Promoting shared decision making in advanced cancer: Development and piloting of a patient communication aid

2019 ◽  
Vol 102 (5) ◽  
pp. 916-923 ◽  
Author(s):  
Inge Henselmans ◽  
Sabrina D. Brugel ◽  
Hanneke C.J.M. de Haes ◽  
Kim J.A. Wolvetang ◽  
Laura M. de Vries ◽  
...  
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Advanced Cancer ◽  
Patient Communication ◽  
Cancer Development ◽  
Shared Decision ◽  
Communication Aid

scholarly journals Differential Influences of Social Support on App Use for Diabetes Self-Management – a Mixed Methods Approach

2020 ◽  
Author(s):  
Nicola Brew-Sam ◽  
Arul Chib ◽  
Constanze Rossmann
Keyword(s):  
Social Support ◽  
Decision Making ◽  
Logistic Regression ◽  
Shared Decision Making ◽  
Healthcare Professionals ◽  
Binary Logistic Regression ◽  
Patient Communication ◽  
Self Management ◽  
Shared Decision ◽  
The Impact

Abstract Background The impact of social support on diabetes management and health outcomes has been investigated comprehensively, with recent studies examining social support delivered via digital technologies. This paper argues that social support has an impact on the use of diabetes technologies. Specifically, we postulate differences between the impact of healthcare professional versus non-professional (family/friends) support on mobile app use for diabetes self-management. Methods This research employed a triangulation of methods including exploratory semi-structured face-to-face interviews (N= 21, Study 1) and an online survey (N= 65, Study 2) with adult type 1 and type 2 diabetes patients. Thematic analysis (Study 1) was used to explore the relevance of social support (by professionals versus non-professionals) for diabetes app use. Binary logistic regression (Study 2) was applied to compare healthcare decision-making, healthcare-patient communication, and the support by the personal patient network as predictors of diabetes app use, complemented by other predictors from self-management and technology adoption theory. Results The interviews (Study 1) demonstrated that (technology-supported) shared decision-making and supportive communication by healthcare professionals depended on the medical specialty of attending physicians. The personal patient network was perceived as either facilitating or hindering the use of mHealth for self-management. Binary logistic regression (Study 2) showed that the specialty of the physician significantly predicted the use of diabetes apps, with supervision by diabetes specialists increasing the likelihood of app use (as opposed to general practitioners). In addition, specialist care positively related to a higher chance of shared decision-making and better physician-patient communication. The support by the personal patient network predicted diabetes app use in the opposite direction, with less family/friend support increasing the likelihood of app use. Conclusion The results emphasize the relevance of support by healthcare professionals and by the patient network for diabetes app use and disclose differences from the existing literature. In particular, we found that the use of diabetes apps may increase in the absence of social support by family or friends (e.g., compensation for lack of support), and that use of diabetes apps may decrease when such support is high (e.g., no perceived need to use technology). Implications for practice are discussed.

Determinants of satisfactory patient communication and shared decision making in patients with multiple myeloma

2019 ◽  
Vol 28 (7) ◽  
pp. 1490-1497 ◽  
Author(s):  
Babak Nejati ◽  
Chien‐Chin Lin ◽  
Neil K. Aaronson ◽  
Andy S.K. Cheng ◽  
Maria Browall ◽  
...  
Keyword(s):  
Decision Making ◽  
Multiple Myeloma ◽  
Shared Decision Making ◽  
Patient Communication ◽  
Shared Decision

Are needs of stakeholders in cancer care being met? A novel approch to assessing needs to improve value in cancer care.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 6581-6581
Author(s):  
Manali I. Patel ◽  
David Moore ◽  
Shannon Randolph ◽  
Heather A. Wakelee ◽  
Douglas W. Blayney ◽  
...  
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Advanced Cancer ◽  
Cancer Care ◽  
Unmet Needs ◽  
Symptom Control ◽  
Healthcare Delivery ◽  
Healthcare Spending ◽  
Shared Decision ◽  
Improve Patient

6581 Background: Advanced cancer is a leading cause of death in the US. While treatments have improved, patients still report physical, emotional, and financial burdens associated with the disease. In order to improve cancer care, a comprehensive examination of unmet needs among patients, health care professionals, and other stakeholders is required to develop interventions that can improve patient outcomes, experience, and reduce healthcare spending. Methods: A national convenience sample of patients, families, caregivers, healthcare professionals, payer groups, and healthcare delivery systems who have experience with cancer care were selected for participation. A 10-question survey was administered to participants regarding their experiences with current cancer care. A novel combination of Grounded theory, Stanford d.school and bio-design needs-findings methodologies were used to assess and prioritize needs. Results: A total of 273 participants presented 99 unique needs over the study period. Needs were organized into five categories: 1. Monitor/Intervene Patient Clinical and Symptom Data 2. Shared Decision-Making 3. Best Practice Communication 4. Integrated Care Team 5. Patient-Tailored Care. The most common needs of cancer patients were improved symptom control. Needs among providers focused on minimizing tasks that could be performed by others. Payer needs reflected improved value in care. Family and caregiver needs reflected shared decision-making in treatment plans. Healthcare delivery system needs included improved guideline development, evidence-based care, and report of quality metrics. Conclusions: A novel methodology to assess, analyze, and organize unmet needs in cancer care reveals that the top concerns among stakeholders are better symptom control, enhanced efforts to improve patient care commensurate with patients’ values, and a more tailored approach to coordinate care delivery using guideline-based care with attention to quality metrics. Future studies should draw upon these needs to develop targeted interventions for patients with advanced cancer that can improve experience, clinical outcomes, and reduce healthcare spending.

scholarly journals Differential Influences of Social Support on App Use for Diabetes Self-Management – a Mixed Methods Approach

2020 ◽  
Author(s):  
Nicola Brew-Sam ◽  
Arul Chib ◽  
Constanze Rossmann
Keyword(s):  
Social Support ◽  
Decision Making ◽  
Logistic Regression ◽  
Shared Decision Making ◽  
Healthcare Professionals ◽  
Binary Logistic Regression ◽  
Patient Communication ◽  
Self Management ◽  
Shared Decision ◽  
The Impact

Abstract Background The impact of social support on diabetes management and health outcomes has been investigated comprehensively, with recent studies examining social support delivered via digital technologies. This paper argues that social support has an impact on the use of diabetes technologies. Specifically, we postulate differences between the impact of healthcare professional versus non-professional (family/friends) support on mobile app use for diabetes self-management.Methods This research employed a triangulation of methods including exploratory semi-structured face-to-face interviews (N= 21, Study 1) and an online survey (N= 65, Study 2) with adult type 1 and type 2 diabetes patients. Thematic analysis (Study 1) was used to explore the relevance of social support (by professionals versus non-professionals) for diabetes app use. Binary logistic regression (Study 2) was applied to compare healthcare decision-making, healthcare-patient communication, and the support by the personal patient network as predictors of diabetes app use, complemented by other predictors from self-management and technology adoption theory.Results The interviews (Study 1) demonstrated that (technology-supported) shared decision-making and supportive communication by healthcare professionals depended on the medical specialty of attending physicians. The personal patient network was perceived as either facilitating or hindering the use of mHealth for self-management. Binary logistic regression (Study 2) showed that the specialty of the physician significantly predicted the use of diabetes apps, with supervision by diabetes specialists increasing the likelihood of app use (as opposed to general practitioners). In addition, specialist care positively related to a higher chance of shared decision-making and better physician-patient communication. The support by the personal patient network predicted diabetes app use in the opposite direction, with lower family/friend support increasing the likelihood of app use.Conclusion The results emphasize the relevance of support by healthcare professionals and by the patient network for diabetes app use and disclose differences from existing literature. In particular, we found that the use of diabetes apps may increase in the absence of social support by family or friends (e.g., compensation for lack of support), and that use of diabetes apps may decrease when support is high (e.g., no perceived need to use technology). Implications for practice are discussed.

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