Saturday, 17 October 2015

The Medical Graph: Not Just An App: The Front End Of The Trillion-Dollar, Full-Stack Revolution

I've been thinking about this for some time, but conversations with Colin Simpson of Triscribe, Stephanie Zhan of Sequoia, Robert Leong of KallDoc and Vinod Khosla,  have made me come up with the concept of the Medical Graph as a dataset by analogy with Zuckerberg's concept of social graph.


So when you look at concepts like KallDoc what you are looking at is Not Just An App: it is in fact The Front End Of The Trillion-Dollar, Full-Stack Revolution the access point to patients at the point of primary healthcare delivery. The thin end of the wedge if you like.

As you remember, the social graph in the Internet context is a graph that depicts personal relations of internet users. In short, it is a social network, where the word graph has been taken from graph theory to emphasize that rigorous mathematical analysis will be applied as opposed to the relational representation in a social network.

The medical graph, by analogy would be a multidimensional graph (and more importantly the underlying data) depicting medical relationships not just of a single individual, but of groups, pathologies, treatments, outcomes etc and encompassing both deep personal data and epidemiological data. Again the word graph has been taken from graph theory to emphasize that rigorous mathematical analysis will be applied as opposed to traditional medical methodologies like case studies (which would be a single vector on such a graph).

Currently much of the information that would form the Medical Graph exists but is not connected such as current (2o15)  electronic medical records (EMR) as well as the corpus of medical literature and more global data such as the data derived in the Human Genome Project (HGP) and data sets such as the Icelandic Health Sector Database (HSD).

Ethically it is likely that "ownership" of personal data on the medical graph data will be primarily by the individual patient but to participate and benefit from shared sets patients will need to take part in sharing arrangement. Of course  interpretation of big data is a key part of the medical graph and the key value will be in the combination of algorithms, data and insights, as is always the case.

A number knowledgeable people have told me that the Medical Graph market is not big enough to excite their interest, much as I was told that downloadable music and video was too small a niche by a number of angels and VCs funds, but as before I beg to differ.

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