Many healthcare organisations are adopting technology solutions such as natural language processing (NLP) tools that can create augmented intelligence workflows that enable the rapid search of unstructured clinical data from various data sources to help clinicians identify uncommon diseases more efficiently and accurately.
Diagnosis may be delayed when important knowledge about a rare condition is missed, and patient outcomes can be affected. However if physicians are provided with better instruments to improve their search efforts, we have the ability to advance rare disease detection and care.
Leveraging augmented intelligence technologies to enhance diagnosis and treatment
Many healthcare facilities are implementing technological solutions to assist in the process in order to help physicians detect rare diseases more efficiently and accurately. Natural language processing (NLP) software, for example, can produce enhanced intelligence workflows that make it easier to rapidly scan unstructured clinical data from various data sources, such as EHRs, patient portals, health infection, etc.
NLP software can look at both structured (discrete fields) and unstructured (free text) data and extract specific information instead of manually digging through various documents or databases. This offers a more detailed, 360-degree view of each individual patient to doctors so that they can make a more accurate diagnosis faster, which is also important when treating patients with a rare disease.
Similarly, using the right data, NLP-driven analytics may provide a better diagnostic picture for all-disease populations, enabling rare disease registries to be developed or improved, recognising clinical trial cohorts, or finding insight into common signs/symptoms or comorbidities. Data can be used by biopharmaceutical businesses for insights into the creation of new medicines when de-anonymized.
Improving understanding and treatment of genetic disease
Clinicians and biopharmaceutical experts are better prepared with augmented intelligence resources and NLP to work together to accurately classify real zebras and advance care and outcomes for individuals with rare diseases. Read more in the source