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

Application of decision analytic modelling to cardiovascular disease prevention in Sub-Saharan Africa: a systematic review

BACKGROUND

This systematic review sought to examine the application of decision analytic models (DAMs) to evaluate cardiovascular disease (CVD) prevention interventions in sub-Saharan Africa (SSA), a region that has experienced an increasing CVD burden in the last two decades.

METHODS

We searched seven databases and identified model-based economic evaluations of interventions targeting CVD prevention among adult populations in SSA. All articles were screened by two reviewers, data was extracted, and narrative synthesis was performed. Quality assessment was performed using the Philips checklist.

RESULTS

The review included 27 articles from eight SSA countries. The majority of the studies evaluated interventions for primary CVD prevention, with primordial prevention interventions being the least evaluated. Markov models were the most commonly used modelling method. Seven studies incorporated equity dimensions in the modelling, which were assessed mainly through subgroup analysis. The mean quality score of the papers was 68.9% and most studies reported data challenges while only three studies conducted model validation.

CONCLUSIONS

The review finds few studies modelling the impact of interventions targeting primordial prevention and those evaluating equitable strategies for improving access to CVD prevention. There is a need for increased transparency in model building, validation and documentation.

Qini Curves for Potential Impact Assessment of Risk Predictive Models Informing Intervention Policies

OBJECTIVES

Predictive models in medicine help make decisions about which individual to treat with a given therapeutic or preventive intervention. Before being tested in large field studies and recommended for clinical adoption, it is important to evaluate not only their statistical accuracy but also the impact they may have when used to inform health intervention policies. We aim to provide simple methods for the potential impact assessment of health intervention policies based on predictive models.

METHODS

We propose an analytic framework based on Qini curves wherein prediction-based policies are analyzed on 2 impact endpoints: (1) the fraction of the population that would be selected for the intervention (coverage) and (2) the effect on the clinical outcomes of interest (disutility). The drivers of values are the disease prevalence, the predictive performance of the model, and the effectiveness of the intervention.

RESULTS

We present simple formulas for calculating coverage and disutility from either observational or randomized controlled data. We illustrate possible value measures arising from geometrical properties on the Qini plane: delta coverage and disutility, number needed to treat, and integrated difference between Qini curves. We show the applicability of the Qini analysis by providing examples about the prevention of falls in older adults and prevention of secondary cardiovascular events with pioglitazone.

CONCLUSIONS

Coverage and disutility capture key value components of prediction-based policies. The method can be used for comparing models or tuning risk thresholds for managing trade-offs between conflicting objectives (eg, clinical benefits, side effects, and healthcare resources).

Public health economic modelling in evaluations of salt and/or alcohol policies: a systematic scoping review

BACKGROUND

Public health economic modelling is an approach capable of managing the intricacies involved in evaluating interventions without direct observational evidence. It is used to estimate potential long-term health benefits and cost outcomes. The aim of this review was to determine the scope of health economic models in the evaluation of salt and/or alcohol interventions globally, to provide an overview of the literature and the modelling methods and structures used.

METHODS

Searches were conducted in Medline, Embase, and EconLit, and complemented with citation searching of key reviews. The searches were conducted between 13/11/2022 and 8/11/2023, with no limits to publication date. We applied a health economic search filter to select model-based economic evaluations of public health policies and interventions related to alcohol consumption, dietary salt intake, or both. Data on the study characteristics, modelling approaches, and the interventions were extracted and synthesised.

RESULTS

The search identified 1,958 articles, 82 of which were included. These included comparative risk assessments (29%), multistate lifetables (27%), Markov cohort (22%), microsimulation (13%), and other (9%) modelling methods. The included studies evaluated alcohol and/or salt interventions in a combined total of 64 countries. Policies from the UK (23%) and Australia (18%) were the most frequently evaluated. A total of 58% of the models evaluated salt policies, 38% evaluated alcohol policies, and only three (4% of included modelling studies) evaluated both alcohol- and salt-related policies. The range of diseases modelled covered diabetes and cardiovascular disease-related outcomes, cancers, and alcohol-attributable harm. Systolic blood pressure was a key intermediate risk factor in the excessive salt-to-disease modelling pathway for 40 (83%) of the salt modelling studies. The effects of alcohol consumption on adverse health effects were modelled directly using estimates of the relative risk of alcohol-attributable diseases.

CONCLUSIONS

This scoping review highlights the substantial utilisation of health economic modelling for estimating the health and economic impact of interventions targeting salt or alcohol consumption. The limited use of combined alcohol and salt policy models presents a pressing need for models that could explore their integrated risk factor pathways for cost-effectiveness comparisons between salt and alcohol policies to inform primary prevention policymaking.

Mathematical modelling to estimate the impact of maternal and perinatal healthcare services and interventions on health in sub-Saharan Africa: A scoping review

INTRODUCTION

Mathematical modelling is a commonly utilised tool to predict the impact of policy on health outcomes globally. Given the persistently high levels of maternal and perinatal morbidity and mortality in sub-Saharan Africa, mathematical modelling is a potentially valuable tool to guide strategic planning for health and improve outcomes.

METHODS

The aim of this scoping review was to explore the characteristics of mathematical models and modelling studies evaluating the impact of maternal and/or perinatal healthcare interventions or services on health-related outcomes in the region. A search across three databases was conducted on 2nd November 2023 which returned 8660 potentially relevant studies, from which 60 were included in the final review. Characteristics of these studies, the interventions which were evaluated, the models utilised, and the analyses conducted were extracted and summarised.

RESULTS

Findings suggest that the popularity of modelling within this field is increasing over time with most studies published after 2015 and that population-based, deterministic, linear models were most frequently utilised, with the Lives Saved Tool being applied in over half of the reviewed studies (n = 34, 57%). Much less frequently (n = 6) models utilising system-thinking approaches, such as individual-based modelling or systems dynamics modelling, were developed and applied. Models were most applied to estimate the impact of interventions or services on maternal mortality (n = 34, 57%) or neonatal mortality outcomes (n = 39, 65%) with maternal morbidity (n = 4, 7%) and neonatal morbidity (n = 6, 10%) outcomes and stillbirth reported on much less often (n = 14, 23%).

DISCUSSION

Going forward, given that healthcare delivery systems have long been identified as complex adaptive systems, modellers may consider the advantages of applying systems-thinking approaches to evaluate the impact of maternal and perinatal health policy. Such approaches allow for a more realistic and explicit representation of the systems- and individual- level factors which impact the effectiveness of interventions delivered within health systems.

Do COVID-19 Infectious Disease Models Incorporate the Social Determinants of Health? A Systematic Review

Objectives

To identify COVID-19 infectious disease models that accounted for social determinants of health (SDH).

Methods

We searched MEDLINE, EMBASE, Cochrane Library, medRxiv, and the Web of Science from December 2019 to August 2020. We included mathematical modelling studies focused on humans investigating COVID-19 impact and including at least one SDH. We abstracted study characteristics (e.g., country, model type, social determinants of health) and appraised study quality using best practices guidelines.

Results

83 studies were included. Most pertained to multiple countries (n = 15), the United States (n = 12), or China (n = 7). Most models were compartmental (n = 45) and agent-based (n = 7). Age was the most incorporated SDH (n = 74), followed by gender (n = 15), race/ethnicity (n = 7) and remote/rural location (n = 6). Most models reflected the dynamic nature of infectious disease spread (n = 51, 61%) but few reported on internal (n = 10, 12%) or external (n = 31, 37%) model validation.

Conclusion

Few models published early in the pandemic accounted for SDH other than age. Neglect of SDH in mathematical models of disease spread may result in foregone opportunities to understand differential impacts of the pandemic and to assess targeted interventions.

Systematic Review Registration

[https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020207706], PROSPERO, CRD42020207706.

Scoping Literature Review of Disease Modeling of the Opioid Crisis

Opioid misuse continues to cause significant harm. To investigate current research, we conducted a scoping literature review of disease spread models of opioid misuse from January 2000 to December 2022. In total, 85 studies were identified and examined for the opioids modeled, model type, data sources used and model calibration and validation. Most of the studies (58%, 49) only modeled heroin; the next largest categories were prescription opioids and unspecified opioids which accounted for 9% (8) each. Most models were theoretical compartmental models (57) or applied compartmental models (21). Previously published research was the most used data source (38), and a majority of the model validation involved the researchers setting initial conditions to verify theoretical results (30). To represent typical opioid use more accurately, multiple opioids need to be incorporated into the disease spread models, and applying different modeling techniques may allow other insights into opioid misuse spread.

The future burden of type 2 diabetes in Belgium: a microsimulation model

OBJECTIVE

To forecast the annual burden of type 2 diabetes and related socio-demographic disparities in Belgium until 2030.

METHODS

This study utilized a discrete-event transition microsimulation model. A synthetic population was created using 2018 national register data of the Belgian population aged 0-80 years, along with the national representative prevalence of diabetes risk factors obtained from the latest (2018) Belgian Health Interview and Examination Surveys using Multiple Imputation by Chained Equations (MICE) as inputs to the Simulation of Synthetic Complex Data (simPop) model. Mortality information was obtained from the Belgian vital statistics and used to calculate annual death probabilities. From 2018 to 2030, synthetic individuals transitioned annually from health to death, with or without developing type 2 diabetes, as predicted by the Finnish Diabetes Risk Score, and risk factors were updated via strata-specific transition probabilities.

RESULTS

A total of 6722 [95% UI 3421, 11,583] new cases of type 2 diabetes per 100,000 inhabitants are expected between 2018 and 2030 in Belgium, representing a 32.8% and 19.3% increase in T2D prevalence rate and DALYs rate, respectively. While T2D burden remained highest for lower-education subgroups across all three Belgian regions, the highest increases in incidence and prevalence rates by 2030 are observed for women in general, and particularly among Flemish women reporting higher-education levels with a 114.5% and 44.6% increase in prevalence and DALYs rates, respectively. Existing age- and education-related inequalities will remain apparent in 2030 across all three regions.

CONCLUSIONS

The projected increase in the burden of T2D in Belgium highlights the urgent need for primary and secondary preventive strategies. While emphasis should be placed on the lower-education groups, it is also crucial to reinforce strategies for people of higher socioeconomic status as the burden of T2D is expected to increase significantly in this population segment.

The cost-effectiveness of a real-time seizure detection application for people with epilepsy

OBJECTIVES

Automated seizure detection modalities can increase safety among people with epilepsy (PWE) and reduce seizure-related anxiety. We evaluated the potential cost-effectiveness of a seizure detection mobile application for PWE in Singapore.

METHODS

We used a Markov cohort model to estimate the expected changes to total costs and health outcomes from a decision to adopt the seizure detection application versus the current standard of care from the health provider perspective. The time horizon is ten years and cycle duration is one month. Parameter values were updated from national databases and published literature. As we do not know the application efficacy in reducing seizure-related injuries, a conservative estimate of 1% reduction was used. Probabilistic sensitivity analysis, scenario analyses, and value of information analysis were performed.

RESULTS

At a willingness-to-pay of $45,000/ quality-adjusted life-years (QALY), the incremental cost-effectiveness ratio was $1,096/QALY, and the incremental net monetary benefit was $13,656. Probabilistic sensitivity analyses reported that the application had a 99.5% chance of being cost-effective. In a scenario analysis in which the reduction in risk of seizure-related injury was 20%, there was a 99.8% chance that the application was cost-effective. Value of information analysis revealed that health utilities was the most important parameter group contributing to model uncertainty.

CONCLUSIONS

This early-stage modeling study reveals that the seizure detection application is likely to be cost-effective compared to current standard of care. Future prospective trials will be needed to demonstrate the real-world impact of the application. Changes in health-related quality of life should also be measured in future trials.

The health and economic impact and cost effectiveness of interventions for the prevention and control of overweight and obesity in Kenya: a stakeholder engaged modelling study

BACKGROUND

The global increase in mean body mass index has resulted in a substantial increase of non-communicable diseases (NCDs), including in many low- and middle-income countries such as Kenya. This paper assesses four interventions for the prevention and control of overweight and obesity in Kenya to determine their potential health and economic impact and cost effectiveness.

METHODS

We reviewed the literature to identify evidence of effect, determine the intervention costs, disease costs and total healthcare costs. We used a proportional multistate life table model to quantify the potential impacts on health conditions and healthcare costs, modelling the 2019 Kenya population over their remaining lifetime. Considering a health system perspective, two interventions were assessed for cost-effectiveness. In addition, we used the Human Capital Approach to estimate productivity gains.

RESULTS

Over the lifetime of the 2019 population, impacts were estimated at 203,266 health-adjusted life years (HALYs) (95% uncertainty interval [UI] 163,752 - 249,621) for a 20% tax on sugar-sweetened beverages, 151,718 HALYs (95% UI 55,257 - 250,412) for mandatory kilojoule menu labelling, 3.7 million HALYs (95% UI 2,661,365-4,789,915) for a change in consumption levels related to supermarket food purchase patterns and 13.1 million HALYs (95% UI 11,404,317 - 15,152,341) for a change in national consumption back to the 1975 average levels of energy intake. This translates to 4, 3, 73 and 261 HALYs per 1,000 persons. Lifetime healthcare cost savings were approximately United States Dollar (USD) 0.14 billion (USD 3 per capita), USD 0.08 billion (USD 2 per capita), USD 1.9 billion (USD 38 per capita) and USD 6.2 billion (USD 124 per capita), respectively. Lifetime productivity gains were approximately USD 1.8 billion, USD 1.2 billion, USD 28 billion and USD 92 billion. Both the 20% tax on sugar sweetened beverages and the mandatory kilojoule menu labelling were assessed for cost effectiveness and found dominant (health promoting and cost-saving).

CONCLUSION

All interventions evaluated yielded substantive health gains and economic benefits and should be considered for implementation in Kenya.

Economic evaluations of non-communicable diseases conducted in Sub-Saharan Africa: a critical review of data sources

BACKGROUND

Policymakers in sub-Saharan Africa (SSA) face challenging decisions regarding the allocation of health resources. Economic evaluations can help decision makers to determine which health interventions should be funded and or included in their benefits package. A major problem is whether the evaluations incorporated data from sources that are reliable and relevant to the country of interest. We aimed to review the quality of the data sources used in all published economic evaluations for cardiovascular disease and diabetes in SSA.

METHODS

We systematically searched selected databases for all published economic evaluations for CVD and diabetes in SSA. We modified a hierarchy of data sources and used a reference case to measure the adherence to reporting and methodological characteristics, and descriptively analysed author statements.

RESULTS

From 7,297 articles retrieved from the search, we selected 35 for study inclusion. Most were modelled evaluations and almost all focused on pharmacological interventions. The studies adhered to the reporting standards but were less adherent to the methodological standards. The quality of data sources varied. The quality level of evidence in the data domains of resource use and costs were generally considered of high quality, with studies often sourcing information from reliable databases within the same jurisdiction. The authors of most studies referred to data sources in the discussion section of the publications highlighting the challenges of obtaining good quality and locally relevant data.

CONCLUSIONS

The data sources in some domains are considered high quality but there remains a need to make substantial improvements in the methodological adherence and overall quality of data sources to provide evidence that is sufficiently robust to support decision making in SSA within the context of UHC and health benefits plans. Many SSA governments will need to strengthen and build their capacity to conduct economic evaluations of interventions and health technology assessment for improved priority setting. This capacity building includes enhancing local infrastructures for routine data production and management. If many of the policy makers are using economic evaluations to guide resource allocation, it is imperative that the evidence used is of the feasibly highest quality.

Stakeholder Engagement in the Development of Public Health Economic Models: An Application to Modelling of Minimum Unit Pricing of Alcohol in South Africa

BACKGROUND

Health economic models aim to provide decision makers with information that is contextually relevant, understandable and credible. This requires ongoing engagement throughout the research project between the modeller and end-users.

OBJECTIVES

We aim to reflect on how a public health economic model of minimum unit pricing of alcohol in South Africa benefited from, and was shaped by, stakeholders. We outline how engagement activities were used during the development, validation and communication phases of the research with input gathered at each stage to inform future priorities.

METHODS

A stakeholder mapping exercise was completed to identify stakeholders with the required knowledge, for example academics with expertise in modelling alcohol harm in South Africa, members of civil society organisations with lived experience of informal alcohol outlets, and policy professionals working at the forefront of alcohol policy development in South Africa. The stakeholder engagement consisted of four phases: developing a detailed understanding of the local policy context; co-producing model focus and structure; scrutinising model development and communication planning; and communicating research evidence to end-users. The first phase utilised 12 individual semi-structured interviews. Phases two to four centred around face-to-face workshops (two online) with both individual and group-based exercises employed to achieve required outputs.

RESULTS

Phase one provided key learning on policy context and initiated working relationships. Phases two to four provided a conceptualisation of the problem of alcohol harm in South Africa and the choice of policy to model. Stakeholders chose population subgroups of interest and advised on both economic and health outcomes. They provided input on critical assumptions, data sources, priorities for future work, and communication strategies. The final workshop provided a platform to communicate the results of the model to a largely policy audience. These activities led to the production of highly contextualised research methods and findings that were able to be communicated widely beyond academia.

CONCLUSIONS

Our programme of stakeholder engagement was fully integrated into the research programme. It resulted in a number of benefits including creating positive working relationships, guiding modelling decisions, tailoring the research to the context, and providing ongoing opportunities for communication.

Model parameters influencing the cost-effectiveness of sacubitril/valsartan in heart failure: evidence from a systematic literature review

OBJECTIVES

To summarize cost-effectiveness (CE) evidence of sacubitril/valsartan for the treatment of heart failure (HF) patients with reduced ejection fraction (HFrEF). The impact of different modeling approaches and parameters on the CE results is also described.

METHODS

We conducted a systematic literature review using multiple databases: Embase^®; MEDLINE^®; MEDLINE^®-In Process; NIHR CRD database including DARE, NHS EED, and HTA databases; and the Cost Effectiveness Analysis registry. We also reviewed HTA countries' websites to identify CE reports of sacubitril/valsartan, published up to 25-July-2021. Articles published in English as full-texts, conference-abstracts, or HTA reports were included.

RESULTS

We included 44 CE models [39 from 37 publications (22 full-texts; 15 conference-abstracts) and 5 HTAs; Europe, n = 20; North and South Americas, n = 14; Asia and Australia, n = 10]. Most models adopted a Markov structure with constant transition probabilities of events (n = 27) or a mix of Markov and regression-based models (n = 16), with variations in structural assumptions and chosen parameters. Study authors concluded sacubitril/valsartan to be a cost-effective therapy in 37/41 models in chronic HFrEF patients and 2/3 models in hospitalized patients stabilized after an acute decompensation for HF. CE models showing sacubitril/valsartan not to be a cost-effective treatment generally modeled a shorter time horizon. Effect of sacubitril/valsartan on cardiovascular and all-cause mortality, cost, duration of effect and time horizon was the main model drivers.

CONCLUSIONS

Most evidence indicated sacubitril/valsartan is cost-effective in HFrEF. The use of a lifetime horizon is recommended in future models as HF is a chronic disease. Data on the CE of sacubitril/valsartan in the inpatient setting were limited and further research is warranted.

Modelling health and economic impact of nutrition interventions: a systematic review

Diet related non-communicable diseases (NCDs), as well as micronutrient deficiencies, are of widespread and growing importance to public health. Authorities are developing programs to improve nutrient intakes via foods. To estimate the potential health and economic impact of these programs there is a wide variety of models. The aim of this review is to evaluate existing models to estimate the health and/or economic impact of nutrition interventions with a focus on reducing salt and sugar intake and increasing vitamin D, iron, and folate/folic acid intake. The protocol of this systematic review has been registered with the International Prospective Register of Systematic Reviews (PROSPERO: CRD42016050873). The final search was conducted on PubMed and Scopus electronic databases and search strings were developed for salt/sodium, sugar, vitamin D, iron, and folic acid intake. Predefined criteria related to scientific quality, applicability, and funding/interest were used to evaluate the publications. In total 122 publications were included for a critical appraisal: 45 for salt/sodium, 61 for sugar, 4 for vitamin D, 9 for folic acid, and 3 for iron. The complexity of modelling the health and economic impact of nutrition interventions is dependent on the purpose and data availability. Although most of the models have the potential to provide projections of future impact, the methodological challenges are considerable. There is a substantial need for more guidance and standardization for future modelling, to compare results of different studies and draw conclusions about the health and economic impact of nutrition interventions.

Model Choice for Quantitative Health Impact Assessment and Modelling: An Expert Consultation and Narrative Literature Review

BACKGROUND

Health impact assessment (HIA) is a widely used process that aims to identify the health impacts, positive or negative, of a policy or intervention that is not necessarily placed in the health sector. Most HIAs are done prospectively and aim to forecast expected health impacts under assumed policy implementation. HIAs may quantitatively and/ or qualitatively assess health impacts, with this study focusing on the former. A variety of quantitative modelling methods exist that are used for forecasting health impacts, however, they differ in application area, data requirements, assumptions, risk modelling, complexities, limitations, strengths, and comprehensibility. We reviewed relevant models, so as to provide public health researchers with considerations for HIA model choice.

METHODS

Based on an HIA expert consultation, combined with a narrative literature review, we identified the most relevant models that can be used for health impact forecasting. We narratively and comparatively reviewed the models, according to their fields of application, their configuration and purposes, counterfactual scenarios, underlying assumptions, health risk modelling, limitations and strengths.

RESULTS

Seven relevant models for health impacts forecasting were identified, consisting of (i) comparative risk assessment (CRA), (ii) time series analysis (TSA), (iii) compartmental models (CMs), (iv) structural models (SMs), (v) agent-based models (ABMs), (vi) microsimulations (MS), and (vii) artificial intelligence (AI)/machine learning (ML). These models represent a variety in approaches and vary in the fields of HIA application, complexity and comprehensibility. We provide a set of criteria for HIA model choice. Researchers must consider that model input assumptions match the available data and parameter structures, the available resources, and that model outputs match the research question, meet expectations and are comprehensible to end-users.

CONCLUSION

The reviewed models have specific characteristics, related to available data and parameter structures, computational implementation, interpretation and comprehensibility, which the researcher should critically consider before HIA model choice.

Avoidable burden of stomach cancer and potential gains in healthy life years from gradual reductions in salt consumption in Vietnam, 2019-2030: a modelling study

OBJECTIVE

Excess salt consumption is causally linked with stomach cancer, and salt intake among adults in Vietnam is about twice the recommended levels. The aim of this study was to quantify the future burden of stomach cancer that could be avoided from population-wide salt reduction in Vietnam.

DESIGN

A dynamic simulation model was developed to quantify the impacts of achieving the 2018 National Vietnam Health Program (8 g/d by 2025 and 7 g/d by 2030) and the WHO (5 g/d) salt reduction policy targets. Data on salt consumption were obtained from the Vietnam 2015 WHO STEPS survey. Health outcomes were estimated over 6-year (2019-2025), 11-year (2019-2030) and lifetime horizons. We conducted one-way and probabilistic sensitivity analyses.

SETTING

Vietnam.

PARTICIPANTS

All adults aged ≥ 25 years (61 million people, 48·4 % men) alive in 2019.

RESULTS

Achieving the 2025 and 2030 national salt targets could result in 3400 and 7200 fewer incident cases of stomach cancer, respectively, and avert 1900 and 4800 stomach cancer deaths, respectively. Achieving the WHO target by 2030 could prevent 8400 incident cases and 5900 deaths from stomach cancer. Over the lifespan, this translated to 344 660 (8 g/d), 411 060 (7 g/d) and 493 633 (5 g/d) health-adjusted life years gained, respectively.

CONCLUSIONS

A sizeable burden of stomach cancer could be avoided, with gains in healthy life years if national and WHO salt targets were attained. Our findings provide impetus for policy makers in Vietnam and Asia to intensify salt reduction strategies to combat stomach cancer and mitigate pressure on the health systems.

Estimated Impact of Achieving the Australian National Sodium Reduction Targets on Blood Pressure, Chronic Kidney Disease Burden and Healthcare Costs: A Modelling Study

Excess sodium intake raises blood pressure which increases the risk of chronic kidney disease (CKD). We aimed to estimate the impact of reduced sodium intake on future CKD burden in Australia. A multi-cohort proportional multistate lifetable model was developed to estimate the potential impact on CKD burden and health expenditure if the Australian Suggested Dietary Target (SDT) and the National Preventive Health Strategy 2021-2030 (NPHS) sodium target were achieved. Outcomes were projected to 2030 and over the lifetime of adults alive in 2019. Achieving the SDT and NPHS targets could lower population mean systolic blood pressure by 2.1 mmHg and 1.7 mmHg, respectively. Compared to normal routines, attaining the SDT and NPHS target by 2030 could prevent 59,220 (95% UI, 53,140-65,500) and 49,890 (44,377-55,569) incident CKD events, respectively, while postponing 568 (479-652) and 511 (426-590) CKD deaths, respectively. Over the lifetime, this generated 199,488 health-adjusted life years (HALYs) and AUD 644 million in CKD healthcare savings for the SDT and 170,425 HALYs and AUD 514 million for the NPHS. CKD due to hypertension and CKD due to other/unspecified causes were the principal contributors to the HALY gains. Lowering sodium consumption in Australia could deliver substantial CKD health and economic benefits.

Bayesian multistate modelling of incomplete chronic disease burden data

A widely-used model for determining the long-term health impacts of public health interventions, often called a "multistate lifetable", requires estimates of incidence, case fatality, and sometimes also remission rates, for multiple diseases by age and gender. Generally, direct data on both incidence and case fatality are not available in every disease and setting. For example, we may know population mortality and prevalence rather than case fatality and incidence. This paper presents Bayesian continuous-time multistate models for estimating transition rates between disease states based on incomplete data. This builds on previous methods by using a formal statistical model with transparent data-generating assumptions, while providing accessible software as an R package. Rates for people of different ages and areas can be related flexibly through splines or hierarchical models. Previous methods are also extended to allow age-specific trends through calendar time. The model is used to estimate case fatality for multiple diseases in the city regions of England, based on incidence, prevalence and mortality data from the Global Burden of Disease study. The estimates can be used to inform health impact models relating to those diseases and areas. Different assumptions about rates are compared, and we check the influence of different data sources.

Estimating Canadian sodium intakes and the health impact of meeting national and WHO recommended sodium intake levels: A macrosimulation modelling study

BACKGROUND

Cardiovascular diseases (CVDs) are the second leading cause of total deaths in Canada. High blood pressure is the main metabolic risk factor for developing CVDs. It has been well established that excess consumption of sodium adversely affects blood pressure. Canadians' mean sodium intakes are well above recommended levels. Reducing dietary sodium intake through food reformulation has been identified as a cost-effective intervention, however, dietary sodium intake and the potential health impact of meeting recommended sodium intake levels due to food reformulation have not been determined in Canada.

OBJECTIVE

This study aimed to 1) obtain robust estimates of Canadians' usual sodium intakes, 2) model sodium intakes had foods been reformulated to align with Health Canada's sodium reduction targets, and 3) estimate the number of CVD deaths that could be averted or delayed if Canadian adults were to reduce their mean sodium intake to recommended levels under three scenarios: A) 2,300 mg/d-driven by a reduction of sodium levels in packaged foods to meet Health Canada targets (reformulation); B) 2,000 mg/d to meet the World Health Organization (WHO) recommendation; and C) 1,500 mg/d to meet the Adequate Intake recommendation.

METHODS

Foods in the University of Toronto's Food Label Information Program 2017, a Canadian branded food composition database, were linked to nationally representative food intake data from the 2015 Canadian Community Health Survey-Nutrition to estimate sodium intakes (and intakes had Health Canada's reformulation strategy been fully implemented). The Preventable Risk Integrated ModEl (PRIME) was used to estimate potential health impact.

RESULTS

Overall, mean sodium intake was 2758 mg/day, varying by age and sex group. Based on 'reformulation' scenario A, mean sodium intakes were reduced by 459 mg/day, to 2299 mg/day. Reducing Canadians' sodium intake to recommended levels under scenarios A, B and C could have averted or delayed 2,176 (95% UI 869-3,687), 3,252 (95% UI 1,380-5,321), and 5,296 (95% UI 2,190-8,311) deaths due to CVDs, respectively, mainly from ischaemic heart disease, stroke, and hypertensive disease. This represents 3.7%, 5.6%, and 9.1%, respectively, of the total number of CVDs deaths observed in Canada in 2019.

CONCLUSION

Results suggest that reducing sodium intake to recommended levels could prevent or postpone a substantial number of CVD deaths in Canada. Reduced sodium intakes could be achieved through reformulation of the Canadian food supply. However, it will require higher compliance from the food industry to achieve Health Canada's voluntary benchmark sodium reduction targets.

Estimating the impact of nutrition and physical activity policies with quasi-experimental methods and simulation modelling: an integrative review of methods, challenges and synergies

BACKGROUND

The promotion of healthy lifestyles has high priority on the global public health agenda. Evidence on the real-world (cost-)effectiveness of policies addressing nutrition and physical activity is needed. To estimate short-term policy impacts, quasi-experimental methods using observational data are useful, while simulation models can estimate long-term impacts. We review the methods, challenges and potential synergies of both approaches for the evaluation of nutrition and physical activity policies.

METHODS

We performed an integrative review applying purposive literature sampling techniques to synthesize original articles, systematic reviews and lessons learned from public international workshops conducted within the European Union Policy Evaluation Network.

RESULTS

We highlight data requirements for policy evaluations, discuss the distinct assumptions of instrumental variable, difference-in-difference, and regression discontinuity designs and describe the necessary robustness and falsification analyses to test them. Further, we summarize the specific assumptions of comparative risk assessment and Markov state-transition simulation models, including their extension to microsimulation. We describe the advantages and limitations of these modelling approaches and discuss future directions, such as the adequate consideration of heterogeneous policy responses. Finally, we highlight how quasi-experimental and simulation modelling methods can be integrated into an evidence cycle for policy evaluation.

CONCLUSIONS

Assumptions of quasi-experimental and simulation modelling methods in policy evaluations should be credible, rigorously tested and transparently communicated. Both approaches can be applied synergistically within a coherent framework to compare policy implementation scenarios and improve the estimation of nutrition and physical activity policy impacts, including their distribution across population sub-groups.

Modelling the health and economic impact of sugary sweetened beverage tax in Canada

Background

With the increasing concerns about the health and economic burden attributed to sugar-sweetened beverages (SSBs) consumption, SSB taxation has been proposed and implemented in many countries. Many previous economic evaluations of SSB taxation have shown that this kind of policy is cost-effective. However, the magnitude of impact varies. This study aims to design a comprehensive model to estimate the impact and cost-effectiveness of the SSB tax in Canada.

Methods

A proportional multi-state life table-based Markov model was chosen to estimate the impacts of SSB tax in Canada. The health-related quality of life (including disability-adjusted life years (DALYs) and quality-adjusted life years (QALYs)), the costs (including health care costs and intervention costs), and the tax revenue were the main health and economic outcomes. We compared the simulated SSB tax with the current practice from the public health care payer perspective, and the tax was applied to the 2015 adult Canadian population up to 100 years. The economic model was built following guidelines from the Canadian Agency for Drugs and Technologies in Health.

Results

After implementing a CAD$0.015/oz SSB tax, 282,104 cases of overweight and obesity, 210,542 cases of diseases, and 2,189 deaths could be prevented. The simulated SSB tax has the potential to avert 2.3 million DALYs, gain 1.5 million QALYs, and save CAD$32,583 million in health care costs in a lifetime period. The incremental cost-effectiveness ratio for the SSB tax was CAD$ -24,933/QALY. The SSB tax with different tax levels (CAD$0.01/oz and CAD$0.02/oz) remained cost-effective.

Conclusion

Implementing the SSB tax in Canada is a potential cost-effective policy option for reducing obesity and related chronic diseases. The model built in this study provides a more accurate estimate of health and economic impact of SSB tax and could be used to estimate other sugar tax options.

Potential productivity loss from uncorrected and under-corrected presbyopia in low- and middle-income countries: A life table modeling study

Objective

To estimate the burden of potential productivity losses due to uncorrected and under-corrected presbyopia in LMICs among the working-age population in both the cross-sectional and longitudinal manner.

Methods

We extracted data for the prevalence of presbyopia from the Global Burden of Diseases (GBD), Injuries, and Risk Factors Study 2019. Data for the gross domestic product (GDP) per capita were extracted from the World Bank database and Central Intelligence Agency's World Factbook. We introduced life table models to construct age cohorts (in 5-year age groups) of the working-age population (aged from 40 to 64 years old) in LMICs, with simulated follow-up until 65 years old in people with and without uncorrected presbyopia. The differences in productivity-adjusted life years (PALYs) lived and productivity between these two cohorts were calculated. The potential productivity loss was estimated based on GDP per capita. The WHO standard 3% annual discount rate was applied to all years of life and PALYs lived.

Results

In 2019, there were 238.40 million (95% confidence interval [CI]: 150.92-346.78 million) uncorrected and under-corrected presbyopia cases in LMICs, resulting in 54.13 billion (current US dollars) (95% confidence interval [CI]: 34.34-79.02 billion) potential productivity losses. With simulated follow-up until retirement, those with uncorrected and under-corrected presbyopia were predicted to experience an additional loss of 155 million PALYs (an average loss of 0.7 PALYs per case), which was equivalent to a total loss of US$ 315 billion (an average loss of US$ 1453.72 per person).

Conclusions

Our findings highlight the considerable productivity losses due to uncorrected and under-corrected presbyopia in LMICs, especially in a longitudinal manner. There is a great need for the development of enabling eye care policies and programs to create access to eye care services, and more healthcare investment in the correction of presbyopia in the working-age population in LMICs. This study could provide evidences for some potential health-related strategies for socio-economic development.

Simulation models of sugary drink policies: A scoping review

INTRODUCTION

Simulation modeling methods are an increasingly common tool for projecting the potential health effects of policies to decrease sugar-sweetened beverage (SSB) intake. However, it remains unknown which SSB policies are understudied and how simulation modeling methods could be improved. To inform next steps, we conducted a scoping review to characterize the (1) policies considered and (2) major characteristics of SSB simulation models.

METHODS

We systematically searched 7 electronic databases in 2020, updated in 2021. Two investigators independently screened articles to identify peer-reviewed research using simulation modeling to project the impact of SSB policies on health outcomes. One investigator extracted information about policies considered and key characteristics of models from the full text of included articles. Data were analyzed in 2021-22.

RESULTS

Sixty-one articles were included. Of these, 50 simulated at least one tax policy, most often an ad valorem tax (e.g., 20% tax, n = 25) or volumetric tax (e.g., 1 cent-per-fluid-ounce tax, n = 23). Non-tax policies examined included bans on SSB purchases (n = 5), mandatory reformulation (n = 3), warning labels (n = 2), and portion size policies (n = 2). Policies were typically modeled in populations accounting for age and gender or sex attributes. Most studies focused on weight-related outcomes (n = 54), used cohort, lifetable, or microsimulation modeling methods (n = 34), conducted sensitivity or uncertainty analyses (n = 56), and included supplementary materials (n = 54). Few studies included stakeholders at any point in their process (n = 9) or provided replication code/data (n = 8).

DISCUSSION

Most simulation modeling of SSB policies has focused on tax policies and has been limited in its exploration of heterogenous impacts across population groups. Future research would benefit from refined policy and implementation scenario specifications, thorough assessments of the equity impacts of policies using established methods, and standardized reporting to improve transparency and consistency.

A scoping review on patient heterogeneity in economic evaluations of precision medicine based on basket trials

INTRODUCTION

Considerable challenges in the economic evaluation of precision medicines have been mentioned in previous studies. However, they have not addressed how an economic assessment would be conducted based on basket trials (novel studies for evaluation of precision medicine effects) in which the included populations have specific biomarkers and various cancers. Since basket trial populations have remarkable heterogeneity, this study aims to investigate the concept of heterogeneity and specific method(s) for considering it in economic evaluations through guidelines and studies that could be applicable in economic evaluation based on basket trials.

AREA COVERED

We searched PubMed, Web of Science, Scopus, Google Scholar, and Google to find studies and pharmacoeconomics guidelines. The inclusion criteria included subjects of patient heterogeneity and suggested explicit method(s). Thirty-nine guidelines and 43 studies were included and evaluated. None of these materials mentioned disease types in a target population as a factor causing heterogeneity. Moreover, in economic evaluations, patient heterogeneity has been considered with four general approaches subgroup analysis, individual-based models, sensitivity analysis, and regression models.

EXPERT OPINION

Type of disease is not considered a contributing factor in population heterogeneity, and the probable appropriate method for this issue could be individual-based models.

Does the Structure Matter? An External Validation and Health Economic Results Comparison of Event Simulation Approaches in Severe Obesity

OBJECTIVES

As obesity-associated events impact long-term survival, health economic (HE) modelling is commonly applied, but modelling approaches are diverse. This research aimed to compare the events simulation and the HE outcomes produced by different obesity modelling approaches.

METHODS

An external validation, using the Swedish obesity subjects (SOS) study, of three main structural event modelling approaches was performed: (1) continuous body mass index (BMI) approach; (2) risk equation approach; and (3) categorical BMI-related approach. Outcomes evaluated were mortality, cardiovascular events, and type 2 diabetes (T2D) for both the surgery and the control arms. Concordance between modelling results and the SOS study were investigated by different state-of-the-art measurements, and categorized by the grade of deviation observed (grades 1-4 expressing mild, moderate, severe, and very severe deviations). Furthermore, the costs per quality-adjusted life-year (QALY) gained of surgery versus controls were compared.

RESULTS

Overall and by study arm, the risk equation approach presented the lowest average grade of deviation (overall grade 2.50; control arm 2.25; surgery arm 2.75), followed by the continuous BMI approach (overall 3.25; control 3.50; surgery 3.00) and by the categorial BMI approach (overall 3.63; control 3.50; surgery 3.75). Considering different confidence interval limits, the costs per QALY gained were fairly comparable between all structural approaches (ranging from £2,055 to £6,206 simulating a lifetime horizon).

CONCLUSION

None of the structural approaches provided perfect external event validation, although the risk equation approach showed the lowest overall deviations. The economic outcomes resulting from the three approaches were fairly comparable.

Modelling decay in effectiveness for evaluation of behaviour change interventions: a tutorial for public health economists

BACKGROUND AND PURPOSE

Recent methodological reviews of evaluations of behaviour change interventions in public health have highlighted that the decay in effectiveness over time has been mostly overlooked, potentially leading to suboptimal decision-making. While, in principle, discrete-time Markov chains-the most commonly used modelling approach-can be adapted to account for decay in effectiveness, this framework inherently lends itself to strong model simplifications. The application of formal and more appropriate modelling approaches has been supported, but limited progress has been made to date. The purpose of this paper is to encourage this shift by offering a practical guide on how to model decay in effectiveness using a continuous-time Markov chain (CTMC)-based approach.

METHODS

A CTMC approach is demonstrated, with a contextualized tutorial being presented to facilitate learning and uptake. A worked example based on the stylized case study in physical activity promotion is illustrated with accompanying R code.

DISCUSSION

The proposed framework presents a relatively small incremental change from the current modelling practice. CTMC represents a technical solution which, in absence of relevant data, allows for formally testing the sensitivity of results to assumptions regarding the long-term sustainability of intervention effects and improving model transparency.

CONCLUSIONS

The use of CTMC should be considered in evaluations where decay in effectiveness is likely to be a key factor to consider. This would enable more robust model-based evaluations of population-level programmes to promote behaviour change and reduce the uncertainty surrounding the decision to invest in these public health interventions.

The avoidable disease burden associated with overweight and obesity in Kenya: A modelling study

BACKGROUND

Globally, there is a rising burden of non-communicable diseases related to high body mass index (BMI). Estimation of the magnitude of the avoidable disease burden related to high BMI in Kenya could inform priority setting in health.

METHODS

Using a proportional multistate life table model, we estimated the impact of the elimination of exposure to high BMI (>22·5 kg/m²) on health adjusted life years, health adjusted life expectancy, and burden of 27 obesity-related diseases. Participants were the 2019 Kenyan population modelled over their remaining lifetime.

FINDINGS

Elimination of high BMI could save approximately 83·5 million health-adjusted life years and increase the health-adjusted life expectancy by 2·3 (95% UI 2·0-2·8) years for females and 1·0 (95% UI 0·8-1·1) years for males. Over the first 25 years, over 7·4 million new cases of BMI-related diseases could be avoided and approximately half a million BMI related deaths postponed. The cumulative number of new cases of type 2 diabetes could reduce by approximately 1·6 million, cardiovascular diseases by over 1·3 million, chronic kidney disease by 850,473 and cancer would reduce by 55,624 estimated cases. In 2044, an estimated 867,664 prevalent cases of musculoskeletal disease would be prevented.

INTERPRETATION

The magnitude of avoidable high BMI-related disease burden in Kenya underscores the need to prioritise the control and prevention of overweight and obesity globally, especially in low- and middle-income settings, where obesity rates are rising rapidly. Reducing population BMI is challenging, but sustained and well-enforced system-wide approaches could be a great starting point.

FUNDING

Mary Njeri Wanjau is supported by the Griffith University International Postgraduate Research Scholarship (GUIPRS) and Griffith University Postgraduate Research Scholarship (GUPRS).

Using decision analysis to support implementation planning in research and practice

BACKGROUND

The process of implementing evidence-based interventions, programs, and policies is difficult and complex. Planning for implementation is critical and likely plays a key role in the long-term impact and sustainability of interventions in practice. However, implementation planning is also difficult. Implementors must choose what to implement and how best to implement it, and each choice has costs and consequences to consider. As a step towards supporting structured and organized implementation planning, we advocate for increased use of decision analysis.

MAIN TEXT

When applied to implementation planning, decision analysis guides users to explicitly define the problem of interest, outline different plans (e.g., interventions/actions, implementation strategies, timelines), and assess the potential outcomes under each alternative in their context. We ground our discussion of decision analysis in the PROACTIVE framework, which guides teams through key steps in decision analyses. This framework includes three phases: (1) definition of the decision problems and overall objectives with purposeful stakeholder engagement, (2) identification and comparison of different alternatives, and (3) synthesis of information on each alternative, incorporating uncertainty. We present three examples to illustrate the breadth of relevant decision analysis approaches to implementation planning.

CONCLUSION

To further the use of decision analysis for implementation planning, we suggest areas for future research and practice: embrace model thinking; build the business case for decision analysis; identify when, how, and for whom decision analysis is more or less useful; improve reporting and transparency of cost data; and increase collaborative opportunities and training.

Comparing health gains, costs and cost-effectiveness of 100s of interventions in Australia and New Zealand: an online interactive league table

BACKGROUND

This study compares the health gains, costs, and cost-effectiveness of hundreds of Australian and New Zealand (NZ) health interventions conducted with comparable methods in an online interactive league table designed to inform policy.

METHODS

A literature review was conducted to identify peer-reviewed evaluations (2010 to 2018) arising from the Australia Cost-Effectiveness research and NZ Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programmes, or using similar methodology, with: health gains quantified as health-adjusted life years (HALYs); net health system costs and/or incremental cost-effectiveness ratio; time horizon of at least 10 years; and 3% to 5% discount rates.

RESULTS

We identified 384 evaluations that met the inclusion criteria, covering 14 intervention domains: alcohol; cancer; cannabis; communicable disease; cardiovascular disease; diabetes; diet; injury; mental illness; other non-communicable diseases; overweight and obesity; physical inactivity; salt; and tobacco. There were large variations in health gain across evaluations: 33.9% gained less than 0.1 HALYs per 1000 people in the total population over the remainder of their lifespan, through to 13.0% gaining > 10 HALYs per 1000 people. Over a third (38.8%) of evaluations were cost-saving.

CONCLUSIONS

League tables of comparably conducted evaluations illustrate the large health gain (and cost) variations per capita between interventions, in addition to cost-effectiveness. Further work can test the utility of this league table with policy-makers and researchers.

Forecast of myocardial infarction incidence, events and prevalence in England to 2035 using a microsimulation model with endogenous disease outcomes

Background

Models that forecast non-communicable disease rates are poorly designed to predict future changes in trend because they are based on exogenous measures of disease rates. We introduce microPRIME, which forecasts myocardial infarction (MI) incidence, events and prevalence in England to 2035. microPRIME can forecast changes in trend as all MI rates emerge from competing trends in risk factors and treatment.

Materials and methods

microPRIME is a microsimulation of MI events within a sample of 114,000 agents representative of England. We simulate 37 annual time points from 1998 to 2035, where agents can have an MI event, die from an MI, or die from an unrelated cause. The probability of each event is a function of age, sex, BMI, blood pressure, cholesterol, smoking, diabetes and previous MI. This function does not change over time. Instead population-level changes in MI rates are due to competing trends in risk factors and treatment. Uncertainty estimates are based on 450 model runs that use parameters calibrated against external measures of MI rates between 1999 and 2011.

Findings

Forecasted MI incidence rates fall for men and women of different age groups before plateauing in the mid 2020s. Age-standardised event rates show a similar pattern, with a non-significant upturn by 2035, larger for men than women. Prevalence in men decreases for the oldest age groups, with peaks of prevalence rates in 2019 for 85 and older at 25.8% (23.3–28.3). For women, prevalence rates are more stable. Prevalence in over 85s is estimated as 14.5% (12.6–16.5) in 2019, and then plateaus thereafter.

Conclusion

We may see an increase in event rates from MI in England for men before 2035 but increases for women are unlikely. Prevalence rates may fall in older men, and are likely to remain stable in women over the next decade and a half.

Estimating cardiovascular health gains from eradicating indoor cold in Australia

BACKGROUND

Exposure to cold indoor temperature (< 18 degrees Celsius) increases cardiovascular disease (CVD) risk and has been identified by the WHO as a source of unhealthy housing. While warming homes has the potential to reduce CVD risk, the reduction in disease burden is not known. We simulated the population health gains from reduced CVD burden if the temperature in all Australian cold homes was permanently raised from their assumed average temperature of 16 degrees Celsius to 20 degrees Celsius.

METHODS

The health effect of eradicating cold housing through reductions in CVD was simulated using proportional multistate lifetable model. The model sourced CVD burden and epidemiological data from Australian and Global Burden of Disease studies. The prevalence of cold housing in Australia was estimated from the Australian Housing Conditions Survey. The effect of cold indoor temperature on blood pressure (and in turn stroke and coronary heart disease) was estimated from published research.

RESULTS

Eradication of exposure to indoor cold could achieve a gain of undiscounted one and a half weeks of additional health life per person alive in 2016 (base-year) in cold housing through CVD alone. This equates to 0.447 (uncertainty interval: 0.064, 1.34; 3% discount rate) HALYs per 1,000 persons over remainder of their lives through CVD reduction. Eight percent of the total health gains are achievable between 2016 and 2035. Although seemingly modest, the gains outperform currently recommended CVD interventions including persistent dietary advice for adults 5-9% 5 yr CVD risk (0.017 per 1000 people, UI: 0.01, 0.027) and persistent lifestyle program for adults 5-9% 5 yr CVD risk (0.024, UI: 0.01, 0.027).

CONCLUSION

Cardiovascular health gains alone achievable through eradication of cold housing are comparable with real-life lifestyle and dietary interventions. The potential health gains are even greater given cold housing eradication will also improve respiratory and mental health in addition to cardiovascular disease.

Microsimulation Modeling in Food Policy: A Scoping Review of Methodological Aspects

Food policies for the prevention and management of diet-related noncommunicable diseases (NCDs) have been increasingly relying on microsimulation models (MSMs) to assess effectiveness. Given the increased uptake of MSMs, this review aims to provide an overview of the characteristics of MSMs that link diets with NCDs. A comprehensive review was conducted in PubMed and Web of Knowledge. Inclusion criteria were: 1) findings from an MSM; 2) diets, foods, or nutrients as the main exposure of interest; and 3) NCDs, such as overweight/obesity, type 2 diabetes, coronary heart disease, stroke, or cancer, as the disease outcome for impact assessment. This review included information from 33 studies using MSM in analyzing diet and diverse food policies on NCDs. Hereby, most models employed stochastic, discrete-time, dynamic microsimulation techniques to calculate anticipated (cost-)effectiveness of strategies based on food pricing, food reformulation, or dietary (lifestyle) interventions. Currently available models differ in the methodology used for quantifying the effect of the dietary changes on disease, and in the method for modeling the disease incidence and mortality. However, all studies provided evidence that the models were sufficiently capturing the close-to-reality situation by justifying their choice of model parameters and validating externally their modeled disease incidence and mortality with observed or predicted event data. With the increasing use of various MSMs, between-model comparisons, facilitated by open access models and good reporting practices, would be important for judging a model's accuracy, leading to continued improvement in the methodologies for developing and applying MSMs and, subsequently, a better understanding of the results by policymakers.

Equity impact of minimum unit pricing of alcohol on household health and finances among rich and poor drinkers in South Africa

Introduction

South Africa experiences significant levels of alcohol-related harm. Recent research suggests minimum unit pricing (MUP) for alcohol would be an effective policy, but high levels of income inequality raise concerns about equity impacts. This paper quantifies the equity impact of MUP on household health and finances in rich and poor drinkers in South Africa.

Methods

We draw from extended cost-effectiveness analysis (ECEA) methods and an epidemiological policy appraisal model of MUP for South Africa to simulate the equity impact of a ZAR 10 MUP over a 20-year time horizon. We estimate the impact across wealth quintiles on: (i) alcohol consumption and expenditures; (ii) mortality; (iii) government healthcare cost savings; (iv) reductions in cases of catastrophic health expenditures (CHE) and household savings linked to reduced health-related workplace absence.

Results

We estimate MUP would reduce consumption more among the poorest than the richest drinkers. Expenditure would increase by ZAR 353 000 million (1 US$=13.2 ZAR), the poorest contributing 13% and the richest 28% of the increase, although this remains regressive compared with mean income. Of the 22 600 deaths averted, 56% accrue to the bottom two quintiles; government healthcare cost savings would be substantial (ZAR 3.9 billion). Cases of CHE averted would be 564 700, 46% among the poorest two quintiles. Indirect cost savings amount to ZAR 51.1 billion.

Conclusions

A MUP policy in South Africa has the potential to reduce harm and health inequality. Fiscal policies for population health require structured policy appraisal, accounting for the totality of effects using mathematical models in association with ECEA methodology.

Non-invasive testing for early detection of neovascular macular degeneration in unaffected second eyes of older adults: EDNA diagnostic accuracy study

BACKGROUND

Neovascular age-related macular degeneration is a leading cause of sight loss, and early detection and treatment is important. For patients with neovascular age-related macular degeneration in one eye, it is usual practice to monitor the unaffected eye. The test used to diagnose neovascular age-related macular degeneration, fundus fluorescein angiography, is an invasive test. Non-invasive tests are available, but their diagnostic accuracy is unclear.

OBJECTIVES

The primary objective was to determine the diagnostic monitoring performance of tests for neovascular age-related macular degeneration in the second eye of patients with unilateral neovascular age-related macular degeneration. The secondary objectives were the cost-effectiveness of tests and to identify predictive factors of developing neovascular age-related macular degeneration.

DESIGN

This was a multicentre, prospective, cohort, comparative diagnostic accuracy study in a monitoring setting for up to 3 years. A Cox regression risk prediction model and a Markov microsimulation model comparing cost-effectiveness of the index tests over 25 years were used.

SETTING

This took place in hospital eye services.

PARTICIPANTS

Participants were adults (aged 50-95 years) with newly diagnosed (within the previous 6 weeks) neovascular age-related macular degeneration in one eye and an unaffected second (study) eye who were attending for treatment injections in the first eye and who had a study eye baseline visual acuity of ≥ 68 Early Treatment Diabetic Retinopathy Study letters.

INTERVENTIONS

The index tests were Amsler chart (completed by participants), fundus clinical examination, optical coherence tomography, self-reported vision assessment (completed by participants) and visual acuity. The reference standard was fundus fluorescein angiography.

MAIN OUTCOME MEASURES

The main outcome measures were sensitivity and specificity; the performance of the risk predictor model; and costs and quality-adjusted life-years.

RESULTS

In total, 552 out of 578 patients who consented from 24 NHS hospitals (n = 16 ineligible; n = 10 withdrew consent) took part. The mean age of the patients was 77.4 years (standard deviation 7.7 years) and 57.2% were female. For the primary analysis, 464 patients underwent follow-up fundus fluorescein angiography and 120 developed neovascular age-related macular degeneration on fundus fluorescein angiography. The diagnostic accuracy [sensitivity (%) (95% confidence interval); specificity (%) (95% confidence interval)] was as follows: optical coherence tomography 91.7 (85.2 to 95.6); 87.8 (83.8 to 90.9)], fundus clinical examination [53.8 (44.8 to 62.5); 97.6 (95.3 to 98.9)], Amsler [33.7 (25.1 to 43.5); 81.4 (76.4 to 85.5)], visual acuity [30.0 (22.5 to 38.7); 66.3 (61.0 to 71.1)] and self-reported vision [4.2 (1.6 to 9.8); 97.0 (94.6 to 98.5)]. Optical coherence tomography had the highest sensitivity across all secondary analyses. The final prediction model for neovascular age-related macular degeneration in the non-affected eye included smoking status, family history of neovascular age-related macular degeneration, the presence of nodular drusen with or without reticular pseudodrusen, and the presence of pigmentary abnormalities [c-statistic 0.66 (95% confidence interval 0.62 to 0.71)]. Optical coherence tomography monitoring generated the greatest quality-adjusted life-years gained per patient (optical coherence tomography, 5.830; fundus clinical examination, 5.787; Amsler chart, 5.736, self-reported vision, 5.630; and visual acuity, 5.600) for the lowest health-care and social care costs (optical coherence tomography, £19,406; fundus clinical examination, £19,649; Amsler chart, £19,751; self-reported vision, £20,198; and visual acuity, £20,444) over the lifetime of the simulated cohort. Optical coherence tomography dominated the other tests or had an incremental cost-effectiveness ratio below the accepted cost-effectiveness thresholds (£20,000) across the scenarios explored.

LIMITATIONS

The diagnostic performance may be different in an unselected population without any history of neovascular age-related macular degeneration; the prediction model did not include genetic profile data, which might have improved the discriminatory performance.

CONCLUSIONS

Optical coherence tomography was the most accurate in diagnosing conversion to neovascular age-related macular degeneration in the fellow eye of patients with unilateral neovascular age-related macular degeneration. Economic modelling suggests that optical coherence tomography monitoring is cost-effective and leads to earlier diagnosis of and treatment for neovascular age-related macular degeneration in the second eye of patients being treated for neovascular age-related macular degeneration in their first eye.

FUTURE WORK

Future works should investigate the role of home monitoring, improved risk prediction models and impact on long-term visual outcomes.

STUDY REGISTRATION

This study was registered as ISRCTN48855678.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 8. See the NIHR Journals Library website for further project information.

The Impact of Diabetes on Productivity in India

OBJECTIVE

Diabetes increases the risk of premature mortality and considerably impacts on work productivity. We sought to examine the impact of diabetes in India, in terms of excess premature mortality, years of life lost (YLL), productivity-adjusted life years (PALYs) lost, and its associated economic impact.

RESEARCH DESIGN AND METHODS

A life table model was constructed to examine the productivity of the Indian working-age population currently aged 20-59 years with diabetes, followed until death or retirement age (60 years). The same cohort was resimulated, hypothetically assuming that they did not have diabetes. The total difference between the two cohorts, in terms of excess deaths, YLL and PALYs lost reflected the impact of diabetes. Data regarding the prevalence of diabetes, mortality, labor force dropouts, and productivity loss attributable to diabetes were derived from published sources.

RESULTS

In 2017, an estimated 54.4 million (7.6%) people of working-age in India had diabetes. With simulated follow-up until death or retirement age, diabetes was predicted to cause 8.5 million excess deaths (62.7% of all deaths), 42.7 million YLL (7.4% of total estimated years of life lived), and 89.0 million PALYs lost (23.3% of total estimated PALYs), equating to an estimated Indian rupee 176.6 trillion (U.S. dollars 2.6 trillion; purchasing power parity 9.8 trillion) in lost gross domestic product.

CONCLUSIONS

Our study demonstrates the impact of diabetes on productivity loss and highlights the importance of health strategies aimed at the prevention of diabetes.

Methodological issues in economic evaluations of disease prevention and health promotion: an overview of systematic and scoping reviews

BACKGROUND

We aimed to provide a comprehensive overview of methodological challenges in economic evaluations of disease prevention and health promotion (DPHP)-measures.

METHODS

We conducted an overview of reviews searching MEDLINE, EMBASE, NHS Economic Evaluation Database, Database of Promoting Health Effectiveness Reviews, Cochrane Database of Systematic Reviews (CDSR) and Database of Promoting Health Effectiveness Reviews (DOPHER) (from their inception to October 2021). We included both systematic and scoping reviews of economic evaluations in DPHP addressing following methodological aspects: (i) attribution of effects, (ii) outcomes, (iii) inter-sectoral (accruing to non-health sectors of society) costs and consequences and (iv) equity. Data were extracted according to the associated sub-criteria of the four methodological aspects including study design economic evaluation (e.g. model-based), type/scope of the outcomes (e.g. outcomes beyond health), perspective, cost categories related to non-health sectors of society, and consideration of equity (method of inclusion). Two reviewers independently screened all citations, full-text articles, and extracted data. A narrative synthesis without a meta-analysis or other statistical synthesis methods was conducted.

RESULTS

The reviewing process resulted in ten systematic and one scoping review summarizing 494 health economic evaluations. A lifelong time horizon was adopted in about 23% of DPHP evaluations, while 64% of trial-based evaluations had a time horizon up to 2 years. Preference-based outcomes (36%) and non-health outcomes (8%) were only applied in a minority of studies. Although the inclusion of inter-sectoral costs (i.e. costs accruing to non-health sectors of society) has increased in recent years, these were often neglected (between 6 and 23% depending on the cost category). Consideration to equity was barely given in economic evaluations, and only addressed in six of the eleven reviews.

CONCLUSIONS

Economic evaluations of DPHP measures give only little attention to the specific methodological challenges related to this area. For future economic DPHP evaluations a tool with structured guidance should be developed. This overview of reviews was not registered and a published protocol does not exist.

Simulation Modeling for the Economic Evaluation of Population-Based Dietary Policies: A Systematic Scoping Review

Simulation modeling can be useful to estimate the long-term health and economic impacts of population-based dietary policies. We conducted a systematic scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guideline to map and critically appraise economic evaluations of population-based dietary policies using simulation models. We searched Medline, Embase, and EconLit for studies published in English after 2005. Modeling studies were mapped based on model type, dietary policy, and nutritional target, and modeled risk factor-outcome pathways were analyzed. We included 56 studies comprising 136 model applications evaluating dietary policies in 21 countries. The policies most often assessed were reformulation (34/136), taxation (27/136), and labeling (20/136); the most common targets were salt/sodium (60/136), sugar-sweetened beverages (31/136), and fruit and vegetables (15/136). Model types included Markov-type (35/56), microsimulation (11/56), and comparative risk assessment (7/56) models. Overall, the key diet-related risk factors and health outcomes were modeled, but only 1 study included overall diet quality as a risk factor. Information about validation was only reported in 19 of 56 studies and few studies (14/56) analyzed the equity impacts of policies. Commonly included cost components were health sector (52/56) and public sector implementation costs (35/56), as opposed to private sector (18/56), lost productivity (11/56), and informal care costs (3/56). Most dietary policies (103/136) were evaluated as cost-saving independent of the applied costing perspective. An analysis of the main limitations reported by authors revealed that model validity, uncertainty of dietary effect estimates, and long-term intervention assumptions necessitate a careful interpretation of results. In conclusion, simulation modeling is widely applied in the economic evaluation of population-based dietary policies but rarely takes dietary complexity and the equity dimensions of policies into account. To increase relevance for policymakers and support diet-related disease prevention, economic effects beyond the health sector should be considered, and transparent conduct and reporting of model validation should be improved.

Effects of minimum unit pricing for alcohol in South Africa across different drinker groups and wealth quintiles: a modelling study

OBJECTIVES

To quantify the potential impact of minimum unit pricing (MUP) for alcohol on alcohol consumption, spending and health in South Africa. We provide these estimates disaggregated by different drinker groups and wealth quintiles.

DESIGN

We developed an epidemiological policy appraisal model to estimate the effects of MUP across sex, drinker groups (moderate, occasional binge, heavy) and wealth quintiles. Stakeholder interviews and workshops informed model development and ensured policy relevance.

SETTING

South African drinking population aged 15+.

PARTICIPANTS

The population (aged 15+) of South Africa in 2018 stratified by drinking group and wealth quintiles, with a model time horizon of 20 years.

MAIN OUTCOME MEASURES

Change in standard drinks (SDs) (12 g of ethanol) consumed, weekly spend on alcohol, annual number of cases and deaths for five alcohol-related health conditions (HIV, intentional injury, road injury, liver cirrhosis and breast cancer), reported by drinker groups and wealth quintile.

RESULTS

We estimate an MUP of R10 per SD would lead to an immediate reduction in consumption of 4.40% (-0.93 SD/week) and an increase in spend of 18.09%. The absolute reduction is greatest for heavy drinkers (-1.48 SD/week), followed by occasional binge drinkers (-0.41 SD/week) and moderate drinkers (-0.40 SD/week). Over 20 years, we estimate 20 585 fewer deaths and 9 00 332 cases averted across the five health-modelled harms.Poorer drinkers would see greater impacts from the policy (consumption: -7.75% in the poorest quintile, -3.19% in richest quintile). Among the heavy drinkers, 85% of the cases averted and 86% of the lives saved accrue to the bottom three wealth quintiles.

CONCLUSIONS

We estimate that MUP would reduce alcohol consumption in South Africa, improving health outcomes while raising retail and tax revenue. Consumption and harm reductions would be greater in poorer groups.

Early detection of neovascular age-related macular degeneration: an economic evaluation based on data from the EDNA study

BACKGROUND/AIMS

To evaluate the cost-effectiveness of non-invasive monitoring tests to detect the onset of neovascular age-related macular degeneration (nAMD) in the unaffected second eye of patients receiving treatment for unilateral nAMD in a UK National Health Service (NHS) hospital outpatient setting.

METHODS

A patient-level state transition model was constructed to simulate the onset, detection, and treatment of nAMD in the second eye. Five index tests were compared: self-reported change in visual function, Amsler test, clinic measured change in visual acuity from baseline, fundus assessment by clinical examination or colour photography, and spectral domain optical coherence tomography (SD-OCT). Diagnosis of nAMD was confirmed by fundus fluorescein angiography (FFA) before prompt initiation of antivascular endothelial growth factor treatment. Quality-adjusted life-years (QALYs) and costs of health and social care were modelled over a 25-year time horizon.

RESULTS

SD-OCT generated more QALYs (SD-OCT, 5.830; fundus assessment, 5.787; Amsler grid, 5.736, patient's subjective assessment, 5.630; and visual acuity, 5.600) and lower health and social care costs (SD-OCT, £19 406; fundus assessment, £19 649; Amsler grid, £19 751; patient's subjective assessment, £20 198 and visual acuity, £20 444) per patient compared with other individual monitoring tests. Probabilistic sensitivity analysis indicated a high probability (97%-99%) of SD-OCT being the preferred test across a range of cost-effectiveness thresholds (£13 000-£30 000) applied in the UK NHS.

CONCLUSIONS

Early treatment of the second eye following FFA confirmation of SD-OCT positive findings is expected to maintain better visual acuity and health-related quality of life and may reduce costs of health and social care over the lifetime of patients.

Comparison of smoking reduction with improvement of social conditions in early life: simulation in a British cohort

BACKGROUND

Health care evaluation models can be useful to assign different levels of priority to interventions or policies targeting different age groups or different determinants of health. We aimed to assess early mortality in counterfactual scenarios implying reduced adverse childhood experience (ACE) and/or improved educational attainment (childhood and early life characteristics), compared with a counterfactual scenario implying reduced smoking in adulthood.

METHODS

We used data from the 1958 National Child Development Study British birth cohort, which initially included 18 558 subjects. Applying a potential outcome approach, scenarios were simulated to estimate the expected mortality between ages 16 and 55 under a counterfactual decrease by half of the observed level of exposure to (i) ACE, (ii) low educational attainment (at age 22), (iii) ACE and low educational attainment (a combined exposure) and (iv) smoking at age 33. Estimations were obtained using g-computation, separately for men and women. Analyses were further stratified according to the parental level of education, to assess social inequalities.

RESULTS

The study population included 12 164 members. The estimated decrease in mortality in the counterfactual scenarios with reduced ACE and improved educational attainment was close to the decreased mortality in the counterfactual scenario with reduced smoking, showing a relative difference in mortality of respectively -7.2% [95% CI (confidence interval) = (-12.2% to 1.2%)] versus -7.0% (-13.1% to +1.2%) for women, and -9.9% (-15.6% to -6.2%) versus -12.3% (-17.0% to -5.9%) for men.

CONCLUSIONS

Our results highlight the potential value of targeting early social characteristics such as ACE and education, compared with well-recognized interventions on smoking.

Accounting for Heterogeneity in Resource Allocation Decisions: Methods and Practice in UK Cancer Technology Appraisals

OBJECTIVES

The availability of novel, more efficacious and expensive cancer therapies is increasing, resulting in significant treatment effect heterogeneity and complicated treatment and disease pathways. The aim of this study is to review the extent to which UK cancer technology appraisals (TAs) consider the impact of patient and treatment effect heterogeneity.

METHODS

A systematic search of National Institute for Health and Care Excellence TAs of colorectal, lung and ovarian cancer was undertaken for the period up to April 2020. For each TA, the pivotal clinical studies and economic evaluations were reviewed for considerations of patient and treatment effect heterogeneity. The study critically reviews the use of subgroup analysis and real-world translation in economic evaluations, alongside specific attributes of the economic modeling framework.

RESULTS

The search identified 49 TAs including 49 economic models. In total, 804 subgroup analyses were reported across 69 clinical studies. The most common stratification factors were age, gender, and Eastern Cooperative Oncology Group performance score, with 15% (119 of 804) of analyses demonstrating significantly different clinical outcomes to the main population; economic subgroup analyses were undertaken in only 17 TAs. All economic models were cohort-level with the majority described as partitioned survival models (39) or Markov/semi-Markov models. The impact of real-world heterogeneity on disease progression estimates was only explored in 2 models.

CONCLUSION

The ability of current modeling approaches to capture patient and treatment effect heterogeneity is constrained by their limited flexibility and simplistic nature. This study highlights a need for the use of more sophisticated modeling methods that enable greater consideration of real-world heterogeneity.

Overview and Use of Tools for Selecting Modelling Techniques in Health Economic Studies

The availability and use of tools to guide the choice of modelling technique are not well understood. Our study aims to review existing tools and explore the use of those tools in health economic models. Two reviews and one case study were conducted. Review 1 aimed to identify tools based on expert opinion and citation searching and explore the value of the tools for health economic models. Review 2, based on citation searching, aimed to describe how those tools have been used in health economic models. Both reviews were conducted using Web of Science and Scopus. Two independent reviewers selected studies for inclusion. A case study, focused on economic evaluations of antipsychotic medication in schizophrenia, was conducted to compare the modelling techniques used by existing models with modelling techniques recommended by identified tools. Seven tools were identified, of which the revised Brennan's toolkit, was assessed to be the most appropriate for health economic models. The seven tools were cited 126 times in publications reporting health economic models. Only 17 of these (13.5%) reported that they used the tool(s) to guide the choice of modelling technique. Application of these tools suggested discrete event simulation is most appropriate for modelling antipsychotic medication in schizophrenia, but discrete event simulation was only used by 17% of existing models. There is considerable inconsistency between the modelling techniques used by existing models and modelling techniques recommended by tools. It is recommended that for future modelling studies the choice of modelling technique should be justified, this can be achieved by the application of model selection tools, such as the revised Brennan's toolkit. Future research is required to explore the barriers to using model selection tools in health economic models and to update existing tools and make them easier to use.

Dehydrated human amnion and chorion allograft versus standard of care alone in treatment of Wagner 1 diabetic foot ulcers: a trial-based health economics study

AIMS

The aim of this health economics study was to estimate the cost-utility of an aseptically processed, dehydrated human amnion and chorion allograft (dHACA) plus standard of care (SOC) (group 1) versus SOC alone (group 2) based on a published randomized controlled trial in which patients who had an eligible Wagner 1 diabetic foot ulcer wound were randomized to either of these treatments.

MATERIALS AND METHODS

A Markov microsimulation was used to project trial results out to a 1-year horizon time with a third-party payer perspective. The starting health state was an unhealed non-infected ulcer with other health states of healed ulcer, infected non-healed ulcer, cellulitis, osteomyelitis, and absorbing states of dead or amputation. All patients started with unhealed non-infected ulcers at cycle 0. Costs were incurred by patients for procedures at hospital outpatient wound care provider-based departments (PBDs) and hospitals (if complications occurred) and were calculated using time-based activity costing methods. Effectiveness units were quality-adjusted life years (QALYs) computed from literature utility values. One-way and probabilistic sensitivity analysis (PSA) were also conducted.

RESULTS

After 1 year, the calculated incremental cost-effectiveness ratio (ICER) for group 1 versus group 2 was -$4,373 with group 1 (dHACA) being dominant over group 2 (SOC). PSA demonstrated that group 1 had 69.2% lower cost values with increased positive incremental effectiveness for 94.9% of values. A willingness to pay (WTP) curve showed that about 92% of interventions were cost effective for group 1 when $50,000 was paid.

CONCLUSIONS

The results of this study demonstrated that dHACA added to SOC compared to SOC alone was extremely cost-effective in the defined trial population.

Proportional multistate lifetable modelling of preventive interventions: concepts, code and worked examples

Burden of Disease studies-such as the Global Burden of Disease (GBD) Study-quantify health loss in disability-adjusted life-years. However, these studies stop short of quantifying the future impact of interventions that shift risk factor distributions, allowing for trends and time lags. This methodology paper explains how proportional multistate lifetable (PMSLT) modelling quantifies intervention impacts, using comparisons between three tobacco control case studies [eradication of tobacco, tobacco-free generation i.e. the age at which tobacco can be legally purchased is lifted by 1 year of age for each calendar year) and tobacco tax]. We also illustrate the importance of epidemiological specification of business-as-usual in the comparator arm that the intervention acts on, by demonstrating variations in simulated health gains when incorrectly: (i) assuming no decreasing trend in tobacco prevalence; and (ii) not including time lags from quitting tobacco to changing disease incidence. In conjunction with increasing availability of baseline and forecast demographic and epidemiological data, PMSLT modelling is well suited to future multiple country comparisons to better inform national, regional and global prioritization of preventive interventions. To facilitate use of PMSLT, we introduce a Python-based modelling framework and associated tools that facilitate the construction, calibration and analysis of PMSLT models.

Modelling the effect of compliance with WHO salt recommendations on cardiovascular disease mortality and costs in Brazil

INTRODUCTION

Cardiovascular diseases (CVDs) represent the main cause of death among non-communicable diseases (NCDs) in Brazil, and they have a high economic impact on health systems. Most populations around the world, including Brazilians, consume excessive sodium, which increases blood pressure and the risk of CVDs.

OBJECTIVE

To model the estimated deaths and costs associated with CVDs, which are mediated by increased blood pressure attributable to excessive sodium consumption in adults from the perspective of the Brazilian public health system in 2017.

METHODS

We employed two macrosimulation methods, using top-down approaches and based on the same relative risks. The models estimated the mortality and costs-of-illness attributable to excessive sodium intake and mediated by hypertension for adults aged over 30 years in 2017. Direct healthcare cost data (inpatient care, outpatient care and medications) were extracted from the Ministry of Health information systems and official records.

RESULTS

In 2017, an estimated 46,651 deaths from CVDs could have been prevented if the average sodium consumption had been reduced to 2 g/day in Brazil. Premature deaths related to excessive sodium consumption caused 575,172 Years of Life Lost and US$ 752.7 million in productivity losses to the economy. In the same year, the National Health System's costs of hospitalizations, outpatient care and medication for hypertension attributable to excessive sodium consumption totaled US$192.1 million. The main causes of death and costs associated with CVDs were coronary heart disease and stroke, followed by hypertensive disease, heart failure and aortic aneurysm.

CONCLUSION

Excessive sodium consumption is estimated to account for 15% of deaths by CVDs and to 14% of the inpatient and outpatient costs associated with CVD. It also has high societal costs in terms of premature deaths. CVDs are a leading cause of disease and economic burden on the global, regional and country levels. As a largely preventable and treatable conditions, CVDs require the strengthening of cost-effective policies, supported by evidence, including modeling studies, to reduce the costs relating to illness borne by the Brazilian public health system and society.

Simulating future public health benefits of tobacco control interventions: a systematic review of models

BACKGROUND

To prioritise tobacco control interventions, simulating their health impacts is valuable. We undertook a systematic review of tobacco intervention simulation models to assess model structure and input variations that may render model outputs non-comparable.

METHODS

We applied a Medline search with keywords intersecting modelling and tobacco. Papers were limited to those modelling health outputs (eg, mortality, health-adjusted life years), and at least two of cancer, cardiovascular and respiratory diseases. Data were extracted for each simulation model with ≥3 arising papers, including: model type, untimed or with time steps and trends in business-as-usual (BAU) tobacco prevalence and epidemiology.

RESULTS

Of 1911 papers, 186 met the inclusion criteria, including 13 eligible simulation models. The SimSmoke model had the largest number of publications (n=46), followed by Benefits of Smoking Cessation on Outcomes (n=12) and Tobacco Policy Model (n=10). Two of 13 models only estimated deaths averted, 1 had no time steps, 5 had no future trends in BAU tobacco prevalence, 9 had no future trends in BAU disease epidemiology and 7 had no time lags from quitting tobacco to reversal of health harm.

CONCLUSIONS

Considerable heterogeneity exists in simulation models, making outputs substantively non-comparable between models. Ranking of interventions by one model may be valid. However, this may not be true if, for example, interventions that differentially affect age groups (eg, a tobacco-free generation policy vs increased cessation among adults) do not account for plausible future trends. Greater standardisation of model structures and outputs will allow comparison across models and countries, and for comparisons of the impact of tobacco control interventions with other preventive interventions.

Evaluation of the Clinical and Economic Effects of a Primary Care Anchored, Collaborative, Electronic Health Lifestyle Coaching Program in Denmark: Protocol for a Two-Year Randomized Controlled Trial

BACKGROUND

Obesity is linked to a number of chronic health conditions, such as type 2 diabetes, heart disease, and cancer, and weight loss interventions are often expensive. Recent systematic reviews concluded that app and web-based interventions can improve lifestyle behaviors and weight loss at a reasonable cost, but long-term sustainability needs to be demonstrated.

OBJECTIVE

This study protocol is for a 2-year randomized controlled trial that aims to evaluate the clinical and economic effects of a primary care, anchored, collaborative, electronic health (eHealth) lifestyle coaching program (long-term Lifestyle change InterVention and eHealth Application [LIVA] 2.0) in obese participants with and without type 2 diabetes. The program's primary outcome is weight loss. Its secondary outcome is the hemoglobin A1c (HbA1c) level, and its tertiary outcomes are retention rate, quality of life (QOL), and cost effectiveness. Analytically, the focus is on associations of participant characteristics with outcomes and sustainability.

METHODS

We conduct a multicenter trial with a 1-year intervention and 1-year retention. LIVA 2.0 is implemented in municipalities within administrative regions in Denmark, specifically eight municipalities located within the Region of Southern Denmark and two municipalities located within the Capital Region of Denmark. The participants are assessed at baseline and at 6-, 12-, and 24-month follow-ups. Individual data from the LIVA 2.0 platform are combined with clinical measurements, questionnaires, and participants' usage of municipality and health care services. The participants have a BMI ≥30 but ≤45 kg/m2, and 50% of the participants have type 2 diabetes. The participants are randomized in an approximately 60:40 manner, and based on sample size calculations on weight loss and intention-to-treat statistics, 200 participants are randomized to an intervention group and 140 are randomized to a control group. The control group is offered the conventional preventive program of the municipality, and it is compared to the intervention group, which follows the LIVA 2.0 in addition to the conventional preventive program.

RESULTS

The first baseline assessments have been carried out in March 2018, and the 2-year follow-up will be carried out between March 2020 and April 2021. The hypothesis is that the trial results will demonstrate decreased body weight and that the number of patients who show normalization of their HbA1c levels in the intervention group will be much higher than that in the control group. The participants in the intervention group are also expected to show a greater decrease in their use of glucose-lowering medication and a greater improvement in their QOL when compared with the control group. Operational costs are expected to be lower than standard care, and the intervention is expected to be cost-effective.

CONCLUSIONS

This is the first time that an app and web-based eHealth lifestyle coaching program implemented in Danish municipalities will be clinically and economically evaluated. If the LIVA 2.0 eHealth lifestyle coaching program is proven to be effective, there is great potential for decreasing the rates of obesity, diabetes, and related chronic diseases.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03788915; https://clinicaltrials.gov/ct2/show/NCT03788915.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/19172.

NUrse-led COntinuum of care for people with Diabetes and prediabetes (NUCOD) in Nepal: study protocol for a cluster randomized controlled trial

BACKGROUND

The purpose of this study will be to improve diabetes prevention, access to care and advocacy through a novel cost-effective nurse-led continuum of care approach that incorporates diabetes prevention, awareness, screening and management for low-income settings, and furthermore utilizes the endeavor to advocate for establishing a standard diabetes program in Nepal.

METHODS

We will conduct a two-arm, parallel group, stratified cluster randomized controlled trial of the NUrse-led COntinuum of care for people with Diabetes (N1 = 200) and prediabetes (N2 = 1036) (NUCOD) program, with primary care centers (9 outreach centers and 17 government health posts) as a unit of randomization. The NUCOD program will be delivered through the trained diabetes nurses in the community to the intervention group and the outcomes will be compared with the usual treatment group at 6 and 12 months of the intervention. The primary outcome will be the change in glycated hemoglobin (HbA1c) level among diabetes individuals and progression to type 2 diabetes among prediabetes individuals, and implementation outcomes measured using the RE-AIM (reach, effectiveness, adoption, implementation and maintenance) framework. Outcomes will be analyzed on an intention-to-treat basis.

DISCUSSION

The results of this trial will provide information about the effectiveness of the NUCOD program in improving clinical outcomes for diabetes and prediabetes individuals, and implementation outcomes for the organization. The continuum of care model can be used for the prevention and management of diabetes and other noncommunicable diseases within and beyond Nepal with similar context.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT04131257. Registered on 18 October 2019.

Estimated population wide benefits and risks in China of lowering sodium through potassium enriched salt substitution: modelling study

OBJECTIVES

To estimate the effects of nationwide replacement of discretionary salt (used at table or during cooking) with potassium enriched salt substitute on morbidity and death from cardiovascular disease in China.

DESIGN

Modelling study.

SETTING

China.

POPULATION

Adult population in China, and specifically individuals with chronic kidney disease (about 17 million people).

INTERVENTIONS

Comparative risk assessment models were used to estimate the effects of a nationwide intervention to replace discretionary dietary salt with potassium enriched salt substitutes (20-30% potassium chloride). The models incorporated existing data and corresponding uncertainties from randomised trials, the China National Survey of Chronic Kidney Disease, the Global Burden of Disease Study, and the Chronic Kidney Disease Prognosis Consortium.

MAIN OUTCOME MEASURES

Averted deaths from cardiovascular disease, non-fatal events, and disability adjusted life years from a reduction in blood pressure were estimated after implementation of potassium enriched salt substitution. In individuals with chronic kidney disease, additional deaths from cardiovascular disease related to hyperkalaemia from increased intake of potassium were calculated. The net effects on deaths from cardiovascular disease were estimated as the difference and ratio of averted and additional deaths from cardiovascular disease.

RESULTS

Nationwide implementation of potassium enriched salt substitution could prevent about 461 000 (95% uncertainty interval 196 339 to 704 438) deaths annually from cardiovascular disease, corresponding to 11.0% (4.7% to 16.8%) of annual deaths from cardiovascular disease in China; 743 000 (305 803 to 1 273 098) non-fatal cardiovascular events annually; and 7.9 (3.3 to 12.9) million disability adjusted life years related to cardiovascular disease annually. The intervention could potentially produce an estimated 11 000 (6422 to 16 562) additional deaths related to hyperkalaemia in individuals with chronic kidney disease. The net effect would be about 450 000 (183 699 to 697 084) fewer deaths annually from cardiovascular disease in the overall population and 21 000 (1928 to 42 926) fewer deaths in individuals with chronic kidney disease. In deterministic sensitivity analyses, with changes to key model inputs and assumptions, net benefits were consistent in the total population and in individuals with chronic kidney disease, with averted deaths outweighing additional deaths.

CONCLUSIONS

Nationwide potassium enriched salt substitution in China was estimated to result in a substantial net benefit, preventing around one in nine deaths from cardiovascular disease overall. Taking account of the risks of hyperkalaemia, a substantial net benefit was also estimated for individuals with chronic kidney disease.

Modelling the health impact of food taxes and subsidies with price elasticities: The case for additional scaling of food consumption using the total food expenditure elasticity

Background

Food taxes and subsidies are one intervention to address poor diets. Price elasticity (PE) matrices are commonly used to model the change in food purchasing. Usually a PE matrix is generated in one setting then applied to another setting with differing starting consumptions and prices of foods. This violates econometric assumptions resulting in likely mis-estimation of total food consumption. In this paper we demonstrate this problem, canvass possible options for rescaling all consumption after applying a PE matrix, and illustrate the use of a total food expenditure elasticity (TFEe; the expenditure elasticity for all food combined given the policy-induced change in the total price of food). We use case studies of: NZ$2 per 100g saturated fat (SAFA) tax, NZ$0.4 per 100g sugar tax, and a 20% fruit and vegetable (F&V) subsidy.

Methods

We estimated changes in food purchasing using a NZ PE matrix applied conventionally, and then with TFEe adjustment. Impacts were quantified for pre- to post-policy changes in total food expenditure and health adjusted life years (HALYs) for the total NZ population alive in 2011 over the rest of their lifetime using a multistate lifetable model.

Results

Two NZ studies gave TFEe’s of 0.68 and 0.83, with international estimates ranging from 0.46 to 0.90 (except a UK outlier of 0.04). Without TFEe adjustment, total food expenditure decreased with the tax policies and increased with the F&V subsidy–implausible directions of shift given economic theory and the external TFEe estimates. After TFEe adjustment, HALY gains reduced by a third to a half for the two taxes and reversed from an apparent health loss to a health gain for the F&V subsidy. With TFEe adjustment, HALY gains (in 1000’s) were: 1,805 (95% uncertainty interval 1,337 to 2,340) for the SAFA tax; 1,671 (1,220 to 2,269) for the sugar tax; and 953 (453 to 1,308) for the F&V subsidy.

Conclusions

If PE matrices are applied in settings beyond where they were derived, additional scaling is likely required. We suggest that the TFEe is a useful scalar, but we also encourage other researchers to examine this issue and propose alternative options.