Improving health in developing countries: what can FOSS contribute? Prof. S. Yunkap Kwankam Executive Director, International Society for Telemedicine and eHealth (ISfTeH) CEO, Global eHealth Consultants, Switzerland IWEEE Las Palmas, de Gran Canaria, Spain – February 10-12, 2010
The International Society ISfTeH – NGO in official relations with WHO 32 national societies
Outline Health – a multi-sectorial production Where can ICT contribute? WHO eHealth priority actions areas Supporting the health workforce Promoting prevention Mobile devices in health Organizing the eHealth profession Final thoughts – RF initiative
Operational definition of eHealth: ICT for health What produces health? Where can we bring ICT to bear on this production?
Pathways to improved health Adapted from World Bank
Focus of health investment should be on improving sector productivity, cannot just increase funding Level of HC spending is a function of Level of HC spending is a function of GDP/capita regardless of external funding GDP/capita regardless of external funding 10000 R 2 = 0.94 Health spend per capita (2005) 1000 100 10 100 1000 10000 100000 GDP PPP per capita (2005) The most effective way to improve productivity is to Source: Nicholas C. Petris Center on Health Care Markets & Consumer Welfare (UC improve health systems Berkeley), WHO, A Handbook of Cultural Economics (James Heilbrun)
Operational definition of eHealth: ICT for health What produces health? Where can we bring ICT to bear on this production? Overwhelming focus on health care T o the neglect of major determinants of health: Water and sanitation Food and nutrition Housing and shelter Some ICT effort in the area of education
Social determinants of health WHO Commission report q Improve daily living conditions q T ackle the inevitable Improve the conditions of daily life – the distribution of circumstances in which people are born, grow, live, work, and age. power, wealth Tackle the inequitable distribution of and resources power, money, and resources – the q Measure and structural drivers of those conditions of daily life – globally, nationally, and locally understand the
MDG 8 – Target 18 Global Partnership for Development Target 18: INDICATORS In cooperation with q T elephone lines per 100 population the private sector, q Internet users per 100 make available the population benefits of new q Cellular subscribers per technologies, 100 population especially information and communications.
Focus on an ICT for development paradigm: MDG 8 supporting the other 7 Promote, in underserved areas, the combined development of : Health Education Agriculture Small business Good governance
What ICT can contribute? – small business Application areas : Examples : Ghana SIM cards Maintenance Small adaptations Cell phone charging ICT equivalent of Data collection William Kamkwamba, Other services Malawian
What ICT can contribute? – eGovernment Application areas : Examples : Easy access to Pakistan – entitlements health care benefits Information agents Morocco – village tele- center information agents
eHealth priority action areas identified by WHO Norms and standards Legal and ethical issues Access to health information SNOME D HL7 v2.5 1 Intelligence on eHealth XML HTTP TCP HINARI IP Global eHealth survey 2005 PPP for ICT R&D for health ICT for health promotion ICT for health workforce development ICT for service delivery eLearning Kenya WHR 2006
ICT and Health: a symbiotic relationship Health promotion Disease prevention Diagnosis & treatment Health needs Rehabilitative care drive Education & development training s in ICT HS performance ICT HEALTH ICT HEALTH Development Bioinformatics s in ICT help Artificial Intelligence shape health Miniaturization systems and Improved access service Wider coverage delivery
Countries with a critical shortage of health service providers (doctors, nurses and midwives)
Distribution of health workers by level of health expenditure and burden of disease, by WHO region
eLearning easing healthcare HR crisis in Kenya eLearning can reach goal w/in eLearning can reach goal w/in In Kenya, chronic shortage of Promising progress since start of next decade versus >200 years w/ In Kenya, chronic shortage of Promising progress since start of next decade versus >200 years w/ highly skilled nurses program in Sep. 2005 traditional classroom methods highly skilled nurses program in Sep. 2005 traditional classroom methods Enrolled Nurses (ENs) eLearning vs. traditional comprise 70% of nursing and methods for upgrading ENs 45% of the health workforce in Kenya (K) 25 • First point of contact for 22,000 ENs to upgrade communities, but are inadequately skilled to 20 manage new and re- emerging diseases like 15 HIV/AIDS As of Nov. 2006, 3,265 nurses •~2,800 ENs upgraded upgraded/yr PPP led by the Nursing Council •Cum. cost ~ $2.5M 10 of Kenya (NCK), the African •~$114/nurse •~100 ENs 27 colleges and schools Medical and Research upgraded/yr participating including Foundation (AMREF) and •Cum. cost ~ AMREF’s Virtual Nursing 5 Accenture to upgrade 22,000 $50M School ENs from ‘enrolled’ to •~$2,273/nurse ‘registered’ level within 5 years Over 100 computer-equipped via eLearning (distance 0 training centers set up in 8 2005 2007 2009 2011 2013 2015 2225 education through ICT) provinces, including remote methods and marginalized districts eLearning Source: Source: WHO, AMREF website Traditional classroom method Results do not just represent dramatic cost and time improvements over status quo, they are nearly impossible without use of ICT
The need for decision support systems Current practice depends upon the clinical decision making capacity and reliability of autonomous individual practitioners for classes of problems that routinely exceed the bounds of unaided human cognition” Daniel Masys, 2001
In God we trust - everyone else needs evidence Knowledge- -coupling system coupling system Knowledge PROBLEM Options Decision Problem- or SELECTION specific filter Action Problem Relevant knowledge characteristics Body of scientific knowledge
Decision support systems Today decision support tools such as Medoctor support diagnosis with robust algorithms for differential diagnosis
Map of Medicine – DSS q A web-based visual representation of evidence-based patient care journeys q q Covers 28 medical specialties q q Contains 393 pathways q q Used to support clinicians; not to replace clinical judgement
The need for prevention
Burden of disease and risk factors
What technology platform? - mobile Mobile devices integrate q Communications q Computing q Media Conceptually compelling – rather than constrain user to take their problem to where technology exists, make technology available wherever the need is.
Internet use focused in developed world Significant penetration in Latin America and select Sub-Saharan African countries Internet users (per 1,000 people) No data available 0 - 50 50 - 100 100 -150 150 -200 200+ Note: Data taken from 2005 Source: World Bank WDI
PCs also focused in developed world Significant penetration in Latin America and select Sub-Saharan African Personal computers (per 1,000 people) countries No data available 0 - 50 50 - 100 100 -150 150 -200 200+ Note: Data taken from 2001-2005, depending on availability for each country Source: World Bank WDI
Mobile phones widely diffused beyond developed countries to many countries “Global South” Mobile phone subscribers (per 1,000 people) No data available 0 - 50 50 - 100 100 -150 150 -200 200+
Mobile phones reaching further Source: ITU World Telecomm unication indicators database
Red Cross survey - Ghana l 30 RC volunteers trained l 2400 surveys in 3 days l 200 for pen and paper system l Survey report to MoH same day after
SAM processing steps 1. Questionnaire programmed on Palm Pilot 2. Data collection with handheld unit 3. Palm synchronized with PC for data 4. Data analysis transfer and production of maps with HealthMapper
Mobile Map A trial of the Mobile Map in 2007 had already proved very popular with Kijabe Hospital Kenya The Map of Medicine on PDA was recommended by participants in the Kenya pilot
Background information RapidSMS is an information tracking tool that collects data over “SMS” or “T ext Messages” from mobile users RapidSMS allows data to be collected in real time to enable LGA, State, Federal, and partners to collect, analyze, and react to data more quickly. Slide by Emmanuel Onyefunafoa
Background Information contd.. RapidSMS has been used in: Malawi Kenya Uganda Ethiopia United States NIGERIA Slide by Emmanuel Onyefunafoa
mHealth – Mobile Communication for Health ECOSOC Africa Regional Ministerial Meeting on eHealth Claire Thwaites 11 June 09
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