Decisional Regret Surrounding Dialysis Initiation: A Comparative Analysis.

Rationale & Objective: Dialysis comes with a substantial treatment burden, so patients must select care plans that align with their preferences. We aimed to deepen the understanding of decisional regret with dialysis choices. Study Design: This study had a mixed-methods explanatory sequential design. Setting & Participants: All patients from a single academic medical center prescribed maintenance in-center hemodialysis or presenting for home hemodialysis or peritoneal dialysis check-up during 3 weeks were approached for survey. A total of 78 patients agreed to participate. Patients with the highest (15 patients) and lowest decisional regret (20 patients) were invited to semistructured interviews. Predictors: Decisional regret scale and illness intrusiveness scale were used in this study. Analytical Approach: Quantitatively, we examined correlations between the decision regret scale and illness intrusiveness scale and sorted patients into the highest and lowest decision regret scale quartiles for further interviews; then, we compared patient characteristics between those that consented to interview in high and low decisional regret. Qualitatively, we used an adapted grounded theory approach to examine differences between interviewed patients with high and low decisional regret. Results: Of patients invited to participate in the interviews, 21 patients (8 high regret, 13 low regret) agreed. We observed that patients with high decisional regret displayed resignation toward dialysis, disruption of their sense of self and social roles, and self-blame, whereas patients with low decisional regret demonstrated positivity, integration of dialysis into their identity, and self-compassion. Limitations: Patients with the highest levels of decisional regret may have already withdrawn from dialysis. Patients could complete interviews in any location (eg, home, dialysis unit, and clinical office), which may have influenced patient disclosure. Conclusions: Although all patients experienced disruption after dialysis initiation, patients' approach to adversity differs between patients experiencing high versus low regret. This study identifies emotional responses to dialysis that may be modifiable through patient-support interventions.

As part of a quality improvement initiative in our dialysis practice, a patient stated, "I wish I never started dialysis." This quote served as the catalyst for embarking on a research project with the aim to understand why patients living with end-stage kidney disease have regret about starting and continuing dialysis, a lifesaving but time-intensive measure. We surveyed and interviewed patients on the topic and learned that patients experiencing regret had a disrupted sense of self and blamed themselves for their need of dialysis. Patients with little to no regret demonstrated positivity and self-compassion. These findings will help health care professionals as they work with patients considering dialysis or having newly started dialysis.

Do patients with high versus low treatment and illness burden have different needs? A mixed-methods study of patients living on dialysis.

BACKGROUND: Approximately 750,000 people in the U.S. live with end-stage kidney disease (ESKD); the majority receive dialysis. Despite the importance of adherence to dialysis, it remains suboptimal, and one contributor may be patients' insufficient capacity to cope with their treatment and illness burden. However, it is unclear what, if any, differences exist between patients reporting high versus low treatment and illness burden. METHODS: We sought to understand these differences using a mixed methods, explanatory sequential design. We enrolled adult patients receiving dialysis, including in-center hemodialysis, home hemodialysis, and peritoneal dialysis. Descriptive patient characteristics were collected. Participants' treatment and illness burden was measured using the Illness Intrusiveness Scale (IIS). Participants scoring in the highest quartile were defined as having high burden, and participants scoring in the lowest quartile as having low burden. Participants in both quartiles were invited to participate in interviews and observations. RESULTS: Quantitatively, participants in the high burden group were significantly younger (mean = 48.4 years vs. 68.6 years respectively, p = <0.001). No other quantitative differences were observed. Qualitatively, we found differences in patient self-management practices, such as the high burden group having difficulty establishing a new rhythm of life to cope with dialysis, greater disruption in social roles and self-perception, fewer appraisal focused coping strategies, more difficulty maintaining social networks, and more negatively portrayed experiences early in their dialysis journey. CONCLUSIONS AND RELEVANCE: Patients on dialysis reporting the greatest illness and treatment burden have difficulties that their low-burden counterparts do not report, which may be amenable to intervention.

Shared Decision Making Tools for People Facing Stroke Prevention Strategies in Atrial Fibrillation: A Systematic Review and Environmental Scan.

OBJECTIVE: Shared decision making (SDM) tools can help implement guideline recommendations for patients with atrial fibrillation (AF) considering stroke prevention strategies. We sought to characterize all available SDM tools for this purpose and examine their quality and clinical impact. METHODS: We searched through multiple bibliographic databases, social media, and an SDM tool repository from inception to May 2020 and contacted authors of identified SDM tools. Eligible tools had to offer information about warfarin and ≥1 direct oral anticoagulant. We extracted tool characteristics, assessed their adherence to the International Patient Decision Aids Standards, and obtained information about their efficacy in promoting SDM. RESULTS: We found 14 SDM tools. Most tools provided up-to-date information about the options, but very few included practical considerations (e.g., out-of-pocket cost). Five of these SDM tools, all used by patients prior to the encounter, were tested in trials at high risk of bias and were found to produce small improvements in patient knowledge and reductions in decisional conflict. CONCLUSION: Several SDM tools for stroke prevention in AF are available, but whether they promote high-quality SDM is yet to be known. The implementation of guidelines for SDM in this context requires user-centered development and evaluation of SDM tools that can effectively promote high-quality SDM and improve stroke prevention in patients with AF.

Normalization of a conversation tool to promote shared decision making about anticoagulation in patients with atrial fibrillation within a practical randomized trial of its effectiveness: a cross-sectional study.

BACKGROUND: Shared decision making (SDM) implementation remains challenging. The factors that promote or hinder implementation of SDM tools for use during the consultation, including contextual factors such as clinician burnout and organizational support, remain unclear. We explored these factors in the context of a practical multicenter randomized trial evaluating the effectiveness of an SDM conversation tool for patients with atrial fibrillation considering anticoagulation therapy. METHODS: In this cross-sectional study, we recruited clinicians who were regularly involved in conversations with patients regarding anticoagulation for atrial fibrillation. Clinicians reported their characteristics and burnout symptoms using the two-item Maslach Burnout Inventory. Clinicians were trained in using the SDM tool, and they recorded their perceptions of the tool's normalization potential using the Normalization MeAsure Development (NoMAD) survey instrument and verbally reflected on their answers to these survey questions. When possible, the training sessions and clinicians' verbal responses to the conversation tool were recorded. RESULTS: Our study comprised 183 clinicians recruited into the trial (168 with survey responses and 112 with recordings). Overall, clinicians gave high scores to the normalization potential of the intervention; they endorsed all domains of normalization to the same extent, regardless of site, clinician characteristics, or burnout ratings. In interviews, clinicians paid significant attention to making sense of the tool. Tool buy-in seemed to depend heavily on their ability to see the tool as accurate and "evidence-based" and their perceptions of having time in the consultation to use it. CONCLUSIONS: While time in the consultation remains a barrier, we did not find a significant association between burnout symptoms and normalization of an SDM conversation tool. Possible areas for improving the normalization of SDM conversation tools in clinical practice include enabling collaboration among clinicians to implement the tool and reporting how clinicians elsewhere use the tool. Direct measures of normalization (i.e., observing how often clinicians access the tool in practice outside of the clinical trial) may further elucidate the role that contextual factors, such as clinician burnout, play in the implementation of SDM. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02905032. Registered on 9 September 2016.

Capacity Coaching: A Focused Ethnographic Evaluation in Clinical Practice.

OBJECTIVE: To qualitatively evaluate the implementation of Capacity Coaching, an intervention to address the work patients must undertake to manage their conditions, implemented as a quality improvement pilot in 1 of 2 implementing US Department of Veterans Affairs medical centers. PARTICIPANTS AND METHODS: Two Veterans Affairs medical centers in the Midwest sought to implement Capacity Coaching as a quality improvement pilot in their Patient-Aligned Care Teams for 6 months (April 1, 2017, through October 31, 2017). Following the pilot, we conducted a focused ethnographic evaluation (on-site data collection, January 2-4, 2018), including interviews, a focus group, and observations with staff at one site to assess the implementation of capacity coaching. Data were analyzed inductively and findings were cross-referenced with implementation theory. RESULTS: We found that implementation was feasible and achieved changes that were aligned with reducing patient work and increasing capacity. We found that the key facilitators for the implementation of this program were in participants making sense of the intervention (coherence) and working collectively to enact the program (collective action). The main challenges for the program were in planning the work of implementation and enrolling a diverse coalition of staff to expand referrals to the program (cognitive participation) and in evaluating the impact of the program on outcomes that upper leadership was interested in (reflexive monitoring). CONCLUSION: Implementation of Capacity Coaching is feasible in clinical practice and may be a promising intervention for the care of chronic conditions. Further research should focus on testing capacity coaching using these lessons learned.

Changing conversations in primary care for patients living with chronic conditions: pilot and feasibility study of the ICAN Discussion Aid.

PURPOSE: To pilot test the impact of the ICAN Discussion Aid on clinical encounters. METHODS: A pre-post study involving 11 clinicians and 100 patients was conducted at two primary care clinics within a single health system in the Midwest. The study examined clinicians' perceptions about ICAN feasibility, patients' and clinicians' perceptions about encounter success, videographic differences in encounter topics, and medication adherence 6 months after an ICAN encounter. RESULTS: 39/40 control encounters and 45/60 ICAN encounters yielded usable data. Clinicians reported ICAN use was feasible. In ICAN encounters, patients discussed diet, being active and taking medications more. Clinicians scored themselves poorer regarding visit success than their patients scored them; this effect was more pronounced in ICAN encounters. ICAN did not improve 6-month medication adherence or lengthen visits. CONCLUSION: This pilot study suggests that using ICAN in primary care is feasible, efficient and capable of modifying conversations. With lessons learned in this pilot, we are conducting a randomised trial of ICAN versus usual care in diverse clinical settings. TRIAL REGISTRATION NUMBER: NCT02390570.

Applying Social Network Analysis to Evaluate Implementation of a Multisector Population Health Collaborative That Uses a Bridging Hub Organization.

Background: Multisector collaboratives are increasingly popular strategies for improving population health. To be comprehensive, collaboratives must coordinate the activities of many organizations across a geographic region. Many policy-relevant models encourage creation and use of centralized hub organizations to do this work, yet there is little guidance on how to evaluate implementation of such hubs and track their network reach. We sought to demonstrate how social network analysis (SNA) could be used for this purpose. Methods: Through formative research, we defined and conceptualized key characteristics of a bridging hub network and identified a set of candidate measures-(1) network membership, (2) network interaction, (3) role and reach of the bridging hub, and (4) network collaboration-to evaluate its implementation within a pre-determined geographic region of Southeast Minnesota, USA. We then developed and administered a survey to assess outcomes as part of a SNA. We commented on the feasibility and usefulness of the methods. Results: The initial surveyed network consisted of 50 healthcare organizational sites and 50 community organizations representing sectors of public health, education, research, health promotion, social services, and long-term care and supports. Fifty-three of these organizations responded to the survey. The network's level of collaboration was "Cooperation" (level 2 of 5) and reported levels of collaboration varied by organization. Thirty-eight additional, unsurveyed organizations were identified as collaborators by respondents, pushing the theoretical network denominator up to 138 organizations. These additional organizations included grocery stores, ambulance services, and smaller, independent healthcare and community-based services focused on meeting the needs of underserved populations. The bridging hub organization had the highest betweenness centrality and was in good position to bridge healthcare and the community, although its organizational reach was estimated at only 51%. The SNA methods were feasible and useful for identifying opportunities and guiding implementation. Conclusions: Bridging hub organizations are not likely to link-or even be aware of-all relevant organizations in a geographic region at initial implementation. SNA may be a useful method for evaluating the value and reach of a bridging hub organization and guiding ongoing implementation efforts. Trial registration: http://ClinicalTrials.gov; #NCT03046498.