Citations

Objective Patients with heart failure (HF) perform a variety of self-care activities to control symptoms and minimise the risk of HF decompensations. The objective of this study was to understand how patients build capacity and manage the work of living with HF. Design A qualitative study using semi-structured telephone interviews. The interview guide was informed by the Cumulative Complexity Model, a conceptual framework that focuses on a patient’s workload and their capacity to manage that work. Interview transcripts were analysed using a mixed inductive and deductive coding approach with organisation into larger thematic categories. Setting Southeastern Minnesota USA (11 counties) with capture of data from local community healthcare providers under the auspices of the Rochester Epidemiology Project. Participants Intentional sampling of local patients with HF (n=24, median age 69.5 years, 54% women, 63% rural, 54% preserved ejection fraction) who reported high treatment burden and/ or poor health status on a questionnaire. Results Three major themes emerged: using capacity to manage workload, disruptions resulting in workload exceeding capacity and regaining workload-capacity balance. Participants described routinising the daily tasks associated with living with HF to minimise the associated burden and identified disruptions to their routines, including hospitalisations, emergency room visits, worsening health status and changes in healthcare access. To accommodate disruptions and regain workload-capacity balance, participants decreased workload and/or transferred tasks to others to maximise capacity. Conclusions Participants with HF described managing patient workload in times of stable health, but they sometimes struggled to accommodate disruptions and worsening health status. These findings can inform the design of interventions to minimise workload, maximise capacity and improve quality of life for patients with HF.

Abstract Introduction: Patient and stakeholder involvement enhances the conduct and applicability of comparative effectiveness research (CER). However, examples of engagement practices for CER leveraging real-world data (i.e., data from routine clinical practice) are scarce. Notably, these studies differ from traditional clinical trials in their technical complexity and minimal prospective data collection, posing unique challenges for stakeholder involvement. This paper describes patient and stakeholder engagement in a CER study of type 2 diabetes (T2D) medications using real-world data from a large administrative claims database. Methods: A Patient and Stakeholder Advisory Group (PSAG) was formed to guide study design, conduct, and dissemination. The PSAG (n = 12) included individuals with T2D, clinicians, health systems leaders, professional society representatives, and a payer representative. Members were surveyed post-study initiation to assess their participation goals and experiences to date. Results: PSAG members influenced key design and methodological decisions, including cohort selection and adding an aim focused on patient preference elicitation. Survey results indicated high satisfaction with engagement processes and a desire for ongoing involvement. Most PSAG members cited their main goals as impacting the lives of people with T2D and ensuring the research’s relevance to clinicians. Conclusions: Best practices for engaging stakeholders in CER using real-world data are underdeveloped. Our experience suggests that an inclusive, stakeholder-engaged approach enriches the research process and ensures diverse perspectives are integrated into study design and conduct. Ongoing efforts will focus on assessing long-term engagement outcomes and PSAG member satisfaction.

Background: Guidelines recommend shared decision-making (SDM) for patients with atrial fibrillation (AF) making decisions regarding anticoagulation for stroke prevention. Decision support tools (e.g., Decision Aids [DAs]) facilitate SDM. However, little research has compared the effectiveness of the two most common types of DAs: (1) encounter decision aid (EDA) and (2) pre-encounter patient decision aid (PDA). Our study assessed the comparative effectiveness of PDAs and EDAs on SDM during AF clinical encounters where stroke prevention strategies were discussed. Research Question: Do decision aids (PDA or EDA), alone or in combination, improve patients’ AF decision-making experience compared to usual care? Methods: A cluster randomized multi-center trial in patients with AF comparing usual care (no DA) vs. one DA (EDA or PDA) or both DAs. Clinicians and patients were randomized independently into 4 study arms. Clinicians were randomized to use or not use the EDA for all study visits, and patients were randomized to use or not use the PDA. Co-primary outcome domains were: (1) quality of SDM (2) patient knowledge, and (3) decisional conflict. Secondary outcomes included: (1) treatment choice, (2) treatment initiation, and (3) treatment persistence. Patient characteristics were assessed. We will present comparisons of the randomized DAs on the co-primary and secondary outcomes and subgroup analyses. Results: Between December 2020-July 2023, investigators in 6 U.S. healthcare systems enrolled 1117 patients (mean (M) age 69, 63% male, 89% White) and 107 clinicians. Compared to usual care (no DA, M=31.6), SDM was better in patients receiving PDA (M=35.4) and EDA (44.5) alone or together (M=43.7; p’s<0.001). Knowledge about AF was greatest for those receiving both DAs or the PDA alone (84% accurate responses for PDA and both vs 76% with no DA, p<0.001), followed closely by the EDA alone (82%, p=0.003). Finally, both DAs (M=19.5) and EDA alone (M=20.0) had better decisional conflict scores compared to usual care (M=25.8; p’s<0.001). We will present analyses that assess the impact of DAs on secondary outcomes and interactions with DA, patient, and clinical characteristics across each outcome. Conclusions: In one of the first randomized trials examining the comparative effectiveness of EDAs and PDAs on SDM in clinical medicine, both PDAs and EDAs improved shared decision-making, decisional conflict, and knowledge compared to patients receiving usual care.

Abstract Objective This study aims to describe the experience of implementing a psychosocial distress screening system for children with serious or chronic medical conditions. Methods Achieving RoutIne Screening for Emotional health (ARISE) was developed to systematically evaluate psychosocial distress in children with serious medical or chronic medical illnesses, by integrating patient-reported outcome measures (PROM) into care delivery. ARISE was developed using a user-centered approach with extensive input from patients, families, and healthcare professionals to overcome barriers to routine PROM collection and integration into care as usual. It comprises a system to capture PROMs and then relay results to clinicians for changing care. We sought to implement ARISE at four subspecialty pediatric clinics caring for patients with cystic fibrosis, sickle cell disease, hemophilia, and neurological malignancy. Results Problems with acceptability, appropriateness, and feasibility represented barriers to implementation which were overcome by modifying the intervention using stakeholder input during the planning phase, leading to broad program acceptance. ARISE was implemented in three of the four clinics, in which 79.8% of eligible children and their family completed PROMs. Conclusion The ARISE program demonstrated the feasibility and effectiveness of integrating psychosocial screenings into subspecialty pediatric clinics, thereby enhancing the identification and management of psychosocial issues in children with serious and chronic medical illnesses.

Introduction Empowering people living with multimorbidity (multiple chronic conditions) to gain greater confidence in managing their health can enhance their quality of life. Education focused on self-management is a key tool for fostering patient empowerment and is mostly provided on an individual basis. Virtual communities of practice (VCoP) present a unique opportunity for online education in chronic condition self-management within a social context. This research aims to evaluate the effectiveness/cost-effectiveness of individualised, online self-management education compared with VCoP among middle-aged individuals living with multiple chronic conditions. Methods and analysis People aged 30–60, living with ≥2 chronic conditions and receiving care in primary care (PC) centres and outpatient hospital-based clinics in Madrid and Canary Islands will enrol in an 18-month parallel-design, blinded (intervention assessment and data analysts), pragmatic (adhering to the intention-to-treat principle), individually randomised trial. The trial will compare two 12-month web-based educational offers of identical content; one delivered individually (control) and the other with online social interaction (VCoP, intervention). Using repeated measures mixed linear models, with the patient as random effect and allocation groups and time per group as fixed effects, we will estimate between-arm differences in the change in Patient Activation Measure from baseline to 12 months (primary endpoint), including measurements at 6-month and 18-month follow-up. Other outcomes will include measures of depression and anxiety, treatment burden, quality of life. In addition to a process evaluation of the VCoP, we will conduct an economic evaluation estimating the relative cost-effectiveness of the VCoP from the perspectives of both the National Health System and the Community. Ethics and dissemination The trial was approved by Clinical Research Ethics Committees of Gregorio Marañón University Hospital in Madrid/Nuestra Señora Candelaria University Hospital in Santa Cruz de Tenerife. The results will be disseminated through workshops, policy briefs, peer-reviewed publications and local/international conferences. Trial registration number NCT06046326 .

Introduction: We validated the “Familial Hypercholesterolemia (FH) Decision Aid” to promote shared decision making (SDM) about lipid lowering therapy, based on patient-clinician encounters. Methods: Validation of the DA included an assessment of whether the content and design of the tool facilitated SDM and patient engagement and to determine how well the tool integrated with clinical workflow. Validation was conducted during patient-clinician encounters in the Mayo preventive cardiology clinic. As inclusion criteria we considered an upcoming appointment in the clinic, an LDL-C level ≥ ~160 mg/dL, and no prior diagnosis of FH. Prior to the encounters, each clinician viewed a demonstration of the online, interactive DA. During the encounters, the DA was shared with patients using the clinic room computer screen, either in-person or virtually. Patient-clinician encounters were video recorded for further analysis by two design researchers and experts in SDM. Results: Ten patients were enrolled in the study (7 male; average age 51 years). The average patient LDL-C level was 207 mg/dL, range 157 - 248 mg/dL. Review and qualitative analysis of the encounter recordings yielded 4 key findings: i) clinicians primarily used the cardiovascular risk estimate in the DA to guide conversation with patients; ii) highly trained specialists needed to change their usual approach to care and conversation to integrate the DA with their clinical workflows; iii) as clinicians became more familiar with the DA, they moved through the tool at a more efficient pace; and iv) each clinician developed his/her own style of navigating the DA, either moving through it one screen at a time or focusing on one specific section for the duration of the conversation. The DA effectively guided conversation and facilitated active patient engagement in 6 of 10 encounters. Social distancing and use of telemedicine encounters, due to the COVID-19 pandemic, limited patient engagement in 2 of 10 encounters. Overall, the DA promoted SDM regarding FH management in 9 of 10 encounters. Conclusion: Using patient-clinician encounters, we found the FH DA to facilitate SDM regarding lipid-lowering therapy. The tool has potential to improve care of FH patients and increase patient engagement and knowledge.

Introduction: Familial Hypercholesterolemia (FH) is a common inherited disorder of lipid metabolism. FH patients are at an increased risk of atherosclerotic cardiovascular disease (ASCVD) due to elevated low-density lipoprotein cholesterol (LDL-C) levels. Patients with FH may not reach target LDL-C levels despite maximally tolerated statin (±ezetimibe) therapy (MTT). The AHA scientific statement on FH highlighted the need for developing decision aids (DAs) to facilitate shared decision making (SDM) regarding additional therapy including PCSK9 inhibitors. Methods: A user-centered design process was initiated to understand FH treatment decisions and to develop prototype interventions. Patients with FH had their diagnosis confirmed by genetic testing. Encounters between FH patients and health care providers were video recorded and analyzed to assess how decisions are made regarding lipid lowering therapy. Nine encounters were recorded: 3 with a genetic counselor and 6 with an FH specialist. Informed by clinical encounters and literature review, we developed content for a DA related to available therapeutic options for FH patients on MTT. Results: A prototype online DA was created to support in-encounter discussion of a patient’s risk of adverse cardiovascular events and which therapies may be best suited to the patient (Figure). 5 and 10-year ASCVD risk is estimated using the SAFEHEART Risk Score (SRS). Risk is communicated in numbers using a 100-person icon array and the language “Out of 100 persons like you...”. Therapeutic options include watchful waiting, bile acid sequestrants, and PCSK9 inhibitors. For each option, the degree of risk reduction, costs, and side effects are presented. The tool is currently being refined by analyzing additional encounters with FH patients. Conclusion: We developed an interactive prototype DA to facilitate SDM for FH patients on MTT. After further iterative testing the tool will be deployed in the electronic health record.