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CC BY 4.0 · ACI open 2022; 06(02): e66-e75
DOI: 10.1055/s-0042-1751088
Original Article

Physicians' Perceptions and Expectations of an Artificial Intelligence-Based Clinical Decision Support System in Cancer Care in an Underserved Setting

Rubina F. Rizvi   *
1   IBM Watson Health, Cambridge, Massachusetts, United States
,
Srinivas Emani   *
2   Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States
3   Department of Behavioral, Social, and Health Education Sciences, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States
,
Hermano A. Lima Rocha
4   Department of Community Health, Federal University of Ceará, Fortaleza, Ceará, Brazil
,
Camila Machado de Aquino
5   Department of Maternal and Child Health, Faculty of Medicine, Federal University of Ceará, Fortaleza, Ceará, Brazil
,
Pamela M. Garabedian
6   Clinical and Quality Analysis, Partners HealthCare, Somerville, Massachusetts, United States
,
Angela Rui
6   Clinical and Quality Analysis, Partners HealthCare, Somerville, Massachusetts, United States
,
Carlos André Moura Arruda
5   Department of Maternal and Child Health, Faculty of Medicine, Federal University of Ceará, Fortaleza, Ceará, Brazil
,
Megan Sands-Lincoln
1   IBM Watson Health, Cambridge, Massachusetts, United States
,
Ronen Rozenblum
2   Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States
,
Winnie Felix
1   IBM Watson Health, Cambridge, Massachusetts, United States
,
Gretchen P. Jackson
7   Departments of Surgery, Pediatrics, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
,
Sérgio F. Juacaba
8   Departments of Surgery, Cancer Institute of Ceara, Fortaleza, Ceará, Brazil
,
David W. Bates
2   Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States
› Author Affiliations Funding This work has been supported by IBM Watson Health (Cambridge, MA, United States), which is not responsible for the content or recommendations made.
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Abstract

Objectives Artificial intelligence (AI) tools are being increasingly incorporated into health care. However, few studies have evaluated users' expectations of such tools, prior to implementation, specifically in an underserved setting.

Methods We conducted a qualitative research study employing semistructured interviews of physicians at The Instituto do Câncer do Ceará, Fortaleza, Brazil. The interview guide focused on anticipated, perceived benefits and challenges of using an AI-based clinical decision support system tool, Watson for Oncology. We recruited physician oncologists, working full or part-time, without prior experience with any AI-based tool. The interviews were taped and transcribed in Portuguese and then translated into English. Thematic analysis using the constant comparative approach was performed.

Results Eleven oncologists participated in the study. The following overarching themes and subthemes emerged from the analysis of interview transcripts: theme-1, “general context” including (1) current setting, workload, and patient population and (2) existing challenges in cancer treatment, and theme-2, “perceptions around the potential use of an AI-based tool,” including (1) perceived benefits and (2) perceived challenges. Physicians expected that the implementation of an AI-based tool would result in easy access to the latest clinical recommendations, facilitate standardized cancer care, and allow it to be delivered with greater confidence and efficiency. Participants had several concerns such as availability of innovative treatments in resource-poor settings, treatment acceptance, trust, physician autonomy, and workflow disruptions.

Conclusion This study provides physicians' anticipated perspectives, both benefits and challenges, about the use of an AI-based tool in cancer treatment in a resource-limited setting.

Keywords

clinical decision support - artificial intelligence - oncology - treatment - physicians - underserved setting - implementation - perceptions

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed and approved by the ICC Review Board.


* Equal contributor first authors.


Supplementary Material



Publication History

Received: 25 January 2022

Accepted: 23 May 2022

Article published online:
30 July 2022

© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

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