Table 3.
Model 2: predictors of percentages of patients reporting being able to get an appointment quickly at their practice, n = 8079 in final modela
| Predictor | Beta (95% CI) | IRRb (95% CI) | Effect size | P-value |
|---|---|---|---|---|
| Number of patients on practice hypertension register | −0.0002 (−0.0002 to −0.0001) | 0.9999 (0.9998 to 0.9999 ) | −0.01% | <0.001 |
| GPs per 1000 practice population | 0.28 (0.25 to 0.32) | 1.33 (1.28 to 1.38 ) | 33% | <0.001 |
| Proportion aged ≥65 years | 0.007 (0.005 to 0.009) | 1.01 (1.005 to 1.009) | 1% | <0.001 |
| IMD | −0.0007 (−0.002 to −0.0001) | 0.9994 (0.998 to 0.9999) | −0.06% | 0.013 |
| Practice list size | −0.0001 (−0.0001 to −0.0001) | 0.99987 (0.99987 to 0.99988) | −0.013% | <0.001 |
| Total Quality and Outcomes Framework points for hypertension management | −0.002 (−0.004 to −0.001) | 0.998 0.996 − 0.999 | −0.2% | <0.001 |
IMD = Index of Multiple Deprivation. IRR = incident rate ratio.
a
Statistical model: negative binomial regression, using log of the list size as the offset.
b
Subtracting 1 from the IRR and then multiplying by 100 gives the percentage change in the expected count for a one-unit increase in the predictor. So for GPs per 1000 practice population, for every extra GP per 1000, the expected percentage of patients able to get an appointment fairly quickly increases by 33%. IRR values less than 1.0 represent decreases and IRR values greater than 1.0 represent increases in the count.