Table 2 Impact of interventions to increase medicine use
From: Bridging evidence-practice gaps: improving use of medicines in elderly Australian veterans
Intervention number and topic (number of veterans targeted) | Targeted therapy | Proportion of veterans on targeted therapy at baseline (%) | 24Â month pre-intervention trend | Intervention effect (%) | 20Â month post intervention trend | Estimated number with changed behaviour from intervention; sustained over two years post intervention |
|---|---|---|---|---|---|---|
2: Beta-blockers, take the next step for heart failure (n = 12047) | Increase beta-blocker use | 8.7% | Trend increasing 1.7% per month | 7% (p < 0.0001) | Trend still increasing but reduced to 0.6% per month (p < 0.0001) | 642 |
3: Diabetes triple check (n = 16612) | Increase ACE inhibitor use | 61.3% | Trend increasing 0.3% per month | 1.3% (p < 0.0001) | Trend still increasing but reduced to 0.1% per month (p < 0.0001) | 543 |
Increase lipid lowering therapy use | 47.9% | Trend increasing 0.6% per month | 1.9% (p < 0.0001) | Trend still increasing but reduced to 0.5% per month (p = 0.015) | 1573 | |
Increase antiplatelet use | 41.9% | Trend increasing 0.4% per month | 3% (p < 0.0001) | Trend still increasing but reduced to 0.1% per month (p < 0. 0.0001) | 543 | |
15: Osteoporosis (n = 83110) | Increase use in women | 9.1% | Trend increasing 1.1% per month | 2.8% (p < 0.004) | Trend still increasing but reduced to 0.4% per month (p < 0.0001) | 712 |
Increase use in men | 4.7% | Trend increasing 1.5% per month | 8.3% (p < 0.0001) | Trend still increasing but reduced to 0.2% per month (p < 0.0001) | 2522 |