Shared Decision Making in the Safety Net: Where Do We Go from Here?

Background: Shared decision making (SDM) is an interactive process between clinicians and patients in which both share information, deliberate together, and make clinical decisions. Clinics serving safety net patients face special challenges, including fewer resources and more challenging work environments. The use of SDM within safety net institutions has not been well studied.Methods: We recruited a convenience sample of 15 safety net primary care clinicians (13 physicians, 2 nurse practitioners). Each answered a 9-item SDM questionnaire and participated in a semistructured interview. From the transcribed interviews and questionnaire data, we identified themes and suggestions for introducing SDM into a safety net environment.Results: Clinicians reported only partially fulfilling the central components of SDM (sharing information, deliberating, and decision making). Most clinicians expressed interest in SDM by stating that they "selected a treatment option together" with patients (8 of 15 in strong or complete agreement), but only a minority (3 of 15) "thoroughly weighed the different treatment options" together with patients. Clinicians attributed this gap to many barriers, including time pressure, overwhelming visit content, patient preferences, and lack of available resources. All clinicians believed that lack of time made it difficult to practice SDM.Conclusions: To increase use of SDM in the safety net, efficient SDM interventions designed for this environment, team care, and patient engagement in SDM will need further development. Future studies should focus on adapting SDM to safety net settings and determine whether SDM can reduce health care disparities.</p

3D space-charge model for GPT simulations of high-brightness electron bunches

For the simulation of high-brightness electron bunches, a new 3D space-charge model is being implemented in the General Particle Tracer (GPT) code. It is based on a non-equidistant multigrid solver, allowing smooth transitions from a high to a low-aspect ratio bunch during a single run. The algorithm scales linearly in CPU time with the number of particles and the insensitivity to aspect ratio ensures that it can be used for a variety of applications. Tracking examples and field comparisons with an analytical model will be shown

Validating the Patient Experience with Treatment and Self-Management (PETS), a patient-reported measure of treatment burden, in people with diabetes

Elizabeth A Rogers,1,2 Kathleen J Yost,3 Jordan K Rosedahl,3 Mark Linzer,4 Deborah H Boehm,5 Azra Thakur,5 Sara Poplau,5 Roger T Anderson,6 David T Eton3 1Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA; 2Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, USA; 3Department of Health Services Research, Mayo Clinic, Rochester, MN, USA; 4Department of Medicine, Hennepin County Medical Center, Minneapolis, MN, USA; 5Minneapolis Medical Research Foundation, Minneapolis, MN, USA; 6University of Virginia School of Medicine, Charlottesville, VA, USA Aims: To validate a comprehensive general measure of treatment burden, the Patient Experience with Treatment and Self-Management (PETS), in people with diabetes. Methods: We conducted a secondary analysis of a cross-sectional survey study with 120 people diagnosed with type 1 or type 2 diabetes and at least one additional chronic illness. Surveys included established patient-reported outcome measures and a 48-item version of the PETS, a new measure comprised of multi-item scales assessing the burden of chronic illness treatment and self-care as it relates to nine domains: medical information, medications, medical appointments, monitoring health, interpersonal challenges, health care expenses, difficulty with health care services, role activity limitations, and physical/mental exhaustion from self-management. Internal reliability of PETS scales was determined using Cronbach&rsquo;s alpha. Construct validity was determined through correlation of PETS scores with established measures (measures of chronic condition distress, medication satisfaction, self-efficacy, and global well-being), and known-groups validity through comparisons of PETS scores across clinically distinct groups. In an exploratory test of predictive validity, step-wise regressions were used to determine which PETS scales were most associated with outcomes of chronic condition distress, overall physical and mental health, and medication adherence. Results: Respondents were 37&ndash;88 years old, 59% female, 29% non-white, and 67% college-educated. PETS scales showed good reliability (Cronbach&rsquo;s alphas &ge;0.74). Higher PETS scale scores (greater treatment burden) were correlated with more chronic condition distress, less medication convenience, lower self-efficacy, and worse general physical and mental health. Participants less (versus more) adherent to medications and those with more (versus fewer) health care financial difficulties had higher mean PETS scores. Medication burden was the scale that was most consistently associated with well-being and patient-reported adherence. Conclusion: The PETS is a reliable and valid measure for assessing perceived treatment burden in people coping with diabetes. Keywords: treatment burden, patient-reported measure, measurement, patient perspective, disease management&nbsp

Healthcare provider relational quality is associated with better self-management and less treatment burden in people with multiple chronic conditions

David T Eton,1,2 Jennifer L Ridgeway,1,2 Mark Linzer,3 Deborah H Boehm,4 Elizabeth A Rogers,5 Kathleen J Yost,1,2 Lila J Finney Rutten,1,2 Jennifer L St Sauver,1,2 Sara Poplau,4 Roger T Anderson6 1Department of Health Sciences Research, 2Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, 3Division of General Internal Medicine, Hennepin County Medical Center, 4Minneapolis Medical Research Foundation, 5Division of General Internal Medicine, University of Minnesota Medical School, Minneapolis, MN, 6Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA Purpose: Having multiple chronic conditions (MCCs) can lead to appreciable treatment and self-management burden. Healthcare provider relational quality (HPRQ) &ndash; the communicative and interpersonal skill of the provider &ndash; may mitigate treatment burden and promote self-management. The objectives of this study were to 1) identify the associations between HPRQ, treatment burden, and psychosocial outcomes in adults with MCCs, and 2) determine if certain indicators of HPRQ are more strongly associated than others with these outcomes.Patients and methods: This is a cross-sectional survey study of 332 people with MCCs. Patients completed a 7-item measure of HPRQ and measures of treatment and self-management burden, chronic condition distress, self-efficacy, provider satisfaction, medication adherence, and physical and mental health. Associations between HPRQ, treatment burden, and psychosocial outcomes were determined using correlational analyses and independent samples t-tests, which were repeated in item-level analyses to explore which indicators of HPRQ were most strongly associated with the outcomes.Results: Most respondents (69%) were diagnosed with &ge;3 chronic conditions. Better HPRQ was found to be associated with less treatment and self-management burden and better psychosocial outcomes (P&lt;0.001), even after controlling for physical and mental health. Those reporting 100% adherence to prescribed medications had higher HPRQ scores than those reporting less than perfect adherence (P&lt;0.001). HPRQ items showing the strongest associations with outcomes were &ldquo;my healthcare provider spends enough time with me&rdquo;, &ldquo;my healthcare provider listens carefully to me&rdquo;, and &ldquo;I have trust in my healthcare provider&rdquo;.Conclusion: Good communication and interpersonal skills of healthcare providers may lessen feelings of treatment burden and empower patients to feel confident in their self-management. Patient trust in the provider is an important element of HPRQ. Educating healthcare providers about the importance of interpersonal and relational skills could lead to more patient-centered care. Keywords: patient&ndash;provider relationship, multi-morbidity, adherence, patient-centered care, trust&nbsp

Development and validation of the patient experience with treatment and self-management (PETS): a patient-reported measure of treatment burden

PURPOSE: The purpose of this study was to develop and validate a new comprehensive patient-reported measure of treatment burden-the Patient Experience with Treatment and Self-management (PETS). METHODS: A conceptual framework was used to derive the PETS with items reviewed and cognitively tested with patients. A survey battery, including a pilot version of the PETS, was mailed to 838 multi-morbid patients from two healthcare institutions for validation. RESULTS: A total of 332 multi-morbid patients returned completed surveys. Diagnostics supported deletion and consolidation of some items and domains. Confirmatory factor analysis supported a domain model for scaling comprised of 9 factors: medical information, medications, medical appointments, monitoring health, interpersonal challenges, medical/healthcare expenses, difficulty with healthcare services, role/social activity limitations, and physical/mental exhaustion. Scales showed good internal consistency (α range 0.79-0.95). Higher PETS scores, indicative of greater treatment burden, were correlated with more distress, less satisfaction with medications, lower self-efficacy, worse physical and mental health, and lower convenience of healthcare (Ps < 0.001). Patients with lower health literacy, less adherence to medications, and more financial difficulties reported higher PETS scores (Ps < 0.01). CONCLUSION: A comprehensive patient-reported measure of treatment burden can help to better characterize the impact of treatment and self-management burden on patient well-being and guide care toward minimally disruptive medicine

Making sense of diabetes medication decisions: a mixed methods cluster randomized trial using a conversation aid intervention

Purpose To determine the effectiveness of a shared decision-making (SDM) tool versus guideline-informed usual care in translating evidence into primary care, and to explore how use of the tool changed patient perspectives about diabetes medication decision making. Methods In this mixed methods multicenter cluster randomized trial, we included patients with type 2 diabetes mellitus and their primary care clinicians. We compared usual care with or without a within-encounter SDM conversation aid. We assessed participant-reported decisions made and quality of SDM (knowledge, satisfaction, and decisional conflict), clinical outcomes, adherence, and observer-based patient involvement in decision-making (OPTION12-scale). We used semi-structured interviews with patients to understand their perspectives. Results We enrolled 350 patients and 99 clinicians from 20 practices and interviewed 26 patients. Use of the conversation aid increased post-encounter patient knowledge (correct answers, 52% vs. 45%, p = 0.02) and clinician involvement of patients (Mean between-arm difference in OPTION12, 7.3 (95% CI 3, 12); p = 0.003). There were no between-arm differences in treatment choice, patient or clinician satisfaction, encounter length, medication adherence, or glycemic control. Qualitative analyses highlighted differences in how clinicians involved patients in decision making, with intervention patients noting how clinicians guided them through conversations using factors important to them. Conclusions Using an SDM conversation aid improved patient knowledge and involvement in SDM without impacting treatment choice, encounter length, medication adherence or improved diabetes control in patients with type 2 diabetes. Future interventions may need to focus specifically on patients with signs of poor treatment fit