Analyze Your Data at the Cellular Level
Data is the lifeblood flowing through every business. The ever-increasing growth and velocity of data in healthcare is astounding.
Whether you’re a healthcare payer or provider, modern data analytics can come to your aid. These tools help you intelligently manage the health of populations, improve quality of care, increase financial efficiency and operational effectiveness, conduct innovative research, and satisfy regulatory requirements.
Discover Insights from Data
As a healthcare leader, you want to improve the efficiency and effectiveness of care delivery. Transforming your data into valuable insights will influence decisions that affect patient and member care.
These decisions require clear, consistent, and trusted data and analytics. We enable you to collect analytics for:
- Population health analysis (risk management, quality of care, registry analysis)
- Regulatory reporting (HEDIS, Stars, P4P, ACO, etc.)
- Contract management (payer scorecards, contract performance, etc.)
- Managed care and leakage analysis
- Disease prevalence, disease management, and gaps in care
- Service line and utilization reporting
- Labor productivity (nursing hours, RVUs, etc.)
- Claim denials reporting
Use Essential Tools to Modernize Your Data
Rapid change requires growing capabilities across your organization. Cloud technologies, modern data architectures, advanced analytics, and data catalogs are key for data modernization. With these tools, you can provide appropriate access, visibility, understanding, and trust in your data.
Data modernization also sets the stage to adopt artificial intelligence (AI), machine learning, and other advanced technologies. The benefit? You unleash valuable insight for delivering and managing care that’s more efficient and effective.
Create Your Enterprise Data Roadmap
Unlocking your data’s full potential requires a pragmatic, flexible plan. You must understand where you are, where you want to be, and how to get there. An enterprise data roadmap is key to making sure the journey is successful.
Your roadmap needs to include people, processes, and technology as the framework creating a world-class data environment.
Solve Problems and Boost Opportunities With Data Analytics
Solving healthcare’s biggest challenges is possible when you put data to work. The scale and types of information available today far exceeds what was out there a few years ago.
Combining structured data from traditional healthcare EMR/EHRs with unstructured data from medical device logs, diagnostic imaging systems, and other sources creates significant opportunities. You can increase quality of care, improve patient and member engagement, and decrease overall associated costs.
Empower Your Decision-Making With Data Governance
Your success with advanced analytics, AI, and machine learning requires significant attention to data consistency and quality. Trusted data stems from a high-functioning data governance program. When building this program, you need appropriate business-friendly tools, processes, and policies to enable that trust and understanding.
With trusted data, you can make great progress with bedside AI and analytics-assisted care to power decision-making.
Build a Solid Foundation With Master Data Management
Master data is the cement that bonds your data foundation. Your organization may face master data challenges as you work through ongoing consolidation while adding a flood of data from new sources.
Some organizations have moved towards an enterprise view and catalogs, which contain true master data for patients, providers, or members. But, they also want to master reference data (diagnosis, lab, medication codes, and others) that are equally important to providing consistent information and meaning across the organization.
Unlock Your Data’s Full Potential With Us
We offer a suite of solutions that will help as you pursue data modernization and analytics, including:
Healthcare Data Modernization Workshop
- Identify opportunities for modernization
- Determine which opportunities offer maximum value, with consideration for cost and complexity
- Understand current readiness and next steps
Cognitive Health Workshop
- Rapidly iterate the application of AI in your organization
- Define measureable goals for your cognitive analytics implementation
AI Innovation Lab for Healthcare
- Discover possible cognitive analytics use cases within and for your organization
- Rapidly prototype and illustrate the art of the possible
- Determine next steps
Comprehensive Data Analytics Program and Platform Implementation Services
- Understand and inform your vision
- Create the roadmap to grow capabilities across people, processes, and technologies – all mapped to clinical, operational, and business value
- Define, design, and implement the architecture, technology, data structures, data pipelines, metadata, data/business glossaries, and master/reference data
- Create the analytics and reporting layer, APIs, and sandboxes, which puts your data to use in support of your business and clinical processes
- Enable and grow capabilities to use, manage, and operate the platform and program over time
Data Analytics Services
- Extract, integrate, and normalize data from and with EMR/EHRs (Epic, Cerner, etc.) and other healthcare-specific systems
- Create data lakes, data warehouses, data pipelines, and APIs
- Build master and reference data management
- Develop business and metadata glossaries and frameworks
- Create data analytics dashboards, visualizations, and advanced analytics
- Strategize and build cognitive AI and ML solutions and projects
- Develop data governance methodology and support its implementation
We understand the importance of achieving your goals cost effectively and efficiently. When and where it makes sense for your organization, we use proven accelerators and automation techniques.
We’ve developed a number of healthcare data integration and management accelerators, fine-tuning them in real-world projects. These accelerators enable operational success and program growth over time and include:
- Data integration designs
- Data mapping
- Metadata and operational frameworks