Documentation of the patient's smoking status in common chronic diseases - analysis of medical narrative reports using the ULMFiT based text classification.

INTRODUCTION: Smoking cessation is essential part of a successful treatment in many chronic diseases. Our aim was to analyse how actively clinicians discuss and document patients' smoking status into electronic health records (EHR) and deliver smoking cessation assistance. METHODS: We analysed the results using a combination of rule and deep learning-based algorithms. Narrative reports of all adult patients, whose treatment started between years 2010 and 2016 for one of seven common chronic diseases, were followed for two years. Smoking related sentences were first extracted with a rule-based algorithm. Subsequently, pre-trained ULMFiT-based algorithm classified each patient's smoking status as a current smoker, ex-smoker, or never smoker. A rule-based algorithm was then again used to analyse the physician-patient discussions on smoking cessation among current smokers. RESULTS: A total of 35,650 patients were studied. Of all patients, 60% were found to have a smoking status in EHR and the documentation improved over time. Smoking status was documented more actively among COPD (86%) and sleep apnoea (83%) patients compared to patients with asthma, type 1&2 diabetes, cerebral infarction and ischemic heart disease (range 44-61%). Of the current smokers (N=7,105), 49% had discussed smoking cessation with their physician. The performance of ULMFiT-based classifier was good with F-scores 79-92. CONCLUSION: Ee found that smoking status was documented in 60% of patients with chronic disease and that the clinician had discussed smoking cessation in 49% of patients who were current smokers. ULMFiT-based classifier showed good/excellent performance and allowed us to efficiently study a large number of patients' medical narratives.

Development of self-assessed work ability among middle-aged asthma patients-a 10 year follow-up study.

OBJECTIVE: The prevalence of asthma has been growing among working age people over the last decades. In this study, we examine the development of Work Ability Score (WAS) among middle-aged asthmatics in a longitudinal setting, in order to find risk factors for poor development. METHODS: We followed the development of WAS trends during 10 years in a cohort of 529 middle-aged asthmatics, who were active in working life. Follow-up questionnaires were mailed in years 1, 2, 4, 6, 8, and 10. To study the development of WAS over time, we computed the discrete Frechet distance, which describes the similarity between the shapes of WAS curves. RESULTS: Sixty-eight percent of the patients' WAS remained good or excellent throughout the follow-up period, while 24% of the patients WAS trend remained moderate. However, in 8%, the WAS was poor already in baseline and decreased further throughout the study. Using logistic regression, the moderate/poor development was associated significantly with high body mass index (BMI), pack years, adult onset asthma, physically strenuous work, number of co-morbidities, especially in psychiatric conditions, hypertension, and gastroesophageal reflux disease(GERD). When the model was adjusted for age and gender, adulthood onset of asthma and pack years lost their significance. Based on medication (high dose of inhaled corticosteroids (ICS) and second controller in use), 8% of the patients had severe asthma. CONCLUSION: In the great majority of middle-aged asthma patients WAS remained stable throughout the follow-up period. However, 8% of the patients, who had more severe asthma and multiple co-morbidities, showed significantly poorer outcomes.

Consistency and reliability of smoking-related variables: longitudinal study design in asthma and COPD.

Introduction: Smoking has a significant impact on the development and progression of asthma and chronic obstructive pulmonary disease (COPD). Self-reported questionnaires and structured interviews are usually the only way to study patients' smoking history. In this study, we aim to examine the consistency of the responses of asthma and COPD patients to repeated standardised questions on their smoking habits over the period of 10 years. Methods: The study population consisted of 1329 asthma and 959 COPD patients, who enrolled in the study during years 2005-2007. A follow-up questionnaire was mailed to the participants 1, 2, 4, 6, 8, and 10 years after the recruitment. Results: Among the participants who returned three or more questionnaires (N = 1454), 78.5 % of the patients reported unchanged smoking status (never smoker, ex-smoker or current smoker) across the time. In 4.5% of the answers, the reported smoking statuses were considered unreliable/conflicting (first never smoker and, later, smoker or ex-smoker). The remainder of the patients changed their status from current smoker to ex-smoker and vice versa at least once, most likely due to struggling with quitting. COPD patients were more frequently heavy ex- or current smokers compared to the asthma group. The intraclass coefficient correlations between self-reported starting (0.85) and stopping (0.94) years as well as the consumption of cigarettes (0.74) over time showed good reliability among both asthma and COPD patients. Conclusion: Self-reported smoking data among elderly asthma and COPD patients over a 10-year follow-up is reliable. Pack years can be considered a rough estimate for their comprehensive consumption of tobacco products over time. We also observed that the questionnaire we used was not designed for dynamic changes in smoking which are rather common among heavy smokers especially when the follow-up time is several years, as in our study.