This is a review of the Health Utilities Index (HUI) multi-attribute health-status classification systems, and single- and multi-attribute utility scoring systems. HUI refers to both HUI Mark 2 ...(HUI2) and HUI Mark 3 (HUI3) instruments. The classification systems provide compact but comprehensive frameworks within which to describe health status. The multi-attribute utility functions provide all the information required to calculate single-summary scores of health-related quality of life (HRQL) for each health state defined by the classification systems. The use of HUI in clinical studies for a wide variety of conditions in a large number of countries is illustrated. HUI provides comprehensive, reliable, responsive and valid measures of health status and HRQL for subjects in clinical studies. Utility scores of overall HRQL for patients are also used in cost-utility and cost-effectiveness analyses. Population norm data are available from numerous large general population surveys. The widespread use of HUI facilitates the interpretation of results and permits comparisons of disease and treatment outcomes, and comparisons of long-term sequelae at the local, national and international levels.
Purpose An essential aspect of patient-centered outcomes research (PCOR) and comparative effectiveness research (CER) is the integration of patient perspectives and experiences with clinical data to ...evaluate interventions. Thus, PCOR and CER require capturing patient-reported outcome (PRO) data appropriately to inform research, healthcare delivery, and policy. This initiative’s goal was to identify minimum standards for the design and selection of a PRO measure for use in PCOR and CER. Methods We performed a literature review to find existing guidelines for the selection of PRO measures. We also conducted an online survey of the International Society for Quality of Life Research (ISOQOL) membership to solicit input on PRO standards. A standard was designated as “recommended” when >50 % respondents endorsed it as “required as a minimum standard.” Results The literature review identified 387 articles. Survey response rate was 120 of 506 ISOQOL members. The respondents had an average of 15 years experience in PRO research, and 89 % felt competent or very competent providing feedback. Final recommendations for PRO measure standards included: documentation of the conceptual and measurement model; evidence for reliability, validity (content validity, construct validity, responsiveness); interpretability of scores; quality translation, and acceptable patient and investigator burden. Conclusion The development of these minimum measurement standards is intended to promote the appropriate use of PRO measures to inform PCOR and CER, which in turn can improve the effectiveness and efficiency of healthcare delivery. A next step is to expand these minimum standards to identify best practices for selecting decision-relevant PRO measures.
Although many Canadian studies have provided disease-specific or patient group-specific utility scores, the utility score norms currently available for the general Canadian population are outdated. ...Canadian guideline recommendations for the economic evaluation of health technologies advocate for utilities reflecting those of the general population and for stratified analyses when results are heterogeneous; as such, there is also a need for age-, sex- and jurisdiction-specific utility score norms.
We used data from the 2013-2014 Canadian Community Health Survey. We used the Health Utilities Index Mark 3 to calculate utility scores. We estimated means (with 95% confidence intervals CIs) and medians (with interquartile ranges IQRs) for utility scores. In addition to Canadian-level measures, we stratified all utility score norms by respondents' age, sex, and province or territory of residence. We weighted respondents' answers and computed 95% CIs using sampling weights and bootstrap weights provided by Statistics Canada to extrapolate the study findings to the Canadian population.
Respondents to the 2013-2014 Canadian Community Health Survey represented 30 014 589 community-dwelling Canadians 12 years of age and older (98% of the Canadian population); half of the respondents were female (50.6%), and the weighted average age was 44.8 (95% CI 44.7-44.9) years. The mean and median self-reported utility scores for Canadians were estimated at 0.863 (95% CI 0.861-0.865) and 0.927 (IQR 0.838-0.972), respectively.
This study provides utility score norms for several age-, sex-and jurisdiction-specific strata in Canada. These results will be useful for future cost-utility analyses and could serve as benchmark values for comparisons with future studies.
Although a clear risk of mortality is associated with obesity, the risk of mortality associated with overweight is equivocal. The objective of this study is to estimate the relationship between BMI ...and all-cause mortality in a nationally representative sample of Canadian adults. A sample of 11,326 respondents aged ≥25 in the 1994/1995 National Population Health Survey (Canada) was studied using Cox proportional hazards models. A significant increased risk of mortality over the 12 years of follow-up was observed for underweight (BMI <18.5; relative risk (RR) = 1.73, P < 0.001) and obesity class II+ (BMI >35; RR = 1.36, P <0.05). Overweight (BMI 25 to <30) was associated with a significantly decreased risk of death (RR = 0.83, P < 0.05). The RR was close to one for obesity class I (BMI 30–35; RR = 0.95, P >0.05). Our results are similar to those from other recent studies, confirming that underweight and obesity class II+ are clear risk factors for mortality, and showing that when compared to the acceptable BMI category, overweight appears to be protective against mortality. Obesity class I was not associated with an increased risk of mortality.
While research suggests that higher continuity of primary and specialty physician care can improve patient outcomes, their effects have rarely been examined and compared concurrently. We investigated ...associations between continuity of primary and specialty physician care and emergency department visits and hospital admissions among community-dwelling older adults with complex care needs. We conducted a retrospective cohort study of home care patients in Ontario, Canada, from October 2014 to September 2016. We measured continuity of primary and specialty physician care over the two years prior to a home care assessment and categorized them into low, medium, and high groups using terciles of the distribution. We used Cox regression models to concurrently test the associations between continuity of primary and specialty care and risk of an emergency department visit and hospital admission within six months of assessment, controlling for potential confounders. We examined interactions between continuity of care and count of chronic conditions, count of physician specialties seen, functional impairment, and cognitive impairment. Of 178,686 participants, 49% had an emergency department visit during follow-up and 27% had a hospital admission. High vs. low continuity of primary care was associated with a reduced risk of an emergency department visit (HR = 0.90 (0.89-0.92)) as was continuity of specialty care (HR = 0.93 (0.91-0.95)). High vs. low continuity of primary care was associated also with a reduced risk of a hospital admission (HR = 0.94 (0.92-0.96)) as was continuity of specialty care (HR = 0.92 (0.90-0.94)). The effect of continuity of specialty care was moderately stronger among patients who saw four or more physician specialties. Higher continuity of primary physician and specialty physician care had independent, protective effects of similar magnitude against emergency department use and hospital admissions. Improving continuity of specialty care should be a priority alongside improving continuity of primary care in complex, older adult populations with significant specialist use.
Cognitive impairment is common in the hip fracture patient population, yet few studies of functional recovery include this subgroup. The objective was to determine whether baseline cognition was a ...determinant of the rate of functional recovery over 6 months after hip fracture.
A consecutive cohort of 383 patients 65 years or older who were treated for hip fracture within a Canadian health region were grouped on cognitive status. Participants with Mini-Mental Status Examination scores <18 at 3-5 days postoperatively were classified as cognitively impaired. Primary outcome was the Functional Independence Measure. Interviews were completed within 5 days postoperatively (baseline), 1, 3, and 6 months postoperatively. Linear mixed modeling examined the pattern of recovery and the effect of cognitive status.
Of the 383 participants, 104 (27%) had Mini-Mental Status Examination scores of less than 18. The effect size for changes in the FIM over 6 months was large for those without cognitive impairment (effect size = 2.3) and smaller for those with cognitive impairment (effect size = 0.9). After adjusting for age, gender, proxy respondent, and fracture type, participants with impaired cognition recovered more slowly, never attaining comparable levels with those without cognitive impairment. The 6-month health status for the cohort was substantially lower than the health status of age-gender-matched, community-dwelling adults.
Patients with cognitive impairment who fracture their hips recover more slowly and achieve less functional recovery. Recovery is not uniform nor is it linear over the initial 6 months. The diversity of patient needs should be recognized postoperatively so that long-term recovery is optimized.
The PROMIS-Preference (PROPr) score is a recently developed summary score for the Patient-Reported Outcomes Measurement Information System (PROMIS). PROPr is a preference-based scoring system for ...seven PROMIS domains created using multiplicative multi-attribute utility theory. It serves as a generic, societal, preference-based summary scoring system of health-related quality of life. This manuscript evaluates construct validity of PROPr in two large samples from the US general population.
We utilized 2 online panel surveys, the PROPr Estimation Survey and the Profiles-Health Utilities Index (HUI) Survey. Both included the PROPr measure, patient demographic information, self-reported chronic conditions, and other preference-based summary scores: the EuroQol-5D (EQ-5D-5L) and HUI in the PROPr Estimation Survey and the HUI in the Profiles-HUI Survey. The HUI was scored as both the Mark 2 and the Mark 3. Known-groups validity was evaluated using age- and gender-stratified mean scores and health condition impact estimates. Condition impact estimates were created using ordinary least squares regression in which a summary score was regressed on age, gender, and a single health condition. The coefficient for the health condition is the estimated effect on the preference score of having a condition vs. not having it. Convergent validity was evaluated using Pearson correlations between PROPr and other summary scores.
The sample consisted of 983 respondents from the PROPr Estimation Survey and 3,000 from the Profiles-HUI survey. Age- and gender-stratified mean PROPr scores were lower than EQ-5D and HUI scores, with fewer subjects having scores corresponding to perfect health on the PROPr. In the PROPr Estimation survey, all 11 condition impact estimates were statistically significant using PROPr, 8 were statistically significant by the EQ-5D, 7 were statistically significant by HUI Mark 2, and 9 were statistically significant by HUI Mark 3. In the Profiles-HUI survey, all 21 condition impact estimates were statistically significant using summary scores from all three scoring systems. In these samples, the correlations between PROPr and the other summary measures ranged from 0.67 to 0.70.
These results provide evidence of construct validity for PROPr using samples from the US general population.
Health‐related quality of life (HRQL) is an amalgam of three elements – the opportunities that a person's health status affords, the constraints that it places upon the person and the value that a ...person places on his/her health status. HRQL measures are specific, for example for a disease, or generic with broad applicability. The latter include preference‐based measures that can be used to generate quality‐adjusted life years and so contribute to economic evaluation. Measures of HRQL in adolescents and young adults (AYAs) with cancer may fail to capture some important dimensions, for example sexual health. However, the use of HRQL measures in this population has identified burdens of morbidity according to disease, treatment status and duration of follow‐up. There are few economic evaluations of the treatment of cancer in AYAs but preliminary evidence suggests that this is a cost‐effective undertaking. Opportunities abound to include measurement of HRQL in routine clinical care.
Objective: This study aimed to describe the self-reported health status of the general adult U.S. population using 3 multi-attribute preference-based measures: the EQ-5D, Health Utilities Index Mark ...2 (HUI2), and Mark 3 (HUI3). Methods: We surveyed the general adult U.S. population using a probability sample with oversampling of Hispanics and non-Hispanic blacks. Respondents to this home-visit survey self-completed the EQ-5D and HUI2/3 questionnaires. Overall health index scores of the target population and selected subgroups were estimated and construct validity of these measures was assessed by testing a priori hypotheses. Results: Completed questionnaires were collected from 4048 respondents (response rate: 59.4%). The majority of the respondents were women (52.0%); the mean age of the sample was 45 years, with 14.8% being 65 or older. Index scores (standard errors) for the general adult U.S. population as assessed by the EQ-5D, HUI2, and HUI3 were 0.87 (0.01), 0.86 (0.01), and 0.81 (0.01), respectively. Generally, younger, male and Hispanic or non-Hispanic black adults had higher (better) index scores than older, female and other racial/ethnic adults; index scores were higher with higher educational attainment and household income. The 3 overall preference indices were strongly correlated (Pearson's r: 0.67-0.87), but systematically different, with intraclass correlation coefficients between these indices ranging from 0.59 to 0.77. Conclusions: This study provides U.S. population norms for self-reported health status on the EQ-5D, HUI2, and HUI3. Although these measures appeared to be valid and demonstrated similarities, health status assessed by these measures is not exactly the same.
The North Star Ambulatory Assessment (NSAA) documents motor performance in ambulatory individuals with Duchenne muscular dystrophy (DMD). Health Utilities Index (HUI) scores, reflecting preferences ...for health-related quality-of-life (HRQoL) implications of health states, are commonly estimated within trials. This study sought to characterize the relationship between the NSAA score and utility in DMD.
Family members serving as proxy respondents for placebo-treated ambulatory individuals with DMD (NCT01254019; BioMarin Pharmaceuticals Inc) completed the HUI and the NSAA (score range, 0-34). Mean change over time on these measures was estimated, and the correlation between changes in NSAA score and a) HUI utility; b) HUI3 ambulation and HUI2 mobility attribute scores, over 48 weeks was calculated.
Baseline mean (range) age was 8.0 years (5-16; n = 61) and mean (standard deviation SD) scores were 0.87 (0.13; HUI2), 0.82 (0.19; HUI3), and 21.0 (8.1; NSAA). Mean (SD) change over 48 weeks was -0.05 (0.14; HUI2), -0.06 (0.19; HUI3), and -2.9 (4.7; NSAA). Weak positive correlations were observed between baseline NSAA score and HUI utility (HUI2: r = 0.29; HUI3: r = 0.17) and for change over 48 weeks (HUI2: r = 0.16; HUI3: r = 0.15). Stronger correlations were observed between change in NSAA score and the HUI3 ambulation (r = 0.41) and HUI2 mobility (r = 0.41) attributes.
Among ambulatory individuals with DMD, NSAA score is weakly correlated with HUI utility, suggesting that motor performance alone does not fully explain HRQoL. Stronger relationships were observed between HUI ambulation and mobility attributes, and NSAA. Although unidimensional measures like the NSAA are informative for documenting disease-specific health impacts, they may not correlate well with measures of overall health status; requiring use in conjunction with other patient-reported and preference-based outcomes.
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