5/5/2023 0 Comments Iscribe youtube![]() EHR solutions embedded with an AI layer can document patient problems, diagnoses and procedures in compliant formats through voice-based commands. Automated capturing of clinical notes through natural language processing (NLP) reduces clinician admin work, freeing up more time to focus on patients.ĪI-based speech-to-text technologies can help ease these pressures by minimizing much of these administrative tasks. Not only does this eat into valuable patient time, but also contributes to excessive work–life imbalance, dissatisfaction, high rates of attrition, and burnout. Reducing administrative burden of clinical documentationĪ study by the American Medical Association (AMA) and the University of Wisconsin, shows that nearly 50% of clinician time is spent on admin work, including documentation, order entry, billing and coding, and system security. In this article, we explore how exactly AI is making EHR systems more efficient.ġ. ![]() This is a concern for the US healthcare system, as extended care delivery times translate into higher costs for patients as well as physician burnout and job dissatisfaction.Ī slew of healthcare and technology firms have stepped up to address this challenge and more through AI. A US study by the American College of Physicians found that doctors spend an average of 16 minutes per patient on EHR functions across specializations. While the use of electronic health records (EHR) aims to help clinicians meet these demands, it has yet to optimize their productivity in a significant way. ![]() The importance of efficiency, speed and productivity in healthcare delivery is indisputable. ![]()
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