Health technology assessment
Evidence has to reach the committee that decides funding, in the form that committee works with. In Australia that means MSAC and the Medicare Benefits Schedule; elsewhere, the equivalent bodies.
The value
of genomics
Determining the value
Micro-costing
- Genome sequencing
- Exome sequencing
- Proteomics
- RNA sequencing
- Long-read sequencing
Benefit valuation
- Discrete choice experiments
- Contingent valuation
- Personal utility
Economic evaluation
- Cost-effectiveness & cost-benefit
- Budget impact
- Return on investment
- Value of information
- Value of implementation
The GUV scale
Realising the value
- Health technology assessment
- Real-world evidence
- Lifecycle evaluation and the learning health system
- AI applications
- Equity-informative economic evaluation
- Health economics of Indigenous genomics
- Macroeconomic effects of genomics investment
- Optimising value from genomic investment
Section one
Determining the value of genomics
Traditional evaluation methods miss much of what genomics does: the personal value of an answer to a family, and the potential to reuse sequence data to improve care and drive research. Determining value means building the measurements that capture it, and building them so that what is measured in one setting can be compared with another.
Determining the value of genomics in healthcare, Nature Medicine ↗
-
01
Micro-costing genomics
What a test costs is not what it is billed at, and the published estimates vary far more than the technology does. A systematic review of micro-costing studies in diagnostic genomics reported costs of US$716 to US$4,817 for exome, and US$2,094 to US$9,706 for genome testing. Micro-costing builds the cost from the bottom up, resource by resource, and has to be repeated as each technology arrives.
-
02
Benefit valuation
A technology cannot be valued without knowing what the people affected by it care about, and that cannot be established by asking them directly. Preferences have to be inferred from the choices people make when one thing is traded against another, and then modelled.
-
03
Economic evaluation
Costs and benefits are brought together in the form a funding committee can assess, with the uncertainty characterised rather than hidden: the decision then rests both on what is known and on how well it is known.
-
04
The four questions that follow
Cost-effectiveness alone rarely settles a funding decision. Four further analyses answer the questions a payer asks next.
- Budget impact. What it costs the system to say yes.
- Return on investment. What comes back, and when.
- Value of information. Whether the uncertainty is worth resolving before deciding.
- Value of implementation. What the evidence is worth only if the service is delivered as designed.
-
05
The GUV scale
None of these measures compares across contexts without a common unit. The GUV scale is a standardised measurement and valuation scale of genomic utility, developed with decision-makers so that value claims about different genomic applications can be set against one another and used in policy. It is the point at which determining value becomes something a health system can act on.
A standardized measurement and valuation scale of genomic utility, Value in Health ↗
Section two
Realising the value of genomics
Determining value is not the same as capturing it. Health systems are resource-constrained and genomic technologies change quickly, so evaluation has to be rigorous and repeatable at the same time: informed by real-world data, revisited across the technology lifecycle, and explicit about who gains and who does not.
Real-world evidence
Economic estimates built from trial data often differ once a test is in routine use, where ordering patterns, turnaround times and follow-up are not what a protocol assumed. Real-world data shows what utilisation, cost and benefit look like in practice.
Lifecycle evaluation and the learning health system
A single appraisal at launch cannot govern a technology that changes from one year to the next. Lifecycle HTA re-evaluates health, economic and societal impact continuously; investment and disinvestment then follow the evidence as it accumulates, rather than a judgement taken once at listing.
AI applications
Some of the work of generating and using evidence can be automated, and some of it cannot. Which is which matters most where a health system has to defend the decision in public.
Equity-informative economic evaluation
An average cost-effectiveness ratio hides distribution. Equity-informative methods make explicit who gains, who misses out, and what a more equitable allocation would cost in health forgone elsewhere.
Health economics of Indigenous genomics
Genomic medicine risks widening the gaps it could close. This work builds the economic evidence for Indigenous genomics on terms set with the communities it concerns, and under the data governance those communities require.
Macroeconomic effects of genomics investment
Value to a health system is not the whole return. One US assessment put it at US$4.75 back on every dollar invested, through jobs and tax revenue. Quantifying this remains badly under-researched, and it is the argument that reaches finance ministries.
Optimising value from genomic investment
A technology can be cost-effective and still return less than it should. Optimisation addresses which patients to test, in what sequence, through which service model, and where to disinvest, so that the same budget delivers more health.
Next
Most of this is method. The point is the decision at the end of it.
The four questions this work is organised around, and the complete peer-reviewed record behind them, sit on the Work page.