Predicting high health-cost users among people with cardiovascular disease using machine learning and nationwide linked social administrative datasets.

OBJECTIVES: To optimise planning of public health services, the impact of high-cost users needs to be considered. However, most of the existing statistical models for costs do not include many clinical and social variables from administrative data that are associated with elevated health care resource use, and are increasingly available. This study aimed to use machine learning approaches and big data to predict high-cost users among people with cardiovascular disease (CVD). METHODS: We used nationally representative linked datasets in New Zealand to predict CVD prevalent cases with the most expensive cost belonging to the top quintiles by cost. We compared the performance of four popular machine learning models (L1-regularised logistic regression, classification trees, k-nearest neighbourhood (KNN) and random forest) with the traditional regression models. RESULTS: The machine learning models had far better accuracy in predicting high health-cost users compared with the logistic models. The harmony score F1 (combining sensitivity and positive predictive value) of the machine learning models ranged from 30.6% to 41.2% (compared with 8.6-9.1% for the logistic models). Previous health costs, income, age, chronic health conditions, deprivation, and receiving a social security benefit were among the most important predictors of the CVD high-cost users. CONCLUSIONS: This study provides additional evidence that machine learning can be used as a tool together with big data in health economics for identification of new risk factors and prediction of high-cost users with CVD. As such, machine learning may potentially assist with health services planning and preventive measures to improve population health while potentially saving healthcare costs.

Prioritization of intervention domains to prevent cardiovascular disease: a country-level case study using global burden of disease and local data.

AIM: We aimed to combine Global Burden of Disease (GBD) Study data and local data to identify the highest priority intervention domains for preventing cardiovascular disease (CVD) in the case study country of Aotearoa New Zealand (NZ). METHODS: Risk factor data for CVD in NZ were extracted from the GBD using the "GBD Results Tool." We prioritized risk factor domains based on consideration of the size of the health burden (disability-adjusted life years [DALYs]) and then by the domain-specific interventions that delivered the highest health gains and cost-savings. RESULTS: Based on the size of the CVD health burden in DALYs, the five top prioritized risk factor domains were: high systolic blood pressure (84,800 DALYs; 5400 deaths in 2019), then dietary risk factors, then high LDL cholesterol, then high BMI and then tobacco (30,400 DALYs; 1400 deaths). But if policy-makers aimed to maximize health gain and cost-savings from specific interventions that have been studied, then they would favor the dietary risk domain (e.g., a combined fruit and vegetable subsidy plus a sugar tax produced estimated lifetime savings of 894,000 health-adjusted life years and health system cost-savings of US$11.0 billion; both 3% discount rate). Other potential considerations for prioritization included the potential for total health gain that includes non-CVD health loss and potential for achieving relatively greater per capita health gain for Maori (Indigenous) to reduce health inequities. CONCLUSIONS: We were able to show how CVD risk factor domains could be systematically prioritized using a mix of GBD and country-level data. Addressing high systolic blood pressure would be the top ranked domain if policy-makers focused just on the size of the health loss. But if policy-makers wished to maximize health gain and cost-savings using evaluated interventions, dietary interventions would be prioritized, e.g., food taxes and subsidies.

Using household economic survey data to assess food expenditure patterns and trends in a high-income country with notable health inequities.

This study aimed to identify dietary trends in Aotearoa New Zealand (NZ) and whether inequities in dietary patterns are changing. We extracted data from the Household Economic Survey (HES), which was designed to provide information on impacts of policy-making in NZ, and performed descriptive analyses on food expenditures. Overall, total household food expenditure per capita increased by 0.38% annually over this period. Low-income households spent around three quarters of what high-income households spent on food per capita. High-income households experienced a greater increase in expenditure on nuts and seeds and a greater reduction in expenditure on processed meat. There was increased expenditure over time on fruit and vegetables nuts and seeds, and healthy foods in Maori (Indigenous) households with little variations in non-Maori households. But there was little change in processed meat expenditure for Maori households and expenditure on less healthy foods also increased over time. Routinely collected HES data were useful and cost-effective for understanding trends in food expenditure patterns to inform public health interventions, in the absence of nutrition survey data. Potentially positive expenditure trends for Maori were identified, however, food expenditure inequities in processed meat and less healthy foods by ethnicity and income continue to be substantial.

Health promoting and demoting consumption: What accounts for budget share differentials by ethnicity in New Zealand.

Background: Health demoting consumption of alcohol and tobacco are some of the most important risk factors for health loss worldwide, however there is limited information on these consumption risk factors in New Zealand (NZ) and whether inequities in the risk factors are ethnically patterned. Methods: We used three nationally representative Household Economic Survey waves (2006/07, 2009/10, 2012/13) (n = 9030) in NZ to examine household expenditure for key health risk-related components of consumption by ethnicity, and its contributors to the differences using non-parametric, parametric and decomposition methods. Results: Maori households (NZ indigenous population) were significantly poorer (25% less) than non-Maori households in terms of household per capita expenditure. However, our various econometric estimations suggested that, in relative terms, Maori spent more on tobacco and alcohol, and less on healthcare. The gaps become larger at upper quantiles of the budget share distributions; the composition effect (the gap due to differences in individual and household characteristics between Maori and non-Maori) explains most of the tobacco and alcohol budget share gap between the two groups, and less for healthcare. The structure effect (the gap due to returns to/or effect of individual and household characteristics) contributes very little to the budget share gap for tobacco and drink, but increasingly and predominantly when moving along the distribution of healthcare budget share.The differences between Maori and non-Maori in household ownership, education, and income negatively affect budget share on these health demoting consumption (tobacco and alcohol). The household head's age, education, and employment contributed most to the structure effect. Conclusions: Our study suggested ethnic inequities in the health risk consumption behaviour are evidenced in NZ. Interventions targeting education and employment that significantly affect household budget shares on risk factors (i.e., harmful consumption) for health loss may help narrow the gaps.

Potential effect of real-world junk food and sugar-sweetened beverage taxes on population health, health system costs and greenhouse gas emissions in New Zealand: a modelling study.

Poor diet is a major risk factor for excess weight gain and obesity-related diseases, including cardiovascular diseases, type 2 diabetes mellitus, osteoarthritis and several cancers. This paper aims to assess the potential impacts of real-world food and beverage taxes on change in dietary risk factors, health gains (in quality-adjusted life years (QALYs)), health system costs and greenhouse gas (GHG) emissions as if they had all been implemented in New Zealand (NZ). Ten taxes or tax packages were modelled. A proportional multistate life table model was used to predict resultant QALYs and costs over the remaining lifespan of the NZ population alive in 2011, as well as GHG emissions. QALYs ranged from 12.5 (95% uncertainty interval (UI) 10.2 to 15.0; 3% discount rate) per 1000 population for the import tax on sugar-sweetened beverages (SSB) in Palau to 143 (95% UI 118 to 171) per 1000 population for the excise duties on saturated fat, chocolate and sweets in Denmark, while health expenditure savings ranged from 2011 NZ$245 (95% UI 188 to 310; 2020 US$185) per capita to NZ$2770 (95% UI 2140 to 3480; US$2100) per capita, respectively. The modelled taxes resulted in decreases in GHG emissions from baseline diets, ranging from -0.2% for the tax on SSB in Barbados to -2.8% for Denmark's tax package. There is strong evidence for the implementation of food and beverage tax packages in NZ or similar high-income settings.

Can a Greenhouse Gas Emissions Tax on Food also Be Healthy and Equitable? A Systemised Review and Modelling Study from Aotearoa New Zealand.

Policies to mitigate climate change are essential. The objective of this paper was to estimate the impact of greenhouse gas (GHG) food taxes and assess whether such a tax could also have health benefits in Aotearoa NZ. We undertook a systemised review on GHG food taxes to inform four tax scenarios, including one combined with a subsidy. These scenarios were modelled to estimate lifetime impacts on quality-adjusted health years (QALY), health inequities by ethnicity, GHG emissions, health system costs and food costs to the individual. Twenty-eight modelling studies on food tax policies were identified. Taxes resulted in decreased consumption of the targeted foods (e.g., -15.4% in beef/ruminant consumption, N = 12 studies) and an average decrease of 8.3% in GHG emissions (N = 19 studies). The "GHG weighted tax on all foods" scenario had the largest health gains and costs savings (455,800 QALYs and NZD 8.8 billion), followed by the tax-fruit and vegetable subsidy scenario (410,400 QALYs and NZD 6.4 billion). All scenarios were associated with reduced GHG emissions and higher age standardised per capita QALYs for Maori. Applying taxes that target foods with high GHG emissions has the potential to be effective for reducing GHG emissions and to result in co-benefits for population health.

The Cost-effectiveness of a Mass Media Campaign to Promote Smartphone Apps for Weight Loss: Updated Modeling Study.

BACKGROUND: Evidence suggests that smartphone apps can be effective in the self-management of weight. Given the low cost, broad reach, and apparent effectiveness of weight loss apps, governments may seek to encourage their uptake as a tool to reduce excess weight in the population. Mass media campaigns are 1 mechanism for promoting app use. However, the cost and potential cost-effectiveness are important considerations. OBJECTIVE: The aim of our study was to use modeling to assess the health impacts, health system costs, cost-effectiveness, and health equity of a mass media campaign to promote high-quality smartphone apps for weight loss in New Zealand. METHODS: We used an established proportional multistate life table model that simulates the 2011 New Zealand adult population over the lifetime, subgrouped by age, sex, and ethnicity (Maori [Indigenous] or non-Maori). The risk factor was BMI. The model compared business as usual to a one-off mass media campaign intervention, which included the pooled effect size from a recent meta-analysis of smartphone weight loss apps. The resulting impact on BMI and BMI-related diseases was captured through changes in health gain (quality-adjusted life years) and in health system costs. The difference in total health system costs was the net sum of intervention costs and downstream cost offsets because of altered disease rates. An annual discount rate of 3% was applied to health gains and health system costs. Multiple scenarios and sensitivity analyses were conducted, including an equity adjustment. RESULTS: Across the remaining lifetime of the modeled 2011 New Zealand population, the mass media campaign to promote weight loss app use had an estimated overall health gain of 181 (95% uncertainty interval 113-270) quality-adjusted life years and health care costs of -NZ $606,000 (-US $408,000; 95% uncertainty interval -NZ $2,540,000 [-US $1,709,000] to NZ $907,000 [US $610,000]). The mean health care costs were negative, representing overall savings to the health system. Across the outcomes examined in this study, the modeled mass media campaign to promote weight loss apps among the general population would be expected to provide higher per capita health gain for Maori and hence reduce health inequities arising from high BMI, assuming that the intervention would be as effective for Maori as it is for non-Maori. CONCLUSIONS: A modeled mass media campaign to encourage the adoption of smartphone apps to promote weight loss among the New Zealand adult population is expected to yield an overall gain in health and to be cost-saving to the health system. Although other interventions in the nutrition and physical activity space are even more beneficial to health and produce larger cost savings (eg, fiscal policies and food reformulation), governments may choose to include strategies to promote health app use as complementary measures.

Impact of taxes on purchases of close substitute foods: analysis of cross-price elasticities using data from a randomized experiment.

OBJECTIVE: To examine the effects of health-related food taxes on substitution and complementary purchases within food groups, including from unhealthier to healthier alternatives and between brands. METHODS: We used data from a virtual supermarket experiment with data from 4,259 shopping events linked to varying price sets. Substitution or complementary effects within six frequently purchased food categories were analyzed. Products' own- and cross-price elasticities were analyzed using Almost Ideal Demand System models. RESULTS: Overall, 37.5% of cross-price elasticities were significant (p < 0.05) and included values greater than 0.10. Supplementary and complementary effects were particularly found in the dairy, meats and snacks categories. For example, a 1% increase in the price of high saturated fat dairy was associated with a 0.18% (SE 0.06%) increase in purchases of low saturated fat dairy. For name- and home-brand products, significant substitution effects were found in 50% (n = 3) of cases, but only in one case this was above the 0.10 threshold. CONCLUSIONS/POLICY IMPLICATIONS: Given the relatively low own-price elasticities and the limited substitution and complementary effects, relatively high taxes are needed to substantively increase healthy food purchases at the population level. TRIAL REGISTRATION: This study included secondary analyses; the original trial was registered in the Australian New Zealand Clinical Trials Registry ACTRN12616000122459 .

Potential impact of COVID-19 related unemployment on increased cardiovascular disease in a high-income country: Modeling health loss, cost and equity.

BACKGROUND: Cardiovascular disease (CVD) is a leading cause of health loss and health sector economic burdens in high-income countries. Unemployment is associated with increased risk of CVD, and so there is concern that the economic downturn associated with the COVID-19 pandemic will increase the CVD burden. AIMS: This modeling study aimed to quantify potential health loss, health cost burden and health inequities among people with CVD due to additional unemployment caused by COVID-19 pandemic-related economic disruption in one high-income country: New Zealand (NZ). METHODS: We adapted an established and validated multi-state life-table model for CVD in the national NZ population. We modeled indirect effects (ie, higher CVD incidence due to high unemployment rates) for various scenarios of pandemic-related unemployment projections from the NZ Treasury. RESULTS: We estimated the potential CVD-related heath loss in NZ to range from 23,300 to 36,900 health-adjusted life years (HALYs) for the different unemployment scenarios. Health inequities would be increased with the per capita health loss for Maori (Indigenous population) estimated to be 3.7 times greater than for non-Maori (49.9 vs 13.5 HALYs lost per 1000 people). The estimated additional health system costs ranged between (NZ$303 million [m] to 503m in 2019 values; or US$209m to 346m). CONCLUSIONS AND POLICY IMPLICATIONS: Unemployment due to the COVID-19 pandemic could cause significant health loss, increase health inequities from CVD, and impose additional health system costs in this high-income country. Prevention measures should be considered by governments to reduce this risk, including additional job creation programs and measures directed towards the primary prevention of CVD.

Should prioritising health interventions be informed by modelling studies? The case of cancer control in Aotearoa New Zealand.

In this viewpoint, we suggest that policymakers should prioritise health interventions by using evidence around health gain, impact on equity, health-system costs and cost-effectiveness. We take the example of the new cancer control agency in New Zealand, Te Aho o Te Kahu, and argue that its decision-making can now be informed by many methodologically compatible epidemiological and health economic analyses. These analyses span primary prevention of cancer (eg, tobacco control, dietary and physical activity interventions and HPV vaccination), cancer screening, cancer treatment and palliative care. The largest health gain and cost-savings from the available modelling work for New Zealand are seen in nutrition and tobacco control interventions in particular. Many of these interventions have potentially greater per capita health gain for Maori than non-Maori and are also found to be cost saving for the health sector. In summary, appropriate prioritisation of interventions can potentially both maximise health benefits as well as making best use of government funding of the health system.

Increased unemployment from the COVID-19 pandemic, what might be the adverse impacts on cardiovascular disease in Aotearoa/New Zealand and how might this be prevented?

Despite success with eliminating the COVID-19 pandemic in Aotearoa New Zealand (at least to early August 2020), the response to the pandemic threat has resulted in a range of negative social and economic impacts, including job losses. Understanding the health consequences of these impacts will be increasingly important in the 'recovery' phase. This article contributes to this understanding by exploring the relationship between unemployment and cardiovascular disease (CVD)-a major contributor to health loss in Aotearoa New Zealand. We reviewed the literature about the impact of unemployment on CVD. The totality of the evidence suggested that increased unemployment arising from economic shocks is associated with increased CVD incidence, particularly for middle-aged men. Continued monitoring and active policy responses are required to prevent increases in CVD (and other health outcomes) as a result of the COVID-19 pandemic response. For example, quantifying the CVD-related health loss from pandemic-associated unemployment, along with the health costs and impact on health inequalities, could help with government decision-making to reduce CVD burdens. This could be via intensifying tobacco control, regulating the food supply (eg, to reduce salt/sodium levels), and improving uptake of CVD preventive medications such as statins and anti-hypertensives.

The effect of food taxes and subsidies on population health and health costs: a modelling study.

BACKGROUND: One possible policy response to the burden of diet-related disease is food taxes and subsidies, but the net health gains of these approaches are uncertain because of substitution effects between foods. We estimated the health and cost impacts of various food taxes and subsidies in one high-income country, New Zealand. METHODS: In this modelling study, we compared the effects in New Zealand of a 20% fruit and vegetable subsidy, of saturated fat, sugar and salt taxes (each set at a level that increased the total food price by the same magnitude of decrease from the fruit and vegetable subsidy), and of an 8% so-called junk food tax (on non-essential, energy-dense food). We modelled the effect of price changes on food purchases, the consequent changes in fruit and vegetable and sugar-sweetened beverage purchasing, nutrient risk factors, and body-mass index, and how these changes affect health status and health expenditure. The pre-intervention intake for 340 food groups was taken from the New Zealand National Nutrition Survey and the post-intervention intake was estimated using price and expenditure elasticities. The resultant changes in dietary risk factors were then propagated through a proportional multistate lifetable (with 17 diet-related diseases) to estimate the changes in health-adjusted life years (HALYs) and health system expenditure over the 2011 New Zealand population's remaining lifespan. FINDINGS: Health gains (expressed in HALYs per 1000 people) ranged from 127 (95% uncertainty interval 96-167; undiscounted) for the 8% junk food tax and 212 (102-297) for the fruit and vegetable subsidy, up to 361 (275-474) for the saturated fat tax, 375 (272-508) for the salt tax, and 581 (429-792) for the sugar tax. Health expenditure savings across the remaining lifespan per capita (at a 3% discount rate) ranged from US$492 (334-694) for the junk food tax to $2164 (1472-3122) for the sugar tax. INTERPRETATION: The large magnitude of the health gains and cost savings of these modelled taxes and subsidies suggests that their use warrants serious policy consideration. FUNDING: Health Research Council of New Zealand.

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.

Health benefits and costs of weight-loss dietary counselling by nurses in primary care: a cost-effectiveness analysis.

OBJECTIVE: We aimed to estimate the cost-effectiveness of brief weight-loss counselling by dietitian-trained practice nurses, in a high-income-country case study. DESIGN: A literature search of the impact of dietary counselling on BMI was performed to source the 'best' effect size for use in modelling. This was combined with multiple other input parameters (e.g. epidemiological and cost parameters for obesity-related diseases, likely uptake of counselling) in an established multistate life-table model with fourteen parallel BMI-related disease life tables using a 3 % discount rate. SETTING: New Zealand (NZ). PARTICIPANTS: We calculated quality-adjusted life-years (QALY) gained and health-system costs over the remainder of the lifespan of the NZ population alive in 2011 (n 4·4 million). RESULTS: Counselling was estimated to result in an increase of 250 QALY (95 % uncertainty interval -70, 560 QALY) over the population's lifetime. The incremental cost-effectiveness ratio was 2011 $NZ 138 200 per QALY gained (2018 $US 102 700). Per capita QALY gains were higher for Maori (Indigenous population) than for non-Maori, but were still not cost-effective. If willingness-to-pay was set to the level of gross domestic product per capita per QALY gained (i.e. 2011 $NZ 45 000 or 2018 $US 33 400), the probability that the intervention would be cost-effective was 2 %. CONCLUSIONS: The study provides modelling-level evidence that brief dietary counselling for weight loss in primary care generates relatively small health gains at the population level and is unlikely to be cost-effective.

Preventive Pharmacotherapy for Cardiovascular Disease: A Modelling Study Considering Health Gain, Costs, and Cost-Effectiveness when Stratifying by Absolute Risk.

Cardiovascular disease (CVD) is the leading cause of death internationally. We aimed to model the impact of CVD preventive double therapy (a statin and anti-hypertensive) by clinician-assessed absolute risk level. An established and validated multi-state life-table model for the national New Zealand (NZ) population was adapted. The new version of the model specifically considered the 60-64-year-old male population which was stratified by risk using a published NZ-specific CVD risk equation. The intervention period of treatment was for five years, but a lifetime horizon was used for measuring benefits and costs (a five-year horizon was also implemented). We found that for this group offering double therapy was highly cost-effective in all absolute risk categories (eg, NZ$1580 per QALY gained in the >20% in 5 years risk stratum; 95%UI: Dominant to NZ$3990). Even in the lowest risk stratum (≤5% risk in 5 years), the cost per QALY was only NZ$25,500 (NZ$28,200 and US$19,100 in 2018). At an individual level, the gain for those who responded to the screening offer and commenced preventive treatment ranged from 0.6 to 4.9 months of quality-adjusted life gained (or less than a month gain with a five-year horizon). Nevertheless, at the individual level, patient considerations are critical as some people may decide that this amount of average health gain does not justify taking daily medication.

The effect of food price changes on consumer purchases: a randomised experiment.

BACKGROUND: Most evidence on health-related food taxes and subsidies relies on observational data and effects on single nutrients or foods instead of total diet. The aim of this study was to measure the effect of randomly assigned food price variations on consumer purchasing, where sets of prices emulated commonly discussed food tax and subsidy policies, including a subsidy on fruit and vegetables, a sweetened beverage tax, and taxes on foods according to sugar, sodium, and saturated fat content. METHODS: In this study, adult participants (≥18 years) in New Zealand completed up to five weekly shops in a virtual supermarket. Each shopping occasion was randomly allocated to control (no change in prices) or one or more pricing options simulating the following: a fruit and vegetable subsidy (20%), a sweetened beverage tax (20% or 40%), a saturated fat tax (NZ$2 per 100 g or $4 per 100 g saturated fat), a salt tax ($0·02 per 100 mg or $0·04 per 100 mg sodium), or sugar tax ($0·40 per 100 g or $0·80 per 100 g sugar). The primary outcome was the healthiness of the total shopping basket for each weekly shop (% of total unit food items defined as healthy). Low and high price change options were combined in analyses (eg, results for a saturated fat tax are an average of $2 per 100 g or $4 per 100 g). FINDINGS: Between Feb 1, and Dec 1, 2016, we randomly assigned 1132 shoppers, of whom 1038 (91·7%) completed at least one shop and 743 (71·6%) completed all five shops. Overall, data from 4258 shops were included in the analysis, including 645 control shops, 2545 shops where one policy was activated, and 1068 shops with two (or more) policies activated. In the control condition, 67·90% (SD 13·01) of food purchases were classified as healthy. Three of the five policies increased this proportion by a small, but significant amount (saturated fat tax mean absolute difference 1·77%, 95% CI 1·03 to 2·52, p<0·0001; sugar tax 1·09%, 0·26 to 1·91, p=0·0099; and salt tax 1·31%, 0·50 to 2·13, p=0·0016). The sweetened beverage tax and fruit and vegetable subsidy resulted in non-significant increases of 0·18% (95% CI -0·49 to 0·85, p=0·60) and 0·41% (-0·26 to 1·07, p=0·23), respectively. Both the saturated fat tax and salt tax resulted in the following important substitution effects: an increase in fruit and vegetable purchases as a percentage by weight of all food purchases (saturated fat tax 4·0%, 0·9 to 7·1; salt tax 4·3%, 0·9 to 7·7); but also an increase in sugar as a percentage of total energy (saturated fat tax 5·0%, 2·1 to 7·9; salt tax 3·2%, 0·0 to 6·5). Interaction terms for combined policies were mostly non-significant, consistent with additive effects of policy combinations. INTERPRETATION: Price changes representing saturated fat, sugar, and salt taxes increased total healthy food purchases. As we observed important substitution effects, a combination of different tax and subsidy policies might be the most effective way to improve diets and decrease diet-related chronic diseases. FUNDING: Health Research Council of New Zealand.

Can cost-effectiveness results be combined into a coherent league table? Case study from one high-income country.

BACKGROUND: Doubts exist around the value of compiling league tables for cost-effectiveness results for health interventions, primarily due to methods differences. We aimed to determine if a reasonably coherent league table could be compiled using published studies for one high-income country: New Zealand (NZ). METHODS: Literature searches were conducted to identify NZ-relevant studies published in the peer-reviewed journal literature between 1 January 2010 and 8 October 2017. Only studies with the following metrics were included: cost per quality-adjusted life-year or disability-adjusted life-year or life-year (QALY/DALY/LY). Key study features were abstracted and a summary league table produced which classified the studies in terms of cost-effectiveness. RESULTS: A total of 21 cost-effectiveness studies which met the inclusion criteria were identified. There were some large methodological differences between the studies, particularly in the time horizon (1 year to lifetime) but also discount rates (range 0 to 10%). Nevertheless, we were able to group the incremental cost-effectiveness ratios (ICERs) into general categories of being reported as cost-saving (19%), cost-effective (71%), and not cost-effective (10%). The median ICER (adjusted to 2017 NZ$) was ~ $5000 per QALY/DALY/LY (~US$3500). However, for some interventions, there is high uncertainty around the intervention effectiveness and declining adherence over time. CONCLUSIONS: It seemed possible to produce a reasonably coherent league table for the ICER values from different studies (within broad groupings) in this high-income country. Most interventions were cost-effective and a fifth were cost-saving. Nevertheless, study methodologies did vary widely and researchers need to pay more attention to using standardised methods that allow their results to be included in future league tables.

Mass media promotion of a smartphone smoking cessation app: modelled health and cost-saving impacts.

BACKGROUND: Smartphones are increasingly available and some high quality apps are available for smoking cessation. However, the cost-effectiveness of promoting such apps has never been studied. We therefore aimed to estimate the health gain, inequality impacts and cost-utility from a five-year promotion campaign of a smoking cessation smartphone app compared to business-as-usual (no app use for quitting). METHODS: A well-established Markov macro-simulation model utilising a multi-state life-table was adapted to the intervention (lifetime horizon, 3% discount rate). The setting was the New Zealand (NZ) population (N = 4.4 million). The intervention effect size was from a multi-country randomised trial: relative risk for quitting at 6 months = 2.23 (95%CI: 1.08 to 4.77), albeit subsequently adjusted to consider long-term relapse. Intervention costs were based on NZ mass media promotion data and the NZ cost of attracting a smoker to smoking cessation services (NZ$64 per person). RESULTS: The five-year intervention was estimated to generate 6760 QALYs (95%UI: 5420 to 8420) over the remaining lifetime of the population. For Maori (Indigenous population) there was 2.8 times the per capita age-standardised QALY gain relative to non-Maori. The intervention was also estimated to be cost-saving to the health system (saving NZ$115 million [m], 95%UI: 72.5m to 171m; US$81.8m). The cost-saving aspect of the intervention was maintained in scenario and sensitivity analyses where the discount rate was doubled to 6%, the effect size halved, and the intervention run for just 1 year. CONCLUSIONS: This study provides modelling-level evidence that mass-media promotion of a smartphone app for smoking cessation could generate health gain, reduce ethnic inequalities in health and save health system costs. Nevertheless, there are other tobacco control measures which generate considerably larger health gains and cost-savings such as raising tobacco taxes.

Health Benefits and Cost-Effectiveness From Promoting Smartphone Apps for Weight Loss: Multistate Life Table Modeling.

BACKGROUND: Obesity is an important risk factor for many chronic diseases. Mobile health interventions such as smartphone apps can potentially provide a convenient low-cost addition to other obesity reduction strategies. OBJECTIVE: This study aimed to estimate the impacts on quality-adjusted life-years (QALYs) gained and health system costs over the remainder of the life span of the New Zealand population (N=4.4 million) for a smartphone app promotion intervention in 1 calendar year (2011) using currently available apps for weight loss. METHODS: The intervention was a national mass media promotion of selected smartphone apps for weight loss compared with no dedicated promotion. A multistate life table model including 14 body mass index-related diseases was used to estimate QALYs gained and health systems costs. A lifetime horizon, 3% discount rate, and health system perspective were used. The proportion of the target population receiving the intervention (1.36%) was calculated using the best evidence for the proportion who have access to smartphones, are likely to see the mass media campaign promoting the app, are likely to download a weight loss app, and are likely to continue using this app. RESULTS: In the base-case model, the smartphone app promotion intervention generated 29 QALYs (95% uncertainty interval, UI: 14-52) and cost the health system US $1.6 million (95% UI: 1.1-2.0 million) with the standard download rate. Under plausible assumptions, QALYs increased to 59 (95% UI: 27-107) and costs decreased to US $1.2 million (95% UI: 0.5-1.8) when standard download rates were doubled. Costs per QALY gained were US $53,600 for the standard download rate and US $20,100 when download rates were doubled. On the basis of a threshold of US $30,000 per QALY, this intervention was cost-effective for Maori when the standard download rates were increased by 50% and also for the total population when download rates were doubled. CONCLUSIONS: In this modeling study, the mass media promotion of a smartphone app for weight loss produced relatively small health gains on a population level and was of borderline cost-effectiveness for the total population. Nevertheless, the scope for this type of intervention may expand with increasing smartphone use, more easy-to-use and effective apps becoming available, and with recommendations to use such apps being integrated into dietary counseling by health workers.

Impact of five tobacco endgame strategies on future smoking prevalence, population health and health system costs: two modelling studies to inform the tobacco endgame.

OBJECTIVE: There is growing international interest in advancing 'the tobacco endgame'. We use New Zealand (Smokefree goal for 2025) as a case study to model the impacts on smoking prevalence (SP), health gains (quality-adjusted life-years (QALYs)) and cost savings of (1) 10% annual tobacco tax increases, (2) a tobacco-free generation (TFG), (3) a substantial outlet reduction strategy, (4) a sinking lid on tobacco supply and (5) a combination of 1, 2 and 3. METHODS: Two models were used: (1) a dynamic population forecasting model for SP and (2) a closed cohort (population alive in 2011) multistate life table model (including 16 tobacco-related diseases) for health gains and costs. RESULTS: All selected tobacco endgame strategies were associated with reductions in SP by 2025, down from 34.7%/14.1% for Maori (indigenous population)/non-Maori in 2011 to 16.0%/6.8% for tax increases; 11.2%/5.6% for the TFG; 17.8%/7.3% for the outlet reduction; 0% for the sinking lid; and 9.3%/4.8% for the combined strategy. Major health gains accrued over the remainder of the 2011 population's lives ranging from 28 900 QALYs (95% Uncertainty Interval (UI)): 16 500 to 48 200; outlet reduction) to 282 000 QALYs (95%UI: 189 000 to 405 000; sinking lid) compared with business-as-usual (3% discounting). The timing of health gain and cost savings greatly differed for the various strategies (with accumulated health gain peaking in 2040 for the sinking lid and 2070 for the TFG). CONCLUSIONS: Implementing endgame strategies is needed to achieve tobacco endgame targets and reduce inequalities in smoking. Given such strategies are new, modelling studies provide provisional information on what approaches may be best.