Investigating the mechanism of impact and differential effect of the Quality Premium scheme on antibiotic prescribing in England: a longitudinal study

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Figure 1. Effect of QP on antibiotic prescribing. The shaded portion around the line represents the 95% CI. The vertical line indicates implementation of the 2015–2016 QP in April 2015. STAR-PU = specific therapeutic group age–sex related prescribing unit
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Figure 2. Association between diabetes prevalence and antibiotic prescribing before and after the 2015–2016 QP (for diabetes prevalence spline terms). The shaded portion around the line represents the 95% CI. QP = Quality Premium
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Figure 3. Association between GP workforce and antibiotic prescribing before and after the 2015–2016 QP (for workforce spline terms). The shaded portion around the line represents the 95% CI. QP = Quality Premium

Table 1. Characteristics of general practices, N = 6251

	Mean, entire study population,2014–2015 & 2015–2016,% (95% CI)	Mean, period before QP,2014–2015,% (95% CI)	Mean, period after QP,2015–2016,% (95% CI)	Mean, top 20% of prescribing practices,2014–2015 & 2015–2016,% (95% CI)
Antibiotic items per STAR-PU	1.057(1.055 to 1.059)	1.106(1.103 to 1.108)	1.009(1.007 to 1.011)	1.357(1.354 to 1.360)
Asthma prevalenceper 100 patients	5.941(5.935 to 5.947)	5.980(5.971 to 5.989)	5.901(5.893 to 5.911)	6.295(6.281 to 6.309)
COPD prevalenceper 100 patients	1.878(1.873 to 1.882)	1.861(1.855 to 1.867)	1.894(1.888 to 1.900)	2.301(2.291 to 2.312)
Cancer prevalenceper 100 patients	2.346(2.342 to 2.350)	2.264(2.258 to 2.270)	2.428(2.421 to 2.434)	2.230(2.291 to 2.309)
CKD prevalenceper 100 patients	4.129(4.119 to 4.139)	4.143(4.129 to 4.157)	4.115(4.101 to 4.129)	4.420(4.398 to 4.442)
Diabetes prevalenceper 100 patients	6.635(6.626 to 6.645)	6.544(6.532 to 6.557)	6.726(6.713 to 6.740)	7.316(7.298 to 7.335)
Opioids prescriptionper 100 patients	3.273(3.265 to 3.282)	3.241(3.229 to 3.253)	3.306(3.293 to 3.318)	4.306(4.285 to 4.328)
Benzodiazepineanxiolytics prescriptionper 100 patients	0.917(0.914 to 0.919)	0.920(0.916 to 0.924)	0.913(0.910 to 0.917)	1.151(1.145 to 1.158)
Benzodiazepinehypnotics prescriptionper 100 patients	1.311(1.308 to 1.315)	1.333(1.328 to 1.338)	1.289(1.284 to 1.294)	1.673(1.664 to 1.682)
GP workforceper 10 000 patients	6.126(6.112 to 6.139)	6.429(6.412 to 6.446)	5.822(5.802 to 5.842)	5.835(5.805 to 5.864)

CKD = chronic kidney disease. COPD = chronc obstructive pulmonary disease. QP = Quality Premium. STAR-PU = specific therapeutic group age–sex related prescribing unit.

Table 2. Association between QP and antibiotic prescribing, N = 6251

	Model without adjustment for practice characteristics	Model with adjustment forpractice characteristics
Co-efficient	95% CI	Co-efficient	95% CI
Lower	Upper	Lower	Upper
2015–2016 QP		-0.172	-0.176	-0.168	-0.166	-0.170	-0.162
Months since QP		0.014	0.013	0.014	0.014	0.013	0.014
Season	Winter	Ref	Ref	Ref	Ref	Ref	Ref
	Spring	-0.040	-0.043	-0.038	-0.044	-0.046	-0.041
	Summer	-0.153	-0.156	-0.150	-0.139	-0.142	-0.136
	Autumn	-0.132	-0.135	-0.129	-0.119	-0.121	-0.116
Comorbidities	Respiratory disease	–	–	–	0.021	0.018	0.024
Comorbidities	Diabetes prevalence	–	–	–	0.028	0.026	0.030
Benzodiazepine anxiolytics prescription		–	–	–	0.123	0.118	0.127
Benzodiazepine hypnotics prescription		–	–	–	0.160	0.157	0.164
GPHC per 10 000 patients(spline terms)	GPHC1 (<4.91)	–	–	–	0.013	0.011	0.015
	GPHC2 (≥4.91 to ≤9.80)	–	–	–	-0.008	-0.010	-0.006
	GPHC3 (≥9.81 to ≤14.72)	–	–	–	0.07	0.002	0.011
	GPHC4 (>14.72)	–	–	–	-0.006	-0.021	0.008

Effects of GPHC are per one increase in GP number per 10 000 patients within each spline term. GPHC = GP headcount. QP = Quality Premium.

Table 3. Subgroup analysis

	Co-efficient	95% CI
Lower	Upper
2015–2016 QP in bottom 80% of prescribers		-0.116	-0.125	-0.106
Effect of 2015–2016 QP in top 20% of prescribers		-0.200	-0.210	-0.187
Top 20% of prescribers		0.309	0.302	0.316
Months since QP		0.013	0.013	0.014
Season	Winter	Ref	Ref	Ref
	Spring	-0.046	-0.049	-0.044
	Summer	-0.148	-0.151	-0.145
	Autumn	-0.124	-0.126	-0.121
Comorbidities prevalence per 100 patients	Respiratory diseases	0.013	0.011	0.015
	Diabetes (<3.93%)	0.097	0.089	0.106
	Diabetes (≥3.93% to ≤7.59%)	0.015	0.012	0.017
	Diabetes (≥7.60% to ≤11.28%) before QP	0.016	0.012	0.021
	Diabetes (≥7.60% to ≤11.28%) after QP	0.007	0.002	0.011
	Diabetes (>11.28%)	0.041	0.030	0.052
GPHC per 10 000 patients, spline terms	GPHC1 (<4.91) before QP	0.015	0.013	0.017
	GPHC1 (<4.91) after QP	0.007	0.005	0.009
	GPHC2 (≥4.91 to ≤9.80) before QP	-0.007	-0.009	-0.005
	GPHC2 (≥4.91 to ≤9.80) after QP	-0.005	-0.007	-0.003
	GPHC3 (≥9.81 to ≤14.72)	0.005	-0.000	0.010
	GPHC4 (>14.72)	-0.007	-0.022	0.008
Benzodiazepine anxiolytics prescription		0.093	0.089	0.097
Benzodiazepine hypnotics prescription		0.118	0.115	0.121

Effects of diabetes are per 1% higher within each spline term. Effects of GPHC are per 1 higher per 10 000 patients within each spline term. GPHC = GP headcount. QP = Quality Premium.

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