Developing preference-based measures for diabetes: DHP-3D and DHP-5D

A scoping review to create a framework for the steps in developing condition-specific preference-based instruments de novo or from an existing non-preference-based instrument: use of item response theory or Rasch analysis

BACKGROUND

There is no widely accepted framework to guide the development of condition-specific preference-based instruments (CSPBIs) that includes both de novo and from existing non-preference-based instruments. The purpose of this study was to address this gap by reviewing the published literature on CSPBIs, with particular attention to the application of item response theory (IRT) and Rasch analysis in their development.

METHODS

A scoping review of the literature covering the concepts of all phases of CSPBI development and evaluation was performed from MEDLINE, Embase, PsychInfo, CINAHL, and the Cochrane Library, from inception to December 30, 2022.

RESULTS

The titles and abstracts of 1,967 unique references were reviewed. After retrieving and reviewing 154 full-text articles, data were extracted from 109 articles, representing 41 CSPBIs covering 21 diseases or conditions. The development of CSPBIs was conceptualized as a 15-step framework, covering four phases: 1) develop initial questionnaire items (when no suitable non-preference-based instrument exists), 2) establish the dimensional structure, 3) reduce items per dimension, 4) value and model health state utilities. Thirty-nine instruments used a type of Rasch model and two instruments used IRT models in phase 3.

CONCLUSION

We present an expanded framework that outlines the development of CSPBIs, both from existing non-preference-based instruments and de novo when no suitable non-preference-based instrument exists, using IRT and Rasch analysis. For items that fit the Rasch model, developers selected one item per dimension and explored item response level reduction. This framework will guide researchers who are developing or assessing CSPBIs.

Patient-reported outcome measures for assessing health-related quality of life in people with type 2 diabetes: A systematic review

Patient-Reported Outcome Measures (PROMs) are important tools to assess outcomes relevant to patients, with Health-Related Quality Of Life (HRQOL) as an important construct to be measured. Many different HRQOL PROMs are used in the type 2 diabetes field, however a complete overview of these PROMs is currently lacking. We therefore aimed to systematically describe and classify the content of all PROMs that have specifically been developed or validated to measure (aspects of) HRQOL in people with type 2 diabetes. A literature search was performed in PubMed and EMBASE until 31 December 2021. Studies on the development or validation of a PROM measuring HRQOL, or aspects of HRQOL, in people with type 2 diabetes were included. Title and abstract and full-text screening were conducted by two independent researchers and data extraction was performed independently by one of the researchers. Data were extracted on language in which the PROM was developed, target population, construct(s) being measured, names of (sub)scales and number of items per (sub)scale. In addition, all PROMs and subscales were classified according to specific aspects of HRQOL based on the Wilson & Cleary model (symptom status, functional status, general health perceptions) to aid researchers in PROM selection. In total 220 studies were identified that developed or validated PROMs that measure (aspects of) HRQOL in people with type 2 diabetes. Of the 116 unique HRQOL PROMs, 91 (of the subscales) measured symptom status, 60 measured functional status and 26 measured general health perceptions. In addition, 16 of the PROMs (subscales) measured global quality of life. 61 of the 116 PROMs (subscales) also include characteristics of the individual (e.g. aspects of personality, coping) or environment (e.g. social or financial support) and patient-reported experience measures (PREMs, e.g. measure of a patient's perception of their personal experience of the healthcare they have received, e.g. treatment satisfaction), which are not part of the HRQOL construct. Only 9 of the 116 PROMs measure all aspects of HRQOL based on the Wilson & Cleary model. Finally, 8 of the 116 PROMs stating to measure HRQOL, measured no HRQOL construct. In conclusion, a large number of PROMs are available for people with type 2 diabetes, which intend to measure (aspects of) HRQOL. These PROMs measure a large variety of (sub)constructs, which are not all HRQOL constructs, with a small amount of PROMs not measuring HRQOL at all. There is a need for consensus on which aspects of HRQOL should be measured in people with type 2 diabetes and which PROMs to use in research and daily practice. PROSPERO: CRD42017071012. COMET database: http://www.comet-initiative.org/studies/details/956 .

Developing the Breast Utility Instrument to Measure Health-Related Quality-of-Life Preferences in Patients with Breast Cancer: Selecting the Item for Each Dimension

Introduction. Generic preference-based instruments inadequately measure breast cancer (BrC) health-related quality-of-life preferences given advances in therapy. Our overall purpose is to develop the Breast Utility Instrument (BUI), a BrC-specific preference-based instrument. This study describes the selection of the BUI items. Methods. A total of 408 patients from diverse BrC health states completed the EORTC QLQ-C30 and BR45 (breast module). For each of 10 dimensions previously assessed with confirmatory factor analysis, we evaluated data fit to the Rasch model based on global model and item fit, including threshold ordering, item residuals, infit and outfit, differential item functioning (age), and unidimensionality. Misfitting items were removed iteratively, and the model fit was reassessed. From items fitting the Rasch model, we selected 1 item per dimension based on high patient- and clinician-rated item importance, breadth of item thresholds, and clinical relevance. Results. Global model fit was good in 7 and borderline in 3 dimensions. Separation index was acceptable in 4 dimensions. Item selection criteria were maximized for the following items: 1) physical functioning (trouble taking a long walk), 2) emotional functioning (worry), 3) social functioning (interfering with social activities), 4) pain (having pain), 5) fatigue (tired), 6) body image (dissatisfied with your body), 7) systemic therapy side effects (hair loss), 8) sexual functioning (interest in sex), 9) breast symptoms (oversensitive breast), and 10) endocrine therapy symptoms (problems with your joints). Conclusions. We propose 10 items for the BUI. Our next steps include assessing the measurement properties prior to eliciting preference weights of the BUI.

Highlights

A previous confirmatory factor analysis established 10 dimensions of the European Organisation for Research and Treatment of Cancer (EORTC) core quality of life questionnaire (QLQ-C30) and its breast module (BR45). In this study, we selected 1 item per dimension based on fit to the Rasch model, patient- and clinician-rated item importance, breadth of item thresholds, and clinical relevance. These items form the core of the future Breast Utility Instrument (BUI). The future BUI will be a novel breast cancer–specific preference-based instrument that potentially will better reflect women’s preferences in clinical decision making and cost utility analyses.

Patient-Reported Experience and Outcome Measures in People Living with Diabetes: A Scoping Review of Instruments

BACKGROUND

Diabetes mellitus is a global public health concern, with over 463 million people living with this chronic disease. Pathology complexity, management difficulty, and limited participation in care has resulted in healthcare systems seeking new strategies to engage people living with diabetes. Patient-reported experience measures (PREMs) and patient-reported outcome measures (PROMs) were developed to address the gap between the healthcare system expectation and patient preference.

OBJECTIVE

This study aimed to review the existing literature on PREMs and PROMs specific to type 1 and 2 diabetes, and report the dimensions report the dimensions they have measured.

METHODS

A scoping review was conducted from January 1985 to March 2020 of six databases, MEDLINE, EMBASE, PsycINFO, CINHAL, Scopus, and BiblioPro, to identify PREM and PROM instruments specific for type 1 and 2 diabetes.

RESULTS

Overall, 34 instruments were identified, 32 PROMs and two PREMs. The most common instrument included outcomes related to quality of life at 44% (n = 15), followed by satisfaction (whether with treatment, device, and healthy habits) at 26% (n = 9). Furthermore, instruments regarding personal well-being accounted for 15% (n = 5). For instruments that measure experiences of persons with diabetes, there were two scales of symptoms, and one related to the attitude patients have toward the disease.

CONCLUSIONS

Diabetes-specific validated instruments mainly focus on quality of life, education, and treatment, and sometimes overlap each other, in their subscales and assessment dimensions. Constructs such as cultural and religious beliefs, leisure, and work life may need more attention. There appears to be a gap in instruments to measure experiences of individuals who "live with diabetes" and seek to lead a "normal life."

A philosophical perspective on the development and application of patient-reported outcomes measures (PROMs)

Questionnaires are a common method in healthcare and clinical research to collect self-reported data on patients' behaviour and outcomes rather than the clinician's perspective. As a consequence there is a plethora of questionnaires and rating forms developed to measure a range of concepts such as health-related quality of life and health status. Given that these measures have been developed within a nomothetic paradigm to enhance our understanding of peoples self-perceived health status by translating complex personal feelings and experiences into a simple numeric score, the patient's illness narrative is lost along the way. This commentary discusses the limitations of the nomothetic approach as completion of a questionnaire is a social and contextually orientated activity and that their development is best viewed within the philosophical tradition of pragmatism, based on sound qualitative methods and rigorous psychometric testing. The commentary discusses the philosophical orientation underpinning PROM development and argues the case for a pragmatic epistemology based on a mixed methods research paradigm which goes beyond the current practice of informing the content validity of a PROM in the early phase of its development but to work towards developing a more composite and holistic picture through mixed methods in the interpretation of a patient's PROM score. Therefore, it is argued that the quality of data obtained will be enhanced but, also importantly and rightly places the participant at the centre of the research.

Measurement Properties of Patient-Reported Outcome Measures for Diabetes: Systematic Review

BACKGROUND

The management of diabetes is complex. There is growing recognition of the use of patient-reported outcome measures (PROMs) as a standardized method of obtaining an outlook on patients' functional status and well-being. However, no systematic reviews have summarized the studies that investigate the measurement properties of diabetes PROMs.

OBJECTIVE

Our aims were to conduct a systematic review of studies investigating the measurement properties of diabetes PROMs by evaluating the methodological quality and overall level of evidence of these PROMs and to categorize them based on the outcome measures assessed.

METHODS

This study was guided by the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. Relevant articles were retrieved from the Embase, PubMed, and PsychINFO databases. The PROMs were evaluated with the COSMIN (COnsensus-based Standards for the selection of health Measurement Instruments) guidelines.

RESULTS

A total of 363 articles evaluating the measurement properties of PROMs for diabetes in the adult population were identified, of which 238 unique PROMs from 248 studies reported in 209 articles were validated in the type 2 diabetes population. PROMs with at least a moderate level of evidence for ≥5 of 9 measurement properties include the Chinese version of the Personal Diabetes Questionnaire (C-PDQ), Diabetes Self-Management Instrument Short Form (DSMI-20), and Insulin Treatment Appraisal Scale in Hong Kong primary care patients (C-ITAS-HK), of which the C-PDQ has a "sufficient (+)" rating for >4 measurement properties. A total of 43 PROMs meet the COSMIN guidelines for recommendation for use.

CONCLUSIONS

This study identified and synthesized evidence for the measurement properties of 238 unique PROMs for patients with type 2 diabetes and categorized the PROMs according to their outcome measures. These findings may assist clinicians and researchers in selecting appropriate high-quality PROMs for clinical practice and research.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42020180978; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020180978.

Dimensions Used in Instruments for QALY Calculation: A Systematic Review

Economic assessment is of utmost importance in the healthcare decision-making process. The quality-adjusted life-year (QALY) concept provides a rare opportunity to combine two crucial aspects of health, i.e., mortality and morbidity, into a single index to perform cost-utility comparison. Today, many tools are available to measure morbidity in terms of health-related quality of life (HRQoL) and a large literature describes how to use them. Knowing their characteristics and development process is a key point for elaborating, adapting, or selecting the most well-suited instrument for further needs. In this aim, we conducted a systematic review on instruments used for QALY calculation, and 46 studies were selected after searches in four databases: Medline EBSCO, Scopus, ScienceDirect, and PubMed. The search procedure was done to identify all relevant publications up to 18 June 2020. We mainly focused on the type of instrument developed (i.e., generic or specific), the number and the nature of dimensions and levels used, the elicitation method and the model selected to determine utility scores, and the instrument and algorithm validation methods. Results show that studies dealing with the development of specific instruments were mostly motivated by the inappropriateness of generic instruments in their field. For the dimensions' and levels' selection, item response theory, Rasch analysis, and literature review were mostly used. Dimensions and levels were validated by methods like the Loevinger H, the standardised response mean, or discussions with experts in the field. The time trade-off method was the most widely used elicitation method, followed by the visual analogue scale. Random effects regression models were frequently used in determining utility scores.

Estimating a Preference-Based Index for Mental Health From the Recovering Quality of Life Measure: Valuation of Recovering Quality of Life Utility Index

BACKGROUND

There are increasing concerns about the appropriateness of generic preference-based measures to capture health benefits in the area of mental health.

OBJECTIVES

The aim of this study is to estimate preference weights for a new measure, Recovering Quality of Life (ReQoL-10), to better capture the benefits of mental healthcare.

METHODS

Psychometric analyses of a larger sample of mental health service users (n = 4266) using confirmatory factor analyses and item response theory were used to derive a health state classification system and inform the selection of health states for utility assessment. A valuation survey with members of the UK public representative in terms of age, sex, and region was conducted using face-to-face interviewer administered time-trade-off with props. A series of regression models were fitted to the data and the best performing model selected for the scoring algorithm.

RESULTS

The ReQoL-Utility Index (UI) classification system comprises 6 mental health items and 1 physical health item. Sixty-four health states were valued by 305 participants. The preferred model was a random effects model, with significant and consistent coefficients and best model fit. Estimated utilities modeled for all health states ranged from -0.195 (state worse than dead) to 1 (best possible state).

CONCLUSIONS

The development of the ReQoL-UI is based on a novel application of item response theory methods for generating the classification system and selecting health states for valuation. Conventional time-trade-off was used to elicit utility values that are modeled to enable the generation of QALYs for use in cost-utility analysis of mental health interventions.

Selection and validation of a classification system for a child-centred preference-based measure of oral health-related quality of life specific to dental caries

Background

Caries Impacts and Experiences Questionnaire for Children (CARIES-QC) is a child-centred caries-specific quality of life measure. This study aimed to select, and validate with children, a classification system for a paediatric condition-specific preference-based measure, based on CARIES-QC.

Methods

First, a provisional classification system for a preference-based measure based on CARIES-QC was identified using Rasch analysis, psychometric testing, involvement of children and parents, and the developer of CARIES-QC. Second, qualitative, semi-structured ‘think aloud’ validation interviews were undertaken with a purposive sample of children with dental caries. The interviewer aimed to identify whether items were considered important and easily understood, whether any were overlapping and if any excluded items should be reintroduced. Interview recordings were transcribed verbatim and thematic analysis conducted.

Results

Rasch analysis identified poor item spread for the items ‘cross’ and ‘school’. Items relating to eating were correlated and the better performing items were considered for selection. Children expressed some confusion regarding the items ‘school’ and ‘food stuck’. Parent representatives thought that impacts surrounding toothbrushing (‘brushing’) were encompassed by the item ‘hurt’. Five items were selected from CARIES-QC for inclusion in the provisional classification system; ‘hurt’, ‘annoy’, ‘carefully’, ‘kept awake’ and ‘cried’. Validation interviews were conducted with 20 children aged 5–16 years old. Participants thought the questionnaire was straightforward and covered a range of impacts. Children thought an item about certain foods being ‘hard to eat’ was more relevant than one about having to eat more carefully because of their teeth and so the ‘carefully’ item was replaced with ‘hard to eat’.

Conclusion

Following child-centred modification, the preliminary five-item classification system is considered valid and suitable for use in a valuation survey. The innovative child-centred methods used to both identify and validate the classification system can be applied in the development of other preference-based measures.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41687-020-00268-9.

Using a Discrete-Choice Experiment Involving Cost to Value a Classification System Measuring the Quality-of-Life Impact of Self-Management for Diabetes

OBJECTIVES

To describe the use of a novel approach in health valuation of a discrete-choice experiment (DCE) including a cost attribute to value a recently developed classification system for measuring the quality-of-life impact (both health and treatment experience) of self-management for diabetes.

METHODS

A large online survey was conducted using DCE with cost on UK respondents from the general population (n = 1497) and individuals with diabetes (n = 405). The data were modeled using a conditional logit model with robust standard errors. The marginal rate of substitution was used to generate willingness-to-pay (WTP) estimates for every state defined by the classification system. Robustness of results was assessed by including interaction effects for household income.

RESULTS

There were some logical inconsistencies and insignificant coefficients for the milder levels of some attributes. There were some differences in the rank ordering of different attributes for the general population and diabetic patients. The WTP to avoid the most severe state was £1118.53 per month for the general population and £2356.02 per month for the diabetic patient population. The results were largely robust.

CONCLUSIONS

Health and self-management can be valued in a single classification system using DCE with cost. The marginal rate of substitution for key attributes can be used to inform cost-benefit analysis of self-management interventions in diabetes using results from clinical studies in which this new classification system has been applied. The method shows promise, but found large WTP estimates exceeding the cost levels used in the survey.