Correction: Anticipatory changes in British household purchases of soft drinks associated with the announcement of the Soft Drinks Industry Levy: A controlled interrupted time series analysis.

[This corrects the article DOI: 10.1371/journal.pmed.1003269.].

The role of health protection teams in reducing health inequities: findings from a qualitative study.

INTRODUCTION: The UK Health Security Agency's (UKHSA) Health Protection Teams (HPTs) provide specialist public health advice and operational support to NHS, local authorities and other agencies in England. The development of a three-year UKHSA Health Equity strategy creates a unique opportunity for HPTs to reduce health inequities within their work. AIMS: This study aimed to understand current health equity activities and structures within HPTs, and to propose future HPT-led health equity activities. METHODS: Between November 2021 - March 2022, HPT staff from the nine UKHSA regions were invited to participate in a semi-structured interview or focus group. RESULTS: Twenty-seven participants covering all nine UKHSA regions took part in a total of 18 interviews and two focus groups. There was enthusiasm to address health inequity, and many reported this as their motivation for working in public health. All HPTs routinely engaged in health equity work including, variously: liaising with other organisations; advocacy in case and outbreak management meetings; developing regional HPT health equity action plans; and targeting under-served populations in day-to-day work. HPT staff discussed the challenge of splitting their time between reacting to health protection incidents (e.g., COVID as the main priority at the time) and pro-active work (e.g., programmes to reduce risk from external hazards for vulnerable populations). Although COVID had raised awareness of health inequities, knowledge of health equity among the professionally diverse workforce appeared variable. Limited evidence about effective interventions, and lack of clarity about future ways of working with other organisations were also shared as barriers to tackling health inequities. CONCLUSION: HPTs welcomed the development of UKHSA's health equity strategy, and through this study identified opportunities where HPTs can influence, support and lead on tackling health inequities. This includes embedding health equity into HPTs' acute response activities, stakeholder working, and staff management. This study also identified a need for health equity training for HPTs to improve knowledge and skills, utilising evidence-based approaches to health equity. Finally, we have identified areas where HPTs can lead, for example using brief advice interventions and through developing resources, such as standard operating procedures that focus on vulnerable populations. These findings will support a more integrated approach to addressing health equity through health protection work.

Translating Evidence into Practice: ACOs' Use of Care Plans for Patients with Complex Health Needs.

BACKGROUND: Care plans are an evidence-based strategy, encouraged by the Centers for Medicare and Medicaid Services, and are used to manage the care of patients with complex health needs that have been shown to lead to lower hospital costs and improved patient outcomes. Providers participating in payment reform, such as accountable care organizations, may be more likely to adopt care plans to manage complex patients. OBJECTIVE: To understand how Medicare accountable care organizations (ACOs) use care plans to manage patients with complex clinical needs. DESIGN: A qualitative study using semi-structured interviews with Medicare ACOs. PARTICIPANTS: Thirty-nine interviews were conducted across 18 Medicare ACOs with executive-level leaders and associated clinical and managerial staff. APPROACH: Development, structure, use, and management of care plans for complex patients at Medicare ACOs. KEY RESULTS: Most (11) of the interviewed ACOs reported using care plans to manage care of complex patients. All care plans include information about patient history, current medical needs, and future care plans. Beyond the core elements, care plans included elements based on the ACO's planned use and level of staff and patient engagement with care planning. Most care plans were developed and maintained by care management (not clinical) staff. CONCLUSIONS: ACOs are using care plans for patients with complex needs, but their use of care plans does not always meet the best practices. In many cases, ACO usage of care plans does not align with prescribed best practices: ACOs are adapting use of care plans to better fit the needs of patients and providers.

The impacts of collaboration between local health care and non-health care organizations and factors shaping how they work: a systematic review of reviews.

BACKGROUND: Policymakers in many countries promote collaboration between health care organizations and other sectors as a route to improving population health. Local collaborations have been developed for decades. Yet little is known about the impact of cross-sector collaboration on health and health equity. METHODS: We carried out a systematic review of reviews to synthesize evidence on the health impacts of collaboration between local health care and non-health care organizations, and to understand the factors affecting how these partnerships functioned. We searched four databases and included 36 studies (reviews) in our review. We extracted data from these studies and used Nvivo 12 to help categorize the data. We assessed risk of bias in the studies using standardized tools. We used a narrative approach to synthesizing and reporting the data. RESULTS: The 36 studies we reviewed included evidence on varying forms of collaboration in diverse contexts. Some studies included data on collaborations with broad population health goals, such as preventing disease and reducing health inequalities. Others focused on collaborations with a narrower focus, such as better integration between health care and social services. Overall, there is little convincing evidence to suggest that collaboration between local health care and non-health care organizations improves health outcomes. Evidence of impact on health services is mixed. And evidence of impact on resource use and spending are limited and mixed. Despite this, many studies report on factors associated with better or worse collaboration. We grouped these into five domains: motivation and purpose, relationships and cultures, resources and capabilities, governance and leadership, and external factors. But data linking factors in these domains to collaboration outcomes is sparse. CONCLUSIONS: In theory, collaboration between local health care and non-health care organizations might contribute to better population health. But we know little about which kinds of collaborations work, for whom, and in what contexts. The benefits of collaboration may be hard to deliver, hard to measure, and overestimated by policymakers. Ultimately, local collaborations should be understood within their macro-level political and economic context, and as one component within a wider system of factors and interventions interacting to shape population health.

COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study.

BACKGROUND: Patients with cancer are purported to have poor COVID-19 outcomes. However, cancer is a heterogeneous group of diseases, encompassing a spectrum of tumour subtypes. The aim of this study was to investigate COVID-19 risk according to tumour subtype and patient demographics in patients with cancer in the UK. METHODS: We compared adult patients with cancer enrolled in the UK Coronavirus Cancer Monitoring Project (UKCCMP) cohort between March 18 and May 8, 2020, with a parallel non-COVID-19 UK cancer control population from the UK Office for National Statistics (2017 data). The primary outcome of the study was the effect of primary tumour subtype, age, and sex and on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevalence and the case-fatality rate during hospital admission. We analysed the effect of tumour subtype and patient demographics (age and sex) on prevalence and mortality from COVID-19 using univariable and multivariable models. FINDINGS: 319 (30·6%) of 1044 patients in the UKCCMP cohort died, 295 (92·5%) of whom had a cause of death recorded as due to COVID-19. The all-cause case-fatality rate in patients with cancer after SARS-CoV-2 infection was significantly associated with increasing age, rising from 0·10 in patients aged 40-49 years to 0·48 in those aged 80 years and older. Patients with haematological malignancies (leukaemia, lymphoma, and myeloma) had a more severe COVID-19 trajectory compared with patients with solid organ tumours (odds ratio [OR] 1·57, 95% CI 1·15-2·15; p<0·0043). Compared with the rest of the UKCCMP cohort, patients with leukaemia showed a significantly increased case-fatality rate (2·25, 1·13-4·57; p=0·023). After correction for age and sex, patients with haematological malignancies who had recent chemotherapy had an increased risk of death during COVID-19-associated hospital admission (OR 2·09, 95% CI 1·09-4·08; p=0·028). INTERPRETATION: Patients with cancer with different tumour types have differing susceptibility to SARS-CoV-2 infection and COVID-19 phenotypes. We generated individualised risk tables for patients with cancer, considering age, sex, and tumour subtype. Our results could be useful to assist physicians in informed risk-benefit discussions to explain COVID-19 risk and enable an evidenced-based approach to national social isolation policies. FUNDING: University of Birmingham and University of Oxford.

Impact of the announcement and implementation of the UK Soft Drinks Industry Levy on sugar content, price, product size and number of available soft drinks in the UK, 2015-19: A controlled interrupted time series analysis.

BACKGROUND: Dietary sugar, especially in liquid form, increases risk of dental caries, adiposity, and type 2 diabetes. The United Kingdom Soft Drinks Industry Levy (SDIL) was announced in March 2016 and implemented in April 2018 and charges manufacturers and importers at £0.24 per litre for drinks with over 8 g sugar per 100 mL (high levy category), £0.18 per litre for drinks with 5 to 8 g sugar per 100 mL (low levy category), and no charge for drinks with less than 5 g sugar per 100 mL (no levy category). Fruit juices and milk-based drinks are exempt. We measured the impact of the SDIL on price, product size, number of soft drinks on the marketplace, and the proportion of drinks over the lower levy threshold of 5 g sugar per 100 mL. METHODS AND FINDINGS: We analysed data on a total of 209,637 observations of soft drinks over 85 time points between September 2015 and February 2019, collected from the websites of the leading supermarkets in the UK. The data set was structured as a repeat cross-sectional study. We used controlled interrupted time series to assess the impact of the SDIL on changes in level and slope for the 4 outcome variables. Equivalent models were run for potentially levy-eligible drink categories ('intervention' drinks) and levy-exempt fruit juices and milk-based drinks ('control' drinks). Observed results were compared with counterfactual scenarios based on extrapolation of pre-SDIL trends. We found that in February 2019, the proportion of intervention drinks over the lower levy sugar threshold had fallen by 33.8 percentage points (95% CI: 33.3-34.4, p < 0.001). The price of intervention drinks in the high levy category had risen by £0.075 (£0.037-0.115, p < 0.001) per litre-a 31% pass through rate-whilst prices of intervention drinks in the low levy category and no levy category had fallen and risen by smaller amounts, respectively. Whilst the product size of branded high levy and low levy drinks barely changed after implementation of the SDIL (-7 mL [-23 to 11 mL] and 16 mL [6-27ml], respectively), there were large changes to product size of own-brand drinks with an increase of 172 mL (133-214 mL) for high levy drinks and a decrease of 141 mL (111-170 mL) for low levy drinks. The number of available drinks that were in the high levy category when the SDIL was announced was reduced by 3 (-6 to 12) by the implementation of the SDIL. Equivalent models for control drinks provided little evidence of impact of the SDIL. These results are not sales weighted, so do not give an account of how sugar consumption from drinks may have changed over the time period. CONCLUSIONS: The results suggest that the SDIL incentivised many manufacturers to reduce sugar in soft drinks. Some of the cost of the levy to manufacturers and importers was passed on to consumers as higher prices but not always on targeted drinks. These changes could reduce population exposure to liquid sugars and associated health risks.

Anticipatory changes in British household purchases of soft drinks associated with the announcement of the Soft Drinks Industry Levy: A controlled interrupted time series analysis.

BACKGROUND: Sugar-sweetened beverage (SSB) consumption is positively associated with obesity, type 2 diabetes, and cardiovascular disease. The World Health Organization recommends that member states implement effective taxes on SSBs to reduce consumption. The United Kingdom Soft Drinks Industry Levy (SDIL) is a two-tiered tax, announced in March 2016 and implemented in April 2018. Drinks with ≥8 g of sugar per 100 ml (higher levy tier) are taxed at £0.24 per litre, drinks with ≥5 to <8 g of sugar per 100 ml (lower levy tier) are taxed at £0.18 per litre, and drinks with <5 g sugar per 100 ml (no levy) are not taxed. Milk-based drinks, pure fruit juices, drinks sold as powder, and drinks with >1.2% alcohol by volume are exempt. We aimed to determine if the announcement of the SDIL was associated with anticipatory changes in purchases of soft drinks prior to implementation of the SDIL in April 2018. We explored differences in the volume of and amount of sugar in household purchases of drinks in each levy tier at 2 years post announcement. METHODS AND FINDINGS: We used controlled interrupted time series to compare observed changes associated with the announcement of the SDIL to the counterfactual scenario of no announcement. We used data from Kantar Worldpanel, a commercial household purchasing panel with approximately 30,000 British members that includes linked nutritional data on purchases. We conducted separate analyses for drinks liable for the SDIL in the higher, lower, and no-levy tiers controlling with household purchase volumes of toiletries. At 2 years post announcement, there was no difference in volume of or sugar from purchases of higher-levy-tier drinks compared to the counterfactual of no announcement. In contrast, a reversal of the existing upward trend in volume (ml) of and amount of sugar (g) in purchases of lower-levy-tier drinks was seen. These changes led to a -96.1 ml (95% confidence interval [CI] -144.2 to -48.0) reduction in volume and -6.4 g (95% CI -9.8 to -3.1) reduction in sugar purchased in these drinks per household per week. There was a reversal of the existing downward trend in the amount of sugar in household purchases of the no-levy drinks but no change in volume purchased. At 2 years post announcement, these changes led to a 6.1 g (95% CI 3.9-8.2) increase in sugar purchased in these drinks per household per week. There was no evidence that volume of or amount of sugar in purchases of all drinks combined was different from the counterfactual. This is an observational study, and changes other than the SDIL may have been responsible for the results reported. Purchases consumed outside of the home were not accounted for. CONCLUSIONS: The announcement of the UK SDIL was associated with reductions in volume and sugar purchased in lower-levy-tier drinks before implementation. These were offset by increases in sugar purchased from no-levy drinks. These findings may reflect reformulation of drinks from the lower levy to no-levy tier with removal of some but not all sugar, alongside changes in consumer attitudes and beliefs. TRIAL REGISTRATION: ISRCTN Registry ISRCTN18042742.

Role of Nurse Practitioners in Caring for Patients With Complex Health Needs.

OBJECTIVE: The objective of this study was to estimate trends in the percentage of Medicare beneficiaries cared for by nurse practitioners from 2012 to 2017, to characterize beneficiaries cared for by nurse practitioners in 2017, and to examine how the percentage of beneficiaries cared for by nurse practitioners varies by practice characteristics. DESIGN: An observational study of 2012-2017 Medicare fee-for-service beneficiaries' ambulatory visits. We computed the percentage of beneficiaries with 1 or more ambulatory visits from nurse practitioners and the percentage of beneficiaries receiving the plurality of their ambulatory visits from a nurse practitioner versus a physician (ie, predominant provider). We compared beneficiary demographics, clinical characteristics, and utilization by the predominant provider. We then characterized the predominant provider by practice characteristics. KEY RESULTS: In 2017, 28.9% of beneficiaries received any care from a nurse practitioner and 8.0% utilized nurse practitioners as their predominant provider-an increase from 4.4% in 2012. Among beneficiaries cared for by nurse practitioners in 2017, 25.9% had 3 or more chronic conditions compared with 20.8% of those cared for by physicians. Beneficiaries cared for in practices owned by health systems were more likely to have a nurse practitioner as their predominant provider compared with those attending practices that were independently owned (9.3% vs. 7.0%). CONCLUSIONS: Nurse practitioners are caring for Medicare beneficiaries with complex needs at rates that match or exceed their physician colleagues. The growing role of nurse practitioners, especially in health care systems, warrants attention as organizations embark on payment and delivery reform.

How Do Accountable Care Organizations Deliver Preventive Care Services? A Mixed-Methods Study.

BACKGROUND: The Affordable Care Act and the introduction of accountable care organizations (ACOs) have increased the incentives for patients and providers to engage in preventive care, for example, through quality metrics linked to disease prevention. However, little is known about how ACOs deliver preventive care services. OBJECTIVE: To understand how Medicare ACOs provide preventive care services to their attributed patients. DESIGN: Mixed-methods study using survey data reporting Medicare ACO capabilities in patient care management and interviews with high-performing ACOs. PARTICIPANTS: ACO executives completed survey data on 283 Medicare ACOs. These data were supplemented with 39 interviews conducted across 18 Medicare ACOs with executive-level leaders and associated clinical and managerial staff. MAIN MEASURES: Survey measures included ACO performance, organizational characteristics, collaboration experience, and capabilities in care management and quality improvement. Telephone interviews followed a semi-structured interview guide and explored the mechanisms used, and motivations of, ACOs to deliver preventive care services. KEY RESULTS: Medicare ACOs that reported being comprehensively engaged in the planning and management of patient care - including conducting reminders for preventive care services - had more beneficiaries and had a history of collaboration experience, but were not more likely to receive shared savings or achieve high-quality scores compared to other surveyed ACOs. Interviews revealed that offering annual wellness visits and having a system-wide approach to closing preventive care gaps are key mechanisms used by high-performing ACOs to address patients' preventive care needs. Few programs or initiatives were identified that specifically target clinically complex patients. Aside from meeting patient needs, motivations for ACOs included increasing patient attribution and meeting performance targets. CONCLUSIONS: ACOs are increasingly motivated to deliver preventive care services. Understanding the mechanisms and motivations used by high-performing ACOs may help both providers and payers to increase the use of preventive care.

PRIMEtime CE: a multistate life table model for estimating the cost-effectiveness of interventions affecting diet and physical activity.

BACKGROUND: Non-communicable diseases are the leading cause of death in England, and poor diet and physical inactivity are two of the principle behavioural risk factors. In the context of increasingly constrained financial resources, decision makers in England need to be able to compare the potential costs and health outcomes of different public health policies aimed at improving these risk factors in order to know where to invest so that they can maximise population health. This paper describes PRIMEtime CE, a multistate life table cost-effectiveness model that can directly compare interventions affecting multiple disease outcomes. METHODS: The multistate life table model, PRIMEtime Cost Effectiveness (PRIMEtime CE), is developed from the Preventable Risk Integrated ModEl (PRIME) and the PRIMEtime model. PRIMEtime CE uses routinely available data to estimate how changing diet and physical activity in England affects morbidity and mortality from heart disease, stroke, diabetes, liver disease, and cancers either directly or via raised blood pressure, cholesterol, and body weight. RESULTS: Model outcomes are change in quality adjusted life years, and change in English National Health Service and social care costs. CONCLUSION: This paper describes PRIMEtime CE and highlights its main strengths and limitations. The model can be used to compare any number of public policies affecting diet and physical activity, allowing decision makers to understand how they can maximise population health with limited financial resources.

Estimating the cost-effectiveness of salt reformulation and increasing access to leisure centres in England, with PRIMEtime CE model validation using the AdViSHE tool.

BACKGROUND: PRIMEtime CE is a multistate life table model that can directly compare the cost effectiveness of public health interventions affecting diet and physical activity levels, helping to inform decisions about how to spend finite resources. This paper estimates the costs and health outcomes in England of two scenarios: reformulating salt and expanding subsidised access to leisure centres. The results are used to help validate PRIMEtime CE, following the steps outlined in the Assessment of the Validation Status of Health-Economic decision models (AdViSHE) tool. METHODS: The PRIMEtime CE model estimates the difference in quality adjusted life years (QALYs) and difference in NHS and social care costs of modelled interventions compared with doing nothing. The salt reformulation scenario models how salt consumption would change if food producers met the 2017 UK Food Standards Agency salt reformulation targets. The leisure centre scenario models change in physical activity levels if the Birmingham Be Active scheme (where swimming pools and gym access is free to residents during defined periods) was rolled out across England. The AdViSHE tool was developed by health economic modellers and divides model validation into five parts: validation of the conceptual model, input data validation, validation of computerised model, operational validation, and other validation techniques. PRIMEtime CE is discussed in relation to each part. RESULTS: Salt reformulation was dominant compared with doing nothing, and had a 10-year return on investment of £1.44 (£0.50 to £2.94) for every £1 spent. By contrast, over 10 years the Be Active expansion would cost £727,000 (£514,000 to £1,064,000) per QALY. PRIMEtime CE has good face validity of its conceptual model and has robust input data. Cross-validation produces mixed results and shows the impact of model scope, input parameters, and model structure on cost-per-QALY estimates. CONCLUSIONS: This paper illustrates how PRIMEtime CE can be used to compare the cost-effectiveness of two different public health measures affecting diet and physical activity levels. The AdViSHE tool helps to validate PRIMEtime CE, identifies some of the key drivers of model estimates, and highlights the challenges of externally validating public health economic models against independent data.

Who breaches the four-hour emergency department wait time target? A retrospective analysis of 374,000 emergency department attendances between 2008 and 2013 at a type 1 emergency department in England.

BACKGROUND: The four-hour target is a key hospital emergency department performance indicator in England and one that drives the physical and organisational design of the ED. Some studies have identified time of presentation as a key factor affecting waiting times. Few studies have investigated other determinants of breaching the four-hour target. Therefore, our objective was to describe patterns of emergency department breaches of the four-hour wait time target and identify patients at highest risk of breaching. METHODS: This was a retrospective cohort study of a large type 1 Emergency department at an NHS teaching hospital in Oxford, England. We analysed anonymised individual level patient data for 378,873 emergency department attendances, representing all attendances between April 2008 and April 2013. We examined patient characteristics and emergency department presentation circumstances associated with the highest likelihood of breaching the four-hour wait time target. RESULTS: We used 374,459 complete cases for analysis. In total, 8.3% of all patients breached the four-hour wait time target. The main determinants of patients breaching the four-hour wait time target were hour of arrival to the ED, day of the week, patient age, ED referral source, and the types of investigations patients receive (p < 0.01 for all associations). Patients most likely to breach the four-hour target were older, presented at night, presented on Monday, received multiple types of investigation in the emergency department, and were not self-referred (p < 0.01 for all associations). Patients attending from October to February had a higher odds of breaching compared to those attending from March to September (OR 1.63, 95% CI 1.59 to 1.66). CONCLUSIONS: There are a number of independent patient and circumstantial factors associated with the probability of breaching the four-hour ED wait time target including patient age, ED referral source, the types of investigations patients receive, as well as the hour, day, and month of arrival to the ED. Efforts to reduce the number of breaches could explore late-evening/overnight staffing, access to diagnostic tests, rapid discharge facilities, and early assessment and input on diagnostic and management strategies from a senior practitioner.

Changes in health in England, with analysis by English regions and areas of deprivation, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

BACKGROUND: In the Global Burden of Disease Study 2013 (GBD 2013), knowledge about health and its determinants has been integrated into a comparable framework to inform health policy. Outputs of this analysis are relevant to current policy questions in England and elsewhere, particularly on health inequalities. We use GBD 2013 data on mortality and causes of death, and disease and injury incidence and prevalence to analyse the burden of disease and injury in England as a whole, in English regions, and within each English region by deprivation quintile. We also assess disease and injury burden in England attributable to potentially preventable risk factors. England and the English regions are compared with the remaining constituent countries of the UK and with comparable countries in the European Union (EU) and beyond. METHODS: We extracted data from the GBD 2013 to compare mortality, causes of death, years of life lost (YLLs), years lived with a disability (YLDs), and disability-adjusted life-years (DALYs) in England, the UK, and 18 other countries (the first 15 EU members [apart from the UK] and Australia, Canada, Norway, and the USA [EU15+]). We extended elements of the analysis to English regions, and subregional areas defined by deprivation quintile (deprivation areas). We used data split by the nine English regions (corresponding to the European boundaries of the Nomenclature for Territorial Statistics level 1 [NUTS 1] regions), and by quintile groups within each English region according to deprivation, thereby making 45 regional deprivation areas. Deprivation quintiles were defined by area of residence ranked at national level by Index of Multiple Deprivation score, 2010. Burden due to various risk factors is described for England using new GBD methodology to estimate independent and overlapping attributable risk for five tiers of behavioural, metabolic, and environmental risk factors. We present results for 306 causes and 2337 sequelae, and 79 risks or risk clusters. FINDINGS: Between 1990 and 2013, life expectancy from birth in England increased by 5·4 years (95% uncertainty interval 5·0-5·8) from 75·9 years (75·9-76·0) to 81·3 years (80·9-81·7); gains were greater for men than for women. Rates of age-standardised YLLs reduced by 41·1% (38·3-43·6), whereas DALYs were reduced by 23·8% (20·9-27·1), and YLDs by 1·4% (0·1-2·8). For these measures, England ranked better than the UK and the EU15+ means. Between 1990 and 2013, the range in life expectancy among 45 regional deprivation areas remained 8·2 years for men and decreased from 7·2 years in 1990 to 6·9 years in 2013 for women. In 2013, the leading cause of YLLs was ischaemic heart disease, and the leading cause of DALYs was low back and neck pain. Known risk factors accounted for 39·6% (37·7-41·7) of DALYs; leading behavioural risk factors were suboptimal diet (10·8% [9·1-12·7]) and tobacco (10·7% [9·4-12·0]). INTERPRETATION: Health in England is improving although substantial opportunities exist for further reductions in the burden of preventable disease. The gap in mortality rates between men and women has reduced, but marked health inequalities between the least deprived and most deprived areas remain. Declines in mortality have not been matched by similar declines in morbidity, resulting in people living longer with diseases. Health policies must therefore address the causes of ill health as well as those of premature mortality. Systematic action locally and nationally is needed to reduce risk exposures, support healthy behaviours, alleviate the severity of chronic disabling disorders, and mitigate the effects of socioeconomic deprivation. FUNDING: Bill & Melinda Gates Foundation and Public Health England.

Choosing an epidemiological model structure for the economic evaluation of non-communicable disease public health interventions.

Non-communicable diseases are the leading global causes of mortality and morbidity. Growing pressures on health services and on social care have led to increasing calls for a greater emphasis to be placed on prevention. In order for decisionmakers to make informed judgements about how to best spend finite public health resources, they must be able to quantify the anticipated costs, benefits, and opportunity costs of each prevention option available. This review presents a taxonomy of epidemiological model structures and applies it to the economic evaluation of public health interventions for non-communicable diseases. Through a novel discussion of the pros and cons of model structures and examples of their application to public health interventions, it suggests that individual-level models may be better than population-level models for estimating the effects of population heterogeneity. Furthermore, model structures allowing for interactions between populations, their environment, and time are often better suited to complex multifaceted interventions. Other influences on the choice of model structure include time and available resources, and the availability and relevance of previously developed models. This review will help guide modelers in the emerging field of public health economic modeling of non-communicable diseases.

Simulating the impact on health of internalising the cost of carbon in food prices combined with a tax on sugar-sweetened beverages.

BACKGROUND: Rising greenhouse gas emissions (GHGEs) have implications for health and up to 30 % of emissions globally are thought to arise from agriculture. Synergies exist between diets low in GHGEs and health however some foods have the opposite relationship, such as sugar production being a relatively low source of GHGEs. In order to address this and to further characterise a healthy sustainable diet, we model the effect on UK non-communicable disease mortality and GHGEs of internalising the social cost of carbon into the price of food alongside a 20 % tax on sugar sweetened beverages (SSBs). METHODS: Developing previously published work, we simulate four tax scenarios: (A) a GHGEs tax of £2.86/tonne of CO2 equivalents (tCO2e)/100 g product on all products with emissions greater than the mean across all food groups (0.36 kgCO2e/100 g); (B) scenario A but with subsidies on foods with emissions lower than 0.36 kgCO2e/100 g such that the effect is revenue neutral; (C) scenario A but with a 20 % sales tax on SSBs; (D) scenario B but with a 20 % sales tax on SSBs. An almost ideal demand system is used to estimate price elasticities and a comparative risk assessment model is used to estimate changes to non-communicable disease mortality. RESULTS: We estimate that scenario A would lead to 300 deaths delayed or averted, 18,900 ktCO2e fewer GHGEs, and £3.0 billion tax revenue; scenario B, 90 deaths delayed or averted and 17,100 ktCO2e fewer GHGEs; scenario C, 1,200 deaths delayed or averted, 18,500 ktCO2e fewer GHGEs, and £3.4 billion revenue; and scenario D, 2,000 deaths delayed or averted and 16,500 ktCO2e fewer GHGEs. Deaths averted are mainly due to increased fibre and reduced fat consumption; a SSB tax reduces SSB and sugar consumption. CONCLUSIONS: Incorporating the social cost of carbon into the price of food has the potential to improve health, reduce GHGEs, and raise revenue. The simple addition of a tax on SSBs can mitigate negative health consequences arising from sugar being low in GHGEs. Further conflicts remain, including increased consumption of unhealthy foods such as cakes and nutrients such as salt.

Assessing the external validity of model-based estimates of the incidence of heart attack in England: a modelling study.

BACKGROUND: The DisMod II model is designed to estimate epidemiological parameters on diseases where measured data are incomplete and has been used to provide estimates of disease incidence for the Global Burden of Disease study. We assessed the external validity of the DisMod II model by comparing modelled estimates of the incidence of first acute myocardial infarction (AMI) in England in 2010 with estimates derived from a linked dataset of hospital records and death certificates. METHODS: Inputs for DisMod II were prevalence rates of ever having had an AMI taken from a population health survey, total mortality rates and AMI mortality rates taken from death certificates. By definition, remission rates were zero. We estimated first AMI incidence in an external dataset from England in 2010 using a linked dataset including all hospital admissions and death certificates since 1998. 95 % confidence intervals were derived around estimates from the external dataset and DisMod II estimates based on sampling variance and reported uncertainty in prevalence estimates respectively. RESULTS: Estimates of the incidence rate for the whole population were higher in the DisMod II results than the external dataset (+54 % for men and +26 % for women). Age-specific results showed that the DisMod II results over-estimated incidence for all but the oldest age groups. Confidence intervals for the DisMod II and external dataset estimates did not overlap for most age groups. CONCLUSION: By comparison with AMI incidence rates in England, DisMod II did not achieve external validity for age-specific incidence rates, but did provide global estimates of incidence that are of similar magnitude to measured estimates. The model should be used with caution when estimating age-specific incidence rates.

Training individuals to implement discrete-trial teaching procedures using behavioral skills training: A scoping review with implications for practice and research.

Behavioral skills training (BST) is an evidence-based approach for training individuals to implement discrete-trial teaching procedures. Despite the effectiveness of this approach, implementing BST can be time and resource intensive, which may interfere with a clinical organization's adoption of this training format. We conducted a scoping review of studies using BST components for training discrete-trial teaching procedures in peer-reviewed articles between 1977 and 2021. We identified 51 studies in 46 publications involving 354 participants. We coded descriptive data on (a) participant characteristics, (b) study characteristics, (c) training conditions (including instructions, modeling, rehearsal, and feedback), and (d) training outcomes. The results indicated that studies have primarily attempted to improve the efficacy and efficiency of BST by modifying or omitting common training components. We provide best-practice considerations for using BST to teach discrete-trial teaching procedures and offer a research agenda to guide future investigation in this area.