Abraham George

England’s population is living longer, a sign of progress and better health, but adult social care (ASC) services must adapt to support a growing number of older residents, who may need help to remain independent, safe, and well. Kent County Council (KCC), in South East England, projects a 28% and 53% increase in its residents aged 65+ and 85+, respectively, over the next decade. This study aimed to inform the development of KCC’s ASC Prevention Framework using a System Dynamics Modelling (SDM) approach to evaluate the impact of preventive interventions on ASC demand and expenditure. Using linked local health and social care data and the Johns Hopkins ACG® tool, the 1.3 million adult population was stratified into Patient Needs Groups. Analyses showed that higher ASC costs were associated with being older females, living alone, deprivation, and frailty-related indicators such as dementia, history of falls, etc. Around 28% of older adults aged 65+ accounted for 80% of ASC costs within that cohort, and related scenario testing projected a 48% rise in ASC costs over 10 years without interventions, moderated to 33% with targeted prevention. These findings demonstrate the value of integrated data and modelling to inform strategic, prevention-focused ASC planning.

Health checks aim to improve the health of the population by identifying individuals with risk factors earlier and intervening to prevent disease. The role of commissioners is to ensure health checks provide as much benefit as possible for taxpayer funds invested into them. As such, evidence of the potential impacts of different commissioning choices is beneficial in this decision-making process. System dynamics modelling can be used to provide this evidence by modelling the health check programme using a pre-existing cohort model of a given population. This modelling considers local data, literature findings, and stakeholder views, from which nine different scenarios of a local health check programme have been tested. These scenarios found that extending the duration of health checks to 20 years and improving treatment uptake for those with high blood pressure or high cholesterol reduced rates of cardiovascular disease, improved healthy life expectancy and reduced years lived in ill health. In contrast, improving attendance in the most deprived quintile of the population made very little change to the health of the population overall, although a larger effect was observed in the most deprived areas. These findings helped guide local commissioning decisions by showing the long-term impact of different health check scenarios.

Objectives To develop, test, validate and implement a system dynamics model to simulate the pandemic progress and the impact of various interventions on viral spread, healthcare utilisation and demand in secondary care. Design We adopted the system dynamics model incorporating susceptible, exposed, infection and recovery framework to simulate the progress of the pandemic and how the interventions for the COVID-19 response influence the outcomes with a focus on secondary care. Setting This study was carried out covering all the local health systems in Southeast of England with a catchment population of six million with a specific focus on Kent and Medway system. Participants Six local health systems in Southeast of England using Kent and Medway as a case study. Interventions Short to medium ‘what if’ scenarios incorporating human behaviour, non-pharmaceutical interventions and medical interventions were tested using the model with regular and continuous feedback of the model results to the local health system leaders for monitoring, planning and rapid response as needed. Main outcome measures Daily output from the model which included number infected in the population, hospital admissions needing COVID-19 care, occupied general beds, continuous positive airway pressure beds, intensive care beds, hospital discharge pathways and deaths. Results We successfully implemented a regional series of models based on the local population needs which were used in healthcare planning as part of the pandemic response. Conclusions In this study, we have demonstrated the utility of system dynamics modelling incorporating local intelligence and collaborative working during the pandemic to respond rapidly and take decisions to protect the population. This led to strengthened cooperation among partners and ensured that the local population healthcare needs were met.

Introduction Familial Mediterranean fever (FMF) is an inherited genetic disorder characterized by recurrent episodes of fever, serositis, arthritis, and skin rash. Uncontrolled disease can lead to amyloid A disposition, nephrotic syndrome and progressive renal failure. Recurrence of AA amyloidosis post kidney transplantation has been reported. Long-term colchicine therapy will reduce the FMF attacks and risk of AA amyloidosis. Although there is high prevalence of FMF in MENA region, the data of end stage renal disease (ESRD) in FMF is limited. We report our center experience. Method A retrospective chart review study was conducted at Tawam Hospital over 12 years (January 2010 to January 2023). We included adult ESRD on hemodialysis with FMF disease and studied their management outcomes. Descriptive analysis was used. Results 1900 ESRD patients were on hemodialysis during study period, and only two patients were diagnosed with FMF and renal amyloidosis. Case 1: A 60-year-old male patient from Syria who is known to have FMF and polycystic kidney disease leading to ESRD. He underwent successful LRD kidney transplantation in 2009. He was on mycophenolic acid: 540 mg, BID, prednisolone: 5 mg, tacrolimus: 1 mg am, 0.5 mg and colchicine 0.5 mg BID. He developed progressive renal allograft dysfunction with evidence of nephrotic syndrome. The renal biopsy revealed recurrence of AA amyloidosis due to FMF in kidney allograft in 2018. He had decline in renal function over years was initiated on hemodialysis on 2022. He developed two attacks of FMF peritonitis while on hemodialysis that responded well to steroid/colchicine therapy. Case 2: 48 years old male, from Egypt, known to have irritable bowel syndrome. He presented to our hospital with bilateral lower limb edema, and progressive shortness of breath for one month. Investigations revealed heavy proteinuria (8.98 g/g Creat) and acute kidney injury. Serology and autoimmune workup were negative. Kidney biopsy showed renal amyloidosis, and chronic tubulointerstitial nephritis with severe interstitial fibrosis (60%). History taken again and was positive for FMF in his uncle. Genetic study and clinical confirmed the diagnosis of FMF. He was started on colchicine, but developed ESRD within 8 months and initiated on hemodialysis. He had attacks of FMF. Conclusion Renal amyloidosis in FMF patient leads to progressive renal failure despite colchicine therapy. In our dialysis cohort over 12 years, only two FMF patients were identified. Colchicine therapy is required in ESRD-FMF in order to managed FMF attacks and prevent other organ AA amyloidosis.

IntroductionIn England, life expectancy has stalled and significant decreases observed in certain geographical areas and populations. The cause of this involves complex dynamics between an individual's health, characteristics, lifestyle, and their wider environment known as the wider determinants of health which are key to good life expectancy, healthy life expectancy, and prevention of long-term medical conditions. Knowing the availability, breadth, features, and linkage potential of datasets relevant to wider determinants of health is important for exploring trends and associations for policy and public health planning. MethodsA systematic mapping of internet content identified accessible datasets relevant to wider determinants of health in England with town level geographical granularity or lower. Search terms were used in search engines and chatbots to identify weblinks subsequently examined for eligible datasets. Results105 potential weblinks to datasets were identified. Of these, twenty-one weblinks were explored further after exclusion of those: not accessible or currently live (n = 13); duplicated across search engines (n = 17); providing information only (i.e. no raw data, n = 14); did not provide freely accessible data (n 3); were not relevant to wider determinants of health (n = 17); lacked geographical granularity (n = 26). Eighty-nine datasets of interest were compiled with sub-town level data aggregation. Approximately half (n = 47, 52%) were from the England and Wales census 2021, with the remaining sources including government bodies, public services, and research datasets. Datasets covered many valuable categories of wider determinants of health. Key data gaps included food consumption, social care data and community/voluntary services. ConclusionIn England, access to data relevant to wider determinants of health is good and available at relatively small geographical resolution. Accessible datasets were identified and compiled within multiple categories of wider determinants of health as a useful data resource to explore wider determinants of health at place if linked to relevant health data or population studies. Key Features This data resource profile describes a systematic mapping of freely accessible population data on wider determinants of health in England. To the authors knowledge this is the first comprehensive compilation of freely accessible data resources of this kind. This data resource profile was created to support research into the mechanisms and impact of wider determinants on the health of populations in England but is applicable to research and populations studies wider than this. Eighty-nine datasets were identified that may be of use to researchers in health and other population data fields. Datasets are held separately but many have the potential to be linked through common geographical area codes to other relevant datasets such as health data. The datasets originate from multiple sources including government bodies, public services, and research datasets. They cover many key categories of wider determinants of health including socioeconomics, employment, housing, support services, and the environment. Key data gaps included food consumption, social care data and community/voluntary services. The data resource profile in this article links directly to freely accessible datasets at the time of publication in the tables provided. The authors welcome contact from researchers for collaboration on exploring wider determinants of health through data use. Please contact Dr Melanie Rees-Roberts m.rees-roberts@kent.ac.uk

Local authorities are central to the implementation of English Integrated Care Systems' health inequalities agendas, embedding public health into population health management planning. They work with partners to deliver a range of 'health determinant' services and facilities for people in a defined geographic area. This work is substantially premised on the use of cross-sectoral data that is linked at the individual level, readily available, longitudinal and contemporaneous. However, multiple challenges exist to such data availability. This paper elaborates upon these challenges to local authority public health systems and their potential solutions.

In public health, the routine use of linear forecasting, which restricts our ability to understand the combined effects of different interventions, demographic changes and wider health determinants, and the lack of reliable estimates for intervention impacts have limited our ability to effectively model population needs. Hence, we adopted system dynamics modelling to forecast health and care needs, assuming no change in population behaviour or determinants, then generated a “Better Health” scenario to simulate the combined impact of thirteen interventions across cohorts defined by age groups and diagnosable conditions, including “no conditions”. Risk factors for the incidence of single conditions, progression toward complex needs and levels of morbidity including frailty were used to create the dynamics of the model. Incidence, prevalence and mortality for each cohort were projected over 25 years with “do nothing” and “Better Health” scenarios. The size of the “no conditions” cohort increased, and the other cohorts decreased in size. The impact of the interventions on life expectancy at birth and healthy life expectancy is significant, adding 5.1 and 5.0 years, respectively. We demonstrate the feasibility, applicability and utility of using system dynamics modelling to develop a robust case for change to invest in prevention that is acceptable to wider partners.

Literature reviews over five decades have reported the paucity of examples of OR methods being routinely used to support decision-making in health and social care. This paper presents insights from an independent evaluation of a project intended to overcome some of the barriers to implementation by establishing a “community of practice” in Kent (England). The project itself was undertaken by practitioners, and had two main aims: providing training in system dynamics modelling to analysts, and making senior managers aware of the benefits of modelling. The findings largely confirmed previous studies, but also raised issues about style of training delivery and selection of problems to be modelled. Project leaders fully understood the barriers to embedding OR modelling skills, and made considerable efforts to avoid them, but nevertheless the main barrier, pressures on people’s time, remained an obstacle. The paper concludes with general reflections and advice.

Introduction Digital programmes in the newly created NHS integrated care boards (ICBs) in the United Kingdom mean that curation and linkage of anonymised patient data is underway in many areas for the first time. In Kent, Surrey and Sussex (KSS), in Southeast England, public health teams want to use these datasets to answer strategic population health questions, but public expectations around use of patient data are unknown. Objectives We aimed to engage with citizens of KSS to gather their views and expectations of data linkage and re-use, through deliberative discussions. Methods We held five 3-hour deliberative focus groups with 79 citizens of KSS, presenting information about potential uses of data, safeguards, and mechanisms for public involvement in governance and decision making about datasets. After each presentation, participants discussed their views in facilitated small groups which were recorded, transcribed and analysed thematically. Results The focus groups generated 15 themes representing participants' views on the benefits, risks and values for safeguarding linked data. Participants largely supported use of patient data to improve health service efficiency and resource management, preventative services and out of hospital care, joined-up services and information flows. Most participants expressed concerns about data accuracy, breaches and hacking, and worried about commercial use of data. They suggested that transparency of data usage through audit trails and clear information about accountability, ensuring data re-use does not perpetuate stigma and discrimination, ongoing, inclusive and valued involvement of the public in dataset decision-making, and a commitment to building trust, would meet their expectations for responsible data use. Conclusions Participants were largely favourable about the proposed uses of patient linked datasets but expected a commitment to transparency and public involvement. Findings were mapped to previous tenets of social license and can be used to inform ICB digital programme teams on how to proceed with use of linked datasets in a trustworthy and socially acceptable way.