Mobile phone technology for collection of monthly service statistics in Family Planning Clinics: Experience from NURHI High Volume sites in Oyo and Kaduna States

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DOI: 10.21522/TIJAR.2014.SE.19.01.Art015

Authors : Ayankola John Oluseun

Abstract:

Background: As the NURHI 2 project goes to scale, it became more expensive and inefficient to routinely collect service statistics on family planning (FP) from its high-Volume sites (HVS) through in person visits. Based on this, the NURHI team piloted and implemented the use of mobile technology to transmit data from its HVS to a central server.

To assess the effectiveness of the approach, the RM&E team carried out an evaluation of the pilot. The results from our qualitative and quantitative analysis showed that the use of mobile phone technology using DHIS2 data collection application for android phones with cloud storage system is a potentially viable means of collecting routine monitoring data from service delivery points in Oyo and Kaduna states.

Objectives/Main research question/Hypothesis and program area: The objective of this pilot is to explore the feasibility of, identify possible challenges that can affect the delivery of a proposed technology-based solutions aimed at improving the routine data monitoring flow in a timely and accurate manner from NURHI supported HVS.

Methodology (location, study design, data source, time frame, sample size, analysis approach): Participants were trained for two days on the newly designed data collection system. After reviewing the existing routine data collection system, participants were familiarized with the system to be piloted. The training included basic but important trouble shooting technics that may be required during the course of using the application. These included how to set up and download the DHIS2 apps on the device, how to collect data and how to upload data into the server. Trouble shooting tips were provided to the participants so that they can solve problems that may arise on their own.

Two months after the pilot of the phone based routine data collection system, the RM&E team evaluated the pilot system in order to know whether the approach is viable or not and if viable, learn how the approach can be improved upon based on lessons learnt.

Same set of participants that were trained and piloted the model were interviewed after twelve sessions of experience with the use of the device including two months of actual routine data collection. The RM&E team assessed the experiences of the participants during the data collection period as well as the different segments of the data collection process including use of android phone, enabling the data option of the device, entering data into DHIS2 and uploading of same into the cloud storage. We also asked questions on their experience about the use of the model and the challenges they had, it also included capturing their overall though on the model.

Over the phone, Key informant interviews (KII) using KII guide (Appendix A) were conducted with the study participants in the two states

Results/key findings: The results from our qualitative and quantitative analysis showed that the use of mobile phone technology using DHIS2 data collection application for android phones with cloud storage using the “ona.io” is a potentially viable means of collecting routine monitoring data from service delivery points in Oyo and Kaduna states.

Conclusion: The participants in the two states generally agree with most of the positive statements on the operations and use of the technology, although Kaduna participants generally have a lower ranking when compared with participants from Oyo states. While our findings showed promising potentials for this approach for the collection of routine monitoring data from the family planning service delivery points, it is also necessary to carry out minor tweaks in the design of the system especially in the type of phones to procure and use for scale up as well as the type of internet provider to subscribe to. The pilot showed that the internet network cannot be a “one size fit all”, but rather should be determined by geography and by what works best in the different locations. 

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