scholarly journals Exclusion Criteria as Measurements II: Effects on Utility Functions

2019 ◽  
Vol 39 (6) ◽  
pp. 704-716
Author(s):  
Barry Dewitt ◽  
Baruch Fischhoff ◽  
Alexander L. Davis ◽  
Stephen B. Broomell ◽  
Mark S. Roberts ◽  
...  
Keyword(s):  
Online Survey ◽  
Standard Gamble ◽  
Utility Functions ◽  
Measurement Information ◽  
Exclusion Criteria ◽  
Health States ◽  
Companion Article ◽  
Patient Reported ◽  
Health Domains ◽  
Standard Gamble Method

Background. Researchers often justify excluding some responses in studies eliciting valuations of health states as not representing respondents’ true preferences. Here, we examine the effects of applying 8 common exclusion criteria on societal utility estimates. Setting. An online survey of a US nationally representative sample ( N = 1164) used the standard gamble method to elicit preferences for health states defined by 7 health domains from the Patient-Reported Outcomes Measurement Information System (PROMIS®). Methods. We estimate the impacts of applying 8 commonly used exclusion criteria on mean utility values for each domain, using beta regression, a form of analysis suited to double-bounded scales, such as utility. Results. Exclusion criteria have varied effects on the utility functions for the different PROMIS health domains. As a result, applying those criteria would have varied effects on the value of treatments (and side effects) that change health status on those domains. Limitations. Although our method could be applied to any health utility judgments, the present estimates reflect the features of the study that produced them. Those features include the selected health domains, standard gamble method, and an online format that excluded some groups (e.g., visually impaired and illiterate individuals). We also examined only a subset of all possible exclusion criteria, selected to represent the space of possibilities, as characterized in a companion article. Conclusions. Exclusion criteria can affect estimates of the societal utility of health states. We use those effects, in conjunction with the results of the companion article, to make suggestions for selecting exclusion criteria in future studies.

scholarly journals Exclusion Criteria as Measurements I: Identifying Invalid Responses

2019 ◽  
Vol 39 (6) ◽  
pp. 693-703
Author(s):  
Barry Dewitt ◽  
Baruch Fischhoff ◽  
Alexander L. Davis ◽  
Stephen B. Broomell ◽  
Mark S. Roberts ◽  
...  
Keyword(s):  
Online Survey ◽  
Health State Valuation ◽  
Measurement Information ◽  
Health State ◽  
Exclusion Criteria ◽  
Health States ◽  
Patient Reported ◽  
Measurement Information System ◽  
Nationally Representative ◽  
Very High

Background. In a systematic review, Engel et al. found large variation in the exclusion criteria used to remove responses held not to represent genuine preferences in health state valuation studies. We offer an empirical approach to characterizing the similarities and differences among such criteria. Setting. Our analyses use data from an online survey that elicited preferences for health states defined by domains from the Patient-Reported Outcomes Measurement Information System (PROMIS®), with a U.S. nationally representative sample ( N = 1164). Methods. We use multidimensional scaling to investigate how 10 commonly used exclusion criteria classify participants and their responses. Results. We find that the effects of exclusion criteria do not always match the reasons advanced for applying them. For example, excluding very high and very low values has been justified as removing aberrant responses. However, people who give very high and very low values prove to be systematically different in ways suggesting that such responses may reflect different processes. Conclusions. Exclusion criteria intended to remove low-quality responses from health state valuation studies may actually remove deliberate but unusual ones. A companion article examines the effects of the exclusion criteria on societal utility estimates.

scholarly journals Estimation of a Preference-Based Summary Score for the Patient-Reported Outcomes Measurement Information System: The PROMIS®-Preference (PROPr) Scoring System

2018 ◽  
Vol 38 (6) ◽  
pp. 683-698 ◽  
Author(s):  
Barry Dewitt ◽  
David Feeny ◽  
Baruch Fischhoff ◽  
David Cella ◽  
Ron D. Hays ◽  
...  
Keyword(s):  
Scoring System ◽  
Patient Reported Outcomes ◽  
Online Survey ◽  
Measurement Information ◽  
Scoring Functions ◽  
Health States ◽  
Outcomes Measurement ◽  
Patient Reported ◽  
Single Attribute ◽  
Measurement Information System

Background. Health-related quality of life (HRQL) preference-based scores are used to assess the health of populations and patients and for cost-effectiveness analyses. The National Institutes of Health Patient-Reported Outcomes Measurement Information System (PROMIS®) consists of patient-reported outcome measures developed using item response theory. PROMIS is in need of a direct preference-based scoring system for assigning values to health states. Objective. To produce societal preference-based scores for 7 PROMIS domains: Cognitive Function–Abilities, Depression, Fatigue, Pain Interference, Physical Function, Sleep Disturbance, and Ability to Participate in Social Roles and Activities. Setting. Online survey of a US nationally representative sample ( n = 983). Methods. Preferences for PROMIS health states were elicited with the standard gamble to obtain both single-attribute scoring functions for each of the 7 PROMIS domains and a multiplicative multiattribute utility (scoring) function. Results. The 7 single-attribute scoring functions were fit using isotonic regression with linear interpolation. The multiplicative multiattribute summary function estimates utilities for PROMIS multiattribute health states on a scale where 0 is the utility of being dead and 1 the utility of “full health.” The lowest possible score is –0.022 (for a state viewed as worse than dead), and the highest possible score is 1. Limitations. The online survey systematically excludes some subgroups, such as the visually impaired and illiterate. Conclusions. A generic societal preference-based scoring system is now available for all studies using these 7 PROMIS health domains.

scholarly journals Performance of the Patient-Reported Outcome Measurement Information System in Patients With Patellofemoral Instability

2020 ◽  
Vol 8 (4) ◽  
pp. 232596712091554 ◽  
Author(s):  
Christina J. Hajewski ◽  
Jacqueline E. Baron ◽  
Natalie A. Glass ◽  
Kyle R. Duchman ◽  
Matthew Bollier ◽  
...  
Keyword(s):  
Information System ◽  
Outcome Measurement ◽  
Patellofemoral Instability ◽  
Patient Reported Outcome ◽  
Measurement Information ◽  
Sf 36 ◽  
Patient Reported ◽  
Ceiling Effects ◽  
Health Domains ◽  
Measurement Information System

Background: The Patient-Reported Outcome Measurement Information System (PROMIS) was developed to improve patient-reported outcome measures (PROMs) and administration through a computer adaptive test (CAT). The PROMIS physical function-CAT (PF-CAT) has not been investigated in patients with patellofemoral instability (PFI). Purpose/Hypothesis: The purpose of this study was to evaluate the construct validity of the PROMIS PF-CAT with previously validated tools for measuring PROMs in patients with a diagnosis of PFI. We hypothesized that the PF-CAT will have the strongest correlations with other PROMs that evaluated PF as well as moderate correlations with PROMs that measured other health domains. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: Patients enrolled in this study who underwent operative intervention for PFI completed the following evaluations preoperatively: PROMIS PF-CAT, 36-Item Short Form Health Survey (SF-36), Knee injury and Osteoarthritis Outcome Score (KOOS), EuroQol-5 dimensions (EQ-5D), and Kujala Anterior Knee Pain Scale (AKPS). Correlation coefficients and the percentage of patients achieving the highest and lowest possible outcome score of each instrument were calculated to assess floor and ceiling effects. Statistical significance was defined as P < .05. Results: In total, 91 participants (63.7% females; mean age, 20.1 ± 7.2 years) completed the questionnaires. PF-CAT had the lowest number of questions (4.3 ± 1.1). The strongest correlations were between the PF-CAT and SF-36 PF subscale ( r = 0.78; P < .01), AKPS ( r = 0.68; P < .01), and KOOS Activities of Daily Living subscale ( r = 0.68; P < .01). Correlation was moderate between the PF-CAT and the KOOS subscales of Sports/Recreation ( r = 0.58; P < .01), Quality of Life ( r = 0.53; P < .01), and Symptoms ( r = 0.47; P < .01). The PROMIS PF-CAT demonstrated no floor or ceiling effects. Conclusion: In patients with PFI, construct validity of the PROMIS PF-CAT was supported by strong correlations demonstrated between the PF-CAT and PROMs evaluating PF and moderate correlations with those assessing other health domains. Our results demonstrated a low respondent burden and no floor or ceiling effects associated with the PROMIS PF-CAT. The PROMIS PF-CAT may be considered a beneficial alternative to previously established PF PROMs for preoperative evaluation of patients with PFI.

Are Health States “Timeless”? The Case of the Standard Gamble Method

1999 ◽  
Vol 52 (11) ◽  
pp. 1047-1053 ◽  
Author(s):  
Mohan V. Bala ◽  
Lisa L. Wood ◽  
Gary A. Zarkin ◽  
Edward C. Norton ◽  
Amiram Gafni ◽  
...  
Keyword(s):  
Standard Gamble ◽  
Health States ◽  
Standard Gamble Method

Defying Tradition

2017 ◽  
Vol 26 (1) ◽  
pp. 22-30 ◽  
Author(s):  
Leena Anand ◽  
Steve N. Du Bois ◽  
Tamara G. Sher ◽  
Karolina Grotkowski
Keyword(s):  
Gender Role ◽  
Online Survey ◽  
Measurement Information ◽  
Long Distance ◽  
Gender Role Socialization ◽  
Health Indices ◽  
Role Socialization ◽  
Patient Reported ◽  
N 93 ◽  
Amazon's Mechanical Turk

The marriage–health association has been investigated extensively among proximal couples (i.e., those living geographically near each other). On average, married men trend toward better health and relationship outcomes from their marital status compared to married women. This may be attributed to gender role socialization that encourages women to adopt a caretaking role toward their partners. Current literature has not addressed whether there are differential relationship or health outcomes by gender within long-distance relationship (LDR). The present study investigated LDR relationship and health indices by gender. Using Qualtrics and Amazon’s Mechanical Turk, married LDR participants ( n = 93, 21 years or older, English speakers) completed an online survey. Relationship measures assessed satisfaction, maintenance, stress, and sex. Health variables included the Patient Reported Outcomes Measurement Information System-29, Perceived Stress Scale, and surveys examining substance use, diet, and exercise. t Tests were used to measure group differences by gender. Women in LDR reported few relationship and health benefits relative to men in LDR. Men reported higher levels of relational distress and increased smoking, yet better physical functioning. Men also trended toward higher levels of relational maintenance and healthier eating as a function of partner presence. This study provides counterevidence for the gender role socialization model within the LDR framework.

scholarly journals Patient Reported Outcomes Measurements Information System in Stroke Patients in Full and Shortened Format

2021 ◽  
Vol 11 ◽  
Author(s):  
Charlotte Lens ◽  
Jelle Demeestere ◽  
Kris Vanhaecht ◽  
Robin Lemmens
Keyword(s):  
Information System ◽  
Physical Function ◽  
Patient Reported Outcomes ◽  
Social Roles ◽  
Measurement Information ◽  
Stroke Patients ◽  
Patient Reported ◽  
Health Domains ◽  
Measurement Information System ◽  
Single Question

Introduction: The modified Rankin Scale (mRS) after 90 days documents outcome in stroke patients, but focusses only on activities of daily living. Here we studied stroke outcome beyond these activities by the Dutch-Flemish version of the Patient Reported Outcomes Measurement Information System (PROMIS) questionnaire.Patients and Methods: We documented the mRS at day 90 in stroke patients who filled out a questionnaire on pain intensity and seven PROMIS domains: physical function, ability to participate in social roles, anxiety, fatigue, depression, sleep disturbance, pain interference. In a subgroup of patients this questionnaire was reduced to one overall question per PROMIS domain. We correlated these findings with the mRS.Results: We received 102 questionnaires and identified physical function as the most affected PROMIS domain. The strongest correlation with mRS was found for the health domains of physical function (ρs = 0.70, p &lt; 0.001) and ability to participate in social roles (ρs = 0.61, p &lt; 0.001). The other domains with substantial proportions of patients with worse scores compared to the general population (19–44%) correlated weakly with the mRS. We identified a strong correlation between the single question per health domain and the overall score per PROMIS domain.Discussion and Conclusion: PROMIS better reflects the overall health status of stroke patients beyond functional outcome as measured by the mRS. Simplification of the questionnaire with a single question per PROMIS domain could potentially replace the full questionnaire, but needs further validation.

scholarly journals Barriers to treatment optimization and achievement of patients’ goals: perspectives from people living with rheumatoid arthritis enrolled in the ArthritisPower registry

2020 ◽  
Vol 22 (1) ◽  
Author(s):  
Kelly Gavigan ◽  
W. Benjamin Nowell ◽  
Mylene S. Serna ◽  
Jeffrey L. Stark ◽  
Mohamed Yassine ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Disease Activity ◽  
Online Survey ◽  
Treatment Decisions ◽  
Treat To Target ◽  
Measurement Information ◽  
Treatment Goals ◽  
Barriers To Treatment ◽  
Treatment Optimization ◽  
Patient Reported

Abstract Background Few studies have investigated patients’ own treatment goals in rheumatoid arthritis (RA). The objective of this real-world, cross-sectional study of US patients with RA was to identify factors that patients believed influenced their physician’s treatment decisions. Secondary objectives included reasons patients tolerated sub-optimal disease control and their perceived barriers to treatment optimization. Methods Eligible participants were enrolled in the ArthritisPower registry, ≥ 19 years, had physician-diagnosed RA, unchanged treatment within 3 months of baseline, prior/current disease-modifying antirheumatic drug treatment (DMARDs), and computer/smartphone access. In December 2017, participants completed Patient-Reported Outcomes Measurement Information System-Computerized Adaptive Tests (PROMIS-CAT) for pain interference, fatigue, sleep disturbance, and physical function. Routine Assessment of Patient Index Data 3 (RAPID3) provided disease activity scores (0–30). Participants completed an online survey on barriers to treatment optimization, including self-perception of disease compared to RAPID3/PROMIS scores. Results A total of 249 participants met inclusion criteria and completed the survey. Mean age (SD) was 52 (11) years, and the majority were female (92%) with high RAPID3 disease activity (175/249 [70%]; median score 18). The main reason participants did not change treatment was their physician’s recommendation (66%; n = 32). Of participants with high RAPID3 disease activity, 66 (38%) were offered a treatment change; 19 (29%) of whom declined the change. Most participants who intensified treatment did so because their symptoms had remained severe or worsened (51%; n = 33); only 16 (25%) participants intensified because they had not reached a specified treatment goal. Among participants who self-reported their disease activity as “none/low” or “medium” (n = 202; 81% of cohort), most still had RAPID3 high disease activity (137/202 [68%]; score > 12). Most PROMIS scores showed moderate agreement with participants’ self-assessment of health status, in contrast to RAPID3 (weighted kappa: 0.05 [95% CI − 0.01, 0.11]). Conclusions Most participants trusted their rheumatologist’s treatment decisions and prioritized their physician’s treatment goals over their own. Patients should be encouraged to share their treatment goals/expectations with their rheumatologist, in line with the treat-to-target approach. RAPID3 may be inappropriate for setting patient-centric treatment goals given the poor agreement with self-reported disease activity; most PROMIS scores showed better alignment with patients’ own assessments.

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