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Evaluation of community health worker's performance at home-based newborn assessment supported by mHealth in rural Bangladesh.
Jahan, Farjana; Foote, Eric; Rahman, Mahbubur; Shoab, Abul Kasham; Parvez, Sarker Masud; Nasim, Mizanul Islam; Hasan, Rezaul; El Arifeen, Shams; Billah, Sk Masum; Sarker, Supta; Hoque, Md Mahbubul; Shahidullah, Mohammad; Islam, Muhammad Shariful; Ashrafee, Sabina; Darmstadt, Gary L.
Afiliação
  • Jahan F; Environmental Intervention Unit, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh. farjana.jahan@icddrb.org.
  • Foote E; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Rahman M; Environmental Intervention Unit, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
  • Shoab AK; Environmental Intervention Unit, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
  • Parvez SM; Environmental Intervention Unit, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
  • Nasim MI; Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
  • Hasan R; Environmental Intervention Unit, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
  • El Arifeen S; Environmental Intervention Unit, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
  • Billah SM; Maternal and Child Health Division, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
  • Sarker S; Maternal and Child Health Division, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
  • Hoque MM; Faculty of Medicine and Health, Sydney School of Public Health, The University of Sydney, Sydney, Australia.
  • Shahidullah M; Environmental Intervention Unit, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
  • Islam MS; Department of Neonatology, Dhaka Shishu (Children) Hospital, Dhaka, Bangladesh.
  • Ashrafee S; Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh.
  • Darmstadt GL; National Newborn Health Program (NNHP) and Integrated Management of Childhood Illness (IMCI), Directorate General of Health Services, Dhaka, Bangladesh.
BMC Pediatr ; 22(1): 218, 2022 04 22.
Article em En | MEDLINE | ID: mdl-35459113
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.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Telemedicina / Hipotermia Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans / Infant / Newborn País/Região como assunto: Asia Idioma: En Revista: BMC Pediatr Assunto da revista: PEDIATRIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Bangladesh

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Telemedicina / Hipotermia Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans / Infant / Newborn País/Região como assunto: Asia Idioma: En Revista: BMC Pediatr Assunto da revista: PEDIATRIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Bangladesh