A Health Informatics Reporting System for Technology Illiterate Workforce Using Mobile Phone.


Journal

Applied clinical informatics
ISSN: 1869-0327
Titre abrégé: Appl Clin Inform
Pays: Germany
ID NLM: 101537732

Informations de publication

Date de publication:
03 2019
Historique:
entrez: 23 5 2019
pubmed: 23 5 2019
medline: 2 4 2020
Statut: ppublish

Résumé

The reduction and control over neonatal, infant, and maternal mortality is a collective mission of the World Health Organization under United Nations. This article summarizes the automation of verbal autopsy reporting for neonatal, infant, and maternal mortality with primary focus on user-centered design for technologically illiterate workforce with minimum available resources. The diminution in neonatal, infant, and maternal deaths is not possible until grassroot level quality data are available for mortality. The estimated data are less effective for developing countries like Pakistan because it has heterogeneous demographic pockets with respect to mortality causes. The Neonatal, Infant, and Maternal Death E-surveillance System is a project in which a real-time reporting system is innovated that is useful in detecting the causes of mortality and effective in adopting appropriate countermeasure policies. In a pilot study, the system was implemented initially in nine districts of Punjab, Pakistan. The initial system was refined after getting detailed feedback from district management staff including Lady Health Workers and Lady Health Supervisors. The refined surveillance system was finally implemented in all 36 districts of Punjab, Pakistan. The results exhibited 31% improvement in infant data collection and 6% improvement in maternal data collection regarding mortality. This research will be helpful in achieving the milestone of gathering real-time mortality data from grassroot level using user-centered design methodology.

Sections du résumé

BACKGROUND
The reduction and control over neonatal, infant, and maternal mortality is a collective mission of the World Health Organization under United Nations.
METHODS
This article summarizes the automation of verbal autopsy reporting for neonatal, infant, and maternal mortality with primary focus on user-centered design for technologically illiterate workforce with minimum available resources. The diminution in neonatal, infant, and maternal deaths is not possible until grassroot level quality data are available for mortality. The estimated data are less effective for developing countries like Pakistan because it has heterogeneous demographic pockets with respect to mortality causes. The Neonatal, Infant, and Maternal Death E-surveillance System is a project in which a real-time reporting system is innovated that is useful in detecting the causes of mortality and effective in adopting appropriate countermeasure policies. In a pilot study, the system was implemented initially in nine districts of Punjab, Pakistan. The initial system was refined after getting detailed feedback from district management staff including Lady Health Workers and Lady Health Supervisors. The refined surveillance system was finally implemented in all 36 districts of Punjab, Pakistan.
RESULTS
The results exhibited 31% improvement in infant data collection and 6% improvement in maternal data collection regarding mortality.
CONCLUSION
This research will be helpful in achieving the milestone of gathering real-time mortality data from grassroot level using user-centered design methodology.

Identifiants

pubmed: 31117136
doi: 10.1055/s-0039-1688830
pmc: PMC6531210
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

348-357

Informations de copyright

Georg Thieme Verlag KG Stuttgart · New York.

Déclaration de conflit d'intérêts

None declared.

Références

Reprod Health. 2015;12 Suppl 2:S9
pubmed: 26063492
Lancet. 2005 Mar 5-11;365(9462):891-900
pubmed: 15752534
Lancet. 2015 Jan 31;385(9966):430-40
pubmed: 25280870
Lancet. 2010 May 8;375(9726):1609-23
pubmed: 20382417
Lancet. 2016 May 14;387(10032):2049-59
pubmed: 26477328
Reprod Health. 2015;12 Suppl 2:S15
pubmed: 26062610
Lancet. 2016 Jan 30;387(10017):462-74
pubmed: 26584737

Auteurs

Muhammad Imran Afzal Durrani (MIA)

Department of Computer Science and IT, The University of Lahore, Lahore, Pakistan.

Noman Sohaib Qureshi (NS)

Department of Computer Science and Engineering, University of Engineering and Technology, Lahore, Pakistan.

Nadeem Ahmad (N)

Department of Computer Science and IT, The Superior University, Lahore, Pakistan.

Tabbasum Naz (T)

Department of Computer Science and IT, The University of Lahore, Lahore, Pakistan.

Alessia Amelio (A)

DIMES University of Calabria, Rende (CS), Italy.

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Classifications MeSH