Application of Maximum Entropy Sampling Design to Traveler Information System Data-Quality Evaluations

2015 ◽  
Vol 141 (7) ◽  
pp. 04015006
Author(s):  
James K. Richardson ◽  
Brian L. Smith
Keyword(s):  
Information System ◽  
Data Quality ◽  
Maximum Entropy ◽  
Sampling Design ◽  
Traveler Information ◽  
System Data

Quality of Routine Health Information System Data and Associated Factors Among Departments in Public Health Facilities of Harari Region, Ethiopia

2021 ◽  
Author(s):  
Adisu Tafari Shama ◽  
Hirbo Shore Roba ◽  
Admas Abera ◽  
Negga Baraki
Keyword(s):  
Public Health ◽  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Health Information System ◽  
Health Facilities ◽  
Quality Data ◽  
Public Health Facilities ◽  
System Data

Abstract Background: Despite the improvements in the knowledge and understanding of the role of health information in the global health system, the quality of data generated by a routine health information system is still very poor in low and middle-income countries. There is a paucity of studies as to what determines data quality in health facilities in the study area. Therefore, this study was aimed to assess the quality of routine health information system data and associated factors in public health facilities of Harari region, Ethiopia.Methods: A cross-sectional study was conducted in all public health facilities in Harari region of Ethiopia. The department-level data were collected from respective department heads through document reviews, interviews, and observation check-lists. Descriptive statistics were used to data quality and multivariate logistic regression was run to identify factors influencing data quality. The level of significance was declared at P-value <0.05. Result: The study found a good quality data in 51.35% (95% CI, 44.6-58.1) of the departments in public health facilities in Harari Region. Departments found in the health centers were 2.5 times more likely to have good quality data as compared to departments found in the health posts. The presence of trained staffs able to fill reporting formats (AOR=2.474; 95%CI: 1.124-5.445) and provision of feedback (AOR=3.083; 95%CI: 1.549-6.135) were also significantly associated with data quality. Conclusion: The level of good data quality in the public health facilities was less than the expected national level. Training should be provided to increase the knowledge and skills of the health workers.

scholarly journals An assessment of routine primary care health information system data quality in Sofala Province, Mozambique

2011 ◽  
Vol 9 (1) ◽  
Author(s):  
Sarah Gimbel ◽  
Mark Micek ◽  
Barrot Lambdin ◽  
Joseph Lara ◽  
Marina Karagianis ◽  
...  
Keyword(s):  
Primary Care ◽  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Health Information System ◽  
Primary Care Health ◽  
System Data ◽  
Care Health

scholarly journals Assessment of quality of routine health information system data and associated factors among departments in public health facilities of Harari region, Ethiopia

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Adisu Tafari Shama ◽  
Hirbo Shore Roba ◽  
Admas Abera Abaerei ◽  
Teferi Gebru Gebremeskel ◽  
Negga Baraki
Keyword(s):  
Public Health ◽  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Health Information System ◽  
Health Facilities ◽  
Quality Data ◽  
Public Health Facilities ◽  
System Data

Abstract Background Despite the improvements in the knowledge and understanding of the role of health information in the global health system, the quality of data generated by a routine health information system is still very poor in low and middle-income countries. There is a paucity of studies as to what determines data quality in health facilities in the study area. Therefore, this study was aimed to assess the quality of routine health information system data and associated factors in public health facilities of Harari region, Ethiopia. Methods A cross-sectional study was conducted in all public health facilities in the Harari region of Ethiopia. The department-level data were collected from respective department heads through document reviews, interviews, and observation checklists. Descriptive statistics were used to data quality and multivariate logistic regression was run to identify factors influencing data quality. The level of significance was declared at P value < 0.05. Result The study found good quality data in 51.35% (95% CI 44.6–58.1) of the departments in public health facilities in the Harari Region. Departments found in the health centers were 2.5 times more likely to have good quality data as compared to those found in the health posts. The presence of trained staffs able to fill reporting formats (AOR = 2.474; 95% CI 1.124–5.445) and provisions of feedbacks (AOR = 3.083; 95% CI 1.549–6.135) were also significantly associated with data quality. Conclusion The level of good data quality in the public health facilities was less than the expected national level. Lack of trained personnel able to fill the reporting format and feedback were the factors that are found to be affecting data quality. Therefore, training should be provided to increase the knowledge and skills of the health workers. Regular supportive supervision and feedback should also be maintained.

DATA SECURITY USING RC6 CIPHER ALGORITHM AS AN IMPLEMENTATION OF PRIVACY PRINCIPLE IN THE UU-ITE PERSPECTIVE AND ISLAMIC LAW

2020 ◽  
Author(s):  
Dedy Agung Prabowo ◽  
Ujang Juhardi ◽  
Bambang Agus Herlambang
Keyword(s):  
Information Technology ◽  
Information System ◽  
Computer Technology ◽  
Data Security ◽  
Block Cipher ◽  
Islamic Law ◽  
Important Thing ◽  
Is Security ◽  
Privacy Principle ◽  
System Data

Recently, Information technology develops rapidly. It is possible for us to get some informationquickly, properly and efficiently. The information technology also has many advantages fo r people. Theneed for information is increasing according to the need of its users. This proves that informationtechnology can make our job easier and it can help us to save our time particularly for the job thatrelated to information and data processin g. With the increasing use of computer technology today, italso brings up some problems. One of them is security and confidentiality problem which is animportant aspect in an information system. Data security is an important thing in maintaining theconf identiality of particular data that only can be known by those who have right. RC6 is a symmetrickey algorithm which encrypts 128 bit plaintext blocks to 128 bit ciphertext blocks. The encryptionprocess involves four operations which is the critical arit hmetic operation of this block cipher. As alegal state, Indonesia has issued a regulation in a form of laws governing information and electronictransaction or commonly referred to UU ITE. Besides, Islam is a religion that comprehensively givesthe guidan ce of life for people. Islam has provided guidance in the various fields ranging from social,politics, economics and various other fields.

Automatic Identification of Roadway Horizontal Alignment Information Using Geographic Information System Data: CurvS Tool

2021 ◽  
pp. 036119812110363
Author(s):  
Bekir Bartin ◽  
Sami Demiroluk ◽  
Kaan Ozbay ◽  
Mojibulrahman Jami
Keyword(s):  
Information System ◽  
New Jersey ◽  
Geographic Information System ◽  
Geographic Information ◽  
Automatic Identification ◽  
Web Based ◽  
Horizontal Alignment ◽  
System Data ◽  
Overlap Ratio ◽  
Geographic Information System Data

This paper introduces CurvS, a web-based tool for researchers and analysts that automatically extracts, visualizes, and analyzes roadway horizontal alignment information using readily available geographic information system roadway centerline data. The functionalities of CurvS are presented along with a brief background on its methodology. The validation of its estimation results are presented using actual horizontal alignment data from two different roadway types: Route 83, a two-lane two-way rural roadway in New Jersey and I-80, a freeway segment in Nevada. Different metrics are used for validation. These are identification rates of curved and tangent sections, overlap ratio of curved and tangent sections between estimated and actual horizontal alignment data, and percent fit of curve radii. The validation results show that CurvS is able to identify all the curves on these two roadways, and the estimated section lengths are significantly close to the actual alignment data, especially for the I-80 freeway segment, where 90% of curved length and 94% of tangent section length are correctly matched. Even when curves have small central angles, such as the ones in Route 83, CurvS’s estimations covers 71% of curved length and 96% of tangent section length.

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