PURPOSE: Patients with breast cancer spend a large amount of time and effort receiving treatment. When the number of health care tasks exceeds a patient's ability to manage that workload, they could become overburdened, leading to decreased plan adherence. We used electronic health record data to retrospectively assess dimensions of treatment workload related to outpatient encounters, commuting, and admissions. METHODS: Using tumor registry and scheduling data, we evaluated the sensitivity of treatment workload measures to detect expected differences in breast cancer treatment burden by stage. We evaluated the impact of the on-body pegfilgrastim injector on the treatment workload of patients undergoing a specific chemotherapy protocol. RESULTS: As hypothesized, patients with higher stage cancer experienced higher treatment workload. Over the first 18 months after diagnosis, patients with stage III disease spent a median of 81 hours (interquartile range [IQR], 39 to 113 hours) in outpatient clinics, commuted 61 hours (IQR, 32 to 86 hours), and spent $1,432 (IQR, $690 to $2,552) in commuting costs. In contrast, patients with stage I disease spent a median of 29 hours (IQR, 18 to 46 hours in clinic), commuted for 34 hours (IQR, 19 to 55 hours), and spent $834 (IQR, $389 to $1,649) in commuting costs. In addition, we substantiated claims that the pegfilgrastim on-body injector was effective in reducing some dimensions of workload such as unique appointment days. CONCLUSION: Treatment workload measures capture an important dimension in the experience of patients with cancer. Patients and health care organizations can use workload measures to plan and allocate resources, leading to higher quality and better coordinated care.
PURPOSE:Patients with breast cancer spend a large amount of time and effort receiving treatment. When the number of health care tasks exceeds a patient's ability to manage that workload, they could become overburdened, leading to decreased plan adherence. We used electronic health record data to retrospectively assess dimensions of treatment workload related to outpatient encounters, commuting, and admissions. METHODS: Using tumor registry and scheduling data, we evaluated the sensitivity of treatment workload measures to detect expected differences in breast cancer treatment burden by stage. We evaluated the impact of the on-body pegfilgrastim injector on the treatment workload of patients undergoing a specific chemotherapy protocol. RESULTS: As hypothesized, patients with higher stage cancer experienced higher treatment workload. Over the first 18 months after diagnosis, patients with stage III disease spent a median of 81 hours (interquartile range [IQR], 39 to 113 hours) in outpatient clinics, commuted 61 hours (IQR, 32 to 86 hours), and spent $1,432 (IQR, $690 to $2,552) in commuting costs. In contrast, patients with stage I disease spent a median of 29 hours (IQR, 18 to 46 hours in clinic), commuted for 34 hours (IQR, 19 to 55 hours), and spent $834 (IQR, $389 to $1,649) in commuting costs. In addition, we substantiated claims that the pegfilgrastim on-body injector was effective in reducing some dimensions of workload such as unique appointment days. CONCLUSION: Treatment workload measures capture an important dimension in the experience of patients with cancer. Patients and health care organizations can use workload measures to plan and allocate resources, leading to higher quality and better coordinated care.
Authors: Marc L Citron; Donald A Berry; Constance Cirrincione; Clifford Hudis; Eric P Winer; William J Gradishar; Nancy E Davidson; Silvana Martino; Robert Livingston; James N Ingle; Edith A Perez; John Carpenter; David Hurd; James F Holland; Barbara L Smith; Carolyn I Sartor; Eleanor H Leung; Jeffrey Abrams; Richard L Schilsky; Hyman B Muss; Larry Norton Journal: J Clin Oncol Date: 2003-02-13 Impact factor: 44.544
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Authors: Marc A Emerson; Yvonne M Golightly; Allison E Aiello; Katherine E Reeder-Hayes; Xianming Tan; Ugwuji Maduekwe; Marian Johnson-Thompson; Andrew F Olshan; Melissa A Troester Journal: Cancer Date: 2020-09-21 Impact factor: 6.860
Authors: Marc A Emerson; Katherine E Reeder-Hayes; Heather J Tipaldos; Mary E Bell; Marina R Sweeney; Lisa A Carey; H Shelton Earp; Andrew F Olshan; Melissa A Troester Journal: Curr Breast Cancer Rep Date: 2020-05-14