Tobacco Use Prevalence and Smoking Cessation Pharmacotherapy Prescription Patterns Among Hospitalized Patients by Medical Specialty

Prescription of Nicotine Replacement Therapy for Hospitalized Tobacco Users

OBJECTIVES

In hospitalized patients, cigarette smoking is linked to increased readmission rates, emergency department visits, and overall mortality. Smoking cessation reduces these risks, but many patients who smoke are unsuccessful in quitting. Nicotine replacement therapy (NRT) is an effective tool that assists patients who smoke with quitting. This study evaluates NRT prescriptions during and after hospitalization at a large health system for patients who smoke.

METHODS

A retrospective cohort study was conducted to determine the number of patients who were prescribed NRT during an inpatient admission and at time of discharge from a network of nine hospitals across South Carolina between January 1, 2019 and January 1, 2023.

RESULTS

This study included 20,757 patients identified as actively smoking with at least one hospitalization during the study period. Of the cohort, 34.9% were prescribed at least one prescription for NRT during their admission to the hospital. Of the patients identified, 12.6% were prescribed NRT upon discharge from the hospital.

CONCLUSIONS

This study identified significantly low rates of NRT prescribed to smokers during hospitalization and at discharge. Although the management of chronic conditions is typically addressed in the outpatient setting, hospitalization may provide an opportunity for patients to initiate health behavior changes. The low rates of prescriptions for NRT present an opportunity to improve tobacco treatment during hospitalization and beyond.

Prevalence of substance use and substance use disorder in medically ill patients: A cross-sectional, hospital-based study from India

Background Untreated co-occurring substance use and substance use disorders (SUDs) in patients with medical conditions may be associated with unfavourable medical outcomes. Understanding the prevalence of substance use and SUDs among patients admitted to hospital for medical illness may help in developing appropriate strategies to manage SUDs in this population and improve the outcomes of medical illness. We assessed the prevalence of substance use and SUDs among patients admitted for medical illnesses and the association between substance use and medical illness. Methods This cross-sectional study was done in an in-patient setting in a multidisciplinary teaching medical institution in India. Using systematic sampling, adult patients admitted in various departments for at least 24 hours were interviewed using standard instruments by psychiatrists trained in the study methodology. Results Two hundred and ninety patients participated. Their mean (SD) age was 42.2 (15.6) years. One hundred and nine participants (37.6%) reported lifetime use of any psychoactive substance, with tobacco being the most common substance used (91, 31.4%), followed by alcohol (69, 23.8%) and cannabis (12, 4.1%). Lifetime alcohol use was significantly associated with diseases of the circulatory system. Lifetime use of any substance or of alcohol, and current use of any substance or tobacco were significantly associated with injuries, poisoning and other consequences of external causes. Conclusions A large proportion of patients hospitalized for medical illness reported the use of psychoactive substances or had SUDs. The use of some of these substances was also associated with injuries as well as diseases of the circulatory system.

Healthcare Providers' Knowledge of Evidence-Based Treatment for Tobacco Dependence, DocStyles 2020

PURPOSE

Although smoking cessation reduces the risk of all-cause mortality, evidence-based cessation treatments are underused. This study examined healthcare provider knowledge of evidence-based cessation treatments and associations between knowledge and clinical practice characteristics.

DESIGN

Cross-sectional survey.

SETTING

2020 DocStyles.

SUBJECTS

1480 U.S. healthcare providers.

MEASURES

Provider knowledge of availability of tobacco use disorder diagnostic criteria, clinical practice guideline availability, treatment efficacy, evidence-based counseling modalities, and medications approved by the U.S. Food and Drug Administration (FDA).

ANALYSIS

Adjusted odds ratios (aORs), adjusted for personal and clinical practice characteristics.

RESULTS

Less than half of respondents demonstrated high knowledge of availability of diagnostic criteria (36.8%), cessation treatment efficacy (33.2%), evidence-based counseling modalities (5.6%), and FDA-approved medications (40.1%). Significant differences were found between specialties: compared to internists, family physicians were less likely to have low knowledge of medications (aOR = .69, 95% CI = .53, .90) and obstetricians/gynecologists were more likely to have low knowledge of medications (aOR = 2.62, 95% CI = 1.82, 3.76). Overall, few associations between knowledge and clinical practice characteristics were identified.

CONCLUSION

Most providers had low knowledge of the topics of interest, with little variation across clinical practice characteristics, indicating room for improvement. Efforts to improve provider knowledge of evidence-based treatments are an important component of a comprehensive approach to improving delivery and use of cessation interventions and increasing tobacco cessation.

Clinical impacts of an integrated electronic health record-based smoking cessation intervention during hospitalisation

OBJECTIVE

To assess the effects of an electronic health record (EHR) intervention that prompts the clinician to prescribe nicotine replacement therapy (NRT) at hospital admission and discharge in a large integrated health system.

DESIGN

Retrospective cohort study using interrupted time series (ITS) analysis leveraging EHR data generated before and after implementation of the 2015 EHR-based intervention.

SETTING

Kaiser Permanente Northern California, a large integrated health system with 4.2 million members.

PARTICIPANTS

Current smokers aged ≥18 hospitalised for any reason.

EXPOSURE

EHR-based clinical decision supports that prompted the clinician to order NRT on hospital admission (implemented February 2015) and discharge (implemented September 2015).

MAIN OUTCOMES AND MEASURES

Primary outcomes included the monthly percentage of admitted smokers with NRT orders during admission and at discharge. A secondary outcome assessed patient quit rates within 30 days of hospital discharge as reported during discharge follow-up outpatient visits.

RESULTS

The percentage of admissions with NRT orders increased from 29.9% in the year preceding the intervention to 78.1% in the year following (41.8% change, 95% CI 38.6% to 44.9%) after implementation of the admission hard-stop intervention compared with the baseline trend (ITS estimate). The percentage of discharges with NRT orders increased acutely at the time of both interventions (admission intervention ITS estimate 15.5%, 95% CI 11% to 20%; discharge intervention ITS estimate 13.4%, 95% CI 9.1% to 17.7%). Following the implementation of the discharge intervention, there was a small increase in patient-reported quit rates (ITS estimate 5.0%, 95% CI 2.2% to 7.8%).

CONCLUSIONS

An EHR-based clinical decision-making support embedded into admission and discharge documentation was associated with an increase in NRT prescriptions and improvement in quit rates. Similar systemic EHR interventions can help improve smoking cessation efforts after hospitalisation.

Assessment of Duration of Smoking Cessation Prior to Surgical Treatment of Non-small Cell Lung Cancer

OBJECTIVE

To define the relationship between the duration of smoking cessation and postoperative complications for patients with lung cancer undergoing surgical treatment.

BACKGROUND

Smoking increases the risk of postoperative morbidity and mortality in patients with lung cancer undergoing surgical treatment. Although smoking cessation before surgery can mitigate these risks, the ideal duration of preoperative smoking cessation remains unclear.

METHODS

Using a uniquely compiled Veterans Health Administration dataset, we performed a retrospective cohort study of patients with clinical stage I non-small cell lung cancer undergoing surgical treatment between 2006 and 2016. We characterized the relationship between duration of preoperative smoking cessation and risk of postoperative complications or mortality within 30-days using multivariable restricted cubic spline functions.

RESULTS

The study included a total of 9509 patients, of whom 6168 (64.9%) were smoking at the time of lung cancer diagnosis. Among them, only 662 (10.7%) patients stopped smoking prior to surgery. Longer duration between smoking cessation and surgery was associated with lower odds of major complication or mortality (adjusted odds ratio [aOR] for every additional week, 0.919; 95% confidence interval [CI], 0.850-0.993; P = 0.03). Compared to nonsmokers, patients who quit at least 3 weeks before surgery had similar odds of death or major complication (aOR, 1.005; 95% CI, 0.702-1.437; P = 0.98) whereas those who quit within 3 weeks of surgery had significantly higher odds of death or major complication (aOR, 1.698; 95% CI, 1.203-2.396; P = 0.003).

CONCLUSION

Smoking cessation at least 3 weeks prior to the surgical treatment of lung cancer is associated with reduced morbidity and mortality. Providers should aggressively encourage smoking cessation in the preoperative period, since it can disproportionately impact outcomes in early-stage lung cancer.

The Impact of Persistent Smoking After Surgery on Long-term Outcomes After Stage I Non-small Cell Lung Cancer Resection

BACKGROUND

Smoking at the time of surgical treatment for lung cancer increases the risk for perioperative morbidity and mortality. The prevalence of persistent smoking in the postoperative period and its association with long-term oncologic outcomes are poorly described.

RESEARCH QUESTION

What is the relationship between persistent smoking and long-term outcomes in early-stage lung cancer after surgical treatment?

STUDY DESIGN AND METHODS

We performed a retrospective cohort study using a uniquely compiled Veterans Health Administration dataset of patients with clinical stage I non-small cell lung cancer (NSCLC) undergoing surgical treatment between 2006 and 2016. We defined persistent smoking as individuals who continued smoking 1 year after surgery and characterized the relationship between persistent smoking and disease-free survival and overall survival.

RESULTS

This study included 7,489 patients undergoing surgical treatment for clinical stage I NSCLC. Of 4,562 patients (60.9%) who were smoking at the time of surgery, 2,648 patients (58.0%) continued to smoke at 1 year after surgery. Among 2,927 patients (39.1%) who were not smoking at the time of surgical treatment, 573 (19.6%) relapsed and were smoking at 1 year after surgery. Persistent smoking at 1 year after surgery was associated with significantly shorter overall survival (adjusted hazard ration [aHR], 1.291; 95% CI, 1.197-1.392; P < .001). However, persistent smoking was not associated with inferior disease-free survival (aHR, 0.989; 95% CI, 0.884-1.106; P = .84).

INTERPRETATION

Persistent smoking after surgery for stage I NSCLC is common and is associated with inferior overall survival. Providers should continue to assess smoking habits in the postoperative period given its disproportionate impact on long-term outcomes after potentially curative treatment for early-stage lung cancer.

Underutilization of guideline-concordant smoking cessation treatments in surgical patients: Lessons from a learning health system

While smoking is a well-established risk factor for surgical complications, it is unclear how frequently guideline-concordant tobacco treatments are prescribed to surgical patients. In this cross-sectional study including 164673 unique patients evaluated in outpatient surgery clinics at a single institution in 2020, despite a relatively high smoking prevalence (14.7%), guideline-concordant treatment rates were very low, with only 12.7% of patients receiving pharmacotherapy and 31.7% receiving any treatment. Addressing disparities in smoking cessation treatments are critical given the disproportionate impact of smoking on surgical outcomes.

Factors associated with changes in inpatients' smoking pattern during hospitalization and one month after discharge: A cohort study

INTRODUCTION

Smokers are frequent users of healthcare services. Admissions to hospital can serve as a "teachable moment" for quitting smoking. Clinical guidelines recommend initiating smoking cessation services during hospitalization; however, in Southern European countries less than 5% of inpatients receive a brief intervention for smoking cessation.

OBJECTIVES

The aims of this study were (i) to examine rates of smoking abstinence during and after hospitalization; (ii) to measure changes in smoking patterns among persons who continued smoking after discharge; and (iii) to identify predictors of abstinence during hospitalization and after discharge.

METHODS

A cohort study of a representative sample of current adult smokers hospitalized in two Spanish and two Portuguese hospitals. We surveyed smokers during hospitalization and recontacted them one month after discharge. We used a 25-item ad hoc questionnaire regarding their smoking pattern, the smoking cessation intervention they have received during hospitalization, and hospital and sociodemographic characteristics. We performed a descriptive analysis using the chi-square test and a multivariate logistic regression to characterize the participant, hospital, and smoking cessation intervention (5As model) characteristics associated with smoking abstinence.

RESULTS

Smoking patients from both countries presented high abstinence rates during hospitalization (Spain: 76.4%; Portugal: 70.2%); however, after discharge, their abstinence rates decreased to 55.3% and 46.8%, respectively. In Spain, smokers who tried to quit before hospital admission showed higher abstinence rates, and those who continued smoking reduced a mean of five cigarettes the number of cigarettes per day (p ≤ 0.001). In Portugal, abstinence rates were higher among women (p = 0.030), those not living with a smoker (p = 0.008), those admitted to medical-surgical wards (p = 0.035), who consumed their first cigarette within 60 min after waking (p = 0.006), and those who were trying to quit before hospitalization (p = 0.043).

CONCLUSIONS

Half of the smokers admitted into the Spanish hospitals are abstinent one month after discharge or have reduced their cigarettes per day. Nevertheless, success rates could be increased by implementing evidence-based tobacco cessation programs at the organizational-level, including post-discharge active quitting smoking support.

CLINICAL RELEVANCE

Three-quarters of the inpatients who smoke remain abstinent during hospitalization and over half achieve to maintain their abstinence or at least reduce their consumption one month after discharge, proving that admission to hospitals is an excellent teachable moment to quit smoking.

Provider and clinical setting characteristics associated with tobacco pharmacotherapy dispensed in the Veterans Health Administration

INTRODUCTION

While initiation rates of tobacco cessation pharmacotherapy have improved both inside and outside the Department of Veteran Affairs (VA), prescribing rates remain low. The objective of this study was to examine correlation of the characteristics of providers, clinics, and facilities with initiation of tobacco cessation pharmacotherapy.

METHODS

This retrospective, observational study used VA outpatient electronic medical record data from federal fiscal year 2011. Logistic regression models estimated the adjusted odds ratio associated with provider characteristics for pharmacotherapy initiation.

RESULTS

For the 639507 veterans who used tobacco, there were 30388 providers caring for them. Younger (p<0.001) and female (p<0.001) providers were more likely to initiate tobacco cessation pharmacotherapy. Compared to physicians, pharmacists were 74% more likely to initiate pharmacotherapy, while all groups of nurses were 5-8% and physicians' assistants were 12% less likely (p<0.001). Compared to those seen in primary care clinics, patients assessed in substance use treatment clinics were 16% more likely to have pharmacotherapy initiated (p<0.001), while those in psychiatry were 10% less likely (p<0.001), and those in outpatient surgery were 39% less likely to initiate pharmacotherapy (p<0.001). Compared to almost all other classes of VA facilities, patients seen in primary care community-based outpatient clinics (CBOCs) were 7-28% more likely to initiate pharmacotherapy (p<0.0001).

CONCLUSIONS

While the VA is at the leading edge of providing tobacco cessation pharmacotherapy, targeting quality improvement efforts towards providers, clinics, and facilities with low prescribing rates will be essential to continue the declining rates of tobacco use among VA patients.

Substance Use Disorder Detection Rates Among Providers of General Medical Inpatients

BACKGROUND

The prevalence of substance use disorders is higher among medical inpatients than in the general population, placing inpatient providers in a prime position to detect these patients and intervene.

OBJECTIVE

To assess provider detection rates of substance use disorders among medical inpatients and to identify patient characteristics associated with detection.

DESIGN

Data drawn from a cluster randomized controlled trial that tested the effectiveness of three distinct implementation strategies for providers to screen patients for substance use disorders and deliver a brief intervention (Clinical Trials.gov : NCT01825057).

PARTICIPANTS

A total of 1076 patients receiving care from 13 general medical inpatient units in a large teaching hospital participated in this study.

MAIN MEASURES

Data sources included patient self-reported questionnaires, a diagnostic interview for substance use disorders, and patient medical records. Provider detection was determined by diagnoses documented in medical records.

KEY RESULTS

Provider detection rates were highest for nicotine use disorder (72.2%) and lowest for cannabis use disorder (26.4%). Detection of alcohol use disorder was more likely among male compared to female patients (OR (95% CI) = 4.0 (1.9, 4.8)). When compared to White patients, alcohol (OR (95% CI) = 0.4 (0.2, 0.6)) and opioid (OR (95% CI) = 0.2 (0.1, 0.7)) use disorders were less likely to be detected among Black patients, while alcohol (OR (95% CI) = 0.3 (0.0, 2.0)) and cocaine (OR (95% CI) = 0.3 (0.1, 0.9)) use disorders were less likely to be detected among Hispanic patients. Providers were more likely to detect nicotine, alcohol, opioid, and other drug use disorders among patients with higher addiction severity (OR (95% CI) = 1.20 (1.08-1.34), 1.62 (1.48, 1.78), 1.46 (1.07, 1.98), 1.38 (1.00, 1.90), respectively).

CONCLUSIONS

Findings indicate patient characteristics, including gender, race, and addiction severity impact rates of provider detection. Instituting formal screening for all substances may increase provider detection and inform treatment decisions.

Factors associated with receipt of the 5As model of brief intervention for smoking cessation among hospitalized patients

BACKGROUND AND AIMS

Guidelines recommend the 5As model of brief intervention for providing smoking cessation support in clinical settings. This study assessed patient and hospital characteristics associated with self-reported receipt of the 5As (ask, advise, assess, assist and arrange).

DESIGN

Multi-center cross-sectional study.

SETTING AND PARTICIPANTS

Adult inpatients (n = 1047) were randomly selected from 13 hospitals in the Barcelona province of Spain in 2014-2015.

MEASUREMENTS

We explored participants' receipt of the 5As through a questionnaire. Given the progressiveness of the 5As, we recoded the fulfillment of the intervention as: A₀ : no intervention; A₁ : ask; A₂ : ask and advise; A₃ : A₂ and assess; A₄ : A₃ and assist; and A₅ : A₄ and arrange a follow-up. We explored patient (e.g. age, sex, comorbidities) and hospital (e.g. type of hospital, unit) characteristics. We adjusted multi-level robust Poisson regression models to estimate the adjusted prevalence ratios (aPR) of the association between the recoded 5As intervention received.

FINDINGS

A total of 60.4% (n = 624) of patients had been asked (A₁ ) about their smoking status. Among smokers, 46.5% (n = 90) were advised (A₂ ), 26.6% (n = 48) assessed (A₃ ) and 4.6% (n = 10) received all the components of the 5As (A₅ ). Middle-aged smokers [aPR = 3.63; 95% confidence interval (CI) = 1.69-7.79] with a respiratory disease (aPR = 2.19; 95% CI = 1.11-4.34) were most likely to have been asked, advised and assessed (A₃ ). The cessation intervention was most frequently performed by physicians.

CONCLUSIONS

In the Barcelona province of Spain, it appears that fewer than half of hospitalized patients who smoke were advised to quit and few received the full 'five As' brief intervention for smoking cessation.

Leverage points to improve smoking cessation treatment in a large tertiary care hospital: a systems-based mixed methods study

OBJECTIVES

To generate system insights on patient and provider levers and strategies that must be activated to improve hospital-based smoking cessation treatment.

DESIGN

Mixed methods study including a series of in-depth group model building sessions, which informed the design of an online survey completed by healthcare providers and a structured interview protocol administered at the bedside to patients who smoke.

SETTING

Large, tertiary care hospital in the Midwestern United States.

PARTICIPANTS

Group model building: 28 healthcare providers and 22 previously-hospitalised patients; Online survey: 308 healthcare providers; Bedside interviews: 205 hospitalised patients.

PRIMARY AND SECONDARY OUTCOME MEASURES

Hypothesis-generating, participatory qualitative methods informed the examination of the following quantitative outcomes: patient interest versus provider perception of patient interest in smoking cessation and treatment; patient-reported receipt versus provider-reported offering of inpatient smoking cessation interventions; and priority ratings of importance and feasibility of strategies to improve treatment.

RESULTS

System insights included patients frequently leaving the floor to smoke, which created major workflow disruption. Leverage points included interventions to reduce withdrawal symptoms, and action ideas included nurse-driven protocols for timely administration of nicotine replacement therapy. Quantitative data corroborated system insights; for instance, 80% of providers reported that patients frequently leave the floor to smoke, leading to safety risks, missed assessments and inefficient use of staff time. Patients reported significantly lower rates of receiving any smoking cessation interventions, compared with provider reports (mean difference=17.4%-33.7%, p<0.001). Although 92% of providers cited patient interest as a key barrier, only 4% of patients indicated no interest in quitting or reducing smoking.

CONCLUSIONS

Engaging hospital providers and patients in participatory approaches to develop an implementation strategy revealed discrepant perceptions of patient interest and frequency of hospital-based treatment for smoking. These findings spurred adoption of standardised point-of-care treatment for cigarette smoking, which remains highly prevalent yet undertreated among hospitalised patients.

A Face-Aging App for Smoking Cessation in a Waiting Room Setting: Pilot Study in an HIV Outpatient Clinic

BACKGROUND

There is strong evidence for the effectiveness of addressing tobacco use in health care settings. However, few smokers receive cessation advice when visiting a hospital. Implementing smoking cessation technology in outpatient waiting rooms could be an effective strategy for change, with the potential to expose almost all patients visiting a health care provider without preluding physician action needed.

OBJECTIVE

The objective of this study was to develop an intervention for smoking cessation that would make use of the time patients spend in a waiting room by passively exposing them to a face-aging, public morphing, tablet-based app, to pilot the intervention in a waiting room of an HIV outpatient clinic, and to measure the perceptions of this intervention among smoking and nonsmoking HIV patients.

METHODS

We developed a kiosk version of our 3-dimensional face-aging app Smokerface, which shows the user how their face would look with or without cigarette smoking 1 to 15 years in the future. We placed a tablet with the app running on a table in the middle of the waiting room of our HIV outpatient clinic, connected to a large monitor attached to the opposite wall. A researcher noted all the patients who were using the waiting room. If a patient did not initiate app use within 30 seconds of waiting time, the researcher encouraged him or her to do so. Those using the app were asked to complete a questionnaire.

RESULTS

During a 19-day period, 464 patients visited the waiting room, of whom 187 (40.3%) tried the app and 179 (38.6%) completed the questionnaire. Of those who completed the questionnaire, 139 of 176 (79.0%) were men and 84 of 179 (46.9%) were smokers. Of the smokers, 55 of 81 (68%) said the intervention motivated them to quit (men: 45, 68%; women: 10, 67%); 41 (51%) said that it motivated them to discuss quitting with their doctor (men: 32, 49%; women: 9, 60%); and 72 (91%) perceived the intervention as fun (men: 57, 90%; women: 15, 94%). Of the nonsmokers, 92 (98%) said that it motivated them never to take up smoking (men: 72, 99%; women: 20, 95%). Among all patients, 102 (22.0%) watched another patient try the app without trying it themselves; thus, a total of 289 (62.3%) of the 464 patients were exposed to the intervention (average waiting time 21 minutes).

CONCLUSIONS

A face-aging app implemented in a waiting room provides a novel opportunity to motivate patients visiting a health care provider to quit smoking, to address quitting at their subsequent appointment and thereby encourage physician-delivered smoking cessation, or not to take up smoking.