scholarly journals After Visit Summary: Not an Afterthought

Author(s):  
Edward Sieferd ◽  
Nivedita Mohanty ◽  
Richard J. Holden

The After Visit Summary (AVS) is provided to patients after clinical visits to summarize what happened during the visit and guide future care. Despite its potential to improve shared decision-making, self-management, and communication, the design of the typical AVS is not optimized to communicate useful information in an understandable way. The AVS usability challenge is magnified in vulnerable patient populations such as those served by community health centers (CHCs). The purpose of this research was to evaluate and refine a redesigned AVS intended to better communicate information to CHC patients.

Author(s):  
Fiona Jones ◽  
Sara Demain

This chapter examines self-management in a way that introduces evidence, ideas, and concepts which illustrate the benefits of a personalized collaborative approach to neurorehabilitation. It reviews constructions of self-management from the chronic disease literature and the relevance to neurology and overlapping methods such as shared decision-making, health coaching, and motivational interviewing. It also reviews the benefits of integrating key self-management strategies into clinical encounters and current methods of measuring outcomes. It has been written for any healthcare professional who seeks to understand how to support and enable self-management within neurorehabilitation.


2010 ◽  
Vol 30 (6) ◽  
pp. 745-758 ◽  
Author(s):  
Russell E. Glasgow

Background . Diabetes self-management presents a series of challenging tasks, and primary care, where the majority of cases of adult diabetes are treated, is hard-pressed to address these issues given competing demands. This article discusses how interactive media (IM) can be used to support diabetes self-management. Methods . Following a brief review of the literature, the 5 As framework for enhancing the effectiveness of health behavior counseling and the RE-AIM model for estimating and enhancing public health impact are used to frame discussion of the strengths and limitations of IM for diabetes shared decision making and self-management support. Results . Data and lessons learned from a series of randomized trials of IM for diabetes self-management education are summarized around 2 key issues. The first is enhancing patient engagement in decision making and includes enhancing user experience and engagement, improving quality of care, and promoting collaborative action planning and follow-up. The second is getting such resources into place and sustaining them in real-world primary care settings and involves enhancing participation at patient, clinician, and health care system levels and enhancing the generalizability of results. Conclusions . Key opportunities for IM to support diabetes self-management include assessment of information for shared decision making, assistance with problem-solving self-management challenges, and provision of follow-up support. A key current challenge is the linkage of IM supports to the rest of the patient’s care, and collection of cost-effectiveness data is a key need for future research.


2020 ◽  
Author(s):  
Nicola Brew-Sam ◽  
Arul Chib ◽  
Constanze Rossmann

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.


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