Understanding Preferences for Treatment After Hypothetical First-Time Anterior Shoulder Dislocation: Surveying an Online Panel Utilizing a Novel Shared Decision-Making Tool

Streufert, Ben; Reed, Shelby D.; Orlando, Lori A.; Taylor, Dean C.; Huber, Joel; Mather, Richard C.

doi:10.1177/2325967117695788

Cited by 23 publications

(18 citation statements)

References 38 publications

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“…This technology can help patients review the latest evidence-based recommendations, limit surgeon bias, and serve as a starting point for discussion regarding benefits and risks of operative and nonoperative treatment. 5,9,12 Our study suggests that application of tools to measure and deliver patient preferences combined with evidence-based risk of recurrence could benefit both providers and patients in optimizing individualized treatment. Overall, CDS tools can serve as a method to improve communication and enhance outcomes.…”

Section: Discussionmentioning

confidence: 91%

“…Overall, CDS tools can serve as a method to improve communication and enhance outcomes. 5,9,12 There were several limitations of this study. For example, limited information was contained within each case study.…”

Section: Discussionmentioning

confidence: 95%

“…CDS tools, such as predictive models or decision aids, could be used to help mitigate biases and accurately disseminate evidence-based rates of recurrence while incorporating patient preferences. 5,12 For example, after a history and physical examination which indicates a diagnosis of FTASD then before a discussion of treatment options, the patient may be asked to complete a survey about his or her characteristics and treatment preferences. The results from this survey could then be used to estimate the recurrence risk while displaying patient preferences in a graphical format (see Table 2) for the surgeon to review with the patient.…”

Section: Discussionmentioning

confidence: 99%

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Surgeon Applications of Patient Preferences in Treatment Decision Making for First-Time Anterior Shoulder Dislocation

Lau

Hutyra

Streufert

et al. 2020

Orthopaedic Journal of Sports Medicine

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Background: Treatment of a first-time anterior shoulder dislocation (FTASD) is sensitive to patient preferences. The operative or nonoperative management debate provides an excellent opportunity to learn how surgeons apply patient preferences in treatment decisions. Purpose: To determine how patient preferences (repeat dislocation risk, recovery difficulties, fear of surgery, treatment costs) and surgeon factors influence a surgeon’s treatment plan for FTASD. Study Design: Cross-sectional study. Methods: Eight clinical vignettes of hypothetical patients with FTASD (including age, sex, and activity level) were presented to members of the Magellan Society. A second set of matched vignettes with patient preferences and clinical variables were also presented. The vignettes represented scenarios in which evidence does not favor one treatment over another. Respondents were asked how they would manage each hypothetical case. Respondents also estimated the risk of redislocation for the nonoperative cases for comparison with the published rates. Finally, respondents completed a Likert-scale questionnaire to determine their perceptions on factors influencing their decisions. Results: A total of 103 orthopaedic surgeons completed the survey; 48% practiced in an academic hospital; 79% were in practice for 10 years or longer; and 75% had completed a sports medicine fellowship. Patient preferences were the single most important factor influencing treatment recommendation, with activity type and age also important. Just 62% of the surgeon estimates of the risk of redislocation were consistent with the published rates. The inclusion of patient preferences to clinical variables changed treatment recommendations in 62.5% of our hypothetical cases. Respondents rated patient treatment preference as the leading factor in their treatment decision making. Conclusion: Patient preferences were important when deciding the appropriate treatment for FTASD. Respondents were inconsistent when applying evidence in their decision making and estimates of recurrent instability. Decision support tools that deliver patient preferences and personalized evidence-based outcome estimates improve the quality of decision making at the point of care.

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Section: Discussionmentioning

confidence: 91%

Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 99%

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Surgeon Applications of Patient Preferences in Treatment Decision Making for First-Time Anterior Shoulder Dislocation

Lau

Hutyra

Streufert

et al. 2020

Orthopaedic Journal of Sports Medicine

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“…A panel of orthopaedic surgeons, health economists, and health services researchers contributed to refine the initial list. The survey was then tested using Amazon’s Mechanical Turk, a web-based participant pool well studied and used in social sciences and recently utilized in orthopaedics 36-40 . Preference results and qualitative comments were used to further refine the attribute list.…”

Section: Methodsmentioning

confidence: 99%

Characterizing Patient Preferences Surrounding Total Knee Arthroplasty

Reuter

Hutyra

Politzer

et al. 2018

JBJS OA

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Background: Episode-based bundled payments for total knee arthroplasty emphasize cost-effective patient-centered care. Understanding patients’ perceptions of components of the total knee arthroplasty care episode is critical to achieving this care. This study investigated patient preferences for components of the total knee arthroplasty care episode. Methods: Best-worst scaling was used to analyze patient preferences for components of the total knee arthroplasty care episode. Participants were selected from patients presenting to 2 orthopaedic clinics with chronic knee pain. They were presented with descriptions of 17 attributes before completing a best-worst scaling exercise. Attribute importance was determined using hierarchical Bayesian estimation. Latent class analysis was used to evaluate varying preference profiles. Results: One hundred and seventy-four patients completed the survey, and 117 patients (67%) were female. The mean age was 62.71 years. Participants placed the highest value on surgeon factors, including level of experience, satisfaction rating, and complication rates. Latent class analysis provided a 4-segment model of the population. Conclusions: This study demonstrated differences in patient preferences for the components of a total knee arthroplasty care episode and characterized distinct preference profiles among patient subsets. Stakeholders can use this information to focus efforts and policy on high-value components and to potentially create customized bundles guided by preference profiles. Clinical Relevance: This study is clinically relevant because the patient preferences identified here may help providers to design customized bundles for total knee arthroplasty care.

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“…24 ACA is currently undergoing increased implementation in the health care field to inform patient decision making. 25–27…”

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confidence: 99%

Efficacy of a Preference-Based Decision Tool on Treatment Decisions for a First-Time Anterior Shoulder Dislocation: A Randomized Controlled Trial of At-Risk Patients

et al. 2019

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Background. First-time anterior shoulder dislocations (FTASD) provide an opportunity to examine the value of integrating stated-preference data with decision modeling to differentiate between patients whose preferred management strategy involves operative or nonoperative treatment. The objective of this study was to evaluate the efficacy of a FTASD decision tool intervention with individual preference measurement compared with a text-based control in a randomized controlled trial. Methods. Two hundred respondents between 18 and 35 years of age at risk for experiencing an FTASD were enrolled from the orthopedic clinics and randomized to receive either an interactive decision tool intervention capable of eliciting patient preferences for treatment of an FTASD or a text-based control on shoulder dislocations and treatments. The primary outcome was preference for operative or nonoperative treatment choice. Secondary outcomes included the decisional conflict scale (DCS), stage of decision making, patient activation and engagement, awareness of preference sensitive decisions, knowledge retention, and instrument acceptability. Results. One hundred respondents were randomized to the intervention and 100 to the control. A total of 154 men and 46 women with an average age of 23.6 years completed the survey. Participants in the intervention group made treatment decisions that aligned more closely with evidence-based recommendations than those in the control group (P = 0.016). Secondary outcomes showed no difference between intervention and control, excluding several DCS subscales. Discussion. An interactive, preference-based decision tool for treatment of FTASD affects patient decision making by guiding respondents toward treatment decisions that align more closely with evidence-based recommendations in the absence of a consultation with an orthopedic provider compared with a standard-of-care control tool. Additional study is needed to evaluate the long-term effects of this tool on treatment outcomes, patient adherence, and satisfaction. LEVEL OF EVIDENCE: 2

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Understanding Preferences for Treatment After Hypothetical First-Time Anterior Shoulder Dislocation: Surveying an Online Panel Utilizing a Novel Shared Decision-Making Tool

Cited by 23 publications

References 38 publications

Surgeon Applications of Patient Preferences in Treatment Decision Making for First-Time Anterior Shoulder Dislocation

Surgeon Applications of Patient Preferences in Treatment Decision Making for First-Time Anterior Shoulder Dislocation

Characterizing Patient Preferences Surrounding Total Knee Arthroplasty

Efficacy of a Preference-Based Decision Tool on Treatment Decisions for a First-Time Anterior Shoulder Dislocation: A Randomized Controlled Trial of At-Risk Patients

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