Table 2:
Factors associated with having a routine chest x-ray based on a mixed-effects logistic regression model, n = 1 709 206
| Fixed effects | OR* (95% CI) |
|---|---|
| Time-based variables | |
| Time (fiscal quarter) | 0.98 (0.98–0.98) |
| April–June v. January–March | 0.92 (0.88–0.96) |
| July–September v. January–March | 0.91 (0.88–0.95) |
| October–November v. January–March | 0.90 (0.86–0.93) |
| Patient characteristics | |
| Age, yr | |
| 45–64 v. 18–44 | 1.82 (1.78–1.86) |
| ≥ 65 v. 18–44 | 2.48 (2.39–2.58) |
| Male | 2.19 (2.14–2.24) |
| Rural | 1.00 (0.95–1.05) |
| Neighbourhood income quintile | |
| 2 v. 1 (lowest) | 0.94 (0.91–0.97) |
| 3 v. 1 (lowest) | 0.85 (0.82–0.87) |
| 4 v. 1 (lowest) | 0.82 (0.79–0.85) |
| 5 v. 1 (lowest) | 0.71 (0.69–0.74) |
| Hospitalization — past 5 yr | 0.89 (0.85–0.93) |
| Mental health diagnosis — past 5 yr | 0.89 (0.86–0.92) |
| Dementia diagnosis — past 5 yr | 1.19 (1.01–1.39) |
| Rheumatologic disease diagnosis — past 5 yr | 1.02 (0.97–1.07) |
| Physician characteristics | |
| Male | 1.55 (1.51–1.59) |
| IMG | 1.01 (0.98–1.03) |
| Years since graduation | |
| 21–30 v. ≤ 20 | 1.21 (1.17–1.24) |
| > 30 v. ≤ 20 | 1.63 (1.59–1.68) |
| Practice characteristics | |
| Primary care practice model† | |
| Family health group v. FFS | 0.92 (0.89–0.96) |
| Family health network v. FFS | 0.73 (0.51–1.03) |
| Family health organization v. FFS | 0.81 (0.77–0.86) |
| Family health team v. FFS | 0.87 (0.82–0.93) |
| Other v. FFS | 1.20 (1.09–1.31) |
| Random effects‡ | |
| Variance (SE) | 0.46 (0.03) |
| MOR (95% CI) | 1.91 (1.86–1.96) |
| ICC,§ % | 12.3 |
Note: CI = confidence interval, CXR = chest x-ray, FFS = fee-for-service, ICC = intraclass correlation coefficient, IMG = international medical graduate, MOR = median odds ratio, OR = odds ratio, SE = standard error. All reported values based on SAS PROC GLIMMIX output; model estimation method = RSPL; denominator degrees of freedom estimation method = between and within (bw); covariance structure = standard variance (vc).
Adjusted for all other factors present in the model/table.
Represents the primary care patient enrollment model that informs practice organization and remuneration.
Estimated based on the distribution of random, practice-specific intercepts.
Calculated using the linear threshold approach.