Arintra
Preeti Bhargava, PhD has a diverse work experience spanning over several years. Preeti most recently co-founded Arintra in 2019 and served as the Chief Technology Officer. Prior to that, in 2018, they worked as a Data Scientist at Demandbase where they built machine learning systems for inferring user topical profiles and auto generating company keyword profiles, significantly impacting the company's business. From 2016 to 2018, they were a Senior Research Engineer in Data Science at Lithium Technologies, leading the development of their resource-constrained, high-throughput and language-agnostic Natural Language Processing (NLP) pipeline. Preeti also improved Klout URL recommendations resulting in a performance improvement of 10-20%. Before that, they worked as a Graduate Research Assistant at the University of Maryland, where they designed, implemented, and tested various systems as part of their PhD dissertation work. Preeti has also gained research and internship experience at Samsung Research America, PARC (a Xerox company), Oracle India, National Sun Yat-sen University, and National Informatics Center.
Preeti Bhargava, PhD, has a strong educational background in computer science. Preeti first attended the Delhi Public School - R. K. Puram for an unspecified degree. After that, from 2003 to 2007, they pursued a Bachelor of Engineering (B.E.) in Information Technology at the Delhi College of Engineering. Wanting to further their knowledge, Preeti attended the University of Maryland from 2010 to 2012 to earn a Master of Science (MS) in Computer Science. Preeti continued their studies at the same institution and obtained a PhD in Computer Science from the University of Maryland from 2010 to 2015. Additionally, Preeti Bhargava holds an ABM Certified Strategist certification from Demandbase, which was obtained in April 2018.
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Arintra
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US hospitals and clinics are losing $125B every year due to delayed and inaccurate medical coding. Arintra is solving this problem by automating medical coding using AI and clinical NLP. Arintra converts a patient chart instantly into insurance claims with 96% accurate medical codes and zero human intervention. Arintra solution is specifically tailored to cater to the varying requirements of ambulatory and outpatient specialties, emergency department services, and inpatient settings, ensuring comprehensive coverage across all healthcare domains. Arintra’s software leverages proprietary artificial intelligence and natural language processing algorithms to process patient charts directly from the EHR to create a direct-to-billing claim. Arintra autonomously goes through every stage of the claim submission process and ensures a clean claim for optimal reimbursements without any human intervention. Arintra is integrated with all the top EHRs to ensure effortless implementation without any change in the workflow. Arintra’s medical coding software offers two powerful modes for medical coding: autonomous coding mode and assisted coding mode. In autonomous coding mode, direct-to-billing claims are generated autonomously with high accuracy, streamlining the billing process for healthcare provider organizations. Whereas, assisted coding mode allows medical coders to meticulously review and optimize charges before submission, leading to increased efficiency and precision in the coding process. With Arintra, healthcare provider organizations can rely on precise direct-to-billing claims that include essential codes like E/M levels, CPT, ICD-10, HCC, HCPCS with appropriate modifiers and units. Arintra’s coding solution provides extensive coverage and flexibility, catering to various coding domains such as professional coding, professional-fee coding, facility coding, and inpatient coding.