Set that disease data free! A call to break down those data silos.

[grow_thumb image=”https://telecareaware.com/wp-content/uploads/2015/03/BlueSiloCollapsing-41.jpg” thumb_width=”175″ /]Awash in a rising sea of data generated by devices and analytics–around treatments, population health, costs–there’s a struggle to make sense of it. We’ve noted the high value and merchandisability of 23andme‘s genomic data (gained by individual user consent) [TTA 5 Mar], but our healthcare institutions which should be codifying and sharing disease and treatment data, largely do not. Those with rare or ‘orphan’ diseases struggle to find information, diagnosis, fellow patients, treatments. They sometimes win breakthroughs by, believe it or not, blogging, and having their articles widely disseminated. Reasons why? According to David Shaywitz in Forbes, they are:

• Hospitals, even research based centers, struggle to codify their genotype and phenotype data of their patients in a meaningful way that would be usable for clinical decision making. We’ve also noted (oddly not Mr Shaywitz) the long implementation process of IBM Watson cognitive processing/decision making tools in healthcare, the concentration on single diseases and their spread into other industries plus third-party integration outside of healthcare [TTA 9 Oct 14]. 
• US patient privacy laws (e.g. HIPAA) which are strict and carry Federal penalties for violations.
• Data protection of the institutional sort: researchers not wanting to share, management very aware of their competitive stance in the healthcare marketplace for researchers, patients and doctors/doctor referrals and desiring to maximize their competitive advantage–a/k/a marketing differentiation.

His recommendation is that certain healthcare institutions would be founded on data collection and sharing–that any patient seeking care at these would consent to both sharing their data and benefiting from the shared data of others–in his term, a ‘data-inhaling clinic’ which would then share with other participating healthcare systems with that model. An alternative model is ‘federated datasets’ where the institution would keep its data but would open it to query engines could extract the limited data needed, no more or less. Data Silos: Healthcare’s Silent Shame