Sentiment analysis of health care tweets: review of the methods used.

BACKGROUND: Twitter is a microblogging service where users can send and read short 140-character messages called "tweets." There are several unstructured, free-text tweets relating to health care being shared on Twitter, which is becoming a popular area for health care research. Sentiment is a metric commonly used to investigate the positive or negative opinion within these messages. Exploring the methods used for sentiment analysis in Twitter health care research may allow us to better understand the options available for future research in this growing field. OBJECTIVE: The first objective of this study was to understand which tools would be available for sentiment analysis of Twitter health care research, by reviewing existing studies in this area and the methods they used. The second objective was to determine which method would work best in the health care settings, by analyzing how the methods were used to answer specific health care questions, their production, and how their accuracy was analyzed. METHODS: A review of the literature was conducted pertaining to Twitter and health care research, which used a quantitative method of sentiment analysis for the free-text messages (tweets). The study compared the types of tools used in each case and examined methods for tool production, tool training, and analysis of accuracy. RESULTS: A total of 12 papers studying the quantitative measurement of sentiment in the health care setting were found. More than half of these studies produced tools specifically for their research, 4 used open source tools available freely, and 2 used commercially available software. Moreover, 4 out of the 12 tools were trained using a smaller sample of the study's final data. The sentiment method was trained against, on an average, 0.45% (2816/627,024) of the total sample data. One of the 12 papers commented on the analysis of accuracy of the tool used. CONCLUSIONS: Multiple methods are used for sentiment analysis of tweets in the health care setting. These range from self-produced basic categorizations to more complex and expensive commercial software. The open source and commercial methods are developed on product reviews and generic social media messages. None of these methods have been extensively tested against a corpus of health care messages to check their accuracy. This study suggests that there is a need for an accurate and tested tool for sentiment analysis of tweets trained using a health care setting-specific corpus of manually annotated tweets first

Systematic review of hospital readmissions in stroke patients

Background Previous evidence on factors and causes of readmissions associated with high-impact users of stroke is scanty. The aim of the study was to investigate common causes and pattern of short- and long-term readmissions stroke patients by conducting a systematic review of studies using hospital administrative data. Common risk factors associated with the change of readmission rate were also examined. Methods The literature search was conducted from 15th February to 15th March 2016 using various databases, such as Medline, Embase, and Web of Science. Results There were total of 24 studies (n=2,126,617) included in the review. Only 4 studies assessed causes of readmissions in stroke patients with the follow-up duration from 30 days to 5 years. Common causes of readmissions in majority of the studies were recurrent stroke, infections and cardiac conditions. Common patient-related risk factors associated with increased readmission rate were age and history of coronary heart disease, heart failure, renal disease, respiratory disease, peripheral arterial disease and diabetes. Among stroke-related factors, length of stay of index stroke admission was associated with increased readmission rate, followed by bowel incontinence, feeding tube and urinary catheter. Conclusion Although risk factors and common causes of readmission were identified, but none of the previous studies investigated causes and their sequence of readmissions among high-impact stroke users

Fifty Years of Innovation in Plastic Surgery

© 2016 The Korean Society of Plastic and Reconstructive Surgeons.Background Innovation has molded the current landscape of plastic surgery. However, documentation of this process only exists scattered throughout the literature as individual articles. The few attempts made to profile innovation in plastic surgery have been narrative, and therefore qualitative and inherently biased. Through the implementation of a novel innovation metric, this work aims to identify and characterise the most prevalent innovations in plastic surgery over the last 50 years. Methods Patents and publications related to plastic surgery (1960 to 2010) were retrieved from patent and MEDLINE databases, respectively. The most active patent codes were identified and grouped into technology areas, which were subsequently plotted graphically against publication data. Expert-derived technologies outside of the top performing patents areas were additionally explored. Results Between 1960 and 2010, 4,651 patents and 43,118 publications related to plastic surgery were identified. The most active patent codes were grouped under reconstructive prostheses, implants, instruments, non-invasive techniques, and tissue engineering. Of these areas and other expert-derived technologies, those currently undergoing growth include surgical instruments, implants, non-invasive practices, transplantation and breast surgery. Innovations related to microvascular surgery, liposuction, tissue engineering, lasers and prostheses have all plateaued. Conclusions The application of a novel metric for evaluating innovation quantitatively outlines the natural history of technologies fundamental to the evolution of plastic surgery. Analysis of current innovation trends provides some insight into which technology domains are the most active

Community detection and role identification in directed networks: understanding the Twitter network of the care.data debate

With the rise of social media as an important channel for the debate and discussion of public affairs, online social networks such as Twitter have become important platforms for public information and engagement by policy makers. To communicate effectively through Twitter, policy makers need to understand how influence and interest propagate within its network of users. In this chapter we use graph-theoretic methods to analyse the Twitter debate surrounding NHS Englands controversial care.data scheme. Directionality is a crucial feature of the Twitter social graph - information flows from the followed to the followers - but is often ignored in social network analyses; our methods are based on the behaviour of dynamic processes on the network and can be applied naturally to directed networks. We uncover robust communities of users and show that these communities reflect how information flows through the Twitter network. We are also able to classify users by their differing roles in directing the flow of information through the network. Our methods and results will be useful to policy makers who would like to use Twitter effectively as a communication medium

Assessment of chronic postsurgical pain after knee replacement : a systematic review

Objective: Approximately 20% of patients experience chronic pain after total knee replacement (TKR), yet there is no consensus about how best to assess such pain. This systematic review aimed to identify measures used to characterise chronic pain after TKR. Methods: MEDLINE, Embase, PsycINFO, Cochrane Library and CINAHL databases were searched for research articles published in all languages from January 2002- November 2011. Articles were eligible for inclusion if they assessed knee pain at a minimum of 3-months after TKR, yielding a total of 1,164 articles. Data extracted included study design, country, timings of assessments, and outcome measures containing pain items. Outcome measures were compared with domains recommended by IMMPACT for inclusion in assessment of chronic pain related outcomes within clinical trials. Temporal trends were also explored. Results: The review found use of a wide variety of composite and single-item measures, with the American Knee Society Score most common. Many measures used in published studies do not capture the multi-dimensional nature of pain recommended by IMMPACT; of those commonly used, the WOMAC and Oxford Knee Score are most comprehensive. Geographical trends were evident, with nation-specific preferences for particular measures. A recent reduction in use of some clinically-administered tools was accompanied by increased use of patient-reported outcome measures. Conclusion: There was wide variation in methods of pain assessment alongside nation-specific preferences and changing temporal trends in pain assessment after TKR. Standardisation and improvements in assessment is needed to enhance the quality of research and facilitate the establishment of a core outcome set

Patient safety and quality of care in mental health: a world of its own?

Quality and safety in healthcare, as an academic discipline, has made significant progress over recent decades, and there is now an active and established community of researchers and practitioners. However, work has predominantly focused on physical health, despite broader controversy regarding the attention paid to, and significance attributed to, mental health. Work from both communities is required in order to ensure that quality and safety is actively embedded within mental health research and practice and that the academic discipline of quality and safety accurately represents the scientific knowledge that has been accumulated within the mental health community