In healthcare, data is delivering life-saving results with predictive capabilities that can address preventable outcomes. The intelligence guiding these initiatives relies on timely data delivery to applications and reviewers. This may involve complex, high velocity data forms with the expectation of reaching users in a state that is analytics-ready.
However, when data delivery fails, patients receive poor outcomes. Which is why modern, data-driven healthcare companies need to ensure their data pipelines can deliver for the business and it’s customers. To ensure these types of results, you need to bring an operations mindset to your data flows; We call that DataOps.
A DataOps Platform allows you to move data between any source and destination and automatically scale data flows. You can create collaborative designs and deploy data flows with full visibility and smart recommendations to solve common pipeline issues including data availability and accuracy. In healthcare, where data privacy is paramount, you can provide common-sense, self-service data access without sacrificing data protection.
A Changing Industry
In the healthcare industry, things are changing all the time. Healthcare companies want to have a full 360-degree picture of a patient’s health but often times that information spans systems and is silo’d in separate locations. Disparate data and semantics makes it complex to combine enterprise data and retain data quality. As data volumes increase and sources grow in number and provenance, a phenomenon called data drift complicates having a single source of truth for patient data.
Additionally, edge processing and IOT open up possibilities to connect devices and derive intelligence. However, as data begins to flow from many sources, data operations can become complex. Traditionally, instrumented devices produce noisy data that needs to be organized and transformed before it is useful. The ability to manage data from IOT sensors is a practice that can often require refinement and developmental agility.
StreamSets In Healthcare
Today, StreamSets counts 4 of the top 20 healthcare companies as their customers with countless healthcare companies using StreamSets open-source offerings. The reason that companies choose StreamSets is simple. They need a modern DataOps platform that can help them manage data flow topologies and deliver reliable, analytics-ready data to internal stakeholders. They need a solution that handles data drift, and prevents data pipelines from breaking when changes in systems and semantics are present. They also need to ensure that patient data is protected, at the destination as well as in motion.
Ensuring that you have an agile data flow technology that can connect directly with popular data platforms and tools that provide easy operation to a wider audience is providing healthcare companies with a new level of business value and is producing positive and life saving patient outcomes.
Availity is a healthcare solutions provider whose platform helps nationwide health plans and providers share administrative, clinical, and financial information with each other in real-time. Increased interaction and collaboration between healthcare stakeholders results in better care and outcomes for patients, and optimized financial performance for Availity clients. Availity needed a platform that provided an economic way to move, store, and analyze hundreds of terabytes (TB) of data while providing leading and innovative solutions. Availity built a real-time data repository and is delivering on the strategy to increase value while lowering costs. By offering a self-service data repository, the company will be able to innovate faster. Availity expects customer satisfaction to rise as a direct result of deeper insights delivered faster and with greater reliability.
GlaxoSmithKline is a pharmaceutical company that began an overhaul transformation of its R&D data and analytics infrastructure. Creating a new drug can take anywhere from 8 years to 20 years for a pharmaceutical company. GSK wanted to make that new drug discovery and development timeline shorter but needed to break down the data-flow barriers among the companies many siloed operations. GSK focused on bringing that siloed data together into a primary data and information platform where users across the enterprise can consume all the data in different ways. The goal is to shorten drug trials to 2 years with an agile analytics practice. GSK hasn’t achieved 2-year drug development yet, but the data and analytics platform environment has brought the company closer to realizing that goal.
StreamSets is helping healthcare companies leverage the data they need to realize business value from a growing list of strategic use cases. By providing a platform that intelligently handles the eminent evolution of data systems and practices, monitors and reports on data pipeline operations, and removes barriers from leveraging complex data types healthcare companies can build groundbreaking functionality that impacts the health and well-being of our society.