Can mobile phones help control neglected tropical diseases? Experiences from Tanzania
Datos Bibliográficos
| ID | 4593404 |
|---|---|
| Autores | Shirin Madon (0000-0002-4497-2165, London School of Economics and Political Science, autor de correspondencia), Jackline Olanya Amaguru (London School of Economics and Political Science), Mwele Ntuli Malecela, Mwele Malecela (National Institute for Medical Research), Elizabeth Michael (0000-0002-9473-4245, University of Notre Dame), Edwin Michael (0000-0001-7940-3512) |
| Año | 2014 |
| Volumen | 102 |
| Páginas | 103-110 |
| Fecha de publicación | 2014-02-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Social Science & Medicine (JOURNAL) |
| Identificadores de la revista | ISSN: 0277-9536 • E-ISSN: 1873-5347 |
| Editorial | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.socscimed.2013.11.036 |
| PMID | 24565147 |
| OpenAlex | W2077598260 |
| Idioma | EN |
| Citas recibidas | 10 |
| Referencias citadas | 13 |
The increasing proliferation of mobiles offers possibilities for improving health systems in developing countries. A case in point is Tanzania which has piloted a mobile phone-based Management Information System (MIS) for the control of neglected tropical diseases (NTDs) where village health workers (VHWs) were given mobile phones with web-based software to test the feasibility of using frontline health workers to capture data at point of source. Based on qualitative case study research carried out in 2011, we found that providing mobile phones to VHWs has helped to increase the efficiency of routine work boosting the motivation and self-esteem of VHWs. However, despite these advantages, the information generated from the mobile phone-based NTD MIS has yet to be used to support decentralised decision-making. Even with improved technology and political will, the biggest hindrance to local usage of information for health planning is the lack of synthesised and analysed health information from the district and national levels to the villages. Without inculcating a culture of providing health information feedback to frontline workers and community organisations, the benefits of the intervention will be limited. If not addressed, this will mean that mobiles have maintained the one-way upward flow of information for NTD control and simply made reporting more hi-tech
Business · Developing country · Economic growth · Economics · Internet privacy · Mobile computing · Mobile phone · Mobile technology · Neglected tropical diseases · Public health · Socioeconomics · Tanzania · Telecommunications · Computer Science · E-Government and Public Services · ICT Impact and Policies · ICT in Developing Communities · Medicine · Nursing
Worlds apart
Understanding hard-to-reach communities
Household profiles of neglected tropical disease symptoms among children
Development and application of an electronic treatment register
Using a mHealth system to recall and refer existing clients and refer community members with health concerns to primary healthcare facilities in South Africa
Healthcare Workers’ Perspectives of mHealth Adoption Factors in the Developing World
Negating neglect
A comparative review of mobile health and electronic health utilization in sub-Saharan African countries
Who bears the cost of ‘informal mhealth’? Health-workers’ mobile phone practices and associated political-moral economies of care in Ghana and Malawi
The role of community participation for sustainable integrated neglected tropical diseases and water, sanitation and hygiene intervention programs
Mobile Phones and Economic Development in Rural Peru
Development as Freedom
Research Approaches to Mobile Use in the Developing World
Health Activism
Local Primary Health Care Committees and Community-Based Health Workers in Mkuranga District, Tanzania
Local Primary Health Care Committees and Community-Based Health Workers in Mkuranga District, Tanzania
District-based malaria epidemic early warning systems in East Africa
Mobile Phones and Economic Development in Africa
| Obras citantes distintas | 10 |
|---|---|
| Citas por año | 1,11 |
| Intervalo de citas | 2017 - 2026 (10) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 10 |