Gizem Demircioglu, MS
No relationships to disclose.
Digital Health Innovation and Informatics
PD 14 - Digital Health Information & Informatics - Poster Discussion
Purpose/Objective(s): Generating accurate patient charges is a critical administrative task that requires the coordination of multiple steps. Optimizing the use of an Electronic Medical Record (EMR) system and task workflow provides powerful means of enhancing the accuracy of this endeavor. Despite the ubiquitous nature of department billing and the widespread acknowledgment of doing so in an accurate fashion, there is a paucity of literature which describes prospective interventions and their effect. This study characterizes charge error rates in a busy hospital department, with the effect of post-intervention modifications in the EMR and workflow.
Materials/Methods: During calendar year 2017, we conducted a retrospective review of charge errors that were generated from discrepancies identified between 3rd party submissions and clinical manager review. Common incorrect charges included incomplete and incorrect billing, double entries, and incorrect dates of service. After identifying common sources of these errors, we implemented a Quality Assurance (QA) initiative to mitigate against frequent sources of charge inaccuracy via a PDCA (plan-do-check-act) iterative process. A post-hoc analysis was conducted to assess the effect of this intervention.
Results: The QA intervention was initiated on August 18, 2017. The content of the QA instrument involved altering the timing of charges, adding new workflow-efficient tabs to the EMR, switching from a manual to an automated EMR activity-based charge system, and educating staff on integrating these changes. Both pre and post intervention, there was an average of 205 encounters per day. Prior to the QA initiative, 1,393 (13.6%) of 10,264 patient encounters were found to exhibit a charge error. Encounter types with the highest yield of billing inaccuracies included: patient simulation (42.0%), treatment (35.2%), follow-ups (17.0%), consults (5%) and charges associated with treatment planning (0.5%). After implementing the Quality Assurance Initiative, 192 (1.9%) of 10,290 patient encounters revealed an identifiable error. The daily average number of charge errors decreased from 27.9 ± 42.1 to 3.8 ± 3.1.
Conclusion: Charge errors can be a common, multifaceted occurrence in a busy hospital department. Identifying the magnitude and type of billing inaccuracies can lead to developing a QA initiative with a focus on improving this outcome. We were able to develop EMR workflow changes, an automated billing system with real-time verification, and staffing education which yielded a significant decrease in charge error rate. Further study is warranted to assess how these workflow changes improve clinical efficiency in terms of work hours saved, as well as decreasing costs and increasing hospital departmental revenue.
No relationships to disclose.
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