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医院分级管理工作在我省已经全面展开,各级医院在“达标上等”的过程中,使医院队伍素质、基础质量、技术水平、管理水平得到明显的提高。过去不甚被重视的信息统计工作也随着医院达标工作的开展出现了可喜的局面。那么评审后的统计信息工作如何巩固、完善、提高其成果,不断解决工作中存在问题,如何在第二周期评审工作中再上一个台阶,是各级医院信息统计人员必然要遇到的问题。对此,笔者就工作体会谈三点看法。 1 努力使统计工作规范化、标准化、制度化 医院分级管理中对信息统计所制定的标准体系,是各级医院工作的目标和准则,要严格遵照执行。并在执行工作中注重实效,不断提高基础质量,提高技术水平,提高管理水平,将“达标上等”过程中制定的各项制度、标准、要求以及一些好的做法,好的经验,不断的加以总结,用规范化、制度化的形式固定下来,并坚持下去。如:统计资料的整理,要求统计人员首先要严格审核资料无误,然后将具有科学性的数据规范化、系统化地分组规纳汇总。数据经集约化整理后,应
The hospital classification management work has been fully carried out in our province. The hospitals at all levels have significantly improved the quality, basic quality, technical level, and management level of the hospital team in the process of “reaching the standard”. In the past, the information statistics work that was not highly valued also showed a gratifying situation as the hospital’s compliance work progressed. Therefore, how to consolidate, improve, and improve the results of post-assessment statistical information, continuously solve problems in the work, and how to go a step further in the second cycle of review work is an inevitable problem for information statisticians at all levels of hospitals. In this regard, the author has three points of view on working-body talks. 1 Efforts to standardize, standardize, and institutionalize statistical work The standard system developed for information statistics in the hierarchical management of hospitals is the goal and criteria for the work of hospitals at all levels and must be strictly followed. In the implementation work, we will focus on practical results, continuously improve the quality of our infrastructure, raise the technological level, and improve the management level. We will work out various systems, standards, and requirements as well as some good practices, good experiences, and continuous Summarize it, use a standardized, institutionalized form, and stick to it. Such as: the finishing of statistical data, requiring statisticians to first strictly review the data is correct, and then will have scientific data standardized, systematic grouping and aggregation. After the data has been intensively sorted, it should be