Data Operating System
Health Catalyst Data Operating System (tm) is Health Catalyst’s response to a simple truth: The future of healthcare will be centered around the broad and more effective use of data.
From population health management to value-based care, healthcare providers face a quagmire of reimbursement schemes and quality initiatives, each requiring precise analysis of clinical, financial and patient data. Yet to get there they must unravel a Gordian knot of diverse information systems that cannot communicate with each other and that separately lack the data needed to succeed. The explosion of information from wearables, mobile phones, genomics and other sources outside the traditional healthcare sphere is exacerbating these problems while also enabling personalized healthcare and management as never before, assuming organizations can manage the transformation.
DOS is a vendor-agnostic digital backbone for healthcare. For the first time, organizations using DOS will be able to populate workflow information systems with critical point-of-decision insights, significantly increasing the value of the EHR to care providers.
Seven attributes of the Data Operating System:
- Reusable clinical and business logic: Registries, value sets, and other data logic lies on top of the raw data and can be accessed, reused, and updated through open APIs, enabling third-party application development.
- Streaming data: Near or real-time data streaming from the source all the way to the expression of that data through the DOS, supporting both transaction-level exchange of data and analytic processing.
- Integrates structured and unstructured data: Integrates text and structured data in the same environment. Eventually, incorporates images, too.
- EHR Integration (closed loop capability): The methods for expressing the knowledge in the DOS include the ability to deliver that knowledge at the point of decision-making, including back into the workflow of source systems, such as an EHR.
- Microservices architecture: In addition to abstracted data logic, open microservices APIs exist for DOS operations such as authorization, identity management, data pipeline management, and software application telemetry. These microservices are built specifically to enable third-party applications to be built on the DOS.
- Machine Learning: The DOS natively runs machine learning models and enables rapid development and utilization of these models, embedded in all applications.
- Agnostic data lake: Some or all of the DOS can be deployed over the top of any healthcare data lake. The reusable forms of logic must support different computation engines (e.g., SQL, Spark SQL, SQL on Hadoop, et al.).