Proceedings of the 2nd International Conference on Social Science, Humanity and Public Health (ICOSHIP 2021)

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Design Clinical Decision Support System (CDSS) in Electronic Health Record to Early Detection of Stroke Disease, Diabetes Mellitus and to Prevent Interaction of Drug Content

Authors
Feby Erawantini1, *, Arinda Lironika Suryana2, Rinda Nurul Karimah3, Arief Setyoargo4, Nachrul Jinan5, Khoirunnisa Afandi6, Nugroho Setyo Wibowo7, Asmak Afriliana8, Raden Roro Lia Chairina9
1, 2, 3,Department of Health, Politeknik Negeri Jember, Indonesia
4Department of Education and Research, RSUD dr. Soebandi Jember, Indonesia
5Department of Medical Record, RSUD dr. R. Soedarsono, Indonesia
6Department of Information Technology, Institut Teknologi Sepuluh Nopember, Indonesia
7Department of Information Technology, Politeknik Negeri Jember, Indonesia
8Department of Food Science,,Universitas Jember, Indonesia
9Department of Agribusiness Management, Politeknik Negeri Jember, Indonesia
*Corresponding author. Email: feby_erawantini@polije.ac.id
Corresponding Author
Feby Erawantini
Available Online 17 February 2022.
DOI
10.2991/assehr.k.220207.054How to use a DOI?
Keywords
Design; Clinical Decision Support System; Electronic Health Record
Abstract

Hospitals must provide the best service to patients. There are include speed in service, on-time, and safe from medical errors. Quality of care depends on quality electronic medical records. Electronic medical records contain social data and patient medical data. The advantages of medical records are data stored in structured files, and timely filling, data can be recalled at any time, ensures patient confidentiality, and ensures patient safety. One of the indicators of electronic health records is clinical decision support systems (CDSS). This study aims to design a clinical decision support system (CDSS) in Electronic Health Records for early detection of stroke disease and to prevent interaction drug content. The method Methode for System Development used Waterfall and System Requirements Analysis was analysed by qualitative. The results of this research are to design a clinical decision support system (CDSS) in Electronic Health Records to early detection of stroke disease and to prevent interaction drug content.

Copyright
© 2022 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the 2nd International Conference on Social Science, Humanity and Public Health (ICOSHIP 2021)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
17 February 2022
ISBN
10.2991/assehr.k.220207.054
ISSN
2352-5398
DOI
10.2991/assehr.k.220207.054How to use a DOI?
Copyright
© 2022 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

risenwbib
TY  - CONF
AU  - Feby Erawantini
AU  - Arinda Lironika Suryana
AU  - Rinda Nurul Karimah
AU  - Arief Setyoargo
AU  - Nachrul Jinan
AU  - Khoirunnisa Afandi
AU  - Nugroho Setyo Wibowo
AU  - Asmak Afriliana
AU  - Raden Roro Lia Chairina
PY  - 2022
DA  - 2022/02/17
TI  - Design Clinical Decision Support System (CDSS) in Electronic Health Record to Early Detection of Stroke Disease, Diabetes Mellitus and to Prevent Interaction of Drug Content
BT  - Proceedings of the 2nd International Conference on Social Science, Humanity and Public Health (ICOSHIP 2021)
PB  - Atlantis Press
SP  - 307
EP  - 310
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.220207.054
DO  - 10.2991/assehr.k.220207.054
ID  - Erawantini2022
ER  -