scholarly journals Optimizing Health Information Technologies for Symptom Management in Cancer Patients and Survivors: Usability Evaluation (Preprint)

2020 ◽  
Author(s):  
Emily G Lattie ◽  
Michael Bass ◽  
Sofia F Garcia ◽  
Siobhan M Phillips ◽  
Patricia I Moreno ◽  
...  

BACKGROUND Unmanaged cancer symptoms and treatment-related side effects can compromise long-term clinical outcomes and health-related quality of life. Health information technologies such as web-based platforms offer the possibility to supplement existing care and optimize symptom management. OBJECTIVE This paper describes the development and usability of a web-based symptom management platform for cancer patients and survivors that will be implemented within a large health system. METHODS A web-based symptom management platform was designed and evaluated via one-on-one usability testing sessions. The System Usability Scale (SUS), After Scenario Questionnaire (ASQ), and qualitative analysis of semistructured interviews were used to assess program usability. RESULTS Ten cancer survivors and five cancer center staff members participated in usability testing sessions. The mean score on the SUS was 86.6 (SD 14.0), indicating above average usability. The mean score on the ASQ was 2.5 (SD 2.1), indicating relatively high satisfaction with the usability of the program. Qualitative analyses identified valued features of the program and recommendations for further improvements. CONCLUSIONS Cancer survivors and oncology care providers reported high levels of acceptability and usability in the initial development of a web-based symptom management platform for cancer survivors. Future work will test the effectiveness of this web-based platform.

10.2196/18412 ◽  
2020 ◽  
Vol 4 (9) ◽  
pp. e18412
Author(s):  
Emily G Lattie ◽  
Michael Bass ◽  
Sofia F Garcia ◽  
Siobhan M Phillips ◽  
Patricia I Moreno ◽  
...  

Background Unmanaged cancer symptoms and treatment-related side effects can compromise long-term clinical outcomes and health-related quality of life. Health information technologies such as web-based platforms offer the possibility to supplement existing care and optimize symptom management. Objective This paper describes the development and usability of a web-based symptom management platform for cancer patients and survivors that will be implemented within a large health system. Methods A web-based symptom management platform was designed and evaluated via one-on-one usability testing sessions. The System Usability Scale (SUS), After Scenario Questionnaire (ASQ), and qualitative analysis of semistructured interviews were used to assess program usability. Results Ten cancer survivors and five cancer center staff members participated in usability testing sessions. The mean score on the SUS was 86.6 (SD 14.0), indicating above average usability. The mean score on the ASQ was 2.5 (SD 2.1), indicating relatively high satisfaction with the usability of the program. Qualitative analyses identified valued features of the program and recommendations for further improvements. Conclusions Cancer survivors and oncology care providers reported high levels of acceptability and usability in the initial development of a web-based symptom management platform for cancer survivors. Future work will test the effectiveness of this web-based platform.


Author(s):  
Amanda Recker ◽  
Jamie Pina ◽  
Barbara L. Massoudi

Usability testing is most often performed after product development has essentially ended and may result in a few slight changes to the system before it is finalized. As such, long-term usability testing is generally not possible even though the results would track user satisfaction through product design iterations. The BioSense 2.0 redesign team, through a contract with the U.S. Centers for Disease Control and Prevention, has conducted long-term usability testing of the BioSense 2.0 syndromic surveillance Web-based application. The results have affected the design of BioSense 2.0 and revealed interesting trends.


2016 ◽  
Author(s):  
Ning Zhang ◽  
Susan Feng Lu ◽  
Biao Xu ◽  
Bingxiao Wu ◽  
Rosa Rodriguez-Monguio ◽  
...  

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