5 Top NLP Startups Integrating Electronics Health Records (EHRs)

We analyzed 173 startups developing natural language processing (NLP) solutions for electronic health records. MedInReal, Mutuo Health Solutions, Plasticity, talkEHR & Emtelligent develop 5 top solutions you should watch out for. Learn more in our Global Startup Heat Map!

Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups working on innovative solutions in the healthcare sector. As there is a large number of startups working on a wide variety of solutions, we want to share our insights with you. This time, you will discover 5 promising natural language processing startups integrating electronic health records.

Heat Map: 5 Top NLP Startups Integrating EHR

Using our StartUs Insights Discovery Platform, covering 1.379.000+ startups & scaleups globally, we looked at innovation in the field of healthcare. For this research, we identified 173 relevant solutions and picked 5 to showcase below. These companies were chosen based on a data-driven startup scouting approach, taking into account factors such as location, founding year, and relevance of technology, among others. Depending on your specific criteria, the top picks might look entirely different.

The Global Startup Heat Map below highlights 5 startups & scaleups developing innovative NLP solutions for EHR integration. Moreover, the Heat Map reveals regions that observe a high startup activity and illustrates the geographic distribution of all 173 companies we analyzed for this specific topic.

NLP-for-EHR-Startups-Healthcare-Heat-Map-StartUs-Insights-noresize

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Which startups develop the other 168 solutions?

 

MedInReal – Voice Recognition

Doctors make clinical notes while observing patients’ health conditions. Artificial intelligence (AI) applications in natural language processing help clinicians spend time efficiently diagnosing the patient and automates the administrative work such as entering the relevant EHR data. Startups develop voice recognition solutions to improve clinical efficiency in treating patients and delivering high-quality healthcare.

Dutch startup MedInReal develops Alex, an artificial intelligence, and natural language processing-based solution for medical practitioners. The startup’s solution uses AI to recognize voices and enables doctors to automatically make clinical notes and populate EHRs. Alex manages clinical workflows such as medical transcription and patient health management and utilizes advanced analytics to remove the burden of administrative tasks for medical professionals.

Mutuo Health Solutions – Clinicians’ Personal Assistant

Patient engagement is critical for diagnosing illnesses as these interactions provide doctors with valuable information in terms of symptoms and the physical condition of the patient. However, making notes of the interactions is a cumbersome process. For this purpose, NLP algorithms help translate speech to text or voice to text and make the process of medical documentation easier and less time-consuming. Startups develop voice assistants to enable doctors to spend more time interacting with patients rather than making detailed notes.

Canadian startup Mutuo Health Solutions develops Autoscribe, a hands-free speech to text solution for making clinical observations and notes. The startup leverages AI and speech recognition technology to eliminate manual clinical documentation. As a result, the time taken by medical professionals in terms of documentation significantly reduces. While speech recognition software translates discussions between patients and doctors into data, machine learning algorithms process the dialogue language and suggest outputs.

Plasticity – Natural Language Engine

Electronic medical records (EMR) contain historical patient data, treatment plans, and the detailed medical history of patients. Medical professionals refer to EMRs to quickly understand patient health. Speech recognition and text recognition further enable medical staff to automate various time-consuming processes. Startups develop language engines that understand complex clinical notes and automatically integrate them with EMR.

The US-based startup Plasticity develops application programming interfaces (APIs) that also leverage NLP to understand complex patient-doctor dialogues. The startup’s language engine, Sapien, enables a deeper understanding of context and relations from sentences in large quantities of data. Further, the startup structures and extracts symptoms data from medical notes, information from case briefs, entities in articles, or additional data hidden in sentences and makes all of it accessible for medical professionals.

talkEHR – Interactive EHR Software

Machine learning algorithms help a wide range of industries including healthcare, manufacturing, energy, pharma, and automotive. EHR is one such application in healthcare that utilizes AI and ML algorithms to automate medical documentation. Startups and scaleups develop voice recognition solutions to integrate with EHR software to make healthcare delivery more seamless.

The US-based startup talkEHR develops Alison, an AI-powered voice assistant for EHR software. The startup enables the automation of repetitive aspects of medical practices with integrated voice assistants resulting in a significant increase in patient interaction. TalkEHR’s dashboard enables users to seamlessly manage appointment schedules, lab testing, and prescription databases. Alison is also ONC-ACB certified, ICD-10 compliant, and MACRA/MIPS certified.

Emtelligent – Medical Language Engine

Medical terms that are computer processable, provide codes, terms, synonyms, and definitions that are usually complex in nature. Such terms are also cataloged in multiple medical dictionaries and sources. Utilizing advanced machine learning algorithms, medical databases become easily processable. Thereby enabling startups to develop advanced language engines to process and translate complex medical terms.

Canadian startup Emtelligent develops emtelliPro, an enterprise-scale deep learning-based NLP engine to process medical text. The engine uses machine learning to deliver high-precision and recall to resolve complicated medical text in various reports. The solution extracts medical definitions using multiple ontologies including MEDCIN, SNOMED, RadLex, RxNorm, HGNC, and the NCI Thesaurus, and also allows the usage of custom ontologies. Further, emtelliPro enables rapid cluster processing of millions of reports every day.

What about the other 168 solutions?

While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence and enable you to achieve your goals faster. The 5 NLP startups integrating EHR solutions showcased above are promising examples out of the 173 we analyzed for this article. To identify the most relevant solutions based on your specific criteria, get in touch.

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