“If we ask, we must act”: co-designing the implementation of the EQ-5D-Y-5L as a Paediatric Patient Reported Outcome Measure in Routine hospital Outpatient Care for Kids to meaningfully impact clinical visits (P-PROM ROCK Phase 2) - Quality of Life Research

Purpose To co-design use of the EQ-5D-Y-5L, a generic Paediatric Patient Reported Outcome Measure (P-PROM), in Routine Outpatient Care for Kids (ROCK), maximising its impact on patient-clinician visits. Methods This Phase 2 co-design study was guided by the co-design framework for public service design and Double Diamond model. Data collection involved facilitated workshops (building on Phase 1), followed by feedback and optimisation sessions. Participants included service providers (doctors, nurses, allied health and medical record staff), adolescents, and caregivers with lived experience of providing or receiving outpatient care at a tertiary paediatric hospital in Australia. Results Five co-design workshops, nine feedback, and two optimisation sessions were conducted with nine service providers, two adolescents, and three caregivers. Co-design participants created resources to introduce EQ-5D-Y-5L as a ‘general health tracking questionnaire’ and explain its purpose. EQ-5D-Y-5L responses were designed to be displayed by item. A display of results over time was also designed. A patient empowerment approach was taken with regards to flagging specific EQ-5D-Y-5L items for discussion with clinicians, whereby patients or caregivers control which items are flagged. To ensure clinical review and action of EQ-5D-Y-5L responses, resources, including clinician training, clinician decision support tool, and matching patient booklet and resource pathway, were co-designed. Combined, these design elements make up the P-PROM ROCK Program. Conclusion Consumer engagement produced important insights that would’ve otherwise been missed, ensuring the P-PROM ROCK Program empowers patients. For generic P-PROMs to meaningfully impact patient-clinician visits, supports and resources are required to ensure clinical review and action.

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Analyzing quality of life among people with opioid use disorder from the National Institute on Drug Abuse Data Share initiative: implications for decision making - Quality of Life Research

Purpose We aimed to estimate health state utility values (HSUVs) for the key health states found in opioid use disorder (OUD) cost-effectiveness models in the published literature. Methods Data obtained from six trials representing 1,777 individuals with OUD. We implemented mapping algorithms to harmonize data from different measures of quality of life (the SF-12 Versions 1 and 2 and the EQ-5D-3 L). We performed a regression analysis to quantify the relationship between HSUVs and the following variables: days of extra-medical opioid use in the past 30 days, injecting behaviors, treatment with medications for OUD, HIV status, and age. A secondary analysis explored the impact of opioid withdrawal symptoms. Results There were statistically significant reductions in HSUVs associated with extra-medical opioid use (-0.002 (95% CI [-0.003,-0.0001]) to -0.003 (95% CI [-0.005,-0.002]) per additional day of heroin or other opiate use, respectively), drug injecting compared to not injecting (-0.043 (95% CI [-0.079,-0.006])), HIV-positive diagnosis compared to no diagnosis (-0.074 (95% CI [-0.143,-0.005])), and age (-0.001 per year (95% CI [-0.003,-0.0002])). Parameters associated with medications for OUD treatment were not statistically significant after controlling for extra-medical opioid use (0.0131 (95% CI [-0.0479,0.0769])), in line with prior studies. The secondary analysis revealed that withdrawal symptoms are a fundamental driver of HSUVs, with predictions of 0.817 (95% CI [0.768, 0.858]), 0.705 (95% CI [0.607, 0.786]), and 0.367 (95% CI [0.180, 0.575]) for moderate, severe, and worst level of symptoms, respectively. Conclusion We observed HSUVs for OUD that were higher than those from previous studies that had been conducted without input from people living with the condition.

Health-related quality of life of adults with spinal muscular atrophy: insights from a nationwide patient registry in Germany

Quality of Life Research | Volume 33, issue 4

Volume 33, issue 4 articles listing for Quality of Life Research

Australian population norms for health-related quality of life measured using the EQ-5D–5L, and relationships with sociodemographic characteristics

Feasibility of self-reported health related quality of life assessment with older people in residential care: insights from the application of eye tracking technology - Quality of Life Research

Purpose Increasingly there are calls to routinely assess the health-related quality of life (HRQoL) of older people receiving aged care services, however the high prevalence of dementia and cognitive impairment remains a challenge to implementation. Eye-tracking technology facilitates detailed assessment of engagement and comprehension of visual stimuli, and may be useful in flagging individuals and populations who cannot reliably self-complete HRQoL instruments. The aim of this study was to apply eye-tracking technology to provide insights into self-reporting of HRQoL among older people in residential care with and without cognitive impairment. Methods Residents (n = 41), recruited based on one of three cognition subgroups (no, mild, or moderate cognitive impairment), completed the EQ-5D-5L on a computer with eye tracking technology embedded. Number and length of fixations (i.e., eye gaze in seconds) for key components of the EQ-5D-5L descriptive system were calculated. Results For all dimensions, participants with no cognitive impairment fixated for longer on the Area of Interest (AOI) for the response option they finally chose, relative to those with mild or moderate cognitive impairment. Participants with cognitive impairment followed similar fixation patterns to those without. There was some evidence that participants with cognitive impairment took longer to complete and spent relatively less time attending to the relevant AOIs, but these differences did not reach statistical significance generally. Conclusions This exploratory study applying eye tracking technology provides novel insights and evidence of the feasibility of self-reported HRQoL assessments in older people in aged care settings where cognitive impairment and dementia are highly prevalent.

Face Validity of Four Preference-Weighted Quality-of-Life Measures in Residential Aged Care: A Think-Aloud Study - The Patient - Patient-Centered Outcomes Research

Objective There is an increased use of preference-weighted quality-of-life measures in residential aged care to guide resource allocation decisions or for quality-of-care assessments. However, little is known about their face validity (i.e., how understandable, appropriate and relevant the measures are ‘on their face’ when respondents complete them). The aim of this study was to assess the face validity of four preference-weighted measures (i.e., EQ-5D-5L, EQ-HWB, ASCOT, QOL-ACC) in older people living in residential aged care. Methods Qualitative cognitive think-aloud interviews were conducted using both concurrent and retrospective think-aloud techniques. To reduce burden, each resident completed two measures, with the four measures randomised across participants. Audio recordings were transcribed and framework analysis was used for data analysis, based on an existing framework derived from the Tourangeau four-stage response model. Results In total, 24 interviews were conducted with residents living across three residential aged care facilities in Melbourne, Australia. Response issues were identified across all four measures, often related to comprehension and difficulty selecting a response level due to double-barrelled and ambiguous items that have different meanings in the residential aged care context. We also identified issues related to understanding instructions, non-adherence to the recall period, and noted positive responding that requires attention when interpreting the data. Conclusions Our findings provide further evidence on the appropriateness of existing measures, indicating numerous response issues that require further research to guide the selection process for research and practice.

Time perspective profile and self-reported health on the EQ-5D - Quality of Life Research

Objectives Time perspective (TP) is a psychological construct that is associated with several health-related behaviours, including healthy eating, smoking and adherence to medications. In this study, we aimed to examine the associations of TP profile with self-reported health on the EQ-5D-5L and to detect which domains display response heterogeneity (cut-point shift) for TP. Methods We conducted a secondary analysis of EQ-5D-5L data from a representative general population sample in Hungary (n = 996). The 17-item Zimbardo Time Perspective Inventory was used to measure individuals' TP on five subscales: past-negative, past-positive, present-fatalist, present-hedonist and future. The associations between TP subscales and EQ-5D-5L domain scores, EQ VAS and EQ-5D-5L index values were analysed by using partial proportional odds models and multivariate linear regressions. Results Respondents that scored higher on the past-negative and present-fatalist and lower on the present-hedonist and future subscales were more likely to report more health problems in at least one EQ-5D-5L domain (p < 0.05). Adjusting for socio-economic and health status, three EQ-5D-5L domains exhibited significant associations with various TP subscales (usual activities: present-fatalist and future, pain/discomfort: past-negative and future, anxiety/depression: past-negative, present-fatalist, present-hedonist and future). The anxiety/depression domain showed evidence of cut-point shift. Conclusions This study identified response heterogeneity stemming from psychological characteristics in self-reported health on the EQ-5D-5L. TP seems to play a double role in self-reported health, firstly as affecting underlying health and secondly as a factor influencing one’s response behavior. These findings increase our understanding of the non-health-related factors that affect self-reported health on standardized health status measures.