List Size Research Articles

General practice characteristics associated with pay-for-performance in the UK: a systematic review.

The Quality and Outcomes Framework (QOF), a pay-for-performance programme, has been the most widespread quality initiative in National Health Service (NHS) general practice since 2004. It has contributed between 25% and 8% of practices' income during this time, but concerns about its effect on equity have been raised. Understand which practice characteristics are associated with QOF performance. Systematic review, NHS general practice. MEDLINE, Embase, CINAHL+, Web-of-Science and grey literature were searched for studies examining the association between general practice characteristics and QOF performance. Twenty-two studies, published between 2006 and 2022, exploring the relationship between six population and 15 organisational characteristics and QOF measures were found. Most studies were cross-sectional, of English general practices, and used data from the early years of QOF. A negative association was frequently found between overall QOF performance and socioeconomic deprivation; proportion of registered patients>65; list size; mean general practitioner (GP) age; and Alternative Provider Medical Services contracts. Group practices (versus single-handed); more full-time-equivalent GPs; and being a training practice were frequently associated with better overall QOF performance. The associations of most other characteristics with performance were inconsistent. Associations with characteristics both within and outside practices' control were identified. Pay-for-performance instruments may systematically disadvantage practices serving those at greatest risk of ill-health, such as older and more deprived populations. Given the cross-sectional design of many studies and focus on the early years of QOF, more up-to-date evidence is needed to understand if and why these relationships persist.

Catamorphic Abstractions for Constrained Horn Clause Satisfiability

Abstract Catamorphisms are functions that are recursively defined on list and trees and, in general, on algebraic data types (ADTs), and are often used to compute suitable abstractions of programs that manipulate ADTs. Examples of catamorphisms include functions that compute size of lists, orderedness of lists, and height of trees. It is well known that program properties specified through catamorphisms can be proved by showing the satisfiability of suitable sets of constrained Horn clauses (CHCs). We address the problem of checking the satisfiability of those sets of CHCs, and we propose a method for transforming sets of CHCs into equisatisfiable sets where catamorphisms are no longer present. As a consequence, clauses with catamorphisms can be handled without extending the satisfiability algorithms used by existing CHC solvers. Through an experimental evaluation on a nontrivial benchmark consisting of many list and tree processing algorithms expressed as sets of CHCs, we show that our technique is indeed effective and significantly enhances the performance of state-of-the-art CHC solvers.

Anti-factor is FPT Parameterized by Treewidth and List Size (but Counting is Hard)

AbstractIn the general AntiFactor problem, a graph G and, for every vertex v of G, a set $$X_v\subseteq {\mathbb {N}}$$ X v ⊆ N of forbidden degrees is given. The task is to find a set S of edges such that the degree of v in S is not in the set $$X_v$$ X v . Standard techniques (dynamic programming plus fast convolution) can be used to show that if M is the largest forbidden degree, then the problem can be solved in time $$(M+2)^{{{\text {tw}}}}\cdot n^{{\mathcal {O}}(1)}$$ ( M + 2 ) tw · n O ( 1 ) if a tree decomposition of width $${{\text {tw}}}$$ tw is given. However, significantly faster algorithms are possible if the sets $$X_v$$ X v are sparse: our main algorithmic result shows that if every vertex has at most $$x$$ x forbidden degrees (we call this special case AntiFactorx), then the problem can be solved in time $$(x+1)^{{\mathcal {O}}({{\text {tw}}})}\cdot n^{{\mathcal {O}}(1)}$$ ( x + 1 ) O ( tw ) · n O ( 1 ) . That is, AntiFactorx is fixed-parameter tractable parameterized by treewidth $${{\text {tw}}}$$ tw and the maximum number $$x$$ x of excluded degrees. Our algorithm uses the technique of representative sets, which can be generalized to the optimization version, but (as expected) not to the counting version of the problem. In fact, we show that #AntiFactor1 is already #$$[1]$$ [ 1 ] -hard parameterized by the width of the given decomposition. Moreover, we show that, unlike for the decision version, the standard dynamic programming algorithm is essentially optimal for the counting version. Formally, for a fixed nonempty set $$X$$ X , we denote by $$X$$ X -AntiFactor the special case where every vertex v has the same set $$X_v=X$$ X v = X of forbidden degrees. We show the following lower bound for every fixed set $$X$$ X : if there is an $$\epsilon >0$$ ϵ > 0 such that #$$X$$ X -AntiFactor can be solved in time $$(\max X+2-\epsilon )^{{{\text {tw}}}}\cdot n^{{\mathcal {O}}(1)}$$ ( max X + 2 - ϵ ) tw · n O ( 1 ) given a tree decomposition of width $${{\text {tw}}}$$ tw , then the counting strong exponential-time hypothesis (#SETH) fails.

Factors affecting prostate cancer detection through asymptomatic PSA testing in primary care in England: Evidence from the 2018 National Cancer Diagnosis Audit.

Background Prostate-Specific Antigen (PSA) is used in primary care for prostate cancer detection, either for symptomatic assessment or asymptomatic testing following an informed decision. Aim To estimate the proportion of prostate cancer cases diagnosed following asymptomatic PSA testing, and patient and practice factors influencing this route. Design and setting 2018 English National Cancer Diagnosis Audit (NCDA) data were analysed, with linkage to the national cancer registry, practice-level Quality Outcomes Framework (QOF), and General Practice Patient Survey (GPPS) data. All 2018 NCDA patients with a diagnosis of prostate cancer were included (n = 9,837). Method Patients with recorded biomarker testing and no recorded symptoms prior to diagnosis were classified as asymptomatic PSA detected prostate cancer. Patient (age, ethnicity, deprivation, co-morbidities) and GP practice (geographical location, area deprivation, list size, urgent suspected cancer referral rate, QOF outcomes, GPPS results) factors were analysed for association with asymptomatic PSA testing using mixed effects logistic regression models. Results 1,884 out of 9,837 (19%) prostate cancer cases were detected following asymptomatic PSA testing, 982 (52.1%) of whom were patients aged 50-69 years. Younger age, non-White ethnicity, lower deprivation, and lower co-morbidity count were associated with an increased likelihood of diagnosis following asymptomatic PSA testing. There was a 13-fold variation between practices in the odds of asymptomatic PSA-detected cases, without clear explanatory GP practice-level factors. Conclusion One in five patients with prostate cancer in England are diagnosed after asymptomatic PSA testing in primary care, with large variation in asymptomatic PSA detection between GP practices.

A path splitting and pruning strategy on list decoder for PAC codes

AbstractRecently, Arıkan proposed a polarization‐adjusted convolutional (PAC) codes, demonstrating their superior error correction performance over polar codes at short block lengths. It was confirmed that PAC codes approached the optimal performance achievable with limited code length. This paper proposes a novel low‐complexity list decoding algorithm for PAC codes, incorporating path splitting and pruning strategies based on a set of highly reliable information bits. Simulation results reveal that the proposed algorithm significantly reduces sorting complexity and average list size, all while incurring negligible performance loss. Unlike previous pruning algorithms designed for polar codes, the proposed strategy eliminates the need to individually assess the reliability of decoding paths in each decoding process. Instead, the algorithm minimizes redundant decoding paths through a high‐reliability information bit set, constructed using Monte Carlo experiments.

Improving dictionary-based named entity recognition with deep learning.

Dictionary-based named entity recognition (NER) allows terms to be detected in a corpus and normalized to biomedical databases and ontologies. However, adaptation to different entity types requires new high-quality dictionaries and associated lists of blocked names for each type. The latter are so far created by identifying cases that cause many false positives through manual inspection of individual names, a process that scales poorly. In this work, we aim to improve block list s by automatically identifying names to block, based on the context in which they appear. By comparing results of three well-established biomedical NER methods, we generated a dataset of over 12.5 million text spans where the methods agree on the boundaries and type of entity tagged. These were used to generate positive and negative examples of contexts for four entity types (genes, diseases, species, and chemicals), which were used to train a Transformer-based model (BioBERT) to perform entity type classification. Application of the best model (F1-score = 96.7%) allowed us to generate a list of problematic names that should be blocked. Introducing this into our system doubled the size of the previous list of corpus-wide blocked names. In addition, we generated a document-specific list that allows ambiguous names to be blocked in specific documents. These changes boosted text mining precision by ∼5.5% on average, and over 8.5% for chemical and 7.5% for gene names, positively affecting several biological databases utilizing this NER system, like the STRING database, with only a minor drop in recall (0.6%). All resources are available through Zenodo https://doi.org/10.5281/zenodo.11243139 and GitHub https://doi.org/10.5281/zenodo.10289360.

The changing shape of English general practice: a retrospective longitudinal study using national datasets describing trends in organisational structure, workforce and recorded appointments

ObjectiveTo describe trends in the organisational structure, workforce and recorded appointments by role in English general practice.DesignRetrospective longitudinal study.SettingEnglish general practice.Data sources and participantsNHS England, Office for Health Improvement and...

Ongoing Decline in Continuity With GPs in English General Practices: A Longitudinal Study Across the COVID-19 Pandemic.

Relationship continuity of care has declined across English primary health care, with cross-sectional and longitudinal variations between general practices predicted by population and service factors. We aimed to describe cross-sectional and longitudinal variations across the COVID-19 pandemic and determine whether practice factors predicted the variations. We conducted a longitudinal, ecological study of English general practices during 2018-2022 with continuity data, excluding practices with fewer than 750 patients or National Health Service (NHS) payments exceeding £500 per patient. Variables were derived from published data. The continuity measure was the product of weighted responses to 2 General Practice Patient Survey questions. In a multilevel mixed-effects model, the fixed effects were 11 variables' interactions with time: baseline continuity, NHS region, deprivation, location, percentage White ethnicity, list size, general practitioner and nurse numbers, contract type, NHS payments per patient, and percentage of patients seen on the same day as booking. The random effects were practices. Main analyses were based on 6,010 practices (out of 7,190 active practices). During 2018-2022, mean continuity in these practices declined (from 29.3% to 19.0%) and the coefficient of variation across practices increased (from 48.1% to 63.6%). Both slopes were steepest between 2021 and 2022. Practices having more general practitioners and higher percentages of patients seen the same day had slower declines. Practices having higher baseline continuity, located in certain non-London regions, and having higher percentages of White patients had faster declines. The remaining variables were not predictors. Variables potentially associated with greater appointment availability predicted slower declines in continuity, with worsening declines and relative variability immediately after the COVID-19 lockdown, possibly reflecting surges in demand. To achieve better levels of continuity for those seeking it, practices can increase appointment availability within appointment systems that prioritize continuity.Annals Early Access article.

The changing shape of general practice in Scotland: the rise of the ‘megapractice’

ObjectivesTo describe the trends in the nature of general practices in Scotland between 2014/15 and 2023. Study designDescriptive ecological study. MethodsWe obtained data from Public Health Scotland and used general practitioner (GP) practice codes, practice names, and the General Medical Council (GMC) numbers of their listed GPs to describe trends in practice characteristics and to identify individual practices that were likely to be operating as a single entity. ResultsDefining practice entities is difficult because different GP practice codes are often retained when GPs are performing across multiple practices. If GP practice codes alone are used, the median practice list size increased from 5094 to 5881, and the mean from 5588 to 6289, between 2013/14 and 2020/21. There was one outlier practice that grew to have over 45,000 patients registered by 2020/21. However, this underestimates the extent of this new mega-practice phenomenon. Using the GMC numbers of GPs listed as performers to identify where the same GPs are working across multiple GP practice codes, we identified a series of mega-practices that span across health board areas and which have experienced a dramatic increase in their list size (with the two largest having list sizes of over 101,000 and 77,000 patients, respectively). ConclusionsFurther research is needed to better understand: how mega-practices provide services and whether this differs from other practices; where financial rewards accumulate within mega-practices; differences in staffing between mega-practices and other models; and the impacts mega-practices have on the quality and continuity of care and on health and inequality outcomes.

Practice list size, workforce composition and performance in English general practice: a latent profile analysis

BackgroundFollowing government calls for General Practices in England to work at scale, some practices have grown in size from traditionally small, General Practitioner (GP)-led organisations to large multidisciplinary enterprises. We assessed the effect of practice list size and workforce composition on practice performance in clinical outcomes and patient experience.MethodsWe linked five practice-level datasets in England to obtain a single dataset of practice workforce, list size, proportion of registered patients ≥ 65 years of age, female-male sex ratio, deprivation, rurality, GP contract type, patient experience of care, and Quality and Outcomes Framework (QOF) and non-QOF clinical processes and outcomes. Latent Profile Analysis (LPA) was used to cluster general practices into groups based on practice list size and workforce composition. Bayesian Information Criterion, Akaike Information Criterion and deliberation within the research team were used to determine the most informative number of groups. One-way ANOVA was used to assess how groups differed on indicator variables and other variables of interest. Linear regression was used to assess the association between practice group and practice performance.ResultsA total of 6024 practices were available for class assignment. We determined that a 3-class grouping provided the most meaningful interpretation; 4494 (74.6%) were classified as ‘Small GP-reliant practices’, 1400 (23.2%) were labelled ‘Medium-size GP-led practices with a multidisciplinary team (MDT) input’ and 131 (2.2%) practices were named ‘Large multidisciplinary practices’. Small GP-reliant practices outperformed larger multidisciplinary practices on all patient-reported indicators except on confidence and trust where medium-size GP-led practices with MDT input appeared to do better. There was no difference in performance between small GP-reliant practices and larger multidisciplinary practices on QOF incentivised indicators except on asthma reviews where medium-size GP-led practices with MDT input performed worse than smaller GP-reliant practices and immunisation coverage where the same group performed better than smaller GP-reliant practices. For non-incentivised indicators, larger multidisciplinary practices had higher cancer detection rates than small GP-reliant practices.ConclusionSmall GP-reliant practices were found to provide better patient reported access, continuity of care, experience and satisfaction with care. Larger multidisciplinary practices appeared to have better cancer detection rates but had no effect on other clinical processes and outcomes. As England moves towards larger multidisciplinary practices efforts should be made to preserve good patient experience.

Review of lidocaine plaster prescribing and monitoring in primary care

Abstract Introduction Lidocaine medicated plasters (LMPs) are accepted by the Scottish Medicines Consortium (SMC) for restricted use in post-herpetic neuralgia where first-line therapies are ineffective or intolerable.[1] Subsequently, LMPs are restricted for use in post-herpetic neuralgia within a large NHS board with Ralvo as formulary brand due to cost-effectiveness. Despite this, the spend on LMPs is increasing with the cost per 1000 list size above the national average.[2] Aim To review and improve LMP prescribing and monitoring in a general practice. Methods An audit within a GP practice was undertaken by conducting an EMIS search to extract all patients prescribed LMPs within the previous 6 months from December 2022. A baseline audit was completed to determine compliance against the criteria (standards set as 100%), shown in Table 1. Data were analysed using Microsoft Excel. In the interest of improving audit results, a pharmacist then conducted telephone reviews with a view to stopping LMP if appropriate, reducing prescription quantities and/or switching to Ralvo. Post review, criteria were re-audited to determine the impact. Following this, an education session was conducted. Results The results against the standards are shown in Table 1. The LMP reviews resulted in: therapy stopped (n=2; 8%), therapy reduced (n=7; 26%), therapy continued (n=11; 40%), and therapy removed from repeat (n=7; 26%). Reductions were achieved by reducing the number of patches, cutting patches or increasing the patch-free interval. Some patients continued therapy despite off-license indication due to a significant reduction in pain score and benefit in physical function. Following the audit and review of LMP, an informal general practitioner education session was conducted to promote adherence to formulary and SMC recommendations, aiming to prevent LMP initiation for off-license indications. Impact was not studied. Conclusion There is a lack of compliance with SMC and formulary recommendations with all patients in this study being prescribed LMPs for off-licensed indications. Pharmacy involvement in regular reviews could ensure patients are prescribed the most cost-effective brand and ongoing treatment appropriateness assessed, particularly for off-license indications. The study was implemented in one general practice; therefore, there is scope for extrapolation across the National Health Service board with aims to reduce LMP prescription costs and medication burden. Further work is also required to achieve a change in prescribing habits.

Fast decoding of lifted interleaved linearized Reed–Solomon codes for multishot network coding

Martínez-Peñas and Kschischang (IEEE Trans. Inf. Theory 65(8):4785–4803, 2019) proposed lifted linearized Reed–Solomon codes as suitable codes for error control in multishot network coding. We show how to construct and decode lifted interleaved linearized Reed–Solomon (LILRS) codes. Compared to the construction by Martínez-Peñas–Kschischang, interleaving allows to increase the decoding region significantly and decreases the overhead due to the lifting (i.e., increases the code rate), at the cost of an increased packet size. We propose two decoding schemes for LILRS that are both capable of correcting insertions and deletions beyond half the minimum distance of the code by either allowing a list or a small decoding failure probability. We propose a probabilistic unique Loidreau–Overbeck-like decoder for LILRS codes and an efficient interpolation-based decoding scheme that can be either used as a list decoder (with exponential worst-case list size) or as a probabilistic unique decoder. We derive upper bounds on the decoding failure probability of the probabilistic-unique decoders which show that the decoding failure probability is very small for most channel realizations up to the maximal decoding radius. The tightness of the bounds is verified by Monte Carlo simulations.

Relationships between the Structural Characteristics of General Medical Practices and the Socioeconomic Status of Patients with Diabetes-Related Performance Indicators in Primary Care.

The implementation of monitoring for general medical practice (GMP) can contribute to improving the quality of diabetes mellitus (DM) care. Our study aimed to describe the associations of DM care performance indicators with the structural characteristics of GMPs and the socioeconomic status (SES) of patients. Using data from 2018 covering the whole country, GMP-specific indicators standardized by patient age, sex, and eligibility for exemption certificates were computed for adults. Linear regression models were applied to evaluate the relationships between GMP-specific parameters (list size, residence type, geographical location, general practitioner (GP) vacancy and their age) and patient SES (education, employment, proportion of Roma adults, housing density) and DM care indicators. Patients received 58.64% of the required medical interventions. A lower level of education (hemoglobin A1c test: β = -0.108; ophthalmic examination: β = -0.100; serum creatinine test: β = -0.103; and serum lipid status test: β = -0.108) and large GMP size (hemoglobin A1c test: β = -0.068; ophthalmological examination β = -0.031; serum creatinine measurement β = -0.053; influenza immunization β = -0.040; and serum lipid status test β = -0.068) were associated with poor indicators. A GP age older than 65 years was associated with lower indicators (hemoglobin A1c test: β = -0.082; serum creatinine measurement: β = -0.086; serum lipid status test: β = -0.082; and influenza immunization: β = -0.032). Overall, the GMP-level DM care indicators were significantly influenced by GMP characteristics and patient SES. Therefore, proper diabetes care monitoring for the personal achievements of GPs should involve the application of adjusted performance indicators.

How Toddlers Use Core and Fringe Vocabulary: What's in an Utterance?

Selecting vocabulary for preliterate individuals who use augmentative and alternative communication presents multiple challenges, as the number of symbols provided must be balanced with cognitive, motoric, and other needs. Prioritizing certain types of vocabulary thus becomes a necessity. For example, prioritizing core vocabulary-that is, words that are commonly used across a group of people and contexts-is a common practice that attempts to address some of these issues. However, most core vocabulary research to date has narrowly focused on individual word counts, ignoring other critical aspects of language development such as how vocabulary aligns with typical development and how children use core and fringe vocabulary within their utterances. Descriptive and inferential statistics were used to analyze 112 transcripts to describe how typically developing toddlers (aged 2.5 years) use core and fringe vocabulary within their utterances, in reference to a range of commonly used core vocabulary lists. Results indicated that the proportion of the toddlers' utterances that consisted of only core, only fringe, or core + fringe vocabulary varied dramatically depending on the size of the core vocabulary list used, with smaller core lists yielding few "core-only" utterances. Furthermore, utterances containing both core and fringe vocabulary were both grammatically and semantically superior to utterances containing only core or only fringe vocabulary, as evidenced by measures such as mean length of utterance and total number of words. Thus, relying on word frequency counts is an insufficient basis for selecting vocabulary for aided preliterate communicators.

Education to improve timeliness of shingles diagnosis in primary care: a cluster randomised study within a trial with nested qualitative study.

Herpes zoster (shingles) is normally diagnosed clinically. Timely diagnosis is important so that antiviral treatment can be started soon after rash onset. To assess whether a practice-level educational intervention, aimed at non-clinical patient-facing staff, improves the timely assessment of patients with shingles. This was a cluster randomised study within a trial (SWAT) with nested qualitative study in general practices in England. Practices were cluster randomised 1:1, stratified by centre and minimised by practice list size and Index of Multiple Deprivation score. Intervention practices were sent educational materials, highlighting the common presenting features of shingles and what action to take if suspected. The primary and secondary outcomes were the mean proportion of patients per practice seen within 72 and 144 h of rash onset, respectively. Comparison between groups was conducted using linear regression, adjusting for randomisation variables. Semi-structured interviews with practice staff in intervention practices explored views and opinions about the intervention. In total, 67 practices were enrolled; 34 randomised to the intervention and 33 to the control. The mean difference in proportion of patients seen within 72 and 144 h was -0.132 (95% confidence interval [CI] = -0.308 to 0.043) and -0.039 (95% CI = -0.158 to 0.080), respectively. In intervention practices, 90.9% reported distributing the educational materials; however, engagement with these was suboptimal. Twelve participants were interviewed, and the poster component of the intervention was said to be easiest to implement. Our educational intervention did not improve the timely assessment of patients with shingles. This may be the result of poor intervention engagement.

Does workforce explain the relationship between funding and patient experience? A mediation analysis of primary care data in England

ObjectivesTo determine whether general practitioner (GP) workforce contributes to the link between practice funding and patient experience. Specifically, to determine whether increased practice funding is associated with better patient experience,...

Appraisal of National Institute for Health and Care Research activity in primary care in England: cross-sectional study.

The National Institute for Health and Care Research (NIHR) was set up to enhance clinical and health research activity in a variety of National Health Service (NHS) healthcare settings, including primary care. To appraise how overall General Practitioner (GP) practice performance, location, and staffing levels may interact with NIHR Portfolio activity in primary care in England. Cross-sectional summary of GP practice research activity and practice descriptors; complete data from 6,171 GP practices was collated from NIHR (using data for 2013-2023 for Portfolio studies), Public Health England, Care Quality Commission, and NHS Digital sources, respectively. In primary care, 1 million patients have been recruited into NIHR Portfolio studies in the last decade. The top 10% of practices-measured by different studies recruited to-contributed over 50% of that accrual. When the top decile of GP practices is compared to the 20% least active GP practices, research activity is significantly and individually linked with larger GP practices. Furthermore, it is significantly yet modestly associated with GP practice performance (positive patient feedback, Care Quality Commission rating), lower locality deprivation levels, and lower patient to GP ratios. Research activity in GP practices is-as seen previously with hospitals-significantly linked with better GP practice performance and patient feedback. Practice list size and staffing levels in particular interact with the aforementioned. This should be taken into account when determining strategies to increase patient and GP practice participation in NIHR Portfolio research studies.

A simulation-based analysis of the impact of rhetorical citations in science

Authors of scientific papers are usually encouraged to cite works that meaningfully influenced their research (substantive citations) and avoid citing works that had no meaningful influence (rhetorical citations). Rhetorical citations are assumed to degrade incentives for good work and benefit prominent papers and researchers. Here, we explore if rhetorical citations have some plausibly positive effects for science and disproportionately benefit the less prominent papers and researchers. We developed a set of agent-based models where agents can cite substantively and rhetorically. Agents first choose papers to read based on their expected quality, become influenced by those that are sufficiently good, and substantively cite them. Next, agents fill any remaining slots in their reference lists with rhetorical citations that support their narrative, regardless of whether they were actually influential. We then turned agents’ ability to cite rhetorically on-and-off to measure its effects. Enabling rhetorical citing increased the correlation between paper quality and citations, increased citation churn, and reduced citation inequality. This occurred because rhetorical citing redistributed some citations from a stable set of elite-quality papers to a more dynamic set with high-to-moderate quality and high rhetorical value. Increasing the size of reference lists, often seen as an undesirable trend, amplified the effects. Overall, rhetorical citing may help deconcentrate attention and make it easier to displace established ideas.

Factors associated with cervical screening coverage: a longitudinal analysis of English general practices from 2013 to 2022.

Cervical cancer remains an important global public health concern. Understanding the factors contributing to a decline in screening uptake in high-income countries is fundamental to improving screening rates. We aimed to identify general practice and patient characteristics related to cervical screening coverage in England between 2013 and 2022. We analyzed a panel of 59271 General Practice (GP)-years from 7881 GP practices. We applied correlated random effects regression to examine the association between cervical screening uptake and a rich set of GP practice workforce, size, quality and patient characteristics. Our results show a decline in overall screening rates from 2013/14 to 2021/22 from 77% to 72%. We find GP workforce and list size characteristics are strongly related to screening rates. An increase in 1 FTE Nurse per 1000 patients is related to a 1.94 percentage point increase in cervical screening rates. GP practices located in more deprived areas have lower screening rates. GP workforce and patient characteristics need to be considered by decision-makers to increase screening rates. The implementation of self-sampling screening methods could help address some of the current barriers to screening, including lack of healthcare staff and facilities.

Diversity Balancing in Two-Stage Collaborative Filtering for Book Recommendation Systems

A book recommender system is a system used to provide relevant book recommendations for readers. One approach that is often used in recommender systems is Collaborative Filtering (CF). CF provides book recommendations based on books liked by other similar users. However, CF only provides recommendations for items that are popular, so items that are less popular will be difficult to recommend. Therefore, we propose a book recommendation system based on Two-stages CF using the Diversity Balancing method. Diversity Balancing method in CF is used to balance diversity in the recommendation results by replacing popular items with less popular relevant items. System accuracy is measured using precision and recall, while diversity is measured using personal diversity and aggregate diversity. The test results show that the accuracy of the proposed system increases with the increasing number of recommended items. meanwhile, the diversity of recommended items continues to decrease as more items are included in the recommendation list. In consideration of the trade-off between accuracy and diversity, our system achieves a recall score of 0.301, a precision score of 0.282, a PD score of 0.048, and an AD score of 0.095 with a recommendation list size of 8 items.