scholarly journals Discharge status validation of the Chang Gung Research Database in Taiwan

2021 ◽  
Author(s):  
Yu-Tung Huang ◽  
Ying-Jen Chen ◽  
Shang-Hung Chang ◽  
Chang-Fu Kuo ◽  
Mei-Hua Chen
2019 ◽  
Vol 26 (12) ◽  
pp. 39-51 ◽  
Author(s):  
T. N. Gavrilyeva ◽  
E. A. Kolomak ◽  
A. I. Zakharov ◽  
K. V. Khorunova

The article assesses the intensity of transformation of settlement pattern in Yakutia, the largest northern region of Russia, based on an analysis of 1939-2010 censuses and contemporary statistics. Scope of the work includes the following: to assess key socio-economic results of rural and urban settlement pattern transformation in the 20th century, to determine the most persistent primary units of settlement pattern, and to identify current trends in the settlement pattern of Yakutia. The research database was built based on digitization of Federal State Statistics Service in the Sakha Republic (Yakutia) population censuses archives. The period under review shows a trend toward larger size of settlements due to two parallel processes: urbanization as a result of industrial development, and compression of rural settlement system due to amalgamation of rural settlements. From 1939 to the present time, Yakutia’s settlement system has been evolving from dispersed type to large settlement type. There were two major waves in the structuring of space in Yakutia. During the first one, caused by industrialization and complete collectivization, shrinking of rural settlement system was accompanied by setup of rural and urban settlements; it started in the 1930s and lasted until late 1950s. The second wave, concurrent with controlled compression of rural settlement pattern as part of elimination of unpromising sovkhoz state farms, was associated with a full-scale development of urban settlement pattern under planned Soviet deployment. Starting from 2002, market mechanisms have changed the direction of development of settlement system and spatial structure of economic activity. Despite several constraints, which include high transportation costs, focal development, key role of mining and resource sector, distinctive features of traditional economies and agriculture, agglomeration processes have gained momentum in the region. Spatial concentration of population is taking place at relatively high rates, primarily in the core of the system - Yakutsk agglomeration. Compression capacity of settlement system in the region is far from being exhausted, as evidenced by behavior of Theil and Herfindahl-Hirschman indices, as well as by average population density of settlements.


2020 ◽  
Author(s):  
Jessica Robinson-Papp ◽  
Gabriela Cedillo ◽  
Richa Deshpande ◽  
Mary Catherine George ◽  
Qiuchen Yang ◽  
...  

BACKGROUND Collecting patient-reported data needed by clinicians to adhere to opioid prescribing guidelines represents a significant time burden. OBJECTIVE We developed and tested an opioid management app (OM-App) to collect these data directly from patients. METHODS OM-App used a pre-existing digital health platform to deliver daily questions to patients via text-message and organize responses into a dashboard. We pilot tested OM-App over 9 months in 40 diverse participants with HIV who were prescribed opioids for chronic pain. Feasibility outcomes included: ability to export/integrate OM-App data with other research data; patient-reported barriers and adherence to OM-App use; capture of opioid-related harms, risk behaviors and pain intensity/interference; comparison of OM-App data to urine drug testing, prescription drug monitoring program data, and validated questionnaires. RESULTS OM-App data was exported/integrated into the research database after minor modifications. Thirty-nine of 40 participants were able to use OM-App, and over the study duration 70% of all OM-App questions were answered. Although the cross-sectional prevalence of opioid-related harms and risk behaviors reported via OM-App was low, some of these were not obtained via the other measures, and over the study duration all queried harms/risks were reported at least once via OM-App. Clinically meaningful changes in pain intensity/interference were captured. CONCLUSIONS OM-App was used by our diverse patient population to produce clinically relevant opioid- and pain-related data, which was successfully exported and integrated into a research database. These findings suggest that OM-App may be a useful tool for remote monitoring of patients prescribed opioids for chronic pain. CLINICALTRIAL NCT03669939 INTERNATIONAL REGISTERED REPORT RR2-doi:10.1016/j.conctc.2019.100468


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