Continuity of care and consultation mode in general practice: a cross-sectional and longitudinal study using patient-level and practice-level data from before and during the COVID-19 pandemic in England

OBJECTIVES

Investigate trends in continuity of care with a general practitioner (GP) before and during the COVID-19 pandemic. Identify whether continuity of care is associated with consultation mode, controlling for other patient and practice characteristics.

DESIGN

Retrospective cross-sectional and longitudinal observational studies.

SETTING

Primary care records from 389 general practices participating in Clinical Practice Research Datalink Aurum in England.

PARTICIPANTS

In the descriptive analysis, 100 000+ patients were included each month between April 2018 and April 2021. Modelling of the association between continuity of care and consultation mode focused on 153 475 and 125 298 patients in index months of February 2020 (before the pandemic) and February 2021 (during the pandemic) respectively, and 76 281 patients in both index months.

PRIMARY AND SECONDARY OUTCOMES MEASURES

The primary outcome measure was the Usual Provider of Care index. Secondary outcomes included the Bice-Boxerman index and count of consultations with the most frequently seen GP.

RESULTS

Continuity of care was gradually declining before the pandemic but stabilised during it. There were consistent demographic, socioeconomic and regional differences in continuity of care. An average of 23% of consultations were delivered remotely in the year to February 2020 compared with 76% in February 2021. We found little evidence consultation mode was associated with continuity at the patient level, controlling for a range of covariates. In contrast, patient characteristics and practice-level supply and demand were associated with continuity.

CONCLUSIONS

We set out to examine the association of consultation mode with continuity of care but found that GP supply and patient demand were much more important. To improve continuity for patients, primary care capacity needs to increase. This requires sufficient, long-term investment in clinicians, staff, facilities and digital infrastructure. General practice also needs to transform ways of working to ensure continuity for those that need it, even in a capacity-constrained environment.

Antibiotic prescribing in remote versus face-to-face consultations for acute respiratory infections in primary care in England: an observational study using target maximum likelihood estimation

Background

The COVID-19 pandemic has led to an ongoing increase in the use of remote consultations in general practice in England. Although the evidence is limited, there are concerns that the increase in remote consultations could lead to more antibiotic prescribing.

Methods

In this cohort study, we used patient-level primary care data from the Clinical Practice Research Datalink to estimate the association between consultation mode (remote versus face-to-face) and antibiotic prescribing in England for acute respiratory infections (ARI) between April 2021 and March 2022. Eligibility criteria were applied at both practice-level and patient-level. 400 practices in England were sampled at random and then 600,000 patients were randomly sampled from the eligible patients (whose sex was recorded). Consultations for acute respiratory infections were identified. All antibiotic prescriptions were included, with the exception of antituberculosis drugs and antileprotic drugs, as identified through chapter 5.1 of the British National Formulary. The CPRD Aurum data was linked to the COVID-19 ONS infection survey by region. All analyses were done at the individual level. Repeated consultations from the same patient within 7 days were grouped together. We used targeted maximum likelihood estimation, a causal machine learning method with adjustment for infection type and patient-level, clinician-level and practice-level factors.

Findings

There were 45,997 ARI consultations (34,555 unique patients) within the study period, of which 28,127 were remote and 17,870 were face-to-face. For children, 48% of consultations were remote and, for adults, 66% were remote. For children, 42% of remote and 43% of face-to-face consultations led to an antibiotic prescription; the equivalent values for adults were 52% and 42%, respectively. After adjustment with TMLE, adults with a remote consultation had 23% (odds ratio [OR] 1.23, 95% CI: 1.18-1.29) higher chance of being prescribed antibiotics than if they had been seen face-to-face. We found no significant association between consultation mode and antibiotic prescribing in children (OR 1.04 95% CI: 0.98-1.11).

Interpretation

The higher rates of antibiotic prescribing in remote consultations for adults are cause for concern. We see no significant difference in antibiotic prescribing between consultation mode for children. These findings should inform antimicrobial stewardship activities for health-care professionals and policy makers. Future research should examine differences in guideline-compliance between remote and face-to-face consultations to understand the factors driving antibiotic prescribing in different consultation modes.

Funding

None.

The impact of the COVID-19 pandemic on antimicrobial prescribing at a specialist paediatric hospital: an observational study

BACKGROUND

The COVID-19 pandemic has severely impacted healthcare delivery and there are growing concerns that the pandemic will accelerate antimicrobial resistance.

OBJECTIVES

To evaluate the impact of the COVID-19 pandemic on antibiotic prescribing in a tertiary paediatric hospital in London, UK.

METHODS

Data on patient characteristics and antimicrobial administration for inpatients treated between 29 April 2019 and Sunday 28 March 2021 were extracted from the electronic health record (EHR). Interrupted time series analysis was used to evaluate antibiotic days of therapy (DOT) and the proportion of prescribed antibiotics from the WHO 'Access' class.

RESULTS

A total of 23 292 inpatient admissions were included. Prior to the pandemic there were an average 262 admissions per week compared with 212 during the pandemic period. Patient demographics were similar in the two periods but there was a shift in the specialities that patients had been admitted to. During the pandemic, there was a crude increase in antibiotic DOTs, from 801 weekly DOT before the pandemic to 846. The proportion of Access antibiotics decreased from 44% to 42%. However, after controlling for changes in patient characteristics, there was no evidence for the pandemic having an impact on antibiotic prescribing.

CONCLUSIONS

The patient population in a specialist children's hospital was affected by the COVID-19 pandemic, but after adjusting for these changes there was no evidence that antibiotic prescribing was significantly affected by the pandemic. This highlights both the value of routine, high-quality EHR data and importance of appropriate statistical methods that can adjust for underlying changes to populations when evaluating impacts of the pandemic on healthcare.

The economic burden of stroke care in England, Wales and Northern Ireland: Using a national stroke register to estimate and report patient-level health economic outcomes in stroke

Introduction

Stroke registries are used in many settings to measure stroke treatment and outcomes, but rarely include data on health economic outcomes. We aimed to extend the Sentinel Stroke National Audit Programme registry of England, Wales and Northern Ireland to derive and report patient-level estimates of the cost of stroke care.

Methods

An individual patient simulation model was built to estimate health and social care costs at one and five years after stroke, and the cost-benefits of thrombolysis and early supported discharge. Costs were stratified according to age, sex, stroke type (ischaemic or primary intracerebral haemorrhage) and stroke severity. The results were illustrated using data on all patients with stroke included in Sentinel Stroke National Audit Programme from April 2015 to March 2016 (n = 84,184).

Results

The total cost of health and social care for patients with acute stroke each year in England, Wales and Northern Ireland was £3.60 billion in the first five years after admission (mean per patient cost: £46,039). There was fivefold variation in the magnitude of costs between patients, ranging from £19,101 to £107,336. Costs increased with older age, increasing stroke severity and intracerebral hemorrhage stroke. Increasing the proportion of eligible patients receiving thrombolysis or early supported discharge was estimated to save health and social care costs by five years after stroke.

Discussion

The cost of stroke care is large and varies widely between patients. Increasing the proportion of eligible patients receiving thrombolysis or early supported discharge could contribute to reducing the financial burden of stroke.

Conclusion

Extending stroke registers to report individualised data on costs may enhance their potential to support quality improvement and research.

Abstract TP178: Relationship Between Deprivation and Outcome for Stroke Patients: Data From the UK National Stroke Registry

Introduction: Previous studies have identified that social deprivation is associated with the onset of stroke, with people from areas of higher deprivation being more likely to have a stroke at a younger age.

Methods: Data were extracted from the national stroke register (Sentinel Stroke National Audit Programme (SSNAP)) of adults with acute ischemic stroke treated in all hospitals in England and Wales from April 2013-March 2014. The patient’s zip code of residence was used to link the data with an index of multiple deprivation, which groups zip codes into quartiles of deprivation.

Results: Of the 66798 adults with acute stroke discharged from 266 hospitals, deprivation data was available for 63007 patients (94.3%).The median age of stroke onset for the most deprived quartile was 5 years lower than for the least deprived quartile (74, 77, 79 and 79 years respectively, Kruskal-Wallis test p<0.001). For patients in the most deprived quartiles compared to the least deprived, the rate of primary intracerebral hemorrhage was lower (9.9%, 10.5%, 10.7% and 11.7% respectively, chi2 p<0.001), the rate of diabetes was higher (22.7%, 20.6%, 17.9% and 15.8%, chi2 p<0.001), and the prevalence of congestive heart failure, hypertension and previous stroke/TIA were similar for all groups. The rate of atrial fibrillation (AF) prior to stroke was lower for more deprived patients (17.6%, 19.8%, 22.9% and 22.6%, chi2 p<0.001), but the percentage of patients on anticoagulants if in AF was similar for all groups. Mortality at 30 days was lower in the most deprived group compared to the least deprived group (12.8%, 14.6%, 15.7% and 15.4%, chi2 p<0.001).

Conclusions: Patients living in more deprived areas have stroke at a younger age and are more likely to have a prior history of diabetes mellitus. Outcomes are similar for all groups but crude mortality at 30 days was lower for the most deprived group. This may be due to the lower median age of stroke onset, and the higher proportion of ischemic strokes. Predictive models for stroke outcome need to consider levels of deprivation and we are currently working on multivariable analysis to identify any independent effect of deprivation on mortality.

Abstract W P288: Using “Big Data” Analytics and Visualization for Quality Improvement in Stroke Care

Introduction: The Sentinel Stroke National Audit Programme (SSNAP) is the new national stroke register of England and Wales. It has been designed to harness the power of “Big Data” to produce near real-time data collection, analysis and reporting. Sophisticated data visualization is used to provide customized analytics for clinical teams, administrators, healthcare funders and stroke survivors and carers.

Methods: A portfolio of cutting edge data visualisation outputs, including team level slidedecks, performance charts, dashboards , and interactive maps, was produced. Visualisations for patients and the public were co-designed with stroke survivors. Stakeholder feedback regarding accessibility and usefulness of the resources was sought via online polls.

Results: Key SSNAP results are made accessible electronically every three months in a range of bespoke graphical formats. Individualised slidedecks and data summaries are produced for every hospital, funding group, and region to enable provider level performance and quality reporting and regional and national benchmarking. Dynamic maps enhance dissemination and use of results. Real time root cause analysis tools help teams identify areas of improvement. Feedback reports unprecedented utility of these resources for clinical teams, funders, regional and national health bodies, patients and the public in identifying areas of good practice and requiring improvements, highlighting variations, and driving change.

Conclusion: SSNAP is a potential new model of healthcare quality measurement that uses recent developments in big data analytics and visualization to provide information on stroke care quality that is more useful to stakeholders. Similar approaches could be used in other healthcare settings and populations.