HSBlox is an Atlanta-based team of healthcare and financial technology professionals. Leveraging our experience in healthcare, fin tech, and digital supply chain management, we are delivering solutions for the healthcare ecosystem.
Our solutions address value-based reimbursement and population health, patient-permissioned data, and machine-learning approaches to analytics.
These programs require melding of structured and unstructured data, integration with multiple providers across the continuum of care, and permissioned disclosure of healthcare data. Initiatives in this space are underserved by existing business processes, technical infrastructure, and legacy systems. HSBlox has developed solutions to these challenges using distributed ledger technology (aka “blockchain”) and machine-learning approaches.
Patient needs are not being addressed with respect to personal medical records and control of patient data. In today’s environment, mobile applications are tied to a specific insurer, provider, or vendor. Additionally, patient medical data is distributed across multiple practice management and EMR systems. Patient integration and consent management are foundational to HSBlox solutionsl
The healthcare system possesses an immense amount of rich, yet disparate data. Analyzing this data can be overwhelming—and more data isn’t better data. Applying our experiences in other industries, HSBlox is deploying its integration tools and machine-learning algorithms to aggregate, analyze, and report on data with unprecedented accuracy and insight. HSBlox’s analytic solutions are a leading-edge example of our approach to healthcare data analysis.
Existing logistics and chain of custody processes lack integration, visibility and interoperability amongst systems and stakeholders, and are susceptible to losses and delays. HSBlox solutions use DLT technology to track and trace products and samples through clinical trials, supply chains and distribution networks while providing stakeholders and trading partners with precise and real time data.