Using technology to improve patient-provider communication and delivery of quality care.

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 76-76
Author(s):  
Gabrielle Betty Rocque ◽  
Amanda Hathaway ◽  
Karina I. Halilova ◽  
Michele Gaguski ◽  
Kathryn A Thomas ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Shared Decision Making ◽  
Treatment Plan ◽  
Planning System ◽  
Site Quality ◽  
Cancer Center ◽  
Shared Decision ◽  
Breast Cancer Patients ◽  
Provider Education

76 Background: Shared decision making (SDM) is a cornerstone of patient-centered care with 85-90% of breast cancer (BC) patients preferring an active or shared role in decision-making for breast surgery. SDM has been shown to, improve patients’ understanding of treatment options, result in more conservative care choices, and lead to lower healthcare costs. However, implementation is complex as numerous misconceptions exist. Methods: We are conducting a multi-site, quality improvement (QI) project to improve SDM behaviors and adherence to quality measures through a combination of provider education and use of a novel technology platform, the Carevive Care Planning System. This platform elicits patient preferences, concerns, history, and symptoms, and presents these data with algorithm-driven recommendations as part of a treatment plan. We report results from baseline provider surveys assessing perception and knowledge of SDM. Results: Baseline surveys from 28 participants were analyzed; 43% from a university based cancer center and 57% from community based cancer centers. Survey respondents were MDs (43%), NPs (7%) and RNs (46%), all specializing in Hematology and/or Oncology. When asked, “What percentage of breast cancer patients prefers an active or shared role in decision making?”, only 29% believed 85-90% of BC patients desired an active or shared role as suggested by surgical literature; 43% believed between 55-70% of patients wanted to be engaged in decision-making. Commonly reported barriers to SDM are shown in the table below. Conclusions: Physicians may underestimate patient’s desire to participate in shared decision-making. The barriers to implementing SDM in oncology practice will likely require multi-faceted interventions to overcome. We aim to address these gaps through an intervention aimed at enhancing knowledge and patient-provider engagement through treatment summaries. [Table: see text]

Shared decision-making for breast cancer patients

2013 ◽  
pp. 311-321
Author(s):  
Catharine Clay ◽  
Alice Andrews ◽  
Dale Vidal
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Cancer Patients ◽  
Shared Decision Making ◽  
Shared Decision ◽  
Breast Cancer Patients

scholarly journals Shared Decision-Making in Breast Reconstruction for Breast Cancer Patients: A Scoping Review

2021 ◽  
Vol Volume 15 ◽  
pp. 2763-2781
Author(s):  
Xuejing Li ◽  
Meiqi Meng ◽  
Junqiang Zhao ◽  
Xiaoyan Zhang ◽  
Dan Yang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Breast Reconstruction ◽  
Cancer Patients ◽  
Shared Decision Making ◽  
Scoping Review ◽  
Shared Decision ◽  
Breast Cancer Patients

Four Conversations: A randomized control trial of an online, shared decision making curriculum among the metastatic breast cancer community.

2017 ◽  
Vol 35 (31_suppl) ◽  
pp. 47-47
Author(s):  
Sophia Kustas Smith ◽  
Kelly E. Westbrook ◽  
Kristin MacDermott ◽  
Matthew Roger LeBlanc ◽  
Sathya Amarasekara ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Metastatic Breast Cancer ◽  
Shared Decision Making ◽  
Self Efficacy ◽  
Metastatic Breast ◽  
T Test ◽  
Shared Decision ◽  
Breast Cancer Patients ◽  
The Impact

47 Background: Evidence shows that shared decision making is effective in improving the quality of end of life care, and that it rarely happens; new interventions are needed. Four Conversations is an evidence-based, online curriculum that facilitates shared decision making. This presentation will report the impact of Four Conversations on key outcomes. Methods: Individuals with metastatic breast cancer and caregivers are being recruited nationally. Consenting participants are randomized 1:1 to the treatment or wait-listed control arm. Treatment arm participants access content online; required activities included viewing interactive videos and completing workbook activities. Surveys are administered at Baseline, Week-4, and Week-8 via REDCap to assess for: decision making self-efficacy and conflict; and program satisfaction. An independent-samples t-test was conducted to compare change in decision making outcomes in treatment and usual care conditions at Week-4. A paired-samples t-test was used to access for changes in outcomes from Baseline to Week-8 among the treatment arm. Results: Participants (n = 138) were: mean age 53.2 (11.8) years; 96% female; 91% white; 72% married. There was significant improvement in decision making self-efficacy and reduction in conflict among the treatment arm at follow-up (p < .05). There was no significant change in decision making self-efficacy and conflict scores for treatment and wait-listed control conditions at the end of the intervention (p > .05). Among treatment arm participants who did not already have an advanced care directive, most (56%) completed one. Most participants (88%) would recommend Four Conversations to others and felt that the program better prepared them to make better decisions. Conclusions: While these results are preliminary (i.e., data collection continues through 9/2017), they suggest that Four Conversations may effect decision-making outcomes for metastatic breast cancer patients and caregivers. Additional research is recommended with larger and more diverse samples following completion of this study. Clinical trial information: NCT02944344.

scholarly journals Is There a Relationship between Shared Decision Making and Breast Cancer Patients’ Trust in Their Medical Oncologists?

2019 ◽  
Vol 40 (1) ◽  
pp. 52-61 ◽  
Author(s):  
Ellen G. Engelhardt ◽  
Ellen M. A. Smets ◽  
Irini Sorial ◽  
Anne M. Stiggelbout ◽  
Arwen H. Pieterse ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Cancer Patients ◽  
Shared Decision Making ◽  
Risk Prediction ◽  
Prediction Models ◽  
Shared Decision ◽  
Negative Consequences ◽  
Breast Cancer Patients ◽  
Low Levels

Background. Adjuvant systemic treatment for early stage breast cancer significantly reduces the risk of mortality but is associated with side effects, reducing patients’ quality of life. Decisions about adjuvant treatment are preference sensitive and are thus ideally suited to a shared decision making (SDM) approach. Whether and how SDM affects patients’ trust in their oncologist is currently unknown. We investigated the association between patients’ trust in their oncologist and 1) observed level of SDM in the consultation, 2) congruence between patients’ preferred and perceived level of participation, and 3) patient and oncologist characteristics. Methods. Decision consultations ( n = 101) between breast cancer patients and their medical oncologist were audio-recorded and transcribed verbatim. Patients’ trust in their oncologist was measured using the Trust in Oncologist Scale (TiOS). The observed level of SDM was scored using the 12-item Observing Patient Involvement In Decision Making scale (OPTION-12), preferred level of participation with the Control Preferences Scale, and perceived level of participation with an open question in telephonic interviews. Results. The average TiOS score was high overall (mean [SD] = 4.1 [.56]; range, 2.6–5.0). Low levels of SDM were observed (mean [SD] = 16 [11.6]; range, 2–56). Neither observed nor perceived level of participation in SDM was associated with trust. Patients’ preferred and perceived role in decision making was incongruent in almost 50% of treatment decisions. Congruence was not related to trust. A larger tumor size (β = 4.5, P = 0.03) and the use of a risk prediction model during the consultation (β = 4.1, P = 0.04) were associated with stronger trust. Conclusion. Patients reported strong trust in their oncologist. While low levels of SDM were observed, SDM was not associated with trust. These findings suggest it may not be necessary to worry about negative consequences for trust of using SDM or risk prediction models in oncological consultations. Considering the increased emphasis on implementing SDM, it is important to further explore how SDM affects trust in clinical practice.

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