as a reader – it’s unlikely that anything will really change as a result as healthcare costs continue to bankrupt individuals, companies, and the country itself.

Book Review: “The Patient Will See You Now”

I enjoy reading articles and tweets by technology fanboy Eric Topol, MD. He’s focused and intense. He’s always whipping out a smartphone-equipped EKG gadget on a plane or sticking a smartphone otoscope in Steven Colbert’s ear on TV. A lot of the tools he digs up seems to be of the “hammer looking for a nail” category and he’s created a nice gig for himself as a geeky critic of the medical establishment (even taking the AMA to task), but sometimes he comes up with ideas that might make a difference someday.

Topol is an undisputed thought leader. I like what he has to say even if I’m often skeptical.

Topol’s new book, “The Patient Will See You Now,” is an impressive (some might say “undisciplined”) romp through the healthcare technology garden. However, it fails to live up to its title, which suggests that savvy, responsible patients armed with cool smartphone EKG devices and fitness trackers have quietly wrested control of healthcare from the government, corporations, and providers of “eminence-based medicine” that make up the plodding and oppressive medical establishment. It’s a cute and gimmicky title, but it contains more hype than the book can deliver.

In fact, it sounds a lot like his earlier book (which I didn’t read) called “The Creative Destruction of Medicine: How the Digital Revolution Will Create Better Health Care.” That one is three years old, so maybe everything in it came true and he moved on.

The book wanders around so much that the only overall sense I could make of it required me to summarize each chapter, as follows:

1. Technology is widely adopted. Patients know their own bodies better than anyone.
2. Doctors are trained to feel superior and to control the flow of medical information.
3. The smart phone is like the Gutenberg press in democratizing and disseminating knowledge.
4. Angelina Jolie’s decision to undergo a double mastectomy because of genetic testing was earth-shattering, but the FDA tried to shut down 23andMe because that testing completely ignored FDA’s inquiries about its marketing and its offer to help the company comply with US laws.
5. I glazed over on Chapter 5 because it was a complex and questionably relevant primer on how genes work and how they can be used to personalize medicine. The bottom line: we should be doing more genetic testing for research and individualizing treatments.
6. Silicon Valley darling Theranos is revolutionizing lab testing. People have the right to see their own information. They should also be informed about the radiation dosage in diagnostic imaging.
7. Patients should be able to see their medical records. OpenNotes and Blue Button give that capability, but only 36 percent of patients can access their records and EHRs are primitive.
8. Prices for hospital services and drugs are irrational and vary widely, especially when comparing high US prices to those the rest of the world pays. We have a lot of waste and spend a lot on treating complications.
9. Telemedicine is cost effective and convenient, but doctors resist new technology just as they did the stethoscope when it was invented.
10. Hospital stays, which are expensive and error-prone, are declining as surgeries move to outpatient. Technology allows care and monitoring to be moved to the home.
11. People are willing to share their medical data for research, which will allow collecting and collating information to discover new research and best practices.
12. People are selling and stealing medical data.
13. Sensors can predict and track medical conditions.
14. Cheap smartphone-connected technology will democratize medicine to less-developed countries.
15. People own their medical data. Big employers should be using it to squeeze big insurance companies, but none have actually done that. Consumers haven’t mobilized. CMS and other administrative waste takes a lot of resources out of the system. Other countries will do better because of our archaic payment and regulatory model.

My frustration is that while the exhausting scattershot of technology nuggets is interesting (although hardly original since I’d heard of nearly all of them), it doesn’t prove the title’s hypothesis. It may well be that a few tech-savvy and demanding patients can convince their individual providers to let them get more involved in their care, but nothing suggests the presence of an unstoppable movement. In fact, while healthcare takes heat for being episode-based, a significant portion of consumers are even more episodic – they pay attention to their health mostly when something is bleeding, hurting, or swelling and then show up expecting a TV-like quick fix. The majority (especially the medically expensive ones) aren’t quantified-selfers or fully engaged participants.

A lot of people have smartphones, health apps, and fitness trackers, but those gadgets haven’t proven to make them healthier. Capturing and tracking information is just a tiny and easy part, as evidenced by the significant penetration of bathroom scales in the homes of overweight people. Patients (or consumers or whatever you want to call the 100 percent of us who will seek medical care at one time or another) can make consumer-like demands on their doctors, hospitals, and insurance companies, but I’ve heard few examples of where that actually accomplished anything other than possibly getting themselves labeled as a troublemaker.

People who receive medical services aren’t really pure consumers, so it’s not realistic to assume that the healthcare cheese can be massively moved by technology as happened in banking and entertainment. Patients don’t usually pay all their own bills. They go to whatever doctor and hospital the party that does pay (the insurance company) dictates, so threats to take their business elsewhere are usually hollow no matter how unpleasant or Luddite their doctors may be. Strap 10 smartphones with cool apps on your belt, pass out OpenNotes articles in the waiting room, and warn hospitals that they had better not make a medical mistake during your admission – your influence is still minimal despite being informed.

Topol’s broad observations and complaints aren’t really actionable. Patients have little control over the items listed above. The book title suggests that patients are in charge, and yet it’s still insurance companies authorizing payments, doctors entering orders and performing procedures, and the much-maligned medical establishment standing between patients and their maker. The healthcare system (or more correctly, the healthcare industry) was built around everybody except the patient. That establishment isn’t just going to step aside because patients carry iPhones. Any plan that requires people to voluntarily stop doing what they’re well paid to do will fail.

A few tech-powered concierge practices, retail clinics, and drug chains are threatening the status quo. They aren’t really scaring anyone. They may cherry pick a tiny bit of profitable business, but they aren’t much of a threat to health systems that keep buying up more providers and using their political influence as big employers to make sure they aren’t pushed away from the table. That’s the best hope for quick innovation that will reverberate through the hallowed walls, such as the real threat that Theranos will force high-margin hospital labs to either increase their efficiency or survive on a fraction of their current business.

Healthcare is like your car (at least if your car was built in this century). Your car is loaded with sensors (some of which, like the speedometer, you may conveniently ignore) and requires a computer to analyze its internal computer data stream. You can’t diagnose and fix it yourself when the idiot light comes on. You can study up all you want, but your only real decisions involve (a) whether you want to get it fixed, and (b) who you choose to fix it given your available options. You sit impatiently until the mechanic hands over a grease-stained list of procedures he or she performed along with a bill (as in hospitals, the computer that creates the bill is the most powerful one). All of that technology and data didn’t benefit you very much – it just generated more business for the mechanic, allowed him or her to work more effectively, and maybe avoided even more expensive repairs down the line. That’s pretty cool, but it’s hardly a revolution in empowering car owners.

That’s my takeaway from the book. Most of the technologies listed help doctors provide better care, assuming they are willing and able to use it. The role of their patients is, at best, to push for them to actually think about using genomics, following evidence-based medicine practices, reviewing their own outcomes information, and staying current on new medical developments. Patients, however, won’t usually voluntarily leave a doctor just because they don’t use an EMR or other gadgetry – that’s the art rather than the science of medicine – so it’s not really much of a threat.

Consumer choice in healthcare involves choosing the “best” provider to interpret, order, and perform procedures (or at least the “best” one willing to see you that your insurance covers). A doctor might be willing in the seven minutes you’re allotted for a return visit to look at your fitness tracker information, sit beside you as you Google your condition, or describe their charges to the price list from the MinuteClinic down the street. Don’t count on it. You’re only as empowered as is convenient for them.

Cardiologists make a great living and Eric Topol is no doubt excited to see his Scripps patients embracing technology and participating in their care, but it just doesn’t work that way for most doctor-patient encounters. People don’t get as broadly excited about health-related technologies as they might with social networking or music since the personal payoff is slower and less certain. Fitness trackers motivate and inform people who are already motivated and informed. Those aren’t the folks running up most of the country’s medical expenses.

Topol’s confidence that abundant technology will upend the US health system in favor of patients seems wildly simplistic. We can all – as patients and industry insiders – make a long list of what’s wrong with healthcare. That doesn’t mean we can change it through our individual actions. Healthcare is like the government in that it’s easy to identify what’s wrong, but hard to even agree on a solution, much less impose it against the will of far more influential people and corporations who are pretty happy with the present arrangement.

That doesn’t mean the book isn’t worth reading as a concise overview of what technologies are on the horizon. It’s good for that, at least for the next six months until it becomes outdated. It also doesn’t mean that Topol isn’t a passionate visionary because clearly he is. However, he could raise an army of fist- and smartphone-waving readers of his book who are upset with how most of us are treated as patients and health-seekers, but that alone won’t get our broken healthcare system fixed.

That’s my disappointment with “The Patient Will See You Now.” Reading it makes it easy to see what the future could be while knowing it probably won’t really happen, at least not in this country. I give it 3.5 stars out of five, docking it a half-star for an unrealistic title. Each chapter would have made a great blog post or magazine article, but I’m not finding them as compelling or entertaining in aggregate.