Presentation
DH16 - Workflow Mapping to Understand Breast Cancer Patient Journeys
DescriptionBreast cancer is the most common cancer diagnosis and the second-leading cause of cancer-related death in women (1). Following a breast cancer diagnosis, patients and their loved ones are faced with many challenging decisions, including which treatment(s) to undergo and how to manage work and daily demands (e.g., childcare) to accommodate treatment (2). Increasingly, technologies, such as clinical decision support, are being adopted as a means to assist medical teams with complex, high stakes health decisions (3). These technologies could be helpful for breast cancer patient decision making and care management. In this study, we aimed to understand how breast cancer patients and their care teams approach their care decisions as a first step in developing technologies that will support the treatment decision-making process.
To understand the diverse decision-making processes and experiences of breast cancer patients, we conducted 20 observations of diverse roles (e.g., medical oncology, surgical oncology) at one academic medical center. One researcher followed a clinician throughout their shift and took structured observation notes using an iPad and smart pencil. The observation form was structured according to the work system model (4). All observation notes were transcribed and uploaded into qualitative data analysis software, Dedoose. In a consensus-based process, two researchers inductively coded each observation, identifying instances of patient-clinician interaction (5). All excerpts coded as “patient-clinician interaction” were exported from Dedoose. We created one workflow diagram for each patient interaction, starting with a sub-set of patient interactions with the medical oncologist. Each workflow diagram visually represented the people involved, information shared, tools and technologies used, key decision points discussed, and next steps for the patient. Once all the workflow diagrams were created, we compared the decision-making workflows across all patients.
The observations lasted a total of 24 hours, and we observed 36 patient interactions with medical oncologists that were developed into workflow diagrams. These diagrams helped to visually display the patient and care team’s decision-making process to allow for easier understanding of the process and comparison across patients. We uncovered a diverse range of decision-making processes for the 36 patients, who had various cancer sub-types (e.g., triple negative) and stages (e.g., stage 1-4). We found that patients make numerous complex decisions relating to various aspects of treatment. Largely, the variance seen across patients related to their backgrounds and decision factors (e.g., hobbies, work demands). Despite differences in the decision factors themselves, these widely represented the same content—including occupational considerations, family history and composition, and lifestyle preferences. Additionally, similar types of key information were required for effective decision-making across all types of patients, including family history and detailed patient histories. There were also many similarities in the individuals involved in the decision-making process across patients, usually including a medical, surgical, and radiation oncologist and a family member providing support (oftentimes a spouse, parent, or adult child). Based on these findings, there is potential for the development of a comprehensive decision support system for breast cancer patients, physicians, and family caregivers.
1. American Cancer Society, Breast cancer factors & figures 2022-2024. 2022: Atlanta, Georgia.
2. Mazzocco, K., Masiero, M., Carriero, M. C., & Pravettoni, G. (2019). The role of emotions in cancer patients' decision-making. Ecancermedicalscience, 13, 914. https://doi.org/10.3332/ecancer.2019.914
3. Reyna, V. F., Nelson, W. L., Han, P. K., & Pignone, M. P. (2015). Decision making and cancer. The American psychologist, 70(2), 105–118. https://doi.org/10.1037/a0036834
4. Smith MJ, Carayon-Sainfort P. A balance theory of job design for stress reduction. Int J Ind Ergon. 1989;4(1):67-79.
5. Elo S, Kyngäs H. The qualitative content analysis process. J of Adv Nurs. 2008;62.
To understand the diverse decision-making processes and experiences of breast cancer patients, we conducted 20 observations of diverse roles (e.g., medical oncology, surgical oncology) at one academic medical center. One researcher followed a clinician throughout their shift and took structured observation notes using an iPad and smart pencil. The observation form was structured according to the work system model (4). All observation notes were transcribed and uploaded into qualitative data analysis software, Dedoose. In a consensus-based process, two researchers inductively coded each observation, identifying instances of patient-clinician interaction (5). All excerpts coded as “patient-clinician interaction” were exported from Dedoose. We created one workflow diagram for each patient interaction, starting with a sub-set of patient interactions with the medical oncologist. Each workflow diagram visually represented the people involved, information shared, tools and technologies used, key decision points discussed, and next steps for the patient. Once all the workflow diagrams were created, we compared the decision-making workflows across all patients.
The observations lasted a total of 24 hours, and we observed 36 patient interactions with medical oncologists that were developed into workflow diagrams. These diagrams helped to visually display the patient and care team’s decision-making process to allow for easier understanding of the process and comparison across patients. We uncovered a diverse range of decision-making processes for the 36 patients, who had various cancer sub-types (e.g., triple negative) and stages (e.g., stage 1-4). We found that patients make numerous complex decisions relating to various aspects of treatment. Largely, the variance seen across patients related to their backgrounds and decision factors (e.g., hobbies, work demands). Despite differences in the decision factors themselves, these widely represented the same content—including occupational considerations, family history and composition, and lifestyle preferences. Additionally, similar types of key information were required for effective decision-making across all types of patients, including family history and detailed patient histories. There were also many similarities in the individuals involved in the decision-making process across patients, usually including a medical, surgical, and radiation oncologist and a family member providing support (oftentimes a spouse, parent, or adult child). Based on these findings, there is potential for the development of a comprehensive decision support system for breast cancer patients, physicians, and family caregivers.
1. American Cancer Society, Breast cancer factors & figures 2022-2024. 2022: Atlanta, Georgia.
2. Mazzocco, K., Masiero, M., Carriero, M. C., & Pravettoni, G. (2019). The role of emotions in cancer patients' decision-making. Ecancermedicalscience, 13, 914. https://doi.org/10.3332/ecancer.2019.914
3. Reyna, V. F., Nelson, W. L., Han, P. K., & Pignone, M. P. (2015). Decision making and cancer. The American psychologist, 70(2), 105–118. https://doi.org/10.1037/a0036834
4. Smith MJ, Carayon-Sainfort P. A balance theory of job design for stress reduction. Int J Ind Ergon. 1989;4(1):67-79.
5. Elo S, Kyngäs H. The qualitative content analysis process. J of Adv Nurs. 2008;62.
Event Type
Poster Presentation
TimeMonday, March 254:45pm - 6:15pm CDT
LocationSalon C
Digital Health
Simulation and Education
Hospital Environments
Medical and Drug Delivery Devices
Patient Safety Research and Initiatives