scholarly journals Patient-reported outcomes in RA care improve patient communication, decision-making, satisfaction and confidence: qualitative results

Rheumatology ◽  
2019 ◽  
Vol 59 (7) ◽  
pp. 1662-1670 ◽  
Author(s):  
Susan J Bartlett ◽  
Elaine De Leon ◽  
Ana-Maria Orbai ◽  
Uzma J Haque ◽  
Rebecca L Manno ◽  
...  
Keyword(s):  
Decision Making ◽  
Focus Groups ◽  
Shared Decision Making ◽  
Patient Reported Outcomes ◽  
Medical Decision ◽  
Measurement Information ◽  
Shared Decision ◽  
Clinic Staff ◽  
Patient Reported ◽  
The Impact

Abstract Objective To evaluate the impact of integrating patient-reported outcomes (PROs) into routine clinics, from the perspective of patients with RA, clinicians and other staff. Methods We conducted a prospective cohort study using a mixed methods sequential explanatory design at an academic arthritis clinic. RA patients completed selected Patient-Reported Outcomes Measurement Information System measures on tablets in the waiting room. Results were immediately available to discuss during the visit. Post-visit surveys with patients and physicians evaluated topics discussed and their impact on decision making; patients rated confidence in treatment. Focus groups or interviews with patients, treating rheumatologists and clinic staff were conducted to understand perspectives and experiences. Results Some 196 patients and 20 rheumatologists completed post-visit surveys at 816 and 806 visits, respectively. Focus groups were conducted with 24 patients, 10 rheumatologists and 4 research/clinic staff. PROs influenced medical decision-making and RA treatment changes (38 and 18% of visits, respectively). Patients reported very high satisfaction and treatment confidence. Impact on clinical workflow was minimal after a period of initial adjustment. PROs were valued by patients and physicians, and provided new insight into how patients felt and functioned over time. Reviewing results together improved communication, and facilitated patient-centred care, shared decision making, and the identification of new symptoms and contributing psychosocial/behavioural factors. Conclusion PRO use at RA visits was feasible, increased understanding of how disease affects how patients feel and function, facilitated shared decision-making, and was associated with high patient satisfaction and treatment confidence.

scholarly journals Development and Evaluation of the Shared Decision Making Process Scale: A Short Patient-Reported Measure

2020 ◽  
pp. 0272989X2097787
Author(s):  
K. D. Valentine ◽  
Ha Vo ◽  
Floyd J. Fowler ◽  
Suzanne Brodney ◽  
Michael J. Barry ◽  
...  
Keyword(s):  
Decision Making ◽  
Construct Validity ◽  
Shared Decision Making ◽  
Small Sample ◽  
Decision Quality ◽  
Medical Decision ◽  
Shared Decision ◽  
Partial Credit ◽  
Patient Reported ◽  
Process Scale

Background The Shared Decision Making (SDM) Process scale is a short patient-reported measure of the amount of SDM that occurs around a medical decision. SDM Process items have been used previously in studies of surgical decision making and exhibited discriminant and construct validity. Method Secondary data analysis was conducted across 8 studies of 11 surgical conditions with 3965 responses. Each study contained SDM Process items that assessed the discussion of options, pros and cons, and preferences. Item wording, content, and number of items varied, as did inclusion of measures assessing decision quality, decisional conflict (SURE scale), and regret. Several approaches for scoring, weighting, and the number of items were compared to identify an optimal approach. Optimal SDM Process scores were compared with measures of decision quality, conflict, and regret to examine construct validity; meta-analysis generated summary results. Results Although all versions of the scale were highly correlated, a short, partial credit, equally weighted version of the scale showed favorable properties. Overall, higher SDM Process scores were related to higher decision quality ( d = 0.18, P = 0.029), higher SURE scale scores ( d = 0.57, P < 0.001), and lower decision regret ( d = −0.34, P < 0.001). Significant heterogeneity was present in all validity analyses. Limitations Included studies all focused on surgical decisions, several had small sample sizes, and many were retrospective. Conclusion SDM Process scores showed resilience to coding changes, and a scheme using the short, partial credit, with equal weights was adopted. The SDM Process scores demonstrated a small, positive relationship with decision quality and were consistently related to lower decision conflict and less regret, providing evidence of validity across several surgical decisions.

scholarly journals Shared Decision Making: From Decision Science to Data Science

2020 ◽  
Vol 40 (3) ◽  
pp. 254-265
Author(s):  
Azza Shaoibi ◽  
Brian Neelon ◽  
Leslie A. Lenert
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Patient Reported Outcomes ◽  
Data Science ◽  
Treatment Effects ◽  
Predictive Analytics ◽  
Simulated Data ◽  
Treatment Recommendations ◽  
Shared Decision ◽  
Patient Reported

Background. Accurate diagnosis of patients’ preferences is central to shared decision making. Missing from clinical practice is an approach that links pretreatment preferences and patient-reported outcomes. Objective. We propose a Bayesian collaborative filtering (CF) algorithm that combines pretreatment preferences and patient-reported outcomes to provide treatment recommendations. Design. We present the methodological details of a Bayesian CF algorithm designed to accomplish 3 tasks: 1) eliciting patient preferences using conjoint analysis surveys, 2) clustering patients into preference phenotypes, and 3) making treatment recommendations based on the posttreatment satisfaction of like-minded patients. We conduct a series of simulation studies to test the algorithm and to compare it to a 2-stage approach. Results. The Bayesian CF algorithm and 2-stage approaches performed similarly when there was extensive overlap between preference phenotypes. When the treatment was moderately associated with satisfaction, both methods made accurate recommendations. The kappa estimates measuring agreement between the true and predicted recommendations were 0.70 (95% confidence interval = 0.052–0.88) and 0.73 (0.56–0.90) under the Bayesian CF and 2-stage approaches, respectively. The 2-stage approach failed to converge in settings in which clusters were well separated, whereas the Bayesian CF algorithm produced acceptable results, with kappas of 0.73 (0.56–0.90) and 0.83 (0.69–0.97) for scenarios with moderate and large treatment effects, respectively. Limitations. Our approach assumes that the patient population is composed of distinct preference phenotypes, there is association between treatment and outcomes, and treatment effects vary across phenotypes. Findings are also limited to simulated data. Conclusion. The Bayesian CF algorithm is feasible, provides accurate cluster treatment recommendations, and outperforms 2-stage estimation when clusters are well separated. As such, the approach serves as a roadmap for incorporating predictive analytics into shared decision making.

512-P: Desire for and Experience of Shared Decision-Making and Associations with Patient-Reported Outcomes in Those with Diabetes

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 512-P
Author(s):  
EMILY SYVERUD ◽  
SARAH T. MANSER ◽  
STEVEN ARRIAZA ◽  
ELIZABETH A. ROGERS
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Patient Reported Outcomes ◽  
Shared Decision ◽  
Patient Reported

Toward Optimal Decision Making among Vulnerable Patients Referred for Cardiac Surgery: A Qualitative Analysis of Patient and Provider Perspectives

2016 ◽  
Vol 37 (5) ◽  
pp. 600-610 ◽  
Author(s):  
Ryan A. Gainer ◽  
Janet Curran ◽  
Karen J. Buth ◽  
Jennie G. David ◽  
Jean-Francois Légaré ◽  
...  
Keyword(s):  
Decision Making ◽  
Cardiac Surgery ◽  
Focus Groups ◽  
Shared Decision Making ◽  
Consent Process ◽  
Decision Making Process ◽  
Shared Decision ◽  
Provider Perspectives ◽  
Increased Risk ◽  
The Impact

Objectives. Comprehension of risks, benefits, and alternative treatment options has been shown to be poor among patients referred for cardiac interventions. Patients’ values and preferences are rarely explicitly sought. An increasing proportion of frail and older patients are undergoing complex cardiac surgical procedures with increased risk of both mortality and prolonged institutional care. We sought input from patients and caregivers to determine the optimal approach to decision making in this vulnerable patient population. Methods. Focus groups were held with both providers and former patients. Three focus groups were convened for Coronary Artery Bypass Graft (CABG), Valve, or CABG +Valve patients ≥ 70 y old (2-y post-op, ≤ 8-wk post-op, complicated post-op course) (n = 15). Three focus groups were convened for Intermediate Medical Care Unit (IMCU) nurses, Intensive Care Unit (ICU) nurses, surgeons, anesthesiologists and cardiac intensivists (n = 20). We used a semi-structured interview format to ask questions surrounding the informed consent process. Transcribed audio data was analyzed to develop consistent and comprehensive themes. Results. We identified 5 main themes that influence the decision making process: educational barriers, educational facilitators, patient autonomy and perceived autonomy, patient and family expectations of care, and decision making advocates. All themes were influenced by time constraints experienced in the current consent process. Patient groups expressed a desire to receive information earlier in their care to allow time to identify personal values and preferences in developing plans for treatment. Both groups strongly supported a formal approach for shared decision making with a decisional coach to provide information and facilitate communication with the care team. Conclusions. Identifying the barriers and facilitators to patient and caretaker engagement in decision making is a key step in the development of a structured, patient-centered SDM approach. Intervention early in the decision process, the use of individualized decision aids that employ graphic risk presentations, and a dedicated decisional coach were identified by patients and providers as approaches with a high potential for success. The impact of such a formalized shared decision making process in cardiac surgery on decisional quality will need to be formally assessed. Given the trend toward older and frail patients referred for complex cardiac procedures, the need for an effective shared decision making process is compelling.

Sign in / Sign up

Export Citation Format

Share Document