Changes in quality of life from a homelessness intervention: true change, response shift, or random variation.

BACKGROUND AND OBJECTIVE: Participants experiencing homelessness and mental illness who received housing and support through the At Home/Chez Soi trial showed modest gains in quality of life (QOL) compared to treatment as usual participants. Participants' QOL ratings over time may have been affected by either response shift triggered by new life circumstances or by random variation in the meaning of QOL ratings. This study seeks to identify both phenomena to estimate the intervention's effect on true change in QOL. METHODS: Using the residuals from a regression model of the global item of Lehman's 20-item quality of life interview (QOLI-20), latent trajectory analysis was used to identify response shift, while a measure of overall variability in residuals identified random variation of QOL. The latter was used to adjust group comparisons of QOLI-20 total scores and the global item. RESULTS: Equivalent distributions of both groups' participants across latent trajectory classes (χ2 = 2.97, p = .397) suggest that the intervention did not trigger response shift. However, random variation interacted significantly with the treatment effect on global item ratings. For every increase of one standard deviation of residuals, treatment odds ratios decreased by a factor of 0.70 (SE 1.18, p = .036, 95% CI 0.50-0.98). CONCLUSIONS: Measuring random variation in QOL ratings from the standard deviation of residuals offers the ability to approximate, although indirectly, how participants' QOL is truly affected by a housing intervention. Specifically, we found that QOL improvement is more evident when QOL ratings have a consistent meaning over time.

Modeling Chronic Obstructive Pulmonary Disease Progression Using Continuous-Time Hidden Markov Models.

Understanding the progression of chronic diseases, such as chronic obstructive pulmonary disease (COPD), is important to inform early diagnosis, personalized care, and health system management. Data from clinical and administrative systems have the potential to advance this understanding, but traditional methods for modelling disease progression are not well-suited to analyzing data collected at irregular intervals, such as when a patient interacts with a healthcare system. We applied a continuous-time hidden Markov model to irregularly-spaced healthcare utilization events and patient-level characteristics in order to analyze the progression through discrete states of 76,888 patients with COPD. A 4-state model allowed classification of patients into interpretable states of disease progression and generated insights about the role of comorbidities, such as cardiovascular diseases, in accelerating severe trajectories. These results can improve the understanding of the evolution of COPD and point to new hypotheses about chronic disease management and comorbidity.

Epidemiology of recurrent traumatic brain injury in the general population: A systematic review.

OBJECTIVE: To comprehensively assess recurrent traumatic brain injury (rTBI) risk and risk factors in the general population. METHODS: We systematically searched MEDLINE, EMBASE, and the references of included studies until January 16, 2017, for general population observational studies reporting rTBI risk or risk factors. Estimates were not meta-analyzed due to significant methodologic heterogeneity between studies, which was evaluated using meta-regression. RESULTS: Twenty-two studies reported recurrence risk and 11 reported on 27 potential risk factors. rTBI risk was heterogeneous and varied from 0.43% (95% confidence interval [CI] 0.19%-0.67%) to 41.92% (95% CI 34.43%-49.40%), with varying follow-up periods (3 days-55 years). Median time to recurrence ranged from 0.5 to 3.8 years. In studies where cases were ascertained from multiple points of care, at least 5.50% (95% CI 4.80%-6.30%) of patients experienced a recurrence after a 1-year follow-up. Studies that used administrative data/self-report surveys to ascertain cases tended to report higher risk. Risk factors measured at time of index traumatic brain injury (TBI) that were significantly associated with rTBI in more than one study were male sex, prior TBI before index case, moderate or severe TBI, and alcohol intoxication. Risk factors reported in a single study that were significantly associated with rTBI were epilepsy, not seeking medical care, and multiple factors indicative of low socioeconomic status. CONCLUSIONS: rTBI is an important contributor to the general population TBI burden. Certain risk factors can help identify individuals at higher risk of these repeated injuries. However, higher quality research that improves on rTBI surveillance methodology is needed.

Multivariate and Longitudinal Health System Indicators.

Within population health information systems, indicators are commonly presented as independent, cross-sectional measures, neglecting the multivariate, longitudinal nature of disease progression, health care use, and profiles of performance. We use administrative claims data of Montreal, Canada to identify patterns across indicators and over time in chronic obstructive pulmonary disease patients. We first cluster regions based on four health service indicators. Our second approach discovers individual-level trajectories based on a hidden Markov model using the same four indicators. Both approaches offer additional insights by facilitating the discovery and interpretation of indicators, such as a dual interpretation of low use of general practitioner services. These approaches to the analysis and visualization of health indicators can provide a foundation for information displays that will help decision makers identify areas of concern, predict future disease burden, and implement appropriate policies.

Media content about vaccines in the United States and Canada, 2012-2014: An analysis using data from the Vaccine Sentimeter.

BACKGROUND: A system for monitoring vaccine-related media content was previously developed and studied from an international perspective. This monitoring approach could also have value at a regional level, but it has yet to be evaluated at this scale. We examined regional patterns of vaccine-related media topics and sentiment in the US and Canada. METHODS: We extracted vaccine-relevant US and Canadian online media reports between June 2012 and October 2014 from the Vaccine Sentimeter, a HealthMap-based automated media monitoring system for news aggregators and blogs. We analyzed regional distributions of reports about vaccines, categories (i.e., topics), sentiment, and measles outbreaks. FINDINGS: The Vaccine Sentimeter captured 10,715 reports during the study period. Negative sentiment was highest in reports about vaccine safety (47%), Hepatitis B (19%), and Vermont (18%). Analyses of measles outbreaks revealed geographical variation in media content. For example, religious beliefs were mentioned in 27% of measles reports in Texas and 22% of British Columbia reports, but there were no references to religion in media on measles from California. INTERPRETATIONS: A regional analysis of online sentiment towards vaccine can provide insights that may give US and Canadian public health practitioners a deeper understanding of media influences on vaccine choices in their regions and consequently lead to more effective public health action.