Experiences of tobacco cessation including a prescription approach among patients in Swedish primary health care with a focus on socioeconomically disadvantaged areas.

BACKGROUND: Tobacco Cessation on Prescription (TCP) is a new intervention that is being evaluated in socioeconomically disadvantaged areas in Swedish primary health care (PHC). Patients' perceptions of TCP are important to understand as this may have implications for the acceptability and adherence to treatment and explain cessation outcomes. Patients' general experiences of tobacco cessation are also important to explore to improve cessation support in this setting. AIM: To explore experiences of tobacco cessation and TCP among patients in Swedish PHC focusing on socioeconomically disadvantaged areas. METHODS: Inductive content analysis of transcripts from eight semi-structured interviews with patients recruited from the intervention group in a randomized controlled trial evaluating the effectiveness of TCP in socioeconomically disadvantaged areas in PHC in Stockholm. RESULTS: Two themes were identified: needing individualized support to quit, taking differences in patients' experiences of tobacco use and cessation into account, acknowledging individual factors such as impact of health and wellbeing on tobacco use and differing attitudes towards tobacco and cessation and needing a supportive environment to facilitate tobacco cessation, taking contextual factors like professional support from the health care system, the importance of the social environment and supportive societal structures into account. Regarding TCP, the prescription form was perceived as useful for providers but did not appear to have a direct impact on tobacco cessation from the informants' perspective. However, individualized counseling from a tobacco cessation specialist, an empathetic approach in the treatment and long-term follow-up was considered important. CONCLUSION: A holistic approach may be needed in cessation treatment, combined with interventions outside the health care system, to facilitate tobacco cessation among patients in socioeconomically disadvantaged areas in Swedish PHC. The TCP prescription form may be helpful for PHC providers but counseling and follow-up appear to be the most important components of TCP for patients in this setting.

CrowdHEALTH: Big Data Analytics and Holistic Health Records.

The aim of this paper is to present examples of big data techniques that can be applied on Holistic Health Records (HHR) in the context of the CrowdHEALTH project. Real-time big data analytics can be performed on the stored data (i.e. HHRs) enabling correlations and extraction of situational factors between laboratory exams, physical activities, biosignals, medical data patterns, and clinical assessment. Based on the outcomes of different analytics (e.g. risk analysis, pathways mining, forecasting and causal analysis) on the aforementioned HHRs datasets, actionable information can be obtained for the development of efficient health plans and public health policies.

The CrowdHEALTH project and the Hollistic Health Records: Collective Wisdom Driving Public Health Policies.

INTRODUCTION: With the expansion of available Information and Communication Technology (ICT) services, a plethora of data sources provide structured and unstructured data used to detect certain health conditions or indicators of disease. Data is spread across various settings, stored and managed in different systems. Due to the lack of technology interoperability and the large amounts of health-related data, data exploitation has not reached its full potential yet. AIM: The aim of the CrowdHEALTH approach, is to introduce a new paradigm of Holistic Health Records (HHRs) that include all health determinants defining health status by using big data management mechanisms. METHODS: HHRs are transformed into HHRs clusters capturing the clinical, social and human context with the aim to benefit from the collective knowledge. The presented approach integrates big data technologies, providing Data as a Service (DaaS) to healthcare professionals and policy makers towards a "health in all policies" approach. A toolkit, on top of the DaaS, providing mechanisms for causal and risk analysis, and for the compilation of predictions is developed. RESULTS: CrowdHEALTH platform is based on three main pillars: Data & structures, Health analytics, and Policies. CONCLUSIONS: A holistic approach for capturing all health determinants in the proposed HHRs, while creating clusters of them to exploit collective knowledge with the aim of the provision of insight for different population segments according to different factors (e.g. location, occupation, medication status, emerging risks, etc) was presented. The aforementioned approach is under evaluation through different scenarios with heterogeneous data from multiple sources.

CrowdHEALTH: Holistic Health Records and Big Data Analytics for Health Policy Making and Personalized Health.

Today's rich digital information environment is characterized by the multitude of data sources providing information that has not yet reached its full potential in eHealth. The aim of the presented approach, namely CrowdHEALTH, is to introduce a new paradigm of Holistic Health Records (HHRs) that include all health determinants. HHRs are transformed into HHRs clusters capturing the clinical, social and human context of population segments and as a result collective knowledge for different factors. The proposed approach also seamlessly integrates big data technologies across the complete data path, providing of Data as a Service (DaaS) to the health ecosystem stakeholders, as well as to policy makers towards a "health in all policies" approach. Cross-domain co-creation of policies is feasible through a rich toolkit, being provided on top of the DaaS, incorporating mechanisms for causal and risk analysis, and for the compilation of predictions.

Are non-responders in a quitline evaluation more likely to be smokers?

BACKGROUND: In evaluation of smoking cessation programs including surveys and clinical trials the tradition has been to treat non-responders as smokers. The aim of this paper is to assess smoking behaviour of non-responders in an evaluation of the Swedish national tobacco cessation quitline a nation-wide, free of charge service. METHODS: A telephone interview survey with a sample of people not participating in the original follow-up. The study population comprised callers to the Swedish quitline who had consented to participate in a 12 month follow-up but had failed to respond. A sample of 84 (18% of all non-responders) was included. The main outcome measures were self-reported smoking behaviour at the time of the interview and at the time of the routine follow-up. Also, reasons for not responding to the original follow-up questionnaire were assessed. For statistical comparison between groups we used Fischer's exact test, odds ratios (OR) and 95% confidence intervals (CI) on proportions and OR. RESULTS: Thirty-nine percent reported to have been smoke-free at the time they received the original questionnaire compared with 31% of responders in the original study population. The two most common reasons stated for not having returned the original questionnaire was claiming that they had returned it (35%) and that they had not received the questionnaire (20%). Non-responders were somewhat younger and were to a higher degree smoke-free when they first called the quitline. CONCLUSION: Treating non-responders as smokers in smoking cessation research may underestimate the true effect of cessation treatment.