Insight vs. Hindsight
Providing current and relevant information to decision-makers is a key requirement of Healthcare and Life Sciences systems. To ensure accurate data is available where and when you need it, a new class of software — the Big Data Fabric — has emerged.
Data fabrics complement traditional BI tools, closing the gap between business expectations and the challenges of Big and Fast Data by increasing agility and simplifying data preparation. They eliminate data latency that results in stale information and hind-sight analysis. Real-time Data Fabric™ from StreamScape takes your analytics to the next level, allowing data from anywhere to be captured, ingested and joined to other sources for deeper insight. Download the white paper to learn how real-time business intelligence can automate and improve the decision process in Healthcare and Life Sciences, creating greater business value. |
|
Providing current and relevant information to decision-makers is a key requirement of Healthcare and Life Sciences systems. To ensure accurate data is available where and when you need it, a new class of software — the AI Data Fabric — has emerged.
Data fabrics complement traditional BI tools, closing the gap between business expectations and the challenges of Big and Fast Data by increasing agility and simplifying data preparation. They eliminate data latency that results in stale information and hind-sight analysis. StreamScape Data Fabric™ takes your analytics to the next level, allowing data from anywhere to be captured, ingested and joined to other sources for deeper insight. Download the white paper to learn how real-time business intelligence can automate and improve the decision process in Healthcare and Life Sciences, creating greater business value. |
Real-time Data Fabric™ from StreamScape takes your analytics to the next level, allowing data from anywhere to be captured, ingested and joined to other sources for deeper insight. Download the white paper to learn how real-time business intelligence can automate and improve the decision process in Healthcare and Life Sciences, creating greater business value. This is a test tip..
Clinical Decision SupportHealthcare decision support applications often rely on Big and Fast Data collected from multiple EHRs — sprawling electronic healthcare datasets so large and complex they can't be processed using traditional data management tools. EHR data is overwhelming because of its volume, diversity of data types (variety) and speed (velocity) at which it moves through an organization.
Clinical decision systems can benifit from real-time analytics a big way, by helping identify and predict risk factors, cross-referencing medical conditions at Point of Care and matching patients with acute conditions to specialists and care units.
Use Cases
Evidence-Based MedicineEvidence-based medicine (EBM) optimizes clinical decision making through use of evidence from authoritative sources and properly conducted research. To ensures that a clinician's opinion is not limited by knowledge gaps or bias, EBM relies on knowledge and best practices from available scientific literature; combined with formal methods for evidence analysis. Results are often collected from numerous sources and shared with practitioners, medical students and policy makers. Use Cases
|
StreamScape's real-time data architecture simplfies EBM application development, allowing non-technical users to build knowledge graphs that identify and correlate information across multiple systems and formats. Models for classification of patient cohorts, historical time-series data from trial results and relevant documents can be easily integrated with real-time content to provide curated, contextual information for accurate decision making. Medical Devices and IoTThe internet of healthcare things has many applications that can benefit patients, families and physicians alike. IoT adoption is alredy under way. From simple monitoring of patient vitals to full-blown Telemedicine, the potential of healthcare IoT is huge. One major challenge to adoption of the new technology is management of the real-time data medical devices collect in a flexible and secure way. Another challenge is the ability of healthcare organizations to turn IoT data into meaningful insights. StreamScape enables healthcare IoT in many ways. MQTT or USB-attached medical devices can connect directly and stream sensor information into the data fabric, allowing business logic and rules for processing sensor data to be developed using familiar SQL-like syntax. Medical device data can be aggregated and processed using probabalistic analysis techniques to spot trends and anomalies in sensor data. Time-series data from medical devices can be visalized in real-time, matched to historical information, stored and analyzed on-the-fly to assist clinical decision making. Use Cases
Our Secret Sauce
StreamScape combines high performance, in-memory computing with stream analytics and data virtualization into a new, unique platform for Real-time Business Intelligence. Analyze and visualize vast amounts of structured and unstructured data in-flight, without loading it into a database or a specialized data store.
.. get started with
the Real-time Data Fabric™ today!
|