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Mobile Phones for Public Health Interventions

Mobile Phones for Public Health Interventions . Dr. Gordon A. Gow Associate Professor Graduate Program in Communication and Technology University of Alberta Edmonton, Canada. Then ….

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Mobile Phones for Public Health Interventions

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  1. Mobile PhonesforPublic Health Interventions Dr. Gordon A. Gow Associate Professor Graduate Program in Communication and Technology University of Alberta Edmonton, Canada

  2. Then … “ … in 1981, ‘mobile phone’ meant pretty much one thing: a big suitcase full of electronic equipment, wired and bolted into a millionaire’s Cadillace limousine, with a three-foot steel antenna drilled through the trunk lid.” (Murray Jr. 2001) http://electronicdesign.com/Files/29/5830/Figure_01.jpg

  3. … and Now “We are the first generation of humans carrying powerful [networked] personal computers in our pockets.” (Justin Hall 2004)

  4. ‘mHealth’ “… mobile technology is beginning to have a big impact is health care, especially in [developing] countries. … Soon mobile technology could play a large role in detecting, mapping and responding to epidemics. A lot of information about a recent polio outbreak in Kenya became available because health workers were using hand-held devices to collect data that used to be recorded on paper forms.” (Economist, April 10, 2008)

  5. Low start up cost wireless local loop consumer handsets multipurpose prepaid option Flexibility voice services text messaging Positive affordances personal, mobile always-on camera/video Uncertain operating costs voice rates data rates roaming charges maintenance/replacement Bandwidth circuit switched data SMS limitations GPRS/3G availability Negative affordances data entry/screen size battery life Pros and Cons Kaplan, W. (2006). ‘Can the ubiquitous power of mobile phones be used to improve health outcomes in developing countries?’ Globalization and Health. 2:9 (May 2006).

  6. Health Applications • mHealth “intervention” • an intentional use of mobile phones ‘for the specific purpose of modifying some health-related outcome or act.’ (Kaplan, 2006) • Personal healthcare intervention • Medical personnel to patients • adherence to medication; immunization rates • Patients to medical personnel • Self reporting (e.g., blood glucose levels) • Public health intervention • Wide area surveillance and notification

  7. CDC in Kenya • CDC/Kenya MOH project: • household morbidity survey • paper vs. PDA • disease surveillance initiative: • SMS introduced • coded reporting • automated analysis • mass notification “… PDA data quality is higher than paper data becauseof the ability to force data validation and skip routines in the field. Data collection-to-analysis time is reduced be-cause your field staff become your data entry staff. PDAdata collection is cheaper because there are no printingand paper costs and no data entry staff costs.” Shah, A. ‘The Future is Now: Mobile Technology and Public HealthYale Journal of Public Health. Winter 2007.

  8. RTBP: Sri Lanka/India • International Development Research Centre • Pan Asia Networking (PAN) Program • PANACeA project • Evaluating RTBP (LIRNEasia) • mHealth-related research questions: • To what extent can mobile phones improve the timeliness and accuracy of reporting patient data from communities to regional/national epidemiology centres? • To what extent can mobile phones improve the timeliness and effectiveness of public health interventions? (i.e., notifications about infectious disease outbreaks)

  9. The ‘last-Mile’ • Digitizing patient data • Test applications to support data acquisition • Assess standards for coding data • Identify unknown issues/examine known issues • Transmitting patient data • Explore methods for sending data to centres • Examine notification and alert possibilities • Develop and assess procedures • Training and technology acceptance

  10. Research Activities • ICT development and testing • data entry application loaded on handset • ICT deployment • introduce into selected communities • provide training and operating procedures • conduct beta tests and make changes as needed • Evaluation • Routine data entry combined with simulations • Assessment criteria could include: • HCI aspects, interoperability, social acceptance

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