E-Posters-10135

10135_Stone

Pdf Summary

The study analyzed Medicare billing and reimbursement data for Female Pelvic and Reconstructive Surgery (FPMRS) providers from 2012 to 2014. Out of 1,212 FPMRS providers, 797 were OB/GYN trained and 294 were urology trained. The mean total yearly reimbursement for OB/GYN trained providers was $64,086.92, while urology trained providers had a mean total yearly reimbursement of $144,539.16. The median reimbursement for OB/GYN trained providers was $54,180.90, compared to $117,230.02 for urology trained providers. The study also identified the codes with the highest and lowest reimbursement/billed ratios for both OB/GYN and urology trained providers.<br /><br />Table 1 shows that among the OB/GYN trained providers, the codes with the highest reimbursement/billed ratio were related to annual wellness visits and pap smears. For urology trained providers, the codes with the highest reimbursement/billed ratio were for ultrasound of the abdomen, cell examination of urine, and unclassified drugs.<br /><br />Table 2 reveals that among the OB/GYN trained providers, the codes with the lowest reimbursement/billed ratio were related to bladder emptying assessment and various surgical procedures. For urology trained providers, the codes with the lowest reimbursement/billed ratio were also related to bladder emptying assessment, as well as ureteral stent insertion and voiding cystogram.<br /><br />In conclusion, the study highlights the differences in Medicare reimbursement between OB/GYN trained and urology trained FPMRS providers. The findings suggest that urology trained providers had higher reimbursement rates compared to OB/GYN trained providers. The study also emphasizes the potential of Medicare claims data in understanding patterns of care for Medicare patients.

Keywords

Medicare billing

reimbursement data

Female Pelvic and Reconstructive Surgery

FPMRS providers

OB/GYN trained

urology trained

total yearly reimbursement

reimbursement/billed ratio

codes

Medicare claims data