@article {1293, title = {Designing mHealth for maternity services in primary health facilities in a low-income setting - lessons from a partially successful implementation.}, journal = {BMC Med Inform Decis Mak}, volume = {18}, year = {2018}, month = {2018 11 12}, pages = {96}, abstract = {

BACKGROUND: Increasing mobile phone ownership, functionality and access to mobile-broad band internet services has triggered growing interest to harness the potential of mobile phone technology to improve health services in low-income settings. The present project aimed at designing an mHealth system that assists midlevel health workers to provide better maternal health care services by automating the data collection and decision-making process. This paper describes the development process and technical aspects of the system considered critical for possible replication. It also highlights key lessons learned and challenges during implementation.

METHODS: The mHealth system had front-end and back-end components. The front-end component was implemented as a mobile based application while the back-end component was implemented as a web-based application that ran on a central server for data aggregation and report generation. The current mHealth system had four applications; namely, data collection/reporting, electronic health records, decision support, and provider education along the continuum of care including antenatal, delivery and postnatal care. The system was pilot-tested and deployed in selected health centers of North Shewa Zone, Amhara region, Ethiopia.

RESULTS: The system was used in 5 health centers since Jan 2014 and later expanded to additional 10 health centers in June 2016 with a total of 5927 electronic forms submitted to the back-end system. The submissions through the mHealth system were slightly lower compared to the actual number of clients who visited those facilities as verified by record reviews. Regarding timeliness, only 11\% of the electronic forms were submitted on the day of the client visit, while an additional 17\% of the forms were submitted within 10~days of clients{\textquoteright} visit. On average forms were submitted 39~days after the day of clients visit with a range of 0 to 150~days.

CONCLUSIONS: In conclusion, the study illustrated that an effective mHealth intervention can be developed using an open source platform and local resources. The system impacted key health outcomes and contributed to timely and complete data submission. Lessons learned through the process including success factors and challenges are discussed.

}, keywords = {Cell Phone, Delivery of Health Care, electronic health records, Ethiopia, Female, Health Facilities, Humans, Maternal Health Services, Mobile Applications, Poverty, Pregnancy, Telemedicine}, issn = {1472-6947}, doi = {10.1186/s12911-018-0704-9}, author = {Shiferaw, Solomon and Workneh, Andualem and Yirgu, Robel and Dinant, Geert-Jan and Spigt, Mark} } @article {1270, title = {Coverage of routine reporting on malaria parasitological testing in Kenya, 2015-2016.}, journal = {Glob Health Action}, volume = {10}, year = {2017}, month = {2017}, pages = {1413266}, abstract = {

BACKGROUND: Following the launch of District Health Information System 2 across facilities in Kenya, more health facilities are now capable of carrying out malaria parasitological testing and reporting data as part of routine health information systems, improving the potential value of routine data for accurate and timely tracking of rapidly changing disease epidemiology at fine spatial resolutions.

OBJECTIVES: This study evaluates the current coverage and completeness of reported malaria parasitological testing data in DHIS2 specifically looking at patterns in geographic coverage of public health facilities in Kenya.

METHODS: Monthly facility level data on malaria parasitological testing were extracted from Kenya DHIS2 between November 2015 and October 2016. DHIS2 public facilities were matched to a geo-coded master facility list to obtain coordinates. Coverage was defined as the geographic distribution of facilities reporting any data by region. Completeness of reporting was defined as the percentage of facilities reporting any data for the whole 12-month period or for 3, 6 and 9 months.

RESULTS: Public health facilities were 5,933 (59\%) of 10,090 extracted. Fifty-nine per Cent of the public facilities did not report any data while 36, 29 and 22\% facilities had data reported at least 3, 6 and 9 months, respectively. Only 8\% of public facilities had data reported for every month. There were proportionately more hospitals (86\%) than health centres (76\%) and dispensaries/clinics (30\%) reporting. There were significant geographic variations in reporting rates. Counties along the malaria endemic coast had the lowest reporting rate with only 1\% of facilities reporting consistently for 12 months.

CONCLUSION: Current coverage and completeness of reporting of malaria parasitological diagnosis across Kenya{\textquoteright}s public health system remains poor. The usefulness of routine data to improve our understanding of sub-national heterogeneity across Kenya would require significant improvements to the consistency and coverage of data captured by DHIS2.

}, keywords = {Health Facilities, Health information systems, Humans, Kenya, Malaria, Mandatory Reporting, Public Health Surveillance}, issn = {1654-9880}, doi = {10.1080/16549716.2017.1413266}, author = {Maina, Joseph K and Macharia, Peter M and Ouma, Paul O and Snow, Robert W and Okiro, Emelda A} }