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A comparison of smartphones to paper-based questionnaires for routine influenza sentinel surveillance, Kenya, 2011-2012.
Njuguna, Henry N; Caselton, Deborah L; Arunga, Geoffrey O; Emukule, Gideon O; Kinyanjui, Dennis K; Kalani, Rosalia M; Kinkade, Carl; Muthoka, Phillip M; Katz, Mark A; Mott, Joshua A.
Afiliación
  • Njuguna HN; Influenza Program, Centers for Disease Control and Prevention-Kenya, P.O. Box 606, 00621, Village Market, Nairobi, Kenya. vkc7@cdc.gov.
  • Caselton DL; Influenza Program, Centers for Disease Control and Prevention-Kenya, P.O. Box 606, 00621, Village Market, Nairobi, Kenya. dcaselton@gmail.com.
  • Arunga GO; Kenya Medical Research Institute (KEMRI), Nairobi, Kenya. garunga@kemricdc.org.
  • Emukule GO; Influenza Program, Centers for Disease Control and Prevention-Kenya, P.O. Box 606, 00621, Village Market, Nairobi, Kenya. uyr9@cdc.gov.
  • Kinyanjui DK; Kenya Medical Research Institute (KEMRI), Nairobi, Kenya. dkinyanjui@kemricdc.org.
  • Kalani RM; Department of Disease Surveillance and Response (DDSR) Ministry of Health, Nairobi, Kenya. rosaliakalani@yahoo.co.uk.
  • Kinkade C; Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control, Atlanta, Georgia, USA. mke5@cdc.gov.
  • Muthoka PM; Department of Disease Surveillance and Response (DDSR) Ministry of Health, Nairobi, Kenya. epmmuthoka@gmail.com.
  • Katz MA; Influenza Program, Centers for Disease Control and Prevention-Kenya, P.O. Box 606, 00621, Village Market, Nairobi, Kenya. markakatz@gmail.com.
  • Mott JA; Influenza Program, Centers for Disease Control and Prevention-Kenya, P.O. Box 606, 00621, Village Market, Nairobi, Kenya. zud9@cdc.gov.
BMC Med Inform Decis Mak ; 14: 107, 2014 Dec 24.
Article en En | MEDLINE | ID: mdl-25539745
BACKGROUND: For disease surveillance, manual data collection using paper-based questionnaires can be time consuming and prone to errors. We introduced smartphone data collection to replace paper-based data collection for an influenza sentinel surveillance system in four hospitals in Kenya. We compared the quality, cost and timeliness of data collection between the smartphone data collection system and the paper-based system. METHODS: Since 2006, the Kenya Ministry of Health (MoH) with technical support from the Kenya Medical Research Institute/Centers for Disease Control and Prevention (KEMRI/CDC) conducted hospital-based sentinel surveillance for influenza in Kenya. In May 2011, the MOH replaced paper-based collection with an electronic data collection system using Field Adapted Survey Toolkit (FAST) on HTC Touch Pro2 smartphones at four sentinel sites. We compared 880 paper-based questionnaires dated Jan 2010-Jun 2011 and 880 smartphone questionnaires dated May 2011-Jun 2012 from the four surveillance sites. For each site, we compared the quality, cost and timeliness of each data collection system. RESULTS: Incomplete records were more likely seen in data collected using pen-and-paper compared to data collected using smartphones (adjusted incidence rate ratio (aIRR) 7, 95% CI: 4.4-10.3). Errors and inconsistent answers were also more likely to be seen in data collected using pen-and-paper compared to data collected using smartphones (aIRR: 25, 95% CI: 12.5-51.8). Smartphone data was uploaded into the database in a median time of 7 days while paper-based data took a median of 21 days to be entered (p < 0.01). It cost USD 1,501 (9.4%) more to establish the smartphone data collection system ($17,500) than the pen-and-paper system (USD $15,999). During two years, however, the smartphone data collection system was $3,801 (7%) less expensive to operate ($50,200) when compared to pen-and-paper system ($54,001). CONCLUSIONS: Compared to paper-based data collection, an electronic data collection system produced fewer incomplete data, fewer errors and inconsistent responses and delivered data faster. Although start-up costs were higher, the overall costs of establishing and running the electronic data collection system were lower compared to paper-based data collection system. Electronic data collection using smartphones has potential to improve timeliness, data integrity and reduce costs.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Escritura / Recolección de Datos / Vigilancia de Guardia / Síndrome Respiratorio Agudo Grave / Teléfono Celular / Gripe Humana Tipo de estudio: Health_economic_evaluation / Screening_studies Límite: Child, preschool / Female / Humans / Infant / Male / Newborn País/Región como asunto: Africa Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2014 Tipo del documento: Article País de afiliación: Kenia Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Escritura / Recolección de Datos / Vigilancia de Guardia / Síndrome Respiratorio Agudo Grave / Teléfono Celular / Gripe Humana Tipo de estudio: Health_economic_evaluation / Screening_studies Límite: Child, preschool / Female / Humans / Infant / Male / Newborn País/Región como asunto: Africa Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2014 Tipo del documento: Article País de afiliación: Kenia Pais de publicación: Reino Unido