Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Nov 21, 2018
Open Peer Review Period: Dec 3, 2018 - Jan 28, 2019
Date Accepted: Apr 4, 2019
(closed for review but you can still tweet)
Using mHealth to support clinical decision-making to improve maternal and neonatal health outcomes in Ghana: Insights of frontline health worker information needs
ABSTRACT
Background:
Developing and maintaining resilient health systems in low resource settings like Ghana requires innovative approaches that adapt technology to context to improve health outcomes. One of such innovations was an mHealth clinical decision-making support system (CDMSS) that utilized text messaging of standard emergency maternal and neonatal protocols via an unstructured supplementary service data (USSD) on request of healthcare providers. This CDMSS was implemented in a cluster randomized controlled trial (CRCT) in the Eastern Region of Ghana.
Objective:
This study aimed to analyse the pattern of requests made to the USSD by frontline health workers. We assessed the relationship between requests made to the USSD and types of maternal and neonatal morbidities reported in health facilities (HFs).
Methods:
For clusters in the intervention arm of the CRCT, all requests to the USSD during the 18-month intervention period were extracted from a remote server, and maternal and neonatal health outcomes of interest were obtained from the District Health Information System (DHIMS-2) of Ghana. Chi-square and Fisher’s exact tests were used to compare the proportion and type of requests made to the USSD by cluster, facility type and location, whether phones accessing the intervention were shared facility phones or individual-use phones (‘type-of-phone’) or whether protocols were accessed during the day or at night (‘time-of-day’). Trends in requests made were analysed over three 6-month periods. The relationship between requests made and the number of cases reported in HFs was assessed using Spearman’s correlation.
Results:
In total, 5,329 requests from 72 (97%) participating HFs were made to the intervention. The average number of requests made per cluster was 667. Requests declined from the first to the third 6-month period (44.96%, 39.82% and 15.22% respectively). Maternal conditions accounted for most of the requests made (66.35%). The most frequently accessed maternal conditions were postpartum haemorrhage (25.23%), ‘other conditions’ (17.82%) and hypertension (16.49%), while the most frequently accessed neonatal conditions were prematurity (20.08%), sepsis (15.45%) and resuscitation (13.78%). Requests made to the CDMSS varied significantly by cluster, type of request (maternal or neonatal) facility type and its location, ‘type-of-phone’ and ‘time-of-day’ at 6-month interval (P-values <.001 for each variable). Trends in maternal and neonatal requests showed varying significance over each 6-month interval. Only asphyxia and sepsis cases showed significant correlations with the number of requests made (Spearman’s rho=.44 and .79; P-value<.001 and .03 respectively).
Conclusions:
Conclusion: There were variations in the pattern of requests made to the mHealth CDMSS over time. Detailed information regarding the use of the mHealth CDMSS provides insight into the information needs of frontline healthcare providers for decision-making and an opportunity to focus support for health worker training and ultimately improved maternal and neonatal health.
Citation
Per the author's request the PDF is not available.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.