Abstract
Objectives
England has invested considerably in diabetes care over recent years through programmes such as the Quality and Outcomes Framework and National Diabetes Audit. However, associations between specific programme indicators and key clinical endpoints, such as emergency hospital admissions, remain unclear. We aimed to examine whether attainment of Quality and Outcomes Framework and National Diabetes Audit primary care diabetes indicators is associated with diabetes-related, cardiovascular, and all-cause emergency hospital admissions.
Design
Historical cohort study.
Setting
A total of 330 English primary care practices, 2010–2017, using UK Clinical Practice Research Datalink.
Participants
A total of 84,441 adults with type 2 diabetes.
Main Outcome Measures
The primary outcome was emergency hospital admission for any cause. Secondary outcomes were (1) diabetes-related and (2) cardiovascular-related emergency admission.
Results
There were 130,709 all-cause emergency admissions, 115,425 diabetes-related admissions and 105,191 cardiovascular admissions, corresponding to unplanned admission rates of 402, 355 and 323 per 1000 patient-years, respectively. All-cause hospital admission rates were lower among those who met HbA1c and cholesterol indicators (incidence rate ratio = 0.91; 95% CI 0.89–0.92; p < 0.001 and 0.87; 95% CI 0.86–0.89; p < 0.001), respectively), with similar findings for diabetes and cardiovascular admissions. Patients who achieved the Quality and Outcomes Framework blood pressure target had lower cardiovascular admission rates (incidence rate ratio = 0.98; 95% CI 0.96–0.99; p = 0.001). Strong associations were found between completing 7–9 (vs. either 4–6 or 0–3) National Diabetes Audit processes and lower rates of all admission outcomes (p-values < 0.001), and meeting all nine National Diabetes Audit processes had significant associations with reductions in all types of emergency admissions by 22% to 26%. Meeting the HbA1c or cholesterol Quality and Outcomes Framework indicators, or completing 7–9 National Diabetes Audit processes, was also associated with longer time-to-unplanned all-cause, diabetes and cardiovascular admissions.
Conclusions
Attaining Quality and Outcomes Framework-defined diabetes intermediate outcome thresholds, and comprehensive completion of care processes, may translate into considerable reductions in emergency hospital admissions. Out-of-hospital diabetes care optimisation is needed to improve implementation of core interventions and reduce unplanned admissions.
Keywords: Type 2 diabetes, Quality and Outcomes Framework, National Diabetes Audit, emergency hospital admissions
Introduction
Individuals with diabetes represent a high proportion of hospital admissions with 18% of all hospital beds in England occupied by those with diabetes, though this figure is as high as 25% in some hospitals.1 Around £5.5 billion is spent on diabetes-related inpatient care in England annually, corresponding to 15% of total National Health Service inpatient care expenditure. Approximately 40% of these costs are due to unplanned admissions.2 Type 2 diabetes mellitus, which accounts for about 90% of all diabetes cases, is associated with emergency care costs that are three times higher than those for people without diabetes.2 This is due to higher all-cause admission and readmission rates, admissions for diabetes-specific causes, greater tendency towards overnight admissions by contrast to day-case admissions and prolonged length of hospital stay.1
Suboptimal diabetes management can result in emergency admissions due to acute metabolic complications (e.g. hyperglycaemic hyperosmolar state, diabetic ketoacidosis, hypoglycaemia) and admissions for microvascular and macrovascular disease in the longer term.3,4 However, much of the human and economic burden of diabetes-related complications is preventable through existing evidence-based interventions.5,6 As such, diabetes is recognised as an ambulatory care-sensitive condition for which timely and effective outpatient care can largely prevent unplanned admissions.7 Relevant primary care-based interventions involve early detection and management of microvascular disease (e.g. through regular retinal screening, foot examinations and renal function monitoring), and assessment and management of micro- and macro-vascular disease risk factors (e.g. blood pressure and glycaemic control).5,6
During the past few decades, significant investments have been made within UK primary care to incentivise implementation of key evidence-based interventions for diabetes secondary prevention.8,9 The Quality and Outcomes Framework is one of the largest pay-for-performance schemes in the world and was introduced throughout the UK in 2004 as part of a new general practitioner contract, under which most general practitioners in England now provide care. The Quality and Outcomes Framework aims to improve the quality of disease management in primary care (including diabetes care) and reduce unwarranted care variations by financially incentivising attainment of specific clinical indicators.10 The National Diabetes Audit was introduced in 2003, was made a compulsory part of the general practitioner contract in 2017 and monitors diabetes-related care process activity. The Quality and Outcomes Framework and National Diabetes Audit clinical indicators were developed based on evidence linking assessed measures to clinical outcomes and standards of good practice. However, evidence is scarce and inconsistent on the relationship between care indicator attainment and clinical outcomes including unplanned admissions.11 Furthermore, associations between achievement of specific Quality and Outcomes Framework and National Diabetes Audit care indicators and unplanned hospital admissions among people with type 2 diabetes mellitus have not been studied in longitudinal studies.11,12 Considering the ongoing rise in unplanned admissions, it is important to understand its links with utilisation of evidence-based interventions in primary care to inform prioritisation of National Health Service resources and optimisation of service delivery. This study aimed to assess whether meeting Quality and Outcomes Framework clinical HbA1c, blood pressure and cholesterol thresholds, or completing National Diabetes Audit care process indicators, is associated with diabetes-related, cardiovascular and all-cause-unplanned hospital admissions among people with type 2 diabetes mellitus.
Methods
Study design and data sources
The UK Clinical Practice Research Datalink GOLD database was used to create this historical cohort. Clinical Practice Research Datalink GOLD contains routinely collected primary care data since 1987 for about 50 million people in the UK, including 14 million currently registered across participating practices. The database is representative of the UK primary care-registered population. Linked Hospital Episode Statistics emergency admissions data and Office for National Statistics mortality data are available for most of the Clinical Practice Research Datalink patients in England. The database has previously been used in several studies of diabetes-related primary care practice and indicators.13,14
Adults with an existing type 2 diabetes mellitus diagnosis and linked Hospital Episode Statistics data were eligible to enter the cohort on 1 April 2010 if they were at least 18 years old, had been registered with their practice – with that practice uploading data into Clinical Practice Research Datalink – for at least one year, and were not censored by 1 April 2011. Those ever diagnosed with type 1 diabetes or another specified form of diabetes other than type 2 diabetes mellitus were excluded. Those prescribed insulin treatment within three months (if diagnosis first recorded at ≥35 years) or within six months (if first recorded diagnosis at <35 years) of diagnosis were excluded due to likelihood of type 1 diabetes.15 Individuals were censored at the first occurrence of any of last Clinical Practice Research Datalink data upload; transfer out of general practice; death; or 31 December 2017 (end of study period). As study exposures at baseline were assessed between 1 April 2010 and 31 March 2011, and outcomes only thereafter, those censored prior to 31 March 2011 were excluded. Those with Quality and Outcomes Framework general diabetes exception reporting codes recorded for 2010–2011, or a diabetes resolved code recorded later than their most recent diabetes diagnosis code and prior to 31 March 2011, were also excluded. Supplementary File 1 contains code lists applied in defining the cohort and study variables provided below.
Exposures
Exposures were defined as attainment, within the 2010–2011 financial year, of the Quality and Outcomes Framework HbA1c (≤59 mmol/mol), blood pressure (≤140/80 mmHg) and total cholesterol (≤5 mmol/L) indicators. Indicator status was determined using most recent measurements during the exposure period, as per Quality and Outcomes Framework Business Rules v38.0.16 If no measurement was taken during the exposure period, no attainment was assigned. Additional exposures describing implementation of National Diabetes Audit annual care processes over the same period were constructed as categorisations of 0–3, 4–6 or 7–9 processes completed.
Outcomes
The primary outcome was unplanned hospital admission for any cause, defined as first Hospital Episode Statistics episode recorded as an emergency admission, where there has been no prior admission in the same month. Secondary outcomes were (1) diabetes-related emergency admission with a record of a section E10–E14 ICD10 code in the first episode of a Hospital Episode Statistics inpatient spell with no previous such admission in the same month and (2) cardiovascular-related emergency admission with a Chapter IX ICD10 code, again with no such prior admission in the same month.
Covariates
Covariates were measured at baseline and included socio-demographic (age, sex, ethnicity and 2010 patient-level index of multiple deprivation), primary care practice geographical region, lifestyle (body mass index, smoking status and alcohol consumption), and disease- and co-morbidity-related variables. Disease-related variables included years since diabetes diagnosis, number of diabetes complications, as well as the number of glucose lowering therapies prescribed and the presence of insulin prescription – both of which were measured in the six months before cohort entry. Co-morbidities were defined by the number of Quality and Outcomes Framework registers in 2010–2011 on which the patient appeared, number of hospital admissions in the same year and number of prescriptions issued in the six months prior to cohort entry. Supplementary File 2 contains complete variable definitions.
Statistical analysis
Cohort baseline characteristics were summarised, including missingness among variables. Practice-level index of multiple deprivation values were used to impute missing patient-level index of multiple deprivation data. Missing ethnicity and lifestyle variables were imputed using the mice package17 in RStudio 3.5.1 from the remaining covariates by employing five imputations. To reduce confounding, logistic regression models, in which each exposure was the response, were used to produce a balanced sample across patient characteristics using nearest neighbour 1:1 propensity score matching through the matchit package,18 with a caliper of 0.2 for each exposure.19 Univariate and multivariate Poisson regression models were implemented using the matched samples for each exposure with the respective exposure included as a covariate. Resulting unadjusted and adjusted incidence rate ratios were produced, denoting the differential incidence of each outcome by exposure status, for each exposure. Concordance statistics were computed for each of the multivariate models. A secondary analysis was performed to explore time-to-first hospitalisation from the matched samples. Univariate and multivariate Cox proportional hazard models were implemented, and hazard ratios for the exposure definitions were produced. Sensitivity analyses were conducted for all unplanned admission outcomes to explore the impact of Quality and Outcomes Framework indicator achievement among those who met the remaining two indicators (i.e. participants not considered as the exposure).
Results
Data availability and cohort characteristics
The study included 84,441 adults (44.2% female), registered across 330 practices, who were diagnosed with type 2 diabetes mellitus before 1 April 2010. Table 1 summarises cohort baseline characteristics. The average age was 68.0 (SD 12.5) years with a mean diabetes duration of 7.4 (SD 5.5) years; 83.6% were of white ethnicity, and deprivation was approximately evenly distributed across quintiles. The majority were overweight or obese (83.4%), current or ex-smokers (51.8%), and/or consumed alcohol (70.5%). Individuals experienced an average of 2.4 (SD 1.7) co-morbidities and 1.7 (SD 1.3) diabetic complications. They received a median of 6.0 (interquartile range, IQR 3–12) different prescriptions and an average of 1.3 (SD 1.0) glucose lowering therapies within six months prior to baseline, with insulin prescribed to 12,014 patients (14.2%) in that period.
Table 1.
Baseline characteristics and outcome summaries of the cohort of people with type 2 diabetes (N = 84,441).
| Variable | n, mean, or median | %, SD, or IQR |
|---|---|---|
| Age, years (mean, SD) | 68 | 12.5 |
| Sex: Female (n, %) | 37,342 | 44.2 |
| Ethnicity (n, %) | ||
| Asian | 4904 | 5.8 |
| Black | 1760 | 2.1 |
| Mixed | 559 | 0.7 |
| Other | 966 | 1.1 |
| White | 70,599 | 83.6 |
| Missing | 5653 | 6.7 |
| Index of multiple deprivation quintile (n, %) | ||
| 0 (Least deprived) | 16,134 | 19.1 |
| 1 | 19,104 | 22.6 |
| 2 | 17,350 | 20.6 |
| 3 | 17,258 | 20.4 |
| 4 (Most deprived) | 14,552 | 17.2 |
| Missing | 43 | 0.1 |
| Region (n, %) | ||
| North East | 2176 | 2.6 |
| North West | 14,794 | 17.5 |
| Yorkshire & The Humber | 3275 | 3.9 |
| East Midlands | 1841 | 2.2 |
| West Midlands | 10,051 | 11.9 |
| East of England | 8718 | 10.3 |
| South West | 11,464 | 13.6 |
| South Central | 10,149 | 12 |
| London | 11,065 | 13.1 |
| South East Coast | 10,908 | 12.9 |
| Weight status according to body mass index in kg/m2 (n, %) | ||
| Underweight (<18.5) | 639 | 0.8 |
| Normal weight (18.5–24.9) | 12,477 | 14.8 |
| Overweight (25.0–29.9) | 28,182 | 33.4 |
| Obese (30+) | 42,225 | 50 |
| Missing | 918 | 1.1 |
| Smoking status (n, %) | ||
| Never smoker | 40,457 | 47.9 |
| Ex-smoker | 32,027 | 37.9 |
| Current smoker | 11,750 | 13.9 |
| Missing | 207 | 0.3 |
| Alcohol consumption in units/week (n, %) | ||
| None | 13,996 | 16.6 |
| 1–14 | 49,558 | 58.7 |
| 15–42 | 8186 | 9.7 |
| >42 | 1801 | 2.1 |
| Missing | 10,900 | 12.9 |
| Co-morbid conditions (mean, SD) | 2.4 | 1.7 |
| Glucose-lowering therapiesa (mean, SD) | 1.3 | 1 |
| Insulin prescription (number, %) | 12,014 | 14.2 |
| Other medications prescribed (median, IQR) | 6 | 3–12 |
| Hospitalisations (mean, SD) | 0.2 | 0.6 |
| 0 (number, %) | 74,255 | 87.9 |
| 1 (number, %) | 7596 | 9 |
| >1 (number, %) | 2590 | 3.1 |
| Duration of diabetes (years, SD) | 7.4 | 5.5 |
| Complications (mean, SD) | 1.7 | 1.3 |
| Follow-up time, years (mean, SD) | 3.9 | 2 |
| Diabetes-related emergency admissions (number) | 115,425 | |
| Diabetes-related emergency admissions rate per 1000 patient-years | 354.6 | |
| Cardiovascular emergency admissions | 105,191 | |
| Cardiovascular emergency admissions rate per 1000 patient-years | 323.1 | |
| All-cause emergency admissions | 130,709 | |
| All-cause emergency admissions rate per 1000 patient-years | 401.5 | |
SD: standard deviation; IQR: interquartile range.
aIncludes insulin.
Across a total follow-up period of 6.75 years (mean 3.9 (SD 2.0) years), there were 130,709 emergency admissions for any cause, including 115,425 and 105,191 diabetes and cardiovascular-related admissions, respectively. This corresponds to unplanned admission rates of 401.5, 354.6 and 323.1, respectively, per 1000 patient-years.
Table 2 presents the distribution of Quality and Outcomes Framework indicator attainment and National Diabetes Audit process completion by the number of indicators/processes met. HbA1c, blood pressure and cholesterol Quality and Outcomes Framework indicators were achieved by 55,022 (65.2%), 49,124 (58.2%) and 63,603 (75.3%) adults, respectively; 27,880 (33.0%) met all three indicators, with slightly more (n = 33,348, 39.5%) achieving two indicators. There were 4819 (5.7%), 3327 (3.9%) and 7780 (9.2%) individuals who did not have a measurement for HbA1c, blood pressure and cholesterol, respectively, Quality and Outcomes Framework indicators during the exposure period and were considered as not attaining the respective indicator. Among National Diabetes Audit processes completed, the range was from 55,253 (65.4%; retinal screening) to 81,114 (96.1%; blood pressure screening). Although fewer than half (n = 35,688, 42.3%) completed all nine National Diabetes Audit processes, most (n = 71,227, 84.4%) completed 7–9 processes.
Table 2.
Number (%) of individuals who attained each of the QOF indicators and NDA processes (columns) by the number of QOF indicators met or NDA processes completed (rows).
| QOF target achieved |
NDA process achieved |
||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No. of QOF Targets/NDA processes met | Total | HbA1c | Blood pressure | Cholesterol | HbA1c | Blood pressure | Cholesterol | Serum creatine | Urine ACR | Foot exam | Body mass index | Smoking history | Retinal screen |
| 0 QOF targets | 5800 (6.9%) | 0 (0%) | 0 (0%) | 0 (0%) | 3097 (53.4%) | 3960 (68.3%) | 2580 (44.5%) | 3273 (56.4%) | 2389 (41.2%) | 2873 (49.5%) | 3353 (57.8%) | 3284 (56.6%) | 3009 (51.9%) |
| 1 QOF target | 17,413 (20.6%) | 4859 (27.9%) | 4238 (24.3%) | 8316 (47.8%) | 15,743 (90.4%) | 16,632 (95.5%) | 14,404 (82.7%) | 15,673 (90.0%) | 12,364 (71%) | 13,511 (77.6%) | 15,081 (86.6%) | 13,942 (80.1%) | 10,853 (62.3%) |
| 2 QOF targets | 33,348 (39.5%) | 22,283 (66.8%) | 17,006 (51%) | 27,407 (82.2%) | 32,902 (98.7%) | 32,642 (97.9%) | 31,797 (95.4%) | 32,565 (97.7%) | 26,883 (80.6%) | 28,650 (85.9%) | 30,805 (92.4%) | 28,473 (85.4%) | 22,319 (66.9%) |
| All 3 QOF targets | 27,880 (33.0%) | 27,880 (100%) | 27,880 (100%) | 27,880 (100%) | 27,880 (100%) | 27,880 (100%) | 27,880 (100%) | 27,658 (99.2%) | 23,886 (85.7%) | 25,039 (89.8%) | 26,461 (94.9%) | 24,577 (88.2%) | 19,072 (68.4%) |
| 0–3 NDA processes | 3520 (4.2%) | 418 (11.9%) | 811 (23.0%) | 244 (6.9%) | 668 (19.0%) | 1608 (45.7%) | 349 (9.9%) | 749 (21.3%) | 160 (4.6%) | 298 (8.5%) | 464 (13.2%) | 643 (18.3%) | 1140 (32.4%) |
| 4–6 NDA processes | 9694 (11.5%) | 5251 (54.2%) | 5013 (51.7%) | 5129 (52.9%) | 8057 (83.1%) | 8689 (89.6%) | 6627 (68.4%) | 7771 (80.2%) | 2972 (30.7%) | 3311 (34.2%) | 5537 (57.1%) | 4303 (44.4%) | 4053 (41.8%) |
| 7–9 NDA processes | 71,227 (84.4%) | 49,353 (69.3%) | 43,300 (60.8%) | 58,230 (81.8%) | 70,897 (99.5%) | 70,817 (99.4%) | 69,685 (97.8%) | 70,649 (99.2%) | 62,390 (87.6%) | 66,464 (93.3%) | 69,699 (97.9%) | 65,330 (91.7%) | 50,060 (70.3%) |
| All 9 NDA processes | 35,688 (42.3%) | 25,511 (71.5%) | 21,960 (61.5%) | 30,411 (85.2%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) |
| Total | 84,441 (100%) | 55,022 (65.2%) | 49,124 (58.2%) | 63,603 (75.3%) | 79,622 (94.3%) | 81,114 (96.1%) | 76,661 (90.8%) | 79,169 (93.8%) | 65,522 (77.6%) | 70,073 (83%) | 75,700 (89.7%) | 70,276 (83.2%) | 55,253 (65.4%) |
QOF: Quality and Outcomes Framework; NDA: National Diabetes Audit; HbA1c: glycated haemoglobin; ACR: albumin creatinine ratio; QOF targets: HbA1c ≤ 59 mmol/mol; blood pressure ≤ 140/80 mmHg; total cholesterol ≤ 5 mmol/L.
Associations between Quality and Outcomes Framework indicator exposures and unplanned admissions
Table 3 presents unadjusted and adjusted incidence rate ratios describing the differential incidence of each unplanned admissions outcome among the exposed versus unexposed, for each exposure representing attainment of each Quality and Outcomes Framework indicator. Key adjusted incidence rate ratio estimates and corresponding 95% confidence intervals are displayed in Figure 1. Unadjusted and adjusted incidence rate ratios show similar estimates for HbA1c and cholesterol indicators, yielding associations of indicator attainment with lower rates of unplanned admissions for any cause, as well as diabetes- and cardiovascular-related emergency admissions. Adjusting for all covariates, those who met HbA1c and cholesterol indicators had a significant incidence rate reduction of 9% (incidence rate ratio = 0.91; 95% CI 0.89–0.92; p < 0.001) and 13% (incidence rate ratio = 0.87, 95% CI 0.86–0.89; p < 0.001), respectively, for any unplanned hospital admission, for example. Blood pressure indicator attainment, conversely, was associated with higher rates of all types of unplanned admission outcomes in unadjusted analyses, as well as with diabetes-related unplanned admissions in the multivariate analysis (incidence rate ratio = 1.01; 95% CI 1.00–1.03; p = 0.04). However, this higher rate was non-significant for any unplanned admission (incidence rate ratio = 1.01; 95% CI 0.99–1.02; p = 0.36). Blood pressure attainment was associated with a lower rate of cardiovascular-related emergency admissions (incidence rate ratio = 0.98; 95% CI 0.96–0.99; p = 0.001), when adjusting for all covariates.
Table 3.
Univariate and multivariate incidence rate ratios (with corresponding 95% CIs and p-values) across hospital emergency admission outcomes and QOF indicator/NDA care process exposures after 1:1 propensity score matching.
| Univariate analyses |
Multivariate analysesa |
||||||||
|---|---|---|---|---|---|---|---|---|---|
| Outcome | Exposure | N after PSM | No. of Adm. | IRR | 95% CI | p | IRR | 95% CI | p |
| All emergency admissions | Achieve HbA1c QOF target | 53,878 | 83,987 | 0.91 | 0.90–0.92 | <0.001 | 0.91 | 0.89–0.92 | <0.001 |
| Achieve blood pressure QOF target | 70,582 | 107,429 | 1.09 | 1.08–1.10 | <0.001 | 1.01 | 0.99–1.02 | 0.36 | |
| Achieve cholesterol QOF target | 41,626 | 63,807 | 0.90 | 0.88–0.91 | <0.001 | 0.87 | 0.86–0.89 | <0.001 | |
| Achieve all QOF targets | 55,760 | 87,744 | 0.94 | 0.93–0.95 | <0.001 | 0.94 | 0.92–0.95 | <0.001 | |
| Meet 4–6 NDA processes (vs. meet 0–3 NDA processes) | 6926 | 10,807 | 1.04 | 1.00–1.08 | 0.04 | 0.97 | 0.94–1.01 | 0.19 | |
| Meet 7–9 NDA processes (vs. meet 0–3 NDA processes) | 19,370 | 33,415 | 0.86 | 0.84–0.88 | <0.001 | 0.85 | 0.84–0.87 | <0.001 | |
| Meet 7–9 NDA Processes (vs. meet 4–6 NDA processes) | 6978 | 10,199 | 0.89 | 0.86–0.92 | <0.001 | 0.81 | 0.78–0.84 | <0.001 | |
| Meet all NDA processes | 71,376 | 107,732 | 0.75 | 0.74–0.76 | <0.001 | 0.75 | 0.74–0.76 | <0.001 | |
| Diabetes-related emergency admissions | Achieve HbA1c QOF target | 53,878 | 75,523 | 0.89 | 0.88–0.90 | <0.001 | 0.89 | 0.88–0.90 | <0.001 |
| Achieve blood pressure QOF target | 70,582 | 94,859 | 1.10 | 1.09–1.11 | <0.001 | 1.01 | 1.00–1.03 | 0.04 | |
| Achieve cholesterol QOF target | 41,626 | 55,791 | 0.91 | 0.90–0.93 | <0.001 | 0.88 | 0.87–0.90 | <0.001 | |
| Achieve all QOF targets | 55,760 | 76,691 | 0.96 | 0.95–0.98 | <0.001 | 0.95 | 0.94–0.96 | <0.001 | |
| Meet 4–6 NDA processes (vs. meet 0–3 NDA processes) | 6926 | 9180 | 1.06 | 1.01–1.10 | 0.01 | 0.98 | 0.94–1.02 | 0.25 | |
| Meet 7–9 NDA processes (vs. meet 0-3 NDA processes) | 19,370 | 29,467 | 0.88 | 0.86–0.90 | <0.001 | 0.87 | 0.85–0.89 | <0.001 | |
| Meet 7–9 NDA processes (vs. meet 4–6 NDA processes) | 6978 | 8781 | 0.93 | 0.89–0.97 | <0.001 | 0.83 | 0.80–0.87 | <0.001 | |
| Meet all NDA processes | 71,376 | 95,392 | 0.76 | 0.75–0.77 | <0.001 | 0.76 | 0.75–0.77 | <0.001 | |
| Cardiovascular emergency admissions | Achieve HbA1c QOF target | 53,878 | 67,126 | 0.93 | 0.91–0.94 | <0.001 | 0.92 | 0.91–0.93 | <0.001 |
| Achieve blood pressure QOF target | 70,582 | 86,560 | 1.07 | 1.06–1.09 | <0.001 | 0.98 | 0.96–0.99 | 0.001 | |
| Achieve cholesterol QOF target | 41,626 | 49,940 | 0.95 | 0.93–0.96 | <0.001 | 0.91 | 0.89–0.92 | <0.001 | |
| Achieve All QOF targets | 55,760 | 70,852 | 0.95 | 0.93–0.96 | <0.001 | 0.94 | 0.93–0.96 | <0.001 | |
| Meet 4–6 NDA processes (vs. meet 0–3 NDA processes) | 6926 | 7978 | 1.14 | 1.09–1.19 | <0.001 | 1.03 | 0.98–1.08 | 0.20 | |
| Meet 7–9 NDA processes (vs. meet 0–3 NDA processes) | 19,370 | 26,875 | 0.88 | 0.86–0.90 | <0.001 | 0.87 | 0.85–0.89 | <0.001 | |
| Meet 7–9 NDA processes (vs. meet 4–6 NDA processes) | 6978 | 7688 | 0.99 | 0.95–1.03 | 0.60 | 0.87 | 0.83–0.91 | <0.001 | |
| Meet all NDA processes | 71,376 | 87,438 | 0.76 | 0.75–0.77 | <0.001 | 0.77 | 0.76–0.78 | <0.001 | |
QOF: Quality and Outcomes Framework; NDA: National Diabetes Audit; HbA1c: glycated haemoglobin; PSM: propensity score matching; Adm.: hospital admissions; IRR: incidence rate ratio; CI: confidence interval; p: p-value.
aAdjusted for age, sex, ethnicity, index of multiple deprivation, practice region, weight status, smoking status, alcohol consumption, co-morbidities, hospitalisations, duration of diabetes, diabetic complications, glucose lowering therapies, and insulin prescription status.
Figure 1.
Key adjusted incidence rate ratio estimates (and corresponding 95% CIs) across emergency admission outcomes for each exposure.
When measuring time-to-unplanned admission, HbA1c indicator attainment was associated with significant risk reductions across outcome measures, with adjusted hazard ratios ranging from 0.89 (95% CI 0.86–0.91; p < 0.001) to 0.93 (95% CI 0.90–0.95; p < 0.001). Cholesterol indicator attainment was also associated with significant risk reductions across all outcome measures, with adjusted hazard ratios ranging from 0.86 (95% CI 0.84–0.89; p < 0.001) to 0.89 (95% CI 0.86–0.92; p < 0.001). Blood pressure indicator attainment was non-significant across all outcome measures within adjusted time-to-unplanned admission analyses (p-values ≥ 0.11). Supplementary File 3 contains full model results, including unadjusted and adjusted incidence rate ratio and hazard ratio estimates for all covariates.
Associations between National Diabetes Audit process completion exposures and unplanned admissions
Unadjusted and adjusted incidence rate ratios summarising associations between National Diabetes Audit process groupings and unplanned admission outcomes are provided in Table 3. Key adjusted incidence rate ratio estimates and corresponding 95% confidence intervals are shown in Figure 1. Upon adjusting for model covariates and among most emergency admission outcomes and comparisons, incidence rates were lower for those completing more National Diabetes Audit processes. Evidence from all multivariate analyses suggests strong associations between completing 7–9 (versus either 4–6 or 0–3) processes and reduced rates of all types of unplanned admissions (p-values < 0.001). Meeting all nine National Diabetes Audit processes had a significant effect on substantially reducing all types of unplanned admissions by between 22% and 26%. Small differences observed among comparisons between completion of 4–6 versus 0–3 processes were non-significant (p-values ≥ 0.19).
When measuring time-to-unplanned admission, completing 7–9 National Diabetes Audit processes (versus either 4–6 or 0–3) was associated with significant risk reductions, with adjusted hazard ratios ranging from 0.83 (95% CI 0.79–0.87; p < 0.001) to 0.87 (95% CI 0.80–0.95; p = 0.003). Completing 4–6 processes (versus 0–3) was not associated with significant risk reductions for any outcome (p-values ≥ 0.38). Supplementary File 3 provides full model results, including unadjusted and adjusted incidence rate ratio and hazard ratio estimates for all covariates.
There are no consistently significant associations between ethnicity and unplanned admissions across outcomes. However, some ethnicities show more consistency than others (Supplementary File 3). For example, upon accounting for meeting any of the Quality and Outcomes Framework indicators, those of Asian ethnic background have significantly lower rates of between 3% and 12% for diabetes-related and 5% and 13% for all-cause admissions compared to white patients (p < 0.001); however, this is not the case for cardiovascular unplanned admissions (p > 0.37). Similar results were found across all National Diabetes Audit process comparisons with rate reductions of 2%–19% for diabetes-related admissions (p < 0.02) and 4%–20% reductions in rates of all-cause admissions (p < 0.01) compared to white individuals.
Sensitivity analyses
Results of multivariate analyses with HbA1c – and separately cholesterol – Quality and Outcomes Framework indicators conditioning on those who had met the other two Quality and Outcomes Framework indicators (i.e. those not considered as the exposure) were similar to those from our primary analyses. Consistent with primary analysis results, blood pressure Quality and Outcomes Framework indicator achievement among those who had met the other two indicators was associated with a significant increase in the diabetes-related unplanned admission incidence rate (incidence rate ratio = 1.05, 95% CI 1.03–1.07, p < 0.001). In contrast to primary analysis results, blood pressure Quality and Outcomes Framework indicator attainment among those who had met the other two indicators was associated with a significant increase in any unplanned hospital admission (incidence rate ratio = 1.04, 95% CI 1.03–1.06, p < 0.001), though with a non-significant increase in the cardiovascular emergency admission incidence rate (incidence rate ratio = 1.01, 95% CI 0.99–1.03, p = 0.44). Supplementary File 3 contains full results of the sensitivity analyses.
Discussion
Diabetes, cardiovascular and all-cause unplanned hospital admission rates were 7%–12% lower among those who met the Quality and Outcomes Framework HbA1c indicator, and 8%–14% lower among those who met the cholesterol indicator. By contrast, univariate analyses demonstrated that blood pressure indicator attainment was associated with higher rates of all types of unplanned admission. However, this association only persisted for diabetes-related admissions in multivariate analyses, and blood pressure attainment was associated with a significantly lower rate of cardiovascular-related unplanned admissions after adjustment for confounders. Longer latency to diabetes, cardiovascular and all-cause unplanned admissions was also observed among those who met the HbA1c or cholesterol indicators, and again an association was not observed for the blood pressure indicator. Completing 7–9 National Diabetes Audit processes was associated with lower rates of all types of unplanned admissions, and meeting all nine National Diabetes Audit care processes was linked to 22%–26% lower rates for all types of unplanned admissions.
Although there is a large body of literature available on the impacts of Quality and Outcomes Framework on incentivised activities and service delivery, evidence is limited on associations between Quality and Outcomes Framework clinical targets and health outcomes including emergency admissions.11,12,20 The literature available on Quality and Outcomes Framework and emergency admissions is limited to a few studies assessing impacts of Quality and Outcomes Framework on demands for secondary acute care.11,12 A previous study showed that increases in emergency hospital admission rates for ambulatory care-sensitive conditions incentivised in Quality and Outcomes Framework were modestly lower compared with that for non-incentivised ambulatory care-sensitive conditions.3 The few studies examining the associations between achievement of Quality and Outcomes Framework indicators and unplanned admissions reported small and inconsistent associations.21, 23 These studies were cross-sectional ecological and used aggregate performance or other measures rather than specific clinical care indicators. Dusheiko et al. studied the link between general practices’ recorded glycaemic control and emergency diabetes-related admissions in a longitudinal ecological study, and reported negative associations at a practice-level.24
Timely and effective interventions can substantially reduce the risk of adverse clinical outcomes in people with type 2 diabetes.5 Our study demonstrates that meeting treatment targets for cholesterol, HbA1c and blood pressure at thresholds defined by Quality and Outcomes Framework may translate into lower risk of emergency hospital admissions in this patient group. Results were consistent for HbA1c and cholesterol across all emergency admission causes, which largely corresponds with evidence from randomised clinical trials demonstrating treatment benefits.25 It is notable that Quality and Outcomes Framework HbA1c indicator attainment was associated with lower unplanned admission rates for cardiovascular causes. Although the benefits of intensive glycaemic control on microvascular disease are well established, previous evidence of its impact on cardiovascular disease has been conflicting apart from reductions in the risk of non-fatal myocardial infarction.26,27 Although the glycaemic threshold in Quality and Outcomes Framework is considerably higher than glucose lowering targets in clinical trials, recent evidence has shown that macrovascular outcomes can be improved without aggressive HbA1c lowering.27 The relatively high glycaemic threshold may also have reduced the risk of severe hypoglycaemic episodes requiring emergency admissions.26 Inconsistent associations between blood pressure target attainment and emergency admissions are likely to be due to reverse causality, or possibly other unmeasured confounders, whereby patients with multiple comorbidities who are at higher risk of emergency admissions may have lower blood pressure levels, such as patients with heart failure.28 This is supported by the observation that associations for cardiovascular admissions changed direction after adjustment for study covariates.
Our study demonstrates that core evidence-based interventions in diabetes care may significantly reduce emergency hospital admissions. Given considerable pressures on the National Health Service, particularly during the COVID-19 pandemic, it is a priority to reduce avoidable hospital admissions and associated human suffering and economic burden. The priority of reducing pressure on emergency hospital services has been emphasised by the National Health Service Long Term Plan alongside a vision for community service redesigns and boosts in out-of-hospital care.29 Although the Quality and Outcomes Framework drove improvements in some aspects of care, particularly in its early years, it has been subject to ongoing and growing criticism.20 Among numerous other concerns, critiques argue that it might pose a barrier towards a more holistic, patient-centred and sophisticated personalised care. Our results highlight the suboptimal implementation of readily available interventions with only one-third of patients meeting all three Quality and Outcomes Framework indicators and less than half completing all 9 National Diabetes Audit care processes. Although the Quality and Outcomes Framework has had positive effects of some aspects of delivery of diabetes care, there was a consensus that it required substantial reforms to improve patient outcomes, reduce harm from the potential overuse of pharmacological therapies and take a holistic view of care to prevent avoidable complications.30 Many of the recommendations around diabetes care were subsequently implemented from April 2019.31
To our knowledge, this is the first published study to have assessed associations between Quality and Outcomes Framework indicator and National Diabetes Audit process attainment with unplanned hospital admissions. Our findings are based on the use of a large sample reasonably representative of those utilising primary care in England. As there is widespread participation in the Quality and Outcomes Framework, and standardised and Quality and Outcomes Framework coding requirements have been relatively stable over time, missing indicator-related data were relatively low, ranging approximately 4%–9%. The exclusion of those who were generally exception reported (e.g. patient informed dissent or unsuitability), thus for whom interventions may be considered inappropriate by the patient or clinician, provide a suitable representation of the study population. However, following Quality and Outcomes Framework Business Rules,16 we did not exclude those related to a lack of service provision, as interventions are likely to be appropriate for this group. As Hospital Episode Statistics data are well established and generally considered to be of relatively high quality, our outcome data are also likely to be reasonably reliable. The data allowed for adjustment for numerous potential confounders through propensity score matching and multivariate analyses. The limitations of the study include that the exposure definition was limited to a single year, despite that standard attainment may be time-variable and the exposure effects cumulative. Some correlation of measurements across time would be anticipated, but associated dilution of any effect is likely. There may be other sources of confounding unaccounted for, and/or the potential for reverse causation, which may be seen in blood pressure results.32 Additional limitations include variation in timing of lifestyle variable measurements and missing data. Coding missing clinical outcome information as representative of non-attainment of the relevant indicator in the primary analysis (as per Quality and Outcomes Framework Business Rules)16 may result in bias with regard to association between the clinical indices and outcomes themselves. The National Diabetes Audit process analyses using categorisations of count measures do not allow for support of specific processes, though our findings support more comprehensive implementation, and support for uptake, of these processes.
Comprehensive completion of evidence-based care processes and attainment of Quality and Outcomes Framework diabetes intermediate outcome indicator thresholds may translate into considerable reductions in emergency hospital admissions among people with type 2 diabetes. However, further improvement, including measures to support interventions, in out-of-hospital diabetes care is needed to optimise implementation of core interventions. This would help reduce avoidable complications and unplanned admissions in this population with a disproportionate share of hospital admissions and emergency care.
Supplemental Material
Supplemental material, sj-pdf-1-jrs-10.1177_01410768211005109 for Associations between attainment of incentivised primary care indicators and emergency hospital admissions among type 2 diabetes patients: a population-based historical cohort study by Laura H Gunn, Ailsa J McKay, Mariam Molokhia, Jonathan Valabhji, German Molina, Azeem Majeed and Eszter P Vamos in Journal of the Royal Society of Medicine
Supplemental material, sj-pdf-2-jrs-10.1177_01410768211005109 for Associations between attainment of incentivised primary care indicators and emergency hospital admissions among type 2 diabetes patients: a population-based historical cohort study by Laura H Gunn, Ailsa J McKay, Mariam Molokhia, Jonathan Valabhji, German Molina, Azeem Majeed and Eszter P Vamos in Journal of the Royal Society of Medicine
Supplemental material, sj-pdf-3-jrs-10.1177_01410768211005109 for Associations between attainment of incentivised primary care indicators and emergency hospital admissions among type 2 diabetes patients: a population-based historical cohort study by Laura H Gunn, Ailsa J McKay, Mariam Molokhia, Jonathan Valabhji, German Molina, Azeem Majeed and Eszter P Vamos in Journal of the Royal Society of Medicine
Footnotes
Acknowledgements: None.
Provenance: Not commissioned; peer-reviewed by Julie Morris, Joana Rigor, and Karla Calumet.
Supplemental material: Supplemental material for this article is available online.
ORCID iDs: Laura H Gunn http://orcid.org/0000-0003-3962-4526 Azeem Majeed http://orcid.org/0000-0002-2357-9858
Declarations
Competing interests: JV is National Clinical Director for Diabetes and Obesity at NHS England & NHS Improvement.
Funding: This report is independent research supported by the National Institute for Health Research Applied Research Collaboration Northwest London. This work was also supported by funds provided by the University of North Carolina at Charlotte. The views expressed in this publication are those of the authors and not necessarily those of the National Institute for Health Research, Department of Health and Social Care, or University of North Carolina at Charlotte.
Ethical approval: Permission for data usage was obtained from the Clinical Practice Research Datalink Independent Scientific Advisory Committee (protocol number 17_217). Linked pseudonymised data were provided by Clinical Practice Research Datalink. Data were linked by National Health Service Digital, the statutory trusted third party for linking data, using identifiable data held only by National Health Service Digital. Select general practices consent to this process at a practice level with individual patients having the right to opt-out.
Guarantor: LHG
Contributorship: AJM, LHG and AM contributed to the idea generation and protocol development. AJM and LHG prepared the data for analysis, and LHG performed the statistical analyses. LHG and GM interpreted study results, and AJM, LHG, EPV and GM had primary responsibility in writing the manuscript. MM, JV and AM also contributed to manuscript writing. All authors critically reviewed the manuscript.
Data accessibility: Due to Clinical Practice Research Datalink licence restrictions, we are unable to share data.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplemental material, sj-pdf-1-jrs-10.1177_01410768211005109 for Associations between attainment of incentivised primary care indicators and emergency hospital admissions among type 2 diabetes patients: a population-based historical cohort study by Laura H Gunn, Ailsa J McKay, Mariam Molokhia, Jonathan Valabhji, German Molina, Azeem Majeed and Eszter P Vamos in Journal of the Royal Society of Medicine
Supplemental material, sj-pdf-2-jrs-10.1177_01410768211005109 for Associations between attainment of incentivised primary care indicators and emergency hospital admissions among type 2 diabetes patients: a population-based historical cohort study by Laura H Gunn, Ailsa J McKay, Mariam Molokhia, Jonathan Valabhji, German Molina, Azeem Majeed and Eszter P Vamos in Journal of the Royal Society of Medicine
Supplemental material, sj-pdf-3-jrs-10.1177_01410768211005109 for Associations between attainment of incentivised primary care indicators and emergency hospital admissions among type 2 diabetes patients: a population-based historical cohort study by Laura H Gunn, Ailsa J McKay, Mariam Molokhia, Jonathan Valabhji, German Molina, Azeem Majeed and Eszter P Vamos in Journal of the Royal Society of Medicine
Data Availability Statement
The study included 84,441 adults (44.2% female), registered across 330 practices, who were diagnosed with type 2 diabetes mellitus before 1 April 2010. Table 1 summarises cohort baseline characteristics. The average age was 68.0 (SD 12.5) years with a mean diabetes duration of 7.4 (SD 5.5) years; 83.6% were of white ethnicity, and deprivation was approximately evenly distributed across quintiles. The majority were overweight or obese (83.4%), current or ex-smokers (51.8%), and/or consumed alcohol (70.5%). Individuals experienced an average of 2.4 (SD 1.7) co-morbidities and 1.7 (SD 1.3) diabetic complications. They received a median of 6.0 (interquartile range, IQR 3–12) different prescriptions and an average of 1.3 (SD 1.0) glucose lowering therapies within six months prior to baseline, with insulin prescribed to 12,014 patients (14.2%) in that period.
Table 1.
Baseline characteristics and outcome summaries of the cohort of people with type 2 diabetes (N = 84,441).
| Variable | n, mean, or median | %, SD, or IQR |
|---|---|---|
| Age, years (mean, SD) | 68 | 12.5 |
| Sex: Female (n, %) | 37,342 | 44.2 |
| Ethnicity (n, %) | ||
| Asian | 4904 | 5.8 |
| Black | 1760 | 2.1 |
| Mixed | 559 | 0.7 |
| Other | 966 | 1.1 |
| White | 70,599 | 83.6 |
| Missing | 5653 | 6.7 |
| Index of multiple deprivation quintile (n, %) | ||
| 0 (Least deprived) | 16,134 | 19.1 |
| 1 | 19,104 | 22.6 |
| 2 | 17,350 | 20.6 |
| 3 | 17,258 | 20.4 |
| 4 (Most deprived) | 14,552 | 17.2 |
| Missing | 43 | 0.1 |
| Region (n, %) | ||
| North East | 2176 | 2.6 |
| North West | 14,794 | 17.5 |
| Yorkshire & The Humber | 3275 | 3.9 |
| East Midlands | 1841 | 2.2 |
| West Midlands | 10,051 | 11.9 |
| East of England | 8718 | 10.3 |
| South West | 11,464 | 13.6 |
| South Central | 10,149 | 12 |
| London | 11,065 | 13.1 |
| South East Coast | 10,908 | 12.9 |
| Weight status according to body mass index in kg/m2 (n, %) | ||
| Underweight (<18.5) | 639 | 0.8 |
| Normal weight (18.5–24.9) | 12,477 | 14.8 |
| Overweight (25.0–29.9) | 28,182 | 33.4 |
| Obese (30+) | 42,225 | 50 |
| Missing | 918 | 1.1 |
| Smoking status (n, %) | ||
| Never smoker | 40,457 | 47.9 |
| Ex-smoker | 32,027 | 37.9 |
| Current smoker | 11,750 | 13.9 |
| Missing | 207 | 0.3 |
| Alcohol consumption in units/week (n, %) | ||
| None | 13,996 | 16.6 |
| 1–14 | 49,558 | 58.7 |
| 15–42 | 8186 | 9.7 |
| >42 | 1801 | 2.1 |
| Missing | 10,900 | 12.9 |
| Co-morbid conditions (mean, SD) | 2.4 | 1.7 |
| Glucose-lowering therapiesa (mean, SD) | 1.3 | 1 |
| Insulin prescription (number, %) | 12,014 | 14.2 |
| Other medications prescribed (median, IQR) | 6 | 3–12 |
| Hospitalisations (mean, SD) | 0.2 | 0.6 |
| 0 (number, %) | 74,255 | 87.9 |
| 1 (number, %) | 7596 | 9 |
| >1 (number, %) | 2590 | 3.1 |
| Duration of diabetes (years, SD) | 7.4 | 5.5 |
| Complications (mean, SD) | 1.7 | 1.3 |
| Follow-up time, years (mean, SD) | 3.9 | 2 |
| Diabetes-related emergency admissions (number) | 115,425 | |
| Diabetes-related emergency admissions rate per 1000 patient-years | 354.6 | |
| Cardiovascular emergency admissions | 105,191 | |
| Cardiovascular emergency admissions rate per 1000 patient-years | 323.1 | |
| All-cause emergency admissions | 130,709 | |
| All-cause emergency admissions rate per 1000 patient-years | 401.5 | |
SD: standard deviation; IQR: interquartile range.
aIncludes insulin.
Across a total follow-up period of 6.75 years (mean 3.9 (SD 2.0) years), there were 130,709 emergency admissions for any cause, including 115,425 and 105,191 diabetes and cardiovascular-related admissions, respectively. This corresponds to unplanned admission rates of 401.5, 354.6 and 323.1, respectively, per 1000 patient-years.
Table 2 presents the distribution of Quality and Outcomes Framework indicator attainment and National Diabetes Audit process completion by the number of indicators/processes met. HbA1c, blood pressure and cholesterol Quality and Outcomes Framework indicators were achieved by 55,022 (65.2%), 49,124 (58.2%) and 63,603 (75.3%) adults, respectively; 27,880 (33.0%) met all three indicators, with slightly more (n = 33,348, 39.5%) achieving two indicators. There were 4819 (5.7%), 3327 (3.9%) and 7780 (9.2%) individuals who did not have a measurement for HbA1c, blood pressure and cholesterol, respectively, Quality and Outcomes Framework indicators during the exposure period and were considered as not attaining the respective indicator. Among National Diabetes Audit processes completed, the range was from 55,253 (65.4%; retinal screening) to 81,114 (96.1%; blood pressure screening). Although fewer than half (n = 35,688, 42.3%) completed all nine National Diabetes Audit processes, most (n = 71,227, 84.4%) completed 7–9 processes.
Table 2.
Number (%) of individuals who attained each of the QOF indicators and NDA processes (columns) by the number of QOF indicators met or NDA processes completed (rows).
| QOF target achieved |
NDA process achieved |
||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No. of QOF Targets/NDA processes met | Total | HbA1c | Blood pressure | Cholesterol | HbA1c | Blood pressure | Cholesterol | Serum creatine | Urine ACR | Foot exam | Body mass index | Smoking history | Retinal screen |
| 0 QOF targets | 5800 (6.9%) | 0 (0%) | 0 (0%) | 0 (0%) | 3097 (53.4%) | 3960 (68.3%) | 2580 (44.5%) | 3273 (56.4%) | 2389 (41.2%) | 2873 (49.5%) | 3353 (57.8%) | 3284 (56.6%) | 3009 (51.9%) |
| 1 QOF target | 17,413 (20.6%) | 4859 (27.9%) | 4238 (24.3%) | 8316 (47.8%) | 15,743 (90.4%) | 16,632 (95.5%) | 14,404 (82.7%) | 15,673 (90.0%) | 12,364 (71%) | 13,511 (77.6%) | 15,081 (86.6%) | 13,942 (80.1%) | 10,853 (62.3%) |
| 2 QOF targets | 33,348 (39.5%) | 22,283 (66.8%) | 17,006 (51%) | 27,407 (82.2%) | 32,902 (98.7%) | 32,642 (97.9%) | 31,797 (95.4%) | 32,565 (97.7%) | 26,883 (80.6%) | 28,650 (85.9%) | 30,805 (92.4%) | 28,473 (85.4%) | 22,319 (66.9%) |
| All 3 QOF targets | 27,880 (33.0%) | 27,880 (100%) | 27,880 (100%) | 27,880 (100%) | 27,880 (100%) | 27,880 (100%) | 27,880 (100%) | 27,658 (99.2%) | 23,886 (85.7%) | 25,039 (89.8%) | 26,461 (94.9%) | 24,577 (88.2%) | 19,072 (68.4%) |
| 0–3 NDA processes | 3520 (4.2%) | 418 (11.9%) | 811 (23.0%) | 244 (6.9%) | 668 (19.0%) | 1608 (45.7%) | 349 (9.9%) | 749 (21.3%) | 160 (4.6%) | 298 (8.5%) | 464 (13.2%) | 643 (18.3%) | 1140 (32.4%) |
| 4–6 NDA processes | 9694 (11.5%) | 5251 (54.2%) | 5013 (51.7%) | 5129 (52.9%) | 8057 (83.1%) | 8689 (89.6%) | 6627 (68.4%) | 7771 (80.2%) | 2972 (30.7%) | 3311 (34.2%) | 5537 (57.1%) | 4303 (44.4%) | 4053 (41.8%) |
| 7–9 NDA processes | 71,227 (84.4%) | 49,353 (69.3%) | 43,300 (60.8%) | 58,230 (81.8%) | 70,897 (99.5%) | 70,817 (99.4%) | 69,685 (97.8%) | 70,649 (99.2%) | 62,390 (87.6%) | 66,464 (93.3%) | 69,699 (97.9%) | 65,330 (91.7%) | 50,060 (70.3%) |
| All 9 NDA processes | 35,688 (42.3%) | 25,511 (71.5%) | 21,960 (61.5%) | 30,411 (85.2%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) | 35,688 (100%) |
| Total | 84,441 (100%) | 55,022 (65.2%) | 49,124 (58.2%) | 63,603 (75.3%) | 79,622 (94.3%) | 81,114 (96.1%) | 76,661 (90.8%) | 79,169 (93.8%) | 65,522 (77.6%) | 70,073 (83%) | 75,700 (89.7%) | 70,276 (83.2%) | 55,253 (65.4%) |
QOF: Quality and Outcomes Framework; NDA: National Diabetes Audit; HbA1c: glycated haemoglobin; ACR: albumin creatinine ratio; QOF targets: HbA1c ≤ 59 mmol/mol; blood pressure ≤ 140/80 mmHg; total cholesterol ≤ 5 mmol/L.