Personalized Chronic Disease Follow‐Up Appointments: Risk‐Stratified Care Through Big Data

Author(s):  
Zlatana Nenova ◽  
Jennifer Shang
Author(s):  
Ying Wang ◽  
Yiding Liu ◽  
Minna Xia

Big data is featured by multiple sources and heterogeneity. Based on the big data platform of Hadoop and spark, a hybrid analysis on forest fire is built in this study. This platform combines the big data analysis and processing technology, and learns from the research results of different technical fields, such as forest fire monitoring. In this system, HDFS of Hadoop is used to store all kinds of data, spark module is used to provide various big data analysis methods, and visualization tools are used to realize the visualization of analysis results, such as Echarts, ArcGIS and unity3d. Finally, an experiment for forest fire point detection is designed so as to corroborate the feasibility and effectiveness, and provide some meaningful guidance for the follow-up research and the establishment of forest fire monitoring and visualized early warning big data platform. However, there are two shortcomings in this experiment: more data types should be selected. At the same time, if the original data can be converted to XML format, the compatibility is better. It is expected that the above problems can be solved in the follow-up research.


2017 ◽  
Vol 72 ◽  
pp. 45-59 ◽  
Author(s):  
Yi-fan Zhang ◽  
Ling Gou ◽  
Tian-shu Zhou ◽  
De-nan Lin ◽  
Jing Zheng ◽  
...  

2016 ◽  
Vol 29 (1) ◽  
pp. 27-34 ◽  
Author(s):  
Hugh Davies ◽  
Nicole McKenzie ◽  
Teresa A. Williams ◽  
Gavin D. Leslie ◽  
Ruth McConigley ◽  
...  

2018 ◽  
Vol 5 (suppl_1) ◽  
pp. S161-S162
Author(s):  
Alfonso J Rodriguez-Morales ◽  
Julio Cesar Gutiérrez-Segura ◽  
Sabina Ocampo-Serna ◽  
Oscar Mauricio Meneses-Quintero ◽  
Sergio Andrés Ochoa-Orozco ◽  
...  

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
J Christiansen ◽  
S S Pedersen ◽  
C M Andersen ◽  
P Qualter ◽  
R Lund ◽  
...  

Abstract Background The present prospective cohort study investigated the association of loneliness and social isolation with healthcare utilisation in the general population over time. We also investigated the synergistic effect of loneliness and social isolation on healthcare utilisation. Methods Data from the 2013 Danish “How are you?' survey (n = 29,472) were combined with individual-level register data from the National Danish Patient Registry and the Danish National Health Service Registry in a 6-year follow-up period (2013-2018). Negative binomial regression analyses were performed while adjusting for baseline demographics, chronic disease, and healthcare utilisation during the follow-up period. Results Loneliness was significantly associated with number of GP visits (incident-rate ratio (IRR) = 1.06, 95% confidence interval (CI) [1.01, 1.13]), emergency admissions (IRR = 1.19, 95% CI [1.03, 1.37]) and number of hospital admission days (IRR = 1.32, 95% CI [1.08, 1.62]). No significant associations were found between social isolation and healthcare utilisation with one minor exception, in which social isolation was associated with less planned admissions (IRR = .88, 95% CI [.78, .99]). Finally, loneliness and social isolation demonstrated a synergistic effect on number of visits to the GP (IRR = .87, 95% CI [.78, .98]) and number of hospital admission days (IRR = .67, 95% CI [.45, .98]). Conclusions Our findings suggest that loneliness is a risk factor for primary and secondary healthcare utilisation, independently of social isolation, baseline demographics, chronic disease, and healthcare utilisation during the follow-up period. Key messages Loneliness is an independent risk factor for healthcare utilisation in the general population. Social isolation is not associated with healthcare utilisation in the general population.


2021 ◽  
Vol 69 (12) ◽  
pp. 3618
Author(s):  
UmeshChandra Behera ◽  
Brooke Salzman ◽  
AnthonyVipin Das ◽  
GumpiliSai Prashanthi ◽  
Parth Lalakia ◽  
...  

Author(s):  
Ing-Mari Dohrn ◽  
Anna-Karin Welmer ◽  
Maria Hagströmer

Abstract Background Associations of objectively assessed physical activity in different intensities and risk of developing chronic disease that requires hospital care have not yet been examined in long term population-based studies. Studies addressing the link between physical activity and sedentary time and subsequent hospital admissions are lacking. Objective To examine the prospective associations between physical activity and sedentary time with morbidity defined as: 1) a registered main diagnosis of cardiovascular disease, cancer, type-2 diabetes, dementia, obesity or depression; 2) number of in- and outpatient hospital visits; and 3) number of in-hospital days. Methods In total, 1220 women and men, 18–75 years, from the population-based Sweden Attitude Behaviour and Change study 2000–2001 were included. Time spent sedentary, in light-intensity physical activity and in moderate-to-vigorous physical activity, and total accelerometer counts were assessed using the ActiGraph 7164 accelerometer. Morbidity data were obtained 2016 from Swedish registers. Cox proportional hazards models estimated hazard ratios (HR) of morbidity with 95% confidence intervals (CI) and negative binomial regression estimated incidence rate ratio (IRR) with 95% CI for number of hospital visits, and length of hospital stay. Results Over a follow-up of 14.4 years (SD = 1.6), 342 persons had at least one registered hospital visit due to any of the included diagnoses. Higher moderate-to-vigorous physical activity was associated with significant risk reductions for combined morbidity (all included diagnoses) (HR: 0.65, 95% CI: 0.48–0.88) and cardiovascular disease (HR: 0.52, 95% CI: 0.33–0.82). Higher total counts showed similar results, and was also associated with fewer hospital visits (IRR = 0.56, 95% CI: 0.37–0.85). Higher sedentary time increased the risk of in-hospital days. (IRR = 2.38, 95% CI: 1.20–4.74). Conclusion This study supports the importance of moderate-to-vigorous physical activity for preventing chronic disease that requires hospital care, especially cardiovascular disease. High volumes of sedentary behavior may increase the risk of future hospitalization. Our results support the public health message “sit less and move more”.


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