The Applications of AI in EHR Systems

The Applications of AI in EHR Systems

Healthcare Tech Outlook | Friday, August 12, 2022

Healthcare providers can leverage Artificial Intelligence to analyze patient satisfaction and predict patient risks.

FREMONT, CA: AI-powered EHR systems provide solutions with various features and allow smooth integration. The recording of patient medical experiences, the organization of sizable EHR data banks for the discovery of vital records, the assessment of patient satisfaction, and other tasks can all be aided by machine learning and Natural Language Processing (NLP). In order to convert voice recognition system speech into text, healthcare professionals can use machine learning models along with NLP. The algorithms can be separated appropriately based on the specific patient, sickness, therapy for illness, etc., and trained on enormous volumes of patient data on patient's treatment, equipment used for treatment, respective doctor, etc. It will improve the ability to find information and documents in sizable databases.

Data extraction

By leveraging the power of artificial intelligence, healthcare providers can extract patient data from multiple sources, such as faxes, clinical data, provider notes, etc., and recognize keywords that provide actionable insights into patient health. Because they are electronically preserved and allow healthcare providers to access patient data from any location, EHRs save lives in emergencies by providing the patient's whole medical history.

Support for decision-making

Treatment procedures and strategies are usually determined by generic decisions that are usually made. With artificial intelligence ingrained in the systems, a wide range of machine learning solutions and initiatives enable personalized care and learning from new and real-time data. They strengthen and improve communication not only among doctors but also between doctors and patients. Better communication always results in better care.

Predictive Analytics

Predictive models generated from the big data will be possible for physicians to be alerted to diseases that could be lethal. A medical image interpretation algorithm powered by AI can also be integrated into the Electronic Health Record (EHR) and be used to provide decision support and treatment strategies based on the interpretation of medical images.

Documentation of clinical results

Companies are developing devices powered by Natural Language Processing (NLP) that can be integrated with their EHRs to capture data directly from clinical notes so doctors can focus more on their patients and their treatments.

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