DETERMINING OPTIMAL INFORMATIONAL INTERVENTION BUNDLES TO MAXIMIZE HEALTH OUTCOMES

Purpose: Preventative information and behavioral change messages, through human contact or mobile phones, can encourage healthful behaviors, improving health outcomes. Widespread, repeated information dissemination is expensive and resource-intensive. Maximizing health outcomes, given limited resources, requires determining the optimal bundle of information dissemination interventions. 

Methods: We develop an optimization framework linking information dissemination, use of preventive behaviors, and health outcomes. First, we map quantities of various information interventions, x_n, to increased compliance with preventive measures, via a multivariate logistic function  p_compliance=p₀/(1+A₁exp(-α₁(x₁-β₁))+A₂exp(-α₂(x₂-β₂))+...+A_nexp(-α_n(x_n-β_n))) where A_n, α_n, and β_n are estimated from data. Next, we model how multiple preventive measures impact health and costs. Employing the compliance probabilities calculated above, if Q_j represents the discounted health benefits from compliance with a particular preventative intervention, and there are i interventions, the average amount of health benefits is Q = (Q_123...i)(p₁)(p₂)(p₃)...(p_i) + (Q_!123...i)(1-p₁)(p₂)(p₃)...(p_i) + (Q_1!23...i)(p₁)(1-p₂)(p₃)...(p_i) + (Q_!1!23...i)(1-p₁)(1-p₂)(p₃)...(p_i) + ... + (Q_!1!2!3...!i)(1-p₁)(1-p₂)(1-p₃)...(1-p_i) Intervention costs are modeled as linear with a non-zero fixed cost. Mathematical programming can then determine the optimal intervention package. This methodology can improve strategies to combat maternal mortality in India, where an estimated 50% of the >50,000 annual maternal deaths are preventable. Two examples illustrate this: 1) two interventions (village health leaders and mobile messages) that increase one preventive behavior (iron supplementation); 2) two interventions of the same type (mobile messages) that increase two preventive behaviors (iron and folate supplementation). 

Result: Both examples yield two forms of optimal intervention bundles: 1) using only one intervention type; 2) using two interventions in combination. The first type occurs intuitively when one intervention is inexpensive per unit of benefit gained compared to the other. The second occurs when  grad_x1,x2(Q) = -λ grad_x1,x2(C) has a solution where x₁>0 and x₂>0. Thus, the solution satisfies the following equations ∂Q/∂x₁ = -λ ∂C/∂x₁ ∂Q/∂x₂ = -λ ∂C/∂x₂ Generally, for many behaviors, compliance with each behavior derives from logistic equations containing those interventions that impact it. Benefits from compliance with multiple behaviors can be nonlinear; behaviors have multiple health effects and two behaviors can have complementary effects on one health effect. 

Conclusion: The framework described considers multiple information dissemination interventions to change multiple preventive behaviors to improve health. It can be applied to diverse global health problems (e.g., maternal mortality, anemia). For some cases, it yields analytic forms and, for complex cases, optimal results via numerical methods.