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Abstract Background Allocating healthcare resources to local areas in proportion to need is an important element of many universal health care systems, aiming to provide equal access for equal need. The UK National Health Service allocates resources to relatively large areas in proportion to need, using needs-weighted capitation formulae. However, within those planning areas, local providers and commissioners also require robust methods for allocating resources to neighbourhoods in proportion to need to ensure equitable access. We therefore developed a local resource allocation formula for NHS district nursing services for a City in the North West of England, demonstrating a novel application of the national formulae principles for equitable resource allocation to small areas. Methods Using linked data from community health services, primary care, secondary care and social care, we used a zero-inflated Poisson regression to model the number of district nursing services contacts for each individual based on predictors of need, while including the supply of district nurses per head to account for historical supply induced patterns. Individual need was estimated based on the predictions from this model, keeping supply fixed at the average. We then compared the distribution of district nurses between neighbourhoods, based on our formula, to the current service staffing distribution. Results Key predictors of need for district nursing services were age, deprivation, chronic diseases such as, cardiovascular disease, chronic liver disease, neurological disease, mental ill health, learning disability living in a nursing home, living alone, and receiving palliative care. Need for district nursing services was highly weighted towards older and more deprived populations. The current distribution of staff was, however, more correlated with age than deprivation. Moving to a needs-based staffing distribution would shift staff from less deprived areas to more deprived areas potentially reducing inequalities. Conclusion A neighbourhood-level model for needs for district nursing is a useful tool that can potentially improve the allocation of resources, addressing unmet need and inequalities.

Abstract Background The challenging nature of studies with incarcerated populations and other offender groups can impede the conduct of research, particularly that involving complex study designs such as randomised control trials and clinical interventions. Providing an overview of study designs employed in this area can offer insights into this issue and how research quality may impact on health and justice outcomes. Methods We used a rule-based approach to extract study designs from a sample of 34,481 PubMed abstracts related to epidemiological criminology published between 1963 and 2023. The results were compared against an accepted hierarchy of scientific evidence. Results We evaluated our method in a random sample of 100 PubMed abstracts. An F1-Score of 92.2% was returned. Of 34,481 study abstracts, almost 40.0% (13,671) had an extracted study design. The most common study design was observational (37.3%; 5101) while experimental research in the form of trials (randomised, non-randomised) was present in 16.9% (2319). Mapped against the current hierarchy of scientific evidence, 13.7% (1874) of extracted study designs could not be categorised. Among the remaining studies, most were observational (17.2%; 2343) followed by systematic reviews (10.5%; 1432) with randomised controlled trials accounting for 8.7% (1196) of studies and meta-analysis for 1.4% (190) of studies. Conclusions It is possible to extract epidemiological study designs from a large-scale PubMed sample computationally. However, the number of trials, systematic reviews, and meta-analysis is relatively small – just 1 in 5 articles. Despite an increase over time in the total number of articles, study design details in the abstracts were missing. Epidemiological criminology still lacks the experimental evidence needed to address the health needs of the marginalized and isolated population that is prisoners and offenders.

IntroductionStructured medication reviews (SMRs), introduced in the United Kingdom (UK) in 2020, aim to enhance shared decision-making in medication optimisation, particularly for patients with multimorbidity and polypharmacy. Despite its potential, there is limited empirical evidence on the implementation of SMRs, and the challenges faced in the process. This study is part of a larger DynAIRx (Artificial Intelligence for dynamic prescribing optimisation and care integration in multimorbidity) project which aims to introduce Artificial Intelligence (AI) to SMRs and develop machine learning models and visualisation tools for patients with multimorbidity. Here, we explore how SMRs are currently undertaken and what barriers are experienced by those involved in them.MethodsQualitative focus groups and semi-structured interviews took place between 2022-2023. Six focus groups were conducted with doctors, pharmacists and clinical pharmacologists (n = 21), and three patient focus groups with patients with multimorbidity (n = 13). Five semi-structured interviews were held with 2 pharmacists, 1 trainee doctor, 1 policy-maker and 1 psychiatrist. Transcripts were analysed using thematic analysis.ResultsTwo key themes limiting the effectiveness of SMRs in clinical practice were identified: 'Medication Reviews in Practice' and 'Medication-related Challenges'. Participants noted limitations to the efficient and effectiveness of SMRs in practice including the scarcity of digital tools for identifying and prioritising patients for SMRs; organisational and patient-related challenges in inviting patients for SMRs and ensuring they attend; the time-intensive nature of SMRs, the need for multiple appointments and shared decision-making; the impact of the healthcare context on SMR delivery; poor communication and data sharing issues between primary and secondary care; difficulties in managing mental health medications and specific challenges associated with anticholinergic medication.ConclusionSMRs are complex, time consuming and medication optimisation may require multiple follow-up appointments to enable a comprehensive review. There is a need for a prescribing support system to identify, prioritise and reduce the time needed to understand the patient journey when dealing with large volumes of disparate clinical information in electronic health records. However, monitoring the effects of medication optimisation changes with a feedback loop can be challenging to establish and maintain using current electronic health record systems.

Valproate is the most effective treatment for idiopathic generalised epilepsy. Currently, its use is restricted in women of childbearing potential owing to high teratogenicity. Recent evidence extended this risk to men's offspring, prompting recommendations to restrict use in everybody aged

IntroductionAntipsychotic medication is increasingly prescribed to patients with serious mental illness. Patients with serious mental illness often have cardiovascular and metabolic comorbidities, and antipsychotics independently increase the risk of cardiometabolic disease. Despite this, many patients prescribed antipsychotics are discharged to primary care without planned psychiatric review. We explore perceptions of healthcare professionals and managers/directors of policy regarding reasons for increasing prevalence and management of antipsychotics in primary care.MethodsQualitative study using semi-structured interviews with 11 general practitioners (GPs), 8 psychiatrists, and 11 managers/directors of policy in the United Kingdom. Data was analysed using thematic analysis.ResultsRespondents reported competency gaps that impaired ability to manage patients prescribed antipsychotic medications, arising from inadequate postgraduate training and professional development. GPs lacked confidence to manage antipsychotic medications alone; psychiatrists lacked skills to address cardiometabolic risks and did not perceive this as their role. Communication barriers, lack of integrated care records, limited psychology provision, lowered expectation towards patients with serious mental illness by professionals, and pressure to discharge from hospital resulted in patients in primary care becoming 'trapped' on antipsychotics, inhibiting opportunities to deprescribe. Organisational and contractual barriers between services exacerbate this risk, with socioeconomic deprivation and lack of access to non-pharmacological interventions driving overprescribing. Professionals voiced fears of censure if a catastrophic event occurred after stopping an antipsychotic. Facilitators to overcome these barriers were suggested.ConclusionsPeople prescribed antipsychotics experience a fragmented health system and suboptimal care. Several interventions could be taken to improve care for this population, but inadequate availability of non-pharmacological interventions and socioeconomic factors increasing mental distress need policy change to improve outcomes. The role of professionals' fear of medicolegal or regulatory censure inhibiting antipsychotic deprescribing was a new finding in this study.

Background Gastrointestinal (GI) infections result in 17 million cases annually, with foodborne illness costing the National Health Service (NHS) £60m per year. The burden of GI infection is unequally distributed, with greater impact in more socioeconomically disadvantaged groups and areas. Local authorities (LA) provide vital services that protect public health and wellbeing. The impact of funding cuts to local services and their effect on public health is an area of concern. Environmental and regulatory (ER) services are responsible for roles such as food safety and infectious disease control. This study aims to understand the impact of local funding cuts on ER and GI infection outcomes. Methods We will conduct an ecological longitudinal study in England from 2010-2019 at the LA level to examine how changes in ER expenditure overtime have impacted ER and GI infection outcomes. Data will be gathered on food hygiene enforcement, food hygiene compliance levels, GI infection hospitalisation, NHS 111 calls relating to GI infection symptoms, GI infection pathogen data, deprivation, and population density. Measures will be aggregated to LA level and statistical analysis will be carried out. Ethics and dissemination University of Liverpool Ethics committee have confirmed ethical approval will not be required. All data will be aggregated and anonymised, therefore only data sharing agreements will be required. Findings will be disseminated to the stakeholder group in addition to outputs through conferences and publications. These findings will help understand impact of key services on public health and should inform government and public health policy and strategy.