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[Current situation and trend of medical laboratory results homogeneity management].
Wang, J J; Xu, L M; Yu, W J; Ke, Q; Gong, Q.
Affiliation
  • Wang JJ; Department of Laboratory Medicine, Qingpu Branch, Zhongshan Hospital, Fudan University, Shanghai 201700,China.
  • Xu LM; Department of Laboratory Medicine, Qingpu Branch, Zhongshan Hospital, Fudan University, Shanghai 201700,China.
  • Yu WJ; Department of Laboratory Medicine, Qingpu Branch, Zhongshan Hospital, Fudan University, Shanghai 201700,China.
  • Ke Q; Department of Laboratory Medicine, Qingpu Branch, Zhongshan Hospital, Fudan University, Shanghai 201700,China.
  • Gong Q; Department of Laboratory Medicine, Qingpu Branch, Zhongshan Hospital, Fudan University, Shanghai 201700,China.
Zhonghua Yu Fang Yi Xue Za Zhi ; 57(9): 1504-1509, 2023 Sep 06.
Article in Zh | MEDLINE | ID: mdl-37743315
ABSTRACT
Medical test results are indispensable and important tools in diagnosis and treatment services. It is necessary to promote the homogenization of test results first, because homogenization is the basis for mutual recognition of test results. Mutual recognition of medical test results can help share resources among medical institutions, provide more reliable test results for early prevention, screening and treatment of diseases, and reduce repeated tests, thus improving people's medical experience. In recent years, with the deepening of medical system reform and the promotion of graded diagnosis and treatment, governments have continuously introduced policies of mutual recognition of test results around country. However, homogenization is a prerequisite for mutual recognition of test results, with the emergence of intelligent medicine in the era of internet big data, opportunities and challenges coexist in the development of homogeneity management. In the future, the homogeneity of medical test results will present a trend of digitalization, automation, informatization and intelligence.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Big Data / Government Limits: Humans Language: Zh Journal: Zhonghua Yu Fang Yi Xue Za Zhi Year: 2023 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Big Data / Government Limits: Humans Language: Zh Journal: Zhonghua Yu Fang Yi Xue Za Zhi Year: 2023 Document type: Article Affiliation country: China