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

Scoping review of telehealth use by Indigenous populations from Australia, Canada, New Zealand, and the United States

INTRODUCTION

Telehealth has the potential to address health disparities experienced by Indigenous people, especially in remote areas. This scoping review aims to map and characterize the existing evidence on telehealth use by Indigenous people and explore the key concepts for effective use, cultural safety, and building therapeutic relationships.

METHODS

A search for published and gray literature, written in English, and published between 2000 and 2022 was completed in 17 electronic databases. Two reviewers independently screened retrieved records for eligibility. For included articles, data were extracted, categorized, and analyzed. Synthesis of findings was performed narratively.

RESULTS

A total of 321 studies were included. The most popular type of telehealth used was mHealth (44%), and the most common health focuses of the telehealth interventions were mental health (26%) and diabetes/diabetic retinopathy (13%). Frequently described barriers to effective telehealth use included concerns about privacy/confidentiality and limited internet availability; meanwhile, telehealth-usage facilitators included cultural relevance and community engagement. Although working in collaboration with Indigenous communities was the most frequently reported way to achieve cultural safety, 40% of the studies did not report Indigenous involvement. Finally, difficulty to establish trusting therapeutic relationships was a major concern raised about telehealth, and evidence suggests that having the first visit-in-person is a potential way to address this issue.

CONCLUSION

This comprehensive review identified critical factors to guide the development of culturally-informed telehealth services to meet the needs of Indigenous people and to achieve equitable access and positive health outcomes.

Predicting the risk of diabetes complications using machine learning and social administrative data in a country with ethnic inequities in health: Aotearoa New Zealand

BACKGROUND

In the age of big data, linked social and administrative health data in combination with machine learning (ML) is being increasingly used to improve prediction in chronic disease, e.g., cardiovascular diseases (CVD). In this study we aimed to apply ML methods on extensive national-level health and social administrative datasets to assess the utility of these for predicting future diabetes complications, including by ethnicity.

METHODS

Five ML models were used to predict CVD events among all people with known diabetes in the population of New Zealand, utilizing nationwide individual-level administrative data.

RESULTS

The Xgboost ML model had the best predictive power for predicting CVD events three years into the future among the population with diabetes (N = 145,600). The optimization procedure also found limited improvement in prediction by ethnicity (using area under the receiver operating curve, [AUC]). The results indicated no trade-off between model predictive performance and equity gap of prediction by ethnicity (that is improving model prediction and reducing performance gaps by ethnicity can be achieved simultaneously). The list of variables of importance was different among different models/ethnic groups, for example: age, deprivation (neighborhood-level), having had a hospitalization event, and the number of years living with diabetes.

DISCUSSION AND CONCLUSIONS

We provide further evidence that ML with administrative health data can be used for meaningful future prediction of health outcomes. As such, it could be utilized to inform health planning and healthcare resource allocation for diabetes management and the prevention of CVD events. Our results may suggest limited scope for developing prediction models by ethnic group and that the major ways to reduce inequitable health outcomes is probably via improved delivery of prevention and management to those groups with diabetes at highest need.

Identifying best modelling practices for tobacco control policy simulations: a systematic review and a novel quality assessment framework

BACKGROUND

Policy simulation models (PSMs) have been used extensively to shape health policies before real-world implementation and evaluate post-implementation impact. This systematic review aimed to examine best practices, identify common pitfalls in tobacco control PSMs and propose a modelling quality assessment framework.

METHODS

We searched five databases to identify eligible publications from July 2013 to August 2019. We additionally included papers from Feirman et al for studies before July 2013. Tobacco control PSMs that project tobacco use and tobacco-related outcomes from smoking policies were included. We extracted model inputs, structure and outputs data for models used in two or more included papers. Using our proposed quality assessment framework, we scored these models on population representativeness, policy effectiveness evidence, simulated smoking histories, included smoking-related diseases, exposure-outcome lag time, transparency, sensitivity analysis, validation and equity.

FINDINGS

We found 146 eligible papers and 25 distinct models. Most models used population data from public or administrative registries, and all performed sensitivity analysis. However, smoking behaviour was commonly modelled into crude categories of smoking status. Eight models only presented overall changes in mortality rather than explicitly considering smoking-related diseases. Only four models reported impacts on health inequalities, and none offered the source code. Overall, the higher scored models achieved higher citation rates.

CONCLUSIONS

While fragments of good practices were widespread across the reviewed PSMs, only a few included a 'critical mass' of the good practices specified in our quality assessment framework. This framework might, therefore, potentially serve as a benchmark and support sharing of good modelling practices.

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 Māori (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.

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

Māori households (NZ indigenous population) were significantly poorer (25% less) than non-Māori households in terms of household per capita expenditure. However, our various econometric estimations suggested that, in relative terms, Māori 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 Māori and non-Māori) 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 Māori and non-Māori 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.

•

Alcohol and tobacco are important risk factors for health loss worldwide.

•

National Household Economic Survey data were analysed by ethnicity for New Zealand.

•

Māori households spent more on tobacco and alcoholic drinks, and less on healthcare.

•

The gap due to differences in household characteristics explains most of the budget share gap.

•

Interventions targeting education and employment may help narrow the gaps.

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 (Māori [Indigenous] or non-Māori). 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 Māori and hence reduce health inequities arising from high BMI, assuming that the intervention would be as effective for Māori as it is for non-Māori.

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.

Prescribing Smartphone Apps for Physical Activity Promotion in Primary Care: Modeling Study of Health Gain and Cost Savings

Background

Inadequate physical activity is a substantial cause of health loss worldwide, and this loss is attributable to diseases such as coronary heart disease, diabetes, stroke, and certain forms of cancer.

Objective

This study aims to assess the potential impact of the prescription of smartphone apps in primary care settings on physical activity levels, health gains (in quality-adjusted life years [QALYs]), and health system costs in New Zealand (NZ).

Methods

A proportional multistate lifetable model was used to estimate the change in physical activity levels and predict the resultant health gains in QALYs and health system costs over the remaining life span of the NZ population alive in 2011 at a 3% discount rate.

Results

The modeled intervention resulted in an estimated 430 QALYs gained (95% uncertainty interval 320-550), with net cost savings of 2011 NZ $2.2 million (2011 US $1.5 million) over the remaining life span of the 2011 NZ population. On a per capita basis, QALY gains were generally larger in women than in men and larger in Māori than in non-Māori. The health impact and cost-effectiveness of the intervention were highly sensitive to assumptions on intervention uptake and decay. For example, the scenario analysis with the largest benefits, which assumed a 5-year maintenance of additional physical activity levels, delivered 1750 QALYs and 2011 NZ $22.5 million (2011 US $15.1 million) in cost savings.

Conclusions

The prescription of smartphone apps for promoting physical activity in primary care settings is likely to generate modest health gains and cost savings at the population level in this high-income country. Such gains may increase with ongoing improvements in app design and increased health worker promotion of the apps to patients.

Improving on estimates of the potential relative harm to health from using modern ENDS (vaping) compared to tobacco smoking

BACKGROUND

Although the harm to health from electronic nicotine delivery systems (ENDS) compared to smoked tobacco remains highly uncertain, society and governments still need to know the likely range of the relative harm to inform regulatory policies for ENDS and smoking.

METHODS

We identified biomarkers with specificity of association with different disease groupings e.g., volatile organic compound (VOCs) for chronic obstructive pulmonary disease; and tobacco-specific N´-nitrosamines (TSNAs) and polycyclic aromatic hydrocarbons (PAHs) for all cancers. We conducted a review of recent studies (post January 2017) that compared these biomarkers between people exclusively using ENDS and those exclusively smoking tobacco. The percentage differences in these biomarkers, weighted by study size and adjusted for acrolein from other sources, were used as a proxy for the assumed percentage difference in disease harm between ENDS and smoking. These relative differences were applied to previously modelled estimates of smoking-related health loss (in health-adjusted life-years; HALYs).

RESULTS

The respective relative biomarker levels (ENDS vs smoking) were: 28% for respiratory diseases (five results, three studies); 42% for cancers (five results, four studies); and 35% for cardiovascular (seven results, four studies). When integrated with the HALY impacts by disease, the overall harm to health from ENDS was estimated to be 33% that of smoking.

CONCLUSIONS

This analysis, suggests that the use of modern ENDS devices (vaping) could be a third as harmful to health as smoking in a high-income country setting. But this estimate is based on a limited number of biomarker studies and is best be considered a likely upper level of ENDS risk given potential biases in our method (i.e., the biomarkers used being correlated with more unaccounted for toxicants in smoking compared to with using ENDS).

Examining Equity Effects of Health Interventions in Cost-Effectiveness Analysis: A Systematic Review

OBJECTIVE

This systematic review aims to catalogue and describe published applications of equity-informative cost-effectiveness analysis (CEAs).

METHODS

Following PRISMA guidelines, we searched Medline for English-language, peer-reviewed CEAs published on or before August 2019. We included CEAs that evaluated 2 or more alternatives; explicitly mentioned equity as a consideration or decision-making principle; and applied an equity-informative CEA method to analyze or examine at least 1 equity criterion in an applied CEA. We extracted data on selected characteristics and analyzed reporting quality using the CHEERS checklist.

RESULTS

Fifty-four articles identified through a search and bibliography reviews met the inclusion criteria. All articles were published on or after 2010, with 80% published after 2015. Most studies evaluated primary prevention interventions in disease areas such as cancer, infectious diseases, and cardiovascular disease. Equity impact analysis alone was the most common equity-informative CEA (56%), followed by equity impact analysis with financial protection effects (30%). At least 11 different equity criteria have been used in equity-informative CEAs; socioeconomic status and race/ethnicity were used most frequently. Seventy-eight percent of studies reported finding "greater value" in an intervention after examining its distributional effects.

CONCLUSION

The number of equity-informative CEAs is increasing, and the wide range of equity criteria, diseases, interventions, settings, and populations represented suggests that broad application of these methods is feasible but will require further refinement. Inclusion of equity into CEAs may shift the value of evaluated interventions and can provide crucial additional information for decision makers.

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.

Health Gain, Cost Impacts, and Cost-Effectiveness of a Mass Media Campaign to Promote Smartphone Apps for Physical Activity: Modeling Study

BACKGROUND

Physical activity smartphone apps are a promising strategy to increase population physical activity, but it is unclear whether government mass media campaigns to promote these apps would be a cost-effective use of public funds.

OBJECTIVE

We aimed to estimate the health impacts, costs, and cost-effectiveness of a one-off national mass media campaign to promote the use of physical activity apps.

METHODS

We used an established multistate life table model to estimate the lifetime health gains (in quality-adjusted life years [QALYs]) that would accrue if New Zealand adults were exposed to a one-off national mass media campaign to promote physical activity app use, with a 1-year impact on physical activity, compared to business-as-usual. A health-system perspective was used to assess cost-effectiveness. and a 3% discount rate was applied to future health gains and health system costs.

RESULTS

The modeled intervention resulted in 28 QALYs (95% uncertainty interval [UI] 8-72) gained at a cost of NZ $81,000/QALY (2018 US $59,500; 95% UI 17,000-345,000), over the remaining life course of the 2011 New Zealand population. The intervention had a low probability (20%) of being cost-effective at a cost-effectiveness threshold of NZ $45,000 (US $32,900) per QALY. The health impact and cost-effectiveness of the intervention were highly sensitive to assumptions around the maintenance of physical activity behaviors beyond the duration of the intervention.

CONCLUSIONS

A mass media campaign to promote smartphone apps for physical activity is unlikely to generate much health gain or be cost-effective at the population level. Other investments to promote physical activity, particularly those that result in sustained behavior change, are likely to have greater health impacts.