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Quality of Care Index (QCI) v1

Authors :
Esmaeil Mohammadi
Erfan Ghasemi
Sahar Saeedi Moghaddam
Moein Yoosefi
Ali Ghanbari
Naser Ahmadi
Masoud Masinaei
Shahin Roshani
Narges Ebrahimi
Mahtab Rouhifard Khalilabad
Maryam Nasserinejad
Sina Azadnajafabad
Bahram Mohajer
Farnam Mohebi
Negar Rezaei
Ali Mokdad
Bagher Larijani
Farshad Farzadfar
Publication Year :
2020
Publisher :
ZappyLab, Inc., 2020.

Abstract

This protocol and set of codes bring forward a newly introduced index and system that can assess the quality of care given to health-seekers on a large-scale, named the quality of care index (QCI). Foremost, QCI is designated for data miners using a large amount of data entry. Dimension reduction approaches are utilized to reduce and ease the complexity of such environments. QCI codes have been trained and built based on the Global Burden of Disease (GBD) database structure [https://vizhub.healthdata.org/gbd-compare/]. Other data sources can be fed to the code upon re-structuring to the same formate as GBD's. Only aggregates are compatible for analysis and individual data sets are not appropriate commodities. Codes are considerately embedded in R language, easily transformable to Python. Classically, we use STATA file extensions (.dta) and efforts should be carried out to reformat files into other extensions if desired. Stages of QCI computation are 1. data acquisition 2. data curation 3. data analysis and/or 4. visualization.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........a54d2efe6604a4e161bb12c36d8add2a