An overview and discussion of the Patient-Centered Outcomes Research Institute's decision aid portfolio

A principal components analysis of factors associated with successful implementation of an LVAD decision support tool

BACKGROUND

A central goal among researchers and policy makers seeking to implement clinical interventions is to identify key facilitators and barriers that contribute to implementation success. Despite calls from a number of scholars, empirical insights into the complex structural and cultural predictors of why decision aids (DAs) become routinely embedded in health care settings remains limited and highly variable across implementation contexts.

METHODS

We examined associations between "reach", a widely used indicator (from the RE-AIM model) of implementation success, and multi-level site characteristics of nine LVAD clinics engaged over 18 months in implementation and dissemination of a decision aid for left ventricular assist device (LVAD) treatment. Based on data collected from nurse coordinators, we explored factors at the level of the organization (e.g. patient volume), patient population (e.g. health literacy; average sickness level), clinician characteristics (e.g. attitudes towards decision aid; readiness for change) and process (how the aid was administered). We generated descriptive statistics for each site and calculated zero-order correlations (Pearson's r) between all multi-level site variables including cumulative reach at 12 months and 18 months for all sites. We used principal components analysis (PCA) to examine any latent factors governing relationships between and among all site characteristics, including reach.

RESULTS

We observed strongest inclines in reach of our decision aid across the first year, with uptake fluctuating over the second year. Average reach across sites was 63% (s.d. = 19.56) at 12 months and 66% (s.d. = 19.39) at 18 months. Our PCA revealed that site characteristics positively associated with reach on two distinct dimensions, including a first dimension reflecting greater organizational infrastructure and standardization (characteristic of larger, more established clinics) and a second dimension reflecting positive attitudinal orientations, specifically, openness and capacity to give and receive decision support among coordinators and patients.

CONCLUSIONS

Successful implementation plans should incorporate specific efforts to promote supportive and mutually informative interactions between clinical staff members and to institute systematic and standardized protocols to enhance the availability, convenience and salience of intervention tool in routine practice. Further research is needed to understand whether "core predictors" of success vary across different intervention types.

Using Nudges to Enhance Clinicians' Implementation of Shared Decision Making With Patient Decision Aids

Background. Although effective interventions for shared decision making (SDM) exist, there is a lack of uptake of these tools into clinical practice. “Nudges,” which draw on behavioral economics and target automatic thinking processes, are used by policy makers to influence population-level behavior change. Nudges have not been applied in the context of SDM interventions but have potential to influence clinician motivation, a primary barrier to long-term adoption of SDM tools. Objective. Describe, evaluate, and propose recommendations for the use of a behavioral economics framework (MINDSPACE) on clinician motivation and behavior during implementation of a validated decision aid (DA) for left ventricular assist device at nine hospitals. Methods. Qualitative thematic analysis of process notes from stakeholder meetings during the first 6 months of implementation to identify examples of how the MINDSPACE framework was operationalized. Quantitative implementation progress was evaluated using the RE-AIM framework. Results. MINDSPACE components were translated into concrete approaches that leveraged influential stakeholders, fostered ownership over the DA and positive emotional associations, spread desirable norms across sites, and situated the DA within established default processes. DA reach to eligible patients increased from 9.8% in the first month of implementation to 70.0% in the sixth month. Larger gains in reach were observed following meetings using MINDSPACE approaches. Limitations. The MINDSPACE framework does not capture all possible influences on behavior and responses to nudges may differ across populations. Conclusions. Behavioral economics can be applied to implementation science to foster uptake of SDM tools by increasing clinician motivation. Our recommendations can help other researchers effectively apply these approaches in real-world settings when there are often limited incentives and opportunities to change organizational- or structural-level factors.

Shared decision making as part of value based care: New U.S. policies challenge our readiness

Shared decision making in the United States is increasingly being recognized as part of value-based care. During the last decade, several state and federal initiatives have linked shared decision making with reimbursement and increased protection from litigation. Additionally, private and public foundations are increasingly funding studies to identify best practices for moving shared decision making from the research world into clinical practice. These shifts offer opportunities and challenges for ensuring effective implementation.