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Creating Health-Related Quality of Life value sets for the health sector

Creating Health-Related Quality of Life value sets

Measuring people’s quality of life associated with various dimensions of physical and mental health such as pain, disability, depression, etc – known as ‘Health-Related Quality of Life’ (HRQoL) – is useful for decision-making applications in the health sector.

1000minds created a user-friendly online tool for eliciting people’s preferences in terms of HRQoL – i.e. how they feel about pain, disability, depression, etc.

The tool was used with large representative samples of the New Zealand population to create ‘value sets’ (explained later below) for the two most widely used systems for representing HRQoL in the world: the ‘EQ-5D-5L’ and ‘SF-6D’ systems.

Important applications of value sets include ‘health technology prioritization’ to decide which pharmaceuticals to fund and assessing the performance of health care providers (e.g. hospitals, etc).

5000+ people surveyed using the 1000minds tool

3125 health states represented by the EQ-5D-5L

18,750 health states represented by the SF-6D

Policy-makers and researchers who use value sets characterizing how people feel about HRQoL need to be able to trust the method used to create it.

That’s why 1000minds developed a valid, reliable and user-friendly tool for creating HRQoL value sets based on the award-winning PAPRIKA method.

About Health-Related Quality of Life (HRQoL)

Quality of life vs length of life.

HRQoL relates to the perceived quality of a person’s life with respect to various dimensions of physical and mental ill health such as pain, disability, depression, etc.

Over the last half century, a global research industry has grown up around the creation of systems for describing and valuing HRQoL, resulting in more than a dozen such systems worldwide.

The two most common systems, used in scores of countries, are the EQ-5D-5L and SF-6D – which stand for ‘EuroQoL-5 Dimension-5 Levels’ (EQ-5D-5L) and ‘Short Form-6 Dimensions’ (SF-6D).

The EQ-5D-5L system has five dimensions for representing HRQoL: mobility, self-care, usual activities, pain/discomfort and anxiety/depression. Each dimension has five levels of severity: ranging from no problems to extreme problems.

Thus, with five dimensions and five levels on each dimension, the EQ-5D-5L represents 3125 (55) possible health states, each of which corresponds to a numerical value representing its HRQoL. Most of these 3125 values lie between 1 for ‘perfect’ health and 0 for dead, with negative values for health states worse than dead.

The SF-6D system is similar to the EQ-5D-5L except that it has six dimensions for representing HRQoL and five or six levels on each dimension. The SF-6D has 18,750 possible health states, corresponding to a value set with 18,750 values.

The challenge

Balancing cost vs outcomes.

HRQoL value sets such as the EQ-5D-5L and SF-6D are very useful for health policy-making. Therefore, policy-makers and researchers need to be able to trust the value sets’ accuracy (i.e. their validity and reliability).

For example, government agencies such as New Zealand’s PHARMAC and the UK’s NICE use value sets to decide which pharmaceuticals to fund (known as ‘health technology prioritization’).

Value sets are also used to create Patient-Reported Outcome Measures (PROMs) for monitoring the performance of health care providers such as hospitals, etc.

In order to be able to trust a value set’s accuracy, it’s important to be able to trust the method used to create it.

The solution

A trade-off decision for 2 health states.

1000minds invented a valid and reliable tool for creating HRQoL value sets based on the award-winning PAPRIKA method.

The tool is user-friendly and takes most people just 10-15 minutes to use. Thus, valuation data can be relatively easily and cheaply collected (compared to other approaches for creating value sets).

The tool can be used for surveying potentially 1000s of people to create a value set representing the HRQoL preferences of a country’s population overall. In the process, a value set for each individual participant is also created.

Thus, the tool is capable of creating both personal and social value sets – i.e. value sets for each individual participant and also a population overall.

The results

The 1000minds tool was used in 2019 to create an EQ-5D value set representing the HRQoL preferences of New Zealand adults. In 2022, the tool was also used to create a SF-6D value set.

Compared to other approaches for creating HRQoL value sets, the 1000minds tool significantly reduces the cost involved. The PAPRIKA method the tool is based on is also more valid and reliable than other methods.

In addition, the tool could be made available on tablets in doctors’ waiting rooms or as a mobile app for patients to quickly create their own personal value sets. Thus, the tool could be used to support decision-making at the individual patient level, enabling the patient’s preferences to be incorporated into their treatment decisions in ‘real time’.

Conclusion

The availability of a tool for creating valid and reliable HRQoL value sets that users can trust ultimately leads to better decision-making in the health sector, especially with respect to allocating scarce resources. The end result is better health outcomes.

This body of work is fully documented in the following peer-reviewed articles.

Articles

Read more about the use of 1000minds for creating HRQoL value sets for the EQ-5D-5L:

T Sullivan, P Hansen, F Ombler, S Derrett & N Devlin (2020), “A new tool for creating personal and social EQ-5D-5L value sets, including valuing ‘dead’”, Social Science & Medicine 246, 112707.

T Sullivan, R Turner, S Derrett & P Hansen (2021), “New Zealand population norms for the EQ-5D-5L constructed from the personal value sets of participants in a national survey”, Value in Health 24, 1308-18.