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Tag: Recon Strategy

An Ad Page In the NEJM and the Future of Cancer Care

I am not sure how many docs still do this, but I still read the actual hard copy of my New England Journal of Medicine, and that means I flip past ad pages with smiling grandfathers playing with grandchildren thanks to supercalifragilistic products on my way to scholarly papers with tables and figures. But this time, I stopped in puzzlement when I came across an ad from Intermountain.

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Intermountain is a health system based in Utah, highly respected for its sound approach to quality and cost control[1], but not broadly well known for cancer care in the way of centers like Dana Farber or Sloan Kettering. Digging further by going to the website uncovers the actual offering which is a streamlined 5 step process:

  1. Send tumor sample
  2. Deep sequencing of 96 key cancer genes
  3. Genomic data analysis
  4. Tumor board makes a treatment recommendation
  5. Facilitated procurement of the relevant cancer drugs

Turn-around time is about two weeks, fast enough to wait for the information before starting a regimen.

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What The Emergence of an EMR Giant Means For the Future of Healthcare Innovation

(Note: the following commentary was co-authored with Tory Wolff, a founding partner of Recon Strategy, a healthcare strategy consulting firm in Boston; Tory and I gratefully acknowledge the insightful feedback provided by Jay Chyung of Recon Strategy.)

Medicine has been notoriously slow to embrace the electronic medical record (EMR), but, spurred by tax incentives and the prospect of cost and outcomes accountability, the use of electronic medical records (EMRs) is finally catching on.

There are a large number of EMR vendors, who offer systems that are either the traditional client server model (where the medical center hosts the system) or a product which can be delivered via Software as a Service (SaaS) architecture, similar to what salesforce.com did for customer relationship management (CRM).

Historically, the lack of extensive standards have allowed hospital idiosyncrasies to be hard-coded into systems.  Any one company’s EMR system isn’t particularly compatible with the EMR system from another company, resulting in – or, more fairly, perpetuating – the Tower of Babel that effectively exists as medical practices often lack the ability to share basic information easily with one another.

There’s widespread recognition that information exchange must improve – the challenge is how to get there.

One much-discussed approach are health information exchanges (HIE’s), defined by the Department of Health and Human Services as “Efforts to rapidly build capacity for exchanging health information across the health care system both within and across states.”

With some public funding and local contributions, public HIE’s can point to some successes (the Indiana Health Information Exchange, IHIE, is a leading example, as described here).  The Direct Project – a national effort to coordinate health information exchange spearheaded by the Office of the National Coordinator for Health IT – also seems to be making progress.  But the public HIEs are a long way from providing robust, rich and sustainable data exchange.

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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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