Suppr超能文献

电子指纹关联数据收集系统的实施:赞比亚女性性工作者中的可行性和可接受性研究

Implementation of an electronic fingerprint-linked data collection system: a feasibility and acceptability study among Zambian female sex workers.

作者信息

Wall Kristin M, Kilembe William, Inambao Mubiana, Chen Yi No, Mchoongo Mwaka, Kimaru Linda, Hammond Yuna Tiffany, Sharkey Tyronza, Malama Kalonde, Fulton T Roice, Tran Alex, Halumamba Hanzunga, Anderson Sarah, Kishore Nishant, Sarwar Shawn, Finnegan Trisha, Mark David, Allen Susan A

机构信息

Department of Epidemiology, Rollins School of Public Health, Laney Graduate School, Emory University, Atlanta, GA, USA.

Rwanda Zambia HIV Research Group, Department of Pathology and Laboratory Medicine, School of Medicine and Hubert Department of Global Health, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, CNR 4011, Atlanta, GA, 30322, USA.

出版信息

Global Health. 2015 Jun 27;11:27. doi: 10.1186/s12992-015-0114-z.

Abstract

BACKGROUND

Patient identification within and between health services is an operational challenge in many resource-limited settings. When following HIV risk groups for service provision and in the context of vaccine trials, patient misidentification can harm patient care and bias trial outcomes. Electronic fingerprinting has been proposed to identify patients over time and link patient data between health services. The objective of this study was to determine 1) the feasibility of implementing an electronic-fingerprint linked data capture system in Zambia and 2) the acceptability of this system among a key HIV risk group: female sex workers (FSWs).

METHODS

Working with Biometrac, a US-based company providing biometric-linked healthcare platforms, an electronic fingerprint-linked data capture system was developed for use by field recruiters among Zambian FSWs. We evaluated the technical feasibility of the system for use in the field in Zambia and conducted a pilot study to determine the acceptability of the system, as well as barriers to uptake, among FSWs.

RESULTS

We found that implementation of an electronic fingerprint-linked patient tracking and data collection system was feasible in this relatively resource-limited setting (false fingerprint matching rate of 1/1000 and false rejection rate of <1/10,000) and was acceptable among FSWs in a clinic setting (2% refusals). However, our data indicate that less than half of FSWs are comfortable providing an electronic fingerprint when recruited while they are working. The most common reasons cited for not providing a fingerprint (lack of privacy/confidentiality issues while at work, typically at bars or lodges) could be addressed by recruiting women during less busy hours, in their own homes, in the presence of "Queen Mothers" (FSW organizers), or in the presence of a FSW that has already been fingerprinted.

CONCLUSIONS

Our findings have major implications for key population research and improved health services provision. However, more work needs to be done to increase the acceptability of the electronic fingerprint-linked data capture system during field recruitment. This study indicated several potential avenues that will be explored to increase acceptability.

摘要

背景

在许多资源有限的环境中,卫生服务机构内部以及不同机构之间的患者身份识别是一项操作挑战。在追踪艾滋病毒风险群体以提供服务以及进行疫苗试验的背景下,患者身份误识别会损害患者护理并使试验结果产生偏差。有人提议采用电子指纹识别技术来长期识别患者,并在不同卫生服务机构之间关联患者数据。本研究的目的是确定:1)在赞比亚实施电子指纹关联数据采集系统的可行性;2)该系统在一个关键艾滋病毒风险群体——女性性工作者(FSW)中的可接受性。

方法

与一家提供生物识别关联医疗保健平台的美国公司Biometrac合作,开发了一种电子指纹关联数据采集系统,供赞比亚女性性工作者中的现场招募人员使用。我们评估了该系统在赞比亚实地使用的技术可行性,并进行了一项试点研究,以确定该系统在女性性工作者中的可接受性以及采用的障碍。

结果

我们发现,在这个相对资源有限的环境中,实施电子指纹关联患者追踪和数据收集系统是可行的(错误指纹匹配率为1/1000,错误拒绝率<1/10000),并且在诊所环境中的女性性工作者中是可接受的(拒绝率为2%)。然而,我们的数据表明,不到一半的女性性工作者在工作时被招募时愿意提供电子指纹。不提供指纹最常见的原因(工作时缺乏隐私/保密问题,通常是在酒吧或旅馆)可以通过在不太繁忙的时间、在她们自己家中、在“女族长”(女性性工作者组织者)在场的情况下或在已经采集过指纹的女性性工作者在场的情况下招募女性来解决。

结论

我们的研究结果对关键人群研究和改善卫生服务提供具有重大意义。然而,需要开展更多工作来提高电子指纹关联数据采集系统在实地招募期间的可接受性。本研究指出了几个将探索以提高可接受性的潜在途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a05e/4489038/44e5dd6bd79b/12992_2015_114_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验