Abstract Background Interpretation of health-related quality of life (QOL) outcomes requires improved methods to control for the effects of multiple chronic conditions (MCC). This study systematically compared legacy and improved method effects of aggregating MCC on the accuracy of predictions of QOL outcomes. Methods Online surveys administered generic physical (PCS) and mental (MCS) QOL outcome measures, the Charlson Comorbidity Index (CCI), an expanded chronic condition checklist (CCC), and individualized QOL Disease-specific Impact Scale (QDIS) ratings in a developmental sample (N = 5490) of US adults. Controlling for sociodemographic variables, regression models compared 12- and 35-condition checklists, mortality vs. population QOL-weighting, and population vs. individualized QOL weighting methods. Analyses were cross-validated in an independent sample (N = 1220) representing the adult general population. Models compared estimates of variance explained (adjusted R2) and model fit (AIC) for generic PCS and MCS across aggregation methods at baseline and nine-month follow-up. Results In comparison with sociodemographic-only regression models (MCS R2 = 0.08, PCS = 0.09) and Charlson CCI models (MCS R2 = 0.12, PCS = 0.16), increased variance was accounted for using the 35-item CCC (MCS R2 = 0.22, PCS = 0.31), population MCS/PCS QOL weighting (R2 = 0.31–0.38, respectively) and individualized QDIS weighting (R2 = 0.33 & 0.42). Model R2 and fit were replicated upon cross-validation. Conclusions Physical and mental outcomes were more accurately predicted using an expanded MCC checklist, population QOL rather than mortality CCI weighting, and individualized rather than population QOL weighting for each reported condition. The 3-min combination of CCC and QDIS ratings (QDIS-MCC) warrant further testing for purposes of predicting and interpreting QOL outcomes affected by MCC.

OBJECTIVE:The objective of this study was to develop the classification system for version of the SF-6D (SF-6Dv2) from the SF-36v2. SF-6Dv2 is an improved version of SF-6D, one of the most widely used generic measures of health for the calculation of quality-adjusted life years.STUDY DESIGN AND SETTING:A 3-step process was undertaken to generate a new classification system: (1) factor analysis to establish dimensionality; (2) Rasch analysis to understand item performance; and (3) tests of differential item function. To evaluate robustness, Rasch analyses were performed in multiple subsets of 2 large cross-sectional datasets from recently discharged hospital patients and online patient samples.RESULTS:On the basis of factor analysis, other psychometric evidence, cross-cultural considerations, and amenability to valuation, the 6-dimension classification used in SF-6D was maintained. SF-6Dv2 resulted in the following modifications to SF-6D: a simpler classification of physical function with clearer separation between levels; a more detailed 5-level description of role limitations; using negative wording to describe vitality; and using pain severity rather than pain interference.CONCLUSIONS:The SF-6Dv2 classification system describes more distinct levels of health than SF-6D, changes the descriptions used for a number of dimensions and provides clearer wording for health state valuation. The second stage of the study has developed a utility value set using discrete choice methods so that the measure can be used in health technology assessment. Further work should investigate the psychometric characteristics of the new instrument.

ObjectiveTo evaluate reliability, validity and responsiveness of KOOS-12, a 12-item short form of the 42-item Knee injury and Osteoarthritis Outcome Score (KOOS) that provides Pain, Function and Quality of Life (QOL) scale scores and a summary knee impact score.DesignData from 1,392 knee osteoarthritis (OA) patients from the FORCE-TJR research cohort who completed KOOS before and 6 and 12 months after total knee replacement (TKR) were analyzed. KOOS-12 includes a pain frequency item and three items measuring pain during increasingly difficult (sitting/lying, walking, stairs) activities; function items about standing, rising from sitting, getting in/out of a car, and twisting/pivoting; and the 4-item KOOS QOL scale. Percent computable scale scores, floor and ceiling effects, internal consistency reliability, validity (scale correlations, tests of known groups validity using one-way analysis of variance (ANOVA)) and responsiveness (effect sizes, standardized response means) were compared for the KOOS-12, full-length KOOS, KOOS-PS and KOOS, JR.ResultsInternal consistency reliability was above 0.70 for all KOOS-12 scales and ≥0.90 for the KOOS-12 Summary score. Validity and responsiveness of KOOS-12 Pain, Function and QOL scales was satisfactory and reached similar conclusions as comparable full-length KOOS scales. The KOOS-12 Summary score was most responsive in discriminating between groups who differed in global ratings of post-TKR change in physical capabilities and had the highest effect sizes and standardized response means.ConclusionsKOOS-12 was a reliable and valid alternative to KOOS in TKR patients with moderate to severe OA and provided three domain-specific and summary knee impact scores with substantially reduced respondent burden.

BACKGROUND Patient-reported outcome measures that are more practical and clinically useful are needed for patients with CKD. We compared a new CKD-specific quality-of-life impact scale (CKD-QOL) with currently used measures. METHODS Patients (n=485) in different treatment groups (nondialysis stages 3-5, on dialysis, or post-transplant) completed the kidney-specific CKD-QOL and Kidney Disease Quality of Life-36 (KDQOL-36) forms and the generic SF-12 Health Survey at baseline and 3 months. New items summarizing quality of life (QOL) impact attributed to CKD across six QOL domains yielded single impact scores from a six-item static (fixed-length) form and from computerized adaptive tests (CATs) with three to six items. Validity tests compared the CKD-QOL, KDQOL-36 (Burden, Effects, and Symptoms/Problems subscales), and generic SF-12 measures across groups in four tests of clinical status and clinician assessment of change (CKD-specific tests), and number of comorbidities. ANOVA was used to test for group mean differences, variances in each measure explained by groups, and relative validity (RV) in comparison with the referent KDQOL-36 Burden subscale. RESULTS KDQOL-36 and CKD-QOL measures generally discriminated better than generic SF-12v2 measures. The pattern of variances across CKD-specific tests comparing validity favored CKD-QOL two-fold over KDQOL-36. Two RV test results confirmed CKD-QOL improvements over the referent KDQOL scale. Results for static and CAT CKD-QOL forms were similar. SF-12 Physical and KDQOL-36 Symptoms scores worsened with increasing comorbid condition counts. CONCLUSIONS Overall, compared with the KDQOL-36, the new approach to summarizing CKD-specific QOL impact performed better across multiple tests of validity. CAT surveys were more efficient than static surveys.

Objective: To evaluate reliability, validity and responsiveness of HOOS-12, a 12-item short form of the 40-item Hip disability and Osteoarthritis Outcome Score (HOOS). HOOS-12 provides Pain, Function and Quality of Life (QOL) scale scores and a summary hip impact score. Design: Data from 1,273 FORCE-TJR hip osteoarthritis (OA) patients who completed HOOS before and six and 12 months after total hip replacement (THR) were analyzed. HOOS-12 includes a pain frequency item and three items measuring pain during increasingly difficult (sitting/lying, walking, stairs) activities; function items about standing, rising from sitting, getting in/out of a car, and walking on an uneven surface; and the 4-item HOOS QOL scale. Percent computable scale scores, floor and ceiling effects, internal consistency reliability, validity (scale correlations, tests of known groups validity using one-way analysis of variance (ANOVA)), and responsiveness (effect sizes (ES), standardized response means (SRM)) were compared for HOOS-12, full-length HOOS, HOOS-PS and HOOS, JR. Results: Internal consistency reliability was above 0.70 for all HOOS-12 scales and above 0.90 for the HOOS-12 Summary score. Validity and responsiveness of HOOS-12 Pain, Function and QOL scales were satisfactory and reached similar conclusions as comparable full-length HOOS scales. The HOOS-12 Summary score was highly responsive in discriminating between groups who differed in global ratings of post-THR change in physical capabilities and had high ES and SRM standardized response means. Conclusions: HOOS-12 was a reliable and valid alternative to HOOS in THR patients with moderate to severe OA and provided three domain-specific and summary hip impact scores with substantially reduced respondent burden. (C) 2019 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Little is known about how barriers to healthcare access affect health-related quality of life (HRQOL) after an acute coronary syndrome (ACS). In a large cohort of ACS survivors from 6 medical centers in Massachusetts and Georgia enrolled from 2011 to 2013, patients were classified as having any financial barriers, no usual source of care (USOC), or transportation barriers to healthcare based on their questionnaire survey responses. The principal study outcomes included clinically meaningful declines in generic physical and mental HRQOL and in disease-specific HRQOL from 1 to 6 months posthospital discharge. Adjusted relative risks (aRRs) for declines in HRQOL were calculated using Poisson regression models, controlling for several sociodemographic and clinical factors of prognostic importance. In 1,053 ACS survivors, 29.0% had a financial barrier, 14.2% had no USOC, and 8.7% had a transportation barrier. Patients with a financial barrier had greater risks of experiencing a decline in generic physical (aRR 1.48, 95% confidence interval [CI] 1.17, 1.86) and mental (aRR 1.36, 95% CI 1.07, 1.75) HRQOL at 6 months. Patients with 2 or more access barriers had greater risks of decline in generic physical (aRR 1.53, 95% CI 1.20, 1.93) and mental (aRR 1.50, 95% CI 1.17, 1.93) HRQOL compared with those without any healthcare barriers. There was a modest association between lacking a USOC and experiencing a decline in disease-specific HRQOL (aRR 1.46, 95% CI 0.96, 2.22). Financial and other barriers to healthcare access may be associated with clinically meaningful declines in HRQOL after hospital discharge for an ACS. (C) 2018 Published by Elsevier Inc.

Objective: To develop 12-item short forms (KOOS-12, HOOS-12) of the 42-item Knee injury and Osteoar-thritis Outcome Score (KOOS) and 40-item Hip disability and Osteoarthritis Outcome Score (HOOS) that represent the full-length instruments sufficiently to provide joint-specific pain, function and quality of life (QOL) domain and summary joint impact scores. This paper describes KOOS-12 and HOOS-12 item selection. Subsequent papers will examine KOOS-12 and HOOS-12 reliability, validity and responsiveness. Design: Items were selected based on qualitative information from patients, clinicians and KOOS/HOOS translators and analysis of data from 1,395 knee osteoarthritis (OA) and 1,281 hip OA patients from the FORCE-TJR cohort who completed KOOS or HOOS before and after total joint replacement (TJR). Item response theory models and computerized adaptive test (CAT) simulations were used to identify items that best measured patients' levels of pain and function pre-and post-TJR. KOOS-12/HOOS-12 items were selected based on content, coverage of a wide measurement range, high item information, item usage in CAT simulations, scale-level properties (reliability, validity, responsiveness), and qualitative information. Results: KOOS-12 and HOOS-12 each included a pain frequency item and three items measuring pain during increasingly difficult activities (sitting/lying, walking, up/down stairs); function items about standing, rising from sitting, getting in/out of a car, and twisting/pivoting (KOOS-12) or walking on an uneven surface (HOOS-12); and the original 4-item QOL scale. Conclusions: This study demonstrated the benefits of examining patient-reported outcome measures using modern psychometric methods, to create short forms with diverse content that provide domain-specific and summary joint impact scores. (C) 2019 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Background: Patient activation comprises the knowledge, skills, and confidence for self-care and may lead to better health outcomes. Objectives: We examined the relationship between patient activation and changes in health-related quality of life (HRQOL) after hospitalization for an acute coronary syndrome (ACS). Methods: We studied patients from 6 medical centers in central Massachusetts and Georgia who had been hospitalized for an ACS between 2011 and 2013. At 1 month after hospital discharge, the patients completed the 6-item Patient Activation Measure and were categorized into 4 levels of activation. Multinomial logistic regression analyses compared activation level with clinically meaningful changes (≥3.0 points, generic; ≥10.0 points, disease-specific) in generic physical (SF-36v2 Physical Component Summary [PCS]), generic mental (SF-36v2 Mental Component Summary [MCS]), and disease-specific (Seattle Angina Questionnaire [SAQ]) HRQOL from 1 to 3 and 1 to 6 months after hospitalization, adjusting for potential sociodemographic and clinical confounders. Results: The patients (N = 1042) were, on average, 62 years old, 34% female, and 87% non-Hispanic white. A total of 10% were in the lowest level of activation. The patients with the lowest activation had 1.95 times (95% confidence interval, 1.05–3.62) and 2.18 times (95% confidence interval, 1.17–4.05) the odds of experiencing clinically significant declines in MCS and SAQ HRQOL, respectively, between 1 and 6 months than the most activated patients. The patient activation level was not associated with meaningful changes in PCS scores. Conclusions: Hospital survivors of an ACS with lower activation may be more likely to experience declines in mental and disease-specific HRQOL than more-activated patients, identifying a group at risk of poor outcomes.

ObjectiveTo evaluate validity and responsiveness of the Knee Injury and Osteoarthritis Outcome Score (KOOS) in relation to other patient-reported outcome measures before and after total knee replacement (TKR).MethodsPre-TKR and 6-month post-TKR data from 1,143 patients in a US joint replacement cohort were used to compare the KOOS, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the SF-36 Health Survey (SF-36). Validity was evaluated with multiple methods, including correlations of pre-TKR scale scores and analysis of variance models that used pre-TKR data to compare the relative validity of scales in discriminating between groups differing in assistive walking device use and number of comorbid conditions. Validity was also evaluated by using post-TKR minus pre-TKR change scores to assess relative validity of scales in discriminating between groups rating themselves as better, same, or worse (BSW) in their capability to do activities at 6 months. Responsiveness also was described using effect sizes and standardized response means.ResultsIn support of convergent and discriminant validity, KOOS scale scores were worse for patients using an assistive device but only declined weakly with increasing comorbid conditions. While all knee-specific scales discriminated between BSW groups, the KOOS quality of life (QOL) scale was significantly better (P<0.05) than all measures except the SF-36 physical component summary. KOOS QOL also had the highest effect size, while SF-36 measures had lower effect sizes and standardized response means. KOOS pain and symptoms scales discriminated better than WOMAC pain and stiffness scales among BSW groups.ConclusionKOOS scales were valid and responsive in this cohort of US TKR patients. KOOS QOL performed particularly well in capturing aggregate knee-specific outcomes.

Physical function (PF) is a core patient-reported outcome domain in clinical trials in rheumatic diseases. Frequently used PF measures have ceiling effects, leading to large sample size requirements and low sensitivity to change. In most of these instruments, the response category that indicates the highest PF level is the statement that one is able to perform a given physical activity without any limitations or difficulty. This study investigates whether using an item format with an extended response scale, allowing respondents to state that the performance of an activity is easy or very easy, increases the range of precise measurement of self-reported PF.

Background: Patient activation comprises the knowledge, skills, and confidence for self-care, and may lead to better health outcomes. Hypothesis: We hypothesized that less-activated survivors of a hospitalization for an acute coronary syndrome (ACS) would be more likely to experience declines in health-related quality of life than more activated patients. Methods: We studiedpatients from 6 medical centers in central Massachusetts and Georgia who had been hospitalized for an ACS between 2011 and 2013. At 1 month after hospital discharge, patients completed the 6-item Patient Activation Measure and at 1, 3, and 6 months after discharge generic physical (SF-36 PCS), generic mental (SF-36 MCS), and disease-specific (SAQ - Seattle Angina Questionnaire) health-related quality of life (QOL) scales. Four categories of 1-month activation levels were defined. Multinomial logistic regression estimated odds ratios were calculated for clinically meaningful changes in QOL, with patients in the highest level of activation serving as the referent group, adjusting for sociodemographic and clinical confounders. Results: Patients (n=1,042) were on average 62 years old, 34% were female, and 87% were non-Hispanic white; 10% and 29% of patients were in the lowest and highest levels of activation, respectively. Higher proportions of patients in the least activated group vs. the most activated group tended to experience clinically meaningful declines in QOL, for all scales and both follow-up periods (Table). Least activated patients had significantly higher adjusted odds of experiencing clinically meaningful declines in MCS and SAQ scores from 1 to 6 months after hospital discharge, but not PCS scores, with a similar pattern observed between 1 and 3 months after hospital discharge. Conclusions: Following hospitalization for an ACS, patients with low activation may be more likely to have declines in mental and disease-specific health-related QOL than highly activated patients, identifying a group at high risk of poor outcomes.

To document the development and evaluation of the Quality of life Disease Impact Scale (QDIS®), a measure that standardizes item content and scoring across chronic conditions and provides a summary, norm-based QOL impact score for each disease.

Background: A crucial assumption underlying all disease-specific quality of life (QOL) measures, that patients can validly differentiate a specific disease in the presence of multiple chronic conditions, has not been tested using multiple methods. Our objective was to evaluate the convergent and discriminant validity of QOL attributions to specific diseases among adults with multiple chronic conditions (MCC). Methods: Adults age 18 and older (N=4,480) sampled from eight pre-identified condition groups (asthma, COPD, angina/MI with angina, congestive heart failure, diabetes, chronic kidney disease, osteoarthritis, rheumatoid arthritis) completed an Internet survey. Comorbid conditions were determined using a 35-condition checklist. Product-moment correlations were analyzed separately by pre-identified condition group using the multitrait-multimethod of construct validation, where traits were defined by 9-26 conditions and each condition was measured by two methods: disease severity rating and Disease-specific Quality of Life Impact Scale (QDIS) global rating. A third method (symptom or clinical marker) was available for the eight pre-identified conditions. Convergent validity was supported when correlations among different methods of measuring the same condition (trait) were substantial (r≥ 0.40). Discriminant validity was supported when correlations between the same and different methods of measuring different conditions were significantly lower than corresponding convergent correlations. Results: In support of convergent validity, 22 of 24 convergent correlations were substantial (r=0.38-0.84, median=0.53). In support of discriminant validity, 833 of 924 tests (90.2%) yielded significantly higher convergent than discriminant correlations across the eight pre-identified conditions. Exceptions to this pattern of results were most often observed for comorbid conditions within the same clinical area. Conclusions: Collectively, convergent and discriminant test results support the construct validity of disease-specific QOL impact attributions across MCC within the eight pre-identified conditions. Noteworthy exceptions should be considered when interpreting some specific QOL impact attributions and warrant further study. Pursuit of a summary disease-specific QOL impact score standardized across MCC is recommended.