Healthcare Industry

Healthcare Industry Solutions

Medical Industry Image

Industry Background
Pain Points
Solutions
Strengths of Rapids Data Solutions
Value Realization
Technical Architechture

The healthcare sector has long been an early adopter of technological advances. Various sources of healthcare data may include hospital records, public healthcare information, medical records of patients, images of medical examination, clinical research results, etc. The vast data collected and saved in the healthcare systems requires proper management and analysis in order to derive important information to contribute to various medical applications, such as early detection of dangerous medical conditions, accurate disease diagnosis, medical imaging, customized treatment and patient care, biomedical research, drug creation and so forth.

Data Volume

The massive volume of data collected and stored by each individual healthcare provider poses a critical cost and performance issue for the IT department.

Data Variety

Healthcare data comes in different types. Legacy data systems do not have the capability to utilize the rich types of information to enhance the patient experience.

Data  Velocity

With the advancement of technologies, some of the healthcare data is not static. This requires a data system which can process both static batch-based data and streaming data.

Data Integration

Healthcare big data silos prevent personalized patient care and coordinated medical efforts.

01

RapidsDB as an MPP in-memory data warehouse provides the scalability and cost effectiveness of a data system in response to the ever-growing data volume of the healthcare industry.

02

RDP provides two healthcare data storage options based on different needs.

03

Rapids StreamDB as an in-memory and distributed stream database can continuously and steadily ingest and analyze streaming data.

04

Rapids Federation, the cross-origin federated real-time analytics connector system, can integrate different types of data across a wide variety of data sources without the need for ETL.

05

RDP supports standard ANSI SQL for data analysts or medical personnel to dive into large datasets.

06

RDP helps caregivers harness AI and machine learning for better healthcare workflow.

01

Provide a complete picture of the hospital-wide operational status for better-informed strategic planning.

02

Tackle rapidly increasing hospital data. Based on detailed and itemized data, calculation and presentation can both respond within seconds.

03

Operational units can all partially perform self-service analysis to meet the needs of medical exploration analysis.

04

Provide real-time alerting for instant care and quickly respond to new analytic needs.

05

Enhance patient management and knowledge sharing.

06

Intelligent search, efficient management knowledge accumulation.Provide intelligent search and management of a growing knowledge-base.

01

The distributed in-memory computing technology greatly improves equipment resource utilization for maximum performance, concurrency and availability. RDP empowers healthcare providers to offer the best patient experience at the lowest possible cost.

02

RDP’s in-memory data storage of MOXE can help doctors retrieve the information they need for patient visits or disease diagnosis in real time, while the self-contained Hadoop framework of RDP allows access to massive data storage for in-depth data mining.

03

Urgent medical queries can be responded within milliseconds. As healthcare data is closely linked to patient safety, the quality of data is extremely important. RDP enhances the completeness, integrity and consistency of data, giving healthcare providers more confidence to use the data.

04

With RDP’s cross-origin federated real-time analytics connector system, heterogenous data can be integrated and presented as a single and federated database to enhance health information integration and sharing.

05

The operational layer of RapidsDB can perform self-service based data search or analysis. The results will be sent to the presentation layer instantaneously for comprehensive reporting or rich data visualization.

06

RDP improves the efficiency of hospital and healthcare system while reducing the cost of care. It also allows clinical researches to be done efficiently with a more predictive approach rather than relying on trial-and-error.

Data layer

Integrates hospital’s different information systems, connects information islands and realizes data sharing.

Modeling layer

Establishes different models for different analytical scenarios.

Operational layer

Streamlines the hospital’s operating processes, and pushes the analysis results to the presentation layer.

Presentation layer

Presents analysis results with rich and comprehensible graphics.