Background: Cardiovascular disease management in primary care in England was disrupted during the COVID-19 pandemic. Objective: We aim to describe the impact of the COVID-19 pandemic on blood pressure screening and hypertension management, based upon a national quality of care scheme (Quality and Outcomes Framework, QOF) across key demographic, regional, and clinical subgroups. To this end, we translate complex clinical quality of care schemes from text descriptions into reusable analytic code. Methods: With the approval of NHS England, a population based cohort study was conducted on 25.2 million patient records in situ using OpenSAFELY-TPP. We included all NHS patients registered at general practices using TPP software between March 2019 and March 2023. Individuals that were eligible for blood pressure screening and with a diagnosis of hypertension were identified according to the QOF 2021/22 business rules. We examined monthly changes in recorded blood pressure screening in the preceding 5 years in patients aged ≥ 45, recorded hypertension prevalence, and the recorded percentage of patients treated to target (i.e., ≤ 140/90 mmHg for patients ≤ 79 years and ≤ 150/90 mmHg for patients ≥ 80 years) in the preceding 12 months, within demographic, regional, and clinical subgroups as well as the variation across practices. Results: The overall percentage of patients aged ≥ 45 who had blood pressure screening recorded in the preceding 5 years decreased from 90% in March 2019 to 85% in March 2023. Recorded hypertension prevalence was relatively stable at 15% throughout the study period. The percentage of patients with a record of hypertension treated to target in the preceding 12 months reduced from a maximum of 71% in March 2020 to a minimum of 47% in February 2021 in patients aged ≤ 79 years, and from 85% in March 2020 to a minimum of 58% in February 2021 in patients aged ≥ 80 years before recovering. Blood pressure screening rates in the preceding 5 years remained stable in older age groups, patients with a record of learning disability, or care home status. Conclusions: There was substantial disruption to hypertension management QOF indicators during the pandemic, which can likely be attributed to a general reduction of blood pressure screening. OpenSAFELY can be used to continuously monitor monthly changes in national quality of care schemes to identify changes in key clinical subgroups early and support prioritisation of recovery from disrupted care caused by COVID-19.
Background: The COVID-19 pandemic created unprecedented pressure on healthcare services. This study aimed to investigate if disease-modifying anti-rheumatic drug (DMARD) safety monitoring was affected during the COVID-19 pandemic. Methods: A population-based cohort study was conducted with the approval of NHS England, using the OpenSAFELY platform to access electronic health record data from 24.2 million patients registered at general practices using TPP's SystmOne software. Patients were included for further analysis if prescribed azathioprine, leflunomide, or methotrexate between November 2019 and July 2022. Outcomes were assessed as monthly trends and variation between various sociodemographic and clinical groups for adherence with standard safety monitoring recommendations. Findings: An acute increase in the rate of missed monitoring occurred across the study population (+12.4 percentage points) when lockdown measures were implemented in March 2020. This increase was more pronounced for some patient groups (70-79 year-olds: +13.7 percentage points; females: +12.8 percentage points), regions (North West: +17.0 percentage points), medications (Leflunomide: +20.7 percentage points), and monitoring tests (Blood Pressure: +24.5 percentage points). Missed monitoring rates decreased substantially for all groups by July 2022. Substantial and consistent differences were observed in overall missed monitoring rates between several groups throughout the study. Interpretation: DMARD monitoring rates temporarily deteriorated during the COVID-19 pandemic. Deterioration coincided with the onset of lockdown measures, with monitoring rates recovering rapidly as lockdown measures were eased. Differences observed in monitoring rates between medications, tests, regions, and patient groups, highlight opportunities to tackle potential inequalities in the provision or uptake of monitoring services. Further research should aim to evaluate the causes of the differences identified between groups. Funding: None. Keywords COVID-19, electronic health records, general practice, primary health care, antirheumatic agents, methotrexate, azathioprine, leflunomide.
Background Approaches to addressing unwarranted variation in health care service delivery have traditionally relied on the prospective identification of activities and outcomes, based on a hypothesis, with subsequent reporting against defined measures. Practice-level prescribing data in England are made publicly available by the National Health Service (NHS) Business Services Authority for all general practices. There is an opportunity to adopt a more data-driven approach to capture variability and identify outliers by applying hypothesis-free, data-driven algorithms to national data sets. Objective This study aimed to develop and apply a hypothesis-free algorithm to identify unusual prescribing behavior in primary care data at multiple administrative levels in the NHS in England and to visualize these results using organization-specific interactive dashboards, thereby demonstrating proof of concept for prioritization approaches. Methods Here we report a new data-driven approach to quantify how “unusual” the prescribing rates of a particular chemical within an organization are as compared to peer organizations, over a period of 6 months (June-December 2021). This is followed by a ranking to identify which chemicals are the most notable outliers in each organization. These outlying chemicals are calculated for all practices, primary care networks, clinical commissioning groups, and sustainability and transformation partnerships in England. Our results are presented via organization-specific interactive dashboards, the iterative development of which has been informed by user feedback. Results We developed interactive dashboards for every practice (n=6476) in England, highlighting the unusual prescribing of 2369 chemicals (dashboards are also provided for 42 sustainability and transformation partnerships, 106 clinical commissioning groups, and 1257 primary care networks). User feedback and internal review of case studies demonstrate that our methodology identifies prescribing behavior that sometimes warrants further investigation or is a known issue. Conclusions Data-driven approaches have the potential to overcome existing biases with regard to the planning and execution of audits, interventions, and policy making within NHS organizations, potentially revealing new targets for improved health care service delivery. We present our dashboards as a proof of concept for generating candidate lists to aid expert users in their interpretation of prescribing data and prioritize further investigations and qualitative research in terms of potential targets for improved performance.
BACKGROUND Approaches to addressing unwarranted variation in health care service delivery have traditionally relied on the prospective identification of activities and outcomes, based on a hypothesis, with subsequent reporting against defined measures. Practice-level prescribing data in England are made publicly available by the National Health Service (NHS) Business Services Authority for all general practices. There is an opportunity to adopt a more data-driven approach to capture variability and identify outliers by applying hypothesis-free, data-driven algorithms to national data sets. OBJECTIVE This study aimed to develop and apply a hypothesis-free algorithm to identify unusual prescribing behavior in primary care data at multiple administrative levels in the NHS in England and to visualize these results using organization-specific interactive dashboards, thereby demonstrating proof of concept for prioritization approaches. METHODS Here we report a new data-driven approach to quantify how “unusual” the prescribing rates of a particular chemical within an organization are as compared to peer organizations, over a period of 6 months (June-December 2021). This is followed by a ranking to identify which chemicals are the most notable outliers in each organization. These outlying chemicals are calculated for all practices, primary care networks, clinical commissioning groups, and sustainability and transformation partnerships in England. Our results are presented via organization-specific interactive dashboards, the iterative development of which has been informed by user feedback. RESULTS We developed interactive dashboards for every practice (n=6476) in England, highlighting the unusual prescribing of 2369 chemicals (dashboards are also provided for 42 sustainability and transformation partnerships, 106 clinical commissioning groups, and 1257 primary care networks). User feedback and internal review of case studies demonstrate that our methodology identifies prescribing behavior that sometimes warrants further investigation or is a known issue. CONCLUSIONS Data-driven approaches have the potential to overcome existing biases with regard to the planning and execution of audits, interventions, and policy making within NHS organizations, potentially revealing new targets for improved health care service delivery. We present our dashboards as a proof of concept for generating candidate lists to aid expert users in their interpretation of prescribing data and prioritize further investigations and qualitative research in terms of potential targets for improved performance.
Background The COVID-19 pandemic caused significant disruption to routine activity in primary care. Medication reviews are an important primary care activity to ensure safety and appropriateness of ongoing prescribing and a disruption could have significant negative implications for patient care. Aim Using routinely collected data, our aim was to i) describe the SNOMED CT codes used to report medication review activity ii) report the impact of COVID-19 on the volume and variation of medication reviews. Design and setting With the approval of NHS England, we conducted a cohort study of 20 million adult patient records in general practice, in-situ using the OpenSAFELY platform. Method For each month between April 2019 - March 2022, we report the percentage of patients with a medication review coded monthly and in the previous 12 months. These measures were broken down by regional, clinical and demographic subgroups and amongst those prescribed high risk medications. Results In April 2019, 32.3% of patients had a medication review coded in the previous 12 months. During the first COVID-19 lockdown, monthly activity substantially decreased (-21.1% April 2020), but the rate of patients with a medication review coded in the previous 12 months was not substantially impacted according to our classification (-10.5% March 2021). There was regional and ethnic variation (March 2022 - London 21.9% vs North West 33.6%; Chinese 16.8% vs British 33.0%). Following the introduction of "structured medication reviews", the rate of structured medication review in the last 12 months reached 2.9% by March 2022, with higher percentages in high risk groups (March 2022 - care home residents 34.1%, 90+ years 13.1%, high risk medications 10.2%). The most used SNOMED CT medication review code across the study period was Medication review done - 314530002 (59.5%). Conclusion We have reported a substantial reduction in the monthly rate of medication reviews during the pandemic but rates recovered by the end of the study period.
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