The performance of the healthcare system has become a central policy concern, as rising costs, an ageing population, and the aftershocks of the COVID-19 pandemic have placed sustained pressure on the healthcare industry and the broader health sector. In high-income countries, healthcare spending has grown faster than GDP, raising urgent questions about healthcare productivity growth and the long-term sustainability of the healthcare sector. 

Policymakers and institutions, like the Productivity Commission, are increasingly focused on whether healthcare services, including hospital services, the hospital system, the emergency department, aged care, and mental health, are delivering measurable productivity gains, meaningful health outcomes, and improvements in quality of life and national health. 

In a conversation following the UNSW-ESCoE Conference on Economic Measurement, Dr Catherine de Fontenay, Commissioner at the Productivity Commission, explained why traditional measurement approaches struggled to capture real improvements in health outcomes and how new advanced methods were changing that picture. 

Following her conference presentation, she was interviewed by Professor Kevin Fox from the School of Economics at UNSW Business School, and the two discussed how improved measurement could inform policy decisions in one of the economy’s largest and most complex sectors.

Rethinking how healthcare productivity is measured

Productivity in healthcare is difficult to measure. As Prof. Fox explained, “the problem is that a lot of this healthcare is not in the market sector [similar to education and training, for example] – so we don't have what you call real prices, or actual market transaction prices. So that's complicated. It's very hard to value things if you don't have a market price.”

New research papers and medical research, often drawing on large datasets, have improved data collection and refined methodologies, highlighting the need for better metrics, clearer benchmarks, and more robust productivity measures to assess the quality of care, patient care, and healthcare delivery. This emerging body of research, informed by OECD comparisons, aims to identify inefficiencies across the healthcare industry. This is expected to strengthen public health and the healthcare sector's resilience over time.

As part of this work, Dr de Fontenay said the Productivity Commission had examined new methods for estimating productivity in healthcare, a sector where conventional price-based methods often fail. “Normally, it's very hard to get an accurate measure of that productivity of the healthcare sector because we don't have real prices,” she said.

Photo gallery: The UNSW-ESCoE Conference on Economic Measurement 2025

“In a lot of this sector, there might be free services offered by government, it might be subsidised services, and so it's very difficult to work out what has happened over time to the value of the services we're receiving relative to the cost.”

Rather than treating costs as prices, the Commission returned to first principles. “We worked out, what's the health we're getting from these healthcare treatments, what's the value of those, the value of that better health, and how much is that worth to us, and how does that compare to the cost of that healthcare?”

This approach reframed productivity as the relationship between health outcomes and resources used, rather than changes in expenditure alone. “It's really important because healthcare spending has been going up faster than GDP,” Dr de Fontenay said. “We need to know whether we're getting value for money.”

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She explained that the standard approach used in official statistics treated the cost of delivering healthcare as a proxy for price. Under this method, productivity improvements were recorded only when costs fell. “If the health care you receive makes you live longer and happier, that's not captured in that type of measure,” she said.

To address this gap, the Commission used ABS survey data to examine disease prevalence, survival probabilities, and quality of life across several major disease groups. “We look at what your quality of life is while you have the disease, and what is your survival probability?” Dr de Fontenay said. “And using that information, we can work out what your valuation is of getting a better treatment.”

She acknowledged that assigning a monetary value to health outcomes and even to a person’s life was uncomfortable but necessary. “It's an awkward concept,” she said. “It's one of those ones that makes people hate economists, but I think it's important when we decide what we are going to spend on.”

“And as a rule of thumb, in 2018, we would measure the value of a life as roughly $110,000. So the way to think about that would be to say, if I come up with a new treatment that will give you an extra year of perfectly healthy life, and it costs less than $110,000, we as a society think that's worth investing in.”

Surprising results across diseases

When Prof. Fox compared the Commission’s results with official productivity statistics, the contrast was surprisingly stark. While ABS measures showed healthcare productivity growth of around 0.1 per cent per year between 2009 and 2019, the new outcome-based approach produced very different findings.

“We found that productivity in healthcare, in the diseases we were able to study, which is about a third of all healthcare, productivity, was an astonishing 3% per year,” said Dr de Fontenay, who attributed much of this growth to the effective adoption of medical innovations. “We think that a lot of this is absorbing new innovations from overseas, feeding them into our treatments, and using them really well,” she said.

However, results varied significantly across disease categories. “Cancers in particular had a really high productivity growth over this period,” Dr de Fontenay said, pointing to major improvements in survival probabilities.

By contrast, cardiovascular disease showed negative productivity growth under this framework. She explained that this reflected the method’s focus on outcomes conditional on having the disease. “Lots fewer people have had cardiovascular disease because we figured out that blood pressure medication and other simple changes to your life can really prevent heart attacks and strokes,” she said.

Implications for policy and future research

Dr de Fontenay situated the work within growing international literature, drawing on institutions such as Harvard, the US Bureau of Economic Analysis, and the UK Office for National Statistics. “We're all working out the best way forward so that we can get some national accounts that properly measure the productivity of health and related sectors,” she said.

She also said better measurement was essential for informed policy debate. “We're having a huge debate about productivity in our country,” Dr de Fontenay said. “And we can't have it without proper measurement of those large sectors of our economy.”

For early-career researchers, she highlighted health productivity and aged care as particularly promising areas. “If we're going to gather all that data, we should make good use of it,” she concluded.

Learn more: Danielle Wood on what Australia gets wrong about productivity

Healthcare productivity measurement FAQ

What is healthcare productivity, and how is it measured? Healthcare productivity measures the relationship between health outcomes achieved and the resources used to deliver healthcare services.

Why is healthcare productivity difficult to measure? Many healthcare services lack market prices, which complicates valuation using traditional price-based productivity methods.

How does outcome-based measurement differ from cost-based methods? Outcome-based measurement values changes in survival probabilities and quality of life rather than relying on expenditure as a proxy for price.

Why does healthcare productivity matter for policy? Accurate measurement informs decisions about healthcare spending growth, resource allocation and long-term health sector sustainability.

What role do survival probabilities and quality of life play in measurement? They provide data to estimate the value of improved treatments and assess productivity beyond changes in costs.

How can better measurement improve national accounts? Improved methods can refine the way large non-market sectors, such as healthcare, are represented in productivity statistics.