Is the provision of a national opt-out tobacco dependence treatment service in acute hospitals in England equitable? A national cohort study

Abstract

Introduction

People who smoke are a third more likely to be admitted to hospital than non-smokers. A disparity in smoking prevalence between the most and least deprived populations persists. Hospital-initiated treatment could reduce smoking-related inequalities if people admitted to hospital from more deprived populations have greater access and uptake of treatment and successfully quit. The National Health Service (NHS) in England has introduced ‘opt-out’ tobacco dependency treatment and in this study, we examined how treatment of tobacco dependency differed in relation to deprivation.

Methods

Data were available from 111 (84%) acute hospital trusts in England, describing 243 847 hospital admissions of people who smoked in 2024, a total of 185 147 individuals. We reviewed whether individuals had made a supported quit attempt and successful quits and used logistic regression to determine if these outcomes differed according to level of deprivation based on patient residence.

Results

Data adjusted for demographic characteristics and hospital clustering demonstrated that the proportion of those making quit attempts was higher in more deprived quintiles of deprivation, 24.8% in quintile 1 (most deprived) versus 18.3% in quintile 5 (least deprived); however, the proportion of people who quit smoking was highest in the least deprived quintile (25.3%) with a gradient to the most deprived quintile (16.0%).

Conclusion

The NHS opt-out inpatient tobacco dependency service provides treatment on an equitable basis across deprivation quintiles, with the greatest proportion of patients making a supported quit attempt in the most deprived quintile. However, there are opportunities to reduce inequalities by improving quit success in this group.

WHAT IS ALREADY KNOWN ON THIS TOPIC

• People who smoke in less advantaged quintiles of deprivation have consistently higher smoking prevalence than those in more advantaged deprivation quintiles, which could be related to poor access to tobacco dependency treatments.

• Opt-out models of treatment provision can offer greater equity of access to treatment leading to more people in less advantaged deprivation quintiles undertaking supported quit attempts and remaining abstinent.

WHAT THIS STUDY ADDS

• Opt-out hospital inpatient treatment of tobacco dependency demonstrated that people in the less advantaged quintiles of deprivation had a sixfold greater number of supported quit attempts and a fourfold greater number of successful quits than those in the more advantaged quintiles of deprivation, but had lower odds of successfully quitting at 4 weeks.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• The opt-out tobacco dependency treatment model for hospital inpatients provides equitable access to treatment and could be expanded to other areas of National Health Service care to close the tobacco-related health inequality gap.

• However, more research is required to optimise quit success for those in less advantaged deprivation quintiles.

Introduction

Smoking remains the single biggest modifiable risk factor for morbidity, mortality and health inequality in England,¹ with some estimates suggesting that up to two-thirds of deaths in current smokers are attributable to smoking.²

In England, 11.6% of the population smokes combustible tobacco with the highest rates of smoking concentrated in populations from routine and manual and long-term unemployed socioeconomic classifications (19.5% and 15.3%, respectively).³ Despite overall smoking prevalence declining over time, the Office of National Statistics suggests that almost a third of people who smoke live within the two most deprived deciles in England,⁴ with some studies suggesting that smoking-related inequalities could actually widen by 2039 without further action.⁵

Smoking tobacco is generally considered the leading risk factor responsible for health inequalities⁶ with one detailed analysis of mortality in England and Wales concluding that 85% of the observed inequalities between socioeconomic groups could be attributed to smoking.⁷ This intrinsic link between smoking and health inequalities is highlighted by the ‘Core20Plus5’ framework⁸ and drives a complex web of multimorbidities, with smoking either causing or exacerbating over 100 clinical conditions including cancer, cardiovascular disease, respiratory disease and mental health conditions.⁹

As such, smoking also has a direct impact on the National Health Service (NHS) in England, with people who smoke 35% more likely to visit their General Practitioners ¹⁰ and 36% more likely to be admitted to hospital¹¹ with approximately 400 000 admissions annually attributable to smoking.¹² It is estimated that the cost of smoking to NHS secondary care in the UK is almost £1 billion, with the highest costs associated with those in the most deprived quintiles of deprivation.⁹

Treating tobacco dependence is a well-evidenced care pathway using both behavioural support techniques and a range of smoking cessation aids.13,15 NHS inpatient settings see higher smoking prevalence rates than among the general population,¹⁶ and there is growing evidence for the effective delivery of tobacco dependence treatment services for admitted patients, although provision of such treatment has historically been poor.^{17 18} Traditionally, people who smoke and are admitted to hospital have been expected to request treatment for tobacco dependency known as an ‘opt-in’ model of care, rather than being provided tobacco dependency treatment automatically, referred to as an ‘opt-out’ approach.¹⁸ The desire of people who smoke to stop smoking is similar across socioeconomic groups; however, access, provision and uptake of effective treatments varies by socioeconomic status and may be exacerbated by ‘opt-in’ models of treatment.^{19 20}

The NHS Long Term Plan (LTP)²¹ is designed to systematically provide opt-out inpatient tobacco dependency treatment equitably across all socioeconomic groups across England, drawing on international and UK models of care.22,24 We analysed data on patients admitted to secondary care inpatient services between 1 January and 31 December 2024, in order to address the following questions:

1. Does deprivation impact on access (measured by commencement of supported quit attempts) to tobacco dependency treatment services in a hospital inpatient setting?

2. Does deprivation impact on the quit success in those supported to commence a quit attempt by hospital inpatient tobacco dependency treatment services?

Research design and methods

Study design

This is a cohort study evaluating the identification and treatment of people who smoke by quintile of deprivation, of a new opt-out NHS Tobacco Dependence Treatment Service for inpatients in England, using prospectively collected national service level data for participants eligible for referral during the specified time period. We followed ‘strengthening the reporting of observational studies in epidemiology’ (STROBE) reporting guidelines.²⁵

Setting

This study examines people who smoke admitted to NHS Acute Care hospitals. Data on admissions in 2024 were reported (to the data collection) by 111 providers of inpatient secondary care (NHS Trusts) representing 84% of eligible trusts.

The NHS has invested new funding into establishing tobacco dependence treatment services for hospital inpatients across England since 2021.²¹ While there is flexibility on how local systems can implement the model of care, it is based on evidence-based care with input from NHS, Office for Health Improvement and Disparities, Public Health and other academic and front-line experts.^{9 22 24} The in-built flexibility is designed to facilitate local adoption and sustainability however, core principles, such as the opt-out identification and treatment of people who smoke in hospitals, dedicated staff trained to National Centre for Smoking Cessation and Training standards, delivery of combined behavioural support and smoking cessation aids were minimum expectations,¹⁵ and recording and reporting of patient-level data including the index of multiple deprivation (IMD) quintile.

The intervention focuses on:

• Systematic identification and recording of smoking status of hospital inpatients alongside brief advice and provision of treatment to avoid withdrawal symptoms postadmission;

• An opt-out referral for an in-depth inpatient consultation with a Tobacco Dependence Adviser (TDA) to support the individual to make an informed choice about quitting smoking;

• Delivery of a personalised treatment plan inclusive of behavioural support techniques and smoking cessation aids; and

• Where appropriate and agreed, ongoing care to continue treatment after leaving hospital, for example, community stop smoking services.

Data sources

The NHS Tobacco Dependence Treatment Programme Patient Level Data (PLD) Collection was used to collect data on all patients admitted to hospital who were eligible for an opt-out referral to the inhouse Tobacco Dependence Treatment Service.²⁶ The data set includes patient characteristics, demographics and details of the patient’s journey through the treatment pathway. Providers are required to populate a patient-level monthly submission form according to a national data specification and associated guidance.²⁷ Data from these submissions were used for these analyses.

The number of hospital inpatient admissions where a smoking status was recorded was obtained, at trust level, from the aggregate section of the NHS Tobacco Dependence Treatment Programme PLD Collection.

Data used in this report has been collected and used in line with NHS England’s purposes as required under the statutory duties outlined in the NHS Act 2006 and Health and Care Act 2022. The data have been disseminated to NHS England under Directions issued under Section 254 of the Health and Care Act 2022 with non-identifiable data processed for publication in line with Annex A of the amended Legal Directions published on 07 January 2022. Utilisation of the Health Research Authority’s decision tool indicates that this work is not research and does not require ethics committee approval.

Participants

Smoking status for patients is recorded on admission. However, this is not universal. Therefore, counts of the number of patients who have their smoking status recorded on admission were collected and used as the denominator for the smoking prevalence calculation.

The main eligibility criteria were being identified as a person who smokes on admission to hospital between 1 January and 31 December 2024. Additionally, only patients admitted with the intention of staying overnight or in an emergency were eligible. Any admissions for maternity or well babies were excluded (using Treatment Function Codes 501 (Obstetrics), 560 (Midwifery service) and 424 (Well babies)). Only patients aged 16 years and over and those who had not died during the hospital spell or the 28-day quit ascertainment date were included.

Records were analysed for whom there were no missing data for age, sex or Lower Super Output Area (LSOA) of Residence (used to derive the IMD quintile). Two records where the patient’s age was recorded as in excess of 115 years were excluded as both outliers and implausible values.

Records that were missing ethnicity were assigned to the unknown ethnicity category for the main analysis and a sensitivity analysis was performed by performing a complete case analysis with missing ethnicity data removed.

Only patients for whom all relevant treatment pathways were present were included in the regression analyses.

As patients could be admitted to hospital inpatient settings multiple times within the study period and to multiple different trusts, only the first admission, during the study period, where a patient was recorded as a current smoker was included in the regression analyses.

Those with any smoking status recorded are used as the denominator for the smoking prevalence calculation

Variables

Exposure

Quintile of deprivation: Deprivation was derived using LSOA (derived from the patient postcode), linked to the deprivation quintile from the English Index of Multiple Deprivation.²⁸ Quintile 1 indicates the most deprived quintile, quintile 5 indicates the least deprived quintile.

Outcomes

1. Whether the patient was seen by the Tobacco Dependence Treatment Service:

   Patients seen were those who had a discussion with a TDA to receive advice and to be able to commence a quit attempt with the ongoing support of the adviser. These patients would have been referred inhouse (not to an external third party) and given a bespoke offer of behavioural support and pharmacotherapy delivered within the NHS service by TDAs.

2. Whether the patient made a supported attempt to quit smoking:

   Supported quit attempts were defined as those where the patient had been seen and agreed on a date to stop smoking and to receive ongoing support from a tobacco dependence service after hospital discharge, for this purpose.²⁶²⁶

3. Whether the quit attempt was successful:

   Quit success was defined according to the National Centre for Smoking Cessation and Training (NCSCT) principle of a self-declaration of ‘not a puff’ over the 28-day duration of the quit attempt, but specifically over the last 14 days.²⁹ For inpatients, the quit attempt was judged to begin on discharge from hospital (when a patient returns to their normal environment and social cues). However, for long-stay inpatients (beyond 28 days), the attempt was judged to start from the date the quit attempt was agreed. Where no outcome was recorded, the patient was considered a current smoker.

Potential confounders

Demographic variables: age, gender and ethnicity. Date of birth at admission was used to derive patients’ age, which was grouped into four broad age bands (18–34 years, 35–44 years, 45–59 years and 60 years and over). Those aged under 18 years were excluded. Gender was recorded as male, female or other. Self-reported ethnicity was categorised as ‘Asian’, ‘Black’, ‘Mixed’, ‘Other’ or ‘White’ with missing ethnicity data categorised as ‘unknown ethnic group’.

Of 111 trusts reporting data in 2024, only 63 (57%) submitted data returns in every month of 2024, indicating a significant but unquantifiable volume of unsubmitted data.

Statistical analyses

Mixed-effects logistic regression analyses were used to assess the relationship between exposures (quintile of deprivation) and outcomes (supported quit attempts and quit success). Exposure was modelled as a categorical variable and outcomes as binary variables. Adjusted models included all potential confounders (age, gender, ethnicity and hospital trust) included as covariates. Potential confounders were included in the model a priori based on clinical judgement without using predictor selection methods. Unadjusted models included the exposure of interest only. Both adjusted and unadjusted regression models included hospital as a random intercept to account for the hierarchical nature of the data, with patients grouped within hospitals. Coefficients are presented as (adjusted) ORs with 95% CIs. Statistical analysis was carried out using R V.4.4.2. Mixed-effects models were performed using the ‘glmer’ function within the ‘lme4’ package V.1.1–37.

Results

At Trusts submitting data to the data collection, between 1 January and 31 December 2024, there were 1537 045 admissions meeting the eligibility criteria. From these, 250 457 (16.3%) were recorded as patients who smoke, that is, smoking prevalence of hospital admissions.

There were 185 195 unique patients recorded as current smokers within the study period (figure 1). Of these, 41 258 (22.3%) made a supported quit attempt, and of those, 8321 (20.2%) quit success was ascertained. Patient characteristics of deprivation quintile, gender, age and ethnicity for people identified as current smokers on admission, those who made a quit attempt and those who successfully quit at 28 days are presented in table 1

Figure 1. Participant data set. LSOA, lower super output area.

Table 1. Patient characteristics at three stages of the Tobacco Dependence Treatment Service pathway (recorded as people who smoke on admission, commencing a quit attempt and making a successful quit attempt).

	Recorded		Commencing a quit attempt		Successful quit attempt
	N	%	N	%	N	%
Total	185 195	100.0%	41 258	100.0%	8321	100.0%
Quintile 1 (most deprived)	72 302	39.0%	17 913	43.4%	2858	34.3%
Quintile 2	43 632	23.6%	9547	23.1%	2083	25.0%
Quintile 3	30 149	16.3%	6319	15.3%	1515	18.2%
Quintile 4	22 982	12.4%	4534	11.0%	1120	13.5%
Quintile 5 (least deprived)	16 130	8.7%	2945	7.1%	745	9.0%
Female	82 027	44.3%	18 319	44.4%	3646	43.8%
Male	103 168	55.7%	22 939	55.6%	4675	56.2%
Age group 18–24 years	8074	4.4%	891	2.2%	117	1.4%
Age group 25–29 years	8453	4.6%	1190	2.9%	204	2.5%
Age group 30–34 years	10 948	5.9%	1760	4.3%	235	2.8%
Age group 35–39 years	12 796	6.9%	2395	5.8%	361	4.3%
Age group 40–44 years	13 984	7.6%	3052	7.4%	474	5.7%
Age group 45–49 years	14 385	7.8%	3444	8.3%	663	8.0%
Age group 50–54 years	18 099	9.8%	4734	11.5%	945	11.4%
Age group 55–59 years	24 061	13.0%	5969	14.5%	1266	15.2%
Age group 60–64 years	20 977	11.3%	5558	13.5%	1280	15.4%
Age group 65–69 years	17 892	9.7%	4639	11.2%	1072	12.9%
Age group 70–74 years	15 050	8.1%	3624	8.8%	804	9.7%
Age group 75–79 years	12 491	6.7%	2716	6.6%	624	7.5%
Age group 80–84 years	6832	3.7%	1195	2.9%	256	3.1%
Age group 90+ years	1153	0.6%	91	0.2%	20	0.2%
Asian or Asian British	5999	3.2%	1665	4.0%	400	4.8%
Black, African, Caribbean or Black British	4398	2.4%	1106	2.7%	232	2.8%
Mixed or multiple ethnic groups	2100	1.1%	565	1.4%	98	1.2%
Other ethnic group	4350	2.3%	989	2.4%	216	2.6%
White	141 413	76.4%	31 411	76.1%	6446	77.5%
Unknown ethnic group	26 935	14.5%	5523	13.4%	929	11.2%

Proportions making a quit attempt (of those recorded as current smokers on admission)

A multiple logistic regression analysis (figure 2 and online supplemental table 1) showed that, when adjusting for demographic characteristics and accounting for clustering by hospital trust, patients that were living in the most deprived quintile had 16.8% higher odds of commencing a quit attempt than those from the least deprived quintile. Quintile 2 had 13.4% higher odds and quintiles 3 and 4, 11.1% and 7.0% higher odds respectively.

Figure 2. Adjusted odds of commencing a supported quit attempt by deprivation quintile.

The number of people who smoke commencing a supported quit attempt out of those identified as smoking on admission was highest in the most deprived quintile (17 913) and decreased with each subsequent quintile (quintile 5=2945), representing an approximate sixfold difference between the most deprived and least deprived deprivation quintiles (figure 3) (online supplemental table 2).

Figure 3. People commencing a supported quit attempt (of those recorded as smoking on admission).

The interclass correlation coefficient (ICC) was 0.887, indicating that there was substantial variation in the baseline number of quit attempts across trusts. Hospitals with more deprived catchment populations are associated with lower proportions making quit attempts.

Proportions making a successful quit attempt

A multiple logistic regression analysis (figure 4 and online supplemental table 3) showed that, when adjusting for demographic characteristics and including hospital trust as the clustering variable, patients who were living in the most deprived quintile had 22.5% lower odds of making a successful quit attempt than those from the least deprived quintile. Those from quintile 2 had 15.6% lower odds to be successful. Those from quintiles 3 and 4 did not have statistically significant odds of being successful.

Figure 4. Adjusted odds of making a successful quit attempt by deprivation quintile.

A fourfold difference was present between the number of successful quitters in people from the most deprived quintile (2858 people) in comparison to the least deprived quintile (745 people), with quintile 1 representing 34.3% of the total number of people who successfully quit (figure 5 and online supplemental table 2)

Figure 5. People successfully quitting after a supported quit attempt.

The ICC was 0.677, indicating that there was substantial variation in the baseline number of successful quit attempts across trusts. Hospitals with more deprived catchment populations are associated with lower proportions of successful quit attempts.

Sensitivity analysis

Sensitivity analysis using complete case ethnicity data showed no changes to the significance of the results in the multiple logistic regression analysis of the proportions making a quit attempt. However, in the same analysis of the proportions making a successful quit attempt, those from IMD quintile 3 were now found to have statistically significant lower odds of being successful than those in IMD quintile 5 (onlinesupplemental tables 4 5).

Discussion

The data presented demonstrate that the new NHS inpatient opt-out tobacco dependency treatment service in England consistently identifies and treats a substantial number of people who smoke, admitted to hospital across all IMD quintiles. Those in the least advantaged quintile of deprivation are more likely to make a quit attempt and have a higher overall number of people who quit; however, there is a lower likelihood of successfully quitting than those in the most advantaged deprivation quintile.

An aspect of the treatment pathway that may have contributed to equitable access and treatment for all patients is the ‘opt-out’ model integral to the NHS LTP pathway, which has demonstrated a more than twofold increase in quit rates compared with opt-in models of care in acute hospital^{22 24} and maternity settings,³⁰ and contrasts with poor uptake of signposting to community Stop Smoking Services identified in a recent study based in an Emergency Department population.³¹ The utilisation of funded, inhouse hospital-based treatment services, which provide immediate access to pharmacotherapy, providing personalised treatment plans by trained TDAs, are necessary components acknowledged by successive national hospital audits,^{16 32 33} that may have driven access and uptake of treatment across all socioeconomic groups. The admission to hospital for acute illness or surgery, inability to smoke while on a hospital ward and uptake of nicotine replacement therapy to counteract nicotine withdrawal may have contributed to greater individual motivation and engagement with TDAs, making a quit attempt equally accessible for all admitted population groups.¹⁷

A feature common to hospital inpatients and community stop smoking services is the lower quit rate of those in the most deprived IMD quintile compared with the least deprived.^{34 35} Several studies have identified factors that may account for this finding, including feelings of stigmatisation, lower self-efficacy, costs of pharmacotherapy, reduced social support for quitting, a greater proportion of friends and family who smoke, lower treatment adherence and stronger addiction to tobacco for people in lower socioeconomic groups.^{19 20 36 37} In addition to the relatively higher service uptake among the more deprived IMD groups, which can compensate for their lower quit rates, measures that have been shown to improve quit rates in lower IMD groups include iterative supported quit attempts, extended courses of pharmacotherapy and behavioural support, and use of text-messaging support postdischarge.38,40

The quit rate of 20.2% for this hospital population was lower than people who actively seek out treatment of tobacco dependency from community stop smoking services,⁴¹ but similar to other hospital-based observational studies of smoking cessation intervention,^{22 24} largely reflecting the difference in population type. However, the size of the hospital inpatient population, combined with a higher smoking prevalence¹¹ than in community settings,³ confers an opportunity to treat a large volume of people with a cost-effective intervention⁴² to reduce health inequality.

The strength of this evaluation is the use of large-volume, high-quality, patient-level data including IMD category, recorded on admission to hospital and subsequently throughout the hospital and community treatment pathway, until a 28-day quit outcome was recorded,²⁷ representing a new and unique national data set not replicated in other jurisdictions. Other data sets in England extrapolate national population survey data to make estimates of smoking prevalence in hospitals and their impact on smoking-related disease or attending community stop smoking services.^{3 15 43}

Limitations of this study include the volume of data not available for evaluation. Approximately 16% of eligible hospitals in England had not reported any data and a further 43% had only submitted partial data for the time period included in this evaluation. This could be as a result of the immaturity of local service implementation, data capture or reporting issues. However, the data set presented used complete pathway data of 185 197 inpatients, with similar demographics to the other national data sets,^{3 16 43} and represents the largest hospital data set reported in the UK to date. Despite the incompleteness of the overall data set, service coverage, the overall volumes of patient and demographic spread will limit bias associated with local prevalence rates or target initiatives focusing on specific population groups.

As shown in figure 1 there were also data completeness issues with a number of the demographic fields required for this analysis, particularly ethnicity. Overall, 6610 records were excluded because age, gender or IMD fields were not populated.

Ascertainment and reporting into the national data collection of smoking status at 28 days after commencing a quit attempt (ie, quit success) should be undertaken by local providers but is frequently incomplete due to difficulty contacting patients or information technology (IT) system incompatibilities between hospital and community providers. Records were not excluded for this reason, but the potential implication is that quit success rates may be higher than reported in this evaluation, as those patients not followed up at 28 days are considered not to have quit. It is unclear whether the missing information is differentially distributed across demographic groups and affects the inequalities analysis. A further limitation is the inability to capture data on people who successfully quit beyond the standard 28-day measurement, which may underestimate quit success as a result of the hospital intervention.

Further limitations were the inability to undertake a qualitative assessment of barriers and enablers of tobacco dependency treatment by IMD category.

To amplify the success of this hospital tobacco dependency treatment pathway addressing tobacco-related health inequality, these data suggest even more could be done to improve quit rates among the most deprived IMD category, for example, by providing more intense, prolonged pharmacotherapy and behavioural support,⁴⁴ using a ‘cut down to quit’⁴⁵ approach for those patients who require a longer period to stop smoking and increasing funding of treatment provision for those in the most deprived IMD group.

To conclude, the NHS opt-out inpatient tobacco dependency service provides tobacco dependency treatment on an equitable basis across IMD quintiles, with the greatest volume of patients treated in the most deprived IMD quintile, and therefore has the potential to reduce health inequality related to smoking.

Data availability statement

Data are available upon reasonable request.