Ontario Healthcare Tech Scene, Hey

Two decades ago I would occasionally find myself in Ontario given the developing innovation corridor between Toronto and Waterloo, affectionately referred to as “Silicon Valley North.” Last week I visited again and saw the emergence of a strong healthcare tech ecosystem, leveraging historic strengths in telecom infrastructure and the recent (and significant) commitments to the artificial intelligence sector. Out of a coordinated series of university initiatives, Thomson Reuters recently reported that over $350 million had been invested in the AI sector over the past three years in Ontario, employing over 1,100 AI researchers alone. “Silicon Valley North” is the third most important AI cluster in the world according to Element AI. This past week, Salesforce said it would invest $2 billion in the Canadian tech sector.

My meetings were on the Canadian side of the Niagara Falls, which I had not visited since I could barely peer over the protective handrails. Niagara Falls is actually three waterfalls, the highest of which is 165 feet. At peak flow rates, over 45 million gallons of water passes over the falls per minute. Let me help you with that: one million gallons would almost fill a football field-sized swimming pool that is ten feet deep. During winter evenings, the mist freezes to create a drip sandcastle effect at the base of the falls which melts when the sun rises.


Many of the entrepreneurs I met were developing fundamental technologies, often addressing infrastructure issues in healthcare – not light-weight engagement apps. While accessing capital was a common complaint given only a few local funds, notably all of the entrepreneurs were scaling their businesses with quite modest burn rates and were knocking down important milestones. With great pride, many pointed to some of the significant local success stories such as PointClickCare (EHR provider for long-term care sector) which had raised $145 million and had nearly 1,000 employees. Some of the other companies cited were developing genetic computational systems or AI-based drug discovery platforms or other broad healthcare management platforms.

Perhaps this is not so surprising given the concerted efforts to strengthen the local healthcare ecosystem. In January 2017, the Ontario Bioscience Innovation Organization published a report highlighting a set of initiatives centered around (i) commercialization, (ii) local healthcare system engagement, and (iii) global engagement with leading multinationals. Such a dedicated effort so far as resulted in $109 million of capital invested in 45 companies and has seen those companies grow the combined employee base by 49%.

Contributing to this success was undoubtedly the broader technology ecosystem. Ontario is the second largest of the 13 provinces and territories in Canada. With 13.5 million people covering 415k square miles, Ontario accounts for 40% of the Canadian population but has 60% of the tech sector’s employment (2014 census data counted 280k tech workers). Over 810k people work in the healthcare industry.

The advent of a successful healthcare tech community often springs from the intersection of the established healthcare delivery system (Ontario has over 460 hospitals) with tech entrepreneurs looking to solve important healthcare problems. Pressing societal health issues also contribute to deep sense of mission. As in every other geography, aging population, chronic diseases and limited access to services drive the need for innovation. As of 2016, nearly 2.3 million Ontarians (that is a word) were over 65 years old (nearly 17% of the population). In 2014, 18.1% of the population smoked and 17.9% were defined as “heavy drinkers” – probably considerable overlap – according to Statistics Canada. Over 54% of adults were deemed overweight or obese; 21.1% of all children. These issues are not at all unique to Ontario. Recognizing this, the provincial government in its Action Plan for Health Care 2106-2018 aggressively advocated for resources to be moved to more community based models and away from acute care settings.

As I left Niagara Falls, I could not shake the stories of the 15 people who deliberately went over the falls, some in barrels (why a barrel?), some in canoes, some with just a life vest. Two people – Steve Trotter (1985, 95) and John Munday (1985, 93) – actually went over twice! As I studied the healthcare census data – 37.1% of males 20-34 years old in Ontario are considered “heavy drinkers” – I could not help but wonder what Steve and John had been drinking.


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Rounding the Bend, Heading For Home…

The 3Q17 year-to-date funding data point to several important emerging themes and may clarify where the broader healthcare technology sector is heading. Through nine months the investment pace has been nothing short of robust with StartUp Health and Rock Health data tallying $9.0 billion and $4.7 billion, respectively, although there are signs of recent moderation ($2.5 billion was invested in 3Q17 according to StartUp Health, suggesting a more muted 4Q17 level).

More specifically, according to StartUp Health there are now three sub-sectors of the healthcare technology sector which have already attracted more than $1.0 billion of capital YTD (Big Data/Analytics ($1.3 billion), Personalized Health ($1.2 billion), Medical Device ($1.0 billion)), underscoring both the maturity and depth of these market opportunities. Notably, seed investment activity was 28% of the total deal count 2017 YTD, which is the lowest annual level since 2010, further suggesting that we are now entering a period of consolidation, when emerging category leaders come of age, separating themselves from the pack. Furthermore, average deal size increased from $14 million in 2016 to $18 million YTD 2017. In 2016, Accenture determined that only ten companies accounted for 38% of all private equity fundings in the healthcare technology sector; expect to see that continue in 2017.

The strong fundamentals are not lost of public stock investors either. The Leerink Healthcare Tech/Services stock index increased 30% over the first three quarters of 2017, trading at a heady 15.5x and 15.3x 2017 and 2018 EBITDA, respectively. EBITDA margins for 2017 and 2018 for this cohort are estimated to be 23.4% and 20.2%, underscoring the profitability of the successful companies in this sector. Accordingly, aggregate revenue growth forecasts for that same group of companies in 2017 and 2018 are 19.1% and 15.3%, which implies 4.3x and 3.7x 2017 and 2018 valuation multiples of revenue.

One emerging paradox then is the relative lack of M&A activity in the healthcare technology sector, particularly considering the growth characteristics of the sector and acquirers with strong public currencies. TripleTree tracked 242 closed M&A transactions in 3Q17, although only 45 disclosed deal metrics; notably, the average revenue multiple in those transactions was 2.8x, meaningfully below the level of publicly traded companies in the sector. Total 3Q17 transaction volume was $16.2 billion which was a decrease of 45% from the prior quarter. Crosstree Capital Partners identified only 7 deals in 3Q17 with announced values of greater than $250 million, suggesting that much of the M&A activity was small, likely distressed sales of companies that were not able to scale. This is not surprising given the amount of venture capital that was deployed in 2015-2016, which afforded start-ups only 18-24 months of runway.

Another topical item has been “healthcare Artificial Intelligence” (AI) and what the likely impact of these solutions will be on healthcare. Rock Health estimates that stand-alone AI vendors will account for nearly $500 million of investments in 2017 (or nearly 10% of all activity) and that 80% of those companies are principally B2C focused. Anecdotally, with increased customer fatigue and elusive ROI for many of these products, we may be at an inflection point here as well. AI vendors will need to modify business models to allow them to take on more risk, aligning with customers to help solve fundamental clinical issues versus simply flagging at-risk members / patients. According to a Pricewaterhouse Coopers (PwC) industry framework, healthcare AI is mid-way through the second of four phases (“Data Fusion” phase) when customers are experimenting with AI solutions and industry alliances emerge. By 2020, PwC calls for the “Commercialization” phase when meaningful clinical impact will start to be realized. Soon will come the day when AI is no longer tracked separately and it is simply part of every healthcare technology company’s product offering.

Two other important themes presented themselves over the last few months: (i) dramatic and large company M&A activity (CVS – Aetna, Humana – Kindred, UnitedHealth – DaVita, etc); and (ii) quite an accommodative regulatory environment. At its essence, the transition to value-based models is driving providers and payors to manage greater elements of the patient / members’ healthcare journey. With possible Medicare and Medicaid cuts coming, the specter of very significant pricing pressure is very real. And recently introduced is the competitive concerns of what a healthcare-focused Amazon means to established businesses as the patient / member becomes even more of a healthcare consumer. If nothing else, with scale should come a stronger hand when negotiating customer contracts.

Health M&A

Undeniably the new FDA Commissioner Gottlieb has created a more accommodative regulatory framework for healthcare technology start-ups, from establishing pre-certification pilot programs to lowering the hurdles for direct-to-consumer genetic health risk tests. Expect to see a wave of novel diagnostic devices, disease management platforms, monitors, etc be introduced to the market without the historic burdensome regulatory pathway. Notably, in 2017 the FDA cleared 51 connected health devices. Additionally, the Creating High-Quality Results and Outcomes Necessary to Improve Chronic Care Act (CHRONIC Act) was passed in 3Q17, which expanded Medicare coverage for telehealth services.

Arguably, the two themes above are beneficial to healthcare technology start-ups. For the established companies, new revenue opportunities and new risks that need to be managed require innovative new products and solutions, sourced (or acquired) by start-ups. Coupled with a more forgiving regulatory environment, expect to see faster “time to market” which has been one of the chronic issues confronting many early-stage healthcare technology companies – rarely is it that the product does not work but rather a window was missed due to poor product / market alignment.

Another interesting perspective to handicap where investor focus will be over the next few years is to look at the gravest threats to the human condition today. Quite clearly, we are struggling with a national addiction crisis as well as confronting a host of devastating neurodegenerative diseases. It is also more understandable why behavioral issues are so front and center in healthcare VCs minds now. As shown below, our biotech VC brethren have had a dramatic impact on many other chronic diseases.

Mortality Disease

So, as we turn the page on another year, there are several emerging opportunities that should continue to gain traction. At their essence is the imperative to have greater presence, real-time, “in line” healthcare infrastructure, implying a handful of elements:

  • Dramatically greater level of data sharing with improved interoperability, particularly in the clinical setting, needs to improve after nearly a decade since widespread electronic medical record adoption, to address widespread data asymmetry in healthcare
  • Novel care delivery models will continue to develop and be more robust, from telehealth to other modalities to meet the patient where it best suits him / her, particularly in the home – healthcare system needs to move from a paradigm of healthcare consumption to one of healthcare experiences, and price accordingly
  • Deeper levels of patient engagement, both active and passive, acknowledging that healthcare complexity requires that much of the coordination and navigation will need to be done on behalf of the member / patient / consumer
  • Employers will continue to play a larger role in what defines success for healthcare technology companies, as the employer has clear and measurable ROI requirements
  • Computational care driven by AI and personalized medicines


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3Q17: Turbulence Ahead at Cruising Altitude?

With Bitcoin blasting through the $7,800 per token ceiling last week (then promptly dropping $1,000 in last two days), Apple now worth $900 billion, and unemployment at 4.1%, it is a good time to look at 3Q17 funding data. The venture capital industry continued to power along in 3Q 2017 as 1,706 companies raised $21.5 billion. While a slight decrease from the activity in 2Q 2017, the annualized pace suggests that 2017 will be one of the most active years on record for capital deployed. Notwithstanding the evidence that mutual funds and hedge funds have pulled back somewhat from their investment pace in 2014-2016, sovereign wealth funds and SoftBank’s recently upsized to $98 billion Vision Fund (closed in May 2017) have continued to drive overall investment activity.


In fact, the SoftBank impact is more dramatic than one might initially have thought. The largest investment in the quarter was the Vision Fund’s $3 billion investment in WeWork, which means that 14% of the capital invested in 3Q17 went to 0.06% of the companies. Year-to-date there were 61 venture financing rounds that were greater than $100 million; in 3Q17 alone, there was $8 billion invested in $100+ million rounds and SoftBank was 52% of that amount. In its first six months, the Vision Fund has invested $18.4 billion in 15 companies already, which is just over 40% of total venture capital invested in last two quarters.

The number of large financings somewhat masks the fact that the overall number of investments is declining markedly. In fact, this past quarter was the lowest deal total in the past 24 quarters extending all the way back to 4Q11. The most dramatic retrenchment occurred in the Angel/Seed and Early Stage rounds, which likely correlates to elevated pre-money valuations, which at $15.9 million for Series A deals year-to-date is over twice the valuation levels from 2008 -2013. Late Stage valuations over that same period were between $50 – $100 million, and through 2017, the average Late Stage valuation was pegged at $250 million.

Most of the buzz this past quarter involved cryptocurrencies and the explosion of Initial Coin Offerings (covered here). Notwithstanding the very legitimate concerns by regulators and the IRS, there were 140 ICOs that raised in aggregate $2.2 billion in 3Q17 according to CoinSchedule. In most cases, these companies do not have an existing product, provide little to no substantive due diligence materials, and the issued tokens trade with extreme volatility. Whether these tokens go on to be an enduring source of financing is not clear, but in the moment, this is a very tempting (and fast and inexpensive) way for entrepreneurs to finance interesting projects with no pesky shareholders. One other emerging issue: according to Motherboard, a single Bitcoin transaction requires 215 kilowatt-hours of electricity which is enough to power the average U.S. home for one week. As a point of comparison, venture capitalists have invested $23.2 billion in 2,272 Software companies year-to-date, highlighting how material ICOs have become.

There was considerable discussion on the state of the exit market and the level of liquidity. With the prevalence of very large Late Stage financings, many high-quality companies are choosing to stay private longer. According to PitchBook, there have been only 530 venture-backed exits year-to-date with aggregate exit value of $36.4 billion ($69 million per exit on average, which likely is below invested capital in many cases). More troubling has been the lack of any meaningful IPO activity. While overall there were 29 IPOs which raised $4.1 billion, only 8 of them were venture-backed. Importantly this was a decrease of 30% from the IPO level in 3Q 2016 and was driven by the 70% decline in technology IPOs. In stark contrast, per Dealogic data, IPOs in China raised $8.6 billion year-to-date.

Exits come in many shapes and sizes. Companies that shut-down are one of the (many) hazards of the job (it is not unusual for great performing venture funds to write-off 25+% of invested capital in any given fund). Per TechCrunch, through the first three quarters of 2017, the top ten venture-backed companies that failed had raised in aggregate $1.7 billion and included some very recognizable names such as Jawbone, Beepi, Yik Yak and Juicero. Ironically, in 3Q17, $1.7 billion was invested in 788 Angel/Seed stage companies.

An interesting lens through which to assess the state of the exit environment is how many companies are funded each year as compared to how many are exited. The chart below shows that ratio to be at a highwater mark of over 11x, underscoring that companies are staying private much longer. Interestingly, it is estimated that the cumulative value of all unicorns today is approximately $575 billion which reflects significant unrealized value for many venture funds.


invest to exit

The time to exit is very important as well and something that is tracked closely. While venture firms tend to be more focused on multiple of invested capital to determine whether a given investment was successful, many fund investors think in terms of IRRs – and time is not your friend in that discussion. Over long durations, the venture capital asset class consistently generates the most attractive net returns to investors, but according to Cambridge Associates, short-term venture capital returns recently have lagged other asset classes. For instance, 2Q17 IRRs for venture capital, private equity and the S&P 500 index were 2.0%, 5.1% and 3.1%, respectively. Year-to-date and the one-year performance for venture, private equity and S&P 500 are 5.3%/9.3%/9.3% and 8.8%/17.4%/17.9%, respectively. Longer holding periods hurt IRRs. Private equity investors have been able to exploit low cost debt to finance large recapitalizations, while public companies have enjoyed unprecedented significant global liquidity flows and record stock prices.

Time to exit no table (002)

Despite generally robust venture capital distributions over the last several years, the venture industry in 3Q17 only raised $5.3 billion across 34 funds, which was significantly below the 2Q17 pace of $10.9 billion across 60 funds. Average fund size in 2017 to-date is $156 million while the median is only $60 million, indicating that a relatively small number of very large funds were raised. In fact, of the 157 funds raised in 2017 so far, 68 have been below $50 million in size with another 26 between $50 – $100 million; 10 funds were greater than $500 million. There were only 25 first-time funds, underscoring again that the venture industry continues to consolidate around a relatively small number of larger firms.

The “Funding Gap” is alive and well. The amount of capital invested continues to meaningfully outstrip the amount venture funds raise, showing that there are other types of investors piling in to fill the gap. Optimistically, one might argue that the venture investors are getting great leverage on their early stage dollars. On the other hand, the pessimist might argue that, once the music stops, non-venture investors will return from whence they came, leaving many venture-backed companies hung up and dependent on a relatively small set of investors. Given that the current economic expansion is now over 100 months old, and the average expansion lasts only 58 months, the optimist may be looking over his/her shoulder.


Raised vs invested wo table (002)


There are always a number of other nuggets in the quarterly funding data that are worth flagging, which provide additional commentary on the current state of the venture capital industry.

  • California continues to be the most active state (it’s also one of the largest geographies) with 580 financings in 3Q17 accounting for $8.7 billion ($15 million average deal size) as compared to New York (#2) with 188 and $5.1 billion ($27 million average – WeWork effect?) and Massachusetts (#3) with 121 and $2.6 billion ($21 million average – biotech effect?)
  • All other states combined were $5.1 billion across 817 companies ($6 million average – really capital efficient) further underscoring the capital concentration concerns
  • The Top Ten financings captured $5.9 billion which means 0.6% of the companies accounted for 27% of the capital invested; all of those companies were in California, New York or Massachusetts except for one (Vets First Choice, which is in Portland, ME, which is kind of northern Massachusetts)
  • Secondary funds raised $29 billion year-to-date, per Preqin, with another 44 funds in market to raise $31 billion, which signifies greater liquidity for LPs as well as suggesting a level of maturity to the private capital markets
  • Per PitchBook, this past quarter debt-to-EBITDA levels in the buyout world hit 5.8x which is the highest levels in the last ten years….hmmm.

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You Are Where You Live…

This will be complicated – and potenitally quite controversal. It is not at all meant to be a political commentary but where you live may directly impact your health. As the role of social determinants in one’s well-being are better measured and understood, there is the promise that they can be better managed. An analysis of the patchwork of differing state regulations, government priorities, economic conditions, and local norms and cultures shows fascinating patterns which provides commentaries on the state of health by state. Geography may be one of the most influential determinants of one’s health.

Undeniably the level of economic disperity across the country has increased dramatically, punctuated by the emergence of highly concentrated pockets of exceptional wealth. The Economic Development Group and its Distressed Communities Index (below) highlights the level of this fragmentation. Their analysis determined that three of every four new jobs were created in only 40% of U.S. zip codes, and that more than half of the communities determined to be distressed have seen a net job loss since 2000. Of most importance, life expectancy for people in those communities was a full five years shorter. As communities become more economically distressed, investments in public health infrastructure naturally become further impaired.




Last month the Brookings Institution’s Metropolitan Policy Program published research comparing the economic conditions of the top 100 cities in the U.S. with the 182 smallest (which had populations between 50,000 and 215,000) and the results were startling. Employment levels grew twice as fast in the largest cities while income levels grew 50% faster. Economic dislocation and disruption, most notably from automation and foreign trade, appear to disproportionately impact smaller cities. The resiliency of larger metropolises is attributed to the aggregation of human and financial capital leading to greater levels of innovation. The cities of New York, Los Angeles and Chicago alone accounted for 17% of the national GDP last year. Not lost on any of us, in the recent presidential election 57% of cities with a population of less than 250,000 voted for the Republican candidate while only 38% voted for Secretary Clinton.

Certainly, large cities are not the panacea for all of a community’s ills. The New York State Technical and Education Assistance Center recently published a sobering analysis on the condition of New York City schools, finding that 10% of the students are homeless. These students demonstrated markedly worse academic performance, often testing at levels 50% that of the other students. One-third of homeless students missed at least one month of schooling and 62% of them were deemed “chronically absent.” Obviously being raised in those conditions will directly impact one’s health and well-being.

Furthermore, while an individual’s “investment” in healthcare comes in several forms, it is perhaps best reflected in the level of out-of-pocket expenses incurred. Interestingly, the JP Morgan Chase Institute recently compared annual out-of-pocket expenses as a percent of take-home pay for 2.3 million customers in 23 states. While generalizations are very difficult to make without further and more complete study, the data strongly suggest that more affluent states spend less as a percent of income on out-of-pocket expenses (healthcare costs are relatively less burdensome perhaps), making quality care more affordable and therefore, attainable. States with less of a healthcare cost burden have fewer distressed communities. Undoubtedly, though, differences by state have as much to do with specific insurance plan designs and local provider costs, which are often influenced by local regulations and how competitive a given market is.


Obviously, there are many factors which influence levels of obesity in any given region; quality of the healthcare system, access to healthy food, cultural considerations and weather to name just a very few. The Body Mass Index map below developed by the Behavioral Risk Factor Surveillance System is even more provocative in light of the map above as states exhibiting greater levels of distress neatly coincide with those that tend to be more obese. As wealth continues to aggregate in fewer distinct regions of the country, many of which are on the coasts, the general well-being of many states in the middle of the country become of greater concern. Somewhat antithetical to that concern are the residents of Colorado who spend a lot on healthcare and appear to be in the best shape of all of us; my namesake of Greeley, CO (“go west”) looks to be particularly relaxed and healthy.



Source: Behavioral Risk Factor Surveillance System

Just to jump to the conclusion, arguably of most importance are relative mortality rates. How much does a social determinant like geography account for the tremendous variability observed in average lifespans? Here again the map is provocative, and perhaps even suggestive. The average annual mortality rate across the country between the years of 1999 – 2015 was 786 people per 100,000; the deep magenta counties were over 200 people more than that average. Are there healthy and less healthy regions of the country? Quiet clearly, yes.


mortality rate


Intermountain Health recently stated that “zip code determines health more than genetic code” when presenting data of two nearby Utah towns with very different demographics. In one town, the average household income was $77,000 with 5% living below the poverty line, and a life expectancy of 85 years. In the other town the average household income was $40,000 with 24% below the poverty line, but tragically the life expectancy plummeted to 76 years.

Shockingly the next map looks quite similar to the others when looking at something as disturbing as murder rates by state. A large swath of the country, which happens to correlate to areas of greater levels of distress, suffers with annual murder rates between 4 – 10 people per 100,000, which in some cases may be 5x the rate experienced in other states.




Just about two years ago I studied the Social Security Administration’s “Life Expectancy Calculator” and learned that I had 10,877 days left, which is now closer to 10,000 days. This is quite sobering and causes me to consider a relocation to Greeley, Colorado, which is nestled in something called the “Front Range Urban Corridor” (sounds enticing) and was determined by Forbes to be #5 of the ten best “Top Small Cities for Jobs” – although being a small city may now be somewhat problematic.


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Silly Rabbit…

Last month General Mills announced to Trix’s die-hard fans that it would return to artificial dyes and flavors, after two years and a lukewarm consumer reception to natural colorings from turmeric, strawberries and radishes. Turns out consumers far preferred Red #40, Yellow #6 and Blue #1 dyes.


For some time now, the healthcare industry has known that social determinants (items like food quality, residential address, access to education, etc) play a significant role in one’s health but the industry has struggled to properly assess, much less manage, such important factors. Coincident with this, my focus for some time has been about how close we are to actually developing tools to effectively accomplish this.

The premise is that multiplexing a set of disparate data sets will provide some startling  (and hopefully actionable) insights. For instance, one question we should be close to answering is “what is the quality of caloric consumption by a specific address, and maybe by each individual at that address?” Census data and voting rolls tell us how many people live at any specific address and their ages. Credit card and other loyalty purchasing programs can provide food purchases by SKU. Other data sets such as medical data, FICO, social media consumption and utility records, when overlaid on top of each other, will provide even more insights as to what happens at that address.

With some fanfare, the Federal Reserve recently announced that U.S. household net worth reached $96.2 trillion at the end of 2Q17 and that the ratio of wealth to income was 670%. Notwithstanding that, economists at Merrill Lynch are worried about tepid consumer spending given that according to their estimates, for every dollar increase in household net worth, consumers only spent $0.02. Ten years ago, pre-Great Recession, total net worth was $68.2 trillion which suggests that a significant amount of the improvement was not cycled into the economy.

But to return to the question at the outset. The Bureau of Labor Statistics (BLS) is a treasure trove of data which gets closer to some answers. At the end of 2016, average household income was $59,039 which was an increase of 3.2% from 2015 (and 2015 was an increase of 5.2% from 2014 levels). But averages can be misleading: the 90th percentile had $170,000 of household income while the 10th percentile earned $13,600 – clearly underscoring the dramatic income inequality gap in this country. Interestingly, the top 20% took home 51% of total income. The U.S. poverty rate at the end of 2016 was 12.7% and represented 40.6 million Americans.

The 90th percentile spent 10.7% of its income on food while the 10th percentile spent 16.1% of its income on food; not terribly surprising given the relatively fixed cost nature of food. According to the USDA, the average middle aged male needs 2,600 calories per day while a female of comparable age requires 2,000 daily calories. Interestingly, if that same male only eats 1,861 calories, he will lose one pound per week. Fortunately, the BLS also breaks down the type of food each percentile purchases, which is where one begins to see some striking differences in the types of calories purchased. Consistently, across the 20 food categories tracked, more processed foods (sugars, fats, etc) were purchased by the 10th percentile than the 90th percentile (fats: 1.9% vs 1.3%, respectively) as a percent of overall household expenditures.

It is quite clear that inexpensive, more processed (relatively unhealthy) food is more readily available and accessible today. Arguably healthy, more expensive food will show great price elasticity; that is, increases in healthy food price will lead consumers to purchase less expensive unhealthier foods. Notably, the average U.S. household spent 9.7% of its annual income in 2016 on food and only 6.2% on healthcare (and 25.3% on housing). As important as the healthcare expenditures are, the “non-healthcare” categories play a material role in one’s health. Globally, the New England Journal of Medicine estimates that there are 700 million obese people, 108 million of which are children. That is, 10% of the world’s population has Body Mass Index (BMI) greater than 30 which is considered obese (dare you to click on that link…). The New York Times recently profiled a multinational processed food company which had developed a sophisticated door-to-door distribution network in Brazil and the resultant increased incidence of associated chronic diseases.

Last week PepsiCo announced 3Q17 results which showed a 3% decline in revenues and a 10% decrease in earnings, which the CFO attributed to efforts to diversify away from sugary drinks and their “multi-year journey to move to healthier products.” Just last week, Kellogg acquired the protein bar manufacturer Rixbar for $600 million to strengthen its healthy products business unit. So far in 2017, the CEOs of the five largest food companies have been replaced as the food industry struggles to find sustainable growth strategies.

Unfortunately, all of this brings back difficult childhood memories from when my friends wanted to get under my skin and chanted “Let’s get Mikey…he won’t eat it…he hates everything” (although I still very much like Life cereal).



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Spain is En Fuego…

When I arrived in Spain a few weeks ago the newspapers were bemoaning the extraordinary loss of global soccer star Neymar from Barcelona to Paris St.-Germain for a staggering $262 million transfer payment. Grown men were crying in the streets. A popular storefront in Ibiza captured the despair many felt, as they searched for meaning post-Neymar.

Ibiza 2017

Tragically, only days later, everyone was now crying in the streets after the horrific terrorist attacks in Barcelona. In addition to the obvious devastation, tourism is 14% of the Spanish economy and given problems elsewhere in European, Spaniards were expecting a bumper summer season of 38 million visitors.

Spain had been relatively insulated from Islamist terrorist attacks, although Barcelona which is in the Catalonia region of Spain has had a restive past with sporadic separatist violence. In three weeks, Catalonians are to vote in a referendum to determine if the region will separate from Spain. This action was just ruled unconstitutional by the Spanish Constitutional Court so expect continued unrest. Three years ago, Catalonia, the most economically powerful of the 17 administrative regions of Spain, held a non-binding referendum that saw 80% of voters pushing to leave Spain.

All of this turmoil belies what is an extraordinary story of economic recovery and a real resurgence of entrepreneurial activity over the past ten years. Gross Domestic Product (GDP) is expected to increase 3% in 2017, which is remarkable given how severe the situation was just a few years ago. The economy contracted 10% from the pre-Eurozone crisis levels of 2008; the unemployment rate was north of 26% and is now at 17%. The IBEX 35 index trades at 13.9x forward P/E, not an unreasonable level given that the Euro Stoxx index is at 14.8x.

This summer most European banks reported relatively stable financial results and appeared to finally be adequately capitalized. Non-performing loan balances at Spanish banks are estimated to be 5% which compares very favorably to their neighboring Portuguese banks which are running at 18%. This is all the more remarkable given the reputation for lax corporate governance, particularly at Spanish banks. The sixth largest bank by assets, Banco Popular Espanol, was sold this summer for 1 euro to Banco Santander SA when the true quality of its balance sheet was revealed, turned upside down by the disastrous level of inside deals with affiliates.

Arguably the harsh steps taken to address the crisis created by the credit-fueled construction boom were quite successful, notwithstanding the pain incurred. The dramatic reduction in government spending led to lower wage levels across the board which analysts attribute to why Madrid is 36% cheaper than London and 28% below Paris. Average Madrid rents are 345 euros per square meter now, which is well below the 504 euros rate in 2008.

This lower wage level had the effect of spurring a significant amount of entrepreneurial activity. Barcelona, which happens to be the location of Amazon’s European headquarters, recently developed 22@District, which is a 40-acre technology zone on the waterfront (no cars are allowed). Regularly we hear from interesting Spanish start-ups as they contemplate raising additional capital and/or expanding into the US market. For instance, Lug Healthcare Technology, a Spanish start-up providing technologies for hospital pharmacies, is deployed in five leading Spanish hospitals and is now looking to expand overseas.

The Spanish healthcare system has always been considered one of the best in the world and should continue to be a source of future healthcare innovation. The World Health Organization places women longevity at 85.5 years, second only to Japan. With a population of 46.5 million, the Spanish spend 9.3% of GDP on healthcare and enjoy universal coverage with no upfront payments and modest co-payments for pharmaceuticals based on an income test. Over 90% of the population uses the public health system, which is quite decentralized across the 17 regional health ministries. Some of the greatest health concerns are obesity at 15% of the population and something called “hazardous drinking” which 7% of men and 3% of women are guilty of.

The Spanish healthcare system was dramatically restructured as part of the General Health Law of 1986 which extended coverage and access to all. As healthcare costs accelerated over the following decade, the 1990s saw a greater focus on cost containment and management reform. This not surprisingly led to a tension in the 2000s between a more federalist approach versus a nationally coordinated system.

The impact of this increased commitment to national wellbeing was dramatic: vaccination rates were 80% in 1985 and are now well above 95%, leading Spain to be ranked fifth globally. The number of CT scanners and MRI machines per million residents was 14.4 and 9.2, respectively in 2008 according to the National Catalogue of Hospitals (last year of data), which compares impressively to other advanced European economies such as the United Kingdom which was 7.4 and 5.6, respectively. Today the central health minister is principally focused on four areas:

  • Chronic and rare disease management
  • National safety issues
  • Resource allocation to regions to endure uniformity and balanced care across the country
  • Nationalized IT system (single patient ID system, single EMR)

As a healthcare tech investor, the fourth priority is most interesting. In addition to a robust “health card” platform which allows access to all Spanish healthcare facilities, the analytics the system generates give administrators effective tools to combat unwarranted regional variability by procedure and outcomes. For instance, it was recently shown that there is up to 12x variability by region for avoidable hospitalizations due to diabetes complications.

Like many summer trips to Europe, one often needs to recuperate upon the return. At least in Ibiza, you can stay on east coast time, US east coast time.



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Dramatic Capital Inflows Continue in 2Q17…Trouble Ahead?

In an environment of microscopic interest rates, it is particularly interesting to read the Preqin 2Q17 Quarterly Update which exhaustively tracks all things private equity and venture capital. At the end of June 2017 there were 1,998 funds in market raising a total of $676 billion – a staggering sum – indicative of global investors desperately looking for alpha. Admittedly, Softbank’s $100 billion Vision Fund skews the data somewhat but at the beginning of 2017, there were 1,834 managers raising $525 billion which were already all-time highs.

In 2Q17 private equity funds raised nearly $121 billion across 206 funds; buyout funds accounted for $88 billion of the totals, which coincidentally was approximately how much was invested ($83 billion) in 1,001 buyout deals. This investment pace comfortably returns the private equity industry to levels not seen since the Great Recession nearly eight years ago.

Amidst of all the distractions swirling around the Russia Probe and “Repeal and Replace,” the venture capital industry also reported startlingly strong results for 2Q17. According to the National Venture Capital Association (in partnership with PitchBook) nearly $21.8 billion was invested in 1,958 companies across all sectors. When the first half of the year is annualized, the industry is on pace to invest over $75 billion in 7,750 companies and would mark the third year comfortably above $70 billion invested. Venture funds raised $11.4 billion in 2Q17 and may well be on pace to exceed 2016’s ten-year high of $41 billion raised. Indicative of the robust level of activity, round sizes and valuations remain somewhat elevated, while the “time to exit” also remain extended with average holding periods of just under six years for venture-backed companies.

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Much of this activity reflects the “unicorn” phenomenon which investors are anxiously watching play out. At the end of 2Q17, according to the Wall Street Journal’s “Billion Dollar Startup Club,” there were 167 unicorns. While 41 unicorns raised capital in 2Q17, only five could go public. As these companies chose to stay private longer, meaningfully larger round sizes are required which likely accounted for the nearly doubling of financings greater than $200 million in size as compared to 2016 levels. In many unfortunate cases, unicorns may not be choosing to stay private but rather are recognizing that IPO valuations are likely to be quite a bit below the last private round’s valuation. The very public failures of companies like Theranos and Jawbone, coupled with the disappointing IPO performance of Blue Apron and Snap, have reminded investors that the exit environment is as important as the early-stage financing environment.

And it may be issues around liquidity that rattled investor confidence among Silicon Valley VCs. The “Silicon Valley Venture Capitalist Confidence Index” (such an index actually exists – its a 5-point scale) dropped to 3.52 from 3.83 quarter-over-quarter, underscoring anxieties about lofty late-stage valuations, a disappointing exit market, and political uncertainty.

Not to be lost “below the fold,” so to speak, was the news reported by CB Insights and PricewaterhouseCoopers that in 2Q17 for the first time ever private Asian technology companies raised about the same amount as their U.S. brethren. To highlight how significant this convergence is, the U.S. venture market was over twice the size of Asia’s in 2016.

More specifically, the healthcare technology sector continued its run of impressive strength in 2Q17, in part as a reflection of the category’s maturity and that very substantial business needs exist across the entirety of the healthcare industry. Per Rock Health, $3.5 billion was invested in 188 companies year-to-date which rivals the annual totals of more than $4 billion in each of 2014, 2015 and 2016. The average size of financing was $18.7 million which is significantly greater than any prior period when round sizes never exceeded $15 million. Notably there have been seven companies that have raised more than $100 million in a 2017 financing, another high-water mark and indicative that many healthcare technology companies are scaling rapidly.

Additional evidence of strength in the U.S. healthcare sector was a recent report from Silicon Valley Bank which highlighted that venture investors had raised approximately $5 billion year-to-date, which is on pace to be one of the most robust VC fundraising years ever.

The political landscape remains uncertain at best. The potential cuts to both Medicaid and federal insurance cost subsidies could be profound with uncertain implications on IT budgets. Fortunately, the dysfunction all of us are watching painfully play out in DC has had so far a surprisingly muted impact on the healthcare technology sector. Analysts are encouraged by the new FDA Commissioner Gottlieb’s positions on regulatory front, and in particular, the early drafts of the “Digital Health Innovation Plan” appear strongly to endorse the continued movement to value-based models. Our core investment themes remain very much intact and perhaps are even more compelling in this environment.

But in light of the emerging political imperatives, there has been some rotation of the sub-categories within the healthcare technology sector. In recent years, the consumer health information, telemedicine and population health categories have given way to greater investor interest in consumer engagement, digital therapies and analytics. There does seem to be evidence that the “quantified self” phenomenon now is either fully penetrated and/or consumers have lost some interest as the wearables category has attracted significantly less capital in 2017.

One other indicator of sector strength is the geographic breadth of healthcare technology innovation. Important and relevant companies are being built in many cities which historically have not attracted significant venture capital. Rock Health estimates that year-to-date, 25 states have seen healthcare technology companies raise capital. Notwithstanding this breadth, certain states such as California, Massachusetts and New York continue to be particularly important hubs of innovation.


Essential to a compelling investment strategy is a robust exit environment. Limited liquidity options have been a concern across all sectors for venture capitalists the last few years. PitchBook recorded 348 exits of venture-backed companies year-to-date 2017, 58 of which Rock Health noted were healthcare technology companies (which disappointingly was behind the 87 exits in 1H16). One of the hallmarks of the healthcare technology sector is both the breadth and depth of the universe of acquirers from large established enterprise technology vendors, insurance companies, traditional business service providers to increasingly other strategic pharma and medical device companies.

Public markets have offered mixed signals as well. Notwithstanding that there have not been any healthcare technology IPOs this year, the Leerink healthcare technology/services public stock index has increased nearly 26% this year and up nearly 12% in 2Q17 alone. The average 2017 revenue and EBITDA trading multiple for this index at the end of 2Q17 was 4.3x and 14.7x, respectively. According to Leerink data demonstrated that this past quarter the payer sector traded much more favorably than the provider section – 20% versus 3%, respectively.

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