中华检验医学杂志
中華檢驗醫學雜誌
중화검험의학잡지
CHINESE JOURNAL OF LABORATORY MEDICINE
2015年
8期
573-576
,共4页
临床实验室技术%标本制备%临床实验室信息系统%时间%比例危险度模型
臨床實驗室技術%標本製備%臨床實驗室信息繫統%時間%比例危險度模型
림상실험실기술%표본제비%림상실험실신식계통%시간%비례위험도모형
Clinical laboratory techniques%Specimen handling%Clinical laboratory information systems%Time%Proportional hazards models
目的:探讨影响实验室内标本周转时间的危险因素并建立比例风险模型。方法回顾性研究,邢台市第三医院检验科2014年1至6月住院急诊血常规标本,随机选取5周数据,共904份,记录标本信息包括:测定日期、送到时间、审核时间、标本状态、消耗时间、测定时段、操作者、项目组合、延时因素、血小板计数、30 min处理结果及测定星期。采用SPSS17.0进行统计分析,对以上指标先行 COX 单因素分析,再行逐步 COX 多因素回归分析。结果规定时间内发送421份,占46.6%;10、20、30、40及50 min发送率分别为10.4%、24.7%、46.6%、58.7%和82.1%;单因素COX分析显示:送到时间、标本状态、测定时段、操作者、项目组合、延时因素对标本周转时间延迟有统计学意义均( P均<0.05);COX多因素分析显示:正确的送到时间为缩短标本周转时间有利因素( Wald=40.446,P=0.000),非正常上班测定时段、项目组合、体检标本和交接班因素为缩短标本周转时间不利因素(Wald=7.904、38.029、42.874、18.617,P=0.005、0.000、0.000、0.000),5号操作者为缩短标本周转时间有利因素(Wald=11.039, P=0.001),3号和10号操作者为缩短标本周转时间不利因素(Wald=6.432、24.242,P=0.011、0.000),其他操作者则无明显差异(P均>0.05)。结论送到时间、测定时段、操作者、项目组合、延时因素是导致实验室内标本周转时间延迟的独立危险因素,其他实验室可根据本医院标本运送、检测流程、主要影响因素等确定比例风险模型的变量数量,对标本处理过程各因素量化评价并加以改善,实现实验室内标本周转时间大幅缩短。(中华检验医学杂志,2015,38:573-576)
目的:探討影響實驗室內標本週轉時間的危險因素併建立比例風險模型。方法迴顧性研究,邢檯市第三醫院檢驗科2014年1至6月住院急診血常規標本,隨機選取5週數據,共904份,記錄標本信息包括:測定日期、送到時間、審覈時間、標本狀態、消耗時間、測定時段、操作者、項目組閤、延時因素、血小闆計數、30 min處理結果及測定星期。採用SPSS17.0進行統計分析,對以上指標先行 COX 單因素分析,再行逐步 COX 多因素迴歸分析。結果規定時間內髮送421份,佔46.6%;10、20、30、40及50 min髮送率分彆為10.4%、24.7%、46.6%、58.7%和82.1%;單因素COX分析顯示:送到時間、標本狀態、測定時段、操作者、項目組閤、延時因素對標本週轉時間延遲有統計學意義均( P均<0.05);COX多因素分析顯示:正確的送到時間為縮短標本週轉時間有利因素( Wald=40.446,P=0.000),非正常上班測定時段、項目組閤、體檢標本和交接班因素為縮短標本週轉時間不利因素(Wald=7.904、38.029、42.874、18.617,P=0.005、0.000、0.000、0.000),5號操作者為縮短標本週轉時間有利因素(Wald=11.039, P=0.001),3號和10號操作者為縮短標本週轉時間不利因素(Wald=6.432、24.242,P=0.011、0.000),其他操作者則無明顯差異(P均>0.05)。結論送到時間、測定時段、操作者、項目組閤、延時因素是導緻實驗室內標本週轉時間延遲的獨立危險因素,其他實驗室可根據本醫院標本運送、檢測流程、主要影響因素等確定比例風險模型的變量數量,對標本處理過程各因素量化評價併加以改善,實現實驗室內標本週轉時間大幅縮短。(中華檢驗醫學雜誌,2015,38:573-576)
목적:탐토영향실험실내표본주전시간적위험인소병건립비례풍험모형。방법회고성연구,형태시제삼의원검험과2014년1지6월주원급진혈상규표본,수궤선취5주수거,공904빈,기록표본신식포괄:측정일기、송도시간、심핵시간、표본상태、소모시간、측정시단、조작자、항목조합、연시인소、혈소판계수、30 min처리결과급측정성기。채용SPSS17.0진행통계분석,대이상지표선행 COX 단인소분석,재행축보 COX 다인소회귀분석。결과규정시간내발송421빈,점46.6%;10、20、30、40급50 min발송솔분별위10.4%、24.7%、46.6%、58.7%화82.1%;단인소COX분석현시:송도시간、표본상태、측정시단、조작자、항목조합、연시인소대표본주전시간연지유통계학의의균( P균<0.05);COX다인소분석현시:정학적송도시간위축단표본주전시간유리인소( Wald=40.446,P=0.000),비정상상반측정시단、항목조합、체검표본화교접반인소위축단표본주전시간불리인소(Wald=7.904、38.029、42.874、18.617,P=0.005、0.000、0.000、0.000),5호조작자위축단표본주전시간유리인소(Wald=11.039, P=0.001),3호화10호조작자위축단표본주전시간불리인소(Wald=6.432、24.242,P=0.011、0.000),기타조작자칙무명현차이(P균>0.05)。결론송도시간、측정시단、조작자、항목조합、연시인소시도치실험실내표본주전시간연지적독립위험인소,기타실험실가근거본의원표본운송、검측류정、주요영향인소등학정비례풍험모형적변량수량,대표본처리과정각인소양화평개병가이개선,실현실험실내표본주전시간대폭축단。(중화검험의학잡지,2015,38:573-576)
Objective To explore the factors influencing the intra-laboratory turnaround time ( ILTAT) and establish a COX regression model.Methods Data of 5 weeks with a total of 904 cases from the samples of blood routine examinations from January 2014 to June 2014 in The Third Hospital of Xingtai were randomly collected.The records of the samples included test dates , times of arrival , times of test , sample statuses, time consumption, time duration, operators, project portfolios, delay, PLT counts, results of 30-minute treatment and test weeks.Based on SPSS 17.0, the above indicators were analyzed by COX single factor analysis and then COX mutiple-factor regression analysis.Results Within the prescribed time , 421 cases were sent taking up 46.6%of the total samples.The ratios of sent cases in 10, 20, 30, 40 and 50 minutes are 10.4%, 24.7%, 46.6%, 58.7% and 82.1% respectively.The results of COX single factor analysis showed that times of arrival , sample statuses, times of examination, operators, project portfolios and delay had statistical significance for ILTAT ( P<0.05 ).The results of COX multiple-factor analysis indicated that right times of arrival had a positive impact in reducing the turnaround time of samples (Wald=40.446,P=0.000);non-office hours, project portfolios, physical check samples, and handovers were unfavorable factors to shorten ILTAT ( Wald =7.904,38.029,42.874,18.617, P =0.005,0.000, 0.000,0.000);Operator 5 was a favorable factor(Wald=11.039, P=0.001) and Operator 3 and Operator 10 were unfavorable factors ( Wald =6.432, 24.242, P =0.011, 0.000 ); no obvious discrepancy was observed for other operators (P>0.05).Conclusions Times of arrival, times of test, operators, project portfolios and delay were the independent risk factors leading to the delay in ILTAT.Other laboratories could determine the variable number of proportional hazards models based on their sample transport , test procedures and principal influence factors , and carry out quantitative evaluation on the factors in sample processing for improvement.Thus, significant decrease on ILTAT would be achieved.