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The UPMC-Highmark Brawl Spills Into Philadelphia’s Backyard

The UPMC/Highmark rivalry continues to open new fronts in Pennsylvania. Highmark’s response to UPMC is differentiated in two ways: first, Highmark is using a coalition-building strategy and, second, it is controlling its exposure to big in-patient assets; in contrast, UPMC is building an integrated, single-brand system and happily taking over hospitals (and building more) along the way. When UPMC and Highmark make major investments in a region, local systems will be caught in the capex arms and feel the pressure to affiliate. Credibly threatening to respond in kind may defuse the arms race. But unaffiliated systems may struggle to find partners willing to bankroll a battle with both Highmark and UPMC, leaving no option for unaligned systems than to pick sides. Philadelphia systems – so far largely neutral to Highmark vs. UPMC – should be able to stay neutral as the fight develops in their western backyard. If the battle moves into northeastern Pennsylvania or jumps into south Jersey, however, the Philadelphia systems will have to develop a response.

The competitive rivalry between Highmark and UPMC is truly epic. Long ago – when Highmark largely focused on insurance and UPMC largely focused on care delivery — they were good partners in the Pittsburgh market. But as each has become more vertically integrated – with Highmark acquiring the West Penn Allegheny system and UPMC’s health plan buisness growing – they have since become bitter rivals. The competition has expanded out of Western Pennsylvania and into the rest of the state. 

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2012 Digital Health Investment Activity: The View From the Valley

Rock Health recently released a decidedly mixed report on the current state of Digital Health investing, as the data suggest many investors continue to tentatively explore the sector, but most have yet to make a serious commitment.

Overall, VC funding for digital health increased significantly over the past year, from just under $1B in 2011 to about $1.4B in 2012; 20% of this total was associated with just five deals: two raises for transparency companies, Castlight (targeting employees with high deductible plans looking to manage their costs) and GoHealth (targeting consumers contemplating purchase of health insurance); two raises for referral companies, Care.com (helps consumers find the right caregiver – defined broadly, as needs addressed include eldercare, child tutoring, babysitting, and pet care) and BestDoctors (helps employees find the right doctor), and one deal for 23andMe (a pioneering consumer genetics company).

Not surprisingly, the largest thematic area of investment ($237M) was “health consumer engagement,” comprised of companies that – like the first four above – help consumers or employees with healthcare purchases.   “Personal health tools and tracking,” the second leading category, captured $143M in funding last year.  “EMR/EHR” ($108M) and “hospital administration” ($78M) rounded out the list; the last two numbers seem shockingly low given the apparent size of these markets, and suggest both areas may be perceived as  firmly owned by incumbent players, and prohibitively difficult for new participants to enter.

Athenahealth’s just-announced acquisition of Epocrates highlights the competitive pressures even existing EMR companies face as they struggle for traction in an environment that seems to be increasingly dominated by a few large players, most notably Epic. “Our biggest obstacle,” Athenahealth CEO Jonathan Bush told Bloomberg Businessweek, “is that 70% of doctors don’t even know we exist.”  In contrast, I’ve suggested that a category I’d broadly define as EMR adjacencies may be primed for growth, as VC’s Stephen Kraus and Ambar Bhattacharyya have also discussed recently in this intelligent post.  The related area of care transitions is also attracting considerable entrepreneurial interest, including current Rock Health portfolio companies WellFrame and OpenPlacement, and TechStars alum Careport; it remains to be seen whether a robust business model will emerge here.

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Why Getting to a Digital Health Care System Is Going to Be Harder Than We Thought Ten Years Ago

A leading scientist once claimed that, with the relevant data and a large enough computer, he could “compute the organism” – meaning completely describe its anatomy, physiology, and behavior. Another legendary researcher asserted that, following capture of the relevant data, “we will know what it is to be human.” The breathless excitement of Sydney Brenner and Walter Gilbert —voiced more than a decade ago and captured by the skeptical Harvard geneticist Richard Lewontin [1]– was sparked by the sequencing of the human genome. Its echoes can be heard in the bold promises made for digital health today.

The human genome project, while an extraordinary technological accomplishment, has not translated easily into improved medicine nor unleashed a torrent of new cures. Perhaps the most successful “genomics” company, Millennium Pharmaceuticals, achieved lasting success not by virtue of the molecular cures they organically discovered, but by the more traditional pipeline they shrewdly acquired (notably via the purchase of LeukoSite, which ultimately yielded Campath and Velcade).

The enduring lesson of the genomics frenzy was succinctly captured by Brown and Goldstein, when they observed, “a gene sequence is not a drug.”

Flash forward to today: technologists, investors, providers, and policy makers all exalt the potential of digital health [2]. Like genomics, the big idea – or leap of faith — is that through the more complete collection and analysis of data, we’ll be able to essentially “compute” healthcare – to the point, some envision, where computers will become the care providers, and doctors will at best be customer service personnel, like the attendants at PepBoys, interfacing with libraries of software driven algorithms.

A measure of humility is in order. Just as a gene sequence is not a drug, information is not a cure. Getting there will take patience, persistence, money and aligned interests. The most successful innovators in digital health will see the promise of the technology, but also accept, embrace, and ideally leverage the ambiguity of disease, the variability of patients, and the complexities of clinical care.
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