Table 2.
Priority‐setting studies in LMICs: overview of peer‐reviewed papers
| Article | Author/year | Paper type | Primary aim | Interventions | Scale (location) |
|---|---|---|---|---|---|
| #1 | Baltussen et al, 2007 | Exploratory | Show how multiple criteria can be used to guide the priority‐setting process. | Lung health programme | National (Nepal) |
| #2 | Hansen & Chapman, 2008 | Exploratory | Assess feasibility of conducting cost‐effectiveness analyses for a large number of health interventions in a developing country. | 65 curative interventions for common health problems and preventative interventions | National (Zimbabwe) |
| #3 | Kapiriri & Norheim, 2004 | Exploratory | Explore stakeholders' acceptance of criteria for setting priorities for the healthcare system. | Not specified | National (Uganda) |
| #4 | Kase, 2006 | Strategic planning | Describe process for designing Government Medium Term Expenditure Framework. | Essential health services (wages/salaries), basic system support and interventions (malaria, immunisation, safe motherhood, outreach, supervision) | National (Papua New Guinea) |
| #5 | Baltussen, 2006 | Exploratory | Identify priority interventions under two assumptions: public spending should be targeted at the whole population or the poor only. | All priority interventions listed in 2002 World Health Report | National (Ghana) |
| #6 | Baltussen et al., 2006 | Exploratory | Show how multiple criteria can be used to guide the priority‐setting process. | Set of hypothetical health interventions – taken from 2002 World Health Report | National (Ghana) |
| #7 | Chisholm et al., 2008 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Schizophrenia | Regional Americas, Africa and South‐East Asia + National (Chile,a Nigeria, Sri Lanka) |
| #8 | Diaby & Lachane, 2011 | Exploratory | Evaluate the feasibility of developing a new formulary for a health mutual fund. | Formulary for drug reimbursement | National (Cote D'Ivoire) |
| #9 | Evans, Lim et al., 2005 | Economic modelling | Summarise key findings from a series of papers on the cost‐effectiveness of strategies to achieve the millennium development goals for health. | Maternal and neonatal health, child health, HIV and Aids, malaria and tuberculosis | Regional (sub‐Saharan Africa and South East Asia) |
| #10 | Ginsberg et al., 2012 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Breast, cervical and colorectal cancers | Regional (sub‐Saharan Africa and South East Asia) |
| #11 | Jehu‐Appiah et al., 2008 | Exploratory | Illustrate how multiple criteria can be used to guide the priority‐setting process. | Child health, reproductive health, and communicable diseasesb | National (Ghana) |
| #12 | Laxminarayan et al., 2006 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | 94 clusters of interventions – representing 218 interventions covering: tuberculosis, HIV/AIDS, illness and mortality in children, tropical diseases, reproductive health, nutrition, cancer, neurological disorders, cardiovascular disease, injury prevention, surgery, alcohol and tobacco use, delivery of interventions and strengthening health systems. | Regional (South Asia and sub‐Saharan Africa) + Global (LMICs) |
| #13 | Makundi et al., 2007 | Exploratory | Test out the ‘balance sheet method’ for priority setting, which incorporates both scientific evidence and public values. | Integrated Management of Childhood Illness (IMCI), safe water, HIV, tuberculosis, malaria | National (Tanzania) |
| #14 | Venhorst et al., 2014 | Exploratory | Develop rating tool for policy makers to prioritise interventions based on multiple criteria. | Breast cancer | Global (LMICs) |
| #15 | Marsh et al., 2014 | Review | Document studies that have used multi‐criteria decision analysis to set healthcare priorities and lessons learnt. | Pharmaceuticals, public health interventions, screening, surgical interventions, and devices | Regional + national |
| #16 | Chao et al., 2014 | Review & economic modelling | Extract and appraise economic assessments for their methodological quality. | Surgery | Regional + national |
| #17 | Diaby et al., 2011 | Review & framework development | Review processes used by high‐, middle‐ and low‐income countries, to prioritise medicines for reimbursement. | Formulary for drug reimbursement | National (Canada, US, UK, France, Germany, Brazil, South Korea, Ghana) |
| #18 | Simons et al., 2011 | Economic modelling | Explain how a disease‐intervention planning tool can be used to prioritise health interventions and review of preliminary user experience. | Measles | Not applicable |
| #19 | Canning, 2006 | Review + exploratory | Explore the economic case for prioritising prevention over the treatment of HIV/AIDS. Compares cost‐effectiveness criterion to other criterion for setting priorities. | HIV prevention and treatment | Regional (Africa) |
| #20 | Whittington et al., 2012 | Economic modelling | Illustrate the challenges and uncertainties of setting priorities amongst competing interventions at the global level using economic evidence. | Water, sanitation and preventive health interventions (insecticide‐treated bed nets, cholera vaccination). | Global (LMICs) |
| #21 | Madi et al., 2007 | Exploratory | Describe a process for involving key stakeholders to elicit and prioritise health interventions. | Maternal | National (Burkina Faso, Ghana and Indonesia) |
| #22 | Adam et al., 2005 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Maternal and neonatal health | Global (LMICs) |
| #23 | Baltussen et al., 2005 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Tuberculosis | Global (LMICs) |
| #24 | Baltussen & Smith, 2012 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Vision and hearing loss | Regional (sub‐Saharan Africa and South East Asia) |
| #25 | Chisholm, Baltussen, et al., 2012 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Non‐communicable diseases and injuries | Regional (sub‐Saharan Africa and South East Asia) |
| #26 | Chisholm, Naci, et al., 2012 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Road traffic injuries | Regional (sub‐Saharan Africa and South East Asia) |
| #27 | Chisholm & Saxena 2012 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Neuropsychiatric conditions | Regional (sub‐Saharan Africa and South East Asia) |
| #28 | Darmstadt et al., 2005 | Review and modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Neonatal | Global (LMICs) |
| #29 | Edejer et al., 2005 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Child health | Global (LMICs) |
| #30 | Morel et al., 2005 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Malaria | Global (LMICs) |
| #31 | Ortegon et al., 2012 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Cardiovascular disease, diabetes, tobacco use | Regional (sub‐Saharan Africa and South East Asia) |
| #32 | Stanciole et al., 2012 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Chronic obstructive pulmonary disease and asthma | Regional (sub‐Saharan Africa and South East Asia) |
| #33 | Hogan et al., 2005 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | HIV/AIDS | Global (LMICs) |
| #34 | Cecchini et al., 2010 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Chronic diseases | National (Brazil, China, India, Mexico, Russia, South Africac) |
| #35 | Chisholm, Doran et al., 2006 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Alcohol, tobacco and illicit drug use | Regional (America, Europe and South East Asiad) |
| #36 | Gureje et al. 2007 | Economic modelling | Identify a package of disease‐specific health care interventions for investment to inform policy discussion. | Mental health | National (Nigeria) |
LMICs, low‐income and lower‐middle‐income countries; MCDA, multi‐criteria decision analysis.
a
Note that Chile is classed as a high‐income country while Nigeria and Sri Lanka are classified as ‘lower‐middle’‐income countries (World Bank, 2014).
b
These are the final set of interventions identified using MCDA. Original exercise included childhood diseases, communicable and non‐communicable diseases, reproductive health and injuries.
c
Only India is a “lower‐middle‐income” country and meets the eligibility criteria for this review.
d
These regions are defined by WHO as American sub‐region AmrB (countries with low rates of child and adult mortality, e.g. Brazil or Mexico); European sub‐region EurA (countries with very low child and adult mortality, e.g. France or Norway); and South East Asian sub‐region SearD (countries with high child and adult mortality, e.g. India or Nepal).