Cost-effectiveness analysis of the CLIP Trials
The community level interventions for pre-eclampsia (CLIP) Trial is an innovative, yet integrated package of interventions aiming to avert pre-eclampsia- and eclampsia (PE/E) related mortality and morbidity at the community level in South Asia and Africa. The utilisation of CLIP package relies primarily on community engagement to encourage care seeking, task shifting of clinical tasks to community health care providers, and mobile health (mHealth) infrastructure and technology for identification and referral of mothers with PE/E at the community level, hence there are incremental cost implications for the post trial program scale-up and sustainability. The cost-effectiveness analysis (CEA) compares the costs and health effects or benefits of interventions to assess, if a particular intervention is worth implementing at a health systems or population level. Evaluating cost-effectiveness of CLIP Trial will help to address the policy argument, mobilize local technology, as well as, human resources to avert morbidity and mortality from PE/E, while maximizing healthy pregnancy outcomes in the selected countries.
We propose the hypothesis that the CLIP Trial intervention will be cost-effective in reducing pre-eclampsia- and eclampsia-related maternal and perinatal mortality and major morbidities in the selected study settings.
The primary objective of this study is to determine the costs and benefits of CLIP for reducing pre-eclampsia- and eclampsia-related maternal and perinatal mortality and major morbidities. Secondary objectives are to strengthen the policy advocacy for introduction, post-trial scale up, and sustainability of CLIP in the existing maternal health policies of selected countries.
Through this study, we will calculate the cost for human resource, equipment, mHealth infrastructure/technology, health care services, as well as, opportunity cost (e.g., family’s wages missed due to illness). The benefits (health gain/consequences) will be measured in natural units (maternal or perinatal mortality and morbidity). Likewise, the cost/benefits estimates of the routine maternal health programme will be assessed in the control clusters that did not receive the CLIP intervention. The initial modelling will be performed using data from Sindh, Pakistan, and then validated in data from Ogun, Nigeria, Maputo and Gaza, Mozambique, and Karnataka, India.
In summary, we will perform cost modelling and calculate cost per death and major morbidity averted per international (US) dollar from pre-eclampsia/eclampsia. Ultimately, we will be able to provide a cost-benefit model for CLIP implementation in non-CLIP low middle income countries in Africa and South Asia.
At end of trial recruitment, clean data will be analysed to estimate the cost for maternal and newborn care in the intervention group. Additional statistics (regression analysis) will be applied to adjust cost estimates to sociodemographic attributes between intervention and control groups. Costs and trial outcome inputs will be modelled to determine the incremental cost-effectiveness ratio (ICER); and a probabilistic analysis will be performed to address costs and outcome related uncertainties. A project report, inclusive of key findings, will be shared with stakeholders.
As of February 2018, the Pakistan dataset is complete and is currently under preparation for publication and in Asif's dissertation. India is finalizing its dataset and analysis will be undertaken in April to June 2018. Data collection is about to launched in Mozambique.