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Evaluation of Community Health Workers Performance at Home Based Newborn Assessment Supported by mHealth Tool in Rural Bangladesh

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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 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 hours 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 assessment. 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 identification of neonatal danger signs aided by mHealth showed moderate to high validity in comparison to physician assessment. 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.Clinical Trial (CT) registration ID: NCT03933423 Name of the trial registry: clinicaltrials.govClinical Trial (CT) registration Date: 01/05/2019
Title: Evaluation of Community Health Workers Performance at Home Based Newborn Assessment Supported by mHealth Tool in Rural Bangladesh
Description:
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 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 hours 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 assessment.
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 identification of neonatal danger signs aided by mHealth showed moderate to high validity in comparison to physician assessment.
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.
Clinical Trial (CT) registration ID: NCT03933423 Name of the trial registry: clinicaltrials.
govClinical Trial (CT) registration Date: 01/05/2019.

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