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Dive into the research topics where Michael Bass is active.

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Featured researches published by Michael Bass.


Cancer | 2015

Bringing PROMIS to practice: Brief and precise symptom screening in ambulatory cancer care

Lynne I. Wagner; Julian C. Schink; Michael Bass; Shalini Patel; Maria Varela Diaz; Nan Rothrock; Timothy Pearman; Richard Gershon; Frank J. Penedo; Steven T. Rosen; David Cella

Supportive oncology practice can be enhanced by the integration of a brief and validated electronic patient‐reported outcome assessment into the electronic health record (EHR) and clinical workflow.


Journal of the American Medical Informatics Association | 2017

Advancing the efficiency and efficacy of patient reported outcomes with multivariate computer adaptive testing

Scott B. Morris; Michael Bass; Mirinae Lee; Richard E. Neapolitan

Objective The Patient Reported Outcomes Measurement Information System (PROMIS) initiative developed an array of patient reported outcome (PRO) measures. To reduce the number of questions administered, PROMIS utilizes unidimensional item response theory and unidimensional computer adaptive testing (UCAT), which means a separate set of questions is administered for each measured trait. Multidimensional item response theory (MIRT) and multidimensional computer adaptive testing (MCAT) simultaneously assess correlated traits. The objective was to investigate the extent to which MCAT reduces patient burden relative to UCAT in the case of PROs. Methods One MIRT and 3 unidimensional item response theory models were developed using the related traits anxiety, depression, and anger. Using these models, MCAT and UCAT performance was compared with simulated individuals. Results Surprisingly, the root mean squared error for both methods increased with the number of items. These results were driven by large errors for individuals with low trait levels. A second analysis focused on individuals aligned with item content. For these individuals, both MCAT and UCAT accuracies improved with additional items. Furthermore, MCAT reduced the test length by 50%. Discussion For the PROMIS Emotional Distress banks, neither UCAT nor MCAT provided accurate estimates for individuals at low trait levels. Because the items in these banks were designed to detect clinical levels of distress, there is little information for individuals with low trait values. However, trait estimates for individuals targeted by the banks were accurate and MCAT asked substantially fewer questions. Conclusion By reducing the number of items administered, MCAT can allow clinicians and researchers to assess a wider range of PROs with less patient burden.


JMIR medical informatics | 2018

Development of an eHealth System to Capture and Analyze Patient Sensor and Self-Report Data: Mixed-Methods Assessment of Potential Applications to Improve Cancer Care Delivery

Alexander R Lucas; Michael Bass; Nan Rothrock; Mary L O'Connor; Mia R Sorkin; Jason Nawyn; Fahd Albinali; Lynne I. Wagner

Background Capturing and Analyzing Sensor and Self-Report Data for Clinicians and Researchers (COMPASS) is an electronic health (eHealth) platform designed to improve cancer care delivery through passive monitoring of patients’ health status and delivering customizable reports to clinicians. Based on data from sensors and context-driven administration of patient-reported outcome (PRO) measures, key indices of patients’ functional status can be collected between regular clinic visits, supporting clinicians in the delivery of patient care. Objective The first phase of this project aimed to systematically collect input from oncology providers and patients on potential clinical applications for COMPASS to refine the system. Methods Ten clinicians representing various oncology specialties and disciplines completed semi-structured interviews designed to solicit clinician input on how COMPASS can best support clinical care delivery. Three cancer patients tested a prototype of COMPASS for 7 days and provided feedback. Interview data were tabulated using thematic content analysis to identify the most clinically relevant objective and PRO domains. Results Thematic content analysis revealed that clinicians were most interested in monitoring vital statistics, symptoms, and functional status, including the physical activity level (n=9), weight (n=5), fatigue (n=9), sleep quality (n=8), and anxiety (n=7). Patients (2 in active treatment and 1 in remission) reported that they would use such a device, were enthusiastic about their clinicians monitoring their health status, especially the tracking of symptoms, and felt knowing their clinicians were monitoring and reviewing their health status provided valuable reassurance. Patients would, however, like to provide some context to their data. Conclusions Clinicians and patients both articulated potential benefits of the COMPASS system in improving cancer care. From a clinician standpoint, data need to be easily interpretable and actionable. The fact that patients and clinicians both see potential value in eHealth systems suggests wider adoption and utilization could prove to be a useful tool for improving care delivery.


Journal of applied measurement | 2010

The use of PROMIS and assessment center to deliver Patient-Reported Outcome Measures in clinical research

Richard Gershon; Nan Rothrock; Rachel T. Hanrahan; Michael Bass; David Cella


Journal of Pain and Symptom Management | 2014

A randomized trial of weekly symptom telemonitoring in advanced lung cancer.

Susan Yount; Nan Rothrock; Michael Bass; Jennifer L. Beaumont; Deborah Pach; Thomas E. Lad; Jyoti D. Patel; Maria E. Corona; Rebecca Weiland; Katherine Del Ciello; David Cella


The journal of supportive oncology | 2007

An Innovative Symptom Monitoring Tool for People With Advanced Lung Cancer: A Pilot Demonstration

Kimberly M. Davis; Susan Yount; Katie Del Ciello; Margaret Whalen; Shaheen Khan; Michael Bass; Hongyan Du; David T. Eton; Gregory A. Masters; Thomas A. Hensing; David Cella


The journal of supportive oncology | 2013

Monitoring of health-related quality of life and symptoms in prostate cancer survivors: a randomized trial.

Kimberly M. Davis; David L. Dawson; Scott Kelly; Sara Red; Sofiya Penek; John H. Lynch; Sean P. Collins; Barlow Lynch; Michael Porrazzo; Michael Bass; Kathryn L. Taylor


american medical informatics association annual symposium | 2015

Utilizing Multidimensional Computer Adaptive Testing to Mitigate Burden With Patient Reported Outcomes

Michael Bass; Scott B. Morris; Richard E. Neapolitan


Lung Cancer | 2003

P-691 Computer technology as a platform for weekly symptom monitoring of patients with advanced lung cancer

Kimberly Davis; David Cella; Susan Yount; Shaheen Khan; Michael Bass; David T. Eton; Katherine Reynolds; Chih Hung Chang; Gregory A. Masters


wearable and implantable body sensor networks | 2018

Measuring fine-grained heart-rate using a flexible wearable sensor in the presence of noise

Lida Zhang; Zachary King; Begum Egilmez; Jonathan T. Reeder; Roozbeh Ghaffari; John A. Rogers; Kristen Rosen; Michael Bass; Judith Tedlie Moskowitz; Darius Tandon; Lauren S. Wakschlag; Nabil Alshurafa

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David Cella

Northwestern University

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Nan Rothrock

Northwestern University

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Susan Yount

Northwestern University

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Gregory A. Masters

Christiana Care Health System

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Shaheen Khan

Northwestern University

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Kimberly Davis

University of South Florida

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