COVID-19 ∙ Population Health Analytics from the Electronic Health Care Record
In the COVID-19 pandemic where healthcare services have been stretched severely across the globe, the ability to understand and map population health dynamics in real time, could provide a critical advantage in healthcare planning and delivery.
Apurba has through 10 years of focused research developed a solution capable of identifying patterns in healthcare narratives and then translating that information into computable data.
Enabling a range of population health predictive analytics that have applications in healthcare provision, disease control and medical research.
Apurba’s technology integrates with SNOMED CT structured clinical vocabulary, used extensively for the electronic health care record. Employing Artificial Intelligence, Natural Language Processing and Machine learning in conjunction with genomics databases with SNOMED CT, we can construct a deep patient history and wider population health models.
Wired Room ∙ Understanding the Nuances of the Clinical Encounter
It is now a documented fact that clinicians are spending less and less time talking and interacting with patients and more and more time on documenting these encounters. The clinician is required to record the interaction, contemporaneously, often with very little time to reflect and digest what is recorded. What is written, then becomes a historical record, for others in the future to analyze.
The directive of the Wired Room project was to demonstrate that the clinician’s administrative burden could be lifted by recording the clinical encounter and extracting notes to form a template for the electronic healthcare record using the latest advances in Artificial Intelligence for natural language processing, speech, image and facial recognition.
Apurba Clinical Coder ∙ for SNOMED-CT
The Apurba Clinical Coder is for busy NHS GP practices who are faced with increasing administrative burdens that drives costs and takes front line staff away from patient care.
It has been designed to streamline their current manually intensive processes, requiring medical secretaries or doctors to correctly assess letters, clinical notes and reports for a given patient and assign the correct SNOMED-CT code that reflects the patient’s diagnosis, treatment and on-going care.
We provide a service that automates the process increasing speed and accuracy whilst reducing staffing costs relating to this and freeing doctors to see patients. The improved quality of the data also improves the ease with which practices can claim additional funding from Clinical Commissioning groups to care for their patient group.