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Cross organizational data for Precessioned health analytics

Satyanarayana Vantipalli

Satyanarayana Vantipalli

Co Founder

To improve the trust and reduce the barriers in the pervasive use of clinical data analytics requires cross Organizational data sharing infrastructure to collect trusted, authenticated health information. The collected data should be patient-centric, historically consolidated clinical data. while exchanging cross organizational patient centric clinical data, more than 80% of the data is unstructured or Semistructured like out patient SOAP notes, discharge summaries, radiology notes and consultant notes etc.

To intervene hidden insights from this unstructured data needs deep domain clinical artificial intelligence technology to convert unstructured data to Structured data. The converted structured data can be leveraged for precisioned clinical analytics to get more substantial improvement in sophisticated quality metrics and hidden insights drawn from the ecosystem of inter connected digital health systems

The major challenges of dealing with the healthcare data is of its sensitive nature and maintaining the privacy, security and ownership is paramount concern.

At the same time ever changing healthcare reforms demanding for value based care rather than volume of care. Today’s care coordination organizations like ACO’s and other healthcare delivery centres faces several challenges in delivering continuum of care.

To provide continuum of care for care coordination, patient centric health information needs to be exchanged between the organizations to eliminate the duplication of services and enabling personalized care. There are several challenges while exchanging the health information across the organizations like

  1. Information may be lost during hand off and take over
  2. Information may be modified or wrongly routed
  3. Exchanged information may not be portable.

Currently, healthcare data split among different entities with different formats in different locations. Patient centric precession analytics requires bundles of cross organizational patient centric data needs to be collected aggregated and purified and transformed to fit into analytical models. To perform precissioned clinical analytics and predictive modelling for the given cohort of disease requires many of such patient centric cross organizational data bundles.

aciana developed private and permissioned blockchain health information exchange products and solutions for cross organizational health information exchange and healthcare interoperability. aciana’s advanced clinical NLP solutions extracts hidden information from the unstructured clinical notes and converts structured  information. aciana’s deep domain artificial intelligence and analytical solutions leverages these structured information to do precisioned analytics.

aciana integrated blockchain-Artificial intelligence-Big data-Products and Solutions helps to securely exchange cross organizational data and performs deep domain clinical, financial and administrative analytics.