Table 5
Prevalence of Prescribing Problems at the End of the Intervention Period
| MOXXI Used at the Visit (1,485 patients) | ||||||||||
| On-demand N = 12 MDs (416 Patients) | Computer-triggered N = 13 MDs (1,069 Patients) | All Patients Visiting During Follow-Up (3,422 patients) | ||||||||
| Prescribing Problems | N | % | N | % | Odds Ratio* | (95% CI) | p-Value | Odds Ratio* | (95% CI) | p-Value |
| Any prescribing problem | 116 | 30.1 | 389 | 38.8 | 1.31 | (0.89–1.92) | 0.17 | 1.03 | (0.80–1.32) | 0.81 |
| By type of problem | ||||||||||
| Drug–disease contraindications | 62 | 16.1 | 213 | 21.3 | 1.09 | (0.83–1.42) | 0.51 | 1.29 | (1.06–1.57) | 0.01 |
| Therapeutic duplication | 21 | 5.4 | 43 | 4.3 | 0.43 | (0.29–0.64) | 0.001 | 0.55 | (0.33–0.90) | 0.02 |
| Cumulative toxicity | 7 | 1.8 | 42 | 4.2 | 1.71 | (0.77–3.79) | 0.19 | 1.20 | (0.79–1.82) | 0.39 |
| Drug interaction | 40 | 10.4 | 125 | 12.5 | 0.91 | (0.51–1.62) | 0.75 | 0.89 | (0.64–1.25) | 1.82 |
| Drug–age contraindication | 8 | 2.1 | 46 | 4.6 | 1.41 | (0.79–2.52) | 0.24 | 1.00 | (0.55–1.82) | 0.98 |
| Dosing error | 21 | 5.4 | 53 | 5.3 | 1.10 | (0.55–2.19) | 0.78 | 1.19 | (0.79–1.80) | 0.39 |
| By severity | ||||||||||
| Level 1: absolutely contraindicated | 24 | 6.2 | 57 | 5.7 | 0.98 | (0.52–1.85) | 0.96 | 1.06 | (0.71–1.58) | 0.77 |
| Level 2: avoid if possible | 37 | 9.6 | 120 | 12.0 | 0.93 | (0.57–1.52) | 0.79 | 0.89 | (0.64–1.24) | 0.51 |
| Level 3: use with caution | 103 | 26.7 | 344 | 1.22 | (0.91–1.65) | 0.18 | 1.03 | (0.82–1.32) | 0.75 | |
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↵* A model was estimated for each type of prescribing problem using logistic regression within a generalized estimating equation framework, and an exchangeable correlation structure was used to account for correlation among residuals for patients of the same physician. All multivariate models were adjusted for patient age, gender, income, number of verified health problems, prior baseline prescribing problem, and number of visits to the study physician.
