A Window into the Incoming Gush of Data: Healthcare in Pittsburgh

I really enjoyed this piece, by Barb Darrow, about the development of healthcare-related data management at the University Pittsburgh Medical Center (UPMC) for a number of reasons.  First of all, as the article explains, UPMC is a leader in the area and is doing some really interesting things!  Secondly, I always enjoy a good story about the economy of Pittsburgh, since it represents one of the best cases (the best case?) of transforming a US rust belt city into a 21st century City (Health care and robotics are among the key fields relevant to that success.).  Finally, and most significantly, the issues raised in the article demonstrate that mastering new levels of data management do not lead to ease and simplicity but rather, to even greater opportunities and challenges.

In the case, of UPMC, getting a head start on developing Electronic Medical Records has led, first of all, to the challenge of coordinating  independent systems across specialties.  Being able to manage enormous amounts of granular data, and to understand how to deploy that data, is one of the frontiers beyond the systems coordination step:

Doctors now try to take a more holistic view of their patients, and that requires the ability to pull together data from different sources. Imaging data is separate from surgery notes, which is separate from pharmacy data.

“If we look at big data, the idea is how to interconnect multiple points of data across the broad, biological continuum,” Shrestha said. “If the patient is diabetic, you don’t just see an endocrinologist looking at the liver in terms of liver function tests or any scans but across the biological spectrum of organs and then down to a cellular level. We look at pathology slides, reports on molecular imaging and down to the genomic levels.”

Darrow explains that data can be broken down into three buckets: imaging data, which accounts for close to 50% of UPMC’s digital information; databases, which account for about 10%; and unstructured information, such as “postoperative notes, radiology reports, discharge summaries,” which accounts for the remaining 40%.  The piece goes on to describe some of the specific technologies that are being used to address these various categories and concludes by pointing to another, even further frontier: the integrated management of pathology reports.

Big data, as the article in which I found the above reference would argue, is here to stay.  The more we know, the more we that will become knowable.  Personally, I find the challenge daunting

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AIDS Research Progress through Online Gaming

Perhaps you’ve already this exciting news:

Over a three-week period, gamers playing Foldit, an online protein-folding game, helped to map out the structure of an enzyme that could be used to help fight HIV and AIDS.

What the gamers were able to accomplish in unlocking the structure of a protein called M-PMV was something that scientists, engineers and automated computer programs haven’t been to pull off in about a decade’s worth of attempts, according to a study published in the journal Nature Structural & Molecular Biology.

This online game, which I’ve referenced several times before, provides a prime example of the open source phenomenon spreading beyond software programming.  It’s interesting to consider why scientific discovery might provide a ripe field for such collaboration.  I’ve yet to see examples as successful in areas such as government, supply chain planning, or other areas of personal interest.  Here’s to hoping that we do see such examples, and in short order.

Collaborative Drug Discovery, Revisited

“Failure is free” today, claims Clay Shirky in Here Comes Everybody. A recent e-mail I received demonstrated how this reality is being put to use in the pharmaceutical industry.  Collaborative Drug Discovery (CDD), about which I’ve written before, offers cash to pharmaceutical researchers willing to share “compounds they have synthesized but are no longer actively pursuing.”  Incidentally, of course, the pharmaceutical industry is having trouble innovating at the same rate as it had been accustomed to.

Here’s most of the text of the e-mail:

Collaborative Drug Discovery (CDD) would like to share with our users an opportunity to take advantage of the compounds they have synthesized but are no longer actively pursuing.

By uploading the structures of these compounds at InnoCentive’s Novel Molecule Pavilion your compounds will be considered for purchase by their Seekers for screening in their Seekers’ assays.

Alternatively, submit your compounds to Innocentive using your CDD Vault. Sign up here and we will facilitate passing the data on to InnoCentive.

Initial awards range from $100-1,000 per compound, while coming up as a hit in a Seeker’s assay could be far more valuable.  Please forward any questions to Christian Stevenson (cstevenson@innocentive.com).

Thanks, and best of luck in the lab! – Sylvia

Sylvia Ernst, Ph.D.

Sr. Director, Community Growth

Crowd-sourced Radiation Data from Japan

Here’s a link to the live map (map below is static).

And here’s an interesting piece (from The Atlantic) on the subject.  Key quote:

“It’s one thing to blindly trust the experts. It’s quite another to doublecheck them with a distributed network of 215 Geiger counters — forcing them to earn that trust.”

And this blogger and “Information Visualization enthusiast” wonders if

“grassroots projects like geigercrowd and pachube make progress in closing the data gap [of unreported values].” [brackets mine]

An interesting example of a traditional government function being taken over (in some measure) by the crowd.

EHR’s and Cloud Computing

From February, but still worth noting:

ONC [The Deparment of Health and Human Services’ Office of the National Coordinator for Health Information Technology] is creating a network of Regional Extension Centers (REC) that will provide regionalized support to medical providers for the selection and implementation of an EHR . . . To track, manage and report on this critical effort, Acumen Solutions will implement a cloud computing CRM and Project Management solution from Salesforce.com that will be used nationally across all Regional Extension Centers. This solution will provide the REC’s with the ability to manage all interactions with medical providers related to their selection and implementation of an EHR solution. [from the website of vendor Acumen Solutions.]

R&D Collaboration in Pharma

A cool site (by Collaborative Drug Discovery, or CDD) that allows researchers to collaborate in drug discovery.

There are three levels of information sharing available:

  • “Vault”:  provides for private storage of a group’s information
  • “Collaborate”: provides for selective sharing of information with selected partners
  • “Public”: self-explanatory

I recently spoke with a top theorist in the pharma industry.  He suggested that the “black-white continuum between sharing all data and sharing no data” is archaic and that a new model is needed for a world in which innovation has decelerated and in which multiple companies are working on similar therapies.  CDD may provide part of the answer to this challenge.

Gvt Rules in EHR Implementation

From the EMR and HIPAA Blog, a concise example of how stimulus money for EHR’s can lead to inefficiencies in electronic investment:

. . . the stage 1 meaningful use criteria really focuses on EMR’s having the ability to share patient information, but doesn’t actually require them to share information. In stage 2 and stage 3, my understanding is that the requirements to start sharing this clinical information will be a major part of the criteria.

. . .  let’s imagine a clinical office spends more than they should on a certified EHR and show stage 1 meaningful use. No doubt they spent a fair amount of time dealing with the reporting requirements of stage 1 meaningful use. As with any EMR implementation they made a lot of changes in their office and for the most part their [sic] satisfied with getting the EMR stimulus money the first year.

Well, stage 2 meaningful use rolls in and now they’re required to start sending their patient data to some state designated HIE [Health Information Exchange] (or other similar entity). What’s going to happen if their state doesn’t have an HIE where they can send the data? Or what if you’re from a small state like Delaware or Montana (small in people) and your EMR vendor decides that they’re not going to build the features required for you to interact with your state EMR?

The example is not surprising but it’s always a good idea to keep track of how the massive funds that can kick-start an industry will inevitably lead to distortions.