[Thoughts and suggestions on arrangement, analysis and summary of medical data during COVID-19 epidemic].
2019-nCoV
COVID-19
clinical research
data application
epidemic situation
mixed research
Journal
Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica
ISSN: 1001-5302
Titre abrégé: Zhongguo Zhong Yao Za Zhi
Pays: China
ID NLM: 8913656
Informations de publication
Date de publication:
Apr 2020
Apr 2020
Historique:
entrez:
4
6
2020
pubmed:
4
6
2020
medline:
6
6
2020
Statut:
ppublish
Résumé
The analysis and utilization of clinical scientific research data is an effective means to promote the progress of diagnosis and treatment, and a key step in the development of medical sciences. During the epidemic of coronavirus disease 2019(COVID-19), how to transform the limited diagnostic data into clinical research resources has attracted much attention. Based on the low efficiency of data collection and extraction, the inconsistency of data analysis, the irregularity of data report and the high timeliness of data update during the epidemic, this paper briefly analyzed the background and reasons of data application under the current situation, and then discusses the problems and feasible solutions of clinical data applications under the epidemic situation and, more importantly, for future medical clinical research methods. We put forward several methodological suggestions: ① gradually improve the medical big data model and establish the national medical health data center; ② improve the scientific research literacy of medical staff and popularize the basic skills and knowledge of GCP; ③ promote a scientific, networked and shared data collection and management mode; ④ use the mixed research method and collective analysis to improve the efficiency of clinical data analysis; ⑤ pay attention to narration of the medical feelings and emphasize the humanistic data of clinical medicine. It is expected to promote the standardized and reasonable use of clinical scientific research data, the rigorous integration of expert opinions, and ultimately the development of big data for national health care.
Identifiants
pubmed: 32489030
doi: 10.19540/j.cnki.cjcmm.20200302.504
doi:
Types de publication
Journal Article
Langues
chi
Sous-ensembles de citation
IM