Concept libraries for automatic electronic health record based phenotyping: A review.

INTRODUCTION: Electronic health records (EHR) are linked together to examine disease history and to undertake research into the causes and outcomes of disease. However, the process of constructing algorithms for phenotyping (e.g., identifying disease characteristics) or health characteristics (e.g., smoker) is very time consuming and resource costly. In addition, results can vary greatly between researchers. Reusing or building on algorithms that others have created is a compelling solution to these problems. However, sharing algorithms is not a common practice and many published studies do not detail the clinical code lists used by the researchers in the disease/characteristic definition. To address these challenges, a number of centres across the world have developed health data portals which contain concept libraries (e.g., algorithms for defining concepts such as disease and characteristics) in order to facilitate disease phenotyping and health studies. OBJECTIVES: This study aims to review the literature of existing concept libraries, examine their utilities, identify the current gaps, and suggest future developments. METHODS: The five-stage framework of Arksey and O'Malley was used for the literature search. This approach included defining the research questions, identifying relevant studies through literature review, selecting eligible studies, charting and extracting data, and summarising and reporting the findings. RESULTS: This review identified seven publicly accessible Electronic Health data concept libraries which were developed in different countries including UK, USA, and Canada. The concept libraries (n = 7) investigated were either general libraries that hold phenotypes of multiple specialties (n = 4) or specialized libraries that manage only certain specialities such as rare diseases (n = 3). There were some clear differences between the general libraries such as archiving data from different electronic sources, and using a range of different types of coding systems. However, they share some clear similarities such as enabling users to upload their own code lists, and allowing users to use/download the publicly accessible code. In addition, there were some differences between the specialized libraries such as difference in ability to search, and if it was possible to use different searching queries such as simple or complex searches. Conversely, there were some similarities between the specialized libraries such as enabling users to upload their own concepts into the libraries and to show where they were published, which facilitates assessing the validity of the concepts. All the specialized libraries aimed to encourage the reuse of research methods such as lists of clinical code and/or metadata. CONCLUSION: The seven libraries identified have been developed independently and appear to replicate similar concepts but in different ways. Collaboration between similar libraries would greatly facilitate the use of these libraries for the user. The process of building code lists takes time and effort. Access to existing code lists increases consistency and accuracy of definitions across studies. Concept library developers should collaborate with each other to raise awareness of their existence and of their various functions, which could increase users' contributions to those libraries and promote their wide-ranging adoption

Frequency and characteristics of disease flares in ankylosing spondylitis

Objective. To examine the characteristics and frequency of disease flares in a cohort of people with AS

Predicting Hospital Readmission for Campylobacteriosis from Electronic Health Records: A Machine Learning and Text Mining Perspective

(1) Background: This study investigates influential risk factors for predicting 30-day readmission to hospital for Campylobacter infections (CI). (2) Methods: We linked general practitioner and hospital admission records of 13,006 patients with CI in Wales (1990−2015). An approach called TF-zR (term frequency-zRelevance) technique was presented to evaluates how relevant a clinical term is to a patient in a cohort characterized by coded health records. The zR is a supervised term-weighting metric to assign weight to a term based on relative frequencies of the term across different classes. Cost-sensitive classifier with swarm optimization and weighted subset learning was integrated to identify influential clinical signals as predictors and optimal model for readmission prediction. (3) Results: From a pool of up to 17,506 variables, 33 most predictive factors were identified, including age, gender, Townsend deprivation quintiles, comorbidities, medications, and procedures. The predictive model predicted readmission with 73% sensitivity and 54% specificity. Variables associated with readmission included male gender, recurrent tonsillitis, non-healing open wounds, operation for in-gown toenails. Cystitis, paracetamol/codeine use, age (21−25), and heliclear triple pack use, were associated with a lower risk of readmission. (4) Conclusions: This study gives a profile of clustered variables that are predictive of readmission associated with campylobacteriosis

Patient perspectives of managing fatigue in ankylosing spondylitis, and views on potential interventions: a qualitative study

<p>Background: Fatigue is a major component of living with ankylosing spondylitis (AS), though it has been largely over-looked, and currently there are no specific agreed management strategies.</p> <p>Methods: This qualitative exploratory study involved participants who are members of an existing population-based ankylosing spondylitis (PAS) cohort. Participants residing in South West Wales were invited to participate in a focus group to discuss; (1) effects of fatigue, (2) self-management strategies and (3) potential future interventions. The focus groups were audio-recorded and the transcripts were analysed using thematic analysis.</p> <p>Results: Participants consisted of 3 males/4 females (group 1) and 4 males/3 females (group 2), aged between 35 and 73 years (mean age 53 years). Three main themes were identified: (1) The effects of fatigue were multi-dimensional with participants expressing feelings of being ‘drained’ (physical), ‘upset’ (emotional) and experiencing ‘low-mood’ (psychological); (2) The most commonly reported self-management strategy for fatigue was a balanced combination of activity (exercise) and rest. Medication was reluctantly taken due to side-effects and worries over dependency; (3) Participants expressed a preference for psychological therapies rather than pharmacological for managing fatigue. Information on Mindfulness-Based Stress Reduction (MBSR) was received with interest, with recommendations for delivery in a group format with the option of distance-based delivery for people who were not able to attend a group course.</p> <p>Conclusions: Patients frequently try and manage their fatigue without any formal guidance or support. Our research indicates there is a need for future research to focus on psychological interventions to address the multi-faceted aspects of fatigue in AS.</p&gt

Perception of Place: Its Role in the Attraction and Retention of Graduates and their Human Capital to Greater Manchester

The understanding of graduate migration is limited mainly to international or interregional flows in the UK, and not much is known about the patterns and drivers of graduate migration at the local level. This thesis uses Greater Manchester in the North West of England as the site for a mixed-methods study that investigates graduate migration in a city context. The research design combines the econometric modelling of microdata provided by the Higher Education Statistical Authority (HESA) with the analysis of primary survey and interview data, whilst also offering a new conceptualisation of Richard Florida’s theory of place quality. This thesis represents the first study to use HESA data to model graduate migration on a local level using binomial and multinomial logistic regression. The findings demonstrate that patterns of graduate retention in Greater Manchester reflect existing hierarchies and inequalities related to geography, gender, ethnicity, socioeconomic status, and employment. This thesis also offers a new conceptualisation of Florida’s place quality theory by relating locational choice to social structures and subjectivities. The survey and interview findings contribute additional evidence that graduate decision making is more complex than Human Capital Theory would suggest, and decisions about where to live and work after leaving university are linked to place attachment, identity, constraints, and subjectivities. Finally, it is argued that the study of graduate migration suffers from being under-conceptualised and under-theorised, and this thesis will bring greater clarity to the issue by making linkages between higher education, human capital, migration, and local economic development. After having brought greater conceptual clarity, this thesis offers a new analytic process to model graduate retention within cities. This thesis will argue that how we measure graduate retention has important policy implications, and policymakers should consider a mix of metrics when developing graduate retention targets for cities

The Impact of Communication Center Visits on Students’ Performance and Engagement

This study sought to empirically evaluate the extent to which visiting the communication center before delivering the first major speech in an introductory communication course improved students’ academic performance and engagement. A total of 262 students were included in this study, half of whom visited the communication center prior to their first speech, and half of whom did not. Between-subjects MANOVAs showed that students who visited the communication center had significantly higher speech grades, course grades, and attendance than students who did not. Likewise, those who visited the communication center also had higher levels of behavioral and cognitive engagement, but not agentic or emotional engagement

Identifying Prenatal and Postnatal Determinants of Infant Growth: A Structural Equation Modelling Based Cohort Analysis

The growth and maturation of infants reflect their overall health and nutritional status. The purpose of this study is to examine the associations of prenatal and early postnatal factors with infant growth (IG). A data-driven model was constructed by structural equation modelling to examine the relationships between pre- and early postnatal environmental factors and IG at age 12 months. The IG was a latent variable created from infant weight and waist circumference. Data were obtained on 274 mother-child pairs during pregnancy and the postnatal periods. Maternal pre-pregnancy BMI emerged as an important predictor of IG with both direct and indirect (mediated through infant birth weight) effects. Infants who gained more weight from birth to 6 months and consumed starchy foods daily at age 12 months, were more likely to be larger by age 12 months. Infant physical activity (PA) levels also emerged as a determinant. The constructed model provided a reasonable fit ( (11) = 21.5, < 0.05; RMSEA = 0.07; CFI = 0.94; SRMR = 0.05) to the data with significant pathways for all examined variables. Promoting healthy weight amongst women of child bearing age is important in preventing childhood obesity, and increasing daily infant PA is as important as a healthy infant diet