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Hill MJ, Huebinger RM, Ebna Mannan I, Yu H, Wisk LE, O'Laughlin KN, Gentile NL, Stephens KA, Gottlieb M, Weinstein RA, Koo K, Santangelo M, Saydah S, Spatz ES, Lin Z, Schaeffer K, Kean E, Montoy JCC, Rodriguez RM, Idris AH, McDonald S, Elmore JG, Venkatesh A. Race, Ethnicity, and Gender Differences in Patient Reported Well-Being and Cognitive Functioning Within 3 Months of Symptomatic Illness During COVID-19 Pandemic. J Racial Ethn Health Disparities 2024:10.1007/s40615-024-02124-8. [PMID: 39172356 DOI: 10.1007/s40615-024-02124-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 07/12/2024] [Accepted: 08/02/2024] [Indexed: 08/23/2024]
Abstract
BACKGROUND Differences in acute COVID-19 associated morbidity based on race, ethnicity, and gender have been well described; however, less is known about differences in subsequent longer term health-related quality of life and well-being. METHODS This prospective cohort study included symptomatic adults tested for SARS-CoV-2 who completed baseline and 3-month follow-up surveys. Using the PROMIS-29 tool, a validated measure of health and well-being, we compared outcomes at 3 months and change in outcomes from baseline to 3 months among groups with different races, ethnicities, and/or sexes. RESULTS Among 6044 participants, 4113 (3202 COVID +) were included. Among COVID + participants, compared to non-Hispanic White participants, Black participants had better PROMIS T-scores for cognitive function (3.6 [1.1, 6.2]) and fatigue (- 4.3 [- 6.6, - 2.0]) at 3 months and experienced more improvement in fatigue over 3 months (- 2.7 [- 4.7, - 0.8]). At 3 months, compared with males, females had worse PROMIS T-scores for cognitive function (- 4.1 [- 5.6, - 2.6]), physical function (- 2.1 [- 3.1, - 1.0]), social participation (- 2.8 [- 4.2, - 1.5]), anxiety (2.8 [1.5, 4.1]), fatigue (5.1 [3.7, 6.4]), and pain interference (2.0 [0.9, 3.2]). Females experienced less improvement in fatigue over 3 months (3.1 [2.0, 4.3]). Transgender/non-binary/other gender participants had worse 3-month scores in all domains except for sleep disturbance and pain interference. CONCLUSIONS Three months after the initial COVID-19 infection, Black participants reported better cognitive function and fatigue, while females and other gender minoritized groups experienced lower well-being. Future studies are necessary to better understand how and why social constructs, specifically race, ethnicity, and gender, influence differences in COVID-19-related health outcomes. Trials Registration ClinicalTrials.gov Identifier: NCT04610515.
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Affiliation(s)
- Mandy J Hill
- Department of Emergency Medicine, McGovern Medical School, UTHealth Houston, 6431 Fannin JJL 475G, Houston, TX, 77030, USA.
| | - Ryan M Huebinger
- Department of Emergency Medicine, McGovern Medical School, UTHealth Houston, 6431 Fannin JJL 475G, Houston, TX, 77030, USA
| | - Imtiaz Ebna Mannan
- Center for Outcomes Research and Evaluation, Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Huihui Yu
- Center for Outcomes Research and Evaluation, Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Lauren E Wisk
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Kelli N O'Laughlin
- Departments of Emergency Medicine and Global Health, University of Washington, Seattle, WA, USA
| | - Nicole L Gentile
- Department of Family Medicine, University of Washington, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
- Post-COVID Rehabilitation and Recovery Clinic, University of Washington, Seattle, WA, USA
| | - Kari A Stephens
- Biomedical Informatics & Medical Education, University of Washington, Seattle, WA, USA
| | - Michael Gottlieb
- Department of Emergency Medicine, Rush University Medical Center, Chicago, IL, USA
| | - Robert A Weinstein
- Cook County Hospital, The CORE Center, Rush University Medical Center, Chicago, IL, USA
| | - Katherine Koo
- Cook County Hospital, The CORE Center, Rush University Medical Center, Chicago, IL, USA
| | - Michelle Santangelo
- Cook County Hospital, The CORE Center, Rush University Medical Center, Chicago, IL, USA
| | - Sharon Saydah
- Centers for Disease Control and Prevention, National Center for Immunizations and Respiratory Diseases, Atlanta, GA, USA
| | - Erica S Spatz
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, USA
- Department of Epidemiology, Yale School of Public Health, New Haven, CT, USA
- Yale Center for Outcomes Research and Evaluation, New Haven, CT, USA
| | - Zhenqiu Lin
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, USA
- Yale Center for Outcomes Research and Evaluation, New Haven, CT, USA
| | - Kevin Schaeffer
- Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, PA, USA
| | - Efrat Kean
- Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, PA, USA
- Center for Connected Care, Thomas Jefferson University, Philadelphia, PA, USA
| | - Juan Carlos C Montoy
- Department of Emergency Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Robert M Rodriguez
- Department of Emergency Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Ahamed H Idris
- Department of Emergency Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Samuel McDonald
- Department of Emergency Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Clinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Joann G Elmore
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Arjun Venkatesh
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, USA
- Yale Center for Outcomes Research and Evaluation, New Haven, CT, USA
- Department of Emergency Medicine, Yale School of Medicine, New Haven, CT, USA
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Rangachari P, Thapa A, Sherpa DL, Katukuri K, Ramadyani K, Jaidi HM, Goodrum L. Characteristics of hospital and health system initiatives to address social determinants of health in the United States: a scoping review of the peer-reviewed literature. Front Public Health 2024; 12:1413205. [PMID: 38873294 PMCID: PMC11173975 DOI: 10.3389/fpubh.2024.1413205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Accepted: 05/17/2024] [Indexed: 06/15/2024] Open
Abstract
Background Despite the incentives and provisions created for hospitals by the US Affordable Care Act related to value-based payment and community health needs assessments, concerns remain regarding the adequacy and distribution of hospital efforts to address SDOH. This scoping review of the peer-reviewed literature identifies the key characteristics of hospital/health system initiatives to address SDOH in the US, to gain insight into the progress and gaps. Methods PRISMA-ScR criteria were used to inform a scoping review of the literature. The article search was guided by an integrated framework of Healthy People SDOH domains and industry recommended SDOH types for hospitals. Three academic databases were searched for eligible articles from 1 January 2018 to 30 June 2023. Database searches yielded 3,027 articles, of which 70 peer-reviewed articles met the eligibility criteria for the review. Results Most articles (73%) were published during or after 2020 and 37% were based in Northeast US. More initiatives were undertaken by academic health centers (34%) compared to safety-net facilities (16%). Most (79%) were research initiatives, including clinical trials (40%). Only 34% of all initiatives used the EHR to collect SDOH data. Most initiatives (73%) addressed two or more types of SDOH, e.g., food and housing. A majority (74%) were downstream initiatives to address individual health-related social needs (HRSNs). Only 9% were upstream efforts to address community-level structural SDOH, e.g., housing investments. Most initiatives (74%) involved hot spotting to target HRSNs of high-risk patients, while 26% relied on screening and referral. Most initiatives (60%) relied on internal capacity vs. community partnerships (4%). Health disparities received limited attention (11%). Challenges included implementation issues and limited evidence on the systemic impact and cost savings from interventions. Conclusion Hospital/health system initiatives have predominantly taken the form of downstream initiatives to address HRSNs through hot-spotting or screening-and-referral. The emphasis on clinical trials coupled with lower use of EHR to collect SDOH data, limits transferability to safety-net facilities. Policymakers must create incentives for hospitals to invest in integrating SDOH data into EHR systems and harnessing community partnerships to address SDOH. Future research is needed on the systemic impact of hospital initiatives to address SDOH.
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Affiliation(s)
- Pavani Rangachari
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Alisha Thapa
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Dawa Lhomu Sherpa
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Keerthi Katukuri
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Kashyap Ramadyani
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Hiba Mohammed Jaidi
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Lewis Goodrum
- Northeast Medical Group, Yale New Haven Health System, Stratford, CT, United States
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Nagy Z, Kiss N, Szigeti M, Áfra J, Lekka N, Misik F, Mucsi I, Banczerowski P. Construct validity of the Hungarian Version of the Patient-Reported Outcomes Measurement Information System-29 Profile Among Patients with Low Back Pain. World Neurosurg 2024; 181:e55-e66. [PMID: 37385441 DOI: 10.1016/j.wneu.2023.06.097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 06/19/2023] [Accepted: 06/20/2023] [Indexed: 07/01/2023]
Abstract
OBJECTIVE We aim to evaluate the psychometric properties of the Hungarian version of the patient-reported outcomes measurement information system (PROMIS)-29 profile domains among patients with chronic low back pain. METHODS We used a convenience, cross-sectional sampling of patients recruited at our neurosurgical institution. The participants completed paper-pencil version of the PROMIS-29 profile in addition to validated legacy questionnaires, including the Oswestry disability index, Research and Development Corporation 36-item short-form survey, 7-item general anxiety disorder scale, 9-item patient health questionnaire. Reliability was evaluated by calculating the internal consistency (Cronbach's α). Test-retest reliability was assessed using the intraclass correlation coefficient. The structural validity of PROMIS-29 was assessed using a confirmatory factor analysis. Construct validity was assessed by evaluating convergent and discriminant validity using Spearman's rank correlation. To further corroborate the construct validity, we also performed known-group comparisons. RESULTS The mean age of the 131 participants was 54 ± 16 years. Of the 131 patients, 62% were women. The internal consistency of each PROMIS domain was high (Cronbach's α >0.89 for all). The test-retest reliability was excellent (intraclass correlation >0.97). The confirmatory factor analysis showed good structural validity (comparative fit index >0.96; standardized root mean square residual <0.026 for all domains). All measured PROMIS scores correlated strongly with the scores obtained using the corresponding primary legacy instrument, indicating excellent convergent validity. The known-group comparisons demonstrated differences as hypothesized. CONCLUSIONS We present data supporting the validity and reliability of the Hungarian PROMIS-29 profile short forms for patients with low back pain. This instrument will be useful for research and clinical applications in spine care.
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Affiliation(s)
- Zoltán Nagy
- Department of Neurology and Neurosurgery, National Institute of Mental Health, Budapest, Hungary; Department of Neurosurgery, Semmelweis University, Budapest, Hungary.
| | - Nóra Kiss
- Department of Neurosurgery, Semmelweis University, Budapest, Hungary
| | - Mátyás Szigeti
- Imperial Clinical Trials Unit, Imperial College London, London, United Kingdom; Physiological Controls Research Center, Obuda University, Budapest, Hungary
| | - Judit Áfra
- Department of Neurology and Neurosurgery, National Institute of Mental Health, Budapest, Hungary
| | - Norbert Lekka
- Department of Neurology and Neurosurgery, National Institute of Mental Health, Budapest, Hungary
| | - Ferenc Misik
- Department of Neurology and Neurosurgery, National Institute of Mental Health, Budapest, Hungary
| | - István Mucsi
- Ajmera Transplant Center, University Health Network, Toronto, Ontario, Canada; Division of Nephrology, University of Toronto, Toronto, Ontario, Canada
| | - Péter Banczerowski
- Department of Neurology and Neurosurgery, National Institute of Mental Health, Budapest, Hungary; Department of Neurosurgery, Semmelweis University, Budapest, Hungary
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Xu RH, Ma B, Xin H, Zhang H, Zeng Y, Luo N, Dong D. Measurement properties of the EQ-5D-5L and PROPr in patients with spinal muscular atrophy. Health Qual Life Outcomes 2023; 21:123. [PMID: 37968716 PMCID: PMC10647137 DOI: 10.1186/s12955-023-02204-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 10/30/2023] [Indexed: 11/17/2023] Open
Abstract
OBJECTIVES Spinal muscular atrophy (SMA) is a rare monogenic neuromuscular disorder caused by loss of function mutations. Measuring health-related quality of life to support economic evaluations in this population is encouraged. However, empirical evidence on the performance of preference-based measures (PBMs) in individuals with SMA is limited. This study aimed to assess the psychometric properties of the EQ-5D-5L and the Patient-Reported Outcomes Measure Information System Preference measure (PROPr) in individuals with SMA. METHODS The data used in this study were obtained via a web-based, cross-sectional survey. All participants completed the self-reporting EQ-5D-5L and PROMIS-29 questionnaires. Information about their socioeconomic and health status was also obtained. Ceiling and floor effects, convergent and divergent validity, known-group validity, and the agreement between the two measures were assessed. RESULTS Strong ceiling and floor effects were observed for four dimensions of the EQ-5D-5L and three subscales, including pain intensity, pain interference, and physical function, of the PROMIS-29. All hypothesized associations between EQ-5D-5L/PROMIS-29 and other neuromuscular questions were confirmed, supporting good convergent validity. Moreover, both EQ-5D-5L and PROPr scores differentiated between impaired functional groups, demonstrating good discriminative ability. Poor agreement between the EQ-5D-5L and PROPr utility scores was observed. CONCLUSIONS The EQ-5D-5L and PROPr both appear to be valid PBMs for individuals with SMA. However, PROPr yielded considerably lower utility scores than EQ-5D-5L and their agreement was poor. Therefore, these two PBMs may not be used interchangeably in economic evaluations of SMA-related interventions.
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Affiliation(s)
- Richard Huan Xu
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| | - Bin Ma
- Meier Advocacy & Support Center for SMA, Beijing, China
| | - Huanping Xin
- Meier Advocacy & Support Center for SMA, Beijing, China
| | - Huanyu Zhang
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
| | - Yan Zeng
- JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Nan Luo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Dong Dong
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
- JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
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Mulhern BJ, Pan T, Norman R, Tran-Duy A, Hanmer J, Viney R, Devlin NJ. Understanding the measurement relationship between EQ-5D-5L, PROMIS-29 and PROPr. Qual Life Res 2023; 32:3147-3160. [PMID: 37347395 PMCID: PMC10522725 DOI: 10.1007/s11136-023-03462-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/08/2023] [Indexed: 06/23/2023]
Abstract
PURPOSE Many generic patient-reported instruments are available for the measurement of health outcomes, including EQ-5D-5L, and the Patient-Reported Outcome Measurement Information System (PROMIS). Assessing their measurement characteristics informs users about the consistency between, and limits of, evidence produced. The aim was to assess the measurement relationship between the EQ-5D-5L descriptive system and value sets, the PROMIS-29 and PROPr (PROMIS value set). METHODS Data were extracted from a cross-sectional survey administering measures of quality of life online in Australia. Descriptive analysis, agreement and construct validity assessment methods were used to compare instruments at the item, domain and value set level. RESULTS In total, 794 Australians completed the survey. Convergent validity analysis found that similar dimensions across instruments were highly correlated (> 0.50), but the PROMIS-29 assesses additional health concepts not explicitly covered by EQ-5D (sleep and fatigue). Known-group assessment found that EQ-5D-5L and PROPr were able to detect those with and without a condition (ES range 0.78-0.83) but PROPr could more precisely detect differing levels of self-reported health. Both instruments were sensitive to differences in levels of pain. DISCUSSION There is some consistency in what the EQ-5D-5L, PROMIS-29 and PROPr measure. Differences between value set characteristics can be linked to differences what is measured and the valuation approaches used. This has implications for the use of each in assessing health outcomes, and the results can inform decisions about which instrument should be used in which context.
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Affiliation(s)
- Brendan J Mulhern
- Centre for Health Economics Research and Evaluation, University of Technology Sydney, Ultimo, Australia.
| | - Tianxin Pan
- Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Australia
| | - Richard Norman
- School of Population Health, Curtin University, Perth, Australia
| | - An Tran-Duy
- Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Australia
| | - Janel Hanmer
- Department of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Rosalie Viney
- Centre for Health Economics Research and Evaluation, University of Technology Sydney, Ultimo, Australia
| | - Nancy J Devlin
- Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Australia
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Hagan K, Javed Z, Cainzos-Achirica M, Hyder AA, Mossialos E, Yahya T, Acquah I, Valero-Elizondo J, Pan A, Nwana N, Taha M, Nasir K. Cumulative social disadvantage and health-related quality of life: national health interview survey 2013-2017. BMC Public Health 2023; 23:1710. [PMID: 37667245 PMCID: PMC10476290 DOI: 10.1186/s12889-023-16168-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 06/21/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND Evidence for the association between social determinants of health (SDoH) and health-related quality of life (HRQoL) is largely based on single SDoH measures, with limited evaluation of cumulative social disadvantage. We examined the association between cumulative social disadvantage and the Health and Activity Limitation Index (HALex). METHODS Using adult data from the National Health Interview Survey (2013-2017), we created a cumulative disadvantage index by aggregating 47 deprivations across 6 SDoH domains. Respondents were ranked using cumulative SDoH index quartiles (SDoH-Q1 to Q4), with higher quartile groups being more disadvantaged. We used two-part models for continuous HALex scores and logistic regression for poor HALex (< 20th percentile score) to examine HALex differences associated with cumulative disadvantage. Lower HALex scores implied poorer HRQoL performance. RESULTS The study sample included 156,182 respondents, representing 232.8 million adults in the United States (mean age 46 years; 51.7% women). The mean HALex score was 0.85 and 17.7% had poor HALex. Higher SDoH quartile groups had poorer HALex performance (lower scores and increased prevalence of poor HALex). A unit increase in SDoH index was associated with - 0.010 (95% CI [-0.011, -0.010]) difference in HALex score and 20% higher odds of poor HALex (odds ratio, OR = 1.20; 95% CI [1.19, 1.21]). Relative to SDoH-Q1, SDoH-Q4 was associated with HALex score difference of -0.086 (95% CI [-0.089, -0.083]) and OR = 5.32 (95% CI [4.97, 5.70]) for poor HALex. Despite a higher burden of cumulative social disadvantage, Hispanics had a weaker SDoH-HALex association than their non-Hispanic White counterparts. CONCLUSIONS Cumulative social disadvantage was associated with poorer HALex performance in an incremental fashion. Innovations to incorporate SDoH-screening tools into clinical decision systems must continue in order to accurately identify socially vulnerable groups in need of both clinical risk mitigation and social support. To maximize health returns, policies can be tailored through community partnerships to address systemic barriers that exist within distinct sociodemographic groups, as well as demographic differences in health perception and healthcare experience.
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Affiliation(s)
- Kobina Hagan
- Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA
| | - Zulqarnain Javed
- Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA
| | - Miguel Cainzos-Achirica
- Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA
- Division of Cardiovascular Prevention and Wellness, Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, 6550 Fannin St Suite 1801, 77030, Houston, TX, USA
| | - Adnan A Hyder
- Center on Commercial Determinants of Health, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Elias Mossialos
- Department of Health Policy, London School of Economics and Political Sciences, London, UK
- Centre for Health Policy, Imperial College London, London, UK
| | - Tamer Yahya
- Division of Cardiovascular Prevention and Wellness, Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, 6550 Fannin St Suite 1801, 77030, Houston, TX, USA
| | - Isaac Acquah
- Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA
| | - Javier Valero-Elizondo
- Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA
| | - Alan Pan
- Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA
| | - Nwabunie Nwana
- Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA
| | - Mohamad Taha
- Division of Cardiovascular Prevention and Wellness, Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, 6550 Fannin St Suite 1801, 77030, Houston, TX, USA
| | - Khurram Nasir
- Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA.
- Division of Cardiovascular Prevention and Wellness, Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, 6550 Fannin St Suite 1801, 77030, Houston, TX, USA.
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Thompson NR, Lapin BR, Katzan IL. Utilities Estimated from PROMIS Scales for Cost-Effectiveness Analyses in Stroke. Med Decis Making 2023; 43:704-718. [PMID: 37401739 DOI: 10.1177/0272989x231182446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/05/2023]
Abstract
BACKGROUND The EQ-5D and Health Utilities Index Mark 3 (HUI-3) are preference-based measures used in cost-effectiveness studies. The Patient Reported Outcomes Measurement Information System (PROMIS) Preference scoring system (PROPr) is a new preference-based measure. In addition, algorithms were previously developed to map PROMIS Global Health (PROMIS-GH) items to HUI-3 using linear equating (HUILE) and 3-level EQ-5D using linear (EQ5DLE). We sought to evaluate and compare estimated utilities based on PROPr and PROMIS-GH in adult stroke survivors. METHODS We performed a retrospective cohort study of adults diagnosed with 1 of ischemic stroke, intracerebral hemorrhage, or subarachnoid hemorrhage seen in an outpatient clinic between 2015 and 2019. Patients completed PROMIS scales and other measures. We computed a modified version of PROPr (mPROPr) and compared the distributional characteristics and correlations with stroke outcomes for mPROPr, HUILE, and EQ5DLE. RESULTS T toal of 4,159 stroke survivors (average age 62.7 ± 14.7 y, 48.4% female, 77.6% ischemic stroke) were included. Mean utility estimates for mPROPr, EQ5DLE, and HUILE were 0.333 ± 0.244, 0.739 ± 0.201, and 0.544 ± 0.301, respectively. Correlations between the modified Rankin Scale and each of mPROPr and HUILE were both -0.48 and -0.43 for EQ5DLE. Regression analyses indicated that mPROPr scores may be too low for stroke patients in good health and that EQ5DLE scores may be too high for stroke patients in poor health. CONCLUSIONS All 3 PROMIS-based utilities were associated with measures of stroke disability and severity, but the distributions of utilities were very different. Our study highlights the problem cost-effectiveness researchers face of valuing health states with certainty. For researchers using utilities estimated from PROMIS scales, our study indicates that mapping PROMIS-GH item scores to HUI-3 via linear equating may be most appropriate in stroke patients. HIGHLIGHTS A new preference-based measure has been developed from the Patient Reported Outcomes Measurement Information System (PROMIS), known as the PROMIS-Preference (PROPr) scoring system, and published equations mapping PROMIS Global Health (PROMIS-GH) items to the Health Utilities Index Mark 3 (HUI-3) and EQ-5D-3L are available for use in cost-effectiveness studies.Our study provides distributional characteristics and comparisons of utilities estimated using a modified version of PROPr and equations mapping PROMIS-GH items to EQ-5D-3L and HUI-3 in a sample of stroke survivors.The results of our study show large differences in the distributions of utilities estimated using the different health state measures, and these differences highlight the ongoing difficulty researchers face in valuing health states with certainty.
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Affiliation(s)
- Nicolas R Thompson
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA
| | - Brittany R Lapin
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA
| | - Irene L Katzan
- Center for Outcomes Research and Evaluation, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
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Rencz F, Brodszky V, Janssen MF. A Direct Comparison of the Measurement Properties of EQ-5D-5L, PROMIS-29+2 and PROMIS Global Health Instruments and EQ-5D-5L and PROPr Utilities in a General Population Sample. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2023; 26:1045-1056. [PMID: 36804583 DOI: 10.1016/j.jval.2023.02.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 01/26/2023] [Accepted: 02/01/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVES We aimed to compare measurement properties of the 5-level version of EQ-5D (EQ-5D-5L) and 2 Patient-Reported Outcomes Measurement Information System (PROMIS) short forms, PROMIS-29+2 and PROMIS Global Health (PROMIS-GH-10), and of EQ-5D-5L and PROMIS-preference scoring system (PROPr) utilities. METHODS A cross-sectional survey was conducted in a general population sample in Hungary (N = 1631). We compared the following measurement properties at the level of items, domains, and utilities, the latter using corresponding US value sets: ceiling and floor, informativity (Shannon's indices), agreement, convergent, and known-group validity. For the analyses, PROMIS items/domains were matched to EQ-5D-5L domains that cover similar concepts of health. RESULTS The majority of PROMIS items showed enhanced distributional characteristics, including lower ceilings and higher informativity than the EQ-5D-5L. Good convergent validity was established between EQ-5D-5L and PROMIS domains capturing similar aspects of health. Mean EQ-5D-5L utilities were substantially higher than those of PROPr (0.864 vs 0.535). EQ-5D-5L utilities correlated moderately or strongly with PROPr (r = 0.61), PROMIS-GH-10 physical (r = 0.68), and mental health summary scores (r = 0.53). EQ-5D-5L utilities decreased with age, whereas PROPr utilities slightly increased with age. EQ-5D-5L utilities discriminated significantly better in 12/28 (ratio of F-statistics) and 18/26 (area under the receiver-operating characteristics curve ratio) known groups defined by age, self-perceived health status, and self-reported physician-diagnosed health conditions, including hypertension, diabetes, coronary heart disease, chronic kidney disease, and stroke. CONCLUSIONS This study provides comparative evidence on the measurement properties of EQ-5D-5L, PROMIS-29+2, and PROMIS-GH-10 and informs decisions about the choice of instruments in population health surveys for assessment of patients' health and for cost-utility analyses.
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Affiliation(s)
- Fanni Rencz
- Department of Health Policy, Corvinus University of Budapest, Budapest, Hungary.
| | - Valentin Brodszky
- Department of Health Policy, Corvinus University of Budapest, Budapest, Hungary
| | - Mathieu F Janssen
- Section Medical Psychology and Psychotherapy, Department of Psychiatry, Erasmus MC, Rotterdam, The Netherlands
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9
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Case KR, Wang CP, Hosek MG, Lill SF, Howell AB, Taylor BS, Bridges J, MacCarthy DJ, Winkler P, Tsevat J. Health-related quality of life and social determinants of health following COVID-19 infection in a predominantly Latino population. J Patient Rep Outcomes 2022; 6:72. [PMID: 35737279 PMCID: PMC9219362 DOI: 10.1186/s41687-022-00473-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 06/01/2022] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND As the COVID-19 pandemic evolves, more information is needed on its long-term impacts on health-related quality of life (HRQoL) and social determinants of health (SDoH). The aim of the study was to assess HRQoL and SDoH among a predominantly Latino population of COVID-19 survivors and to compare effects in Latinos versus non-Latinos. METHODS This cross-sectional study consisted of a survey (in English and Spanish) of COVID-19 survivors from December 2020 to July 2021. The study assessed sociodemographic data, clinical characteristics, and SDoH, consisting of 10 COVID-19-related concerns. The PROMIS-29 + 2 (PROPr) measure, which captures 8 HRQoL domains and a preference-based health utility, was used to assess HRQoL. Bivariate analyses included chi-square tests and t-tests. Generalized linear models were conducted for multivariable analyses. RESULTS Of 230 respondents (6.3% response rate), the mean [SD] age was 43.1 [14.3] years; 83.0% were Latino; the mean [SD] time since diagnosis was 8.1 [3.2] months; and 12.6% had a history of hospitalization with COVID-19. HRQoL scores were slightly worse than population norms on all domains, especially anxiety; the mean [SD] PROPr health utility was 0.36 [0.25]. Domain scores were similar by ethnicity except for cognitive function-abilities, where scores were lower in Latinos. Multivariable analyses revealed that: (1) financial concerns were associated with worse health utility, as well as worse scores on all 8 PROMIS domains; (2) interpersonal conflict was associated with worse health utility and worse scores on 6 of the 8 PROMIS domains (anxiety, depression, fatigue, sleep disturbance, social function, and pain interference); and (3) Latino ethnicity was only associated with 1 PROMIS domain (cognitive function-abilities) after controlling for covariates. CONCLUSION COVID-19 infection is associated with HRQoL decrements long after the acute infection, and financial concerns and interpersonal conflict are particularly associated with worse HRQoL.
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Affiliation(s)
- Kathleen R Case
- Center for Research to Advance Community Health (ReACH), Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
- Division of General and Hospital Medicine, Department of Medicine, Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
| | - Chen-Pin Wang
- Department of Population Health Sciences, Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Meredith G Hosek
- Joe R. and Teresa Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- School of Public Health, The University of Texas Health Science Center at Houston, San Antonio Campus, San Antonio, TX, USA
| | - Sarah F Lill
- Center for Research to Advance Community Health (ReACH), Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Alexandra B Howell
- Joe R. and Teresa Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- School of Public Health, The University of Texas Health Science Center at Houston, San Antonio Campus, San Antonio, TX, USA
| | - Barbara S Taylor
- Division of Infectious Diseases, Department of Medicine, Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - James Bridges
- Center for Research to Advance Community Health (ReACH), Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Division of General and Hospital Medicine, Department of Medicine, Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Daniel J MacCarthy
- Department of Population Health Sciences, Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Paula Winkler
- Center for Research to Advance Community Health (ReACH), Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- School of Nursing, University of Texas Health Science Center, San Antonio, TX, USA
- South Central Area Health Education Center, University of Texas Health Science Center, San Antonio, TX, USA
| | - Joel Tsevat
- Center for Research to Advance Community Health (ReACH), Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Division of General and Hospital Medicine, Department of Medicine, Joe R. and Teresa Lozano Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
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10
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Neville TH, Hays RD, Tseng CH, Gonzalez CA, Chen L, Hong A, Yamamoto M, Santoso L, Kung A, Schwab K, Chang SY, Qadir N, Wang T, Wenger NS. Survival After Severe COVID-19: Long-Term Outcomes of Patients Admitted to an Intensive Care Unit. J Intensive Care Med 2022; 37:1019-1028. [PMID: 35382627 PMCID: PMC8990100 DOI: 10.1177/08850666221092687] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND Understanding the long-term sequelae of severe COVID-19 remains limited, particularly in the United States. OBJECTIVE To examine long-term outcomes of patients who required intensive care unit (ICU) admission for severe COVID-19. DESIGN, PATIENTS, AND MAIN MEASURES This is a prospective cohort study of patients who had severe COVID-19 requiring an ICU admission in a two-hospital academic health system in Southern California. Patients discharged alive between 3/21/2020 and 12/31/2020 were surveyed approximately 6 months after discharge to assess health-related quality of life using Patient-Reported Outcomes Measurement Information System (PROMIS®)-29 v2.1, post-traumatic stress disorder (PTSD) and loneliness scales. A preference-based health utility score (PROPr) was estimated using 7 PROMIS domain scores. Patients were also asked their attitude about receiving aggressive ICU care. KEY RESULTS Of 275 patients admitted to the ICU for severe COVID-19, 205 (74.5%) were discharged alive and 132 (64%, median age 59, 46% female) completed surveys a median of 182 days post-discharge. Anxiety, depression, fatigue, sleep disturbance, ability to participate in social activities, pain interference, and cognitive function were not significantly different from the U.S. general population, but physical function (44.2, SD 11.0) was worse. PROPr mean score of 0.46 (SD 0.30, range -0.02 to 0.96 [<0 is worse than dead and 1 represents perfect health]) was slightly lower than the U.S. general population, with an even distribution across the continuum. Poor PROPr was associated with chronic medical conditions and receipt of life-sustaining treatments, but not demographics or social vulnerability. PTSD was suspected in 20% and loneliness in 29% of patients. Ninety-eight percent of patients were glad they received life-saving treatment. CONCLUSION Most patients who survive severe COVID-19 achieve positive outcomes, with health scores similar to the general population at 6 months post-discharge. However, there is marked heterogeneity in outcomes with a substantial minority reporting severely compromised health.
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Affiliation(s)
- Thanh H Neville
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Ron D Hays
- Department of Medicine, Division of General Internal Medicine and Health Services Research, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Chi-Hong Tseng
- Department of Medicine, Division of General Internal Medicine and Health Services Research, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Cynthia A Gonzalez
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Lucia Chen
- Department of Medicine, Division of General Internal Medicine and Health Services Research, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Ashley Hong
- 8783University of California, Los Angeles, California, USA
| | - Myrtle Yamamoto
- Department of Medicine, Quality, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Laura Santoso
- Department of Medicine, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Alina Kung
- Department of Medicine, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Kristin Schwab
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Steve Y Chang
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Nida Qadir
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Tisha Wang
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
| | - Neil S Wenger
- Department of Medicine, Division of General Internal Medicine and Health Services Research, 12222David Geffen School of Medicine, UCLA, Los Angeles, California, USA
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11
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Pan T, Mulhern B, Viney R, Norman R, Hanmer J, Devlin N. A Comparison of PROPr and EQ-5D-5L Value Sets. PHARMACOECONOMICS 2022; 40:297-307. [PMID: 34786591 PMCID: PMC8866274 DOI: 10.1007/s40273-021-01109-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 10/31/2021] [Indexed: 06/13/2023]
Abstract
OBJECTIVES The EQ-5D-5L and its value sets are widely used internationally. However, in the US and elsewhere, there is growing use of PROMIS, which has a value set (PROPr) based on the stated preferences of the US population. This paper aims to compare the characteristics of EQ-5D-5L and PROPr value sets and to highlight potential implications for users. METHODS US, Australian and English value sets were used for EQ-5D-5L. PROPr utilities were calculated based on PROMIS-29 + 2. We examined, in each case, (i) the characteristics (e.g. range of values, number of unique values) and distribution of all possible 'theoretical' utilities; (ii) dimension/domain importance ranking by the utility of corner states (i.e. health states with the worst level in one domain and the best in all others); (iii) comparisons of utilities for health states hypothesised to be comparable in terms of severity across EQ-5D-5L descriptive systems and PROMIS-29 + 2 domain scores; (iv) the changes in values of adjacent states (i.e. a one-level change in one dimension for EQ-5D-5L and a four-point change in raw scores for PROMIS-29 + 2, with the other dimensions held constant) for dimensions hypothesised to overlap conceptually or be correlated between the two instruments. RESULTS EQ-5D-5L and PROPr utilities differ systematically. First, the US EQ-5D-5L utilities range from - 0.573 to 1, whereas PROPr values for PROMIS-29 + 2 range from - 0.022 to 0.954. Second, in the US (and English) EQ-5D-5L value sets, pain is the most important dimension whereas in PROPr pain is one of the least important (apart from sleep disturbance). Third, classified based on severity across EQ-5D-5L descriptive systems and PROMIS-29 + 2 domain scores, PROPr has substantially lower values than EQ-5D-5L values for comparable 'mild' health states, but higher values for more 'severe' health states. Last, when one dimension is considered across its best to worst levels and all other dimensions are held constant at their best or moderate level, in EQ-5D-5L value sets, the greatest changes in utility occur between levels 3 and 4 (moderate and severe) problems; in PROPr that occurred between the most severe states and their descriptively adjacent health states. CONCLUSION There are very considerable differences between US EQ-5D-5L and PROPr utilities, despite both in principle representing utility on the same scale anchored at 0 and 1 and both representing the preferences of the US general public. It is important for decision makers and clinical triallists to be aware of these differences. Further work is needed to assess the impact of these differences in value sets using population and patient data, and in longitudinal settings.
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Affiliation(s)
- Tianxin Pan
- Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, 207 Bouverie Street, Carlton, VIC 3053 Melbourne, Australia
- School of Population Health, Curtin University, Perth, WA Australia
| | - Brendan Mulhern
- Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, NSW Australia
| | - Rosalie Viney
- Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, NSW Australia
| | - Richard Norman
- School of Population Health, Curtin University, Perth, WA Australia
| | - Janel Hanmer
- Department of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA USA
| | - Nancy Devlin
- Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, 207 Bouverie Street, Carlton, VIC 3053 Melbourne, Australia
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12
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Hussain J, Chawla G, Rafiqzad H, Huang S, Bartlett SJ, Li M, Howell D, Peipert JD, Novak M, Mucsi I. Validation of the PROMIS sleep disturbance item bank computer adaptive test (CAT) in patients on renal replacement therapy. Sleep Med 2022; 90:36-43. [DOI: 10.1016/j.sleep.2022.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 11/21/2021] [Accepted: 01/04/2022] [Indexed: 10/19/2022]
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13
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Abstract
Patient-reported outcomes are recognized as essential for the evaluation of medical and public health interventions. Over the last 50 years, health-related quality of life (HRQoL) research has grown exponentially from 0 to more than 17,000 papers published annually. We provide an overview of generic HRQoL measures used widely in epidemiological studies, health services research, population studies, and randomized clinical trials [e.g., Medical Outcomes Study SF-36 and the Patient-Reported Outcomes Measurement Information System (PROMIS®)-29]. In addition, we review methods used for economic analysis and calculation of the quality-adjusted life year (QALY). These include the EQ-5D, the Health Utilities Index (HUI), the self-administered Quality of Well-being Scale (QWB-SA), and the Health and Activities Limitation Index (HALex). Furthermore, we consider hybrid measures such as the SF-6D and the PROMIS-Preference (PROPr). The plethora of HRQoL measures has impeded cumulative science because incomparable measures have been used in different studies. Linking among different measures and consensus on standard HRQoL measurement should now be prioritized. In addition, enabling widespread access to common measures is necessary to accelerate future progress. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Robert M Kaplan
- Clinical Excellence Research Center, Department of Medicine, Stanford University, Stanford, California, USA;
| | - Ron D Hays
- Division of General Internal Medicine, Department of Medicine, University of California, Los Angeles, California, USA
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14
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Hanmer J. Measuring population health: association of self-rated health and PROMIS measures with social determinants of health in a cross-sectional survey of the US population. Health Qual Life Outcomes 2021; 19:221. [PMID: 34551778 PMCID: PMC8459525 DOI: 10.1186/s12955-021-01854-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 09/02/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Self-reported health-related quality of life is an important population health outcome, often assessed using a single question about self-rated health (SRH). The Patient Reported Outcomes Measurement Information System (PROMIS) is a new set of measures constructed using item response theory, so each item contains information about an underlying construct. This study's objective is to assess the association between SRH and PROMIS scores and social determinants of health (SDoH) to evaluate the use of PROMIS for measuring population health. METHODS A cross sectional survey of 4142 US adults included demographics, 7 PROMIS domains with 2 items each, the PROMIS-preference (PROPr) score, self-rated health (SRH), 30 social determinants of health (SDoH), and 12 chronic medical conditions. SDoH and chronic condition impact estimates were created by regressing the outcome (PROMIS domain, PROPr, or SRH) on demographics and SDoH or a single chronic condition. Linear regression was used for PROMIS domains and PROPr; ordinal logistic regression was used for SRH. RESULTS Both SRH and PROPr detected statistically significant differences for 11 of 12 chronic conditions. Of the 30 SDoH, 19 statistically significant differences were found by SRH and 26 statistically significant differences by PROPr. The SDoH with statistically significant differences included those addressing education, income, financial insecurity, and social support. The number of statistically significant differences found for SDoH varies by individual PROMIS domains from 13 for Sleep Disturbance to 25 for Physical Function. CONCLUSIONS SRH is a simple single question that provides information about health-related quality of life. The 14 item PROMIS measure used in this study detects more differences in health-related quality of life for social determinants of health than SRH. This manuscript illustrates the relative costs and benefits of each approach to measuring health-related quality of life.
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Affiliation(s)
- Janel Hanmer
- Department of General Medicine, University of Pittsburgh, 230 McKee Place, Pittsburgh, PA, 15213, USA.
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15
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Pan T, Mulhern B, Viney R, Norman R, Tran-Duy A, Hanmer J, Devlin N. Evidence on the relationship between PROMIS-29 and EQ-5D: a literature review. Qual Life Res 2021; 31:79-89. [PMID: 34181154 DOI: 10.1007/s11136-021-02911-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/10/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE EQ-5D and PROMIS-29 are both concise, generic measures of patient-reported outcomes accompanied by preference weights that allow the estimation of quality-adjusted life years (QALYs). Both instruments are candidates for use in economic evaluation. However, they have different features in terms of the domains selected to measure respondents' self-perceived health and the characteristics of (and methods used to obtain) the preference weights. It is important to understand the relationship between the instruments and the implications of choosing either for the evidence used in decision-making. This literature review aimed to synthesise existing evidence on the relationship between PROMIS-29 (and measures based on it, such as PROMIS-29+2) and EQ-5D (both EQ-5D-3L and EQ-5D-5L). METHODS A literature review was conducted in PubMed and Web of Science to identify studies investigating the relationship between PROMIS-29 and EQ-5D-based instruments. RESULTS The literature search identified 95 unique studies, of which nine studies met the inclusion criteria, i.e. compared both instruments. Six studies examined the relationship between PROMIS-29 and EQ-5D-5L. Three main types of relationship have been examined in the nine studies: (a) comparing PROMIS-29 and EQ-5D as descriptive systems; (b) mapping PROMIS-29 domains to EQ-5D utilities; and (c) comparing and transforming PROMIS-29 utilities to EQ-5D utilities. CONCLUSION This review has highlighted the lack of evidence regarding the relationship between PROMIS-29 and EQ-5D. The impact of choosing either instrument on the evidence used in cost-effectiveness analysis is currently unclear. Further research is needed to understand the relationship between the two instruments.
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Affiliation(s)
- Tianxin Pan
- Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health , University of Melbourne, 207 Bouverie Street, Melbourne, VIC, 3010, Australia.
- School of Population Health, Curtin University, Perth, WA, Australia.
| | - Brendan Mulhern
- Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, NSW, Australia
| | - Rosalie Viney
- Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, NSW, Australia
| | - Richard Norman
- School of Population Health, Curtin University, Perth, WA, Australia
| | - An Tran-Duy
- Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health , University of Melbourne, 207 Bouverie Street, Melbourne, VIC, 3010, Australia
| | - Janel Hanmer
- Department of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nancy Devlin
- Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health , University of Melbourne, 207 Bouverie Street, Melbourne, VIC, 3010, Australia
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