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WATERTOWN, MA, JUNE 1, 2016 – JWRG’s multi-year effort to broaden the content of disease-specific health-related quality of life (QOL) measurement with a briefer scale standardized and  scored  in relation to norms for the chronically ill US population has been documented in an article about the Quality of life Disease Impact Scale (QDIS®), published in Health and Quality of Life Outcomes. QDIS is a suite of disease-specific measures, including a 25-item bank which can be used in computerized adaptive testing, a 7-item fixed-length short form and a global QOL item, each of which estimates a summary QOL disease impact score. The content of QDIS questions is standardized across conditions, but questions vary in their disease-specific attribution. For example, a QDIS question for chronic kidney disease might ask “How much did your kidney disease limit your everyday activities or your quality of life?”, while the same question also might be asked with attribution to asthma. Scores on both the kidney disease impact and asthma impact measures are interpreted in relation to general population norms. By standardizing the content and scoring of disease-specific measures across conditions, QDIS provides a new approach to measurement, one that combines the precision and discrimination of disease-specific measures with the comprehensiveness and standardization of generic QOL measures which are not specific to any disease or treatment. Crucial assumptions underlying the QDIS approach were evaluated favorably in the Health and Quality of Life Outcomes article, which documents the development of QDIS and Internet administration of QDIS items with attribution […]

WORCESTER, MA, January 8, 2016 — Researchers at UMass Medical School and JWRG have published results that open up a new pathway to disease-specific quality of life (QOL) impact measurement, as reported in a special issue of International Journal of Statistics in Medical Research (IJSMR) on methods for estimating treatment effects for persons with multiple chronic conditions (MCC). This study, sponsored by the Agency for Healthcare Research and Quality (AHRQ), evaluated alternative approaches to measuring disease-specific impact across people who reported MCC. Results demonstrated the feasibility of JWRG’s new approach to individualized disease impact measurement  The QOL Disease-specific Impact Scale (QDIS®), which standardizes content and scoring across diseases, is central to JWRG’s new measurement approach. Previous research has shown that calculating a single QDIS impact score across multiple QOL content areas was justified, that standardization of QDIS content and scoring across diseases was psychometrically sound, and that QDIS administration was practical (10-15 seconds per patient per disease). The following question remained: are QOL impact attributions to a specific disease valid in the presence of multiple chronic conditions?   Although disease attribution often is addressed in single-disease studies, this question has rarely been examined in the presence of MCC. In the IJSMR study, the validity of responses to multiple disease-specific measures (symptoms, severity ratings, QDIS ratings) was tested in 4,480 US adults, all of whom were known to have a pre-identified condition. Respondents also provided information on disease severity and QDIS disease impact for every comorbid condition (out of 35) they […]

WORCESTER, MA, August 10, 2015 – Results from an article published in Health and Quality of Life Outcomes link a new smoking-specific quality of life measure based on JWRG’s QOL Disease Impact Scale (QDIS®) to smoking behavior and to smoking-specific symptoms. This article presented data from two independent studies: a German trial and a US general population survey. Like many others, these studies both focused on young and otherwise healthy current and former adult smokers. Both studies found that the QDIS smoking impact scale had stronger associations than the generic SF-36® Health Survey with smoking status (current versus former) and the number of cigarettes smoked per day. In the German trial, which also included laboratory test results, the QDIS smoking impact measure also correlated substantially and significantly higher than the SF-36 with four clinical biomarkers of tobacco exposure and impact. These and other results showed that the German- and English-language QDIS smoking impact scale and other measures in JWRG’s Tobacco QOL Impact Test (TQOLITv1™) have comparable and satisfactory psychometric properties for use in smoking outcomes research, including studies of otherwise healthy smokers. Additional information about the German trial design and results were published in Nicotine & Tobacco Research. JWRG gratefully acknowledges unrestricted research grant support from British American Tobacco, Group Research & Development, to evaluate the psychometric properties of TQOLITv1 measures among current and former smokers.

WORCESTER, MA, April 27, 2015 – A new quality of life instrument, the Tobacco Quality of Life Impact Tool (TQOLIT™), developed by the John Ware Research Group, was proven to be useful in a 6-month clinical trial of the effects of switching smokers to a reduced toxicant prototype cigarette. Like many smoking studies, this trial focused on young and otherwise healthy adult current and former smokers for whom reliable measurement throughout the range of functional health and well-being is critical.  The results were recently published in Nicotine & Tobacco Research. Measuring the health-related quality of life (HRQOL) of young and middle-aged smokers is challenging because many of the impacts of smoking are not apparent for decades. In addition, prior to QDIS there was no brief HRQOL scale that measured the impact of smoking on physical, emotional and social aspects of life. TQOLIT integrates several JWRG advances in patient-reported outcomes (PRO) measurement to address these challenges. First, TQOLIT includes a short 7-item scale that measures the impact of smoking on quality of life. The TQOLIT smoking impact measure is a smoking-specific version of JWRG’s QOL Disease Impact Scale (QDIS®), which is a comprehensive disease-specific PRO measure that is standardized across 35 chronic conditions. For TQOLIT, QDIS was adapted to ask about limitations in HRQOL specifically attributed to smoking. For example, one question asks how often smoking limited everyday activities over the past four weeks, while another question asks how often smoking led to worrying about health now or in the future. […]

WORCESTER, MA, February 10, 2015 – A national registry recently conducted a field test to collect patient-reported outcomes (PRO) data using a new method.  Patients logged on from home or the clinic to complete the survey, as is typical for web-based assessments, before and after total joint replacement (TJR).  The difference was in what happened next.  The survey used the Quality of Life (QOL) Information System (QOLIX®) which uses a powerful new adaptive survey logic (ASLX®) to automatically adapt to the presence of multiple comorbid conditions while also estimating outcomes with metrics equivalent to those underlying widely-used legacy PROs.  Although each of the major elements of QOLIX, including standardized disease-specific (QDIS®) and generic (QGEN®) modules, and the power of ASLX had been evaluated successfully in real data simulations, this was the first real-world test of the entire system in an ongoing PRO registry.  Despite collecting more comprehensive and more individualized information, QOLIX surveys were faster in the TJR field test for most patients in comparison with state-of-the-art PRO surveys that were administered in parallel. The Function and Outcomes Research for Comparative Effectiveness in TJR (FORCE-TJR) registry is sponsored by AHRQ and led by a team of researchers at UMass Medical School in cooperation with a national network of surgeons.  FORCE-TJR goes beyond traditional approaches to comparative effectiveness research (CER) that are based on retrospective analyses of rates of implant failure or revision.  The FORCE-TJR model is patient-centered, more comprehensive, and integrates population-based sampling and prospective monitoring of functional health and […]