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. 2008 Jan;101(1):27–33. doi: 10.1258/jrsm.2007.070424

Table 2.

Effect of gender on activity rates - accounting for confounding variables

Effect Estimate 95% confidence interval P value
Model 1: Finished consultant episodes
Sample:1 6451 male and 886 female
Gender effect (additional activity by men) 160 116 to 204 <0.0001
Model 2: Casemix adjusted activity (£000)2
Sample: 6448 male and 884 female
Gender effect (additional activity by men) 214 147 to 280 <0.0001
Model 3: FCEs including contract and bonus payments as predictors
Sample: 6451 male and 886 female
Gender effect (additional activity by men) 153 109 to 197 <0.0001
Contract effect (additional activity by maximum part-time contract holders) 75 39 to 112 <0.0001
Effect of discretionary point or local CEA 48 17 to 79 0.003
Effect of distinction award or national CEA −6 −53 to 39 0.8
Model 4: Casemix adjusted activity (£000) including contract and bonus payments as predictors
Sample: 6448 male and 884 female
Gender effect (additional activity by men) 204 138 to 271 <0.0001
Contract effect (additional activity by maximum part-time contract holders) 97 42 to 153 0.0006
Effect of discretionary point or local CEA 67 19 to 113 0.005
Effect of distinction award or national CEA −17 −87 to 53 0.6

Notes:

1

Sample sizes differ due to linking of datasets and some missing variables

2

Casemix-adjusted activity is estimated by summing the tariff cost of the healthcare related group (HRG) that is assigned to each episode