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A Decision Support Tool for Using an ICD-10 Anatomographer to Address Admission Coding Inaccuracies: A Commentary
Author(s) -
Christopher M. Bell,
Arash Jalali,
Edward Mensah
Publication year - 2013
Publication title -
online journal of public health informatics
Language(s) - English
Resource type - Journals
ISSN - 1947-2579
DOI - 10.5210/ojphi.v5i2.4813
Subject(s) - emergency department , coding (social sciences) , medical emergency , icd 10 , medical diagnosis , diagnosis code , medicine , decision support system , computer science , data mining , nursing , statistics , population , mathematics , environmental health , pathology
In the chaotic environment of an emergency department trauma unit, accuracy and timeliness in decision making are required to save a patient’s life. In a large urban city, where gun violence is high, emergency department physicians must have a wide array of tools in order to effectively and efficiently treat victims of gun violence and ensure that their diagnoses are properly coded. A disparity currently exists between the accuracy of ICD-9 admission coding and discharge coding with some error rates as much as seventy percent. [1,2,3,4] The elevated error rate is poised to increase even more, as the US transitions from ICD-9 to ICD-10 coding standard. The proposed decision support tool, the ICD-10 anatomographer, will have many advantages to medical professionals working in high-intensity settings. Emergency department physicians in busy trauma care units in large urban hospitals will be able to utilize this technology to find the accurate ICD-10 code in an efficient manner, thereby improving quality of care and saving lives. Keywords: decision support, ICD-9 to ICD-10 transition, anatomography

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