2019 HSC Section 2 - Practice Management

FIGURE. Monthly average billing level heavy black line indicates date of intervention. Solid colored lines represent composite averages for the preintervention period; dashed colored lines represent composite averages for the postintervention period.

correspond almost identically to national coding trends, reported by the Department of Health and Human Services, providing evidence for better coding accuracy (i.e., external validity) in the postintervention group. 11 The overall increase in coding complexity demonstrates an important problem that has been previously shown among trainees — a high frequency of “ undercoding. ” 12-15 Ignorance of coding “ rules ” and necessary documentation as well as systems barriers (e.g., information technology) seem to contribute to this undercoding. For attending physicians, there are incentives (i.e., reimbursement) for better coding and billing, especially for of fi ce-based practices, which makes this study in a group of surgeons even more demonstrative. On the contrary, fi nancial motivation is generally lacking for residents and more compre- hensive documentation may even be a deterrent through increased workload. Despite these barriers, we found that direct attending feedback and teaching were primary motivators for residents as a balance of service and education. 16 There are several important limitations to recognize in this study. First, the resident population used was small. Although it would be more challenging to implement this training on a larger scale, we believe it would be feasible. Second, it is possible that the changes in coding re fl ect more complex patients in the postintervention period. However, the patient sample size and duration of study make this less likely through a larger clinical volume and increased case mix. Third, multiple interventions were performed, each contributing to an unknown degree to the outcomes of the study. Finally, the Hawthorne effect may skew the results. Furthermore, follow-up after residents were no longer being observed would be useful to evaluate the long-term effects of the intervention.

trend toward signi fi cance (p ¼ 0.05). There was also a signi fi cant decrease in the number of documented lower complexity (Level II) codes by 31.5% (p o 0.01). Finally, we found that the difference in complexity of established and new patient visits narrowed from the preintervention (2.14 vs 2.61, p o 0.01) to the postintervention time period (3.05 vs 3.19, p ¼ 0.04). DISCUSSION This preintervention/postintervention study demonstrates improved documentation of outpatient clinic encounters with a statistically signi fi cant increase in higher complexity billing. Accuracy of this coding was veri fi ed by 3 levels of review (i.e., attending staff, researchers, and clinical coding auditors). Although it is not clear if single intervention was more bene fi cial than the others, the results of this study demonstrate that a simple training curriculum and basic infrastructure improve- ments can positively affect resident behaviors and decision- making. An interesting fi nding was a signi fi cant decrease in the difference of average coding complexity between established and new patients in the preintervention (2.14 vs 2.61) and postintervention groups (3.05 vs 3.19) ( Fig. ). The narrowing of this gap, which represents better parity in new and established patient complexity, indicates more accurate coding of medical- decision making — the fundamental element in the E&M coding paradigm. 10 Based on national trends, we expect that the average complexity for the 2 types of of fi ce visits should be nearly equal as found in the postintervention time period. These results

Journal of Surgical Education Volume 74/Number 2 March/April 2017

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