Differences in prevention scores across funding models in multilevel regression analyses
| Variable | Overall prevention score* (95% CI) | Multilevel regression analysis; β estimate for effect on prevention score† (95% CI) | |||
|---|---|---|---|---|---|
| Analysis A (unadjusted)‡ | Analysis B§ | Analysis C¶ | Analysis D** | ||
| Intercept | 2.4 (59.5 to 69.2) | 46.5 (42.1 to 51.0) | 41.9 (37.3 to 46.6) | 40.1 (36.2 to 44.0) | |
| Funding model†† | |||||
| New capitation | 65 (62 to 67) | ref | ref | ref | |
| Salaried | 68 (65 to 70) | 3.4 (−3.4 to 10.3) | −0.8 (−6.5 to 4.8) | −4.5 (−10.0 to 1.0) | |
| Fee for service | 58 (55 to 61) | −6.4 (−13.2 to 0.5) | −6.3 (−11.9 to −0.6) | −6.4 (−11.7 to −1.1) | |
| Established capitation | 52 (49 to 55) | −12.0 (−19.0 to −5.0) | −9.1 (−14.9 to −3.3) | −6.8 (−12.2 to −1.3) | |
| Patient profile | |||||
| Males, all ages | ref | ref | ref | ||
| Females 17–49 yr‡‡ | 34.6 (31.5 to 37.7) | 34.3 (31.2 to 37.4) | 34.5 (31.4 to 37.6) | ||
| Women 50–64 yr‡‡ | 18.4 (14.7 to 22.1) | 17.9 (14.1 to 21.6) | 18.1 (14.4 to 21.8) | ||
| Women 65–69 yr | 6.7 (−0.2 to 13.6) | 6.0 (−1.0 to 13.0) | 6.3 (−0.7 to 13.3) | ||
| Women ≥ 70 yr | 0.7 (−4.1 to 5.4) | 0.4 (−4.4 to 5.3) | 0.5 (−4.3 to 5.3) | ||
| Family physician profile | |||||
| Presence of ≥ 1 female family physician | 9.8 (5.6 to 14.0) | 8.0 (4.2 to 11.8) | |||
| Organizational structure | |||||
| Panel size < 1600 patients per FTE family physician | 6.8 (3.1 to 10.6) | ||||
| Presence of electronic reminder system | 4.6 (0.4 to 8.7) | ||||
Note: CI = confidence interval, FTE = full-time equivalent, ref = reference category.
↵* Each patient was assigned a prevention score that was calculated by dividing the number of manoeuvres performed by the number of manoeuvres for which the patient was eligible within the previous 24 months and then mulitplying by 100; the score ranged from 0 (if no eligible manoeuvres were performed) to 100 (if all eligible manoeuvres were performed).
↵† The β estimates were derived from multilevel linear regression analyses. Only statistically significant variables (p < 0.05) were retained in the model.
↵‡ Analysis A: Only funding model variables were forced into the equation, with no adjustment for other factors. Compared with the prevention score for practices in the new capitation model, the score was significantly lower for practices in the established capitation model, whereas the score in the salaried model was superior to that in both the fee-for-service model and the established capitation model.
↵§ Analysis B: Factors considered were variables in analysis A plus contextual factors (rurality index ≥ 4, nearest hospital < 10 km) and patient profile (sex, age, public insurance and number of chronic diseases). Significant variables entered in the equation were age–sex interactions; contextual factors were not significant. In this analysis, the prevention scores were significantly lower for the fee-for-service practices and the practices in the established capitation model than for the practices in the new capitation model, whereas the salaried model had a superior score to the established capitation model only (results not shown).
↵¶ Analysis C: Factors considered were variables in analysis B plus all of the variables contained under “family physician profile” in Table 3. Significant variables entered in the equation were age–sex interaction and presence of ≥ 1 female family physician in the practice. As in Analysis B, prevention scores in this analysis were significantly lower for the fee-for-service practices and the practices in the established capitation model than for practices in the new capitation model. Scores for the salaried model were not statistically different from those for the other funding models (results not shown).
↵** Analysis D: Factors considered were variables in analysis C plus all of the variables contained under “organizational structure” in Table 3. Variables significantly associated with the prevention score and retained in the equation were age–sex interaction, presence of ≥ 1 female family physician in the practice, number of patients per FTE physician and presence of electronic reminder system; organizational factors were not significant. Using the variable “electronic health records” instead of electronic reminder system had a similar effect size (4.6, 95% CI 0.8 to 8.4).
↵†† The four models are known by their financing arrangement: salaried (community health centres), fee for service (fee-for-service practices), new capitation model (family health networks) and established capitation model (health services organizations). See Table 1 for more information.
↵‡‡ The β estimates are very high because the scores in these age/sex groups are driven by the high adherence to recommended guidelines for breast and cervical cancer screening.