Jen Rogers1, Nicholas Spina2, Ashley Neese2, Rachel Hess3, Darrel Brodke2, Alexander Lex1. 1. Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, United States. 2. Department of Orthopedics, University of Utah, Salt Lake City, Utah, United States. 3. Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, United States.
Abstract
OBJECTIVE: Visual cohort analysis utilizing electronic health record data has become an important tool in clinical assessment of patient outcomes. In this article, we introduce Composer, a visual analysis tool for orthopedic surgeons to compare changes in physical functions of a patient cohort following various spinal procedures. The goal of our project is to help researchers analyze outcomes of procedures and facilitate informed decision-making about treatment options between patient and clinician. METHODS: In collaboration with orthopedic surgeons and researchers, we defined domain-specific user requirements to inform the design. We developed the tool in an iterative process with our collaborators to develop and refine functionality. With Composer, analysts can dynamically define a patient cohort using demographic information, clinical parameters, and events in patient medical histories and then analyze patient-reported outcome scores for the cohort over time, as well as compare it to other cohorts. Using Composer's current iteration, we provide a usage scenario for use of the tool in a clinical setting. CONCLUSION: We have developed a prototype cohort analysis tool to help clinicians assess patient treatment options by analyzing prior cases with similar characteristics. Although Composer was designed using patient data specific to orthopedic research, we believe the tool is generalizable to other healthcare domains. A long-term goal for Composer is to develop the application into a shared decision-making tool that allows translation of comparison and analysis from a clinician-facing interface into visual representations to communicate treatment options to patients. Georg Thieme Verlag KG Stuttgart · New York.
OBJECTIVE: Visual cohort analysis utilizing electronic health record data has become an important tool in clinical assessment of patient outcomes. In this article, we introduce Composer, a visual analysis tool for orthopedic surgeons to compare changes in physical functions of a patient cohort following various spinal procedures. The goal of our project is to help researchers analyze outcomes of procedures and facilitate informed decision-making about treatment options between patient and clinician. METHODS: In collaboration with orthopedic surgeons and researchers, we defined domain-specific user requirements to inform the design. We developed the tool in an iterative process with our collaborators to develop and refine functionality. With Composer, analysts can dynamically define a patient cohort using demographic information, clinical parameters, and events in patient medical histories and then analyze patient-reported outcome scores for the cohort over time, as well as compare it to other cohorts. Using Composer's current iteration, we provide a usage scenario for use of the tool in a clinical setting. CONCLUSION: We have developed a prototype cohort analysis tool to help clinicians assess patient treatment options by analyzing prior cases with similar characteristics. Although Composer was designed using patient data specific to orthopedic research, we believe the tool is generalizable to other healthcare domains. A long-term goal for Composer is to develop the application into a shared decision-making tool that allows translation of comparison and analysis from a clinician-facing interface into visual representations to communicate treatment options to patients. Georg Thieme Verlag KG Stuttgart · New York.
Authors: Blanca Gallego; Scott R Walter; Richard O Day; Adam G Dunn; Vijay Sivaraman; Nigam Shah; Christopher A Longhurst; Enrico Coiera Journal: J Comp Eff Res Date: 2015-05-11 Impact factor: 1.744
Authors: David Cella; William Riley; Arthur Stone; Nan Rothrock; Bryce Reeve; Susan Yount; Dagmar Amtmann; Rita Bode; Daniel Buysse; Seung Choi; Karon Cook; Robert Devellis; Darren DeWalt; James F Fries; Richard Gershon; Elizabeth A Hahn; Jin-Shei Lai; Paul Pilkonis; Dennis Revicki; Matthias Rose; Kevin Weinfurt; Ron Hays Journal: J Clin Epidemiol Date: 2010-08-04 Impact factor: 6.437
Authors: Darrel S Brodke; Vadim Goz; Maren W Voss; Brandon D Lawrence; William Ryan Spiker; Man Hung Journal: Spine (Phila Pa 1976) Date: 2017-06-15 Impact factor: 3.241
Authors: Carla Floricel; Nafiul Nipu; Mikayla Biggs; Andrew Wentzel; Guadalupe Canahuate; Lisanne Van Dijk; Abdallah Mohamed; C David Fuller; G Elisabeta Marai Journal: IEEE Trans Vis Comput Graph Date: 2021-12-24 Impact factor: 4.579
Authors: Michael Bass; Christian Oncken; Allison W McIntyre; Chris Dasilva; Joshua Spuhl; Nan E Rothrock Journal: Appl Clin Inform Date: 2021-10-20 Impact factor: 2.342