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.

IntroductionElectronic healthcare records from the UK are accessible to researchers via a number of platforms, but these platforms typically include data from a limited subset of health and care services. The Kent Integrated Dataset (KID) aims to provide insight into system-wide health and care utilisation for the whole population of Kent and Medway. MethodsThe KID uses pseudonymisation-at-source to link patient-level records from services including general practices, hospitals, community health services and social care. The design and governance of the dataset is led by local authorities, health commissioners and service providers. ResultsA population-level dataset has been developed, including data from April 2014 onwards. Data providers add new data on a monthly basis. The KID has been used to understand the costs associated with frailty, estimate the prevalence of rare conditions and compare the risk of non-elective hospitalisation between general practices. ConclusionThe KID is a unique and rich dataset available to researchers who are investigating a broad range of public health questions. It provides system-level insight into patient journeys and care utilisation and supports commissioning based on patient needs.

Objectives: Research into the socio-economic patterning of health and social care costs in the UK has so far been limited to examining only particular aspects of healthcare. In this study, we explore the social gradients in overall healthcare and social care costs, as well as in the disaggregated costs by cost category. Study design: We calculated the social gradient in health and social care costs by cost category using a linked electronic health record data set for Kent, a county in South East England. We performed a cross-sectional analysis on a sample of 323,401 residents in Kent older than 55 years to assess the impact of neighbourhood deprivation on mean annual per capita costs in 2016/17. Methods: Patient-level costs were estimated from activity data for the financial year 2016/17 and were extracted alongside key patient characteristics. Mean costs were calculated for each area deprivation quintile based on the index of multiple deprivation of the neighbourhood (lower super output area) in which the patient lived. Cost subcategories were analysed across primary care, secondary care, social care, community care and mental health. Results: The mean annual per capita cost increased with deprivation across each deprivation quintile, with a cost of £1205 in the most affluent quintile, compared with £1623 in the most deprived quintile, a 35% cost increase. Social gradients were found across all cost subcategories. Conclusions: Health inequalities in the population older than 55 years in Kent are associated with health and social care costs of £109m, equivalent to 15% of the estimated total expenditure in this age group. Such significant costs suggest that appropriate interventions to reduce socio-economic inequalities have the potential to substantially improve population health and, depending on how much investment they require, may even result in cost savings.

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.

Since 2013, local authorities in England have been responsible for commissioning preventative public health interventions. The aim of this systematic review was to support commissioning by collating published data on economic evaluations and modelling of local authority commissioned public health preventative interventions in the UK. Following the PRISMA protocol, we searched for economic evaluations of preventative intervention studies in four different areas: overweight and obesity, physical inactivity, alcohol and illicit drugs use and smoking cessation. The systematic review identified studies between January 1994 and February 2015, using five databases. We synthesized the studies to identify the key methods and examined results of the economic evaluations. The majority of the evaluations related to cost-effectiveness, rather than cost-benefit analyses or cost-utility analyses. These analyses found preventative interventions to be cost effective, though the context of the interventions differed between the studies. Preventative public health interventions in general are cost-effective. There is a need for further studies to support justification of continued and/or increased funding for public health interventions. There is much variation between the types of economically evaluated preventative interventions in our review. Broader studies incorporating different contexts may help support funding for local authority-sponsored public health initiatives.