Intelligently transform, activate and unify healthcare data into one source of truth.
DISTRIBUTED ENTERPRISE DATA MANAGMENT
DeepHive is developing a next-generation distributed enterprise data management system that uniquely merges cloud and DLT with machine intelligence to connect healthcare data across the entire care continuum. Our architecture is designed to provide AI and data analytics applications with a faster, cheaper and more secure way of instantly accessing any type and amount of healthcare data. Our patented architecture improves data utilization, empowering healthcare delivery.
Healthcare data consists of unstructured and structured data. This data is often located in siloed databases and networks, reducing the ability to gain actionable clinical, operational, financial and regulatory insights. Proper data formatting, storing and processing is essential for AI and analytics applications to extract relevant information and deliver data-driven outcomes.
Data has low fidelity and is not formatted into a single HL7® FHIR® standard, making non-normalized data incompatible within a network.
Data is siloed in multiple storage systems in different locations and is not in a unified storage structure, making data inaccessible.
Interdepartmental data and workflows are not processed across the network, leading to poor performance and low data usage.
Applications cannot simultaneously process data in real-time amongst patients, payors and providers, significantly limiting decision-making.
Data is computed centrally and not processed in parallel locally on a distributed network, vastly increasing latency, workloads and costs.
Centralized cloud systems have a single point of failure and don’t have self-inclusive HIPAA compliance, increasing risks of a data breach.
Seamlessly connect unlimited amounts of fully encrypted healthcare data at memory speed from anywhere in the network.
Connects disparate datasets under a unified distributed system, enabling data utilization across the network.
Provides instantaneous access to unlimited amounts of data across entire network, improving decision-making.
Creates scalable economies for healthcare ecosystems, harnessing the growth in AI, analytics and big data.
Faster, cheaper and more secure than cloud and traditional DLT.
An Intelligent Distributed Data Management Network | Qeros Protocol-Layer
Reducing datasets into subsets of independent or constituent parts—optimizing security and storage.
INTELLIGENT MULTI-PARALLEL PROCESSING
Using MI to optimize the process in which transactions and data are updated—infinite scalability.
Partitioned digital ledgers to enable multi-parallel processing within each ledger—unlimited throughput.
Unified Distributed Network
One Source of Truth for All Data
Connects existing or new applications via a single point of access, API or SDK, to multiple distributed storage systems regardless of physical location. Avoid costly application-layer data management processes and eliminate the need to create duplicate data storage silos.
End to End Encryption
Data and transactions are cryptographically processed, prohibiting any centralized points of failure on the network. Proprietary architecture eliminates dependency on any public networks including AWS, Azure, Ethereum and IPFS, reducing global cyber-security risks and healthcare data breaches.
HIPAA Compliant Framework
Immutable Regulatory Compliance
Immutably store and transact healthcare data on our network in accordance with our proprietary HIPAA compliant governance structure and EDI (ASC) X12 data standards. Updateable, appendable and permanent data record for all users in the network, enhancing compliance and auditability.
Unified Language Translations
One Language for All Data Types
Translate any type of healthcare data, from file to object data and vice versa, utilizing a server-side API. Convert from a client-side interface to a HIPAA, HL7® FHIR® and CDA® compliant storage interface. Eliminating the need for costly replication of data management systems.
Unlimited Data Processing
Data on Demand at Network Capacity
Process unlimited amounts of healthcare data, including static and dynamic data. Data processing capacity only limited to hardware, bandwidth and network speed, making accurate and fully encrypted data instantly available across the entire distributed network.
Intelligent Transaction Processing
Intelligent processing of transactions and fractalized data, allowing more transactions to be processed at the same time. Transaction speeds in excess of 1,000,000 per second. Eliminate information delays amongst siloed data systems with information on demand, enabling synchronized decision-making.
Bi-Directional Data Interoperability
Interoperable Across Multiple Networks
Proprietary data bridges provide for multi-network and bidirectional data interoperability. Healthcare systems can share data with and gather data from disparate divisions, systems and networks, eliminating data isolability.
Empower AI and big data analytics applications—driving interventions and insights that improve healthcare delivery.
An Intelligent Identity Management Application | Application-Layer
INTELLIGENT DATA NORMALIZATION
Intelligently normalize and format disparate datasets utilizing various forms of MI and field mapping.
Providing access to one source of truth by unifying all healthcare data amongst disparate systems.
Unified On-Demand Data Formatting
One Format for All Data Types
Intelligently normalize any type of healthcare data on-demand into HL7® Fast Healthcare Interoperability Resources (FHIR®) and Clinical Document Architecture (CDA®) compliant data standards. Reformat any unstructured qualitative data or HL7 v2 (and higher) data, increasing usefulness of legacy data and enabling faster to time to value.
Making unlimited amounts of accurate and fully encrypted data instantly available across the entire network.
Reduce cyber security risk and healthcare data breaches through more secure HIPAA compliant network architectures.
Due to our architecture, transactions per second (TPS) are infinitely scalable with no upper bound limitation, enabling healthcare systems to make real-time data-backed decisions at scale.
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