A national quitline service and its promotion in the mass media: modelling the health gain, health equity and cost–utility

Nghiem, Nhung; Cleghorn, Christine; Leung, William; Nair, Nisha; Deen, Frederieke S van der; Blakely, Tony; Wilson, Nick

doi:10.1136/tobaccocontrol-2017-053660

Cited by 26 publications

(33 citation statements)

References 24 publications

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“…In modelling health gain and net health system costs we used a well-established Markov macro-simulation model utilizing a multi-state life-table approach: the "BODE 3 Tobacco Model" including probabilistic uncertainty about multiple input parameters [12,[19][20][21][22][23]. This model includes 16 tobacco-related diseases using national data by sex, age and ethnicity for the whole New Zealand population in 2011.…”

Section: Modelling Approachmentioning

confidence: 99%

“…Promotion of smoking cessation using mass media campaigns (and more targeted advertising) has been found to be a cost-effective investment in tobacco control [10,11]. In New Zealand (NZ), such mass media campaigns have also been reported to be cost-effective when promoting the national quitline service [12]. This suggested to us the possible value of promotion of smoking apps as an additional intervention for those smokers not using the quitline.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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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 Māori (Indigenous population) there was 2.8 times the per capita age-standardised QALY gain relative to non-Māori. 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.

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Section: Modelling Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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“…Given these issues, additional RCTs are desirable, especially those measuring quitting out to 12 months and actual costs of recruitment that might likely occur in population roll out. Furthermore, policy-makers need to compare app promotion with other potential tobacco control interventions eg, as per the published league table of tobacco control studies using the BODE 3 Tobacco Model" in Nghiem et al [11] and online [26]. Some of these major interventions (eg, further tax increases, a tobacco-free generation and a sinking lid on supply) would be likely to generate much greater health gain (although they are also typically applied for greater than this five-year intervention, indeed lifelong), as well as accelerating progress to tobacco endgame goals.…”

Section: Discussionmentioning

confidence: 99%

“…In modeling health gain and net health system costs we used a well-established Markov macrosimulation model utilizing a multi-state life-table approach: the "BODE 3 Tobacco Model" including probabilistic uncertainty about multiple input parameters [11,[17][18][19][20][21]. This model includes 16 tobacco-related diseases using national data by sex, age and ethnicity for the whole New Zealand population in 2011.…”

Section: Methodsmentioning

confidence: 99%

“…Promotion of smoking cessation using mass media campaigns (and more targeted advertising) has been found to be a cost-effective investment in tobacco control [9,10]. In New Zealand (NZ), such mass media campaigns have also been reported to be cost-effective when promoting the national quitline service [11]. This suggested to us the possible value of promotion of smoking apps as an additional intervention for those smokers not using the quitline.…”

Section: Introductionmentioning

confidence: 99%

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Mass media promotion of a smartphone smoking cessation app: Modeled health and cost impacts

Nghiem

Leung

Cleghorn

et al. 2018

Preprint

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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.Objective: 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 six months = 2.23 (95%CI: 1.08 to 4.77). Intervention costs were based on NZ mass media promotion data and the NZ cost of attracting a smoker to smoking cessation services ($NZ64 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 Māori (Indigenous population) there was 2.8 times the per capita age-standardized QALYs relative to non-Māori. The intervention was also estimated to be cost-saving to the health system (saving NZ$115, 95%UI: 72.5 million [m] 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 one year. Conclusions:This study provides modelling-level evidence that mass-media promotion of a smartphone app for smoking cessation is likely to generate health gain, reduce ethnic inequalities in health and save health system costs. Nevertheless, there are other tobacco control which generate considerably larger health gains and cost-savings such as raising tobacco taxes.

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A systematic review of economic evaluations of public health interventions targeting alcohol, tobacco, illicit drug use and problematic gambling: Using a case study to assess transferability

et al. 2021

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A national quitline service and its promotion in the mass media: modelling the health gain, health equity and cost–utility

Cited by 26 publications

References 24 publications

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

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

Mass media promotion of a smartphone smoking cessation app: Modeled health and cost impacts

A systematic review of economic evaluations of public health interventions targeting alcohol, tobacco, illicit drug use and problematic gambling: Using a case study to assess transferability

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