Related Experiment Video
Updated: Aug 9, 2026
06:46
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
General practice closures or mergers: a survival analysis of contributing practice
Joseph Hutchinson1, Michael Anderson2, Rita Santos3
1Loughborough University, Division of Population Health, Health Services Research & Primary Care (L5) joseph.hutchinson@manchester.ac.uk.
Summary
General practice closures in England are linked to contract type, location, and patient list size. Smaller practices and those with lower funding or quality face higher risks of closure or merger.
Area of Science:
- General Practice and Primary Care Research
- Health Services Research
- Health Policy Analysis
Background:
- General practices in England have experienced significant closures and mergers since 2013, impacting healthcare accessibility.
- Understanding the factors contributing to these closures is crucial for the sustainability and recovery of general practice.
- Previous research has highlighted negative impacts, but specific risk factors remain underexplored.
Purpose of the Study:
- To investigate the association between practice characteristics (patient mix, location, workforce, funding, quality) and the risk of general practice closure or merger.
- To identify key predictors of general practice closure to inform strategies for practice recovery and stability.
- To analyze how various operational and demographic factors influence the future risk of general practice closure.
Main Methods:
- A multilevel survival analysis was conducted on all general practices in England open as of April 1, 2019, followed until April 1, 2025.
- Data on practice population characteristics, workforce, funding, and quality were collected and analyzed using Cox proportional hazards models.
- The study examined the association between these measures and the time until practice closure or merger.
Main Results:
- Practice contract type and geographic location (region and rurality) were significant factors associated with closures, with closure rates varying significantly by region.
- Smaller practices (e.g., 3,032 patients) exhibited a substantially higher risk (253%) of closure or merger compared to median-sized practices (7,256 patients).
- Increased risk was also linked to patient list decline, lower baseline funding, poorer clinical quality, higher socioeconomic deprivation, and specific contract types; GP or nurse supply was not a significant factor.
Conclusions:
- Practice contract, geographic region, practice list size, funding levels, and clinical quality are identified as critical hazards for general practice closure or merger.
- These findings underscore the importance of considering practice-specific operational and contextual factors in strategies aimed at preventing closures.
- The study provides evidence to support targeted interventions and policy adjustments to enhance the resilience and sustainability of general practices.
Related Concept Videos
01:20Comparing the Survival Analysis of Two or More Groups
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
01:21Cancer Survival Analysis
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
01:15Assumptions of Survival Analysis
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
01:18Introduction To Survival Analysis
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time until a...
The primary goal of survival analysis is to estimate survival time—the time until a...
01:26Methods of Documentation II: POMR
The Problem-Oriented Medical Record (POMR) revolutionized medical record-keeping by introducing a systematic approach focusing on the patient's problems rather than merely listing symptoms. Dr. Lawrence Weed's introduction of this method in the 1960s marked a significant advancement in medical documentation. The POMR framework consists of four key components: the database, problem list, plan of care, and progress notes.
01:24Kaplan-Meier Approach
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...