Healthcare Data Analytics & Warehousing

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Patient outcomes are improved when providers and researchers have access to the latest analytics capabilities and tools in conjunction with consolidated, accurate, and verified information. Providing healthcare professionals with the right tools enhances prevention and the ability to diagnose diseases and find new treatments.

Create a window into your data and utilize tools that provide real-time insight. Leverage technology that drives research.

Saga's diverse team with a wide range of experience across the industry provides the knowledge and skill set to solve challenges where other teams fall short. We enjoy the challenges of large scale scale projects, big data and complex data sets. Our effectiveness with data modeling, design and implementation will not only drive your project but can make a real difference in healthcare.

Data Visualization: Your ability to 'see data' facilitates deeper understanding.

Report Writing, Analytics & Visualization

Saga report writers and SQL developers work closely with report consumers and stakeholders, gathering requirements to create or modify existing reports. Our data analysts and engineers are highly skilled writers of SQL queries and EMR products. Our experience with data modeling and visualization will streamline your business processes. Some of the products we support:
Saga's database administration (DBA) team has experience across a wide range of databases including relational, flat file and NoSQL. We provide performance tuning, query troubleshooting and analysis, and backup/disaster recovery strategies.
  • Relational Databases: PostgreSQL, MySQL, IBM DB2, Oracle, Microsoft SQL Server, and more...
  • NoSQL: MUMPS, Redis, MongoDB
  • Database Design & Architecture
    • ACID & Transactional Databases
    • Data Modeling
    • Big Data
  • Logging, Audits and Pruning
  • Indexing, Performance Tuning
Contact Saga today with your project details and we'll provide a free technical consultation

Clinical Data Warehousing (CDW)

Consolidating patient data to a single source from a variety of systems (EHR, HIS, LIS, third-party vendors) is vital not only from a business perspective but also for improving patient outcomes. Initiatives involving CDW/Clinical Data Reposities (CDR) have historically had difficulties consolidating disparate data sources. Data normalization is a key part of the process, using clinical vocabularies and other tools will facilitate the data aggregation process.

Observational Medical Outcomes Partnership (OMOP)

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OMOP is a collaborative and open data model designed for the analysis of disparate data sources. The common data model and vocabulary (LOINC, RxNorm, ICD, CPT) included in OMOP allow easy integration with EMRs and other applications. While EHRs are focused on storage of patient records, OMOP databases are designed to efficiently normalize and store patient data, consolidating it into a standardized format useful for analytics and research.

Saga consultants have worked extensively in the OMOP common data model (CDM). We can augment your team, filling knowledge gaps and set you on the path to maximize the potential of your data.

Trending News: Healthcare Data Analytics

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5 days ago ... The following is a guest article by Scott Hampel, President of MedeAnalytics. Making improvements in healthcare data analytics has the potential to lead to.

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