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Association between Payer-Class and Patient Satisfaction Scores in an Academic Urology Outpatient Clinic
Dan Hayward1, Stephanie Bui1, Cornelia de Riese2
1Texas Tech University Health Sciences Center School of Medicine, Lubbock, Texas.
Introduction:
As physician reimbursement models transition from fee-for-service to value-based purchasing, patient satisfaction is becoming an important payment modifier. Studies have shown correlation between nonmodifiable patient attributes and satisfaction scores. This study aims to investigate potential patient bias in survey scores associated with payer type in an academic urology outpatient clinic setting.
Methods:
The survey results of 20,944 patients seen in an academic urology clinic were analyzed, and the weighted mean±SD scores of patient experience in 6 major payer categories were compared: 1) commercial insurance, 2) Medicare, 3) Medicaid, 4) other government plans, 5) workers' comp and 6) self-pay/uncompensated. ANOVA and Tukey-Kramer Honestly Significant Difference were utilized to assess statistical significance.
Results:
Medicare patients reported the highest satisfaction scores (93.03), followed by other government coverage (91.49), commercial insurance (91.32), workers' comp (90.72), Medicaid (89.21) and self-pay/uncompensated (89.00). ANOVA analysis resulted in an F value of 40.198 (p <0.001). Tukey-Kramer demonstrated statistical significance in the difference between the means of the following groups: commercial vs Medicaid (p <0.001), commercial vs Medicare (p <0.001), commercial vs self-pay/uncompensated (p <0.01), other government vs Medicaid (p <0.001), other government vs Medicare (p <0.01), Medicaid vs Medicare (p <0.001), Medicare vs self-pay/uncompensated (p <0.001).
Conclusions:
Our data suggest that patient experience scores are impacted by the type of coverage the patient carries and not only by the quality of care provided. Urology clinicians should be aware of these nuances when selecting MIPS quality reporting metrics. Currently, these biased scores may have an impact on physicians' reimbursement, and policymakers should consider adjusting reimbursement according to payer-mix.
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