Healthcare

Healthcare is an increasingly interconnected, digital industry. The need to exchange data between healthcare clinicians, hospitals, payers, patients, researchers, drug developers, and regulators is exploding, as is the challenge of making sense of massive amounts of EHR, claims, genomic, and other healthcare data.

The industry recognizes this challenge. HL7 and other industry standard groups are turning towards semantic standards to better describe and improve the utility of healthcare data. Healthcare organizations are taking advantage of Anzo’s group-up support for semantic standards, flexible integration tools, and end-user self-service analytics capabilities to solve various use cases, such as:

Mapping between Industry Standards

Taking a holistic look at data across the healthcare landscape requires navigating a complex and ever-changing environment of vocabularies, taxonomies, ontologies, and coding schemes. Anzo combines automated, heuristics-driven algorithms with easy-to-use manual interfaces to give you a practical and efficient approach to mapping data between different standards. With Anzo, organizations deploy incremental, semi-automated processes for harmonizing data expressed using SNOMED, RxNorm, ICD-9, ICD-10, MeSH, and proprietary coding systems. The resulting unified data can be used for clinical decision support, research, billing quality and optimization, and more.

Cross-functional Clinical Research

Anzo significantly accelerates the pace at which diverse information can be brought together in support of agile and adaptive clinical research studies. Because Anzo does not require a rigid up-front data model, it can easily bring together disparate operational and clinical data such as study protocols, treatment plans, laboratory results, demographics, and personnel data. And Anzo’s ease-of-use means that clinical researchers can bring on-board new data and pursue new lines of investigation with little or no IT involvement.

Public Health Policy

Governments and other public agencies use Anzo to combine patient, diagnostics, treatment, and outcomes data from a wide variety of clinical sources and in a wide variety of formats. By taking advantage of Anzo’s flexibility, these organizations can aggregate healthcare statistics in an ad-hoc and as-needed basis in support of evolving public health policy decision making.