Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing

• Published in: BMC Medical Informatics and Decision Making
• Main Authors: Mary E. Cooley, Janet L. Abrahm, Donna L. Berry, Michael S. Rabin, Ilana M. Braun, Joanna Paladino, Manan M. Nayak, David F. Lobach
• Format: Article in Journal/Newspaper
• Language: English
• Published: BMC 2018
• Subjects: Rule-based clinical decision support; Symptom management; Patient engagement; Patient self-management; Cancer; Computer applications to medicine. Medical informatics; R858-859.7; sami
• Online Access: https://doi.org/10.1186/s12911-018-0608-8; https://doaj.org/article/e4485bbd05f24700a3a913856a62a211

Abstract Background It is essential that cancer patients understand anticipated symptoms, how to self-manage these symptoms, and when to call their clinicians. However, patients are often ill-prepared to manage symptoms at home. Clinical decision support (CDS) is a potentially innovative way to provide information to patients where and when they need it. The purpose of this project was to design and evaluate a simulated model of an algorithm-based CDS program for self-management of cancer symptoms. Methods This study consisted of three phases; development of computable algorithms for self-management of cancer symptoms using a modified ADAPTE process, evaluation of a simulated model of the CDS program, and identification of design objectives and lessons learned from the evaluation of patient-centered CDS. In phase 1, algorithms for pain, constipation and nausea/vomiting were developed by an expert panel. In phase 2, we conducted usability testing of a simulated symptom assessment and management intervention for self-care (SAMI-Self-Care) CDS program involving focus groups, interviews and surveys with cancer patients, their caregivers and clinicians. The Acceptability E-scale measured acceptability of the program. In phase 3, we developed design objectives and identified barriers to uptake of patient-centered CDS based on the data gathered from stakeholders. Results In phase 1, algorithms were reviewed and approved through a consensus meeting and majority vote. In phase 2, 24 patients & caregivers and 13 clinicians participated in the formative evaluation. Iterative changes were made in a simulated SAMI-Self-Care CDS program. Acceptability scores were high among patients, caregivers and clinicians. In phase 3, we formulated CDS design objectives, which included: 1) ensure patient safety, 2) communicate clinical concepts effectively, 3) promote communication with clinicians, 4) support patient activation, and 5) facilitate navigation and use. We identified patient barriers and clinician concerns to using CDS ...