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- W4205504763 abstract "Abstract Background: Guideline-based medical care has been identified to improve outcomes in stroke. However, data acquisition and medical quality management during hospital stay still need to be improved in China. We have developed a computer-based medical data collecting system, together with automated calculation of Key Performance Indicators (KPIs) and regular individualized education, and thus aim to explore whether it can improve the medical care quality of acute ischemic stroke (AIS) during hospital stay in stroke centers. Methods: The individualized quality improvement based on the Computer Analysing system to improve Stroke management quality Evaluation (CASE) trial is a prospective, multi-center, historical control study among 30 stroke centers in China. In this trial, the data is directly extracted from the saved original medical record of each AIS patient during hospital stay, regardless of different Electronic Medical Record System (EMRS) in each center. Then the automated calculation of KPIs and the regular education via tele-conference per month allows the clinicians to examine the causes of non-compliance of guideline-based care and develop programs to decrease their frequency. Discussion: We compare KPIs between pre-intervention stage and post-intervention stage (without or with education) among stroke centers. If proved effective, this approach might be generalized around China and even worldwide, where a unified EMRS is difficult to be applied and in-patient care needs to be improved. Trial registration: clinicaltrials.gov, ID: NCT03684629. Registered on 9 December 2018. Retrospectively registered." @default.
- W4205504763 created "2022-01-26" @default.
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- W4205504763 date "2020-06-18" @default.
- W4205504763 modified "2023-10-16" @default.
- W4205504763 title "Rationale and design of individualized quality improvement based on the Computer Analysing system to improve Stroke management quality Evaluation (CASE): a multicentre historically controlled study" @default.
- W4205504763 doi "https://doi.org/10.21203/rs.2.18008/v2" @default.
- W4205504763 hasPublicationYear "2020" @default.
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