Preference-based measures (PBMs) are generally used to calculate quality-adjusted life-years (QALYs) and evaluate health states. A QALY is a life-year weighted by values measured through PBMs, which are anchored to 0 (death) and 1 (full health); it is widely used for the economic evaluation of health interventions, and its use is recommended by many health technology assessment (HTA) agencies.
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As examples of generic PBM,
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the following instruments are frequently used: 3-level version of EQ-5D
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and 5-level version of EQ-5D,
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Health Utilities Index (HUI) Mark 2 and 3,
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Short Form-6 Dimensions (SF-6D
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), 15D, Assessment of Quality of Life 8-Dimension,
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and the Quality of Well-Being self-administered
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scale. Additionally, disease- or respondent-specific PBMs can be used, such as for pediatrics (eg, EQ-5D-Y
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), specific diseases (eg, EORTC QLU C-10D
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), and care users or caregivers (ASCOT
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It is important to note that these PBMs have been originally developed in Western countries. For example, the EQ-5D was developed in Europe; HUI in Canada; 15D in northern Europe; Assessment of Quality of Life in Australia; and SF-6D, ASCOT, and CHU-9D in the United Kingdom. EORTC is a European organization, and Facit.org
, which manages FACT, is an organization based in the United States. Naturally, translated versions of these PBMs were established in several non-Western countries. The psychometric properties of some PBMs were confirmed, and valuation surveys were performed to convert response to utility. For example, construct validity is established for some instruments in East and Southeast Asian countries.
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Utilities measured using existing PBMs based on Western concepts may not reflect the true preference of those living in other regions, thereby rendering these scores less meaningful.
Nevertheless, East and Southeast Asian researchers have become more active in the HTA field, and economic evaluation has officially been introduced in the drug policies
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of some Asian countries or regions,
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Health technology assessment in South Korea.
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a collaborative network of Asian HTA agencies, has also been established in Asia. Therefore, we need to develop a new region-specific PBM that can appropriately represent the health concepts of East and Southeast Asians. This study aims to construct a region-specific PBM through concept elicitation using an interview survey and qualitative analysis.
Interview Method and Protocol
Local, trained interviewers were recruited in each country by the same research company, and interviews were conducted using a semistructured guide. The questions were open ended to gain insight into the notions the subjects used to describe their health and health problems and how these problems affected their daily lives. Interviewers modified specific questions or probes to maintain the natural topic flow during the 60-minute session (Appendix
The study materials included an interview guide translated from American English to the following 10 local languages: Tagalog and Cebuano (the Philippines), Bahasa (Indonesia), Japanese, Korean, Malay (Malaysia), simplified Chinese (mainland China), Tamil (Singapore), traditional Chinese (Taiwan), and Thai (Thailand). Furthermore, 6 language adaptations including English (Malaysia, the Philippines, and Singapore), Malay (Singapore), and simplified Chinese (Malaysia and Singapore) were formulated.
The participants were asked to complete a sociodemographic form that helped them to describe themselves and capture their health comorbidities. Subsequently, the first part of the interview focused on understanding the general health of participants, rating their health, and identifying health problems. This interview was used only to understand the patients’ background in more detail.
In the next section, “health domain,” interviewers used the discussion item that comprised a list of general conditions organized by 10 health domains, each comprising 4 to 9 individual conditions or ailments. The interviewer read the list to the participants and asked them to indicate their experience with each condition/ailment, as well as how it affected their daily life. (“I’m going to read a list of health-related items that have been brought up by other people. Can you tell me if you remember experiencing any of these? If you have, can you tell me how it affects your daily life?”)
For the third section, “health impact on daily life,” interviewers asked participants questions about how their current health status affected their lives, including their relationships with others. The participants could discuss these impacts spontaneously before the interviewer asked about specific topics, using a predefined list of 13 areas that a negative health condition may affect. (“What areas of your life are affected by your health problems?”)
In the last section, “declining health,” interviewers asked participants to list the areas of their daily life that they would not want a decline in their health to impact. (“If your health became worse, what areas of your life would you NOT like to see become impacted, and why?”)
Study Design of the Interview Survey
This cross-sectional study involved 225 adults (aged ≥ 18 years) recruited from the general population of 9 Asian countries or regions (ie, Indonesia, Japan, Korea, mainland China, Malaysia, the Philippines, Singapore, Taiwan, and Thailand). A sample of 25 participants from the general population of each country or region was interviewed. This was not determined by rigid statistical consideration, but we assumed that saturation may be achieved in each country if 25 samples were collected. The samples were collected by quota sampling according to sex and age. We collected interview data from the general public. We think PBM needs to be constructed based on a general public health concept because this is used for resource allocation. It is similar to the idea that a valuation study is normally performed by collecting the general public’s preferences.
The participants were recruited from a panel prepared by a Japanese research company (INTAGE Research Inc, Tokyo) and engaged in one-on-one, semistructured concept elicitation interviews. The inclusion criteria of the study included that the participant must (1) be an adult according to local laws at the time of signing the informed consent form; (2) sufficiently understand, read, and speak at least 1 dialect selected for this study to complete the interview; (3) be willing and able to attend an in-person interview session; and (4) provide a written informed consent. The participants received some financial compensation from the research company. Given the outbreak of COVID-19 in the region, online or telephonic interviews were organized.
Analysis of Qualitative Data
The interviewers recorded written notes during the interviews, which were reviewed during and after data collection to ensure consistency in data quality. The interviews were audio recorded for subsequent transcription by a company. Interviews conducted in the participants’ native language (other than English) were transcribed directly into English. We reviewed the interview transcripts for content and removed any participant-identifying information. We also corrected any obvious transcription errors.
For sociodemographic and health characteristics, descriptive statistics (mean, SD, and frequency) were calculated to characterize the participants. Qualitative data from the interview records were analyzed using content analysis. Transcripts were loaded onto the ATLAS.ti (Scientific Software Development GmbH, Berlin) qualitative analysis software (version 8.0 or higher) to organize the data and identify the major concepts.
ATLAS.Ti 7 User Guide and Reference.
The analysis involved developing a coding dictionary based on the structure of the interview guide. Two members independently coded the transcripts, and the coding was reviewed by another member until the coding was consistent between coders. Participant quotes were grouped and summarized using thematic codes from the coding dictionary.
Constructing the New Region-Specific PBM
The development team, involving representative members of HTAsiaLink (a network of HTA agencies and experts in Asia), reviewed and agreed upon the concepts identified in the interview survey, in addition to using published literature, existing instruments, and qualitative data from the concept elicitation interviews, to determine the items to be included in the new PBM. The frequency with which items were mentioned in the interviews was considered for item selection. Transcripts of the concept elicitation interviews are available upon request. The number of items was determined based on team member discussions, considering the content validity of the instrument and the ease of response for users and other PBMs (EQ-5D, SF-6D, and HUI). A heat map was used to confirm whether the selected items were important for any country. We considered the homogeneity or heterogeneity of the results using the heat map. Once the included items were decided, the description of each item was based on the interview survey. The number of the scale of the instruments was determined to be 4 (“not at all,” “a little,” “quite a bit,” and “very much”) based on our discussion referring to other instruments.
Confirming the Structure of the Instrument
After draft instruments were constructed, we had to consider the face validity of the instrument. Therefore, we collected responses to Asia PBM 7 dimensions (AP-7D) data from people in the general population in Japan. These data were collected separately from the first interview data. Using these data, we performed exploratory and confirmatory factorial analyses to confirm face validity.
Responses to the new PBM were collected in Japan from February 2021 through a face-to-face survey. The inclusion criteria for respondents were as follows: (1) be between the ages of 20 and 65 years, (2) have current Japanese residency, (3) be able to visit the survey room, (4) provide a informed consent, and (5) complete the instrument in Japanese. A research company recruited participants based on nonrandom quota sampling by sex and age, which sampled 500 respondents. The sample size was not based on rigid statistical considerations. All participants were asked to complete the new PBM and provide demographic information.
Collected data were used for exploratory and confirmatory factor analysis. First, we performed exploratory factorial analysis using promax rotation to detect a structure in the items. If factor loading > 0.4, we considered that the item belonged to the factor. Based on the results of the exploratory factorial analysis, a hypothetical model, which shows the relationship between domains and items, was constructed for confirmatory factorial analysis. The goodness of fit was considered by confirmatory factorial analysis. We applied the following goodness-of-fit criteria for a constructed model based on Braizer et al
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: (1) root mean square error of approximation (RMSEA) < 0.08, (2) standardized root mean square residual < 0.05, (3) comparative fit index > 0.90, and (4) Tucker and Lewis index > 0.95. Both factorial analyses were performed using Stata 17 software (StataCorp LLC, College Station).
In our study, we developed a new instrument for measuring utility scores in non-Western countries. We believe that such region-specific PBMs will become more important as the structure of health concepts differs from that of Western countries. When comparing items from the AP-7D with items from other existing instruments (the EQ-5D, SF-6D, and HUI Mark 3), all instruments have pain and mental health (anxiety/depression in the EQ-5D and emotion in the HUI Mark 3) items in common, although only the SF-6D has energy (vitality in the SF-6D) as an item. Some instruments refer to interpersonal interactions (social activities in the SF-6D) and work/school (daily activities in the EQ-5D and role limitation in the SF-6D), although specific items are not included. All the 3 instruments do not have the burden to others item. We think some items overlap with existing PBMs that are constructed in Western countries, but the 7 items are based on the East and Southeast Asian people’s interview survey. The combination of items is also original. These differences between existing PBMs and the region-specific AP-7D may reflect cultural differences between Asian and Western countries. In contrast, referring to the heat map, the health concept may be a little different among East and Southeast Asian countries, although this survey does not have enough power to detect the difference. Of course, there are large cultural differences among these 9 countries. It is our future task to consider such a difference.
According to the results of our explanatory and confirmatory factorial analyses, the AP-7D contains 7 items, each of which consists of 3 components. We labeled the components as the physical, mental, and social health domains. These domains include 3 (physical), 2 (mental), and 2 (social) items, respectively. When we consider the face validity of the 7 items, this analysis supports the validity of the AP-7D, which ensures that the instrument has the potential to capture these health-related quality of life concerns.
A key strength of our study is the interview survey covering the major East and Southeast Asian countries. This has enabled us to capture the varied health concepts of Asian people. Our hypothesized conceptual framework was supported by our confirmatory factorial analysis. A major limitation is that our interview survey was not face-to-face owing to the outbreak of COVID-19. The COVID-19 pandemic and the differences in interview modes may also influence the interview results. Additionally, to analyze the results of the multicountry surveys, the interview scripts were translated into English, and the English text (not the local text) was analyzed. When the scripts were translated into different languages, subtle meanings or nuances may have changed. The translators were well trained, but no qualification was required. The development team members, who are fluent in English and local languages, provided quality assurance by carefully reviewing the translated versions. Finally, our target for the interview survey was people in the general population rather than patients or government or HTA agency decision makers. If patients or decision makers had been included in the survey, other concepts might have been elicited. Patients may experience a response shift compared with their previous states. In addition, regarding the representativeness of the samples, it is possible that the education level is higher. This is another limitation.
The next steps in the development process for the AP-7D measure comprise evaluating the psychometric properties (validity and reliability) by including the measure in a large, general population study to assess its scoring. The AP-7D measure is intended to be used in health economic evaluations to calculate QALYs and comprises a descriptive set that patients can use to describe various aspects of their health. These patient-reported values can then be converted into utility scores using a scoring algorithm. These algorithms may be country specific and based on surveys of the preferences of the general public for different combinations of health states. This would be the focus of our future research.
Article and Author Information
Author Contributions: Concept and design: Shiroiwa, Murata, Li, Nakamura, Teerawattananon, Kun, Shafie, Valverde, Lam, Ng, Nadjib, Pwu, Nugraha, Fukuda
Acquisition of data: Shiroiwa, Murata, Ahn, Chen
Analysis and interpretation of data: Shiroiwa, Murata, Ahn, Teerawattananon, Shafie, Lam, Ng, Nugraha
Drafting of the manuscript: Shiroiwa, Shafie, Ng, Nadjib, Fukuda
Critical revision of the paper for important intellectual content: Ahn, Li, Nakamura, Teerawattananon, Kun, Shafie, Valverde, Lam, Ng, Nadjib, Pwu, Nugraha, Fukuda
Provision of study materials or patients: Nadjib, Chen
Administrative, technical, or logistic support: Murata, Li, Kun, Nakamura, Shafie, Valverde, Pwu, Nugraha, Chen, Fukuda
Supervision: Nadjib, Fukuda
Conflict of Interest Disclosures: Drs Shafie and Lam are editors of Value in Health Regional Issues and had no role in the peer-review process of this article. No other disclosures were reported.
Funding/Support: This work was supported by the National Institute of Public Health in Japan .
Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study.