CAJ | 학술논문

目的通过对2013年全国卫生统计年报数据质量的评估，分析可能影响数据质量的主要因素，探索适用于卫生统计数据的质量评估方法。方法利用逻辑检查、经验比对和综合指数等方法，评估2013年卫生统计年报数据中重点指标的填报情况，综合评价各地区的数据质量。结果2013年年报数据中，固定资产的缺项率最高（占核查机构的2.74%），次均门诊费用的异常值占比最高（占核查机构的0.70%），设备总价值与设备总台数的逻辑错误率最高（占核查机构的1.01%），医院等级的编码错误率最高（占核查机构的0.34%）。年报数据质量排序靠前的省份东部地区较多，排位靠后的省份中西部地区较多。结论2013年年报数据中填报质量较差的指标和地区是日后需要加强监督检查、改进数据质量的重点；针对各种可能造成统计数据失真的因素，应制定数据质量考核办法，建立质量考核体系。
목적통과대2013년전국위생통계년보수거질량적평고，분석가능영향수거질량적주요인소，탐색괄용우위생통계수거적질량평고방법。방법이용라집검사、경험비대화종합지수등방법，평고2013년위생통계년보수거중중점지표적전보정황，종합평개각지구적수거질량。결과2013년년보수거중，고정자산적결항솔최고（점핵사궤구적2.74%），차균문진비용적이상치점비최고（점핵사궤구적0.70%），설비총개치여설비총태수적라집착오솔최고（점핵사궤구적1.01%），의원등급적편마착오솔최고（점핵사궤구적0.34%）。년보수거질량배서고전적성빈동부지구교다，배위고후적성빈중서부지구교다。결론2013년년보수거중전보질량교차적지표화지구시일후수요가강감독검사、개진수거질량적중점；침대각충가능조성통계수거실진적인소，응제정수거질량고핵판법，건립질량고핵체계。
Objective Evaluate the quality of national health statistics data in 2013, analyze the main factors that may affect the quality of data, provide reference for exploring the evaluation method of statistical data quality.Method Use the logic examination, experience comparison and comprehensive index method, Analyze the key indicate of affecting the quality of national health statistics data in 2013, comprehensively evaluate the data quality of each province.Result In the annual report of 2013, the missing rate of “the fixed assets” was the highest (accounting for 2.74%), The abnormal value ratio of “average medical expense per visit” was the highest (accounting for 0.70%), The logic error rate of “between equipment total value and the number of equipment” was the highest (accounting for 1.01%), Coding errors of “hospital grade” was the highest (accounted for 0.34%). There are more provinces in the eastern region in front of the quality ranking; there are more provinces in the central and western region in back of the quality ranking.Conclusion The indicators and area of poor quality in national health statistics data in 2013 is the key to strengthen the supervision and inspection in the future, and improve the data quality. According to various factors that may cause the quality distortion of statistical data, we should develop data quality assessment methods, and establish the quality evaluation system.