The need to exchange data between all healthcare personnel, from patients to researchers to healthcare clinicians to regulators, is at an all-time high due to Healthcare’s relatively recent transformation into a digital-heavy industry. The exchange of such massive amounts of information can be both taxing and inaccurate.
Making sense of this data proves to be another equally burdensome challenge, particularly when people from different sectors of the industry want to communicate. Not only does Anzo solve both of these problems, but it also allows for data to be collected from trusted outside sources, including payers, genomic research centres, public health databases, biobanks, and social media feeds.
Read this whitepaper to learn how the Anzo Smart Data Lake solves these problems by disrupting the way IT and businesses alike manage and analyze data at enterprise scale with unprecedented flexibility, insight and speed.
Establish processes for harmonizing data expressed, and use these results for clinical decision support, research, billing quality, optimization, and more.
Support clinical research by fusing conflicting operational and clinical data such as study protocols, treatment plans, laboratory results, demographics, and personnel data.
Organize data from a wide variety of clinical sources and in a wide variety of formats, and aggregate healthcare statistics in support of evolving public health policy decision-making.
Combine data, applications, and analytics in a meaningful way to improve health management, value-based care, and patient-centered medical homes.
This blogpost discusses how semantic graph technology can help overcome the challenges presented by healthcare regulations and standards such as HL7.
This Slideshare was presented at our inaugural Life Sciences Smart Data Discovery and Analytics Forum where industry leaders met to discuss the application of smart data technology to healthcare data to gain more actionable insights.
In this blogpost, we sit down with our' own Dan Szot, VP Sales, Life Sciences and Healthcare, for a short Q&A on the state of data discovery and analytics in healthcare.