"How" Versus "Why" Messaging to Increase Uptake of Booster Vaccination Against COVID-19: Results of a Pragmatic Randomized Trial.

BACKGROUND: Messages aimed at increasing uptake of vaccines have been modestly successful, perhaps in part because they often focus on why individuals should receive a vaccine. Construal Level Theory posits that messages emphasizing "how" to get a vaccine may be more effective at encouraging vaccination than emphasizing "why." This message framing may be particularly important for COVID-19 booster acceptance. OBJECTIVE: To determine if pre-visit patient portal messages designed using Construal Level Theory increase rates of COVID-19 booster vaccination. DESIGN AND INTERVENTIONS: This 3-arm randomized trial was conducted across three large, diverse primary care clinics in Massachusetts between February and May 2022, testing the impact of "how" versus "why" framed pre-visit messages versus no messages ("usual care"). Messages were sent by patient portal two business days before a visit. PARTICIPANTS: Adults with upcoming primary care visits who had electronic health record evidence of receiving their initial COVID-19 vaccination series but not a booster dose. MAIN MEASURES: Receipt of a COVID-19 booster vaccination after the message was sent through the visit date (primary outcome) or 6 weeks (secondary outcome). KEY RESULTS: A total of 3665 patients were randomized (mean age: 53.5 years (SD: 17.3), 59% female, 65.2% White, 26.6% Hispanic), with 1249 to "how" 1199 to "why," and 1217 to usual care arms. Except for clinic and preferred language, characteristics were well balanced across arms. Rates of COVID-19 booster were 13.6% (usual care), 11.7% ("how") (odds ratio (OR) "how" vs usual care: 0.87, 95%CI: 0.67-1.14), and 13.7% ("why") ("why" vs usual care: OR: 1.01, 95%CI: 0.81-1.28). At 6 weeks, "why" outperformed "how" for vaccination (OR: 1.26, 95%CI: 1.06-1.49), with no difference versus usual care. CONCLUSIONS: We found no differences on visit booster receipt after single pre-visit portal messages designed using Construal Level Theory. Further studies to identify effective messaging interventions are needed, especially as additional doses are recommended. CLINICAL TRIAL REGISTRATION: This trial is registered at clinicaltrials.gov, ID: NCT04871776 . Initial release occurred 04/30/2021.

Prescribing decision making by medical residents on night shifts: A qualitative study.

INTRODUCTION: Prescribing of medications with well-known adverse effects, like antipsychotics or benzodiazepines, during hospitalisation is extremely common despite guideline recommendations against their use. Barriers to optimal prescribing, including perceived pressure from allied health professionals and fatigue, may be particularly pronounced for less experienced medical residents, especially during night shifts when these medications are often prescribed. Under these circumstances, physicians may be more likely to use 'quick', often referred to as System 1 choices, rather than 'considered' System 2 strategies for decisions. Understanding how medical residents use, these different cognitive approaches could help develop interventions to improve prescribing. METHODS: To understand decision-making and contextual contributors that influence suboptimal prescribing during night coverage by medical residents, we conducted semi-structured qualitative interviews with residents in general medicine inpatient settings. The interviews elicited perspectives on shift routines, stressful situations, factors influencing prescribing decision making and hypothetical measures that could improve prescribing. Interviews were audio-recorded and transcribed. Data were analysed using codes developed by the team to generate themes using immersion/crystallisation approaches. RESULTS: We conducted interviews with 21 medical residents; 47% were female, 43% were White, and 43% were Asian. We identified five key themes: (i) time pressures affecting prescribing decisions, (ii) fears of judgement by senior physicians and peers and being responsible for patient outcomes, (iii) perceived pressure from nursing staff, amplified by nurses' greater experience, (iv) clinical acuity as a key factor influencing prescribing, and (v) strategies to improve communication between members of the care team, like ensuring adequate hand-off by day teams. CONCLUSION: Medical residents highlighted numerous contextual factors that promote quick thinking rather than slower thinking when prescribing on night shifts, particularly time constraints, perceived pressure and patient clinical acuity. Interventions aimed at reducing prescribing should address how to manage stress and perceived pressure in decision making.

Behavioral Design Teams: The Next Frontier in Clinical Delivery Innovation?

Issue: A deep understanding of human behavior is critical to designing effective health care delivery models, tools, and processes. Currently, however, few mechanisms exist to systematically apply insights about human behavior to improve health outcomes. Behavioral design teams (BDTs) are a successful model for applying behavioral insights within an organization. Already operational within government, this model can be adapted to function in a health care setting. Goal: To explore how BDTs could be applied to clinical care delivery and review models for integrating these teams within health care organizations. Methods: Interviews with experts in clinical delivery innovation and applied behavioral science, as well as leaders of existing government BDTs. Findings and Conclusions: BDTs are most effective when they enjoy top-level executive support, are co-led by a domain expert and behavioral scientist, collaborate closely with key staff and departments, have access to data and IT support, and operate a portfolio of projects. BDTs could be embedded in health care organizations in multiple ways, including in or just below the CEO's office, within a quality improvement unit, or within an internal innovation center. When running a portfolio, BDTs achieve a greater number and diversity of insights at lower costs. They also become a platform for strategic learning and scaling.

Pragmatic trial evaluating the impact of simulation training on high-risk prescribing to older adults by junior physicians.

BACKGROUND: High-risk medications like benzodiazepines, sedative hypnotics, and antipsychotics are commonly prescribed for hospitalized older adults, despite guidelines recommending avoidance. Prior interventions have not fully addressed how physicians make such prescribing decisions, particularly when experiencing stress or cognitive overload. Simulation training may help improve prescribing decision-making but has not been evaluated for overprescribing. METHODS: In this two-arm pragmatic trial, we randomized 40 first-year medical resident physicians (i.e., interns) on inpatient general medicine services at an academic medical center to either intervention (a 40-minute immersive simulation training) or control (online educational training) groups. The primary outcome was the number of new benzodiazepine, sedative hypnotic, or antipsychotic orders for treatment-naïve older adults during hospitalization. Secondary outcomes included the same outcome by all providers, being discharged on one of the medications, and orders for related or control medications. Outcomes were measured using electronic health record data over each intern's service period (~2 weeks). Outcomes were evaluated using generalized estimating equations, adjusting for clustering. RESULTS: In total, 522 treatment-naïve older adult patients were included in analyses. Over follow-up, interns prescribed ≥1 high-risk medication for 13 (4.9%) intervention patients and 13 (5.0%) control patients. The intervention led to no difference in the number of new prescriptions (Rate Ratio [RR]: 0.85, 95%CI: 0.31-2.35) versus control and no difference in secondary outcomes. In secondary analyses, intervention interns wrote significantly fewer "as-needed" ("PRN") order types for the high-risk medications (RR: 0.29, 95%CI: 0.08-0.99), and instead tended to write more "one-time" orders than control interns, though this difference was not statistically significant (RR: 2.20, 95%CI: 0.60-7.99). CONCLUSIONS: Although this simulation intervention did not impact total high-risk prescribing for hospitalized older adults, it did influence how the interns prescribed, resulting in fewer PRN orders, suggesting possibly greater ownership of care. Future interventions should consider this insight and implementation lessons raised. TRIAL REGISTRATION: Clinicaltrials.gov(NCT04668248).

Overcoming Decisional Gaps in High-Risk Prescribing by Junior Physicians Using Simulation-Based Training: Protocol for a Randomized Controlled Trial.

BACKGROUND: Gaps between rational thought and actual decisions are increasingly recognized as a reason why people make suboptimal choices in states of heightened emotion, such as stress. These observations may help explain why high-risk medications continue to be prescribed to acutely ill hospitalized older adults despite widely accepted recommendations against these practices. Role playing and other efforts, such as simulation training, have demonstrated benefits to help people avoid decisional gaps but have not been tested to reduce overprescribing of high-risk medications. OBJECTIVE: This study aims to evaluate the impact of a simulation-based training program designed to address decisional gaps on prescribing of high-risk medications compared with control. METHODS: In this 2-arm pragmatic trial, we are randomizing at least 36 first-year medical resident physicians (ie, interns) who provide care on inpatient general medicine services at a large academic medical center to either intervention (simulation-based training) or control (online educational training). The intervention comprises a 40-minute immersive individual simulation training consisting of a reality-based patient care scenario in a simulated environment at the beginning of their inpatient service rotation. The simulation focuses on 3 types of high-risk medications, including benzodiazepines, antipsychotics, and sedative hypnotics (Z-drugs), in older adults, and is specifically designed to help the physicians identify their reactions and prescribing decisions in stressful situations that are common in the inpatient setting. The simulation scenario is followed by a semistructured debriefing with an expert facilitator. The trial's primary outcome is the number of medication doses for any of the high-risk medications prescribed by the interns to patients aged 65 years or older who were not taking one of the medications upon admission. Secondary outcomes include prescribing by all providers on the care team, being discharged on 1 of the medications, and prescribing of related medications (eg, melatonin, trazodone), or the medications of interest for the control intervention. These outcomes will be measured using electronic health record data. RESULTS: Recruitment of interns began on March 29, 2021. Recruitment for the trial ended in Q42021, with follow-up completed by Q12022. CONCLUSIONS: This trial will evaluate the impact of a simulation-based training program designed using behavioral science principles on prescribing of high-risk medications by junior physicians. If the intervention is shown to be effective, this approach could potentially be reproducible by others and for a broader set of behaviors. TRIAL REGISTRATION: ClinicalTrials.gov NCT04668248; https://clinicaltrials.gov/ct2/show/NCT04668248. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/31464.

Nudging Emergency Department-Initiated Addiction Treatment.

OBJECTIVES: When initiated in the Emergency Department (ED), medication for addiction treatment (MAT) with buprenorphine improves outcomes, increases engagement in addiction treatment and decreases the use of inpatient addiction treatment services. Unfortunately, initiating MAT in the ED is not yet standard practice. We assessed the impact of the addition of a multipart behavioral science-based intervention to increase opioid use disorder (OUD)-related treatments prescribed in the ED. METHODS: Our ED initiated a campaign to help ED faculty obtain their DEA-X waiver required to prescribe buprenorphine. In parallel, we implemented 2 ED-initiated buprenorphine treatment pathways. We then conducted a two-stage qualitative process informed by behavioral science to identify key barriers to physician use of the MAT protocol. Using these insights, we developed 4 behavioral science-based interventions. To assess the impact of the interventions on the number of OUD-related treatments per day among patients meeting the inclusion criteria we compared the number of OUD-related treatments per day before versus after the interventions began using t tests. Then, in our primary model, we estimated the causal effect of the behavioral interventions using a regression discontinuity in time approach. RESULTS: Across the entire year study period, there is an increase in OUD-related treatment after the interventions begin, driven by greater use of ambulatory referral orders. The unadjusted mean difference in any OUD treatments per day pre- versus post-intervention increased by 0.80 (95% confidence interval [CI]: 0.04, 1.56; P = 0.039) whereas the number of ambulatory referral orders placed increased by 0.82 (95% CI: 0.48,1.16; P < 0.001). Using the 120-day study window and an ordinary least squares regression discontinuity in time model, the 4-part intervention increased the number of patients receiving any opioid treatment in the ED by 1.6 additional treatments per day (95% CI: 0.04, 3.19; P = 0.045). CONCLUSIONS: To support our protocol and increase the provision of ED-MAT, we implemented 1 patient-facing and 3 provider-facing interventions rooted in behavioral science principles. Our results show that this pack of behavioral science interventions increased the likelihood that ED providers offer MAT to patients with OUD.

Randomised controlled trial targeting habit formation to improve medication adherence to daily oral medications in patients with gout.

INTRODUCTION: Medication adherence for patients with chronic conditions such as gout, a debilitating form of arthritis that requires daily medication to prevent flares, is a costly problem. Existing interventions to improve medication adherence have only been moderately effective. Habit formation theory is a promising strategy to improve adherence. The cue-reward-repetition principle posits that habits are formed by repeatedly completing an activity after the same cue and having the action rewarded every time. Over time, cues become increasingly important whereas rewards become less salient because the action becomes automatic. Leveraging the cue-reward-repetition principle could improve adherence to daily gout medications. METHODS AND ANALYSIS: This three-arm parallel randomised controlled trial tests an adaptive intervention that leverages the repetition cue-reward principle. The trial will began recruitment in August 2021 in Boston, Massachusetts, USA. Eligible patients are adults with gout who have been prescribed a daily oral medication for gout and whose most recent uric acid is above 6 mg/dL. Participants will be randomised to one of three arms and given electronic pill bottles. In the two intervention arms, participants will select a daily activity to link to their medication-taking (cue) and a charity to which money will be donated every time they take their medication (reward). Participants in Arm 1 will receive reminder texts about their cue and their charity reward amount will be US$0.50 per day of medication taken. Arm 2 will be adaptive; participants will receive a US$0.25 per adherent-day and no reminder texts. If their adherence is <75% 6 weeks postrandomisation, their reward will increase to US$0.50 per adherent-day and they will receive reminder texts. The primary outcome is adherence to gout medications over 18 weeks. ETHICS AND DISSEMINATION: This trial has ethical approval in the USA. Results will be published in a publicly accessible peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT04776161.

Rationale and design of the Novel Uses of adaptive Designs to Guide provider Engagement in Electronic Health Records (NUDGE-EHR) pragmatic adaptive randomized trial: a trial protocol.

BACKGROUND: The prescribing of high-risk medications to older adults remains extremely common and results in potentially avoidable health consequences. Efforts to reduce prescribing have had limited success, in part because they have been sub-optimally timed, poorly designed, or not provided actionable information. Electronic health record (EHR)-based tools are commonly used but have had limited application in facilitating deprescribing in older adults. The objective is to determine whether designing EHR tools using behavioral science principles reduces inappropriate prescribing and clinical outcomes in older adults. METHODS: The Novel Uses of Designs to Guide provider Engagement in Electronic Health Records (NUDGE-EHR) project uses a two-stage, 16-arm adaptive randomized pragmatic trial with a "pick-the-winner" design to identify the most effective of many potential EHR tools among primary care providers and their patients ≥ 65 years chronically using benzodiazepines, sedative hypnotic ("Z-drugs"), or anticholinergics in a large integrated delivery system. In stage 1, we randomized providers and their patients to usual care (n = 81 providers) or one of 15 EHR tools (n = 8 providers per arm) designed using behavioral principles including salience, choice architecture, or defaulting. After 6 months of follow-up, we will rank order the arms based upon their impact on the trial's primary outcome (for both stages): reduction in inappropriate prescribing (via discontinuation or tapering). In stage 2, we will randomize (a) stage 1 usual care providers in a 1:1 ratio to one of the up to 5 most promising stage 1 interventions or continue usual care and (b) stage 1 providers in the unselected arms in a 1:1 ratio to one of the 5 most promising interventions or usual care. Secondary and tertiary outcomes include quantities of medication prescribed and utilized and clinically significant adverse outcomes. DISCUSSION: Stage 1 launched in October 2020. We plan to complete stage 2 follow-up in December 2021. These results will advance understanding about how behavioral science can optimize EHR decision support to improve prescribing and health outcomes. Adaptive trials have rarely been used in implementation science, so these findings also provide insight into how trials in this field could be more efficiently conducted. TRIAL REGISTRATION: Clinicaltrials.gov ( NCT04284553 , registered: February 26, 2020).