EQ-5D

Last updated

EQ-5D is a standardised measure of health-related quality of life developed by the EuroQol Group to provide a simple, generic questionnaire for use in clinical and economic appraisal and population health surveys. EQ-5D assesses health status in terms of five dimensions of health and is considered a ‘generic’ questionnaire because these dimensions are not specific to any one patient group or health condition. EQ-5D can also be referred to as a patient-reported outcome (PRO) measure, because patients can complete the questionnaire themselves to provide information about their current health status and how this changes over time. ‘EQ-5D’ is not an abbreviation and is the correct term to use when referring to the instrument in general. [1]

Contents

EQ-5D is widely used around the world in clinical trials and real-world clinical settings, population studies, and health economic evaluations. By mid-2020, the number of EQ-5D studies registered with the EuroQol Group totalled over 39,000. These comprised over 80 clinical areas and related to surgical procedures, hospital waiting lists, physiotherapy, general practice and primary care, and rehabilitation. The number of annual requests to use EQ-5D is approximately 5000, and EQ-5D data have been reported in over 8000 peer-reviewed papers over the past 30 years. [2]

EQ-5D can be used for a variety of purposes.

EQ-5D is recommended by many health technology assessment (HTA) bodies internationally as a key component of cost-utility analyses. [3]

EQ-5D was developed by the EuroQol Group, and its distribution and licensing are managed by the EuroQol Research Foundation. The EuroQol website [4] provides detailed information and the latest developments about EQ-5D including guidance for users, a list of available language versions and value sets by country/region, population norms, and key EQ-5D references. It also explains how to obtain the questionnaire. Those wishing to use EQ-5D must first register their study or trial via the website, using the page ‘How to obtain EQ-5D’, [5] which has more detailed information about registering, including an animated video. EQ-5D is provided without charging a license fee to non-commercial organisations after they have registered (approximately 95% of users), while commercial users are charged a fee. Registering a study does not obligate the purchase of an EQ-5D licence, but it enables the EuroQol Research Foundation to provide further information relevant to the type of study proposed, including terms and conditions (and licence fees if applicable).

Development

The EuroQol Group first met in 1987 with the goal of identifying a set of standardised questions that could be used to collect data on how people's lives were affected by illness and by health interventions. What was originally termed ‘the EuroQol instrument’ was developed by 1990 and contained questions on five aspects (or ‘dimensions’) of health, with three levels of severity in each dimension. [6] It was constructed simultaneously in five languages: Dutch, Finnish, Norwegian, Swedish, and English (which was to function as the source, or reference, language). [7] The questionnaire was renamed ‘EQ-5D’ in 1995 and now comprises a family of questionnaires: the three-level EQ-5D-3L, the five-level EQ-5D-5L, and the youth version EQ-5D-Y.

EQ-5D was designed as a self-completed questionnaire to fulfil two functions: (i) to provide a descriptive profile of current health status; and (ii) to provide a way of assigning a single numerical value to each of the possible health states described by the descriptive system, for use in economic evaluations of health care. [8] The requirements for its design were that (i) the dimensions should be relevant to both patients and members of the general population; (ii) the descriptive system should be simple – with as few dimensions as possible, and as few levels as possible within each dimension; (iii) it should be short and easily self-completed in a range of settings, and simple enough not to require detailed instructions; and (iv) it should be reliable, valid, and able to identify changes in health status related to illness and health interventions.

Components

The EQ-5D essentially consists of two pages: the EQ-5D descriptive system (page 2 of the questionnaire) and the EQ-5D visual analogue scale (EQ VAS) (page 3 of the questionnaire) (Video: Explaining the EQ-5D in about Two and Half Minutes). As noted above, ‘EQ-5D’ is not an abbreviation and is the correct term to use when referring to the instrument. Sample versions in UK English can be viewed at https://euroqol.org/eq-5d-instruments/sample-demo/.

Descriptive systems

The EQ-5D descriptive system comprises five dimensions: mobility, self-care, usual activities, pain and discomfort, and anxiety and depression. The number of levels in these dimensions differ in the EQ-5D-3L (three levels) and the EQ-5D-5L (five levels). The EQ-5D-Y has the same five dimensions, but they are worded more appropriately for young people.

EQ-5D-3L

In EQ-5D-3L, the five dimensions each have three response levels of severity.

  • The mobility dimension ranges from ‘I have no problems walking about’ to ‘I am confined to bed’.
  • The self-care dimension ranges from ‘I have no problems with self-care’ to ‘I am unable to wash or dress myself’.
  • The usual activities dimension concerns work, study, housework, family, or leisure activities and ranges from ‘I have no problems doing my usual activities’ to ‘I am unable to do my usual activities’.
  • The pain/discomfort dimension ranges from ‘I have no pain or discomfort’ to ‘I have extreme pain or discomfort’.
  • The anxiety/depression dimension ranges from ‘I am not anxious or depressed’ to ‘I am extremely anxious or depressed’.

Respondents are asked to choose the statement in each dimension that best describes their health status on the day they are surveyed. Their responses are coded as a number (1, 2, or 3) that corresponds to the respective level of severity: 1 indicates no problems, 2 some problems, and 3 extreme problems. In this way, a person's health state profile can be defined by a 5-digit number, ranging from 11111 (having no problems in any of the dimensions) to 33333 (having extreme problems in all the dimensions). The health state 12321 would indicate a person having no problems with mobility, having some problems with self-care, being unable to perform their usual activities, having some pain or discomfort, and not being anxious or depressed. In total, the EQ-5D-3L describes 243 (=3⁵) potential health states. [9]

EQ-5D-5L

EQ-5D-5L was introduced in 2009 with the aim of enhancing instrument sensitivity and providing respondents with the opportunity to provide a more detailed and accurate picture of their health. The EQ-5D-5L descriptive system uses the same five dimensions as the EQ-5D-3L but has two extra levels of severity in each dimension. The five levels in each dimension are worded as (1) ‘not /no problems’, (2) ‘slight problems’, (3) ‘moderate problems’, (4) ‘severe problems’, and (5) ‘unable to’ (mobility, self-care, usual activities), ‘extreme’ (pain/depression), or ‘extremely’ (anxiety/depression). A few changes in the wording of some levels were also made. For example, in the mobility dimension, the 3L term ‘confined to bed’ has been replaced with ‘unable to walk about’ in the 5L; and the first level of self-care in the 5L now refers to washing and dressing, to be consistent with the other levels. Because of the additional levels in EQ-5D-5L, the descriptive system describes 3125 (=5⁵) potential health states. [10]

EQ-5D-Y

The EQ-5D version (EQ-5D-Y) was introduced by the EuroQol Group in 2009 as a more suitable questionnaire for children and adolescents. [11] It is based on the EQ-5D-3L, but the wording has been modified to be more easily understood and relevant for younger people. The dimensions are: mobility (walking about); looking after myself; doing usual activities (e.g., going to school, hobbies, sports, playing, doing things with family and friends); having pain or discomfort; and feeling worried, sad, or unhappy. The levels for the first four dimensions are: ‘none/no problems’, ‘some (problems)’, and ‘a lot (of problems)’. The levels in the feeling worried, sad, or unhappy dimension are: ‘not’, ‘a bit’, and ‘very’. EQ-5D-Y is recommended for use with 8–11-year-olds and for 12–15-year-olds (although the adult version may be appropriate in the older age group, depending on study design; see Table 1. [12] For children aged 4–7 years, a proxy version should be used – i.e. a version of the questionnaire that is suitable for completion by a third party (e.g. a parent, caregiver, or health professional) on the child's behalf.

TABLE 1: Recommended age range of users of the EQ-5D-Y version [12]
Age rangeRecommendation
0–3 yearsNo EQ-5D-Y version is available for this age range
4–7 yearsFor children aged 4–7, a proxy version should be used

No self-reported EQ-5D-Y is available for this age range at present.

8–11 yearsUse EQ-5D-Y

The EQ-5D-Y is more understandable for children in this age range than an adult version of the EQ-5D

12–15 yearsBoth the EQ-5D-Y and adult EQ-5D versions can be used

An overlapping area. Generally, EQ-5D-Y is recommended. Depending on the study design, however, it might be appropriate to use one of the EQ-5D adult versions. For example, if a study includes both adult respondents and respondents between the ages of 12 and 15, the study team might prefer to use just one version of EQ-5D across the whole study population.

16 years and overUse an adult version (EQ-5D-3L or EQ-5D-5L)

A possible exception would be a study that only includes children up to age 18. In this case, EQ-5D-Y would be recommended across the full age range, to avoid using two different versions of EQ-5D.

EQ VAS

The second part of the questionnaire in all three versions of EQ-5D comprises a standard vertical 20-cm VAS that is calibrated from ‘the worst health you can imagine’ (scored 0) at its base to ‘the best health you can imagine’ (scored 100) at its apex. Respondents are asked to ‘mark an X on the scale to indicate how your health is TODAY’ and to write the number in an adjoining box.

This procedure makes it possible for respondents to provide a rating of their overall health on the day they complete the questionnaire. The VAS can also be used to assess changes in a patient's perception of their own health over time. For example, a patient may rate their current health as 50 on the scale, but after a medical intervention the respondent's rating may be 85, reflecting a substantial improvement in health status. When a group of patients completes the EQ-5D questionnaire before and after treatment, the change in self-rated health can be recorded from the VAS data.

EQ-5D versions

Modes of administration

EQ-5D is available in different formats depending on the mode of administration. The 3L, 5L, and Y versions can be self-completed on paper or by telephone or digitally, e.g., laptop/desktop, tablet, REDCap, interactive voice response (IVR), and smartphone/personal digital assistant (PDA). The EQ-5D can be hosted on local servers or on alternatives such as REDCap, LimeSurvey, Castor EDC, or Qualtrics platforms.

If people are unable to complete the EQ-5D themselves for any reason, e.g. due to ill-health or literacy problems, interviewer-administered versions are available for use in telephone, online, or face-to-face interviews.

It is sometimes appropriate to ask a caregiver (or proxy) to answer on behalf of people who cannot complete the questionnaire themselves (e.g. because they are too young, too ill, or have severe mental health problems or intellectual disability). The EQ-5D has two proxy versions: proxy version 1 asks the proxy to provide their own rating of the other person's health, while proxy version 2 asks the proxy how they think the person being evaluated would describe his/her own health if they were able to complete the questionnaire.

Translations

EQ-5D is available in more than 200 languages. Translation of the EQ-5D into new languages is overseen by the EuroQol Group's Version Management Committee (VMC) and is usually carried out in a collaboration with professional agencies with expertise in the cultural adaptation of PRO measures. [13]

All translations follow a standard and closely monitored process that conforms to internationally recognised guidelines. [14] The main steps in the translation process are forward translation, back translation, and cognitive debriefing (Animation video: Translating Patient Reported Outcome Measures for Use Around the World - The Example of EQ-5D). The goal of translation is to produce an EQ-5D version that has the same meaning as the English source version. Furthermore, it must sound natural and be easily understood in the target language.

Value sets for EQ-5D health states

When a person completes the EQ-5D questionnaire, the descriptive system produces a 5-digit health status profile that represents that person's level of reported problems on the five EQ-5D health dimensions. These profiles are usually referred to as ‘EQ-5D health states’. As noted above, EQ-5D-3L describes 243 potential health states while the EQ-5D-5L describes 3125 potential health states.

A numerical value can be attached to each EQ-5D health state to reflect how good or bad a health state is according to the preferences of the general population of a country/region. Health state values can also be referred to as EQ-5D ‘index values’ or ‘index scores’. The collection of index values for all possible EQ-5D states is called a value set. EQ-5D value sets are constructed at the national level, reflecting the belief that preferences for health can differ across populations.[ citation needed ]

Valuation research aims to measure people's preferences with respect to health – in other words, how health is valued. This involves the participation of a representative sample of people from the general population in a standardised valuation experiment. In this experiment, participants are asked to value health by reviewing EQ-5D health states (see utility assessment).[ citation needed ]

Because EQ-5D has values attached to its health states, it is widely used in the economic evaluation of health care interventions, where the convention is to measure health gains as value-weighted time using quality-adjusted life years (QALYs).[ citation needed ] The values can also inform other research, such as studies in the burden of illness.

Various techniques can be used to assign a value to an EQ-5D state. The EuroQol Group has done extensive research on different methods of valuing EQ-5D health states (see the historical review below). Most EQ-5D value sets are based on the time trade-off (TTO) approach, used either alone or in combination with discrete choice experiments (DCE). EQ-5D-3L value sets using TTO are available for over 30 countries or regions. [15] EQ-5D-5L value sets using TTO (+ DCE) are available for many countries, [16] and valuation studies are ongoing in further countries.

EQ-5D-3L value sets: VAS and TTO approaches

Valuation research in the late 1980s investigated several different methods, including ranking, magnitude estimation, paired comparisons as well as several forms of rating, as ways of obtaining values for health states and resulted in the choice of a VAS approach. [17] At that time, other methods such as TTO and Standard Gamble (SG) were primarily associated with the development in Canada of the Health Utilities Index (HUI).

Investigation into valuation methods continued, [18] including a head:head comparison between TTO and SG which resulted in the selection of TTO for use in the 1993 Measurement and Valuation of Health (MVH) study, a programme funded by the UK Department of Health and carried out by the University of York, UK. This generated an EQ-5D value set based on TTO values from the general public that could be used to generate QALYs. The MVH value set [19] [20] became widely applied in economic evaluations in the UK and other countries, and continues to be used today.

Over the following years, EQ-5D-3L value sets were produced for many countries using either TTO and/or VAS approaches [8]. Over time, however, TTO emerged as the method of first choice.

The EQ-net project of 1998–2001, which was funded by the Biomed programme of the European Commission, resulted in the establishment of TTO and VAS databases to facilitate international comparisons of health state values. [21] [22]

In 2009, the MVH protocol for valuation of EQ-5D-3L health states was refined to improve the data collection process; this was referred to as the ‘Paris protocol’. This protocol has been used in a number of EQ-5D-3L valuation studies, including those of South Korea, China, France, Portugal, and Brazil. [23]

The development of the EQ-5D-5L renewed interest in the methodology of valuing health. Until 5L value sets were produced, interim values for the EQ-5D-5L were made available using a ‘crosswalk’ approach based on a study in six countries, in which the EQ-5D-3L and 5L had been completed in parallel. [24] This meant that values for EQ-5D-5L health states could be derived from existing EQ-5D-3L value sets. [25]

EQ-5D-5L value sets: EQ-VT combining composite TTO and DCE

Value sets for QALY calculations are required to range from 1 (representing full health) to 0 (representing dead), and it is generally accepted that very poor health states may be considered worse than being dead. Due to the recognised challenges of valuing states worse than death, the EuroQol Group initiated a programme of research to further investigate valuation of these states. This involved testing new methods for TTO, including multiple variants of ‘lead-time’ TTO [26] and ‘lag-time’ TTO. [27] [28] It should also be noted that in the 5L valuation procedure EuroQol continued to use TTO, but VAS was discarded and replaced by DCE.

With the introduction of 5L, the opportunity was taken to introduce a standardised protocol for the first time. This decision was based on multiple considerations. Variability in how value sets were produced had provide much information about what worked and what did not work in the valuation of health, but it limited the comparability of value sets. Moreover, valuation of 5L was considered more challenging than valuation of 3L – hence efforts to define best practice had to be renewed, to ensure high-quality data. Furthermore, the programme of work that followed enabled several open methodological questions to be addressed.[ citation needed ]

A key aspect in this research was the potential of computer-based technology to help guide the respondents through the valuation tasks. The programme led to a new TTO approach (the composite TTO; cTTO [29] ) that removed the need for arbitrary rescaling of values for states worse than dead. Composite TTO uses the conventional approach for states considered better than dead, but lead-time TTO for states considered worse than dead. [30] At the same time, new approaches to health state valuation were being tested, such as DCEs. [31]

This work culminated in the EQ-VT (EuroQol Valuation Technology) protocol, which uses a standardised computer-assisted personal interview (CAPI) to derive health preferences for EQ-5D-5L using cTTO and DCE [30]. The first valuation studies using this approach were conducted in Canada, China, England, the Netherlands, and Spain in 2012. Following several refinements, the current EQ-VT is labelled version 2.1. [32] By September 2019, the EQ-VT had been used in 34 countries around the world.[ citation needed ]

EQ-5D-Y value sets

Due to the added difficulties of obtaining values for health states in paediatric populations, value sets for the EQ-5D-Y have taken longer to develop. In 2020, the EuroQol Group published an international valuation protocol for the youth version [33] [34] and the first EQ-5D-Y valuation study, for Slovenia, was published in 2021. [35] Further EQ-5D-Y valuation studies are underway in countries around the world. Note that EQ-5D-3L value sets should not be used to assign values to EQ-5D-Y health states. [36] [37]

EQ-5D data analysis

More detailed information on how to analyse EQ-5D data is available in a book [38] that describes various analytical approaches for the EQ-5D descriptive profiles, EQ VAS, and EQ-5D value sets.

EQ-5D data can be analysed in several different formats - per dimension, as a descriptive health state, as a weighted index on a 0-1 scale and as an overall measure of self-assessed health status (EQ VAS). It is important to consider these different formats separately, especially when reaching a judgement regarding the psychometric properties of the instrument as a whole.

Theoretical and psychometric properties

The validity, reliability, and responsiveness of EQ-5D-3L have been assessed for EQ-5D versions in many different health conditions, including cardiovascular disease, [39] [40] mental health populations, [41] aged care, [42] skin conditions, [43] cancer, [44] and total knee arthroplasty. [45]

The brevity of EQ-5D-3L is likely to be a major factor in its widespread use, but the three-level format can be a limitation in some clinical areas. The EQ-5D-3L descriptive system can be less sensitive to small and medium changes in health status, [46] so it may be less able to detect change in some conditions. [47] [48]

The 5L descriptive system has shown improved responsiveness compared to the 3L system, e.g. in a comparison of eight patient groups,[ citation needed ] osteoarthritis, [49] and joint replacement, [50] as well as acceptable psychometric properties in conditions such as stroke, [51] chronic obstructive lung disease, [52] and scoliosis. [53] Some studies have assessed the EQ-5D-3L and EQ-5D-5L together. [54]

The psychometric properties of EQ-5D-Y have been assessed in a variety of settings and conditions. [33] [55]

A value set derived from a general population sample has been criticized when used for economic evaluation for a lack of a compelling theoretical support [56] however, such "experienced" value sets are nonetheless relevant in clinical settings or in population health studies (see below) where social preference weighted index scores are contraindicated.

EQ-5D in population health studies

EQ-5D has been extensively utilised in population health studies, both at the national level and for subsections of a country's population, such as a specific region. Data collected with EQ-5D can be used to assess and compare health status between groups of patients, between patients and the general population, or between the general populations of different countries. It can also be used to monitor changes in health status over time at population level.[ citation needed ]

Self-reported health as captured by EQ VAS comes directly from the respondent and perfectly meets the published FDA criteria for Patient Reported Outcome (PRO) measures. Imposing social preference weights on such data violates the PRO condition and creates obstacles in cross-national comparisons of population health.

Cross-country analyses of self-reported population health using EQ-5D data have been reported and subsequently updated. [21] [57] [58] The first publication incorporated data from 15 countries,[ citation needed ] and the second from 24 countries. [57] Since then, EQ-5D-5L population norms have also been published for Japanese, [59] German, [60] and South Australian populations. [61]

EQ-5D in economic evaluation

EQ-5D is the most widely used health-related quality of life questionnaire in health economic evaluations. [62] EQ-5D can be used to derive a set of values that reflect people's opinions of the relative importance of different health problems. These values can be used to derive QALYs for application in cost-effectiveness and cost-utility evaluations.

In a review study of recommendations from national HTA agencies, EQ-5D, HUI, and SF-6D were the three multi-attribute utility instruments (MAUIs) most frequently mentioned in HTA guidelines. The most commonly-cited MAUI (in 85% of pharmacoeconomic guidelines) was the index form of EQ-5D, either as a preferred MAUI or as an example of a suitable MAUI for use in cost-utility analysis in HTA. [3]

Alternatives

There are various other multi-attribute utility instruments for health conditions, for example: SF-6D, Health Utilities Index (HUI), 15D, Quality of Well-Being, and AQoL-8D. [63]

Related Research Articles

<span class="mw-page-title-main">Quality-adjusted life year</span> Measure of disease burden

The quality-adjusted life year (QALY) is a generic measure of disease burden, including both the quality and the quantity of life lived. It is used in economic evaluation to assess the value of medical interventions. One QALY equates to one year in perfect health. QALY scores range from 1 to 0 (dead). QALYs can be used to inform health insurance coverage determinations, treatment decisions, to evaluate programs, and to set priorities for future programs.

A pain scale measures a patient's pain intensity or other features. Pain scales are a common communication tool in medical contexts, and are used in a variety of medical settings. Pain scales are a necessity to assist with better assessment of pain and patient screening. Pain measurements help determine the severity, type, and duration of the pain, and are used to make an accurate diagnosis, determine a treatment plan, and evaluate the effectiveness of treatment. Accurately measuring pain is a necessity in medical settings, especially if the pain measurement is going to be used as a screening tool, either for potential diseases or medical problems, or as a type of triage to determine urgency of one patient over another. Pain scales are based on trust, cartoons (behavioral), or imaginary data, and are available for neonates, infants, children, adolescents, adults, seniors, and persons whose communication is impaired. Pain assessments are often regarded as "the 5th Vital Sign".

<span class="mw-page-title-main">Disability-adjusted life year</span> Measure of disease burden

The disability-adjusted life year (DALY) is a measure of overall disease burden, expressed as the number of years lost due to ill-health, disability or early death. It was developed in the 1990s as a way of comparing the overall health and life expectancy of different countries.

A patient-reported outcome (PRO) is a health outcome directly reported by the patient who experienced it. It stands in contrast to an outcome reported by someone else, such as a physician-reported outcome, a nurse-reported outcome, and so on. PRO methods, such as questionnaires, are used in clinical trials or other clinical settings, to help better understand a treatment's efficacy or effectiveness. The use of digitized PROs, or electronic patient-reported outcomes (ePROs), is on the rise in today's health research setting.

In health economics, time trade-off (TTO) is a technique used to measure the quality of life that a person or group is experiencing. An individual will be presented with a set of directions such as:

Imagine that you are told that you have 10 years left to live. In connection with this you are also told that you can choose to live these 10 years in your current health state or that you can choose to give up some life years to live for a shorter period in full health. Indicate with a cross on the line the number of years in full health that you think is of equal value to 10 years in your current health state.

<span class="mw-page-title-main">Prucalopride</span> Drug used to treat chronic constipation

Prucalopride, sold under brand names Resolor and Motegrity among others, is a medication acting as a selective, high affinity 5-HT4 receptor agonist which targets the impaired motility associated with chronic constipation, thus normalizing bowel movements. Prucalopride was approved for medical use in the European Union in 2009, in Canada in 2011, in Israel in 2014, and in the United States in December 2018. The drug has also been tested for the treatment of chronic intestinal pseudo-obstruction.

<span class="mw-page-title-main">Quality of life (healthcare)</span> Notion in healthcare

In general, quality of life is the perceived quality of an individual's daily life, that is, an assessment of their well-being or lack thereof. This includes all emotional, social and physical aspects of the individual's life. In health care, health-related quality of life (HRQoL) is an assessment of how the individual's well-being may be affected over time by a disease, disability or disorder.

The Patient Health Questionnaire (PHQ) is a multiple-choice self-report inventory that is used as a screening and diagnostic tool for mental health disorders of depression, anxiety, alcohol, eating, and somatoform disorders. It is the self-report version of the Primary Care Evaluation of Mental Disorders (PRIME-MD), a diagnostic tool developed in the mid-1990s by Pfizer Inc. The length of the original assessment limited its feasibility; consequently, a shorter version, consisting of 11 multi-part questions - the Patient Health Questionnaire was developed and validated.

The Diabetes Health Profile (DHP) is a diabetes-specific patient reported outcome measure (PROM) developed to evaluate the health-related quality of life (HRQoL) of people living with Type 1 and Type 2 diabetes aged 16 years and older. It has been used in community surveys, research studies, clinical trials, and educational interventions both in Europe and completed globally by more than 10,000 patients. The DHP was the diabetes-specific PROM selected by the UK Department of Health for their Long Terms Conditions PROM Pilot Study being carried out by Oxford University.

The Patient Activation Measure (PAM) is a commercial product which assesses an individual's knowledge, skill, and confidence for managing one's health and healthcare. Individuals who measure high on this assessment typically understand the importance of taking a pro-active role in managing their health and have the skills and confidence to do so.

The minimal important difference (MID) or minimal clinically important difference (MCID) is the smallest change in a treatment outcome that an individual patient would identify as important and which would indicate a change in the patient's management.

The Quality of Life Assessment of Growth Hormone Deficiency in Adults (QoL-AGHDA) is a disease specific patient-reported outcome measure which measures the effect growth hormone deficiency has on adult patients. The score of the QoL-AGHDA is used to determine the extent to which growth hormone deficiency has affected the patient’s quality of life, and what treatment can then be administered. A high score on the QoL-AGHDA indicates that the patient suffers from many symptoms and therefore has a lower quality of life.

The Rheumatoid Arthritis Quality of Life Questionnaire (RAQoL) is a disease-specific patient-reported outcome measure which determines the effect rheumatoid arthritis has on a patient’s quality of life. The RAQoL has 30 items with a yes and no response format and takes about six minutes to complete.

The Cambridge Pulmonary Hypertension Outcome Review (CAMPHOR) is a disease specific patient-reported outcome measure which assesses quality of life of patients with pulmonary hypertension (PH). It was the first pulmonary hypertension specific questionnaire for assessing patient reported symptoms, quality of life and functioning.

The Psoriatic Arthritis Quality of Life (PsAQoL) measure is a disease specific patient-reported outcome measure which measures the effect that psoriatic arthritis has on a patient’s quality of life.

The Unidimensional Fatigue Impact Scale (U-FIS) is a disease-specific patient-reported outcome measure which measures the impact of multiple sclerosis related fatigue. It is a 22-item unidimensional scale which is based on needs-based quality of life theory.

The Quality of Well-Being Scale (QWB) is a general health quality of life questionnaire which measures overall status and well-being over the previous three days in four areas: physical activities, social activities, mobility, and symptom/problem complexes.

In medicine, insomnia is widely measured using the Athens Insomnia Scale (AIS). AIS was first introduced in the year 2000 by a group of researchers from Athens, Greece to assess the insomnia symptoms in patients with sleep disorders.

<span class="mw-page-title-main">Donald L. Patrick</span> American social scientist

Donald L. Patrick is a social scientist, academic, and an author. He is a Professor Emeritus of Health Systems and Population Health at the University of Washington, Director of Seattle Quality of Life Group, and Creator of the Biobehavioral Cancer Prevention and Control Training Program jointly with the Fred Hutchinson Cancer Center. He has served as the co-chair of the Cochrane Collaboration's Patient Reported Outcomes Methods Group. His research interests revolve around various aspects of public health which integrate the themes from fields such as psychological intervention, social stratification, public health, and quality of life. Much of his research works have focused on outcomes research on vulnerable populations, health disparities, and end-of-life-care.

References

  1. Brooks, Richard; Boye, Kristina S.; Slaap, Bernhard (December 2020). "EQ-5D: a plea for accurate nomenclature". Journal of Patient-Reported Outcomes. 4 (1): 52. doi: 10.1186/s41687-020-00222-9 . PMC   7334333 . PMID   32620995.
  2. https://pubmed.ncbi.nlm.nih.gov/?term=eq-5d&filter=dates.1990-2020%2F12%2F21 (accessed 21st December 2020).[ not specific enough to verify ]
  3. 1 2 Kennedy-Martin, Matthew; Slaap, Bernhard; Herdman, Michael; van Reenen, Mandy; Kennedy-Martin, Tessa; Greiner, Wolfgang; Busschbach, Jan; Boye, Kristina S. (November 2020). "Which multi-attribute utility instruments are recommended for use in cost-utility analysis? A review of national health technology assessment (HTA) guidelines". The European Journal of Health Economics. 21 (8): 1245–1257. doi:10.1007/s10198-020-01195-8. PMC   7561556 . PMID   32514643.
  4. https://euroqol.org
  5. "How to obtain EQ-5D – EQ-5D".
  6. EuroQol, Group. (December 1990). "EuroQol - a new facility for the measurement of health-related quality of life". Health Policy. 16 (3): 199–208. doi:10.1016/0168-8510(90)90421-9. PMID   10109801.
  7. Brooks, Richard (2013). The EuroQol Group after 25 years. doi:10.1007/978-94-007-5158-3. ISBN   978-94-007-5157-6. S2CID   7173431.[ page needed ]
  8. Rabin, Rosalind; Charro, Frank de (January 2001). "EQ-SD: a measure of health status from the EuroQol Group". Annals of Medicine. 33 (5): 337–343. doi: 10.3109/07853890109002087 . PMID   11491192. S2CID   32312004.
  9. EuroQol Research Foundation. EQ-5D-3L User Guide, 2018. Available from https://euroqol.org/publications/user-guides.
  10. EuroQol Research Foundation. EQ-5D-5L User Guide, 2019. Available from: https://euroqol.org/publications/user-guides.
  11. Wille, Nora; Badia, Xavier; Bonsel, Gouke; Burström, Kristina; Cavrini, Gulia; Devlin, Nancy; Egmar, Ann-Charlotte; Greiner, Wolfgang; Gusi, Narcis; Herdman, Michael; Jelsma, Jennifer; Kind, Paul; Scalone, Luciana; Ravens-Sieberer, Ulrike (August 2010). "Development of the EQ-5D-Y: a child-friendly version of the EQ-5D". Quality of Life Research. 19 (6): 875–886. doi:10.1007/s11136-010-9648-y. PMC   2892611 . PMID   20405245.
  12. 1 2 EuroQol Research Foundation. EQ-5D-Y User Guide, Version 2.0, 2020. Available from: https://euroqol.org/publications/user-guides/.
  13. Rabin, Rosalind; Gudex, Claire; Selai, Caroline; Herdman, Michael (January 2014). "From Translation to Version Management: A History and Review of Methods for the Cultural Adaptation of the EuroQol Five-Dimensional Questionnaire". Value in Health. 17 (1): 70–76. doi: 10.1016/j.jval.2013.10.006 . PMID   24438719.
  14. Wild, Diane; Grove, Alyson; Martin, Mona; Eremenco, Sonya; McElroy, Sandra; Verjee-Lorenz, Aneesa; Erikson, Pennifer; ISPOR Task Force for Translation and Cultural, Adaptation. (March 2005). "Principles of Good Practice for the Translation and Cultural Adaptation Process for Patient-Reported Outcomes (PRO) Measures: Report of the ISPOR Task Force for Translation and Cultural Adaptation". Value in Health. 8 (2): 94–104. doi: 10.1111/j.1524-4733.2005.04054.x . PMID   15804318.
  15. "Valuation – EQ-5D".
  16. "Valuation – EQ-5D".
  17. Devlin, Nancy J.; Brooks, Richard (April 2017). "EQ-5D and the EuroQol Group: Past, Present and Future". Applied Health Economics and Health Policy. 15 (2): 127–137. doi:10.1007/s40258-017-0310-5. PMC   5343080 . PMID   28194657.
  18. Brooks, Richard (July 1996). "EuroQol: the current state of play". Health Policy. 37 (1): 53–72. doi:10.1016/0168-8510(96)00822-6. PMID   10158943.
  19. Dolan, Paul; Gudex, Claire; Kind, Paul; Williams, Alan (1996). "The time trade-off method: Results from a general population study". Health Economics. 5 (2): 141–154. doi:10.1002/(SICI)1099-1050(199603)5:2<141::AID-HEC189>3.0.CO;2-N. PMID   8733106.
  20. Dolan, Paul (November 1997). "Modeling Valuations for EuroQol Health States". Medical Care. 35 (11): 1095–1108. doi:10.1097/00005650-199711000-00002. PMID   9366889.
  21. 1 2 Szende, Agota; Oppe, Mark; Devlin, Nancy, eds. (2007). EQ-5D Value Sets. EuroQol Group Monographs. Vol. 2. doi:10.1007/1-4020-5511-0. ISBN   978-1-4020-5510-2.[ page needed ]
  22. Brooks, Richard; Rabin, Rosalind; De Charro, Frank, eds. (2003). The Measurement and Valuation of Health Status Using EQ-5D: A European Perspective. doi:10.1007/978-94-017-0233-1. ISBN   978-90-481-6261-1. S2CID   45485182.[ page needed ]
  23. Oppe, Mark; Rand-Hendriksen, Kim; Shah, Koonal; Ramos‐Goñi, Juan M.; Luo, Nan (October 2016). "EuroQol Protocols for Time Trade-Off Valuation of Health Outcomes". PharmacoEconomics. 34 (10): 993–1004. doi:10.1007/s40273-016-0404-1. PMC   5023738 . PMID   27084198.
  24. Janssen, M. F.; Pickard, A. Simon; Golicki, Dominik; Gudex, Claire; Niewada, Maciej; Scalone, Luciana; Swinburn, Paul; Busschbach, Jan (September 2013). "Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study". Quality of Life Research. 22 (7): 1717–1727. doi:10.1007/s11136-012-0322-4. PMC   3764313 . PMID   23184421.
  25. van Hout, Ben; Janssen, M.F.; Feng, You-Shan; Kohlmann, Thomas; Busschbach, Jan; Golicki, Dominik; Lloyd, Andrew; Scalone, Luciana; Kind, Paul; Pickard, A. Simon (July 2012). "Interim Scoring for the EQ-5D-5L: Mapping the EQ-5D-5L to EQ-5D-3L Value Sets". Value in Health. 15 (5): 708–715. doi: 10.1016/j.jval.2012.02.008 . PMID   22867780.
  26. Robinson, Angela; Spencer, Anne (April 2006). "Exploring challenges to TTO utilities: valuing states worse than dead". Health Economics. 15 (4): 393–402. doi:10.1002/hec.1069. PMID   16389652.
  27. Devlin, Nancy; Buckingham, Ken; Shah, Koonal; Tsuchiya, Aki; Tilling, Carl; Wilkinson, Grahame; van Hout, Ben (May 2013). "A comparison of alternative variants of the lead and lag time TTO" (PDF). Health Economics. 22 (5): 517–532. doi:10.1002/hec.2819. PMID   22715069.
  28. Attema, Arthur E.; Versteegh, Matthijs M.; Oppe, Mark; Brouwer, Werner B. F.; Stolk, Elly A. (April 2013). "Lead time TTO: leading to better health state valuations?". Health Economics. 22 (4): 376–392. doi:10.1002/hec.2804. PMID   22396243.
  29. Oppe, Mark; Devlin, Nancy J.; van Hout, Ben; Krabbe, Paul F.M.; de Charro, Frank (June 2014). "A Program of Methodological Research to Arrive at the New International EQ-5D-5L Valuation Protocol". Value in Health. 17 (4): 445–453. doi: 10.1016/j.jval.2014.04.002 . PMID   24969006.
  30. Janssen, Bas M. F.; Oppe, Mark; Versteegh, Matthijs M.; Stolk, Elly A. (July 2013). "Introducing the composite time trade-off: a test of feasibility and face validity". The European Journal of Health Economics. 14 (S1): 5–13. doi:10.1007/s10198-013-0503-2. PMC   3728457 . PMID   23900660.
  31. Stolk, Elly A.; Oppe, Mark; Scalone, Luciana; Krabbe, Paul F.M. (December 2010). "Discrete Choice Modeling for the Quantification of Health States: The Case of the EQ-5D". Value in Health. 13 (8): 1005–1013. doi: 10.1111/j.1524-4733.2010.00783.x . hdl: 1765/21600 . PMID   20825618.
  32. Stolk, Elly; Ludwig, Kristina; Rand, Kim; van Hout, Ben; Ramos-Goñi, Juan Manuel (January 2019). "Overview, Update, and Lessons Learned From the International EQ-5D-5L Valuation Work: Version 2 of the EQ-5D-5L Valuation Protocol". Value in Health. 22 (1): 23–30. doi: 10.1016/j.jval.2018.05.010 . PMID   30661630. S2CID   58620873.
  33. 1 2 Kreimeier, Simone; Greiner, Wolfgang (January 2019). "EQ-5D-Y as a Health-Related Quality of Life Instrument for Children and Adolescents: The Instrument's Characteristics, Development, Current Use, and Challenges of Developing Its Value Set". Value in Health. 22 (1): 31–37. doi: 10.1016/j.jval.2018.11.001 . PMID   30661631. S2CID   58601153.
  34. Ramos-Goñi, Juan M.; Oppe, Mark; Stolk, Elly; Shah, Koonal; Kreimeier, Simone; Rivero-Arias, Oliver; Devlin, Nancy (July 2020). "International Valuation Protocol for the EQ-5D-Y-3L". PharmacoEconomics. 38 (7): 653–663. doi: 10.1007/s40273-020-00909-3 . hdl: 11343/252049 . PMID   32297224. S2CID   215774622.
  35. Prevolnik Rupel, Valentina; Ogorevc, Marko; IMPACT HTA HRQoL Group (April 2021). "EQ-5D-Y Value Set for Slovenia". PharmacoEconomics. 39 (4): 463–471. doi:10.1007/s40273-020-00994-4. PMC   8009800 . PMID   33565048.
  36. Kreimeier, Simone; Oppe, Mark; Ramos-Goñi, Juan M.; Cole, Amanda; Devlin, Nancy; Herdman, Michael; Mulhern, Brendan; Shah, Koonal K.; Stolk, Elly; Rivero-Arias, Oliver; Greiner, Wolfgang (November 2018). "Valuation of EuroQol Five-Dimensional Questionnaire, Youth Version (EQ-5D-Y) and EuroQol Five-Dimensional Questionnaire, Three-Level Version (EQ-5D-3L) Health States: The Impact of Wording and Perspective". Value in Health. 21 (11): 1291–1298. doi: 10.1016/j.jval.2018.05.002 . hdl: 10453/130540 . PMID   30442276. S2CID   53565736.
  37. Kind, Paul; Klose, Kristina; Gusi, Narcis; Olivares, Pedro R.; Greiner, Wolfgang (October 2015). "Can adult weights be used to value child health states? Testing the influence of perspective in valuing EQ-5D-Y". Quality of Life Research. 24 (10): 2519–2539. doi:10.1007/s11136-015-0971-1. PMC   4564451 . PMID   25894060.
  38. Devlin, Nancy; Parkin, David; Janssen, Bas (2020). Methods for Analysing and Reporting EQ-5D Data. doi:10.1007/978-3-030-47622-9. ISBN   978-3-030-47621-2. PMID   33347096. S2CID   220656994.[ page needed ]
  39. Dyer, Matthew TD; Goldsmith, Kimberley A; Sharples, Linda S; Buxton, Martin J (2010). "A review of health utilities using the EQ-5D in studies of cardiovascular disease". Health and Quality of Life Outcomes. 8 (1): 13. doi: 10.1186/1477-7525-8-13 . PMC   2824714 . PMID   20109189.
  40. Batóg, Paulina; Rencz, Fanni; Péntek, Márta; Gulácsi, László; Filipiak, Krzysztof J.; Rupel, Valentina Prevolnik; Simon, Judit; Brodszky, Valentin; Baji, Petra; Závada, Jakub; Petrova, Guenka; Rotar, Alexandru; Golicki, Dominik (2018). "EQ-5D studies in cardiovascular diseases in eight Central and Eastern European countries: a systematic review of the literature". Kardiologia Polska (Polish Heart Journal). 76 (5): 860–870. doi: 10.5603/KP.a2018.0033 . PMID   29350378.
  41. Brazier, John; Connell, Janice; Papaioannou, Diana; Mukuria, Clara; Mulhern, Brendan; Peasgood, Tessa; Lloyd Jones, Myfawnwy; Paisley, Suzy; O’Cathain, Alicia; Barkham, Michael; Knapp, Martin; Byford, Sarah; Gilbody, Simon; Parry, Glenys (May 2014). "A systematic review, psychometric analysis and qualitative assessment of generic preference-based measures of health in mental health populations and the estimation of mapping functions from widely used specific measures". Health Technology Assessment. 18 (34): vii–viii, xiii–xxv, 1–188. doi:10.3310/hta18340. PMC   4781324 . PMID   24857402.
  42. Bulamu, Norma B.; Kaambwa, Billingsley; Ratcliffe, Julie (9 November 2015). "A systematic review of instruments for measuring outcomes in economic evaluation within aged care". Health and Quality of Life Outcomes. 13 (1): 179. doi: 10.1186/s12955-015-0372-8 . PMC   4640110 . PMID   26553129.
  43. Yang, Yaling; Brazier, John; Longworth, Louise (December 2015). "EQ-5D in skin conditions: an assessment of validity and responsiveness". The European Journal of Health Economics. 16 (9): 927–939. doi:10.1007/s10198-014-0638-9. PMC   4646948 . PMID   25358263.
  44. Schwenkglenks, Matthias; Matter-Walstra, Klazien (3 March 2016). "Is the EQ-5D suitable for use in oncology? An overview of the literature and recent developments". Expert Review of Pharmacoeconomics & Outcomes Research. 16 (2): 207–219. doi:10.1586/14737167.2016.1146594. PMID   26808097. S2CID   22941200.
  45. Shim, J.; Hamilton, D. F. (July 2019). "Comparative responsiveness of the PROMIS-10 Global Health and EQ-5D questionnaires in patients undergoing total knee arthroplasty". The Bone & Joint Journal. 101-B (7): 832–837. doi:10.1302/0301-620X.101B7.BJJ-2018-1543.R1. PMC   6616061 . PMID   31256677.
  46. Herdman, M.; Gudex, C.; Lloyd, A.; Janssen, Mf.; Kind, P.; Parkin, D.; Bonsel, G.; Badia, X. (December 2011). "Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L)". Quality of Life Research. 20 (10): 1727–1736. doi:10.1007/s11136-011-9903-x. PMC   3220807 . PMID   21479777.
  47. Payakachat, Nalin; Ali, Mir M.; Tilford, J. Mick (November 2015). "Can The EQ-5D Detect Meaningful Change? A Systematic Review". PharmacoEconomics. 33 (11): 1137–1154. doi:10.1007/s40273-015-0295-6. PMC   4609224 . PMID   26040242.
  48. Hounsome, Natalia; Orrell, Martin; Edwards, Rhiannon Tudor (March 2011). "EQ-5D as a Quality of Life Measure in People with Dementia and Their Carers: Evidence and Key Issues". Value in Health. 14 (2): 390–399. doi: 10.1016/j.jval.2010.08.002 . PMID   21402307.
  49. Bilbao, Amaia; García-Pérez, Lidia; Arenaza, Juan Carlos; García, Isidoro; Ariza-Cardiel, Gloria; Trujillo-Martín, Elisa; Forjaz, Maria João; Martín-Fernández, Jesús (November 2018). "Psychometric properties of the EQ-5D-5L in patients with hip or knee osteoarthritis: reliability, validity and responsiveness". Quality of Life Research. 27 (11): 2897–2908. doi:10.1007/s11136-018-1929-x. PMID   29978346. S2CID   49574374.
  50. Jin, Xuejing; Al Sayah, Fatima; Ohinmaa, Arto; Marshall, Deborah A.; Johnson, Jeffrey A. (September 2019). "Responsiveness of the EQ-5D-3L and EQ-5D-5L in patients following total hip or knee replacement". Quality of Life Research. 28 (9): 2409–2417. doi:10.1007/s11136-019-02200-1. PMID   31089988. S2CID   153313710.
  51. Chen, Poyu; Lin, Keh-Chung; Liing, Rong-Jiuan; Wu, Ching-Yi; Chen, Chia-Ling; Chang, Ku-Chou (June 2016). "Validity, responsiveness, and minimal clinically important difference of EQ-5D-5L in stroke patients undergoing rehabilitation". Quality of Life Research. 25 (6): 1585–1596. doi:10.1007/s11136-015-1196-z. PMID   26714699. S2CID   21457035.
  52. Nolan, Claire M; Longworth, Louise; Lord, Joanne; Canavan, Jane L; Jones, Sarah E; Kon, Samantha S C; Man, William D-C (June 2016). "The EQ-5D-5L health status questionnaire in COPD: validity, responsiveness and minimum important difference". Thorax. 71 (6): 493–500. doi:10.1136/thoraxjnl-2015-207782. PMC   4893131 . PMID   27030578.
  53. Cheung, Prudence Wing Hang; Wong, Carlos King Ho; Lau, Sin Ting; Cheung, Jason Pui Yin (February 2018). "Responsiveness of the EuroQoL 5-dimension (EQ-5D) in adolescent idiopathic scoliosis". European Spine Journal. 27 (2): 278–285. doi:10.1007/s00586-017-5330-1. hdl: 10722/247508 . PMID   28993884. S2CID   3356866.
  54. Qian, Xinyu; Tan, Rachel Lee-Yin; Chuang, Ling-Hsiang; Luo, Nan (February 2020). "Measurement Properties of Commonly Used Generic Preference-Based Measures in East and South-East Asia: A Systematic Review". PharmacoEconomics. 38 (2): 159–170. doi:10.1007/s40273-019-00854-w. PMC   7081654 . PMID   31761995.
  55. Ravens-Sieberer, Ulrike; Wille, Nora; Badia, Xavier; Bonsel, Gouke; Burström, Kristina; Cavrini, Gulia; Devlin, Nancy; Egmar, Ann-Charlotte; Gusi, Narcis; Herdman, Michael; Jelsma, Jennifer; Kind, Paul; Olivares, Pedro R.; Scalone, Luciana; Greiner, Wolfgang (August 2010). "Feasibility, reliability, and validity of the EQ-5D-Y: results from a multinational study". Quality of Life Research. 19 (6): 887–897. doi:10.1007/s11136-010-9649-x. PMC   2892614 . PMID   20401552.
  56. Gandjour, Afschin (July 2010). "Theoretical Foundation of Patient v. Population Preferences in Calculating QALYs". Medical Decision Making. 30 (4): E57–E63. doi:10.1177/0272989X10370488. PMID   20511562. S2CID   26946686.
  57. 1 2 Szende, A.; Janssen, B.; Cabases, J. (2014). Szende, Agota; Janssen, Bas; Cabases, Juan (eds.). Self-Reported Population Health: An International Perspective based on EQ-5D. doi:10.1007/978-94-007-7596-1. ISBN   978-94-007-7595-4. PMID   29787044. S2CID   21394237.[ page needed ]
  58. Janssen, M. F.; Szende, A.; Cabases, J.; Ramos-Goñi, J. M.; Vilagut, G.; König, H. H. (March 2019). "Population norms for the EQ-5D-3L: a cross-country analysis of population surveys for 20 countries". The European Journal of Health Economics. 20 (2): 205–216. doi:10.1007/s10198-018-0955-5. PMC   6438939 . PMID   29445941.
  59. Shiroiwa, Takeru; Fukuda, Takashi; Ikeda, Shunya; Igarashi, Ataru; Noto, Shinichi; Saito, Shinya; Shimozuma, Kojiro (March 2016). "Japanese population norms for preference-based measures: EQ-5D-3L, EQ-5D-5L, and SF-6D". Quality of Life Research. 25 (3): 707–719. doi:10.1007/s11136-015-1108-2. PMC   4759213 . PMID   26303761.
  60. Hinz, Andreas; Kohlmann, Thomas; Stöbel-Richter, Yve; Zenger, Markus; Brähler, Elmar (March 2014). "The quality of life questionnaire EQ-5D-5L: psychometric properties and normative values for the general German population". Quality of Life Research. 23 (2): 443–447. doi:10.1007/s11136-013-0498-2. PMID   23921597. S2CID   11634481.
  61. McCaffrey, Nikki; Kaambwa, Billingsley; Currow, David C.; Ratcliffe, Julie (December 2016). "Health-related quality of life measured using the EQ-5D–5L: South Australian population norms". Health and Quality of Life Outcomes. 14 (1): 133. doi: 10.1186/s12955-016-0537-0 . PMC   5028927 . PMID   27644755.
  62. Wisløff, Torbjørn; Hagen, Gunhild; Hamidi, Vida; Movik, Espen; Klemp, Marianne; Olsen, Jan Abel (April 2014). "Estimating QALY Gains in Applied Studies: A Review of Cost-Utility Analyses Published in 2010". PharmacoEconomics. 32 (4): 367–375. doi:10.1007/s40273-014-0136-z. PMC   3964297 . PMID   24477679.
  63. Richardson, Jeff; Iezzi, Angelo; Khan, Munir A.; Maxwell, Aimee (2014-03-01). "Validity and Reliability of the Assessment of Quality of Life (AQoL)-8D Multi-Attribute Utility Instrument". The Patient - Patient-Centered Outcomes Research. 7 (1): 85–96. doi:10.1007/s40271-013-0036-x. ISSN   1178-1661. PMC   3929769 . PMID   24271592.