|InterJournal Complex Systems, 2246
|Manuscript Number: |
Submission Date: 20080226
|Developing a complex approach to health phenomenon (step 1)|
Health is a complex object for science and operative levels, partly because there are many approaches defining it but not scientifically sufficient or operatively accepted. This is relevant for health understanding but also for health related problems decision making. “Determinants of Health” (DH) widely accepted theoretical proposal identifies as problematic the reductionist health view as disease opposite, attempting to develop it positively according to WHO´s definition, proposes a set of factors determining health outcomes. Though this allows a larger comprehension of health causes and effects importance, still has insufficiently defined theoretical statements and unproved assumptions which difficult understanding and effective actions orientation. Complexity deductive modeling (theory to simulation) from insufficiently theoretical and formal frameworks implies incorporating unmanageable object assumptions or reducing health broadness. Taking profit of Bogotá government adherence to DH proposal on health information systems development is possible inductive modeling since a systemic massive database (690.000 registries). In this way DH theoretical statements about health connectedness were explored by statistic classical approach and by bayesian networks learning from data (data mining). First approach showed computational and interpreting difficulties. Second was advantageous in approximating within and between determinants relationship structure. However, though DH introduces a systemic approach in considering diverse interacting elements is not empirically sufficient for constructing health complexity, just matching analytic fashioned constructs depending and also orienting data expression. A strong networked model developing health complexity needs human agency and organization based theoretical orientation to explore emergent patterns of health.
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