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Intervention strategies to reduce the burden of non-communicable diseases in Mexico: cost effectiveness analysis

BMJ 2012; 344 doi: https://doi.org/10.1136/bmj.e355 (Published 02 March 2012) Cite this as: BMJ 2012;344:e355
  1. Joshua A Salomon, associate professor of international health1,
  2. Natalie Carvalho, doctoral student2,
  3. Cristina Gutiérrez-Delgado, deputy director general of economics and health3,
  4. Ricardo Orozco, analyst4,
  5. Anna Mancuso, clinical social worker5,
  6. Daniel R Hogan, postdoctoral fellow6,
  7. Diana Lee, doctoral student7,
  8. Yuki Murakami, health economist/policy analyst8,
  9. Lakshmi Sridharan, resident in internal medicine9,
  10. María Elena Medina-Mora, director general4,
  11. Eduardo González-Pier, director of finance10
  1. 1Department of Global Health and Population, Harvard School of Public Health, 665 Huntington Avenue, Boston, MA 02115, USA
  2. 2Harvard University, Cambridge, MA
  3. 3Unidad de Análisis Económico, Secretaría de Salud, México DF, Mexico
  4. 4Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, México DF
  5. 5Boston Center for Refugee Health and Human Rights, Boston Medical Center, Boston, MA
  6. 6Harvard School of Public Health, Boston, MA
  7. 7University of California, Berkeley, CA
  8. 8Organisation for Economic Co-operation and Development, Paris, France
  9. 9University of California, San Francisco, CA
  10. 10Instituto Mexicano del Seguro Social, México DF
  1. Correspondence to: J A Salomon jsalomon{at}hsph.harvard.edu
  • Accepted 6 November 2011

Abstract

Objective To inform decision making regarding intervention strategies against non-communicable diseases in Mexico, in the context of health reform.

Design Cost effectiveness analysis based on epidemiological modelling.

Interventions 101 intervention strategies relating to nine major clusters of non-communicable disease: depression, heavy alcohol use, tobacco use, cataracts, breast cancer, cervical cancer, chronic obstructive pulmonary disease, cardiovascular disease, and diabetes.

Data sources Mexican data sources were used for most key input parameters, including administrative registries; disease burden and population estimates; household surveys; and drug price databases. These sources were supplemented as needed with estimates for Mexico from the WHO-CHOICE unit cost database or with estimates extrapolated from the published literature.

Main outcome measures Population health outcomes, measured in disability adjusted life years (DALYs); costs in 2005 international dollars ($Int); and costs per DALY.

Results Across 101 intervention strategies examined in this study, average yearly costs at the population level would range from around ≤$Int1m (such as for cataract surgeries) to >$Int1bn for certain strategies for primary prevention in cardiovascular disease. Wide variation also appeared in total population health benefits, from <1000 DALYs averted a year (for some components of cancer treatments or aspirin for acute ischaemic stroke) to >300 000 averted DALYs (for aggressive combinations of interventions to deal with alcohol use or cardiovascular risks). Interventions in this study spanned a wide range of average cost effectiveness ratios, differing by more than three orders of magnitude between the lowest and highest ratios. Overall, community and public health interventions such as non-personal interventions for alcohol use, tobacco use, and cardiovascular risks tended to have lower cost effectiveness ratios than many clinical interventions (of varying complexity). Even within the community and public health interventions, however, there was a 200-fold difference between the most and least cost effective strategies examined. Likewise, several clinical interventions appeared among the strategies with the lowest average cost effectiveness ratios—for example, cataract surgeries.

Conclusions Wide variations in costs and effects exist within and across intervention categories. For every major disease area examined, at least some strategies provided excellent value for money, including both population based and personal interventions.

Footnotes

  • doi: 10.1136/bmj.e586
  • , doi: 10.1136/bmj.e615
  • , doi: 10.1136/bmj.e609
  • , doi: 10.1136/bmj.e612
  • , doi: 10.1136/bmj.e607
  • , doi: 10.1136/bmj.e608
  • , doi: 10.1136/bmj.e614
  • We thank Julio Frenk, Mariana Barraza-Llorens, Raúl Porras-Condey, Héctor Peña-Baca, Octavio Gómez-Dantés, Jaime Sepúlveda, Héctor Hernández-Llamas, Felicia Knaul, Rafael Lozano, Norman Daniels, Dov Chernichovsky, Colin Mathers, Christopher Murray, Majid Ezzati, Emmanuela Gakidou, Ken Hill, Michael Lisman, Kevin Thomas, Philip Clarke, Gretchen Stevens, Rodrigo Dias, Dennis Feehan, Sandeep Kulkarni, Kristen Loncich, Ben Peterson, Jane Kim, Steven Sweet, Jeremy Barofsky, Chloe Bryson-Cahn, Sue Goldie, Jochen Profit, Jennifer Yeh, Anila Gopalakrishnan, Jeremy Goldhaber-Fiebert, Melanie Bertram, Piali Mukhopadhyay, Simon Barquera, Guilherme Borges, Eric Monterrubio Flores, Jürgen Rehm, Juan Rivera Dommarco, Leonora Rojas Bracho, Jorge Villatoro, Miriam Zuk, and Tessa Tan-Torres for their useful input to this study. We thank and acknowledge Dan Chisholm, Jeremy Lauer, Stephen Lim, and Monica Ortegon for their contributions to the data analyses. We also acknowledge the experts who participated in a series of workshops in Mexico for their inputs on analyses and revisions during this project.

  • Contributors: JAS designed the study, led the data collection, analysis, and interpretation, and drafted and revised the manuscript. He is guarantor. NC collected and analysed data and contributed to design of the study, interpretation of results, and writing and revision of the manuscript. CG-D contributed to study design, data collection and analysis, and revision of the manuscript. RO, AM, DRH, DL, YM, LS, and MEM-M contributed to intervention analyses and revision of the manuscript. EGP contributed to study design, analysis and interpretation of results, and revision of the manuscript.

  • Funding source: This project was supported by funding from the Ministry of Health, Mexico.

  • Role of sponsor: The sponsor defined the scope of analysis for the project, but played no other role in study design; collection, analysis, and interpretation of data; writing of the article; or the decision to submit it for publication.

  • Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

  • Ethical approval: Not required.

  • Data sharing: No additional data available.

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