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

ABSTRACT: 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.

SUBMITTER: Ramsey AT

PROVIDER: S-EPMC6609123 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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

Ramsey Alex T AT Prentice Donna D Ballard Ellis E Chen Li-Shiun LS Bierut Laura J LJ

BMJ open 20190702 7

<h4>Objectives</h4>To generate system insights on patient and provider levers and strategies that must be activated to improve hospital-based smoking cessation treatment.<h4>Design</h4>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.<h4>Setting</h4>Large, tertiary care hospital in the Midwestern Uni ...[more]

PMID: 31270124

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Project description:People who smoke make up a significant number of those admitted to hospital (NICE 2014). Being admitted to hospital can present a unique opportunity to attempt to stop smoking. Many smokers find quitting very difficult (Rigotti et al 2007), in large part due to them living and working in environments that contain many cues and triggers associated with nicotine consumption and smoking behaviours. Hospitals generally do not contain such environmental prompts to smoke. In the community, smokers have access to numerous types of support including GP's, pharmacies and Stop Smoking Services (SSS). Once admitted to hospital access to such support is significantly diminished. Given that many patients may be highly motivated to attempt to stop smoking due to heightened concerns about their health and being in an environment not associated with their smoking habits, it seems prudent to ensure there is access to all the levels of smoking cessation support available outside of the hospital. Not providing such support neglects implementing an evidence based, cost-effective health intervention in a major health setting (NICE 2014). A SSS pathway was designed that enabled existing hospital healthcare staff to be trained to identify patients that smoke, ask if the patient is considering quitting or abstaining whilst in hospital. If motivated to quit or abstain, to complete an assessment. This being based around dependence to nicotine and motivation to quit. Access to all available stop smoking medications should be included. Medication should only be provided alongside some level of motivational support up to discharge. Training core staff was felt to be the best option. They are available outside of office hours and access hospital systems such as pharmacy more readily than satellite staff. On discharge the patient is 'handed over' to SSS for continued contact and support once at home. Over 200 staff are trained to complete the assessment and support inpatients to stop or abstain. Approximately 30-35 referrals are made to the local SSS each month, the quit rate at 4 weeks averaging around 40-45%. Most referrals are seen from cardiology and respiratory. All hospital departments should identify staff to be trained to offer cessation support to their patients .

Project description:BackgroundConsidering the values and preferences of individuals who attempt to quit smoking is a crucial step in the development of smoking cessation technologies. This study aimed to explore preferences regarding smart smoking cessation technologies.MethodsThis parallel convergent mixed-methods study was conducted in two phases: quantitative and qualitative. In the quantitative phase, a cross-sectional study was conducted with 360 participants selected through stratified random sampling from technology-based smoking cessation clinics in Tabriz, Tehran, and Karaj cities in Iran. Data on demographic characteristics and preferences for smart smoking cessation technologies were collected using questionnaires and analyzed using descriptive statistics. In the qualitative phase, 25 users of these technologies were selected through purposeful and snowball sampling. The data were gathered through in-depth semistructured interviews and analyzed using qualitative content analysis with a conventional approach. Quantitative and qualitative data were integrated using the merging strategy and convergence model.ResultsThe quantitative phase results indicated that the highest preference was related to wearing and using a smartwatch for smoking cessation and using mobile apps. In the qualitative phase, 17 subcategories were extracted and classified into 8 main categories: high effectiveness, better management of the smoking cessation process, personalized technology, safe and uncomplicated technologies, attractiveness and innovative design, scientific basis, mobile applications, and smart monitoring devices.ConclusionBy combining and integrating quantitative and qualitative results, it can be concluded that users are more interested in wearable technologies and interactive mobile applications. The findings of this study can assist smoking cessation technology developers in designing and improving their tools based on user needs and preferences to enhance their effectiveness and acceptability.

Project description:BackgroundA major cause of lapse and relapse to smoking during a quit attempt is craving triggered by cues from a smoker's immediate environment. To help smokers address these cue-induced cravings when attempting to quit, we have developed a context-aware smoking cessation app, Q Sense, which uses a smoking episode-reporting system combined with location sensing and geofencing to tailor support content and trigger support delivery in real time.ObjectiveWe sought to (1) assess smokers' compliance with reporting their smoking in real time and identify reasons for noncompliance, (2) assess the app's accuracy in identifying user-specific high-risk locations for smoking, (3) explore the feasibility and user perspective of geofence-triggered support, and (4) identify any technological issues or privacy concerns.MethodsAn explanatory sequential mixed-methods design was used, where data collected by the app informed semistructured interviews. Participants were smokers who owned an Android mobile phone and were willing to set a quit date within one month (N=15). App data included smoking reports with context information and geolocation, end-of-day (EoD) surveys of smoking beliefs and behavior, support message ratings, and app interaction data. Interviews were undertaken and analyzed thematically (N=13). Quantitative and qualitative data were analyzed separately and findings presented sequentially.ResultsOut of 15 participants, 3 (20%) discontinued use of the app prematurely. Pre-quit date, the mean number of smoking reports received was 37.8 (SD 21.2) per participant, or 2.0 (SD 2.2) per day per participant. EoD surveys indicated that participants underreported smoking on at least 56.2% of days. Geolocation was collected in 97.0% of smoking reports with a mean accuracy of 31.6 (SD 16.8) meters. A total of 5 out of 9 (56%) eligible participants received geofence-triggered support. Interaction data indicated that 50.0% (137/274) of geofence-triggered message notifications were tapped within 30 minutes of being generated, resulting in delivery of a support message, and 78.2% (158/202) of delivered messages were rated by participants. Qualitative findings identified multiple reasons for noncompliance in reporting smoking, most notably due to environmental constraints and forgetting. Participants verified the app's identification of their smoking locations, were largely positive about the value of geofence-triggered support, and had no privacy concerns about the data collected by the app.ConclusionsUser-initiated self-report is feasible for training a cessation app about an individual's smoking behavior, although underreporting is likely. Geofencing was a reliable and accurate method of identifying smoking locations, and geofence-triggered support was regarded positively by participants.

Project description:BackgroundNear-miss organizational learning is important for perspective and proactive risk management. Although nursing organizations are the largest component of the healthcare system and act as the final safety barrier, there is little research about the current status of near-miss organizational learning. Thus, we conducted this study to explore near-miss organizational learning in a Chinese nursing organization and offer suggestions for future improvement.MethodsThis was a mixed methods study with an explanatory sequence. It was conducted in a Chinese nursing organization of a tertiary hospital under the guidance of the 4I Framework of Organizational Learning. The quantitative study surveyed 600 nurses by simple random sampling. Then, we applied purposive sampling to recruit 16 nurses across managerial levels from low-, middle- and high-scored nursing units and conducted semi-structured interviews. Descriptive statistics, structured equation modelling and content analysis were applied in the data analysis. The Good Reporting of A Mixed Methods Study (GRAMMS) checklist was used to report this study.ResultsOnly 33% of participants correctly recognized near-misses, and 4% of participants always reported near-misses. The 4I Framework of Organizational Learning was verified in the surveyed nursing organization (χ2 = 0.775, p = 0.379, RMSEA < 0.01). The current organizational learning behaviour was not conducive to near-miss organizational learning due to poor group-level learning (βGG = 0.284) and poor learning absorption (βMisalignment= -0.339). In addition, the researchers developed 13 codes, 9 categories and 5 themes to depict near-miss organizational learning, which were characterized by nurses' unfamiliarity with near-misses, preferences and the dominance of first-order problem-solving behaviour, the suspension of near-miss learning at the group level and poor learning absorption.ConclusionThe performance of near-miss organizational learning is unsatisfactory across all levels in surveyed nursing organization, especially with regard to group-level learning and poor learning absorption. Our research findings offer a scientific and comprehensive description of near-miss organizational learning and shed light on how to measure and improve near-miss organizational learning in the future.

Project description:IntroductionThis study evaluated whether introducing performance obligations (a policy intervention) to service agreements between hospitals (n = 15) and their local health authority: (1) improved provision of an evidence-based tobacco cessation intervention (the "Ottawa Model" for Smoking Cessation) and (2) changed the quality of the cessation intervention being delivered.MethodsInterrupted time series analysis was used to evaluate the change in the proportion of smoker patients provided the Ottawa Model 3 years before and 3 years after introducing the performance obligations. Changes in secondary outcomes related to program quality were described using mean differences, risk differences, and risk ratios, as appropriate.ResultsThe proportion and number of patients provided the Ottawa Model doubled in the 3-year period following introduction of the new policy-from 3453 patients (33.7%) in the year before to 6840 patients (62.8%) in the final assessment year. This resulted in a signification slope change (+9.2%; 95% confidence interval [CI] 4.5%, 13.9%; p = .01) between the pre- and post-obligation assessment periods, signifying the policy had a positive impact on performance. Quality and effectiveness of the in-hospital intervention remained steady.ConclusionsImplementation of performance obligations by a healthcare funder increased delivery of an evidence-based smoking cessation intervention across multiple hospitals. Given the known health and economic impacts of smoking cessation interventions, health authorities and hospitals should consider pairing adoption of systematic interventions, like the Ottawa Model, with policy to enhance reach and impact.Implications• The hospital-based Ottawa Model for Smoking Cessation (OMSC) intervention has been shown to increase smoking abstinence, while reducing mortality and healthcare utilization.• The uptake of systematic, evidence-based interventions, like the OMSC, by hospitals has been relatively low despite the known positive impacts.• The introduction of smoking cessation performance obligations by a healthcare funder resulted in more patients receiving an OMSC intervention while in hospital, with no corresponding change in intervention quality or effectiveness.• Healthcare funders and hospitals should consider pairing the adoption of effective, systematic interventions, like the OMSC, with policy to enhance reach and impact.

Project description:BackgroundThe pandemic of SARS-CoV-2, which causes COVID-19, has caused disruptions in ongoing clinical trials and is expected to accelerate interest in conducting research studies remotely.ObjectiveA quasi-experimental, mixed methods approach was used to examine the rates of visit completion as well as the opinions and experiences of participants enrolled in an ongoing clinical trial of smoking cessation who were required to change from in-person clinic visits to remote visits using video or telephone conferencing due to the COVID-19 pandemic.MethodsFor quantitative comparisons, we used a quasi-experimental design, comparing a cohort of participants followed during the pandemic (n=23, COVID-19 cohort) to a comparable cohort of participants followed over a similar time period in the calendar years 2018 and 2019 (n=51, pre-COVID-19 cohort) to examine the rates of completion of scheduled visits and biospecimen collection. For the qualitative component, interviews were conducted with participants who experienced the transition from in-person to remote visits.ResultsParticipants in the COVID-19 cohort completed an average of 83.6% of remote clinic visits (95% CI 73.1%-91.2%), which was not significantly different than the in-person completion rate of 89.8% in the pre-COVID-19 cohort. Participants in the COVID-19 cohort returned an average of 93.2% (95% CI 83.5%-98.1%) of saliva specimens for remote clinic visits completed, which was not significantly different than the in-person saliva specimen completion rate of 100% in the pre-COVID-19 cohort. Two broad themes emerged from the qualitative data: (1) the benefits of remote visits and (2) the challenges of remote counseling compared to in-person counseling. Despite limited experience with telehealth prior to this transition, most participants expressed a willingness to engage in remote visits in the future.ConclusionsEven in the context of a rapid transition from in-person to remote visits necessitated by the COVID-19 pandemic, rates of visit completion and return of biospecimens remained high. Participants were generally accepting of the transition. Further research is needed to identify the optimal mix of in-person and remote visits beyond the pandemic context and to better understand how these changes may impact study outcomes.Trial registrationClinicalTrials.gov NCT03262662; https://clinicaltrials.gov/ct2/show/study/NCT03262662.

Dataset Information

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

Publications

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

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