Validation of use of billing codes for identifying telemedicine encounters in administrative data

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Abstract

Background: Telemedicine is the use of telecommunication technology to remotely provide healthcare services. Evaluation of telemedicine use often relies on administrative data, but the validity of identifying telemedicine encounters in administrative data is not known. The objective of this study was to assess the accuracy of billing codes for identifying telemedicine use. Methods: In this retrospective study of encounters within a large integrated health system from January 2016 to December 2017, we examined the accuracy of billing codes for identifying live-interactive and store-and-forward telemedicine encounters compared to manual chart review. To further examine external validity, we applied these codes and assessed patient and visit characteristics for identified live-interactive telemedicine encounters and store-and-forward telemedicine encounters in a second data set. Results: In manual review of 390 encounters, 75 encounters were live-interactive telemedicine and 158 were store-and-forward telemedicine. In weighted analysis, the presence of the GT modifier in the absence of the GQ modifier or CPT code 99444 yielded 100% sensitivity and 99.99% specificity for identification of live-interactive telemedicine encounters. The presence of either the GQ modifier or the CPT code 99444 had 100% sensitivity and 100% specificity for identification of store-and-forward telemedicine encounters. Applying these algorithms to a second data set (n = 5,917,555) identified telemedicine encounters with expected patient and visit characteristics. Conclusions: These findings provide support for use of CPT codes to perform telemedicine research in administrative data, aiding ongoing work to understand the role of non-face-to-face care in optimizing health care delivery.

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Yeramosu, D., Kwok, F., Kahn, J. M., & Ray, K. N. (2019). Validation of use of billing codes for identifying telemedicine encounters in administrative data. BMC Health Services Research, 19(1). https://doi.org/10.1186/s12913-019-4753-2

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