Dataset Information

Long-Term Cost-Effectiveness of Smoking Cessation Interventions in People With Mental Disorders: A Dynamic Decision Analytical Model.

ABSTRACT:

Objectives

People with mental disorders are more likely to smoke than the general population. The objective of this study is to develop a decision analytical model that estimates long-term cost-effectiveness of smoking cessation interventions in this population.

Methods

A series of Markov models were constructed to estimate average lifetime smoking-attributable inpatient cost and expected quality-adjusted life-years. The model parameters were estimated using a variety of data sources. The model incorporated uncertainty through probabilistic sensitivity analysis using Monte Carlo simulations. It also generated tables presenting incremental cost-effectiveness ratios of the proposed interventions with varying incremental costs and incremental quit rates. We used data from 2 published trials to demonstrate the model's ability to make projections beyond the observational time frame.

Results

The average smoker's smoking-attributable inpatient cost was 3 times higher and health utility was 5% lower than ex-smokers. The intervention in the trial with a statistically insignificant difference in quit rate (19% vs 25%; P=.2) showed a 45% to 49% chance of being cost-effective compared with the control at willingness-to-pay thresholds of £20 000 to £30 000/quality-adjusted life-years. The second trial had a significant outcome (quit rate 35.9% vs 15.6%; P<.001), and the corresponding probability of the intervention being cost-effective was 65%.

Conclusions

This model provides a consistent platform for clinical trials to estimate the potential lifetime cost-effectiveness of smoking cessation interventions for people with mental disorders and could help commissioners direct resources to the most cost-effective programs. However, direct comparisons of results between trials must be interpreted with caution owing to their different designs and settings.

SUBMITTER: Wu Q

PROVIDER: S-EPMC8404974 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Long-Term Cost-Effectiveness of Smoking Cessation Interventions in People With Mental Disorders: A Dynamic Decision Analytical Model.

Wu Qi Q Gilbody Simon S Li Jinshuo J Wang Han-I HI Parrott Steve S

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research 20210603 9

<h4>Objectives</h4>People with mental disorders are more likely to smoke than the general population. The objective of this study is to develop a decision analytical model that estimates long-term cost-effectiveness of smoking cessation interventions in this population.<h4>Methods</h4>A series of Markov models were constructed to estimate average lifetime smoking-attributable inpatient cost and expected quality-adjusted life-years. The model parameters were estimated using a variety of data sour ...[more]

PMID: 34452705

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Project description:AimTo measure the cost-effectiveness of adding text message (TMB), exercise (EB) and abstinent-contingent financial incentive-based (CFIB) stop smoking interventions to standard smoking cessation support for pregnant women in England.DesignModelling cost-effectiveness outcomes by separately adding three cessation interventions to standard cessation care offered to pregnant women in England. English National Health Service Stop Smoking Services (NHS SSS) statistics from 2019 to 2020 were used for estimating the base quit rate. Intervention effectiveness and cost data for interventions were taken from trial reports. Cost-effectiveness was derived using the economics of smoking in pregnancy (ESIP) model from a health service and personal social services perspective. Interventions were compared with each other as well as against standard cessation care.SettingEnglish NHS SSS.Participants/casesA total of 13 799 pregnant women who accessed NHS SSS. Interventions and comparator; comparator: standard stop smoking support comprising behavioural intervention and an offer of nicotine replacement therapy (NRT). Three additive interventions were TMB, EB and CFIB.MeasurementsIncremental cost-effectiveness ratios per quality-adjusted life-years gained for both mothers and offspring over their life-times; return on investment (ROI); and cost-effectiveness acceptability curves (CEACs).FindingsThe addition of any of the interventions compared with standard care alone was preferred, but only significant for the addition of CFIB, with the CEAC suggesting an at least 90% chance of being favoured to standard care alone. When compared against each other CFIB appeared to yield the largest returns, but this was not significant. The estimated ROI for CFIB was £2 [95% confidence interval (CI) = £1-3] in health-care savings for every £1 spent by the NHS on the cessation intervention.ConclusionsFor a health system which currently provides behavioural support and an offer of nicotine replacement therapy as standard stop smoking support for pregnant women, the greatest economic gains would be provided by operating an abstinent-contingent financial incentives scheme alongside this.

Project description:BackgroundPeople with a serious mental illness are more likely to smoke more and to be more dependent smokers than the general population. This may be due to a wide range of factors that could include a common aetiology to both smoking and the illness, self medication, smoking to alleviate adverse effects of medications, boredom in the existing environment, or a combination of these factors. It is important to undertake this review to facilitate improvements in both the health and safety of people with serious mental illness who smoke, and to reduce the overall burden of costs (both financial and health) to the smoker and, eventually, to the taxpayer.ObjectivesTo review the effects of smoking cessation advice for people with serious mental illness.Search methodsWe searched the Cochrane Schizophrenia Group Specialized Trials Register up to 2 April 2015, which is based on regular searches of CENTRAL, BIOSIS, PubMed, MEDLINE, EMBASE, CINAHL, PsycINFO, and trial registries. We also undertook unsystematic searches of a sample of the component databases (BNI, CINHAL, EMBASE, MEDLINE, and PsycINFO), up to 2 April 2015, and searched references of all identified studiesSelection criteriaWe planned to include all randomised controlled trials (RCTs) that focussed on smoking cessation advice versus standard care or comparing smoking cessation advice with other more focussed methods of delivering care or information.Data collection and analysisThe review authors (PK, AC, and DB) independently screened search results but did not identify any trials that fulfilled the inclusion criteria of this review.Main resultsWe did not identify any RCTs that evaluated advice regarding smoking cessation for people with serious mental illness. The excluded studies illustrate that randomisation of packages of care relevant to smokers with serious mental illness is possible.Authors' conclusionsPeople with serious mental illness are more likely to smoke than the general population. Yet we could not find any high quality evidence to guide the smoking cessation advice healthcare professionals pass onto service users. This is an area where trials are possible and needed.

Project description:Background and aimsPeople with severe mental ill health smoke more and suffer greater smoking-related morbidity and mortality. Little is known about the effectiveness of behavioural interventions for smoking cessation in this group. This review evaluated randomized controlled trial evidence to measure the effectiveness of behavioural smoking cessation interventions (both digital and non-digital) in people with severe mental ill health.DesignSystematic review and random-effects meta-analysis. We searched between inception and January 2020 in Medline, EMBASE, PsycINFO, CINAHL, Health Management Information Consortium and CENTRAL databases.Setting and participantsRandomized controlled trials (RCTs) assessing the effects of behavioural smoking cessation and reduction interventions in adults with severe mental ill health, conducted in any country, in either in-patient or community settings and published in English.MeasurementsThe primary outcome was biochemically verified smoking cessation. Smoking reduction and changes in mental health symptoms and body mass index (BMI) were included as secondary outcomes. Narrative data synthesis and meta-analysis were conducted and the quality of included studies was appraised using the risk of bias 2 (RoB2) tool.FindingsWe included 12 individual studies (16 articles) involving 1861 participants. The first meta-analysis (three studies, 921 participants) demonstrated effectiveness of bespoke face-to-face interventions compared with usual care across all time-points [medium-term: relative risk (RR) = 2.29, 95% confidence interval (CI) = 1.38-3.81; long-term: RR = 1.58, 95% CI = 1.09-2.30]. The second (three studies, 275 participants) did not demonstrate any difference in effectiveness of bespoke digital on-line interventions compared with standard digital on-line interventions (medium-term: RR = 0.87, 95% CI = 0.17-4.46). A narrative overview revealed mixed results when comparing bespoke face-to-face interventions with other active interventions. The methodological quality of studies was mixed, with the majority having some concerns mainly around risk of selective reporting.ConclusionsFace-to-face bespoke smoking cessation interventions for adults with severe mental ill health appear to be effective when compared with treatment as usual, but evidence is equivocal when compared with other active interventions. There is limited evidence comparing bespoke digital interventions with generic interventions, and we found no studies comparing them with usual treatment.

Project description:BackgroundLung cancer is one of the most common causes of death from cancer worldwide. Smoking induces and aggravates many health problems, including vascular diseases, respiratory illnesses and cancers. Tobacco smoking constitutes the most important risk factor for lung cancer. Most people with lung cancer are still active smokers at diagnosis or frequently relapse after smoking cessation. Quitting smoking is the most effective way for smokers to reduce the risk of premature death and disability. People with lung cancer may benefit from stopping smoking. Whether smoking cessation interventions are effective for people with lung cancer and whether one method of quitting is more effective than any other has not been systematically reviewed.ObjectivesTo determine the effectiveness of smoking cessation programmes for people with lung cancer.Search methodsWe searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (accessed via PubMed) and Embase up to 22 December 2018. We also searched the American Society of Clinical Oncology (ASCO) Annual Meeting proceedings, the lung cancer sections of the proceedings of the ESMO Congress, the lung cancer sections of the proceedings of the European Conference of Clinical Oncology (ECCO) Congress, the World Conference on Lung Cancer proceedings, the Society for Research on Nicotine and Tobacco Annual Meeting from 2013, the Food and Drug Administration website, the European Medicine Agency for drug registration website, the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) search portal, ClinicalTrials.gov, and the metaRegister of Controlled Trials (mRCT) to 30 December 2018. We applied no restriction on language of publication.Selection criteriaWe planned to include any randomised controlled trial (RCT) of any psychosocial or pharmacological smoking cessation intervention or combinations of both, compared with no intervention, a different psychosocial or pharmacological (or both) intervention or placebo for pharmacological interventions in people with lung cancer.Data collection and analysisTwo review authors independently screened the studies from the initial search for potential trials for inclusion. We planned to use standard methodological procedures expected by Cochrane. We found no trials that met the inclusion criteria.Main resultsWe identified no RCTs that met our inclusion criteria. Among the 1817 records retrieved using our search strategy, we retrieved 19 studies for further investigation. We excluded 15 trials: ten trials because we could not distinguish people with lung cancer from the other participants, or the participants were not people with lung cancer, four because they were not randomised, or RCTs. We excluded one trial because, though it was completed in 2004, no results are available. We assessed four ongoing trials for inclusion when data become available.Authors' conclusionsThere were no RCTs that determined the effectiveness of any type of smoking cessation programme for people with lung cancer. There was insufficient evidence to determine whether smoking cessation interventions are effective for people with lung cancer and whether one programme is more effective than any other. People with lung cancer should be encouraged to quit smoking and offered smoking cessation interventions. However, due to the lack of RCTs, the efficacy of smoking cessation interventions for people with lung cancer cannot be evaluated and concluded. This systematic review identified a need for RCTs to explore these.

Project description:ImportanceGuidelines recommend cancer care clinicians offer smoking cessation treatment. Cost analyses will help stakeholders understand and plan for implementation of cessation programs.ObjectiveTo estimate the incremental cost per quit (ICQ) of adopting an intensive smoking cessation intervention among patients undergoing treatment at cancer care clinics, from a clinic perspective.Design, setting, and participantsThis economic evaluation, a secondary analysis of the Smokefree Support Study (conducted 2013-2018; completed 2021), used microcosting methods and sensitivity analyses to estimate the ICQ of the interventions. Participants included patients undergoing treatment for a broad range of solid tumors and lymphomas who reported current smoking and were receiving care at cancer care clinics within 2 academic medical centers.ExposuresIntensive smoking cessation treatment (up to 11 counseling sessions with free medications), standard of care (up to 4 counseling sessions with medication advice), or usual care (referral to the state quitline).Main outcomes and measuresTotal costs, component-specific costs, and the ICQ of the intensive smoking cessation treatment relative to both standard of care (comparator in the parent randomized trial) and usual care (a common comparator outside this trial) were calculated. Overall and post hoc site-specific estimates are provided. Because usual care was not included in the parent trial, sensitivity analyses were conducted to assess how assumptions about usual care quit rates affected study outcomes (ie, base case [from a published smoking cessation trial among patients with thoracic cancer], best case, and conservative case scenarios).ResultsThe per-patient costs of offering intensive smoking cessation treatment, standard of care, and usual care were $1989, $1482, and $0, respectively. For intensive treatment, the dominant costs were treatment (35%), staff supervision (26%), and patient enrollment (24%). Relative to standard of care, intensive treatment had an overall ICQ of $3906, and one site had an ICQ of $2892. Relative to usual care, intensive treatment had an ICQ of $9866 overall (base case), although at one site, the ICQ was $5408 (base case) and $3786 (best case).Conclusions and relevanceIn this economic evaluation study, implementation of an intensive smoking cessation treatment intervention was moderately to highly cost-effective, depending on existing smoking cessation services in place.

Project description:BackgroundAlthough safe and effective anti-retrovirals (ARVs) are readily available, non-adherence to ARVs is highly prevalent among people living with human immunodeficiency virus/acquired immunodeficiency syndrome (PLWHA). Different adherence-improving interventions have been developed and examined through decision analytic model-based health technology assessments. This systematic review aimed to review and appraise the decision analytical economic models developed to assess ARV adherence-improvement interventions.MethodsThe review protocol was registered on PROSPERO (CRD42022270039), and reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Relevant studies were identified through searches in six generic and specialized bibliographic databases, i.e. PubMed, Embase, NHS Economic Evaluation Database, PsycINFO, Health Economic Evaluations Database, tufts CEA registry and EconLit, from their inception to 23 October 2022. The cost-effectiveness of adherence interventions is represented by the incremental cost-effectiveness ratio (ICER). The quality of studies was assessed using the quality of the health economics studies (QHES) instrument. Data were narratively synthesized in the form of tables and texts. Due to the heterogeneity of the data, a permutation matrix was used for quantitative data synthesis rather than a meta-analysis.ResultsFifteen studies, mostly conducted in North America (8/15 studies), were included in the review. The time horizon ranged from a year to a lifetime. Ten out of 15 studies used a micro-simulation, 4/15 studies employed Markov and 1/15 employed a dynamic model. The most commonly used interventions reported include technology based (5/15), nurse involved (2/15), directly observed therapy (2/15), case manager involved (1/15) and others that involved multi-component interventions (5/15). In 1/15 studies, interventions gained higher quality-adjusted life years (QALYs) with cost savings. The interventions in 14/15 studies were more effective but at a higher cost, and the overall ICER was well below the acceptable threshold mentioned in each study, indicating the interventions could potentially be implemented after careful interpretation. The studies were graded as high quality (13/15) or fair quality (2/15), with some methodological inconsistencies reported.ConclusionCounselling and smartphone-based interventions are cost-effective, and they have the potential to reduce the chronic adherence problem significantly. The quality of decision models can be improved by addressing inconsistencies in model selection, data inputs incorporated into models and uncertainty assessment methods.

Project description:BackgroundSmoking cessation represents an opportunity to reduce both short and long-term effects of smoking on complications after lumbar fusion and smoking-related morbidity and mortality. However, the cost-effectiveness of smoking-cessation interventions prior to lumbar fusion is not fully known.MethodsWe created a decision-analytic Markov model to evaluate the cost-effectiveness of 5 smoking-cessation strategies (behavioral counseling, nicotine replacement therapy [NRT], bupropion or varenicline monotherapy, and a combined intervention) prior to single-level, instrumented lumbar posterolateral fusion (PLF) from the health payer perspective. Probabilities, costs, and utilities were obtained from published sources. We calculated the costs and quality-adjusted life years (QALYs) associated with each strategy over multiple time horizons and accounted for uncertainty with probabilistic sensitivity analyses (PSAs) consisting of 10,000 second-order Monte Carlo simulations.ResultsEvery smoking-cessation intervention was more effective and less costly than usual care at the lifetime horizon. In the short term, behavioral counseling, NRT, varenicline monotherapy, and the combined intervention were also cost-saving, while bupropion monotherapy was more effective but more costly than usual care. The mean lifetime cost savings for behavioral counseling, NRT, bupropion monotherapy, varenicline monotherapy, and the combined intervention were $3,291 (standard deviation [SD], $868), $2,571 (SD, $479), $2,851 (SD, $830), $6,767 (SD, $1,604), and $34,923 (SD, $4,248), respectively. The minimum efficacy threshold (relative risk for smoking cessation) for lifetime cost savings varied from 1.01 (behavioral counseling) to 1.15 (varenicline monotherapy). A PSA revealed that the combined smoking-cessation intervention was always more effective and less costly than usual care.ConclusionsEven brief smoking-cessation interventions yield large short-term and long-term cost savings. Smoking-cessation interventions prior to PLF can both reduce costs and improve patient outcomes as health payers/systems shift toward value-based reimbursement (e.g., bundled payments) or population health models.Level of evidenceEconomic Level II. See Instructions for Authors for a complete description of levels of evidence.

Project description:BackgroundHealthcare professionals, including nurses, frequently advise people to improve their health by stopping smoking. Such advice may be brief, or part of more intensive interventions.ObjectivesTo determine the effectiveness of nursing-delivered smoking cessation interventions in adults. To establish whether nursing-delivered smoking cessation interventions are more effective than no intervention; are more effective if the intervention is more intensive; differ in effectiveness with health state and setting of the participants; are more effective if they include follow-ups; are more effective if they include aids that demonstrate the pathophysiological effect of smoking.Search methodsWe searched the Cochrane Tobacco Addiction Group Specialized Register and CINAHL in January 2017.Selection criteriaRandomized trials of smoking cessation interventions delivered by nurses or health visitors with follow-up of at least six months.Data collection and analysisTwo review authors extracted data independently. The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically-validated rates if available. Where statistically and clinically appropriate, we pooled studies using a Mantel-Haenszel fixed-effect model and reported the outcome as a risk ratio (RR) with a 95% confidence interval (CI).Main resultsFifty-eight studies met the inclusion criteria, nine of which are new for this update. Pooling 44 studies (over 20,000 participants) comparing a nursing intervention to a control or to usual care, we found the intervention increased the likelihood of quitting (RR 1.29, 95% CI 1.21 to 1.38); however, statistical heterogeneity was moderate (I2 = 50%) and not explained by subgroup analysis. Because of this, we judged the quality of evidence to be moderate. Despite most studies being at unclear risk of bias in at least one domain, we did not downgrade the quality of evidence further, as restricting the main analysis to only those studies at low risk of bias did not significantly alter the effect estimate. Subgroup analyses found no evidence that high-intensity interventions, interventions with additional follow-up or interventions including aids that demonstrate the pathophysiological effect of smoking are more effective than lower intensity interventions, or interventions without additional follow-up or aids. There was no evidence that the effect of support differed by patient group or across healthcare settings.Authors' conclusionsThere is moderate quality evidence that behavioural support to motivate and sustain smoking cessation delivered by nurses can lead to a modest increase in the number of people who achieve prolonged abstinence. There is insufficient evidence to assess whether more intensive interventions, those incorporating additional follow-up, or those incorporating pathophysiological feedback are more effective than one-off support. There was no evidence that the effect of support differed by patient group or across healthcare settings.

Dataset Information

Long-Term Cost-Effectiveness of Smoking Cessation Interventions in People With Mental Disorders: A Dynamic Decision Analytical Model.

Objectives

Methods

Results

Conclusions

Publications

Long-Term Cost-Effectiveness of Smoking Cessation Interventions in People With Mental Disorders: A Dynamic Decision Analytical Model.

Similar Datasets

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