Modelling the recovery of elective waiting lists following COVID-19: scenario projections for England

Background: A significant indirect impact of COVID-19 has been the increasing elective waiting times observed in many countries. In England's National Health Service, the waiting list has grown from 4.4 million in February 2020 to 5.7m by August 2021. Aims: The objective of this study was to estimate the trajectory of future waiting list size and waiting times to December 2025. Methods: A scenario analysis was performed using computer simulation and publicly available data as of November 2021. Future demand assumed a phased return of various proportions (0, 25, 50 and 75%) of the estimated 7.1 million referrals 'missed' during the pandemic. Future capacity assumed 90, 100 and 110% of that provided in the 12 months immediately before the pandemic. Results: As a worst case, the waiting list would reach 13.6m (95% CI: 12.4m to 15.6m) by Autumn 2022, if 75% of missed referrals returned and only 90% of pre pandemic capacity could be achieved. Under this scenario, the proportion of patients waiting under 18 weeks would reduce from 67.6% in August 2021 to 42.2% (37.4% to 46.2%) with the number waiting over 52 weeks reaching 1.6m (0.8m to 3.1m) by Summer 2023. At this time, 29.0% (21.3% to 36.8%) of patients would be leaving the waiting list before treatment. Waiting lists would remain pressured under even the most optimistic of scenarios considered, with 18-week performance struggling to maintain 60% (against the 92% constitutional target). Conclusions: This study reveals the long-term challenge for the NHS in recovering elective waiting lists as well as potential implications for patient outcomes and experience.

Comparative analysis of routing techniques in chord overlay network

Overlay networks are not a new field or area of study. This domain of computing will someday drive P2P systems in various application areas such as block-chain, energy trading, video multicasting, and distributed file storage. This study highlights the two widely known methods of routing information employed in one of such overlay networks called chord. In this study, simulations of both routing modes (iterative and recursive) and their variations under no-churn (leaving and joining of nodes) and churn conditions was carried out. The routing parameter (successor list size) was varied for each of the routing techniques in a simulation study. The results obtained show that semi recursive routing gives a better routing performance under churn scenarios.

On Error Probability of CRC/Polar Codes with List Decoding

<p>In this work the study has been done on the performance pertaining to the binary antipodal AWGN channel for rate ½ coding approaches, with short and medium blocklengths. This work emphasizes on the contributions of various events leading to block error and their dependence on signal-to-noise ratio, decoder list size, CRC length, if any, and the role of list sorting. Furthermore, this work generalizes to variations, including Reed-Muller/Polar codes that follow the polarization and the method of successive decoding.<br></p>

On Error Probability of CRC/Polar Codes with List Decoding

<p>In this work the study has been done on the performance pertaining to the binary antipodal AWGN channel for rate ½ coding approaches, with short and medium blocklengths. This work emphasizes on the contributions of various events leading to block error and their dependence on signal-to-noise ratio, decoder list size, CRC length, if any, and the role of list sorting. Furthermore, this work generalizes to variations, including Reed-Muller/Polar codes that follow the polarization and the method of successive decoding.<br></p>

A new formula for managing family doctors’ patient list in Portugal

In Portugal, family doctors work with a well-defined list of patients to whom they provide healthcare throughout their lives. Several studies showed that larger list sizes are associa- ted with poorer health outcomes and compromise the quality of care. A significant increase in the average list size has been observed in recent years due to the Portuguese unfavorable socioeconomic context and the lack of family doctors. In 2017, the Portuguese Association of General and Fa- mily Medicine (APMGF) developed technical and scientific research that ultimately typified a set of different clinical practice contexts. It considers the geographic and socioeconomic characteristics and a set of population-based indicators, adjusting the list size according to the population’s specific needs. Such adjustments ensure health care services with better quality, safety, efficacy, and personalized to their features. In this paper, a brief review is made on this topic, focusing on the work developed by APMGF and its main results.

Self-Declared Roma Ethnicity and Health Insurance Expenditures: A Nationwide Cross-Sectional Investigation at the General Medical Practice Level in Hungary

The inevitable rising costs of health care and the accompanying risk of increasing inequalities raise concerns. In order to make tailored policies and interventions that can reduce this risk, it is necessary to investigate whether vulnerable groups (such as Roma, the largest ethnic minority in Europe) are being left out of access to medical advances. Objectives: The study aimed to describe the association between general medical practice (GMP) level of average per capita expenditure of the National Health Insurance Fund (NHIF), and the proportion of Roma people receiving GMP in Hungary, controlled for other socioeconomic and structural factors. Methods: A cross-sectional study that included all GMPs providing care for adults in Hungary (N = 4818) was conducted for the period 2012–2016. GMP specific data on health expenditures and structural indicators (GMP list size, providing care for adults only or children also, type and geographical location of settlement, age of GP, vacancy) for secondary analysis were obtained from the NHIF. Data for the socioeconomic variables were from the last census. Age and sex standardized specific socioeconomic status indicators (standardized relative education, srEDU; standardized relative employment, srEMP; relative housing density, rHD; relative Roma proportion based on self-reported data, rRP) and average per capita health expenditure (standardized relative health expenditure, srEXP) were computed. Multivariate linear regression model was applied to evaluate the relationship of socioeconomic and structural indicators with srEXP. Results: The srEDU had significant positive (b = 0.199, 95% CI: 0.128; 0.271) and the srEMP had significant negative (b = −0.282, 95% CI: −0.359; −0.204) effect on srEXP. GP age > 65 (b = −0.026, 95% CI: −0.036; −0.016), list size <800 (b = −0.043, 95% CI: −0.066; −0.020) and 800–1200 (b = −0.018, 95% CI: −0.031; −0.004]), had significant negative association with srEXP, and GMP providing adults only (b = 0.016, 95% CI: 0.001;0.032) had a positive effect. There was also significant expenditure variability across counties. However, rRP proved not to be a significant influencing factor (b = 0.002, 95% CI: −0.001; 0.005). Conclusion: As was expected, lower education, employment, and small practice size were associated with lower NHIF expenditures in Hungary, while the share of self-reported Roma did not significantly affect health expenditures according to our GMP level study. These findings do not suggest the necessity for Roma specific indicators elaborating health policy to control for the risk of widening inequalities imposed by rising health expenses.

Socioeconomic status and HRT prescribing: a study of practice-level data in England

BackgroundConcerns have been raised that women from deprived backgrounds are less likely to be receiving hormone replacement therapy (HRT) treatment and its benefits, although evidence in support of this is lacking.AimTo investigate general practice HRT prescription trends and their association with markers of socioeconomic deprivation.Design and settingCross-sectional study of primary care prescribing data in England in 2018.MethodPractice-level prescribing rate was defined as the number of items of HRT prescribed per 1000 registered female patients aged ≥40 years. The association between Index of Multiple Deprivation (IMD) score and HRT prescribing rate was tested using multivariate Poisson regression, adjusting for practice proportions of obesity, smoking, hypertension, diabetes, coronary heart disease and cerebrovascular disease, and practice list size.ResultsThe overall prescribing rate of HRT was 29% lower in practices from the most deprived quintile compared with the most affluent (incidence rate ratio [IRR] = 0.71; 95% confidence interval [CI] = 0.68 to 0.73). After adjusting for all cardiovascular disease outcomes and risk factors, the prescribing rate in the most deprived quintile was still 18% lower than in the least deprived quintile (adjusted IRR = 0.82; 95% CI = 0.77 to 0.86). In more deprived practices, there was a significantly higher tendency to prescribe oral HRT than transdermal preparations (P<0.001).ConclusionThis study highlights inequalities associated with HRT prescription. This may reflect a large unmet need in terms of menopause care in areas of deprivation. Further research is needed to identify the factors from patient and GP perspectives that may explain this.

A primary care network analysis: natural communities of general practices in London

BackgroundPrimary care networks (PCNs) are a new organisational hierarchy introduced in the NHS Long Term Plan with wide-ranging responsibilities. The vision is that they represent ‘natural’ communities of general practices with boundaries that make sense to practices, other healthcare providers, and local communities.AimOur study aims to identify natural communities of general practices based on patient registration patterns, using network analysis methods and unsupervised clustering to create catchments for these communities.MethodPatients resident in and attending GP practices in London were identified from Hospital Episode Statistics from 2017 to 2018. We used a series of novel methods for unsupervised graph clustering. A cosine similarity matrix was constructed representing similarities between each general practice to each other, based on registration of patients in each Lower Super Output Area (LSOA). Unsupervised graph partitioning using Markov Multiscale Community Detection was conducted to identify communities of general practices. Catchments were assigned to each PCN based on the majority attendance from an LSOA.ResultsIn total 3 428 322 unique patients attended 1334 GPs in general practices LSOAs in London. The model grouped 1291 general practices (96.8%) and 4721 LSOAs (97.6%), into 165 mutually exclusive PCNs. The median PCN list size was 53 490 and a median of 70.1% of patients attended a general practice within their allocated PCN, ranging from 44.6% to 91.4%.ConclusionWith PCNs expected to take a role in population health management and with community providers expected to reconfigure around them, it is vital we recognise how PCNs represent their communities. This method may be used by policymakers to understand the populations and geography shared between networks.

Determinants of primary care workforce variation in England

BackgroundThe General Practice Forward View (GPFV) outlined how the government plans to attain a strengthened model of general practice. A key component of this proposal is an expansion of the workforce by employing a varied range of practitioners, in other words ‘skill mix’. A significant proportion of this investment focuses on increasing the number of ‘new’ roles such as clinical pharmacists, physiotherapists, physician associates, and paramedics.AimThe aim of this study is to examine what practice characteristics are associated with the current employment of these ‘new’ roles.MethodThe study uses practice level workforce data (2015–2019), publicly available from NHS Digital. The authors model FTE of specific workforce groups (for example, advanced nurse) as a function of deprivation, practice rurality, patient demographics (total list size and percentage of patients aged >65 years) and FTEs from other staff groups.ResultsAlthough analysis is ongoing, initial estimation suggests that the employment of ‘new’ roles has occurred in larger practices (in terms of list size), in practices with a higher proportion of patients living in deprived areas and practices with a larger proportion of patients aged >65 years. FTE for advanced nurses is negatively associated with GP FTE.ConclusionA negative correlation between advanced nurse FTE and GP FTE is potentially suggestive of substitution between roles, deliberate or otherwise. For example, practices may employ ‘new’ roles if they are unable to recruit GPs or they may recruit staff to free up GP time. Further work is needed to confirm these findings and to explore the reasons behind practice employment decisions.