One Health and Information Management Using Big Data in Health

2022 ◽  
pp. 36-51
Author(s):  
Joaquim Teixeira Netto ◽  
Zulmira Hartz ◽  
Jorge Lima de Magalhães
Keyword(s):  
Big Data ◽  
Information Management ◽  
Health Professionals ◽  
One Health ◽  
Health Centers ◽  
Health Clinic ◽  
Health Concepts ◽  
World Information ◽  
Application Requirements ◽  
Public Health Clinic

In an increasingly connected world, information regarding the contagion and spread of COVID-19 has been an important weapon to enable better coping with the disease. The use of information technology can assist in the prevention, care, and monitoring of patients. In addition, remote service using applications avoids the overload of health centers and contagion. This research reports the experience of a research project initiated in Brazil at the Oswaldo Cruz Foundation, with the objective of developing an application and big data for the new coronavirus in a public health clinic using information management and One Health concepts. Initially, the application requirements were defined through interviews with users and health professionals. The partial results obtained so far demonstrate improvements in the different processes of the health center with the use of the application. The use of big data for the analysis of information makes it possible to define better health policies for the population in a more precise way and in a shorter time.

Health Complaints Related to Pesticide Stored at a Public Health Clinic

2000 ◽  
Vol 82 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Lina S. Balluz ◽  
Rossanne M. Philen ◽  
John Brock ◽  
Kenneth Falter ◽  
Max Kiefer ◽  
...  
Keyword(s):  
Public Health ◽  
Health Clinic ◽  
Health Complaints ◽  
Public Health Clinic

Compliance to mineral supplementation among pregnant women at a public health clinic in Malaysia

2021 ◽  
Vol 29 (6) ◽  
pp. 316-322
Author(s):  
Nurul Nabilah Ahmad Fadzil ◽  
Azura Abdul Halain ◽  
Santhi A/P Yew Roan Nee ◽  
Soh Kim Lam ◽  
Salimah Japar
Keyword(s):  
Pregnant Women ◽  
Household Income ◽  
Postpartum Haemorrhage ◽  
Simple Random Sampling ◽  
Health Clinic ◽  
Cross Sectional ◽  
Mineral Supplementation ◽  
Cross Sectional Design ◽  
Vitamin And Mineral Supplementation ◽  
Public Health Clinic

Background Prenatal supplementation has been introduced to pregnant women during early pregnancy to prevent complication to both mother and fetus. The complications include anaemia, postpartum haemorrhage, low birth weight and fetal defects. Aim To assess compliance with vitamin and mineral supplementation in pregnant women. Methods A cross-sectional design with simple random sampling was used in this study with 100 respondents who attended the maternal and child clinic in Selangor, Malaysia. Findings The findings showed that 86 respondents (86%) were compliance towards vitamin and mineral supplementation, whereas 35 respondents (35%) were non-compliance mainly due to forgetfulness. The result indicated a significant association between compliance with race (p=0.02), occupation (p<0.01), household income (p=0.02), education (p<0.01), parity (p<0.01) and trimester (p=0.02). Conclusion Majority of the respondents acknowledge that side effects and forgetfulness were the main influencing factors towards non-compliance.

scholarly journals An Accident-Prone Employee: No, Multiple Sclerosis

2017 ◽  
Vol 66 (1) ◽  
pp. 5-7
Author(s):  
Ann Regina Lurati
Keyword(s):  
Public Health ◽  
Multiple Sclerosis ◽  
Physical Examination ◽  
Review Article ◽  
Health Clinic ◽  
Workplace Interventions ◽  
Public Health Clinic

An employee is labeled “accident-prone,” and sustained an acute lumbar injury at work. Upon physical examination, a diagnosis of multiple sclerosis was suspected. She was referred to a public health clinic for further evaluation. This is a review article of multiple sclerosis and workplace interventions.

scholarly journals Student Physical Health Information Management Model under Big Data Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Hui Wang ◽  
Ning Wang ◽  
MeiJie Li ◽  
Simeng Mi ◽  
YaYa Shi
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Physical Health ◽  
Health Information ◽  
Information Management ◽  
Health Management ◽  
Health Information Management ◽  
Management Model ◽  
Student Health ◽  
Management Service

Health is considered an important foundation for students’ success. However, with the accelerated pace of life, rising pressure from various parties, weak health awareness, lack of exercise time, and other reasons, students’ physical quality is generally declining, the incidence of health diseases is increasing, and the onset age tends to be younger. With the development of the concept of “health first,” health management continues to expand and extend and students’ health management has attracted more attention from many aspects. Due to the late and low starting point of health management research and the lack of professional theoretical support, a complete, mature, and effective health management service system has not been established to deal with the students’ health. In order to make student health management more scientific, normative, and effective, this article has proposed big data technology to build the student health information management model. The first step of the approach is to store and analyze the data of students’ physical health. It is necessary to combine the data collection, supervision, data analysis, and data application of students’ physical health and gradually improve the national monitoring and evaluation system of students’ physical health. Student health check-up management platform is mainly used in realizing the school student information management and student health information relationship between system, science, standardization, and automation, and its main task is to use a computer to perform daily management of all previous medical information of students, such as query, modify, add, delete, and enhance the physical health of students information management ability given the large data analysis of useful information. In addition, we have built a doctor recommendation model based on online questions and answers to give specific health recommendations for students of different physiques.

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