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 skillset 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 consultaiton

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)


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 EMR's and other applications. While EHR's are focused on storage of patient records, OMOP databases are designed to efficiently normalize and store patient data, consildating 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

Keck Medicine tests Black Box to improve patient safety by ...

Dec 12, 2017 ... When attached to a robotic surgery system during radical prostatectomy procedures, the most common treatment for prostate cancer, the black box recorder captures data that could be used to discern the difference between novice and expert surgeons. The recorder used in the study, called the dVLogger , captures both ...

Future-proofing population health: Embrace predictive analytics ...

Nov 30, 2017 ... The full tech stack includes Microsoft Azure to host the data warehouse, Alteryx for data preparation and data blending, Tableau for data visualization dashboards, Python and R for machine learning and building algorithms for patient risk profiling. “The RHIO is also an important technology for us as are other data-sharing ...

Predictive analytics is about finding patterns, riding a surfboard in a ...

Mar 26, 2017 ... As data analytics progresses, researchers are learning more about how to harness the massive amounts of information being collected in the provider and payer realms and channel it into a useful purpose for predictive modeling and population health management as well as for a multitude of clinical and administrative ...

NIST weighs in on EHR copy-and-paste safety | Healthcare IT News

Feb 6, 2017 ... In collaboration with ECRI, a new report outlines best practices, suggesting that copy-and-paste data should be easily identifiable, with its original source easy to discern.