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. Author manuscript; available in PMC: 2015 Aug 1.
Published in final edited form as: Health Serv Res. 2014 Jan 24;49(4):1165–1183. doi: 10.1111/1475-6773.12148

Table 3.

Odds ratios of surgical complications using doubly robust logistic regression*

Type of Complication
30-Day Surgical Late Urinary Long-term incontinence
Urologist change
    No Change 1.00 1.00 1.00
    Urologist change 0.82 (0.76-0.89) 0.94 (0.87-1.01) 0.97 (0.89-1.05)
Urologist volume of treating urologist
    Low 1.00 1.00 1.00
    High 0.86 (0.77-0.97) 0.83 (0.76-0.91) 0.82 (0.73-0.93)
Years since medical school graduation for treating urologist**
    Top quartile (Oldest) 1.00 1.00 1.00
    Middle top quartile 0.99 (0.89-1.12) 0.86 (0.77-0.95) 1.03 (0.91-1.17)
    Middle bottom quartile 0.97 (0.86-1.10) 1.00 (0.90-1.11) 1.08 (0.95-1.22)
    Lowest quartile (Youngest) 1.07 (0.91-1.26) 1.06 (0.92-1.21) 1.37 (1.15-1.62)
Board certification of treating urologist
    No 1.00 1.00 1.00
    Yes 1.11 (1.01-1.24) 1.23 (1.13-1.37) 1.12 (1.00-1.25)
Type of procedure
    Open prostatectomy 1.00 1.00 1.00
    Minimally invasive prostatectomy 0.68 (0.50-0.93) 1.15 (0.88-1.50) 0.69 (0.44-1.08)
*

Propensity score weighted models adjust for age, race, comorbidities, marital status, income, t-stage, grade, SEER-site, diagnosing urologist volume, laparoscopic or robotic prostatectomy experience of the treating physician, type of procedure, SEER-site, and year of diagnosis.

**

Years since medical school graduation was calculated as the number of years between 2005 and graduation year. This variable was then categorized into quartiles based on the physician distribution.

Note: The “doubly robust” models include all variables used in generating the propensity score as well as the variables listed in the table. The odds ratios for the covariates included in the propensity score model are not interpretable in the outcome model and therefore not listed above.