Prescription of suboptimal statin treatment regimens: a retrospective cohort study of trends and variation in English primary care

Investigating innovations in outpatient services: a mixed-methods rapid evaluation

Background

Within outpatient services, a broad range of innovations are being pursued to better manage care and reduce unnecessary appointments. One of the least-studied innovations is Patient-Initiated Follow-Up, which allows patients to book appointments if and when they need them, rather than follow a standard schedule.

Objectives

To use routine national hospital data to identify innovations in outpatient services implemented, in recent years, within the National Health Service in England. To carry out a rapid mixed-methods evaluation of the implementation and impact of Patient-Initiated Follow-Up.

Methods

The project was carried out in four sequential workstreams: (1) a rapid scoping review of outpatient innovations; (2) the application of indicator saturation methodology for scanning national patient-level data to identify potentially successful local interventions; (3) interviews with hospitals identified in workstream 2; and (4) a rapid mixed-methods evaluation of Patient-Initiated Follow-Up. The evaluation of Patient-Initiated Follow-Up comprised an evidence review, interviews with 36 clinical and operational staff at 5 National Health Service acute trusts, a workshop with staff from 13 National Health Service acute trusts, interviews with four patients, analysis of national and local data, and development of an evaluation guide.

Results

Using indicator saturation, we identified nine services with notable changes in follow-up to first attendance ratios. Of three sites interviewed, two queried the data findings and one attributed the change to a clinical assessment service. Models of Patient-Initiated Follow-Up varied widely between hospital and clinical specialty, with a significant degree of variation in the approach to patient selection, patient monitoring and discharge. The success of implementation was dependent on several factors, for example, clinical condition, staff capacity and information technology systems. From the analysis of national data, we found evidence of an association between greater use of Patient-Initiated Follow-Up and a lower frequency of outpatient attendance within 15 out of 29 specialties and higher frequency of outpatient attendance within 7 specialties. Four specialties had less frequent emergency department visits associated with increasing Patient-Initiated Follow-Up rates. Patient-Initiated Follow-Up was viewed by staff and the few patients we interviewed as a positive intervention, although there was varied impact on individual staff roles and workload. It is important that sites and services undertake their own evaluations of Patient-Initiated Follow-Up. To this end we have developed an evaluation guide to support trusts with data collection and methods.

Limitations

The Patient-Initiated Follow-Up evaluation was affected by a lack of patient-level data showing who is on a Patient-Initiated Follow-Up pathway. Engagement with local services was also challenging, given the pressures facing sites and staff. Patient recruitment was low, which affected the ability to understand experiences of patients directly.

Conclusions

The study provides useful insights into the evolving national outpatient transformation policy and for local practice. Patient-Initiated Follow-Up is often perceived as a positive intervention for staff and patients, but the impact on individual outcomes, health inequalities, wider patient experience, workload and capacity is still uncertain.

Future research

Further research should include patient-level analysis to determine clinical outcomes for individual patients on Patient-Initiated Follow-Up and health inequalities, and more extensive investigation of patient experiences.

Study registration

This study is registered with the Research Registry (UIN: researchregistry8864).

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 16/138/17) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 38. See the NIHR Funding and Awards website for further award information.

Reducing health inequalities through general practice: a realist review and action framework

Background

Socio-economic inequalities in health have been in the public agenda for decades. General practice has an influential role to play in mitigating the impact of inequalities especially regarding chronic conditions. At the moment, general practice is dealing with serious challenges in relation to workforce shortages, increasing workload and the impact of the COVID-19 pandemic. It is important to identify effective ways so that general practice can play its role in reducing health inequalities.

Objectives

We explored what types of interventions and aspects of routine care in general practice decrease or increase inequalities in health and care-related outcomes. We focused on cardiovascular disease, cancer, diabetes and/or chronic obstructive pulmonary disease. We explored for whom these interventions and aspects of care work best, why, and in what circumstances. Our main objective was to synthesise this evidence into specific guidance for healthcare professionals and decision-makers about how best to achieve equitable general practice.

Design

Realist review.

Main outcome measures

Clinical or care-related outcomes by socio-economic group, or other PROGRESS-Plus criteria.

Review methods

Realist review based on Pawson's five steps: (1) locating existing theories, (2) searching for evidence, (3) selecting articles, (4) extracting and organising data and (5) synthesising the evidence.

Results

Three hundred and twenty-five studies met the inclusion criteria and 159 of them were selected for the evidence synthesis. Evidence about the impact of general practice interventions on health inequalities is limited. To reduce health inequalities, general practice needs to be: • connected so that interventions are linked and coordinated across the sector; • intersectional to account for the fact that people's experience is affected by many of their characteristics; • flexible to meet patients' different needs and preferences; • inclusive so that it does not exclude people because of who they are; • community-centred so that people who receive care engage with its design and delivery. These qualities should inform action across four domains: structures like funding and workforce distribution, organisational culture, everyday regulated procedures involved in care delivery, interpersonal and community relationships.

Limitations

The reviewed evidence offers limited detail about the ways and the extent to which specific interventions increase or decrease inequalities in general practice. Therefore, we focused on the underpinning principles that were common across interventions to produce higher-level, transferrable conclusions about ways to achieve equitable care.

Conclusions

Inequalities in general practice result from complex processes across four different domains that include structures, ideas, regulated everyday procedures, and relationships among individuals and communities. To achieve equity, general practice needs to be connected, intersectional, flexible, inclusive and community-centred.

Future work

Future work should focus on how these five essential qualities can be better used to shape the organisational development of future general practice.

Study registration

This trial is registered as PROSPERO CRD42020217871.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR130694) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 7. See the NIHR Funding and Awards website for further award information.

Machine Learning Applied to Cholesterol-Lowering Pharmacotherapy: Proof-of-Concept in High-Risk Patients Treated in Primary Care

Objectives: Machine learning has potential to improve the management of lipid disorders. We explored the utility of machine learning in high-risk patients in primary care receiving cholesterol-lowering medications. Methods: Machine learning algorithms were created based on lipid management guidelines for England [National Institute for Health and Care Excellence (NICE) CG181] to reproduce the guidance with >95% accuracy. Natural language processing and therapy identification algorithms were applied to anonymized electronic records from six South London primary care general practices to extract medication information from free text fields. Results: Among a total of 48,226 adult patients, a subset of 5630 (mean ± standard deviation, age = 67 ± 13 years; male:female = 55:45) with a history of lipid-lowering therapy were identified. Additional major cardiometabolic comorbidities included type 2 diabetes in 13% (n = 724) and hypertension in 32% (n = 1791); all three risk factors were present in a further 28% (n = 1552). Of the 5630 patients, 4290 (76%) and 1349 (24%) were in primary and secondary cardiovascular disease prevention cohorts, respectively. Statin monotherapy was the most common current medication (82%, n = 4632). For patients receiving statin monotherapy, 71% (n = 3269) were on high-intensity therapy aligned with NICE guidance with rates being similar for the primary and secondary prevention cohorts. In the combined cohort, only 46% of patients who had been prescribed lipid-lowering therapy in the previous 12 months achieved the NICE treatment goal of >40% reduction in non-high-density lipoprotein cholesterol from baseline pretreatment levels. Based on the most recent data entry for patients not at goal the neural network recommended either increasing the dose of statin, adding complementary cholesterol-lowering medication, or obtaining an expert lipid opinion. Conclusions: Machine learning can be of value in (a) quantifying suboptimal lipid-lowering prescribing patterns, (b) identifying high-risk patients who could benefit from more intensive therapy, and (c) suggesting evidence-based therapeutic options.

Reducing health inequalities through general practice

Although general practice can contribute to reducing health inequalities, existing evidence provides little guidance on how this reduction can be achieved. We reviewed interventions influencing health and care inequalities in general practice and developed an action framework for health professionals and decision makers. We conducted a realist review by searching MEDLINE, Embase, CINAHL, PsycINFO, Web of Science, and Cochrane Library for systematic reviews of interventions into health inequality in general practice. We then screened the studies in the included systematic reviews for those that reported their outcomes by socioeconomic status or other PROGRESS-Plus (Cochrane Equity Methods Group) categories. 159 studies were included in the evidence synthesis. Robust evidence on the effect of general practice on health inequalities is scarce. Focusing on common qualities of interventions, we found that to reduce health inequalities, general practice needs to be informed by five key principles: involving coordinated services across the system (ie, connected), accounting for differences within patient groups (ie, intersectional), making allowances for different patient needs and preferences (ie, flexible), integrating patient worldviews and cultural references (ie, inclusive), and engaging communities with service design and delivery (ie, community-centred). Future work should explore how these principles can inform the organisational development of general practice.

How to Use Statins in Secondary Prevention of Atherosclerotic Diseases: from the Beneficial Early Initiation to the Potentially Unfavorable Discontinuation

Statins, a class of lipid-lowering drugs, reduce morbidity and mortality in patients with established atherosclerosis-related cardiovascular disease. Early initiation of statin therapy after admission for acute coronary syndromes (ACS), stroke, or transient ischemic attack (TIA) is associated with improved cardiovascular outcomes. Moreover, high-dose statin treatment prior to coronary or carotid revascularization has been shown to reduce cardiovascular events in these patients. However, many patients may be undertreated, and a residual cardiovascular risk remains in current clinical practice. Despite the beneficial role of statins, their discontinuation rate among patients is still elevated leading to severe adverse cardiovascular events due to atherosclerotic plaque destabilization. In this review, we summarized the impact of statin treatment among patients, focusing on the initiation time-points as well as the potential harm derived by their discontinuation.

Identifying Patterns of Clinical Interest in Clinicians' Treatment Preferences: Hypothesis-free Data Science Approach to Prioritizing Prescribing Outliers for Clinical Review

BACKGROUND

Data analysis is used to identify signals suggestive of variation in treatment choice or clinical outcome. Analyses to date have generally focused on a hypothesis-driven approach.

OBJECTIVE

This study aimed to develop a hypothesis-free approach to identify unusual prescribing behavior in primary care data. We aimed to apply this methodology to a national data set in a cross-sectional study to identify chemicals with significant variation in use across Clinical Commissioning Groups (CCGs) for further clinical review, thereby demonstrating proof of concept for prioritization approaches.

METHODS

Here we report a new data-driven approach to identify unusual prescribing behaviour in primary care data. This approach first applies a set of filtering steps to identify chemicals with prescribing rate distributions likely to contain outliers, then applies two ranking approaches to identify the most extreme outliers amongst those candidates. This methodology has been applied to three months of national prescribing data (June-August 2017).

RESULTS

Our methodology provides rankings for all chemicals by administrative region. We provide illustrative results for 2 antipsychotic drugs of particular clinical interest: promazine hydrochloride and pericyazine, which rank highly by outlier metrics. Specifically, our method identifies that, while promazine hydrochloride and pericyazine are barely used by most clinicians (with national prescribing rates of 11.1 and 6.2 per 1000 antipsychotic prescriptions, respectively), they make up a substantial proportion of antipsychotic prescribing in 2 small geographic regions in England during the study period (with maximum regional prescribing rates of 298.7 and 241.1 per 1000 antipsychotic prescriptions, respectively).

CONCLUSIONS

Our hypothesis-free approach is able to identify candidates for audit and review in clinical practice. To illustrate this, we provide 2 examples of 2 very unusual antipsychotics used disproportionately in 2 small geographic areas of England.

Effects of general and central adiposity on circulating lipoprotein, lipid, and metabolite levels in UK Biobank: A multivariable Mendelian randomization study

Background

The direct effects of general adiposity (body mass index (BMI)) and central adiposity (waist-to-hip-ratio (WHR)) on circulating lipoproteins, lipids, and metabolites are unknown.

Methods

We used new metabolic data from UK Biobank (N=109,532, a five-fold higher N over previous studies). EDTA-plasma was used to quantify 249 traits with nuclear-magnetic-resonance spectroscopy including subclass-specific lipoprotein concentrations and lipid content, plus pre-glycemic and inflammatory metabolites. We used univariable and multivariable two-stage least-squares regression models with genetic risk scores for BMI and WHR as instruments to estimate total (unadjusted) and direct (mutually-adjusted) effects of BMI and WHR on metabolic traits; plus effects on statin use and interaction by sex, statin use, and age (proxy for medication use).

Findings

Higher BMI decreased apolipoprotein B and low-density lipoprotein cholesterol (LDL-C) before and after WHR-adjustment, whilst BMI increased triglycerides only before WHR-adjustment. These effects of WHR were larger and BMI-independent. Direct effects differed markedly by sex, e.g., triglycerides increased only with BMI among men, and only with WHR among women. Adiposity measures increased statin use and showed metabolic effects which differed by statin use and age. Among the youngest (38-53y, statins-5%), BMI and WHR (per-SD) increased LDL-C (total effects: 0.04-SD, 95%CI=-0.01,0.08 and 0.10-SD, 95%CI=0.02,0.17 respectively), but only WHR directly. Among the oldest (63-73y, statins-29%), BMI and WHR directly lowered LDL-C (-0.19-SD, 95%CI=-0.27,-0.11 and -0.05-SD, 95%CI=-0.16,0.06 respectively).

Interpretation

Excess adiposity likely raises atherogenic lipid and metabolite levels exclusively via adiposity stored centrally, particularly among women. Apparent effects of adiposity on lowering LDL-C are likely explained by an effect of adiposity on statin use.

Funding

UK Medical Research Council; British Heart Foundation; Novo Nordisk; National Institute for Health Research; Wellcome Trust; Cancer Research UK.

Variation in statin prescription among veterans with HIV and known atherosclerotic cardiovascular disease

BACKGROUND

People with HIV have increased atherosclerotic cardiovascular disease (ASCVD) risk, worse outcomes following incident ASCVD, and experience gaps in cardiovascular care, highlighting the need to improve delivery of preventive therapies in this population.

OBJECTIVE

Assess patient-level correlates and inter-facility variations in statin prescription among Veterans with HIV and known ASCVD.

METHODS

We studied Veterans with HIV and existing ASCVD, ie, coronary artery disease (CAD), ischemic cerebrovascular disease (ICVD), and peripheral arterial disease (PAD), who received care across 130 VA medical centers for the years 2018-2019. We assessed correlates of statin prescription using two-level hierarchical multivariable logistic regression. Median odds ratios (MORs) were used to quantify inter-facility variation in statin prescription.

RESULTS

Nine thousand six hundred eight Veterans with HIV and known ASCVD (mean age 64.3 ± 8.9 years, 97% male, 48% Black) were included. Only 68% of the participants were prescribed any-statin. Substantially higher statin prescription was observed for those with diabetes (adjusted odds ratio [OR] = 2.3, 95% confidence interval [CI], 2.0-2.6), history of coronary revascularization (OR = 4.0, CI, 3.2-5.0), and receiving antiretroviral therapy (OR = 3.0, CI, 2.7-3.4). Blacks (OR = 0.7, CI, 0.6-0.9), those with non-coronary ASCVD, ie, ICVD and/or PAD only, (OR 0.53, 95% CI: 0.48-0.57), and those with history of illicit substance use (OR=0.7, CI, 0.6-0.9) were less likely to be prescribed statins. There was significant variation in statin prescription across VA facilities (10th, 90th centile: 55%, 78%), with an estimated 20% higher likelihood of difference in statin prescription practice for two clinically similar individuals treated at two comparable facilities (adjusted MOR = 1.21, CI, 1.18-1.24), and a greater variation observed for Blacks or those with non-coronary ASCVD or history of illicit drug use.

CONCLUSION

In an analysis of large-scale VA data, we found suboptimal statin prescription and significant interfacility variation in statin prescription among Veterans with HIV and known ASCVD, particularly among Blacks and those with a history of non-coronary ASCVD.

Longitudinal evaluation of treatment patterns, risk factors and outcomes in patients with cardiovascular disease treated with lipid-lowering therapy in the UK

OBJECTIVES

To compare treatment patterns, risk factors and cardiovascular disease (CVD) event rates in the UK from 2008 to 2017.

DESIGN

Retrospective cohort study using the Clinical Practice Research Datalink.

SETTING

UK primary care.

PARTICIPANTS

We selected 10 annual cohorts of patients with documented CVD receiving lipid-lowering therapy and the subsets with myocardial infarction (MI). Each cohort included patients ≥18 years old, with ≥1 year of medical history and ≥2 lipid-lowering therapy prescriptions in the prior year.

PRIMARY AND SECONDARY OUTCOME MEASURES

For each annual cohort, we identified cardiovascular risk factors and lipid-lowering therapy and estimated the 1-year composite rate of fatal and non-fatal MI, ischaemic stroke (IS) or revascularisation.

RESULTS

The documented CVD cohort mean age was 71.6 years in 2008 (N=173 424) and 72.5 (N=94 418) in 2017; in the MI subset, mean age was 70.1 years in 2008 (N=38 999) and 70.4 in 2017 (N=25 900). Both populations had larger proportions of men. In the documented CVD cohort, the proportion receiving high-intensity lipid-lowering therapy from 2008 to 2017 doubled from 16% to 32%; in the MI subset, the increase was 20% to 48%. In the documented CVD cohort, the proportion of patients with low-density lipoprotein cholesterol (LDL-C) <1.8 mmol/L increased from 28% to 38%; in the MI subset, the proportion with LDL-C <1.8 mmol/L increased from 32% to 42%. The composite event rate per 100 person-years declined over time, from 2.5 to 2.0 in the documented CVD cohort, and from 3.7 to 2.8 in the MI subset. After excluding revascularisation from the composite outcome, the decline in the event rate in both populations was substantially attenuated.

CONCLUSIONS

Despite an increase in high-intensity therapy use and a decline in revascularisation, more than half of patients did not receive high-intensity lipid-lowering therapy by 2017 and incidence rates of MI and IS remained virtually unchanged.

Determining propensity for sub-optimal low-density lipoprotein cholesterol response to statins and future risk of cardiovascular disease

BACKGROUND

Variability in low-density lipoprotein cholesterol (LDL-C) response to statins is underappreciated. We characterised patients by their statin response (SR), baseline risk of cardiovascular disease (CVD) and 10-year CVD outcomes.

METHODS AND RESULTS

A multivariable model was developed using 183,213 United Kingdom (UK) patients without CVD to predict probability of sub-optimal SR, defined by guidelines as <40% reduction in LDL-C. We externally validated the model in a Hong Kong (HK) cohort (n = 170,904). Patients were stratified into four groups by predicted SR and 10-year CVD risk score: [SR1] optimal SR & low risk; [SR2] sub-optimal SR & low risk; [SR3] optimal SR & high risk; [SR4] sub-optimal SR & high risk; and 10-year hazard ratios (HR) determined for first major adverse cardiovascular event (MACE). Our SR model included 12 characteristics, with an area under the curve of 0.70 (95% confidence interval [CI] 0.70-0.71; UK) and 0.68 (95% CI 0.67-0.68; HK). HRs for MACE in predicted sub-optimal SR with low CVD risk groups (SR2 to SR1) were 1.39 (95% CI 1.35-1.43, p<0.001; UK) and 1.14 (95% CI 1.11-1.17, p<0.001; HK). In both cohorts, patients with predicted sub-optimal SR with high CVD risk (SR4 to SR3) had elevated risk of MACE (UK HR 1.36, 95% CI 1.32-1.40, p<0.001: HK HR 1.25, 95% CI 1.21-1.28, p<0.001).

CONCLUSIONS

Patients with sub-optimal response to statins experienced significantly more MACE, regardless of baseline CVD risk. To enhance cholesterol management for primary prevention, statin response should be considered alongside risk assessment.

Ethnic differences in guideline-indicated statin initiation for people with type 2 diabetes in UK primary care, 2006-2019: A cohort study

BACKGROUND

Type 2 diabetes is 2-3 times more prevalent in people of South Asian and African/African Caribbean ethnicity than people of European ethnicity living in the UK. The former 2 groups also experience excess atherosclerotic cardiovascular disease (ASCVD) complications of diabetes. We aimed to study ethnic differences in statin initiation, a cornerstone of ASCVD primary prevention, for people with type 2 diabetes.

METHODS AND FINDINGS

Observational cohort study of UK primary care records, from 1 January 2006 to 30 June 2019. Data were studied from 27,511 (88%) people of European ethnicity, 2,386 (8%) people of South Asian ethnicity, and 1,142 (4%) people of African/African Caribbean ethnicity with incident type 2 diabetes, no previous ASCVD, and statin use indicated by guidelines. Statin initiation rates were contrasted by ethnicity, and the number of ASCVD events that could be prevented by equalising prescribing rates across ethnic groups was estimated. Median time to statin initiation was 79, 109, and 84 days for people of European, South Asian, and African/African Caribbean ethnicity, respectively. People of African/African Caribbean ethnicity were a third less likely to receive guideline-indicated statins than European people (n/N [%]: 605/1,142 [53%] and 18,803/27,511 [68%], respectively; age- and gender-adjusted HR 0.67 [95% CI 0.60 to 0.76], p < 0.001). The HR attenuated marginally in a model adjusting for total cholesterol/high-density lipoprotein cholesterol ratio (0.77 [95% CI 0.69 to 0.85], p < 0.001), with no further diminution when deprivation, ASCVD risk factors, comorbidity, polypharmacy, and healthcare usage were accounted for (fully adjusted HR 0.76 [95% CI 0.68, 0.85], p < 0.001). People of South Asian ethnicity were 10% less likely to receive a statin than European people (1,489/2,386 [62%] and 18,803/27,511 [68%], respectively; fully adjusted HR 0.91 [95% CI 0.85 to 0.98], p = 0.008, adjusting for all covariates). We estimated that up to 12,600 ASCVD events could be prevented over the lifetimes of people currently affected by type 2 diabetes in the UK by equalising statin prescribing across ethnic groups. Limitations included incompleteness of recording of routinely collected data.

CONCLUSIONS

In this study we observed that people of African/African Caribbean ethnicity with type 2 diabetes were substantially less likely, and people of South Asian ethnicity marginally less likely, to receive guideline-indicated statins than people of European ethnicity, even after accounting for sociodemographics, healthcare usage, ASCVD risk factors, and comorbidity. Underuse of statins in people of African/African Caribbean or South Asian ethnicity with type 2 diabetes is a missed opportunity to prevent cardiovascular events.

Variation in statin prescribing across England

Overview of: Curtis HJ, Walker AJ, MacKenna B, et al Prescription of suboptimal statin treatment regimens: a retrospective cohort study of trends and variation in English primary care. Br J Gen Pract 2020;70:e525-e533.