The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Estimating health opportunity costs in low-income and middle-income countries: a novel approach and evidence from cross-country data
Open accessAbstract
The economic evaluation of healthcare interventions requires an assessment of whether the improvement in health outcomes they offer exceeds the improvement in health that would have been possible if the additional resources required had, instead, been made available for other healthcare activities. Therefore, some assessment of these health opportunity costs is required if the best use is to be made of the resources available for healthcare. This paper provides a framework for generating country-specific estimates of cost per disability-adjusted life year (DALY) averted ‘thresholds’ that reflect health opportunity costs. We apply estimated elasticities on mortality, survival, morbidity and a generic measure of health, DALYs, that take account of measures of a country’s infrastructure and changes in donor funding to country-specific data on health expenditure, epidemiology and demographics to determine the likely DALYs averted from a 1% change in expenditure on health. The resulting range of cost per DALY averted ‘threshold’ estimates for each country that represent likely health opportunity costs tend to fall below the range previously suggested by WHO of 1–3× gross domestic product (GDP) per capita. The 1–3× GDP range and many other previous and existing recommendations about which interventions are cost-effective are not based on an empirical assessment of the likely health opportunity costs, and as a consequence, the health effects of changes in health expenditure have tended to be underestimated, and there is a risk that interventions regarded as cost-effective reduce rather than improve health outcomes overall.
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Cites
Instrumental Variables Regression with Weak Instruments
Staiger, D., & Stock, J. H. (1997) · Econometrica · doi:10.2307/2171753 · Cited by 7,081
Instrumental Variables Regression with Weak Instruments
Staiger, D., & Stock, J. (1994) · doi:10.3386/t0151 · Cited by 5,302 · cited 1×
“This is typically judged by calculating the f-statistic of a joint test of the excluded instruments where the statistic should be at least 10.(21) The second criterion is that the instruments are valid, which means that the instruments themselves do not affect the outcome variable directly or through some unobserved f…”
BackgroundUpdating cost-effectiveness—the curious resilience of the $50,000-per-QALY threshold
Neumann, P. J., Cohen, J. T., & Weinstein, M. C. (2014) · New England Journal of Medicine · doi:10.1056/nejmp1405158 · Cited by 2,249
Salomon, J. A., Vos, T., Hogan, D. R., Gagnon, M., Naghavi, M., Mokdad, A., Begum, N., Shah, R., Karyana, M., Kosen, S., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61680-8 · Cited by 1,322
Country-Level Cost-Effectiveness Thresholds: Initial Estimates and the Need for Further Research
Woods, B., Revill, P., Sculpher, M., & Claxton, K. (2016) · Value in Health · doi:10.1016/j.jval.2016.02.017 · Cited by 884
Self-citationClaxton, K., Martin, S., Soares, M., Rice, N., Spackman, E., Hinde, S., Devlin, N., Smith, P. C., & Sculpher, M. (2015) · Health Technology Assessment · doi:10.3310/hta19140 · Cited by 853
Self-citationThe impact of public spending on health: does money matter?
Filmer, D., & Pritchett, L. (1999) · Social Science & Medicine · doi:10.1016/s0277-9536(99)00150-1 · Cited by 788
Cost–effectiveness thresholds: pros and cons
Bertram, M., Lauer, J., De Joncheere, K., Edejer, T., Hutubessy, R., Kieny, M.-P., & Hill, S. (2016) · Bulletin of the World Health Organization · doi:10.2471/blt.15.164418 · Cited by 783
National Institute for Clinical Excellence and its value judgments
Rawlins, M. D., & Culyer, A. J. (2004) · BMJ · doi:10.1136/bmj.329.7459.224 · Cited by 765
Gupta, J. K., Daniels, J. P., Middleton, L. J., Pattison, H. M., Prileszky, G., Roberts, T. E., Sanghera, S., Barton, P., Gray, R., Kai, J., et al. (2015) · Health Technology Assessment · doi:10.3310/hta19880 · Cited by 399
Cited by
Pichon-Riviere, A., Drummond, M., Palacios, A., Garcia-Marti, S., & Augustovski, F. (2023) · The Lancet Global Health · doi:10.1016/s2214-109x(23)00162-6 · Cited by 268
Kazibwe, J., Gheorghe, A., Wilson, D., Ruiz, F., Chalkidou, K., & Chi, Y.-L. (2022) · Value in Health · doi:10.1016/j.jval.2021.08.014 · Cited by 139
Scientific advances and the end of tuberculosis: a report from the Lancet Commission on Tuberculosis
Reid, M., Agbassi, Y. J. P., Arinaminpathy, N., Bercasio, A., Bhargava, A., Bhargava, M., Bloom, A., Cattamanchi, A., Chaisson, R., Chin, D., et al. (2023) · The Lancet · doi:10.1016/s0140-6736(23)01379-x · Cited by 87
Nsengiyumva, N. P., Hussain, H., Oxlade, O., Majidulla, A., Nazish, A., Khan, A. J., Menzies, D., Ahmad Khan, F., & Schwartzman, K. (2021) · Open Forum Infectious Diseases · doi:10.1093/ofid/ofab567 · Cited by 34
Metadata
- Authors
- Ochalek, J., Lomas, J., & Claxton, K.
- Venue
- BMJ Global Health
- Publisher
- BMJ
- Published
- 2018-11
- Volume
- 3
- Issue
- 6
- Pages
- e000964
- ISSN
- 2059-7908 (ISSN-L)
- OpenAlex
- W2894020737
- Cited by
- 334
- References
- 24
- FWCI
- 33.94
- Type
- journal article
- Language
- en
- Open access
- gold
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- Ochalek, J., Lomas, J., & Claxton, K. (2018). Estimating health opportunity costs in low-income and middle-income countries: a novel approach and evidence from cross-country data. BMJ Global Health. https://doi.org/10.1136/bmjgh-2018-000964
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