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Guthrie B, Yu N, Murphy D, et al. Measuring prevalence, reliability and variation in high-risk prescribing in general practice using multilevel modelling of observational data in a population database. Southampton (UK): NIHR Journals Library; 2015 Oct. (Health Services and Delivery Research, No. 3.42.)
Measuring prevalence, reliability and variation in high-risk prescribing in general practice using multilevel modelling of observational data in a population database.
Show detailsTABLE 29
Indicator | Baseline % | Trend, % change per quarter (95% CI) (if present second line is quadratic term) |
---|---|---|
Composite 1: NSAIDs | 8.30 | –0.39 (–0.46 to –0.32) |
0.011 (0.007 to 0.015) | ||
Composite 2: NSAIDs and antiplatelets | 9.62 | –0.37 (–0.45 to –0.30) |
0.009 (0.005 to 0.013) | ||
Composite 3: drug–disease interactions | 3.85 | –0.042 (–0.049 to –0.036) |
Composite 4: drug–drug interactions | 11.21 | –0.43 (–0.52 to –0.34) |
0.011 (0.0026 to 0.016) | ||
Composite 5: renal adverse effects | 10.18 | –0.16 (–0.21 to –0.11) |
Composite 6: all indicators except CKD | 7.68 | –0.23 (–0.28 to –0.18) |
0.006 (0.003 to 0.009) |
TABLE 30
Indicator | ICC (95% CI), Q1 2005 | ICC (95% CI), Q1 2006 | ICC (95% CI), Q1 2007 | ICC (95% CI), Q1 2008 | ICC (95% CI), Q1 2009 | F-test for difference in variances, Q1 2009 vs. Q1 2005a |
---|---|---|---|---|---|---|
1: Drugs to avoid in heart failure | 0.016 (0.009 to 0.029) | 0.013 (0.006 to 0.025) | 0.013 (0.006 to 0.027) | 0.012 (0.005 to 0.025) | 0.008 (0.003 to 0.022) | p-value < 0.0001 |
2: Beta blockers in asthma | 0.051 (0.034 to 0.075) | 0.048 (0.032 to 0.071) | 0.047 (0.031 to 0.071) | 0.039 (0.025 to 0.061) | 0.036 (0.023 to 0.056) | p-value < 0.004 |
3: LABA use without ICS usea | 0.125 (0.085 to 0.180) | 0.131 (0.091 to 0.184) | 0.151 (0.107 to 0.210) | 0.200 (0.153 to 0.259) | 0.202 (0.149 to 0.268) | p-value < 0.0001 |
4: NSAID in peptic ulcer | 0.041 (0.027 to 0.063) | 0.036 (0.022 to 0.057) | 0.049 (0.032 to 0.075) | 0.062 (0.040 to 0.095) | 0.041 (0.024 to 0.069) | p-value = 0.142 |
5: NSAID in over-75-year-olds | 0.053 (0.041 to 0.069) | 0.065 (0.050 to 0.084) | 0.082 (0.063 to 0.106) | 0.079 (0.060 to 0.103) | 0.087 (0.067 to 0.114) | p-value = 0.0004 |
6: Methotrexate in mixed strengths | 0.151 (0.085 to 0.254) | 0.139 (0.083 to 0.224) | 0.185 (0.118 to 0.278) | 0.227 (0.151 to 0.326) | 0.320 (0.239 to 0.415) | p-value < 0.0001 |
7: COCP in previous thromboembolismb | – | – | – | – | – | – |
8: Oestrogens in previous breast cancerb | – | – | – | – | – | – |
9: Antipsychotics in dementia | 0.074 (0.048 to 0.113) | 0.065 (0.042 to 0.101) | 0.056 (0.034 to 0.089) | 0.069 (0.046 to 0.103) | 0.064 (0.041 to 0.100) | p-value = 0.313 |
10: Parkinson’s diseaseb | – | – | – | – | – | – |
11: NSAID in CKD 3–5a | – | – | 0.051 (0.033 to 0.076) | 0.049 (0.035 to 0.069) | 0.068 (0.050 to 0.091) | p-value < 0.0001 |
12: Drugs to avoid in CKD 4 and 5a | – | – | 0.053 (0.023 to 0.117) | 0.048 (0.023 to 0.098) | 0.009 (0.001 to 0.104) | p-value < 0.0001 |
13: NSAID and OAC | 0.109 (0.053 to 0.213) | 0.132 (0.064 to 0.253) | 0.215 (0.131 to 0.334) | 0.211 (0.122 to 0.340) | 0.167 (0.086 to 0.300) | p-value = 0.0016 |
14: NSAID with aspirin or clopidogrel | 0.057 (0.044 to 0.072) | 0.064 (0.050 to 0.082) | 0.069 (0.054 to 0.088) | 0.077 (0.060 to 0.098) | 0.071 (0.055 to 0.092) | p-value = 0.180 |
15: NSAID with ACE inhibitor/ARB and diuretic | 0.057 (0.042 to 0.075) | 0.054 (0.040 to 0.072) | 0.054 (0.040 to 0.072) | 0.063 (0.048 to 0.083) | 0.069 (0.052 to 0.091) | p-value = 0.063 |
16: Aspirin/clopidogrel with OAC | 0.062 (0.038 to 0.101) | 0.067 (0.041 to 0.106) | 0.046 (0.026 to 0.081) | 0.063 (0.039 to 0.102) | 0.052 (0.030 to 0.089) | p-value = 0.019 |
17: Aspirin and clopidogrel | 0.036 (0.022 to 0.056) | 0.023 (0.013 to 0.038) | 0.048 (0.033 to 0.070) | 0.053 (0.036 to 0.078) | 0.038 (0.024 to 0.061) | p-value = 0.997 |
18: High-risk drug and coumarin OAC | 0.056 (0.025 to 0.121) | 0.027 (0.007 to 0.097) | 0.033 (0.012 to 0.086) | 0.033 (0.013 to 0.081) | 0.023 (0.006 to 0.077) | p-value < 0.0001 |
19: PPDE-5 inhibitor and oral nitrateb | – | – | – | – | – | – |
COCP, combined oral contraceptive pill; OAC, oral anticoagulant.
- a
Q1 2009 vs. Q1 2007 for CKD indicators; degrees of freedom vary from 190,190 to 181,183 as some practices have no eligible patients for some indicators.
- b
Models did not converge reliably and/or distribution of level 2 (practice-level) residuals was very non-normally distributed.
TABLE 31
Indicator | ICC (95% CI), Q1 2005 | ICC (95% CI), Q1 2006 | ICC (95% CI), Q1 2007 | ICC (95% CI), Q1 2008 | ICC (95% CI), Q1 2009 | F-test for difference in variances, Q1 2009 vs. Q1 2005a |
---|---|---|---|---|---|---|
Composite 1: NSAIDs | 0.049 (0.039 to 0.061) | 0.050 (0.040 to 0.063) | 0.055 (0.044 to 0.069) | 0.058 (0.046 to 0.073) | 0.058 (0.046 to 0.073) | p-value = 0.305 |
Composite 2: NSAIDs and antiplatelets | 0.038 (0.030 to 0.047) | 0.037 (0.029 to 0.046) | 0.042 (0.033 to 0.053) | 0.045 (0.036 to 0.057) | 0.043 (0.034 to 0.054) | p-value = 0.465 |
Composite 3: drug–disease interactions | 0.032 (0.024 to 0.035) | 0.032 (0.024 to 0.043) | 0.026 (0.019 to 0.035) | 0.027 (0.020 to 0.036) | 0.025 (0.018 to 0.054) | p-value = 0.018 |
Composite 4: drug–drug interactions | 0.028 (0.022 to 0.036) | 0.027 (0.021 to 0.035) | 0.029 (0.022 to 0.037) | 0.034 (0.027 to 0.045) | 0.030 (0.023 to 0.039) | p-value = 0.730 |
Composite 5: Renal adverse effects | – | – | 0.042 (0.032 to 0.056) | 0.044 (0.034 to 0.058) | 0.051 (0.039 to 0.066) | p-value = 0.040 |
Composite 6: all indicators except CKD | 0.027 (0.021 to 0.035) | 0.027 (0.021 to 0.034) | 0.028 (0.022 to 0.035) | 0.029 (0.022 to 0.037) | 0.025 (0.020 to 0.033) | p-value = 0.470 |
- a
Q1 2009 vs. Q1 2007 for CKD indicators.
- Change over time in high-risk prescribing prevalence and variation between pract...Change over time in high-risk prescribing prevalence and variation between practices: detailed tables and figures - Measuring prevalence, reliability and variation in high-risk prescribing in general practice using multilevel modelling of observational data in a population database
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