Application Research on Mining the Value of EMR Data Based on Word Frequency Analysis

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Focusing on the discovery of the value of in-hospital electronic medical record data for the three "chronic diseases" of diabetes, liver disease and hypertension, it provides data support for improving the hospital's "patient-centered" service level. Through web crawler technology, word frequency analysis technology, WeChat applet development technology, etc., we complete the design and development of big data systems such as data collection, preprocessing, analysis, and visualization, and tap the potential value of ten-year electronic medical record data. The standardized data collation platform and the development of the "Community Online" WeChat applet were completed. The original html data was standardized and stored in a relational database; through data mining, the distribution rules of occupation, age, gender, etc. of regional chronic diseases were found; through word frequency analysis, three kinds of chronic disease admission symptoms, treatment medication and discharge life suggestions were found hot word. Taking the system as the carrier, and through the research on the value discovery of Electronic Medical Records (EMR) data, a systematic chronic disease service system from health warning to admission treatment to discharge tracking has been built for patients with diabetes, liver disease and hypertension. Provide decision-making support for "early warning, early detection, early diagnosis, and early treatment" of chronic diseases and regional improvement of comprehensive management of chronic diseases and scientific treatment.

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