• Real-time Decisionware for Healthcare + Life Sciences

    Real-time Decisionware

    for Healthcare + Life Sciences

    Real-time analytics extends traditional BI and offers a new way of processing data in-flight as it’s being created and changed, allowing organizations to observe and react to business events as they happen. Get instant insight into threats and opportunities without the need for ETL or a complex specialized data store.

    Automating the decision process across Life Science and Healthcare disciplines results in more thorough analysis, targeted diagnoses, better trial results and treatments, delivering higher quality care at lower costs and better overall patient outcomes.

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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.

  • REAL-TIME HEALTHCARE INTELLIGENCE CAN IMPROVE PATIENT OUTCOMES, LOWER COSTS, AND SAVE LIVES BY ENABLING PREVENTATIVE ACTIONS 

    REAL-TIME HEALTHCARE INTELLIGENCE
    CAN IMPROVE PATIENT OUTCOMES, LOWER COSTS, AND SAVE LIVES BY ENABLING PREVENTATIVE ACTIONS
     

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Clinical Decision Support

Healthcare decision support applications often rely on Big and Fast Data collected from multiple EHRssprawling 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.



But healthcare organizations have long strugged with cost containment and data integration, resulting is sub-optimal patient outcomes. StreamScape eliminates complexity and makes decision support automation affordable.

  Use Cases  

  • Enable active engagement with patients, pharmacies and physicians
  • Analyze and correlate patient characteristics to predict care outcomes
    and identify the most effective treatments
  • Optimize care facility resource allocation and provide a 360 patient view
  • Capture changes across care management systems for coordinated,
    collaborative care
  • React to adverse incidents or claims as they are reported to reduce
    fraud, waste and abuse


Evidence-Based Medicine

Evidence-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  

  • Combining and analyzing structured and unstructured data from
    EMRs, clinical research and genomic data to match treatments
    with outcomes and predict patient risk
  • Compare patient profiles for predictive modeling and segmentation
  • Using historical data to personalize care by estimating outcomes,
    such as elective surgery
  • Collection, ranking and publishing of innovative treatment procedures
    and adverse effects to determine best value and outcomes
  • Integration and curation of public data to identify population
    risk and threats


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 IoT

The 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  

  • Monitoring of medical devices and warables to capture and analyze sensor
    data in real-time
  • Correlate patient characteristics to predict care outcomes and identify
    the most effective treatments
  • Remote monitoring of patient adherence to drug and treatment regimens
    to detect active risk contitions
  • Advanced telemedicine for ICU and triage engagement, allowing clinicians
    to predict acute medical events

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. 

Easily capture data changes at the source and blend traditional BI with stream analysis techniques; allowing information from Payees, Admittance, ICU, Claims and other authoritative sources to be modeled and aggregated on-demand. Our real-time decisionware reduces data sprawl and data drift, eliminating the people and process bottleneck of ETL-centric solutions.

Unlike traditional BI applications, StreamScape can react to data changes and push computation results directly to mobile devices and client applications, using web streaming technologies, Kafka or Instant Messaging; eliminating the hassle of multi-application security or the need for single sign-on. Data arrives where you need it, when you need it.

.. get started with 
the Real-time Data Fabric™ today!

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