HumanInsight A Retrospective Analysis of Patients Undergoing Telemedicine Evaluation in the PreAnesthesia Testing Clinic at H. Lee Moffitt Cancer Center
Cancer Control. 2021 Jan-Dec;28:10732748211044347. doi: 10.1177/10732748211044347.
BACKGROUND: Telemedicine for preanesthesia evaluation can decrease access disparities by minimizing commuting, time off work, and lifestyle disruptions from frequent medical visits. We report our experience with the first 120 patients undergoing telemedicine preanesthesia evaluation at Moffitt Cancer Center.
METHODS: This is a retrospective analysis of 120 patients seen via telemedicine for preanesthesia evaluation compared with an in-person cohort meeting telemedicine criteria had it been available. Telemedicine was conducted from our clinic to a patient's remote location using video conferencing. Clinic criteria were revised to create a tier of eligible patients based on published guidelines and anesthesiologist consensus.
RESULTS: Day-of-surgery cancellation rate was 1.67% in the telemedicine versus 0% in the in-person cohort. The two telemedicine group cancellations were unrelated to medical workup, and cancellation rate between the groups was not statistically significant (P = .49). Median round trip distance and time saved by the telemedicine group was 80 miles [range 4; 1180] and 121 minutes [range 16; 1034]. Using the federal mileage rate, the median cost savings was $46 [range $2.30; 678.50] per patient. Patients were similar in gender and race in both groups (P = .23 and .75, respectively), but the in-person cohort was older and had higher American Society of Anesthesiologists physical status classification (P = .0003).
CONCLUSIONS: Telemedicine preanesthesia evaluation results in time, distance, and financial savings without increased day-of-surgery cancellations. This is useful in cancer patients who travel significant distances to specialty centers and have a high frequency of health care visits. American Society of Anesthesiologists Physical Status classification and age differences between cohorts indicate possible patient or provider selection bias. Randomized controlled trials will aid in further exploring this technology.
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