Strongest inclines in uptake and reach of our decision aid occurred across the first year, with frequency of uptake fluctuating over the second year. That the largest of these fluctuations coincided with typical seasonal/holiday shifts (October-December 2019) as well as the sharp rise of the COVID-19 pandemic in the United Stated (March 2020), suggests that larger situational factors at the national or even global level can influence reach. At a more local level, however, we discovered key site characteristics that appear to have important associations with reach. These site characteristics form two distinct constellations of variables that are non-overlapping, apart from their pivotal associations with reach, suggesting there may be more than one effective pathway to implementation success.
On one dimension, we found that reach is associated with site characteristics indicating greater organizational infrastructure and clinical standardization, variables typical of larger, more established clinics. Specifically, this constellation of traits includes greater volume of patient evaluations and implants, more frequent physician involvement with LVAD nurse coordinators, more highly specified role distribution (i.e. designated personnel for delivering patient education and decisional support), and greater standardization of patient education protocols.
Meanwhile, on a separate, second dimension, reach showed strong associations with a group of variables suggesting the importance of attitudinal orientation, including openness and capacity to give and receive decision support among coordinators and LVAD candidates, respectively. On this factor, high reach was associated with greater patient health literacy, greater coordinator/clinician satisfaction with the DA, and greater readiness for change. Thus, a patient’s ability to understand the health information conveyed during patient education, coupled with a coordinator’s more positive attitudes toward the DA and a broader sentiment among other staff of readiness for improvements, may together facilitate greater uptake of decision support.
The Attitudinal Dimension: Pro-Change Attitudes and Motivation
An openness to provide and receive decision support has long been recognized as a crucial ingredient in the uptake of shared decision making tools (1, 15, 27). Indeed, motivation of health professionals was found to be a top factor in a systematic review of barriers and facilitators of implementing SDM, including DAs, in practice (13). However, generating “buy-in” to the theoretical and practical importance of providing decision support is one of the most formidable challenges to effective implementation. A number of documented implementation approaches center on providing education to clinicians and staff members (27–31). However, the assumption that with knowledge comes motivation may be erroneous, and some researchers (32–34) have pointed out that education- or persuasion-based approaches may be ineffective if they do not also address individuals’ diverse motivations for engaging with an intervention. Such approaches are likely to encounter resistance from clinical staff’s default, habitual ways of thinking and behaving (sometimes called ‘‘bounded rationality’’) (35).
To address the need for fostering incentives that are internalized as positive, reflexive attitudes towards an intervention, we have outlined elsewhere a series of tools designed to positively affect clinicians’ and staff members’ motivations for using a DA (36). This toolkit, called MINDSPACE, draws from robust insights in behavioral economics to offer empirically supported strategies for implementers seeking to initiate small attitudinal, emotional, or behavioral responses that can collectively help bring about lasting, positive behavioral change. One optimistic insight is that attitudes and orientations towards shared decision-making and positive change may be more easily altered than structural variables, such as patient volume or available time spent on patient education, and are likely to be less economically and logistically costly to modify (36). For this reason, implementation scientists seeking to foster clinical characteristics associated with successful implementation of decision support tools may look towards strategies to generate staff interest in and motivation to use SDM tools. This recommendation is widely cited by an already sizable implementation science literature and empirically supported by our findings (1, 15, 27).
The Structural Dimension: Organizational Size, Standardization and Interaction
A second implementation approach suggested by our findings is to consider how larger clinics may serve as models for smaller clinics, specifically with regard to organizational characteristics that may be normatively linked to but not necessarily dependent on clinic size and infrastructure. For example, a close examination of our results on the first dimension reveals that the two variables most highly associated with reach include interaction between clinicians and staff and level of standardization involved in administration of our DA. Our findings show that larger clinics (with greater patient volume and number of evaluations) have greater communication and standardization of clinic procedures. This may be because, just as standardization in industry allows for economies of scale and enables markets to optimize their transactional efficiency, it is also likely that greater standardization and greater organizational guidance and oversight from physicians are features that help larger clinics to efficiently and effectively (safely) deliver services to large patient populations, particularly where staff members may be busiest and most time-constrained (37). While these structural and organizational features may be more prevalent among larger, highly resourced clinics, they are not dependent on clinic size and may serve as goalposts for smaller clinics hoping to effectively position themselves for successful implementation.
To better understand the significance of these organizational variables and their “active ingredients” for implementation success, we turn to a growing literature in implementation science and clinical decision support. Specifically, what may account for the positive impacts of frequent interaction between clinicians and staff, and what might these interactions entail? Studies from over two decades of implementation research suggest that implementation success is typically bolstered by having at least one clinician champion to promote the use of a decision support intervention (23, 32, 38–42). Interactions that demonstrate support and endorsement of a decision support tool from a respected clinician (especially a physician) “messenger” can offer the extra incentive needed for a clinical staff member to prioritize and recognize the value of an intervention (36). The critical role of clinician champions has also recently been highlighted by Berry et al. (41), who found that designating a clinical lead for implementation helped to address staff misunderstandings about which contexts and resources were best suited for administering decisional support. Brinkman et al. (42) likewise found that implementation was facilitated by buy-in from physicians about the value of SDM and formal training workshops for clinical staff implementing decision support. Further, a study by Uy et al. (16) similarly identified physician support as “crucial” to the distribution success of patient decision supports. In our own experience, we observed that communication between and among clinicians and coordinators offered important opportunities to communicate buy-in from clinicians to coordinators and other members of the clinical team who prioritized use of our DA as a result.
In our implementation project, we observed that physician buy-in was most crucial at the first stages of implementation (orientation and startup) to demonstrate support of our DA from clinical leaders and to provide the leverage necessary to make workflow changes or transition towards integration with or (in rarer cases) replacement of existing patient education materials. After this initial startup period, clinicians were called on less often to actively demonstrate their support as coordinators increasingly sustained their own momentum and expertise in using the DA. Thus, we recommend enlisting clinician support at early stages of implementation to leverage their practical knowledge and influence.
The studies cited above indicate that frequent clinician and clinical staff interaction may positively impact on implementation success by providing incentives and motivations for clinical staff engagement. However, because we did not see this variable appear alongside the attitudinal and motivational dimension revealed by our PCA, we must consider that other aspects of interaction may be equally important. In particular, interaction between clinical team members may also help to communicate practical support and guidelines for how to undergo implementation in ways that are consistent with site-specific goals and available resources. Tietbohl et al. (43) showed that clinical sites with high implementation success exhibited frequent, timely and accurate communication between clinicians and clinical staff, while lower performing clinics had more contentious relationships and inadequate communication. The nature of these interactions involved conveying practical guidance, troubleshooting and ongoing feedback to keep staff apprised of their distribution progress. Interaction may thus be associated with greater standardization because interaction provides a forum for communicating practical, concrete steps towards standardizing use of an intervention in practice. Cuypers et al. (44) similarly found that success in implementing a decision support tool was dependent on integrating clinical team members not only to influence their motivation but also to help navigate the clinical infrastructure needed to integrate and standardize use of an intervention into daily work patterns.
The importance of making an intervention “visible” in routine practice can also enhance use of decision support and systematize implementation by providing reminders to use the tool, encouraging strategic placement of visual cues in the workspace such as distribution checklists on computers, providing pre-written scripts with talking points for staff administering the DA, and scheduling timely feedback sessions for staff to discuss implementation progress (17). In a further example from our own project, one of our highest-reach sites used our DA as part of a more extensive clinical evaluation and patient education checklist instituted and championed by the director of the LVAD program. Other examples from the literature (e.g. Scalia et al. (32)) suggest that standardizing use of a decision support tool as part of a mandate or milestone completion expected by a clinical supervisor can result in improved interactions between patients and healthcare professionals, with patients asking more questions and feeling more satisfied and empowered in decision making. Evidence suggests that interaction with clinician champions can also provide structural insights about how best to systematize procedures within existing flow to facilitate referral, ordering and administration of DAs to patients (10, 23, 32, 41).
Examples of how to effectively standardize or systematize implementation to promote use of a DA include systematically identifying eligible patients to receive decision support tools in advance of their clinical visits(32), offering referral or ordering options in a patient’s electronic health record to ensure availability of a DA for patients to review ahead of their clinic visits (42), and having a DA readily accessible at a standardized place and time of decision making (23). Based on our results and experience, contextualized by these previous studies, we thus offer an additional concrete recommendation to standardize the time, place and process for administering decision support using checklists or “kits” to ensure their availability, salience and convenience for routine use, particularly in fast-paced, busy clinical settings.
The Importance of Multi-Directional Communication
We also observed that physicians are not always the only individuals to conceive of or initiate pro-implementation changes, and that the direction of effective communication is not always “top-down” (i.e. physician to coordinator) but multidirectional. Physicians can also learn from coordinators, nurses and other clinical staff who work in more regular proximity with patients about other “ground-level” considerations that are important for administering decision supports effectively or meaningfully in the daily clinic setting. In our own project, we observed that certain LVAD coordinators were the de facto champions of using our DA in practice and were effective at generating awareness and support from clinicians and other clinical staff. Coordinators harbor a wealth of observational experience that inform practical suggestions and solutions for implementation success at the patient level. Thus, while physician champions may be more suited to authorize and gain higher-level buy-in for infrastructural changes, bi-directional communication with nurse coordinators and other clinical staff can help to generate “grass roots” support and practical insights for implementing an intervention effectively in routine practice. We believe that our findings offer further support for the importance of fostering effective communication channels between physicians and staff in order to integrate different and equally important perspectives on engaging stakeholders at multiple levels (administrative, clinician-, staff- and patient-level). Based on these insights, we thus offer a final recommendation: to create forums for frequent exchange of perspectives and practical information across multiple roles, prioritizing “on the ground” insights (e.g. from coordinators) within a larger context of organizational resources and constraints (conveyed by clinicians or administrative personnel). The recommendations discussed above are listed in Table 5 as key takeaways for researchers interested in empirical insights to inform implementation science theory, and/or for clinicians and clinical programs seeking to better position themselves for implementation success.
Summary of recommendations for decision support implementation
Generate staff interest in and motivation to use SDM tools.
Enlist clinician support at early stages of implementation to leverage their practical knowledge and influence.
Standardize the time, place and process for administering decision support
Create forums for frequent exchange of perspectives and practical information across multiple roles
A primary limitation is that our analysis leaves over 50% of the variance unexplained by the measured variables. Further, the proportion of variance among variables that might be due to common variance, was moderately low (.38), indicating that the variables we measured may be only loosely related and require further verification, or a larger number of cases to better understand variable associations.
A second limitation is that we measured “interaction between clinicians and staff” by asking respondents to report on frequency of interaction. Further, we asked about “level of standardization” with reference to timing consistency – that is, whether coordinators’ administered the DA at the same time in the educational process across patients. A potential shortcoming of these phrasings is that other aspects of interaction and standardization beyond frequency and timing, respectively, may be equally or more important. Greater insights are needed into which features of clinician-coordinator interaction and standardization impact on implementation success.
A third limitation is that our results are based on respondents’ perceptions and may thus not accurately reflect the actual clinic characteristics and team-wide attitudes. Further research involving a more extensive range of clinics as well as rigorous measurement of site characteristics is needed to confirm our findings.