scholarly journals Logical Observation Identifiers Names and Codes (LOINC®) Applied to Microbiology: A National Laboratory Mapping Experience in Taiwan

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1564
Author(s):  
Chih-Yang Yeh ◽  
Syu-Jyun Peng ◽  
Hsuan Chia Yang ◽  
Mohaimenul Islam ◽  
Tahmina Nasrin Poly ◽  
...  
Keyword(s):  
Information Exchange ◽  
Disease Surveillance ◽  
National Laboratory ◽  
General Meeting ◽  
Error Pattern ◽  
Complete Mapping ◽  
Disease Surveillance System ◽  
Clinical Observations ◽  
Domain Expertise ◽  
Universal Standard

Background and Objective: Logical Observation Identifiers Names and Codes (LOINC) is a universal standard for identifying laboratory tests and clinical observations. It facilitates a smooth information exchange between hospitals, locally and internationally. Although it offers immense benefits for patient care, LOINC coding is complex, resource-intensive, and requires substantial domain expertise. Our objective was to provide training and evaluate the performance of LOINC mapping of 20 pathogens from 53 hospitals participating in the National Notifiable Disease Surveillance System (NNDSS). Methods: Complete mapping codes for 20 pathogens (nine bacteria and 11 viruses) were requested from all participating hospitals to review between January 2014 and December 2016. Participating hospitals mapped those pathogens to LOINC terminology, utilizing the Regenstrief LOINC mapping assistant (RELMA) and reported to the NNDSS, beginning in January 2014. The mapping problems were identified by expert panels that classified frequently asked questionnaires (FAQs) into seven LOINC categories. Finally, proper and meaningful suggestions were provided based on the error pattern in the FAQs. A general meeting was organized if the error pattern proved to be difficult to resolve. If the experts did not conclude the local issue’s error pattern, a request was sent to the LOINC committee for resolution. Results: A total of 53 hospitals participated in our study. Of these, 26 (49.05%) used homegrown and 27 (50.95%) used outsourced LOINC mapping. Hospitals who participated in 2015 had a greater improvement in LOINC mapping than those of 2016 (26.5% vs. 3.9%). Most FAQs were related to notification principles (47%), LOINC system (42%), and LOINC property (26%) in 2014, 2015, and 2016, respectively. Conclusions: The findings of our study show that multiple stage approaches improved LOINC mapping by up to 26.5%.

scholarly journals Spatiotemporal analysis of COVID-19 outbreaks in Wuhan, China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wei Liu ◽  
Dongming Wang ◽  
Shuiqiong Hua ◽  
Cong Xie ◽  
Bin Wang ◽  
...  
Keyword(s):  
Population Density ◽  
Disease Surveillance ◽  
Influence Factors ◽  
Spatiotemporal Analysis ◽  
Disease Surveillance System ◽  
Local Aggregation ◽  
Short Time ◽  
Effective Public Health ◽  
Global And Local ◽  
Spatial Transmission

AbstractFew study has revealed spatial transmission characteristics of COVID-19 in Wuhan, China. We aimed to analyze the spatiotemporal spread of COVID-19 in Wuhan and its influence factors. Information of 32,682 COVID-19 cases reported through March 18 were extracted from the national infectious disease surveillance system. Geographic information system methods were applied to analysis transmission of COVID-19 and its influence factors in different periods. We found decrease in effective reproduction number (Rt) and COVID-19 related indicators through taking a series of effective public health measures including restricting traffic, centralized quarantine and strict stay-at home policy. The distribution of COVID-19 cases number in Wuhan showed obvious global aggregation and local aggregation. In addition, the analysis at streets-level suggested population density and the number of hospitals were associated with COVID-19 cases number. The epidemic situation showed obvious global and local spatial aggregations. High population density with larger number of hospitals may account for the aggregations. The epidemic in Wuhan was under control in a short time after strong quarantine measures and restrictions on movement of residents were implanted.

Incidence of acute myocardial infarction in the workforce: Findings from the Occupational Disease Surveillance System

2021 ◽  
Vol 64 (5) ◽  
pp. 338-357
Author(s):  
Natalie Troke ◽  
Chloë Logar‐Henderson ◽  
Nathan DeBono ◽  
Mamadou Dakouo ◽  
Selena Hussain ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Occupational Disease ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Disease Surveillance System

scholarly journals Apply IOT technology to practice a pandemic prevention body temperature measurement system: A case study of response measures for COVID-19

2021 ◽  
Vol 17 (5) ◽  
pp. 155014772110181
Author(s):  
Wei-Ling Lin ◽  
Chun-Hung Hsieh ◽  
Tung-Shou Chen ◽  
Jeanne Chen ◽  
Jian-Le Lee ◽  
...  
Keyword(s):  
Body Temperature ◽  
Temperature Measurement ◽  
Measurement System ◽  
Disease Surveillance ◽  
Disease Surveillance System ◽  
Temperature Detection ◽  
Wide Range ◽  
Body Temperature Measurement ◽  
Analysis System ◽  
Temperature Measurement System

Today, the most serious threat to global health is the continuous outbreak of respiratory diseases, which is called Coronavirus Disease 2019 (COVID-19). The outbreak of COVID-19 has brought severe challenges to public health and has attracted great attention from the research and medical communities. Most patients infected with COVID-19 will have fever. Therefore, the monitoring of body temperature has become one of the most important basis for pandemic prevention and testing. Among them, the measurement of body temperature is the most direct through the Forehead Thermometer, but the measurement speed is relatively slow. The cost of fast-checking body temperature measurement equipment, such as infrared body temperature detection and face recognition temperature machine, is too high, and it is difficult to build Disease Surveillance System (DSS). To solve the above-mentioned problems, the Intelligent pandemic prevention Temperature Measurement System (ITMS) and Pandemic Prevention situation Analysis System (PPAS) are proposed in this study. ITMS is used to detect body temperature. However, PPAS uses big data analysis techniques to prevent pandemics. In this study, the campus field is used as an example, in which ITMS and PPAS are used. In the research, Proof of Concept (PoC), Proof of Service (PoS), and Proof of Business (PoB) were carried out for the use of ITMS and PPAS in the campus area. From the verification, it can be seen that ITMS and PPAS can be successfully used in campus fields and are widely recognized by users. Through the verification of this research, it can be determined that ITMS and PPAS are indeed feasible and capable of dissemination. The ITMS and PPAS are expected to give full play to their functions during the spread of pandemics. All in all, the results of this research will provide a wide range of applied thinking for people who are committed to the development of science and technology.

Disease Surveillance System for Big Climate Data Processing and Dengue Transmission

2017 ◽  
Vol 8 (2) ◽  
pp. 88-105 ◽  
Author(s):  
Gunasekaran Manogaran ◽  
Daphne Lopez
Keyword(s):  
Climate Change ◽  
Big Data ◽  
Data Processing ◽  
Real Time ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Sensor Data ◽  
Climate Data ◽  
The Real ◽  
Disease Surveillance System

Ambient intelligence is an emerging platform that provides advances in sensors and sensor networks, pervasive computing, and artificial intelligence to capture the real time climate data. This result continuously generates several exabytes of unstructured sensor data and so it is often called big climate data. Nowadays, researchers are trying to use big climate data to monitor and predict the climate change and possible diseases. Traditional data processing techniques and tools are not capable of handling such huge amount of climate data. Hence, there is a need to develop advanced big data architecture for processing the real time climate data. The purpose of this paper is to propose a big data based surveillance system that analyzes spatial climate big data and performs continuous monitoring of correlation between climate change and Dengue. Proposed disease surveillance system has been implemented with the help of Apache Hadoop MapReduce and its supporting tools.

scholarly journals Assessment of the core and support functions of the Integrated Disease Surveillance system in Maharashtra, India

2013 ◽  
Vol 13 (1) ◽  
Author(s):  
Revati K Phalkey ◽  
Sharvari Shukla ◽  
Savita Shardul ◽  
Nutan Ashtekar ◽  
Sapna Valsa ◽  
...  
Keyword(s):  
Surveillance System ◽  
Disease Surveillance ◽  
Support Functions ◽  
The Core ◽  
Disease Surveillance System
Sign in / Sign up

Export Citation Format

Share Document