Preparing the 21st century healthcare industry

Bob Curry, Ph.D.

As KGI prepares the strategic plan that will take it to its 25th anniversary, the members of the KGI community are being challenged to imagine where we need to be 2022 to continue to prepare cutting-edge graduates who will work across the healthcare value chain.

During a post-dinner exercise Wednesday night, we were encouraged to consider a map of imminent changes in healthcare suggested by Bob Curry, who is chairman of our Board of Trustees, a veteran VC, and now CEO of Perceptimed.

Based on this experience, Bob suggested four megatrends that KGI should consider:

1. Growth in the science of diagnostic, prognostic, and monitoring tools will be explosive and be increasing paired with drug and procedure usage.
2. Drugs will become every more customized to treat highly defined cohorts as characterized in the discussion point above. This will change both the nature of drug discovery and of clinical trail design.
3. Healthcare will be delivered by a broader, integrated team of professionals than has been the traditional norm. Pharmacists and clinical diagnosticians will be teamed with physicians and nurses in staffing the healthcare system.
4. Hospital systems and health insurance companies, as we currently recognize them, will disappear and will be replaced by 50-100 integrated care organizations to cover the entire U.S. (e.g. 50-100 Kaiser-like organizations).

The first two points appealed to our scientists in the room, who (since our 1997 founding) have been thinking about genomic and personalized medicine. The third point relates to those interested in clinical care delivery, particularly our pharmacy school which trains its PharmD students to work in teams with MDs and RNs. The final point ties to the business side — our group within KGI — and the changes brought by ACA (Obamacare), both pushed by the strong patient incentives for adverse selection and pulled by incentives for Affordable Care Organizations.

Based on this, the 70+ trustees, faculty, staff and students at nine tables generated a series of ideas. From their ideas — and my own observations — I see four important trends:

• The importance of big data and data analytics. This is not just for analyzing genomic data for personalized medicine, but for patterns of clinical and other bioinformatic data for efficacy, drug-drug interactions, and other healthcare outcomes.
• New types of healthcare providers and business models for funding them. 
• Increasing importance of healthcare economics. Whether it’s HMOs, ACOs, capitation models, bundled pricing, or other approaches, we are moving away from a fee-for-service and dollars-per-pill model toward outcomes-based compensation.
• New regulatory approaches to deal with these changes.

Some of these trends were building and accelerating over the past two decades. (I've been with one HMO for 30 years). Others were accelerated by the ACA. Still others (the destruction of insurance companies) were not among the announced goals of the ACA, but may be its inevitable outcome.

Stone age EHR

Today was my first #bigdatamed conference data at Stanford Medical School, which is hosting a three day conference on Big Data in Biomedicine. (I wasn't able to come Wednesday but watched two sessions on the live webcast).

I first learned of the conference last year from Atul Butte (@ajbutte), who I met when he presented at the 2012 Open Science Summit. My impression from Atul (and watching the webcast last year) is this is a bunch of computational biologists who’ve replaced their wet labs with databases (or nowadays, cloud computing accounts), in search of the next great lead to be found on their computer screen.

Certainly the first two panels yesterday fit that pattern (the first moderated by Butte). So did the after-lunch keynote by former UCSD professor Phil Bourne, creator of the PDB (protein database): a few months ago, Bourne joined NIH as its first-ever associate director for data science, reporting directly to NIH Director Francis Collins.

Translating from Science to Practice

But today the conversation broadened (as one slide put it) from the "science of medicine (biomedical research)" to the "practice of medicine (healthcare)". In other words, from faculty to the clinicians, and from universities (few industry scientists were present) to hospitals and clinics.

Some of the differences were as expected. Drug discovery researchers are at the bleeding edge of the science, and then after 5 or 10 or 15 years of drug development (animal models, clinical trials, regulatory filings, manufacturing, marketing etc.) the product finally shows up in the hands of doctors. Similarly, researchers are hoping to add to their journal publications while providers are trying to improve clinical outcomes — and increasingly under pressure to do so at higher efficiency (of both time their time and the amount spent on tests and treatments).

For clinicians, HIPAA privacy rules limit dramatically what and how data can be used and shared. Researchers have institutional review boards, but also face HIPAA restrictions. The NIH helpfully makes available a brief (16-page) note on researchers should interpret the interaction of IRB and HIPAA privacy constraints. (As it turns out, both clinicians and non-clinical researchers at the conference complained that HIPAA places unrealistic limits on combining data from differing sources to render an assessment of a given patient's health).

Proprietary vs. Open Platforms
At some point, it was inevitable that participants would discuss where the patient’s clinical data resides. Ten years ago, it was in paper charts, but now the ACA has strong incentives and penalties to store it in an electronic health record or EHR. (The administration’s healthcare IT czar says don’t call it an “electronic medical record”).

It was also inevitable that someone would ask: if we are compiling personal genomic data for patients, how will that data be made available for the clinical benefit of that patient? By one estimate, a patient’s EHR runs less than 100 megabytes while whole genome data (I’m told) runs into the gigabytes. As David Watson (ex Kaiser CTO, now at Oracle) said on today’s opening panel, medical images (such as MRI scans) are stored external to the EHR; will that happen with genomic data?

More seriously, how will such data be phased into operational systems? On the same panel, Jim Davies (CTO for England’s 100K genome project) suggested that existing EHRs would need an abstraction layer that would allow new data types to be added on, i.e. the way that apps, plug-in modules and extensions are added to other modern software systems.

However, today the EHR vendors (except for VistA) as proprietary as mainframe platform companies of the 1960s. Even Kaiser — which in 2010 had the largest private EHR implementation to date — is highly dependent on a proprietary vendor (Epic).

Proprietary control of the platform means high switching costs and other proprietary control of the customer, and so (I predict) this is something that none will relinquish unless forced to. We have a technical solution, but not a market solution. And the ACA penalties for EHR non-compliance mean that no provider can credibly defer or set aside EHR adoption until one provides the necessary openness.

So we know where we need to go, but it’s not clear how we get there. Two Harvard researchers — Zak Kohane and Ken Mandl — have proposed a way forward, and the following year won $15 million from HHS to implement their Smart Platforms project.

However, the plan seems to think that either vendors will see openness as being in their own interests or that customers will organize to demand openness. As someone who’s studied IT openness for 15 years, I can say that openness is almost always instituted by the weakest player (e.g. a late entrant), and right now I don’t see an obvious candidate in the EHR market.

WIthout such openness, health care providers are stuck with healthcare IT systems without third party add-ons. This is not just pre-app store, but pre-IBM PC, pre-Apple II, vertically integrated platforms with little if any choice to extend or change their systems. In other words, EHR systems are stuck in the stone age (1960s) of the digital computer era, with little prospect for improvement.

Someday putting doctors out of business

In the KGI business class today, a student idly asked “when will computer replacing doctors in diagnosing patients?” Another student said “never”.

It's pretty clear that technology will reduce the labor-intensity of medical care, and also shift some tasks from expensive high-skill people to inexpensive low-skill people. Look at how cars were made by Gottlieb Daimler, Henry Ford, Toyota in the 1970s and then today.

Computers will over the next 20-40 years replace some or all of the role of doctors in diagnosing conditions. It’s too labor intensive and expensive not to become a target. The question is not if, but when, where first and how fast.

The claim will be that it's intended to improve consistency and accuracy, but the real reason will be cost. Claimed improvements in quality — such as for patients who lack access to a specialist for diagnosis — could be used to overcome the opposition of highly educated, compensated and organized physicians.

The initial push thus will come from an organization that both has scale economies and a record of innovating to save pennies. My prediction is that the first major use in North America will fall in one of three categories:

• US government, probably the Veterans Health Administration
• An HMO, almost certainly Kaiser Permanente; or
• A provider serving rural areas, most likely the First Nations and Inuit Health Branch of Health Canada.

How "Perfecting Medicine" will reshape the life science industry

At his talk this morning at KGI, Dr. Paul Billings argued that the vision for 21st century medicine needs to go beyond personalized medicine to “perfected medicine.”

The chief medical officer of Life Technologies, Billings started by reviewing where medicine was for centuries, and the progress that was made in the 20th century to improve upon that. He illustrated the 19th century state of the art with “The Doctor,” pained by Sir Luke Fildes after his son died in 1877 of tuberculosis. As an MD working for a life science company, Billings argued for a world that both keeps the personal attention of the caring physician while providing doctors with the best science for preventing and curing illness.

Unfortunately, while the 20th century brought many lifesaving therapeutics, the approach towards selecting and dispensing these therapies is remains one of “trial and error.” He showed a chart that failure rates for post-heart attack medications and mammographs of are more than 10%, while airline flights have a fatality rate of less than 1 PPM. Billings lamented that having hospitals "more like bagging handling is not what I'd like to see about healthcare delivery".

From the perspective of systems biology, a solution proposed for this existing paradigm has been proposed through approach of “4P medicine”: predictive, personalized, preventive, participatory.

However, Billings argues that we need to go further: "We want 1P medicine: perfected medicine.” Such an approach would rebuild healthcare from the ground up, to tailor solutions for individuals make choices based on scientific understanding. To support this vision, he cited the 2008 report of a presidential advisory board, “Priorities for Personalized Medicine.”

Billings wants sequencing to be more mainstream in healthcare, the way that imaging and other modalities are: "I don't want to be in the basement of hospitals any more — I want it to be on the ground floor”. (Of course, Billings works for one of the major vendors of sequencing products.)

Based on the research of Jonathan Rothberg (of Ion Torrent), DNA sequencing has shifted optical-based sequencing to semiconductor-based sequencing. For the audience, Billings waved around a DNA sequencer chip the size of a postage stamp. A $50k sequencer that in 2013 will soon do a sequence in 2 hours for a marginal cost of $1,000.

Billing predicted that the performance improvements by this CMOS-based sequencing will continue indefinitely — as did microprocessors — and allowing sequencing to shift from sequencing specific genes to whole genome sequencing. (Of course, there is the nagging problem of the cost of the data analysis to make sense of that data).

But, Billings argues, the benefits are not just limited to price. Instead of sequencing in batches and taking weeks, the results will come back in hours. Various conditions — such as a heart attack, TV or sepsis — need answers much much sooner than weeks to make the appropriate clinical intervention. Cheap sequencing will also allow applying therapeutics — especially expensive biologic compounds — only for those patients who will benefit.

In an era of limited resources for healthcare, there’s a need to also demonstrate this technology can (as in the case of Sir Luke’s personal tragedy) to deliver "outcomes that matter". He provided the example of the May 2011 fatal E. coli outbreak in Germany, in which a DNA sequencer was used to characterize the bacteria and develop a scalable screening process in less than a week. (See the PLOSone article for more info.)

This is going to be highly disruptive to existing business models. For example, when Billings put up a slide showing how a series of existing tests might eventually be replaced by a singled sequencing test, I immediately thought about all the buggy whip makers that are going to put out of business.

I raised this question during the subsequent panel discussion, a discussion that included Billings, Board of Trustees chairman (and health care VC) Bob Curry, Advisory Council member Russ Teagarden of Medco, and Professor Jim Osborne (formerly of Beckman Coulter).

To Billings, I suggested that if firm can’t sell diagnostic tests, they’ll try to extract patent royalties from their gene patents from companies that are selling the all-in-one tests. I’ve lived this world in my previous research, as it’s S.O.P. for cellphones and other parts of the telecom industry. Diagnosing human disease with a single whole genome test will bring patent stacking that will go far beyond any pocket-sized device (at least until the patents expire).

Billings noted that companies who have such gene patents are aware of the problem (although he doesn’t know or wouldn’t say what they think the solution is). As an example, he mentioned the controversial diagnostics company Myriad Genetics, whose sequencing of cancer genes has done so much to improve our understanding and treatment of breast cancer. (At lunchtime, we discussed whether the gene patenting industry needed an Apple to impose an iTunes-like pricing model, or whether it could organize an ASCAP or BMI to collect and allocate royalties among rightsholders).

Ready or not, the existing businesses are going to be disrupted in a classic Schumpeterian example of “creative destruction.“

On the other hand, based on past experience it seems unlikely that the US regulatory bureaucracy — or the rest of the healthcare payment or delivery system — are ready to be disrupted. As Advisory Council member Weaver Gaines put it, it takes 20 years for a new medical approach to be adopted — or even a generation for the old guard to die off.

Bob Curry was a little more optimistic about FDA cooperation due to the pressure it will face from regulatory arbitrage: if the US won’t approve new approaches, then other countries — like Denmark or Switzerland — will.

However, adoption of a new paradigm also requires acceptance by healthcare providers and also healthcare payers. Both Teagarden and Curry noted the delays (and often unrealistic evidentiary expectations) required to get payers to agree to reimburse for diagnostics. The panel agreed that adoption will increasingly require that new approaches not only save lives, but also save money.

The panel also discussed the challenge of getting new practice accurately explained and adopted by frontline health providers. Curry pointed to the ongoing trend for doctors to leave their individual practices and affiliate with regional hospital groups, which he predicted would make it easier both to reach and to incentivize these M.Ds. to adopt the new scientific paradigm.

Photo credit: “The Doctor” (1891) by Sir Luke Fildes, courtesy of Wikimedia Commons.

What are doctors worth?

US doctors have historically been among the best paid members of a community. One list puts surgeons ahead of CEOs, while another study (based on BLS data) shows medical and dental professionals best represented among the top 25 professions.

However, in countries where government runs and controls healthcare, the premium for doctors is not so high: doctors are paid like government professionals rather than self-employed small business owners. A NYT report puts doctors’ pay in some of the Scandinavian countries at half that of the US. Not surprisingly, many economists expect that (for good or for bad) if the US system continues to evolve towards the European model, doctors’ salaries will do likewise.

Now a Business Week report suggests the premium for doctors in China is ridiculously low:

A newly qualified doctor makes about 2,000 to 3,000 yuan ($309 to $464) a month, while a one-bedroom apartment in Dalian, a city of 6 million people, goes for 2,000 to 2,500 yuan. Typically three or four newly qualified doctors will rent a flat together to defray their costs, Mao says.

Shi Yingkang, dean of the West China Medical School at Sichuan University in Chengdu and vice-president of the Chinese Medical Doctor Assn., says half his students spurn local hospitals for better-paying jobs overseas or in drug sales. “To them, the pay does not match the effort put in,” explains Shi, who says pharmaceutical reps can earn two to three times more.

In fact, the article is about how the doctors are quitting their practice to become sales reps for Western pharma companies, including Pfizer, Sanofi and Bayer. An estimated 30-40% of sales jobs in China are staffed by doctors, with pharmacists and nurses also being targeted.

I would be curious to see how the salaries of Chinese doctors compare to party officials, entrepreneurs or software engineers. But with the state in full control of this segment of the economy, it’s not like they have a choice — other than to join the pharma companies or emigrate.

BTW, it had occurred to me that top US sales reps might be paid so generously that they are paid better than doctors. Certainly I’ve met B2B sales representatives who are paid $100k, $200k or more. But according to Monster.com, the median compensation (salary+commission) for pharma sales reps with 20+ years experience is only $125k.

Still — as with any government policy to set salaries — there are important questions about what is a fair price for doctors. The medical profession is highly skilled, with long training required and a need to attract the most talented people. Even for systems that set pay by central planning (rather than the market), one would expect doctors to command a salary well above average.