Feasibility of an innovative electronic mobile system to assist health workers to collect accurate, complete and timely data in a malaria control programme in a remote setting in Kenya

• Published in: Malaria journal Vol. 14; no. 422; p. 430
• Main Authors: Soti, David O, Kinoti, Stephen N, Omar, Ahmeddin H, Logedi, John, Mwendwa, Teresa K, Hirji, Zahra, Ferro, Santiago
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 04.11.2015; BioMed Central
• Subjects: Adolescent; Adult; Aged; Aged, 80 and over; Analysis; Automatic Data Processing; Care and treatment; Child; Child, Preschool; Complications and side effects; Electronic Health Records; Electronics - methods; Epidemiological Monitoring; Female; Health aspects; Humans; Infant; Infant, Newborn; Kenya; Malaria; Malaria - diagnosis; Malaria - epidemiology; Malaria - prevention & control; Male; Medical personnel; Middle Aged; Physician and patient; Practice; Reminder Systems; Workers; Young Adult; Kenya
• ISSN: 1475-2875; 1475-2875
• DOI: 10.1186/s12936-015-0965-z

The cornerstone of decision making aimed at improving health services is accurate and timely health information. The Ministry of Public Health and Sanitation in Kenya decided to pilot feasibility of Fionet, an innovation that integrates diagnostics, data capture and cloud services, in its malaria control programme to demonstrate usability and feasibility by primary level workers in a remote setting in Kenya. Eleven sites comprising one sub-district hospital, ten health centres and dispensaries were selected in three districts of Kisumu County to participate. Two health workers per site were selected, trained over a two-day period in the use of the Deki Reader™ to undertake rapid diagnostic testing (RDT) for malaria and data capture of patients' records. Health managers in the three districts were trained in the use of Fionet™ portal (web portal to cloud based information) to access the data uploaded by the Deki Readers. Field Support was provided by the Fio Corporation representative in Kenya. A total of 5812 malaria RDTs were run and uploaded to the cloud database during this implementation research study. Uploaded data were automatically aggregated into predetermined reports for use by service managers and supervisors. The Deki Reader enhanced the performance of the health workers by not only guiding them through processing of a malaria RDT test, but also by doing the automated analysis of the RDT, capturing the image, determining whether the RDT was processed according to guidelines, and capturing full patient data for each patient encounter. Supervisors were able to perform remote Quality assurance/Quality control (QA/QC) activities almost in real time. Quality, complete and timely data collection by health workers in a remote setting in Kenya is feasible. This paperless innovation brought unprecedented quality control and quality assurance in diagnosis, care and data capture, all in the hands of the health worker at point of care in an integrated way.