SySearch™ helps health systems and payors accurately search and collect clinical insights across complex datasets and unstructured narrative medical records.
ZEPHYR COVE, NEVADA, UNITED STATES, June 9, 2021 /EINPresswire.com/ — Healthcare organizations generate unmeasurable amounts of patient information: medical histories, diagnoses, observations, lab, and imaging reports, to name a few. Each patient record is unique, and medical data is complex & confusing, making it difficult for machine learning algorithms and analytics to consume, process, and organize. In addition to complexity, clinical data is notorious for being simultaneously redundant and incomplete, confined in separate data systems or repositories, and with spelling errors and inconsistencies. In order to use patient information to analyze health trends, improve workflows and advance care, it needs to be pre-processed using a system that can recognize sentence semantics and appropriately tag, index, and normalize data. Some tools are available to help healthcare organizations structure their data and tag some clinical information (typically underpowered word search), but these solutions are often unable to handle the many complexities of health data. This results in falsely coding and reporting the data.
SyTrue, Inc, announces the worldwide availability of its revolutionary SySearch™, a clinical Natural Language Processing service to help organizations such as health systems, pharma/medical research organizations, and health payors spot trends in endless amounts of unstructured data. SySearch™ processes health records from all sources and file types within an organization and automatically maps clinical information to standardized terminologies such as SNOMED-CT, RxNorm, LOINC, MedDRA, ICD-9 and ICD-10. SySearch™ looks around the targeted data, processing the structure of a sentence, the context in which a sentence was written (including the page it is found on), and relational mappings to understand the difference between “AMI” documented in a psychology medication list (amitriptyline) versus “AMI” documented in an emergency room intake summary (acute myocardial infarction). SySearch™ can organize data from an individual’s health journey, an entire patient population, or an enterprise’s data warehouse. Organizations that use SySearch™ have the ability to retrospectively analyze longitudinal health data to find that needle in a haystack, or identify populations that require further exploration.
Health data processed by SySearch™ is accessible to query with a user-friendly Natural Language Query (NLQ), so you can get answers to your questions in real-time. You no longer need to be a data scientist to access valuable insights from medical records. Research analysts, business development specialists, and medical professionals have different questions to ask health data, so SySearch™ allows natural phrases and expressions to query your entire population of records the same way you would type a question into Google. For example, you can search for “What are the top symptoms of female patients between the ages of 25 and 47 with a history of breast cancer who are also on narcotics?”
“While others such as IBM, Google, and Amazon are still pilot testing and releasing unproven conceptual platforms, SySearch™ has been pressure tested across billions of real-world health records and is already being used commercially by large organizations in North America, right now.” Says SyTrue’s Chief Medical Officer, and digital health expert, Dr. Ketan Patel. “Our clients are currently deriving value from this technology, which is now ready for prime-time internationally through our collaboration with Microsoft and availability on Azure Marketplace.”
Often, organizations in the midst of a digital transformation resort to expensive manual data entry or settle for unstructured PDF files to retain their clinical histories, resulting in missed opportunities to mine, learn, and build from the wealth of patient data. SySeach™ unlocks access to unstructured clinical notes, so health systems, payors, and research organizations can better understand what is occurring within their patient populations, improving how healthcare is delivered, analyzed, and developed for the future.
SyTrue, Inc. is addressing healthcare’s unstructured data problem with its suite of tools that use proprietary clinical Natural Language Processing (NLP) to read and understand medical records. SyTrue’s clinical analyzers dive deep into the content contained within medical records shedding valuable insights on the patients’ healthcare journey.
SyTrue is built to fix our broken workflows within the healthcare system by automating healthcare’s most onerous tasks, delivering increased productivity, reducing review costs, and increasing revenue to Health Plans and Service Providers. Health organizations consume hundreds of millions to billions of pages of clinical documentation annually. Most of this documentation is locked in unstructured formats like PDF, TIFF, DOC, etc., preventing the insights contained within them from being widely consumed and distributed across an organization. This blocks your enterprise from fully realizing the exponential benefits of those insights. SyTrue is designed to solve this problem. We can consume billions of pages of clinical documentation and publish accurate insights throughout the organization providing a new enterprise view that can drive twenty or more different objectives rather than just one. SyTrue is used by national health plans to extract meaningful insights to make clinical decisions more efficient, affordable, and effective.
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