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Discussion on rational drug equipping scheme of hospital ward rescue vehicles |
WANG Fang1 LIU Qingxiang1 YANG Moyuan1 WANG Xinhui1 ZHENG Jun1 WANG Yawei1 MA Xuehua2▲ |
1.Department of Pharmacy, Medical Supplies Center of PLA General Hospital, Beijing 100028, China;
2.Department of Military Sick and Wounded Management, the 4th Medical Center of PLA General Hospital, Beijing 100048, China
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Abstract Objective To analyze the use of the drug types and quantity of the rescue car in hospital ward, and to provide methods and suggestions for rational allocation of drugs in the rescue car. Methods Big data analysis method was used to extract and analyze the variety and quantity of drugs used in large and medium-sized rescue in a Grade-Ⅲ hospital from April 2021 to April 2022, and statistically calculate the utilization rate, convenient use frequency, the rate of meeting the rescue demand, and the use of varieties inside and outside the rescue vehicle. And the use of quartile method, according to 75% of the points to determine the number of varieties equipped with emergency vehicles, the use of Plato method to determine the rescue vehicle should be equipped with varieties. Statistics were made on the outside access of emergency vehicles after optimization, and the rationality of the optimization scheme was verified. Results The utilization rate of rescue vehicle was 62.22%, and that of outpatient medical technology department was 0. The rate of fully meeting the rescue demand was 30.65%. The dose of epinephrine was adjusted from 10 to 17, and the dose of Dopamine Hydrochloride Injection was adjusted from ten to nine. With the application of Plato analysis, it was concluded that in addition to keeping the drugs in the original fixed template, another seven drugs outside the list were equipped as unified equipment. Human blood albumin, and other varieties were added according to the drug characteristics of hepatobiliary surgery, geriatrics and other departments. The proportion of drugs was used outside emergency vehicles with optimized equipment decreased from 44% to 11%, which better met the needs of clinical first aid. Conclusion Using scientific statistical methods to optimize the emergency vehicle allocation scheme can accurately meet the emergency needs.
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