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中国防痨杂志 ›› 2018, Vol. 40 ›› Issue (2): 200-206.doi: 10.3969/j.issn.1000-6621.2018.02.017

• 论著 • 上一篇    下一篇

2011—2016年合肥市非结核病防治机构网络报告肺结核患者追踪未到位的影响因素分析

曹红(),王莉丽,邓继祥   

  1. 安徽医科大学公共卫生学院2013级(邓继祥)
  • 收稿日期:2017-08-09 出版日期:2018-02-10 发布日期:2018-03-14

Analysis on influencing factors of tracking failure among reported pulmonary tuberculosis cases in internet-based reporting system from 2011 to 2016 in Hefei

Hong CAO(),Li-li WANG,Ji-xiang. DENG   

  1. Division of Tuberculosis Control and Prevention, the Center for Disease Control and Prevention in Hefei City, Hefei 230001, China
  • Received:2017-08-09 Online:2018-02-10 Published:2018-03-14

摘要: 目的

分析合肥市非结核病防治机构(简称“非结防机构”)网络报告肺结核患者追踪未到位原因及其影响因素,以提高总体到位率。

方法

收集《结核病信息管理系统》中2011—2016年合肥市非结防机构网络报告应转诊的37854例肺结核患者及疑似肺结核患者信息,运用Excel及SPSS 19.0软件进行相关数据的整理、汇总及统计分析,以构成比作为主要评价指标;采用logistic回归分析相关影响因素,以P<0.05为差异有统计学意义。

结果

2011—2016年各级各类非结防机构共报告应转诊的肺结核患者及疑似肺结核患者中,总体到位患者36286例(95.86%);应追踪患者16484例,追踪到位患者14916例(90.49%),追踪未到位患者1561例(9.47%),7例(0.04%)患者无追踪信息。1561例未到位原因分别为患者自身因素(45.04%,703/1561)、非结防机构因素(29.34%,458/1561)及结防机构因素(25.62%,400/1561)。单因素分析显示:患者的年龄、报告医院类别、现住址所属地区、职业、患者分类对患者是否能追踪到位均有不同程度的影响(χ 2值分别为33.19、938.83、206.13、26.71、24.64,P值均<0.001);多因素logistic回归分析显示:患者的年龄、报告医院类别、现住址所属地区、职业均为患者追踪未到位的主要影响因素(Wald χ 2值分别为39.65、621.62、288.81、25.65,P值均<0.001)。

结论

患者年龄、报告医院类别、住址所属地区和职业等为追踪未到位的影响因素,应增加结防机构与非结防机构的交流、沟通,加强对非结防机构结核病归口管理工作的培训和督查,以提高肺结核患者总体到位率。

关键词: 结核, 病人转诊, 失随访, 因素分析, 统计学

Abstract: Objective

To explore the reasons and influencing factors of tracking failure among reported pulmonary tuberculosis (PTB) cases from Internet-based report by non-TB control institution (NTI)in Hefei, in order to improve the overall arrival rate.

Methods

The data of 37854 PTB and suspected PTB patients, who should be referred, reported by NTI of Hefei in 2011-2016 the TB information management system were collected from TB Information Management System. All analysis (e.g. collation, summary and statistical analysis) was performed using Excel and SPSS (version 19.0). The constituent ratio was the main evaluation index. Logistic regression was used to analyze the related factors and P values less than 0.05 was considered statistically significant.

Results

Among the PTB and suspected PTB patients who should be referred reported by all kinds of NTI in 2011-2016, 36286 (95.86%) referral cases arrived. A total of 16484 cases should be tracked, 14916 (90.49%) cases arrived and 1561 (9.47%) cases didn’t arrived, and 7 (0.04%) cases had no track information. The reasons for 1561 cases did not arrive included factors of patients (45.04%, 703/1561), factors of NTI (29.34%, 458/1561) and factors of TB control institution (25.62%, 400/1561). Single factor analysis showed that the age of the patient, the type of reported hospital, location of the present address, occupation, and the classification of patients had different level of effects on whether the patients could be tracked (χ 2 values were 33.19, 938.83, 206.13, 26.71, 24.64, Ps<0.001). Multivariate logistic regression analysis showed that the age of the patient, the type of reported hospital, location of the present address, and occupation played important roles in tracking failure (Wald χ 2 values were 39.65, 621.62, 288.81 and 25.65, Ps<0.001).

Conclusion

The age of the patient, the type of reported hospital, the location of the present address and occupation are important factors of tracking failure. We should increase the communication of TB control institution with NTI and strengthen the training and monitor of NTI on TB Centralized Management in order to improve the overall arrival rate of TB patients.

Key words: Tuberculosis, Patient transfer, Lost to follow-up, Factor analysis, statistical