- 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