Revisiting the scope and expectations of Implementation Science and Implementation Science Communications.

This editorial updates the scope and submission expectations of Implementation Science and Implementation Science Communications. We refine our protocol publishing policies and set out new expectations for reporting studies describing determinants and their relationship with implementation outcomes. Our central focus remains on the implementation of evidence-based interventions into healthcare practice and policy. We are most interested in rigorous empirical studies of the implementation of evidence-based healthcare interventions, practices, and policies, and the de-implementation of those that are demonstrated to be of low-value or no benefit. Alongside this, we remain interested in the systematic study of implementation mechanisms and processes and on the influences of patient, professional, and organizational behaviours. Novel theoretical and methodological developments are considered. For all submissions, we expect authors to demonstrate how their work is integrated with existing knowledge in the field and to clearly state the added value of the work to the field broadly.

A Qualitative Examination of Clinician Anxiety about Suicide Prevention and Its Impact on Clinical Practice.

Clinician distress about working with patients at risk for suicide is well documented in the literature, yet little work has examined its pervasiveness across clinical settings. We conducted a secondary analysis of qualitative data gathered from 26 clinicians in primary care and outpatient mental health clinics serving both adult and child clients on their perception of evidence-based practice use for suicide screening, assessment, and brief intervention. Qualitative data were coded for any mentions of clinician anxiety or emotional response, and brief quantitative measures were collected to characterize our sample. When discussing broader barriers to implementation, 85% of participants spontaneously mentioned anxiety or heightened emotional responses related to delivering suicide prevention practices to those at risk for suicide. Common themes included low self-efficacy in suicide prevention skills, distress related to escalating care, efforts to alleviate such distress, and difficulty related to tolerating the uncertainty inherent in suicide prevention work. Similarly, while standardized anxiety ratings for participants were consistent with those of non-clinical norming samples, clinicians reported mild to moderate anxiety when screening for suicide risk (M = 3.64, SD = 2.19, Range = 0-8) and engaging in safety planning (M = 4.1, SD = 2.88, Range = 1-7) on post-interview surveys. In contrast, survey responses reflected generally high self-efficacy in their ability to screen for suicide risk (M = 7.66, SD = 1.29, Range = 5.25-10) and engage in safety planning (M = 8.25, SD = 0.87, Range = 7-9.5). Findings highlight pervasiveness of clinician distress when implementing suicide prevention practices and can inform future suicide prevention implementation efforts.

Implementation of a Secure Firearm Storage Program in Pediatric Primary Care: A Cluster Randomized Trial.

Importance: Increased secure firearm storage can reduce youth firearm injury and mortality, a leading cause of death for children and adolescents in the US. Despite the availability of evidence-based secure firearm storage programs and recommendations from the American Academy of Pediatrics, few pediatric clinicians report routinely implementing these programs. Objective: To compare the effectiveness of an electronic health record (EHR) documentation template (nudge) and the nudge plus facilitation (ie, clinic support to implement the program; nudge+) at promoting delivery of a brief evidence-based secure firearm storage program (SAFE Firearm) that includes counseling about secure firearm storage and free cable locks during all pediatric well visits. Design, Setting, and Participants: The Adolescent and Child Suicide Prevention in Routine Clinical Encounters (ASPIRE) unblinded parallel cluster randomized effectiveness-implementation trial was conducted from March 14, 2022, to March 20, 2023, to test the hypothesis that, relative to nudge, nudge+ would result in delivery of the firearm storage program to an additional 10% or more of the eligible population, and that this difference would be statistically significant. Thirty pediatric primary care clinics in 2 US health care systems (in Michigan and Colorado) were included, excluding clinics that were not the primary site for participating health care professionals and a subset selected at random due to resource limitations. All pediatric well visits at participating clinics for youth ages 5 to 17 years were analyzed. Interventions: Clinics were randomly assigned in a 1:1 ratio to receive either the nudge or nudge+. Main Outcomes and Measures: Patient-level outcomes were modeled to estimate the primary outcome, reach, which is a visit-level binary indicator of whether the parent received both components of the firearm storage program (counseling and lock), as documented by the clinician in the EHR. Secondary outcomes explored individual program component delivery. Results: A total of 47 307 well-child visits (median [IQR] age, 11.3 [8.1-14.4] years; 24 210 [51.2%] male and 23 091 [48.8%] female) among 46 597 children and 368 clinicians were eligible to receive the firearm storage program during the trial and were included in analyses. Using the intention-to-treat principle, a higher percentage of well-child visits received the firearm storage program in the nudge+ condition (49%; 95% CI, 37-61) compared to nudge (22%; 95% CI, 13-31). Conclusions and Relevance: In this study, the EHR strategy combined with facilitation (nudge+) was more effective at increasing delivery of an evidence-based secure firearm storage program compared to nudge alone. Trial Registration: ClinicalTrials.gov Identifier: NCT04844021.

Calculating power for multilevel implementation trials in mental health: Meaningful effect sizes, intraclass correlation coefficients, and proportions of variance explained by covariates.

Background: Despite the ubiquity of multilevel sampling, design, and analysis in mental health implementation trials, few resources are available that provide reference values of design parameters (e.g., effect size, intraclass correlation coefficient [ICC], and proportion of variance explained by covariates [covariate R 2]) needed to accurately determine sample size. The aim of this study was to provide empirical reference values for these parameters by aggregating data on implementation and clinical outcomes from multilevel implementation trials, including cluster randomized trials and individually randomized repeated measures trials, in mental health. The compendium of design parameters presented here represents plausible values that implementation scientists can use to guide sample size calculations for future trials. Method: We searched NIH RePORTER for all federally funded, multilevel implementation trials addressing mental health populations and settings from 2010 to 2020. For all continuous and binary implementation and clinical outcomes included in eligible trials, we generated values of effect size, ICC, and covariate R2 at each level via secondary analysis of trial data or via extraction of estimates from analyses in published research reports. Effect sizes were calculated as Cohen d; ICCs were generated via one-way random effects ANOVAs; covariate R2 estimates were calculated using the reduction in variance approach. Results: Seventeen trials were eligible, reporting on 53 implementation and clinical outcomes and 81 contrasts between implementation conditions. Tables of effect size, ICC, and covariate R2 are provided to guide implementation researchers in power analyses for designing multilevel implementation trials in mental health settings, including two- and three-level cluster randomized designs and unit-randomized repeated-measures designs. Conclusions: Researchers can use the empirical reference values reported in this study to develop meaningful sample size determinations for multilevel implementation trials in mental health. Discussion focuses on the application of the reference values reported in this study.

To improve the planning and execution of implementation research in mental health settings, researchers need accurate estimates of several key metrics to help determine what sample size should be obtained at each level of a multi-level study (e.g., number of patients, doctors, and clinics). These metrics include the (1) effect size, which indicates how large of a difference in the primary outcome is expected between a treatment and control group, (2) intraclass correlation coefficient, which describes how similar two people in the same group might be, and (3) covariate R ², which indicates how much of the variability in an outcome is explained by a background variable, such as level of health at the start of a study. We collected data from mental health implementation trials conducted between 2010 and 2020. We extracted information about each of these metrics and aggregated the results for researchers to use in planning their own studies. Seventeen trials were eligible, and we were able to obtain statistical information on 53 different outcome variables from these studies. We provide a set of values which will assist in sample size calculations for future mental health implementation trials.

A research agenda to advance the study of implementation mechanisms.

BACKGROUND: Implementation science scholars have made significant progress identifying factors that enable or obstruct the implementation of evidence-based interventions, and testing strategies that may modify those factors. However, little research sheds light on how or why strategies work, in what contexts, and for whom. Studying implementation mechanisms-the processes responsible for change-is crucial for advancing the field of implementation science and enhancing its value in facilitating equitable policy and practice change. The Agency for Healthcare Research and Quality funded a conference series to achieve two aims: (1) develop a research agenda on implementation mechanisms, and (2) actively disseminate the research agenda to research, policy, and practice audiences. This article presents the resulting research agenda, including priorities and actions to encourage its execution. METHOD: Building on prior concept mapping work, in a semi-structured, 3-day, in-person working meeting, 23 US-based researchers used a modified nominal group process to generate priorities and actions for addressing challenges to studying implementation mechanisms. During each of the three 120-min sessions, small groups responded to the prompt: "What actions need to be taken to move this research forward?" The groups brainstormed actions, which were then shared with the full group and discussed with the support of facilitators trained in structured group processes. Facilitators grouped critical and novel ideas into themes. Attendees voted on six themes they prioritized to discuss in a fourth, 120-min session, during which small groups operationalized prioritized actions. Subsequently, all ideas were collated, combined, and revised for clarity by a subset of the authorship team. RESULTS: From this multistep process, 150 actions emerged across 10 priority areas, which together constitute the research agenda. Actions included discrete activities, projects, or products, and ways to shift how research is conducted to strengthen the study of implementation mechanisms. CONCLUSIONS: This research agenda elevates actions to guide the selection, design, and evaluation of implementation mechanisms. By delineating recommended actions to address the challenges of studying implementation mechanisms, this research agenda facilitates expanding the field of implementation science, beyond studying what works to how and why strategies work, in what contexts, for whom, and with which interventions.

Opportunities to Advance Equity Through Implementation Strategy Design.

Background: Implementation strategies are potential tools for advancing equity goals in healthcare. Implementation scientists have increased attention to the integration of equity considerations into implementation research, but limited concrete guidance is available for developing implementation strategies to improve equity. Main: In parallel to an active hybrid effectiveness-implementation trial in two large health systems, our research team explored potential inequities in implementation across four non-study clinics, developed equity focused audit and feedback procedures, examined the feasibility of our approach, and identified design insights that could be tested in future work to inform equitable program scale-up. Based on our experiences deploying these strategies in pilot format, our research team identified key complexities meriting further examination in future work. These considerations are vital given the dearth of guidance on delivering feedback to clinicians in efforts to improve equity. Key takeaways include the importance of understanding local data culture, engaging constituents in co-design for the full feedback cycle, leveraging feedback for shared discourse, and centering multi-level strategies as part of robust implementation approaches. Conclusion: Prioritizing health equity in implementation science requires that research teams probe, interrogate, and innovate - and in doing so, grapple with central conceptual and pragmatic considerations that arise in the design of implementation strategies. Our work emphasizes the value of bidirectional and continuous learning.

A multi-constituent qualitative examination of facilitators and barriers to caregiver coaching for autistic children in publicly funded early intervention.

LAY ABSTRACT: Caregiver coaching is an evidence-based practice for young autistic children, but it is not widely used in community-based early intervention services. Previous research has explored why caregiver coaching is not widespread in early intervention, but only from the perspective of early intervention providers. Caregivers, providers, and administrators are all involved in the decision of whether to use caregiver coaching in early intervention. Therefore, it is important to include all perspectives in research regarding this practice. In this study we interviewed 20 caregivers of autistic children, 36 early intervention providers, and 6 administrators from early intervention agencies and asked questions about their perspectives regarding the use of caregiver coaching in early intervention. We did this to figure out what factors help and hinder the use of caregiver coaching in this setting and to see how caregivers, providers, and administrators agreed or disagreed on these factors. All participants agreed that caregivers' attitudes and expectations can influence whether caregiver coaching is used. In addition, all participants agreed that when caregivers and providers collaborate and have a strong working relationship, it can facilitate the use of caregiver coaching in early intervention. Other factors, such as caregiver stress and provider flexibility were also discussed. Based on these findings, we suggest strategies that can be used to possibly increase the use of caregiver coaching in early intervention for autistic children and their families.

A critical review of clinician-directed nudges.

As nudges-subtle changes to the way options are presented to guide choice-have gained popularity across policy domains in the past 15 years, healthcare systems and researchers have eagerly deployed these light-touch interventions to improve clinical decision-making. However, recent research has identified the limitations of nudges. Although nudges may modestly improve clinical decisions in some contexts, these interventions (particularly nudges implemented as electronic health record alerts) can also backfire and have unintended consequences. Further, emerging research on crowd-out effects suggests that healthcare nudges may direct attention and resources toward the clinical encounter and away from the main structural drivers of poor health outcomes. It is time to move beyond nudges and toward the development of multi-level, structurally focused interventions.

Integrating insights from implementation science and behavioral economics to strengthen suicide screening strategies for pediatric populations.

Suicide is a leading cause of death for young people globally. Professional organizations such as the American Academy of Pediatrics (AAP) recommend suicide screening for every young person at every healthcare contact and these guidelines are now being implemented across the US. To optimize deployment of these guidelines, we draw on insights from two parallel fields, implementation science - or the study of how to support clinicians in providing evidence-based care within organizational constraints - and behavioral economics, which centers human decision-making. In this brief review, we offer potential barriers to suicide screening and strategies to address barriers drawing on these two literatures, illustrating how best to integrate insights from these fields for maximal impact.

Continuous pulse oximetry monitoring in children hospitalized with bronchiolitis: A qualitative analysis of clinicians' justifications.

Continuous pulse oximetry (cSpO2) monitoring use outside established guidelines is common in children hospitalized with bronchiolitis. We analyzed clinicians' real-time rationale for continuous monitoring in stable children with bronchiolitis not requiring supplemental oxygen. Data for this study were collected as part a multicenter deimplementation trial for cSpO2 in children hospitalized with bronchiolitis. We analyzed 371 clinician responses across 36 hospitals; 258 (70%) responses did not include a clinical reason for monitoring ("nonclinical"; e.g., respondent forgot to discontinue monitoring, did not know why the patient was monitored, or was following an order). The remaining 113 (30%) responses contained a clinical reason for monitoring ("clinical"; e.g., recently requiring oxygen, physical exam concerns, or concerns relating to patient condition or history). Strategies to reduce unnecessary monitoring should include changes in workflow to facilitate shared understanding of monitoring goals and timely discontinuation of monitoring.

Clinician- and Patient-Directed Communication Strategies for Patients With Cancer at High Mortality Risk: A Cluster Randomized Trial.

Importance: Serious illness conversations (SICs) that elicit patients' values, goals, and care preferences reduce anxiety and depression and improve quality of life, but occur infrequently for patients with cancer. Behavioral economic implementation strategies (nudges) directed at clinicians and/or patients may increase SIC completion. Objective: To test the independent and combined effects of clinician and patient nudges on SIC completion. Design, Setting, and Participants: A 2 × 2 factorial, cluster randomized trial was conducted from September 7, 2021, to March 11, 2022, at oncology clinics across 4 hospitals and 6 community sites within a large academic health system in Pennsylvania and New Jersey among 163 medical and gynecologic oncology clinicians and 4450 patients with cancer at high risk of mortality (≥10% risk of 180-day mortality). Interventions: Clinician clusters and patients were independently randomized to receive usual care vs nudges, resulting in 4 arms: (1) active control, operating for 2 years prior to trial start, consisting of clinician text message reminders to complete SICs for patients at high mortality risk; (2) clinician nudge only, consisting of active control plus weekly peer comparisons of clinician-level SIC completion rates; (3) patient nudge only, consisting of active control plus a preclinic electronic communication designed to prime patients for SICs; and (4) combined clinician and patient nudges. Main Outcomes and Measures: The primary outcome was a documented SIC in the electronic health record within 6 months of a participant's first clinic visit after randomization. Analysis was performed on an intent-to-treat basis at the patient level. Results: The study accrued 4450 patients (median age, 67 years [IQR, 59-75 years]; 2352 women [52.9%]) seen by 163 clinicians, randomized to active control (n = 1004), clinician nudge (n = 1179), patient nudge (n = 997), or combined nudges (n = 1270). Overall patient-level rates of 6-month SIC completion were 11.2% for the active control arm (112 of 1004), 11.5% for the clinician nudge arm (136 of 1179), 11.5% for the patient nudge arm (115 of 997), and 14.1% for the combined nudge arm (179 of 1270). Compared with active control, the combined nudges were associated with an increase in SIC rates (ratio of hazard ratios [rHR], 1.55 [95% CI, 1.00-2.40]; P = .049), whereas the clinician nudge (HR, 0.95 [95% CI, 0.64-1.41; P = .79) and patient nudge (HR, 0.99 [95% CI, 0.73-1.33]; P = .93) were not. Conclusions and Relevance: In this cluster randomized trial, nudges combining clinician peer comparisons with patient priming questionnaires were associated with a marginal increase in documented SICs compared with an active control. Combining clinician- and patient-directed nudges may help to promote SICs in routine cancer care. Trial Registration: ClinicalTrials.gov Identifier: NCT04867850.

Spanish translation of the Expert Recommendations for Implementing Change (ERIC) compilation.

BACKGROUND: Most implementation science resources (e.g., taxonomies) are published in English. Linguistic inaccessibility creates a barrier to the conduct of implementation research among non-English-speaking populations, so translation of resources is needed. Translation into Spanish can facilitate widespread reach, given the large proportion of Spanish speakers around the world. This research aimed to systematically translate the Expert Recommendations for Implementation Change (ERIC) compilation into Spanish as an exemplar for the linguistic translation process. METHODS: Using the World Health Organization guidelines, this work translated the ERIC compilation strategy names, short definitions, and thematic clusters through a three-step process: 1) forward translation into Spanish by a native Spanish-speaking implementation scientist, 2) back-translation into English by a bilingual global health researcher, and 3) piloting via virtual focus group discussions with bilingual researchers not conducting implementation research. To achieve a generalizable translation, recruitment targeted a multicultural group of Spanish-speaking researchers. At the conclusion of each step, the transdisciplinary research team (N = 7) met to discuss discrepancies and refine translations. The Spanish version of the ERIC compilation was finalized through group consensus. Reflections from research team meetings and focus group discussions were synthesized qualitatively. RESULTS: Given that dialectical nuances exist between Spanish-speaking regions, efforts prioritized universally accepted terminology. Team discussions focused on difficult translations, word choice, and clarity of concepts. Seven researchers participated in two focus groups, where discussion surrounded clarity of concepts, alternative word choice for Spanish translations, linguistic formality, grammar, and conciseness. Translation difficulties highlighted lack of precision in implementation science terminology, and the lack of conceptual clarity of words underscored limitations in the application of the compilation. CONCLUSIONS: The work demonstrated the feasibility of translating implementation science resources. As one of the first systematic efforts to translate implementation resources, this study can serve as a model for additional efforts, including translation into other languages and the expansion to conceptual modifications. Further, this work yielded insights into the need to provide conceptual clarity in implementation science terminology. Importantly, the development of Spanish resources will increase access to conduct implementation research among Spanish-speaking populations.

Advancing a mission of translational intervention science: Comment on premature implementation.

Replies to comments made by Kenneth E. Freedland et al. (see record 2024-89430-002) on Rinad S. Beida, Lisa Saldana, and Rachel C. Shelton's original article (see record 2023-46817-001). In reading Freedland et al.'s (2024) commentary, it appears that their lens prioritizes internal validity and more explanatory and mechanistic work. While we also value these scientific goals and concur that the approaches they identify are clearly methodologically rigorous, we do not think the approaches will substantially reduce the unacceptable translation gap or address the fundamental issues of context. Our approach recognizes that there is tremendous value in cocreating solutions and interventions with patients, clinicians, and community members in the settings where we are seeking to promote health and address health inequities, and questions traditional assumptions and paradigms that scientists "know best" have effective solutions or should hold all of the power and knowledge (Brownson et al., 2022; Sanchez et al., 2023; Shelton, Adsul, & Oh, 2021; Shelton, Adsul, Oh, et al., 2021). We believe it is critical that we expand the pathways through which we advance intervention science in a meaningful and impactful way, and with more explicit attention to issues of context, equity, engagement, and external validity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Navigating grey areas in HIV and mental health implementation science.

INTRODUCTION: Implementation science (IS) offers methods to systematically achieve the Ending the HIV Epidemic goals in the United States, as well as the global UNAIDS targets. Federal funders such as the National Institutes of Mental Health (NIMH) have invested in implementation research to achieve these goals, including supporting the AIDS Research Centres (ARCs), which focus on high-impact science in HIV and mental health (MH). To facilitate capacity building for the HIV/MH research workforce in IS, "grey areas," or areas of IS that are confusing, particularly for new investigators, should be addressed in the context of HIV/MH research. DISCUSSION: A group of IS experts affiliated with NIMH-funded ARCs convened to identify common and challenging grey areas. The group generated a preliminary list of 19 grey areas in HIV/MH-related IS. From the list, the authors developed a survey which was distributed to all ARCs to prioritize grey areas to address in this paper. ARC members across the United States (N = 60) identified priority grey areas requiring clarification. This commentary discusses topics with 40% or more endorsement. The top grey areas that ARC members identified were: (1) Differentiating implementation strategies from interventions; (2) Determining when an intervention has sufficient evidence for adaptation; (3) Integrating recipient perspectives into HIV/MH implementation research; (4) Evaluating whether an implementation strategy is evidence-based; (5) Identifying rigorous approaches for evaluating the impact of implementation strategies in the absence of a control group or randomization; and (6) Addressing innovation in HIV/MH IS grants. The commentary addresses each grey area by drawing from the existing literature (when available), providing expert guidance on addressing each in the context of HIV/MH research, and providing domestic and global HIV and HIV/MH case examples that address these grey areas. CONCLUSIONS: HIV/MH IS is key to achieving domestic and international goals for ending HIV transmission and mitigating its impact. Guidance offered in this paper can help to overcome challenges to rigorous and high-impact HIV/MH implementation research.

Population mental health science: Guiding principles and initial agenda.

A recent American Psychological Association Summit provided an urgent call to transform psychological science and practice away from a solely individual-level focus to become accountable for population-level impact on health and mental health. A population focus ensures the mental health of all children, adolescents, and adults and the elimination of inequities across groups. Science must guide three components of this transformation. First, effective individual-level interventions must be scaled up to the population level using principles from implementation science, investing in novel intervention delivery systems (e.g., online, mobile application, text, interactive voice response, and machine learning-based), harnessing the strength of diverse providers, and forging culturally informed adaptations. Second, policy-driven community-level interventions must be innovated and tested, such as public efforts to promote physical activity, public policies to support families in early life, and regulation of corporal punishment in schools. Third, transformation is needed to create a new system of universal primary care for mental health, based on models such as Family Connects, Triple P, PROmoting School-community-university Partnerships to Enhance Resilience, Communities That Care, and the Early Childhood Collaborative of the Pittsburgh Study. This new system must incorporate valid measurement, universal screening, and a community-based infrastructure for service delivery. Addressing tasks ahead, including scientific creativity and discovery, rigorous evaluation, and community accountability, will lead to a comprehensive strategic plan to shape the emergent field of public mental health. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Possible unintended consequences of pediatric clinician strategies for communicating about social-emotional and developmental concerns in diverse young children.

INTRODUCTION: Screening to promote social-emotional well-being in toddlers has positive effects on long-term health and functioning. Communication about social-emotional well-being can be challenging for primary care clinicians for various reasons including lack of time, training and expertise, resource constraints, and cognitive burden. Therefore, we explored clinicians' perspectives on identifying and communicating with caregivers about social-emotional risk in toddlers. METHOD: In 2021, semistructured interviews were conducted with pediatric clinicians (N = 20) practicing in Federally Qualified Health Centers in a single metropolitan area. Most participants identified as female (n = 15; 75%), white non-Hispanic/Latino (n = 14; 70%), and were Doctors of Medicine or Osteopathic Medicine (n = 14; 70%). Thematic analysis was conducted on audio-recorded interview transcripts. RESULTS: Clinicians used various approaches to identify social-emotional concerns which were sometimes difficult to distinguish from other developmental concerns. The clinician-caregiver relationship guided identification and communication practices and cut-across themes. Themes include: starting with caregivers' concerns, communicating concerns with data and sensitivity, navigating labels, culture, and stigma, and limiting communication based on family capacity and interest. DISCUSSION: Prioritizing the clinician-caregiver relationship is consistent with best practice and family-centered care. Yet, the dearth of standardized decision support may undermine clinician confidence and impede timely conversations about social-emotional concerns. An evidence-based approach with developmentally based culturally informed quantitative tools and standardized decision supports could help ensure equitable management and decision making about young children's social and emotional well-being and development. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Addressing social needs in oncology care: another research-to-practice gap.

Social determinants of health and unmet social needs are directly related to cancer outcomes, from diagnosis to survivorship. If identified, unmet social needs can be addressed in oncology care by changing care plans in collaboration with patients' preferences and accounting for clinical practice guidelines (eg, reducing the frequency of appointments, switching treatment modalities) and connecting patients to resources within healthcare organizations (eg, social work support, patient navigation) and with community organizations (eg, food banks, housing assistance programs). Screening for social needs is the first step to identifying those who need additional support and is increasingly recognized as a necessary component of high-quality cancer care delivery. Despite evidence about the relationship between social needs and cancer outcomes and the abundance of screening tools, the implementation of social needs screening remains a challenge, and little is known regarding the adoption, reach, and sustainability of social needs screening in routine clinical practice. We present data on the adoption and implementation of social needs screening at two large academic cancer centers and discuss three challenges associated with implementing evidence-based social needs screening in clinical practice: (1) identifying an optimal approach for administering social needs screening in oncology care, (2) adequately addressing identified unmet needs with resources and support, and (3) coordinating social needs screening between oncology and primary care.

Suicide Screening, Risk Assessment, and Lethal Means Counseling During Zero Suicide Implementation.

OBJECTIVE: The authors measured implementation of Zero Suicide (ZS) clinical practices that support identification of suicide risk and risk mitigation, including screening, risk assessment, and lethal means counseling, across mental health specialty and primary care settings. METHODS: Six health care systems in California, Colorado, Michigan, Oregon, and Washington participated. The sample included members ages ≥13 years from 2010 to 2019 (N=7,820,524 patients). The proportions of patients with suicidal ideation screening, suicide risk assessment, and lethal means counseling were estimated. RESULTS: In 2019, patients were screened for suicidal ideation in 27.1% (range 5.0%-85.0%) of mental health visits and 2.5% (range 0.1%-35.0%) of primary care visits among a racially and ethnically diverse sample (44.9% White, 27.2% Hispanic, 13.4% Asian, and 7.7% Black). More patients screened positive for suicidal ideation in the mental health setting (10.2%) than in the primary care setting (3.8%). Of the patients screening positive for suicidal ideation in the mental health setting, 76.8% received a risk assessment, and 82.4% of those identified as being at high risk received lethal means counseling, compared with 43.2% and 82.4%, respectively, in primary care. CONCLUSIONS: Six health systems that implemented ZS showed a high level of variation in the proportions of patients receiving suicide screening and risk assessment and lethal means counseling. Two opportunities emerged for further study to increase frequency of these practices: expanding screening beyond patients with regular health care visits and implementing risk assessment with lethal means counseling in the primary care setting directly after a positive suicidal ideation screening.

Family cascade screening for equitable identification of familial hypercholesterolemia: study protocol for a hybrid effectiveness-implementation type III randomized controlled trial.

BACKGROUND: Familial hypercholesterolemia (FH) is a heritable disorder affecting 1.3 million individuals in the USA. Eighty percent of people with FH are undiagnosed, particularly minoritized populations including Black or African American people, Asian or Asian American people, and women across racial groups. Family cascade screening is an evidence-based practice that can increase diagnosis and improve health outcomes but is rarely implemented in routine practice, representing an important care gap. In pilot work, we leveraged best practices from behavioral economics and implementation science-including mixed-methods contextual inquiry with clinicians, patients, and health system constituents-to co-design two patient-facing implementation strategies to address this care gap: (a) an automated health system-mediated strategy and (b) a nonprofit foundation-mediated strategy with contact from a foundation-employed care navigator. This trial will test the comparative effectiveness of these strategies on completion of cascade screening for relatives of individuals with FH, centering equitable reach. METHODS: We will conduct a hybrid effectiveness-implementation type III randomized controlled trial testing the comparative effectiveness of two strategies for implementing cascade screening with 220 individuals with FH (i.e., probands) per arm identified from a large northeastern health system. The primary implementation outcome is reach, or the proportion of probands with at least one first-degree biological relative (parent, sibling, child) in the USA who is screened for FH through the study. Our secondary implementation outcomes include the number of relatives screened and the number of relatives meeting the American Heart Association criteria for FH. Our secondary clinical effectiveness outcome is post-trial proband cholesterol level. We will also use mixed methods to identify implementation strategy mechanisms for implementation strategy effectiveness while centering equity. DISCUSSION: We will test two patient-facing implementation strategies harnessing insights from behavioral economics that were developed collaboratively with constituents. This trial will improve our understanding of how to implement evidence-based cascade screening for FH, which implementation strategies work, for whom, and why. Learnings from this trial can be used to equitably scale cascade screening programs for FH nationally and inform cascade screening implementation efforts for other genetic disorders. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05750667. Registered 15 February 2023-retrospectively registered, https://clinicaltrials.gov/study/NCT05750667 .

How can a behavioral economics lens contribute to implementation science?

BACKGROUND: Implementation science in health is an interdisciplinary field with an emphasis on supporting behavior change required when clinicians and other actors implement evidence-based practices within organizational constraints. Behavioral economics has emerged in parallel and works towards developing realistic models of how humans behave and categorizes a wide range of features of choices that can influence behavior. We argue that implementation science can be enhanced by the incorporation of approaches from behavioral economics. Main body First, we provide a general overview of implementation science and ways in which implementation science has been limited to date. Second, we review principles of behavioral economics and describe how concepts from BE have been successfully applied to healthcare including nudges deployed in the electronic health record. For example, de-implementation of low-value prescribing has been supported by changing the default in the electronic health record. We then describe what a behavioral economics lens offers to existing implementation science theories, models and frameworks, including rich and realistic models of human behavior, additional research methods such as pre-mortems and behavioral design, and low-cost and scalable implementation strategies. We argue that insights from behavioral economics can guide the design of implementation strategies and the interpretation of implementation studies. Key objections to incorporating behavioral economics are addressed, including concerns about sustainment and at what level the strategies work. CONCLUSION: Scholars should consider augmenting implementation science theories, models, and frameworks with relevant insights from behavioral economics. By drawing on these additional insights, implementation scientists have the potential to boost efforts to expand the provision and availability of high quality care.