| Title |
How much might a society spend on life-saving interventions at different ages while remaining cost-effective? A case study in a country with detailed data
|
|---|---|
| Published in |
Population Health Metrics, July 2015
|
| DOI | 10.1186/s12963-015-0052-2 |
| Pubmed ID | |
| Authors |
Giorgi Kvizhinadze, Nick Wilson, Nisha Nair, Melissa McLeod, Tony Blakely |
| Abstract |
We aimed to estimate the maximum intervention cost (EMIC) a society could invest in a life-saving intervention at different ages while remaining cost-effective according to a user-specified cost-effectiveness threshold. New Zealand (NZ) was used as a case study, and a health system perspective was taken. Data from NZ life tables and morbidity data from a burden of disease study were used to estimate health-adjusted life-years (HALYs) gained by a life-saving intervention. Health system costs were estimated from a national database of all publicly funded health events (hospitalizations, outpatient events, pharmaceuticals, etc.). For illustrative purposes we followed the WHO-CHOICE approach and used a cost-effectiveness threshold of the gross domestic product (GDP) per capita (NZ$45,000 or US$30,000 per HALY). We then calculated EMICs for an "ideal" life-saving intervention that fully returned survivors to the same average morbidity, mortality, and cost trajectories as the rest of their cohort. The EMIC of the "ideal" life-saving intervention varied markedly by age: NZ$1.3 million (US$880,000) for an intervention to save the life of a child, NZ$0.8 million (US$540,000) for a 50-year-old, and NZ$0.235 million (US$158,000) for an 80-year-old. These results were predictably very sensitive to the choice of discount rate and to the selected cost-effectiveness threshold. Using WHO data, we produced an online calculator to allow the performance of similar calculations for all other countries. We present an approach to estimating maximal cost-effective investment in life-saving health interventions, under various assumptions. Our online calculator allows this approach to be applied in other countries. Policymakers could use these estimates as a rapid screening tool to determine if more detailed cost-effectiveness analyses of potential life-saving interventions might be worthwhile or which proposed life-saving interventions are very unlikely to benefit from such additional research. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 25% |
| Spain | 1 | 25% |
| Australia | 1 | 25% |
| United States | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 3% |
| Unknown | 28 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 28% |
| Student > Master | 5 | 17% |
| Other | 3 | 10% |
| Student > Ph. D. Student | 3 | 10% |
| Professor | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 6 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 17% |
| Social Sciences | 4 | 14% |
| Business, Management and Accounting | 3 | 10% |
| Nursing and Health Professions | 3 | 10% |
| Mathematics | 1 | 3% |
| Other | 4 | 14% |
| Unknown | 9 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 December 2021.
All research outputs
#12,587,003
of 22,714,025 outputs
Outputs from Population Health Metrics
#247
of 392 outputs
Outputs of similar age
#111,579
of 262,190 outputs
Outputs of similar age from Population Health Metrics
#5
of 8 outputs
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