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Automated Charge Capture

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Book cover Anesthesia Informatics

Part of the book series: Health Informatics ((HI))

The primary motivation, or return on investment (ROI), for purchasing an EMR for most office-based physician practices focuses predominately on the ability to enhance and automate charge capture. In the paper world, a patient would be seen by a physician, who would create notes on paper records. The physician would then typically complete a “superbill”—a fairly standardized form that contains most of the chargeable items for that particular specialty. This superbill would be sent to the front office at checkout and form the basis for the documentation of services rendered, charges generated by the office staff, and the subsequent claim submission to the payer. Unfortunately, in this scenario, the physician filling out the superbill would frequently code or bill for a visit that was not adequately justified from the documentation in the chart. Concomitant with the passage of HIPAA, this miscoding became fraudulent billing, susceptible to fines and penalties. 1 With the advent of EMRs, the selection of charges could be generated by software algorithms based on specific rules that are incorporated into the charge functionality. These sophisticated systems could even “recommend” actions that would enhance the documentation and consequently increase the level of coding for the medical visit. 2, 3 For example, an on-screen alert could indicate that if the physician would simply define the social history, the visit could qualify for an evaluation and management code that would be slightly higher than that coded without the social history. A significant proportion of the ROI cited by vendors of these systems is the ability to accurately capture all charges and potentially enhance revenue generation. Despite the obvious advantage of digitizing the clinical records and the concomitant ability to analyze these data, no business entity would decide to invest in these expensive systems unless they could generate savings, either through reduced expenses or increased revenues.

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© 2008 Springer-Verlag London Limited

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Reeves, C., Stonemetz, J. (2008). Automated Charge Capture. In: Anesthesia Informatics. Health Informatics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-76418-4_14

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  • DOI: https://doi.org/10.1007/978-0-387-76418-4_14

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-76417-7

  • Online ISBN: 978-0-387-76418-4

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