JMIR Publications

ABSTRACT

Background:

Mobile-health has increasing potential to address health outcomes in under-resourced settings as smart-phone coverage increases. The NeoTree is a mobile-health application co-developed in Malawi to improve the quality of newborn care at the point of admission to neonatal units. While collecting vital demographic and clinical data this interactive platform provides clinical decision-support, and training for the end-users (health care workers (HCW)), according to evidence based national and international guidelines.

Objective:

Our aims were to examine one month of data collected using the NeoTree in an outcome audit of babies admitted to a district-level neonatal nursery in Malawi and to demonstrate proof of concept of digital audit data in this setting.

Methods:

Using a phased approach over one month (21 Nov – 19 Dec, 2016), frontline HCWs were trained and supported to use the NeoTree to admit newborns. Discharge data were collected by the research team using a discharge form within the NeoTree ‘NeoDischarge’. Descriptive analysis was conducted on the exported pseudonomysed data and presented to the newborn care department as a digital audit.

Results:

Of 191 total admissions, 134 (70%) admissions were completed using the NeoTree and 129 (67%) were exported and analysed. Of these 129, 102 (79%) were discharged alive. Overall case fatality rate was 93 per 1000 admitted babies. Prematurity with respiratory distress syndrome, Birth Asphyxia, and Neonatal sepsis contributed to 41.6%, 58.3% and 16.6% of deaths respectively. Deaths may have been under-reported due to phased implementation and some families of babies with imminent deaths self-discharging home. Detailed characterisation of the data enabled departmental discussion of modifiable factors for quality improvement, for example improved thermoregulation of infants.

Conclusions:

This digital outcome audit demonstrates that data can be captured digitally at the bedside by HCWs in under-resourced newborn facilities and these data can contribute to meaningful review of quality of care/outcomes and potential modifiable factors. Coverage may be improved during future implementation by streamlining the admission process to be solely via digital format. Our results present a new methodology for newborn audit in low-resource settings and are a proof of concept for a novel newborn data system in these settings.