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BackgroundAsthma affects a large proportion of the population and leads to many hospital encounters involving both hospitalizations and emergency department visits every year. To lower the number of such encounters, many health care systems and health plans deploy predictive models to prospectively identify patients at high risk and offer them care management services for preventive care. However, the previous models do not have sufficient accuracy for serving this purpose well. Embracing the modeling strategy of examining many candidate features, we built a new machine learning model to forecast future asthma hospital encounters of patients with asthma at Intermountain Healthcare, a nonacademic health care system. This model is more accurate than the previously published models. However, it is unclear how well our modeling strategy generalizes to academic health care systems, whose patient composition differs from that of Intermountain Healthcare. ObjectiveThis study aims to evaluate the generalizability of our modeling strategy to the University of Washington Medicine (UWM), an academic health care system. MethodsAll adult patients with asthma who visited UWM facilities between 2011 and 2018 served as the patient cohort. We considered 234 candidate features. Through a secondary analysis of 82,888 UWM data instances from 2011 to 2018, we built a machine learning model to forecast asthma hospital encounters of patients with asthma in the subsequent 12 months. ResultsOur UWM model yielded an area under the receiver operating characteristic curve (AUC) of 0.902. When placing the cutoff point for making binary classification at the top 10% (1464/14,644) of patients with asthma with the largest forecasted risk, our UWM model yielded an accuracy of 90.6% (13,268/14,644), a sensitivity of 70.2% (153/218), and a specificity of 90.91% (13,115/14,426). ConclusionsOur modeling strategy showed excellent generalizability to the UWM, leading to a model with an AUC that is higher than all of the AUCs previously reported in the literature for forecasting asthma hospital encounters. After further optimization, our model could be used to facilitate the efficient and effective allocation of asthma care management resources to improve outcomes. International Registered Report Identifier (IRRID)RR2-10.2196/resprot.5039

Chronic pain and post-traumatic stress disorder (PTSD) frequently co-occur, and research suggests that these 2 conditions exacerbate one another producing greater impact on normal functioning in combination than separately. The influence of traumatic experiences on both pain and PTSD has been shown, but the nature of this interplay remains unclear. Although Criterion A trauma is required for the diagnosis of PTSD, whether the association between PTSD and chronic pain is dependent on Criterion A is underexplored. In this observational cohort study, we examined the association between pain and PTSD-like symptoms in the context of Criterion A trauma in 5,791 men from the Vietnam Era Twin Registry. Correlations and mixed-effects regression models were used to evaluate the relationship between PTSD Checklist-Civilian Version symptoms and multiple indicators of pain from the Short Form McGill Pain Questionnaire across trauma history and chronic pain conditions. 53.21% of the participants experienced trauma consistent with DSM-IV Criterion A for PTSD. The associations between pain indicators and PTSD-like symptoms was stronger for individuals with a history of trauma but remained robust for individuals without trauma history. Small but significant interactions between past trauma and pain indicators and PTSD-like symptoms were observed. Findings were similar in a subsample of participants with history of chronic pain conditions. The relationship between PTSD-like symptoms and indicators of pain were largely independent of trauma consistent with Criterion A, highlighting the need to better understand and address stressful life events in chronic pain patients and pain concerns in individuals reporting trauma. PERSPECTIVE: This article demonstrates that the relationship between PTSD-like symptoms and indicators of pain is largely independent of trauma consistent with Criterion A. This finding highlights the need to better understand and address stressful life events in chronic pain patients and pain concerns in individuals reporting trauma.

Back pain is the #1 cause of years lived with disability worldwide, yet surprisingly little is known regarding the biology underlying this symptom. We conducted a genome-wide association study (GWAS) meta-analysis of chronic back pain (CBP). Adults of European ancestry were included from 15 cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and from the UK Biobank interim data release. CBP cases were defined as those reporting back pain present for ≥3-6 months; non-cases were included as comparisons ("controls"). Each cohort conducted genotyping using commercially available arrays followed by imputation. GWAS used logistic regression models with additive genetic effects, adjusting for age, sex, study-specific covariates, and population substructure. The threshold for genome-wide significance in the fixed-effect inverse-variance weighted meta-analysis was p

Supplemental Digital Content is Available in the Text. New measures, including the Numeric Rating Scale of Underlying Pain without concurrent Analgesic use—may allow pain randomized controlled trials to target alternate estimands with clinical relevance. Although many individuals with chronic pain use analgesics, the methods used in many randomized controlled trials (RCTs) do not sufficiently account for confounding by differential post-randomization analgesic use. This may lead to underestimation of average treatment effects and diminished power. We introduce (1) a new measure—the Numeric Rating Scale of Underlying Pain without concurrent Analgesic use (NRS-UP(A))—which can shift the estimand of interest in an RCT to target effects of a treatment on pain intensity in the hypothetical situation where analgesic use was not occurring at the time of outcome assessment; and (2) a new pain construct—an individuals' perceived effect of analgesic use on pain intensity (EA). The NRS-UP(A) may be used as a secondary outcome in RCTs of point treatments or nonpharmacologic treatments. Among 662 adults with back pain in primary care, participants' mean value of the NRS-UP(A) among those using analgesics was 1.2 NRS points higher than their value on the conventional pain intensity NRS, reflecting a mean EA value of −1.2 NRS points and a perceived beneficial effect of analgesics. More negative values of EA (ie, greater perceived benefit) were associated with a greater number of analgesics used but not with pain intensity, analgesic type, or opioid dose. The NRS-UP(A) and EA were significantly associated with future analgesic use 6 months later, but the conventional pain NRS was not. Future research is needed to determine whether the NRS-UP(A), used as a secondary outcome may allow pain RCTs to target alternative estimands with clinical relevance. [ABSTRACT FROM AUTHOR]

Purpose: The growing use of internet-based learning (IBL) platforms in institutions of higher education is producing profound changes in the traditional teaching learning process worldwide. This paper aims to identify and understand the ways in which higher education institutions draw benefits by the use of such means, synthesizing the literature research. Design/methodology/approach: The study synthesized the literature research by using a mixed method approach in which both Web of Science (WoS) and bibliographic techniques were used to retrieve the relevant data base. Findings: The comprehensive review of the literature suggests that communication technology (CT), massive open online courseware (MOOCs), social networking sites (SNSs), blogs, real simple syndication (RSS) and YouTube are creating new possibilities and avenues of collaborative learning by transforming the traditional class and teacher-centric system. Research limitations/implications: Multiplicity of the IBL platforms and rapid technological obsolesce are some of the limitations of this paper. Originality/value: The findings of this study are highly useful in developing a strategic framework to accelerate the integration of IBL platforms to make teaching learning process more interactive and informative.