Real World Studies
Clinical trials are the key to medical progress. In order to have enough data available, you need a sufficient number of research participants, whose recruitment takes a lot of time and effort.
One solution would be to use routine medical data as a basis for research, but getting this data in a user-friendly format is no easy task. Much of the information needed in clinical research, such as medical history, diagnoses and symptoms, course of therapy, functional values, etc., is often only available in free texts such as the doctor’s letter and thus cannot be used directly for evaluations. It is an enormous effort to manually extract the valuable information from thousands of documents. For this reason, some research questions are not even tackled and important developments are slowed down or do not take place.
With Health Discovery, Averbis improves the way research is conducted for university hospitals or other medical research institutions and prepares routine data accordingly. With our solution, facts can be quickly and easily extracted from texts and made available in a structured and semantically normalised form. We simplify the recruitment of research participants by quickly identifying large patient cohorts. This enables scientists to conduct more studies, as many more clinical parameters are available and more patients can be included in the studies.
Employees of cancer registries also benefit from Health Discovery. Every year they receive hundreds of thousands of diagnostic reports from clinics that are submitted in continuous text form – and thus unstructured. Averbis Health Discovery helps to structure this data, prepare findings and automate processes.
Health Discovery Allows You To:
In this way, we prepare the ground for more accurate diagnostic and treatment decisions, new insights for effective and sustainable disease control, and contribute to making patient care even better.
TriNetX is a global network of healthcare organizations and life sciences companies driving real-world research to accelerate the development of new therapies. Through its self-service, HIPAA, GDPR, and LGPD-compliant platform of federated EHR, datasets, and consulting partnerships, TriNetX puts the power of real-world data into the hands of its worldwide community to improve protocol design, streamline trial operations, refine safety signals, and enrich real-world evidence generation.
TriNetX provides NLP services powered by Averbis that utilize sophisticated algorithms to extract clinical facts from physician notes, clinical and pathology reports, and links this data with other structured data from EHRs.
TriNetX mines unstructured data, such as measurements and observation on ECOG performance status for oncology, NYHA classification, Ejection Fraction, and Corrected QT Interval for cardiac studies. NLP also collects information from clinician notes for patients whose hospital medical records may be incomplete due to visits to multiple healthcare facilities. Extracted data is subsequently mapped to standardized clinical terminologies that can be easily analyzed by researchers using the TriNetX Platform.
TriNetX chose Averbis as its NLP partner for the following reasons:
- Deep experience in healthcare
- Unparalleled accuracy across data domains
- Comprehensive understanding of multiple languages
Averbis Health Discovery is used by three consortia of the Medical Informatics Initiative for the analysis of unstructured data.
One of them is Miracum which focuses on data integration centres that will be embedded in the hospital IT-infrastructure and will facilitate the collection and exchange of data within the consortia university hospitals. The methods of their use case “From Data to Knowledge – Clinico-Molecular Predictive Knowledge Tool” will be used to generate knowledge that can be directly applied in clinical practice.
In this way, Averbis is supporting the Medical Informatics Initiative to narrow the gap between research and patient care. The medical informatics initiative is intended to make the best possible use of the opportunities of digitalisation in medicine for care and research. In a first step, data integration centers are being established and networked at university hospitals and partner institutions. In these centers, the prerequisites will be created to be able to link research and care data across locations.
Health Discovery is used in the initiative to structure the flood of unstructured data that accumulates every day in the health and research sector in different departments and to make it usable – for the benefit of the individual patient, for a better understanding of diseases and for the adaptation of treatments to the needs of the individual. The aim is to create an opportunity to exchange research and care data between university hospitals. This will improve patient care and help to combat diseases more effectively.
What our Customers say
Averbis Health Discovery is a valuable contribution to data protection-compliant, networked medical research.
Health Discovery is an effective tool to prepare textual information for research quickly and in accordance with data protection regulations.
Averbis Health Discovery helps us to slim down our work processes and reduce the burden on our documentalists. This saves us valuable time we can invest in other activities.
All hospitals should receive appropriate remuneration for their services. In order to adequately take into account coding-relevant information from free-text routine data such as doctors’ letters or laboratory reports, we use the AI software Health Discovery from Averbis. We are pleased that we were able to integrate one of the best text mining solutions in Germany into our MetaKIS product. Our customers are thrilled.
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