Data for this publication are extracted each month as a snapshot in time from the Primary Care Registration database within the NHAIS (National Health Application and Infrastructure Services) system. This release is an accurate snapshot as at 1 April 2024. This publication also includes monthly data outputs from the Personal Demographic Service, which will become the data source for this publication from May 2024. More information about the data source change can be found in the Data Quality Statement. GP Practice; Primary Care Network (PCN); Sub Integrated Care Board Locations (SICBL); Integrated Care Board (ICB) and NHS England Commissioning Region level data are released in single year of age (SYOA) and 5-year age bands, both of which finish at 95+, split by gender. In addition, organisational mapping data is available to derive PCN; SICBL; ICB and Commissioning Region associated with a GP practice and is updated each month to give relevant organisational mapping. Quarterly publications in January, April, July and October will include Lower Layer Super Output Area (LSOA) populations.

A quarterly reference file of active GP Practices and their list size (number of registered patients) at the start of each quarter. Local Commissioning Group (LCG) is based on the postcode of the GP Practice. Note that Practices 473 and 475 are located in the South Eastern Local Commissioning Group (Health Trust) but are managed by the Southern Trust Local Commissioning Group.

Data for this publication are extracted each month as a snapshot in time from the Primary Care Registration database within the PDS (Personal Demographics Service) system. This release is an accurate snapshot as at 1 January 2025. GP Practice; Primary Care Network (PCN); Sub Integrated Care Board Locations (SICBL); Integrated Care Board (ICB) and NHS England Commissioning Region level data are released in single year of age (SYOA) and 5-year age bands, both of which finish at 95+, split by gender. In addition, organisational mapping data is available to derive PCN; SICBL; ICB and Commissioning Region associated with a GP practice and is updated each month to give relevant organisational mapping. Quarterly publications in January, April, July and October will include Lower Layer Super Output Area (LSOA) populations.

This statistic displays the distribution of GP practices in the United Kingdom by devolved health service and patient list size in 2017. In England and Scotland, the highest proportion of GP practices have ***** to ***** patients as of 2017. In the NHS in Wales, the highest percentage of practices have to deal with patient list sizes of ***** to *****.

Data for this publication are extracted each month as a snapshot in time from the GP Payments system (Open Exeter) maintained by NHS Digital. This release is an accurate snapshot as at 1 July 2018. GP Practice; Sustainability and transformation partnership (STP); Clinical Commissioning Group (CCG); NHS England Region and NHS England Commissioning Region level data are released in single year of age (SYOA) and 5-year age bands, both of which finish at 95+, split by gender. In addition, organisational mapping data is available to derive STP; CCG; Region and Commissioning Region associated with a GP practice and is updated each month to give relevant organisational mapping. Quarterly publications in January, April, July and October will include Lower Layer Super Output Area (LSOA) populations and a topic of interest.

Data for this publication are extracted each month as a snapshot in time from the GP Payments system (Open Exeter) maintained by NHS Digital. This release is an accurate snapshot as at 1 October 2017. Since April 2014, geographical references have been taken from 2011 census information and reflect NHS England's health geography structure as at 1 April 2017. GP Practices are matched to Organisational Data Services reference data. GP Practice; Sustainability and transformation partnership (STP); Clinical Commissioning Group (CCG); NHS England Region and NHS England Commissioning Region level data are released in single year of age (SYOA) and 5-year age bands, both of which finish at 95+, split by gender. Quarterly publications in January, April, July and October will include Lower Layer Super Output Area (LSOA) populations and a topic of interest.

This dataset contains information on list sizes for all GP practices in Scotland by age and sex. All publications and supporting material to this topic area can be found on the Public Health Scotland website.

This dataset contains information on contact details and list sizes for all GP practices in Scotland. All publications and supporting material to this topic area can be found on the Public Health Scotland website.

This dataset presents the prevalence of heart failure among patients registered with GP practices in England. It reflects the proportion of individuals diagnosed with heart failure as recorded in the Quality and Outcomes Framework (QOF), a system used by NHS Digital to monitor the quality of care provided by general practices. The data is expressed as a percentage of the total practice list size and is intended to support monitoring and improvement of cardiovascular health outcomes.

Rationale Heart failure is a significant public health concern, contributing to high levels of morbidity and healthcare utilization. Monitoring its prevalence at the practice level helps identify areas with higher disease burden and supports targeted interventions. Reducing the prevalence of heart failure is a key objective in improving population health and reducing avoidable hospital admissions.

Numerator The numerator is defined as the number of patients diagnosed with heart failure, as recorded on their GP practice's disease register. This information is sourced from the Quality and Outcomes Framework (QOF), maintained by NHS Digital.

Denominator The denominator is the total number of patients registered at the GP practice (the total practice list size). This is also sourced from the QOF dataset provided by NHS Digital.

Caveats No specific caveats were noted in the source metadata. However, it is important to consider that the accuracy of prevalence data depends on the completeness and consistency of clinical coding practices across GP practices.

External References Public Health England - Fingertips Tool

Localities ExplainedThis dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations:Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs).Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities.This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address.

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

Eine vierteljährliche Referenzdatei der aktiven GP-Praxis und ihrer Listengröße (Anzahl der registrierten Patienten) zu Beginn jedes Quartals.

Background: Primary nonadherence to prescribed medications occurs when patients do not fill or dispense prescriptions written by healthcare providers. Although it has become an important public health issue in recent years, little is known about its frequency, causes, and consequences. Moreover, the pattern of risk factors shows remarkable variability across countries according to the published results. Our study aimed to assess primary nonadherence to medications prescribed by general practitioners (GPs) and its associated factors among adults in Hungary for the period of 2012–2015.Methods: Data on all general medical practices (GMPs) of the country were obtained from the National Health Insurance Fund and the Central Statistical Office. The ratio of the number of dispensed medications to the number of prescriptions written by a GP for adults was used to determine the medication adherence, which was aggregated for GMPs. The effect of GMP characteristics (list size, GP vacancy, patients’ education provided by a GMP, settlement type [urban or rural], and geographical location [by county] of the center) on adherence, standardized for patients’ age, sex, and eligibility for an exemption certificate, were investigated through generalized linear regression modeling.Results: A total of 281,315,386 prescriptions were dispensed out of 438,614,000 written by a GP. Overall, 64.1% of prescriptions were filled. According to the generalized linear regression coefficients, there was a negative association between standardized adherence and urban settlement type (b = -0.099, 95%CI = -0.103 to -0.094), higher level of education (b = -0.440, 95%CI = -0.468 to -0.413), and vacancy of the general practices (b = -0.193, 95%CI = -0.204 to -0.182). The larger GMP size proved to be a risk factor, and there was a significant geographical inequality for counties as well.Conclusions: More than one-third of the written prescriptions of GPs for adults in Hungary were not dispensed. This high level of nonadherence had great variability across GMPs, and can be explained by structural characteristics of GMPs, the socioeconomic status of patients provided, and the quality of cooperation between patients and GPs. Moreover, our findings suggest that the use of the dispensed-to-prescribed medication ratio in routine monitoring of primary health care could effectively support the necessary interventions.

The percentage of patients with established hypertension, as recorded on practice disease registers (proportion of total list size).

Definition of numerator Patients with stroke or transient ischaemic attack (TIA), as recorded on practice disease registers.

Definition of denominator Total practice list size.

Ένα τριμηνιαίο αρχείο αναφοράς των ενεργών πρακτικών GP και το μέγεθος του καταλόγου τους (αριθμός εγγεγραμμένων ασθενών) στην αρχή κάθε τριμήνου.

This dataset provides insights into the prevalence of atrial fibrillation (AF) among patients registered with GP practices in England. It captures the proportion of individuals diagnosed with AF, based on entries in the Quality and Outcomes Framework (QOF) disease registers maintained by NHS Digital. The data is presented as a percentage of the total practice list size and is intended to support cardiovascular health monitoring and service planning.

Rationale Atrial fibrillation is a common cardiac arrhythmia associated with increased risk of stroke and other cardiovascular complications. Monitoring its prevalence helps identify population health trends and supports efforts to reduce the burden of AF through early detection, effective management, and prevention strategies.

Numerator The numerator is the number of patients diagnosed with atrial fibrillation, as recorded on their GP practice's disease register. This data is sourced from the Quality and Outcomes Framework (QOF), managed by NHS Digital.

Denominator The denominator is the total number of patients registered at the GP practice (total practice list size), also sourced from the QOF dataset provided by NHS Digital.

Caveats No specific caveats were noted in the source metadata. However, the accuracy of prevalence estimates may be influenced by variations in clinical coding practices and diagnostic criteria across GP practices.

External References Public Health England - Fingertips Tool

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

BackgroundRising healthcare expenditures places the potential for substitution of hospital care towards primary care high on the political agenda. As low-risk basal cell carcinoma (BCC) care is one of the potential targets for substitution of hospital care towards primary care the objective of this study is to gain insight in the views of healthcare professionals regarding substitution of skin cancer care, and to identify perceived barriers and potential strategies to facilitate substitution.MethodsA qualitative study was conducted consisting of 40 interviews with dermatologists and GPs and three focus groups with 18 selected GPs with noted willingness regarding substitution of skin cancer care. The interviews and focus groups focused on general views, perceived barriers and potential strategies to facilitate substitution of skin cancer care, using predefined topic lists. All sessions were audio-taped, transcribed verbatim and analyzed using the program AtlasTi.ResultsGPs were generally positive regarding substitution of skin care whereas dermatologists expressed more concerns. Lack of trust in GPs to adequately perform skin cancer care and a preference of patients for dermatologists are reported as barriers by dermatologists. The main barriers reported by GPs were a lack of confidence in own skills to perform skin cancer care, a lack of trust from both patients and dermatologists and limited time and financial compensation. Facilitating strategies suggested by both groups mainly focused on improving GPs’ education and improving the collaboration between primary and secondary care. GPs additionally suggested efforts from dermatologists to increase their own and patients’ trust in GPs, and time and financial compensation. The selected group of GPs suggested practical solutions to facilitate substitution focusing on changes in organizational structure including horizontal referring, outreach models and practice size reduction.ConclusionsGPs and, to lesser extent, dermatologists are positive regarding substitution of low-risk BCC care, though report substantial barriers that need to be addressed before substitution can be further implemented. Aside from essential strategies such as improving GPs’ skin cancer education and time and financial compensation, rearranging the organizational structure in primary care and between primary and secondary care may facilitate effective and safe substitution of low-risk BCC care.

The percentage of patients with stroke or transient ischaemic attack (TIA), as recorded on practice disease registers (proportion of total list size).

Rationale Stroke is the third most common cause of death in the developed world. One quarter of stroke deaths occur under the age of 65 years. There is evidence that appropriate diagnosis and management can improve outcomes.

Definition of numerator Patients with stroke or transient ischaemic attack (TIA), as recorded on practice disease registers.

Definition of denominator Total practice list size.

Abstract

Objective. To determine whether a systematic geriatric evaluation performed by general practitioners (GPs) that includes a brief assessment of geriatric syndromes and a management plan can prevent functional decline in older patients. Design. Controlled, open-label, pragmatic cluster-randomised trial, randomising at the GP level. Setting. 42 GP practices, western Switzerland. Participants. Participating GPs had to work at least 20 hours per week as GPs in French-speaking Switzerland, and were expected to enroll ten community-dwelling adults at least 75-years-old, able to understand French, and having visited their GP at least twice in the prior year. Intervention. Yearly assessment by the GP of eight geriatric syndromes associated with ad hoc management plans. Main outcome measures. The primary outcome was, at individual participant level, the proportion of patients losing at least one instrumental activity of daily living (IADL) over two years, compared by a generalised 2-level mixed model with a logit regression. Secondary outcomes were losses in basic ADLs and quality-of-life (WHOQOL-OLD) scores. After complete case analysis, predefined sensitivity analyses were performed with last observation carried forward and considering patients who died or were institutionalized as having lost an IADL. Randomization and masking. The randomisation unit was the GP, with GPs assigned on a 1:1 ratio to the intervention or usual care arm, based on a computer-based randomisation list, using uneven block sizes. GPs were allocated to their respective arm after patient enrolment. The study staff performing the main outcome measures (telephone interviews), study coordinator and study statistician were blinded to the allocation. Results: 42 GPs recruited 429 participants of mean age 82·5 years (SD 4·8) at inclusion, 63% women, with 217 participants allocated to the intervention and 212 to the control arm. The proportion of patients losing at least one IADL during the course of the study was 43·6% and 47·6% in the intervention and control arms, respectively (p=0·476). Mean reduction in quality-of-life score was -0·12 and 0·74 (p=0·331). There was no difference between arms in any of the outcomes considered. Concerning adhesion to the intervention, 85·7% (186/217) of patients in the intervention arm had at least one assessment and GPs adhered to 43·4% of the recommendations in the management plans. Conclusion. A yearly geriatric evaluation associated with a management plan conducted systematically among community-dwelling, ≥75-year-old patients in GP practices does not lessen functional decline. Trial registration. The trial was registered in ClinicalTrials.gov with identifier NCT02618291.

Geographic coverage

Western Switzerland (cantons of Vaud, Neuchâtel, Fribourg)

Analysis unit

429 individuals from 42 clusters

Universe

family medicine patients aged 75 years and older

Sampling procedure

Consecutive enrolment or random sampling at family physician level

Mode of data collection

phone interview, data extraction from medical file

Research instrument

eCRF (secuTrial)

Cleaning operations

Electronic and central data validation AGE3 data are collected via secuTrial. Predefined checks incorporated in secuTrial concern mainly: - Respect of the time intervals between annual study visits. - Height (>= 120 and <220 cm)

Secutrial software has an inbuilt data management tool allowing investigators to produce queries. Each form is revised by a member of the study staff. After solving of the pending queries, each form is locked, preventing further modification.

Completion status of each section was predefined during database development. The secuTrial system includes visual aid to inform of data entry completion. Monthly exports of the data as .csv files were performed by the data manager and stored in her personal folder. Data were then transformed to respect anonymisation (excluding Contact information) and blinding of study coordinator (_4_egb and _10_plansoins forms unlinked to study ID), and stored in .dta format for further management within Stata. The study coordinator performed monthly data monitoring, to identify missing items or discrepancies, in which case an electronic query was made in secuTrial to the person responsible of data entry for this section. Source data validation (when applicable) was performed by the study assistant during his/her annual visits to each practice (“review A”). These visits were also an opportunity to solve all remaining queries. A final data validation took place when data entry was considered complete. The database was locked after all study data had been validated and monitoring review had been completed.

The General Medical Practices industry’s revenue is anticipated to stay flat overall during the five years through 2025-26. However, in 2025-26, revenue is estimated to edge up by 1% to £16.6 billion. The industry has faced numerous pressures that have led it to stagnate. Despite high demand from an ageing population, coupled with a rise in chronic illnesses like obesity and diabetes leading to a surge in demand for healthcare services, long waiting lists, chronic underfunding and staff shortages persist. There has been a notable decline in the number of qualified GPs in recent years – according to the British Medical Association, there were 1,115 fewer fully qualified GPs in April 2025 than in September 2015. In 2024, collective action from GPs against NHS contracts, partly due to only 8.1% of total NHS funding being spent on primary care, according to the NHS Confederation, led to services faltering and backlogs increasing. As reported by NHS England, backlogs have been rising by an average of 18,751 patients each month in early 2025. In recent years, the emergence of private-sector providers as a competitive alternative for patients seeking faster access to healthcare services has started to reshape the industry. Low disposable income hinders individual household demand for private healthcare, but corporations continue to invest in it for employee benefits. More private providers are being handed NHS contracts, helping a struggling NHS stay on its feet. Such partnerships are changing revenue and profit patterns within the industry. Typically, publicly backed GPs are not for profit and any surplus is reinvested back into the system, but privately backed GPs keep hold of their profit for shareholders and management. Over the five years through 2030-31, revenue is forecast to expand at a compound annual rate of 3.6% to reach £19.9 billion. The Labour government’s £29 billion transformation plan is looking to revitalise the NHS over the 10 years through 2035, improving GP infrastructure, patient handling and contractual models. This aims to enhance patient access, while alleviating administrative burdens and should help to bolster general medical practices' revenue. The new 2025-26 NHS GP contract looks to enhance the digitisation of the NHS, cutting back time spent on admin and freeing up more time for consultations, bolstering productivity.

Warning: Large file size (over 1GB).

Each monthly data set is large (over 4 million rows), but can be viewed in standard software such as Microsoft WordPad (save by right-clicking on the file name and selecting 'Save Target As', or equivalent on Mac OSX). It is then possible to select the required rows of data and copy and paste the information into another software application, such as a spreadsheet.

What does the data cover?

General practice prescribing data is a list of all medicines, dressings and appliances that are prescribed and dispensed each month. A record will only be produced when this has occurred and there is no record for a zero total.

For each practice in England, including GP Practices, the following information is presented at presentation level for each medicine, dressing and appliance, (by presentation name):

• the total number of items prescribed and dispensed
• the total net ingredient cost
• the total actual cost
• the total quantity

The data covers NHS prescriptions written in England and dispensed in the community in the UK. Prescriptions written in England but dispensed outside England are included. The data includes prescriptions written by GPs and other non-medical prescribers (such as nurses and pharmacists) who are attached to GP practices.

Practices are identified only by their national code, so an additional data file - linked to the first by the practice code - provides further detail in relation to the practice.

Presentations are identified only by their BNF code, so an additional data file - linked to the first by the BNF code - provides the chemical name for that presentation.