Estimates are adjusted means. Bars represent the number of scripts per 1,000 consults and bar labels represent the percentage decreases compared to the no-letter group. See Appendix B for a table of estimates, p-values and confidence intervals. Effect of the letters by month Looking at prescription rates for each month (Figure and the impact of our three 4 Table 2), behaviourally-informed letters increased until September (three months after the letters were sent). At its peak, the letter reduced filled scripts by 14.6 per cent peer comparison with graph (or 17.3 scripts per 1,000 consults). After this, the difference between the group and no-letter the three peer comparison groups began to narrow. At the end of the six-month period, our three behaviourally-informed letters continued to have an impact, with statistically significant reductions ranging from 7.3 per cent to 8.8 per cent (or 6.5 to 7.8 scripts per 1,000 consults). In contrast, the impact of the education-only letter was small and was not always statistically significant at the conventional threshold. Figure 4: Monthly results of each letter (prescription rates) Table 2: Monthly percent change compared to no-letter control group Peer Education with Peer comparison Education-only peer comparison with delayed comparison with graph prescribing July -1.2% -10.7% -9.8% -10.6% (month 1) August -3.4% -12.6% -13.1% -14.6% 2) September -3.4% -12.2% -12.4% -13.6% 3) October -2.4% -9.0% -10.9% -11.5% 4) November -3.3% -8.3% -7.4% -8.5% (month 5) December -1.8% -7.3% -7.4% -8.8% (month 6) See Appendix B, Table 5 for a full table of estimates, confidence intervals and p-values Impact on the total number of scripts filled All up, we estimate our four letters reduced the number of scripts filled by 126,352 over the six-month period after letters were sent compared to the prescribing pattern of GPs who
Estimates are adjusted means. Bars represent the number of scripts per 1,000 consults and bar labels represent the percentage decreases compared to the no-letter group. See Appendix B for a table of estimates, p-values and confidence intervals. Effect of the letters by month Looking at prescription rates for each month (Figure 4 and Table 2), the impact of our three behaviourally-informed letters increased until September (three months after the letters were sent). At its peak, the peer comparison with graph letter reduced filled scripts by 14.6 per cent (or 17.3 scripts per 1,000 consults). After this, the difference between the no-letter group and the three peer comparison groups began to narrow. At the end of the six-month period, our three behaviourally-informed letters continued to have an impact, with statistically significant reductions ranging from 7.3 per cent to 8.8 per cent (or 6.5 to 7.8 scripts per 1,000 consults). In contrast, the impact of the education-only letter was small and was not always statistically significant at the conventional threshold. Figure 4: Monthly results of each letter (prescription rates) Table 2: Monthly percent change compared to no-letter control group Education-only Education with peer comparison Peer comparison with delayed prescribing Peer comparison with graph July (month 1) -1.2% -10.7% -9.8% -10.6% August 2) -3.4% -12.6% -13.1% -14.6% September 3) -3.4% -12.2% -12.4% -13.6% October 4) -2.4% -9.0% -10.9% -11.5% November (month 5) -3.3% -8.3% -7.4% -8.5% December (month 6) -1.8% -7.3% -7.4% -8.8% See Appendix B, Table 5 for a full table of estimates, confidence intervals and p-values Impact on the total number of scripts filled All up, we estimate our four letters reduced the number of scripts filled by 126,352 over the six-month period after letters were sent compared to the prescribing pattern of GPs who
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