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评估孟加拉国农村地区基于移动医疗的家庭新生儿评估中社区卫生工作者的表现。

Evaluation of community health worker's performance at home-based newborn assessment supported by mHealth in rural Bangladesh.

机构信息

Environmental Intervention Unit, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.

Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.

出版信息

BMC Pediatr. 2022 Apr 22;22(1):218. doi: 10.1186/s12887-022-03282-6.

Abstract

BACKGROUND

In low to middle-income countries where home births are common and neonatal postnatal care is limited, community health worker (CHW) home visits can extend the capability of health systems to reach vulnerable newborns in the postnatal period. CHW assessment of newborn danger signs supported by mHealth have the potential to improve the quality of danger sign assessments and reduce CHW training requirements. We aim to estimate the validity (sensitivity, specificity, positive and negative predictive value) of CHW assessment of newborn infants aided by mHealth compared to physician assessment.

METHODS

In this prospective study, ten CHWs received five days of theoretical and hands-on training on the physical assessment of newborns including ten danger signs. CHWs assessed 273 newborn infants for danger signs within 48 h of birth and then consecutively for three days. A physician repeated 20% (n = 148) of the assessments conducted by CHWs. Both CHWs and the physician evaluated newborns for ten danger signs and decided on referral. We used the physician's danger sign identification and referral decision as the gold standard to validate CHWs' identification of danger signs and referral decisions.

RESULTS

The referrals made by the CHWs had high sensitivity (93.3%), specificity (96.2%), and almost perfect agreement (K = 0.80) with the referrals made by the physician. CHW identification of all the danger signs except hypothermia showed moderate to high sensitivity (66.7-100%) compared to physician assessments. All the danger signs assessments except hypothermia showed moderate to high positive predictive value (PPV) (50-100%) and excellent negative predictive value (NPV) (99-100%). Specificity was high (99-100%) for all ten danger signs.

CONCLUSION

CHW's identification of neonatal danger signs aided by mHealth showed moderate to high validity in comparison to physician assessments. mHealth platforms may reduce CHW training requirements and while maintaining quality CHW physical assessment performance extending the ability of health systems to provide neonatal postnatal care in low-resource communities.

TRIAL REGISTRATION

clinicaltrials.gov NCT03933423 , January 05, 2019.

摘要

背景

在中低收入国家,家庭分娩较为常见,新生儿产后护理有限,社区卫生工作者(CHW)家访可以扩展卫生系统的能力,以便在产后期间为弱势新生儿提供服务。由 mHealth 支持的 CHW 对新生儿危险征象的评估有可能提高危险征象评估的质量,并降低 CHW 培训的要求。我们旨在评估与医生评估相比,mHealth 辅助的 CHW 对新生儿的评估的有效性(敏感性、特异性、阳性和阴性预测值)。

方法

在这项前瞻性研究中,十名 CHW 接受了五天关于新生儿体格评估的理论和实践培训,包括十个危险征象。CHW 在出生后 48 小时内对 273 名新生儿进行了危险征象评估,然后连续三天进行评估。一名医生对 CHW 进行的 20%(n=148)评估进行了重复。CHW 和医生都对十个危险征象的新生儿进行了评估并决定是否转诊。我们使用医生的危险征象识别和转诊决定作为金标准,以验证 CHW 对危险征象的识别和转诊决策。

结果

CHW 的转诊具有很高的敏感性(93.3%)、特异性(96.2%)和几乎完美的一致性(K=0.80),与医生的转诊结果一致。与医生评估相比,CHW 对除低体温以外的所有危险征象的识别都具有中等至高的敏感性(66.7-100%)。除低体温外,所有危险征象的评估都具有中等至高的阳性预测值(PPV)(50-100%)和极好的阴性预测值(NPV)(99-100%)。所有十个危险征象的特异性均很高(99-100%)。

结论

与医生评估相比,mHealth 辅助的 CHW 对新生儿危险征象的识别具有中等至高的有效性。mHealth 平台可以降低 CHW 培训的要求,同时保持 CHW 体格评估的质量,从而扩展卫生系统在资源匮乏社区提供新生儿产后护理的能力。

试验注册

clinicaltrials.gov NCT03933423 ,2019 年 1 月 5 日。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43b9/9027479/c292f90d8907/12887_2022_3282_Fig1_HTML.jpg

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