http://www.healthyfutures.eu
SURVEY & INTERVIEW RESPONSES ON DECISION-MAKING
AND DECISION-SUPPORT TOOLS (DSTs) FOR HEALTH ...
HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014
Online survey sent to s/h & HF partners
• 1 KEMRI -Kenya
• 1 ...
HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014
Important factors in decision-making
• Participatory approach...
HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014
Data used in the decisions
• Surveys, feasibility studies, po...
HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014
Challenges in the decision-making
• Domestication of integrat...
HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014
Decision-making needs & research outputs
Needs in the decisio...
HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014
How does uncertainty complicate decision-making?
• Incomplete...
HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014
How is uncertainty dealt with?
• Stakeholder consultation/sha...
Time horizons of decision-making for DST
tools
• Decisions that need to be made in the very near future (within
weeks or m...
HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014
Spatial scales of decision-making
• East Africa & neighboring...
HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014
• Uncertainty
– Statistical uncertainty: main dimension taken...
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Hf ppt survey results

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This presentation summarizes the survey and interview responses on decision-making and decision-support tools (DSTs) for health and environmental change in the context of the Healthy Futures project.

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Hf ppt survey results

  1. 1. http://www.healthyfutures.eu SURVEY & INTERVIEW RESPONSES ON DECISION-MAKING AND DECISION-SUPPORT TOOLS (DSTs) FOR HEALTH AND ENVIRONMENTAL CHANGE HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014 Monica Coll Besa & Richard Taylor SEI Oxford Centre
  2. 2. HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014 Online survey sent to s/h & HF partners • 1 KEMRI -Kenya • 1 Ministry of Agriculture, Livestock & Fisheries • 1 University of Rwanda –College of Medicine and Health Sciences • 1 Action de Lutte contre la Malaria, A.LU.MA -Burundi • 1Ifakara Health Institute –Tanzania • 1Dept. Veterinary Services –Kenya • 1 ICTP • 1 ILRI • 1 CSAG • 1 Ministry of Health -Uganda 10 responses in total
  3. 3. HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014 Important factors in decision-making • Participatory approaches through consultation, sharing views • Environmental & socio-economic concerns • Technology, finances, audience, size of data & database • Availability of scientific data & knowledge • Improved performance of the health sector and improved service delivery – Other important criteria: • More cross-sectoral integration in development planning • Global trends in data mgmt, literature, environmental concerns • Individual public health experience • Information on previous performance & past achievements
  4. 4. HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014 Data used in the decisions • Surveys, feasibility studies, population dynamic data • Costs data: income, expenditure patterns (HH level) • Health mgmt information system • Data sets from clinical trials to implementation • Ecology of the area, community perception on control and materials to be used • Sector performance reports, disease epidemics and outbreaks, scarcity of medicines
  5. 5. HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014 Challenges in the decision-making • Domestication of integrated vector mgmt strategies at the HH level • Sustainability of problems; relaxation when problem declines • Taking vector surveillance as 2nd priority to disease treatment • Timely detection of outbreaks => inadequate preparedness at lower levels • Competing interests for funding, fear for wrong decisions
  6. 6. HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014 Decision-making needs & research outputs Needs in the decision-making: • Entire life cycle of clinical research (clinical trial to implementation) • Economic returns & savings; if preventive measures are as successful as vector control. • Livelihood analysis • Past trends & factors influencing trends • Information on current findings wrt control of diseases, updates on current trends, information-sharing • Forecasting & early detection • Assessment on vulnerability & impacts of diseases rather than presence of the hazard  Endemicity level maps  Socio-economic vulnerability map  Cost-benefits information about options  Hazard maps
  7. 7. HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014 How does uncertainty complicate decision-making? • Incomplete knowledge: when the decision-maker lacks enough knowledge about the system. This can be due to different factors, such as lack of theoretical understanding, ignorance, lack of information or data, unreliability of data describing the system, etc. e.g. the efficacy of preventive measures). 7 people mentioned it • Multiple knowledge frames: results from having different, and sometimes conflicting views about the system (e.g. which people should be prioritised for receiving a specific health care treatment). 4 people mentioned it • Unpredictability: when the decision-maker is not able to predict, in space or time, the behaviour of a system (e.g. the timing and extent of a malaria or RVF outbreak, e.g. longer term effects of environmental change on diseases). 3 people mentioned it
  8. 8. HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014 How is uncertainty dealt with? • Stakeholder consultation/sharing knowledge (very common) • Scenario building & analysis with key experts (Delphi method) – If control of uncertainty: build on preventive strategies – If no control of uncertainty: ranking of strategies • Lobbying • Use of surveillance system from the Ministry • Critical synthesis of existing data • Range or envelope of change using model agreement as providing some confidence in at least the direction of change. Focus on the dynamics –what is behind or driving the change. (CSAG)
  9. 9. Time horizons of decision-making for DST tools • Decisions that need to be made in the very near future (within weeks or months) -3 people • Decisions in the short to medium-term (within 5 yrs) -3 people • Decisions that need to be made on annual cycles -2 people • Longer term decisions than the above -2 people
  10. 10. HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014 Spatial scales of decision-making • East Africa & neighboring countries (5) • National (5) • District/provincial (4) • Local (3) Local District/provinci al National East Africa & neighboring countries
  11. 11. HEALTHY FUTURES Fifth Partners meeting, Nairobi, Kenya, 2014 • Uncertainty – Statistical uncertainty: main dimension taken into account. Handled by making improvements in data collection, multiple sources of evidence, etc. – Epistemic uncertainty (i.e. in the impact or effectiveness of preventative measures) – No mention of ‘scenario uncertainty’ –suggesting lack of familiarity. • Relevant timeframes varied, both in terms of taking a decision and implementing it (from days to 20/30 years for long-term planning) • Value for money of actions & stakeholder support through consultation– most important factors in decision-making • Lack of coordination among stakeholders and more funding needed • Sequencing of decisions –based on the data collected, and the success/failure indicators, it may prompt a new decision. If control is successful it may switch to elimination. Summary of findings from the interviews in Nairobi

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