Understanding the barriers to successful adoption and use of a mobile health information system in a community health center in São Paulo, Brazil: a cohort study

BACKGROUND: Mobile technology to support community health has surged in popularity, yet few studies have systematically examined usability of mobile platforms for this setting. METHODS: We conducted a mixed-methods study of 14 community healthcare workers at a public healthcare clinic in São Paulo, Brazil. We held focus groups with community healthcare workers to elicit their ideas about a mobile health application and used this input to build a prototype app. A pre-use test survey was administered to all participants, who subsequently use-tested the app on three different devices (iPhone, iPad mini, iPad Air). Usability was assessed by objectively scored data entry errors and through a post-use focus group held to gather open-ended feedback on end-user satisfaction. RESULTS: All of the participants were women, ranging from 18–64 years old. A large percentage (85.7%) of participants had at least a high school education. Internet (92.8%), computer (85.7%) and cell phone (71.4%) use rates were high. Data entry error rates were also high, particularly in free text fields, ranging from 92.3 to 100%. Error rates were comparable across device type. In a post-use focus group, participants reported that they found the app easy to use and felt that its design was consistent with their vision. The participants raised several concerns, including that they did not find filling out the forms in the app to be a useful task. They also were concerned about an app potentially creating more work for them and personal security issues related to carrying a mobile device in low-income areas. CONCLUSION: In a cohort of formally educated community healthcare workers with high levels of personal computer and cell phone use, we identified no technological barriers to adapting their existing work to a mobile device based system. Transferring current data entry work into a mobile platform, however, uncovered underlying dissatisfaction with some data entry tasks. This dissatisfaction may be a more significant barrier than the data entry errors our testing revealed. Our results highlight the fact that without a deep understanding of local process to optimize usability, technology-based solutions in health may fail. Developing such an understanding must be a central component in the design of any mHealth solution in global health

Analysis of the Spatial Variation of Hospitalization Admissions for Hypertension Disease in Shenzhen, China

In China, awareness about hypertension, the treatment rate and the control rate are low compared to developed countries, even though China’s aging population has grown, especially in those areas with a high degree of urbanization. However, limited epidemiological studies have attempted to describe the spatial variation of the geo-referenced data on hypertension disease over an urban area of China. In this study, we applied hierarchical Bayesian models to explore the spatial heterogeneity of the relative risk for hypertension admissions throughout Shenzhen in 2011. The final model specification includes an intercept and spatial components (structured and unstructured). Although the road density could be used as a covariate in modeling, it is an indirect factor on the relative risk. In addition, spatial scan statistics and spatial analysis were utilized to identify the spatial pattern and to map the clusters. The results showed that the relative risk for hospital admission for hypertension has high-value clusters in the south and southeastern Shenzhen. This study aimed to identify some specific regions with high relative risk, and this information is useful for the health administrators. Further research should address more-detailed data collection and an explanation of the spatial patterns

Adverse weather conditions for European wheat production will become more frequent with climate change

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The project for intercomparison of land-surface parameterization schemes (PILPS) phase 2(c) Red-Arkansas River basin experiment: 1. Experiment description and summary intercomparisons

Sixteen land-surface schemes participating in the project for the Intercomparison of Land-surface Schemes (PILPS) Phase 2(c) were run using 10 years (1979-1988) of forcing data for the Red-Arkansas River basins in the Southern Great Plains region of the United States. Forcing data (precipitation, incoming radiation and surface meteorology) and land-surface characteristics (soil and vegetation parameters) were provided to each of the participating schemes. Two groups of runs are presented. (1) Calibration-validation runs, using data from six small catchments distributed across the modeling domain. These runs were designed to test the ability of the schemes to transfer information about model parameters to other catchments and to the computational grid boxes. (2) Base-runs, using data for 1979-1988, designed to evaluate the ability of the schemes to reproduce measured energy and water fluxes over multiple seasonal cycles across a climatically diverse, continental-scale basin. All schemes completed the base-runs but five schemes chose not to calibrate. Observational data (from 1980-1986) including daily river flows and monthly basin total evaporation estimated through an atmospheric budget analysis, were used to evaluate model performance. In general, the results are consistent with earlier PILPS experiments in terms of differences among models in predicted water and energy fluxes. The mean annual net radiation varied between 80 and 105 W m-2 (excluding one model). The mean annual Bowen ratio varied from 0.52 to 1.73 (also excluding one model) as compared to the data-estimated value of 0.92. The run-off ratios varied from a low of 0.02 to a high of 0.41, as compared to an observed value of 0.15. In general, those schemes that did not calibrate performed worse, not only on the validation catchments, but also at the scale of the entire modeling domain. This suggests that further PILPS experiments on the value of calibration need to be carried out

Immune checkpoint inhibitor colitis: the flip side of the wonder drugs

Immune checkpoint inhibitors block the co-inhibitory receptors on T cells to activate their cytotoxic immune function and are rapidly being explored for the treatment of various advanced-stage malignancies. These novel drugs have already significantly increased survival rates. The first available immune checkpoint inhibitors were cytotoxic T lymphocyte antigen 4 (CTLA-4) inhibitors (such as ipilimumab), followed by programmed cell death protein 1 (PD-1) and programmed cell death protein ligand 1 (PD-L1) inhibitors (such as pembrolizumab and nivolumab). Anti-PD-1 and anti-PD-L1 therapies have demonstrated better efficacy and tolerability and less severe adverse effects compared to anti-CTLA-4 agents. Idelalisib, a PI3Kδ isoform inhibitor, is another immunotherapeutic agent that is often classified separately and is currently used in treatment of chronic lymphocytic leukemia and non-Hodgkin lymphomas. Despite successful therapeutic responses, immune-related adverse events have been reported with the use of these agents. The gastrointestinal side effects, particularly diarrhea, are among the most commonly reported symptoms. The histologic features of immune checkpoint inhibitor-associated colitis show a spectrum of patterns of injury among various drug classes. There is significant overlap between immune checkpoint inhibitor-associated colitis and other colitides, making the differential diagnosis difficult—especially in the absence of clinical history. The histopathology data on immune checkpoint inhibitor-associated colitis are limited. Here we review clinical features as well as various histologic patterns of colitis associated with these groups of medications