Motivating Developers to Use Interoperable Standards for Data in Pandemic Health Apps

被引：1

作者：

Muzoora, Michael Rusongoza ^{[1
,2
]}

El-Badawi, Nabil ^{[1
,2
]}

Elsner, Christian ^{[5
]}

Essenwanger, Andrea ^{[1
]}

Gocke, Peter ^{[2
]}

Krefting, Dagmar ^{[3
]}

Poyraz, Rasim Atakan ^{[1
,2
]}

Pryss, Ruediger ^{[6
]}

Sax, Ulrich ^{[4
]}

Thun, Sylvia ^{[1
,2
,3
]}

机构：

[1] Charite Univ Med Berlin, Berlin Inst Hlth, Berlin, Germany

[2] Charite Univ Med Berlin, Berlin, Germany

[3] Hsch Niederrhein Univ Appl Sci, Krefeld, Germany

[4] Univ Med Gottingen, Gottingen, Germany

[5] Univ Med Mainz, Mainz, Germany

[6] Univ Klinikum Wurzburg, Wurzburg, Germany

来源：

PUBLIC HEALTH AND INFORMATICS, PROCEEDINGS OF MIE 2021 | 2021年 / 281卷

关键词：

Pandemic app; COVID-19; interoperability; healthcare data;

D O I：

10.3233/SHTI210339

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The COVID-19 pandemic has brought along a massive increase in app development. However, most of these apps are not using interoperable data. The COMPASS project of the German COVID-19 Research Network of University Medicine ("Netzwerk Universitatsmedizin (NUM)") tackles this issue, by offering open-source technology, best practice catalogues, and suggestions for designing interoperable pandemic health applications (https://www.netzwerkuniversitaetsmedizin.de/projekte/compass). Therefore, COMPASS conceived a framework that includes automated conformity checks as well as reference implementations for more efficient and pandemic-tailored app developments. It further aims to motivate and support developers to use interoperable standards.

引用

页码：1027 / 1028

页数：2

共 3 条

[1]

[Anonymous], 2020, Profile | COMPASS

[2] The COVID-19 Pandemic Highlights Shortcomings in US Health Care Informatics Infrastructure: A Call to Action [J].

O'Reilly-Shah, Vikas N. ;

Gentry, Katherine R. ;

Van Cleve, Wil ;

Kendale, Samir M. ;

Jabaley, Craig S. ;

Long, Dustin R. .

ANESTHESIA AND ANALGESIA, 2020, 131 (02) :340-344

[3] The German Corona Consensus Dataset (GECCO): a standardized dataset for COVID-19 research in university medicine and beyond [J].

Sass, Julian ;

Bartschke, Alexander ;

Lehne, Moritz ;

Essenwanger, Andrea ;

Rinaldi, Eugenia ;

Rudolph, Stefanie ;

Heitmann, Kai U. ;

Vehreschild, Joerg J. ;

von Kalle, Christof ;

Thun, Sylvia .

BMC MEDICAL INFORMATICS AND DECISION MAKING, 2020, 20 (01)

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