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While racial/ethnic disparities in blood pressure control are documented, few interventions have successfully reduced these gaps. Under-prescribing, lack of treatment intensification, and suboptimal follow-up care are thought to be central contributors. Electronic health record (EHR) tools may help address these barriers and may be enhanced with behavioral science techniques.To evaluate the impact of a multicomponent behaviorally-informed EHR-based intervention on blood pressure control.Reducing Ethnic and racial Disparities by improving Undertreatment, Control, and Engagement in Blood Pressure management with health information technology (REDUCE-BP) (NCT05030467) is a two-arm cluster-randomized hybrid type 1 pragmatic trial in a large multi-ethnic health care system. Twenty-four clinics (350 primary care providers [PCPs] and10,000 eligible patients) are assigned to either multi-component EHR-based intervention or usual care. Intervention clinic PCPs will receive several EHR tools designed to reduce disparities delivered at different points, including a: (1) dashboard of all patients visible upon logging on to the EHR displaying blood pressure control by race/ethnicity compared to their PCP peers and (2) set of tools in an individual patient's chart containing decision support to encourage treatment intensification, ordering home blood pressure measurement, interventions to address health-related social needs, default text for note documentation, and enhanced patient education materials. The primary outcome is patient-level change in systolic blood pressure over 12 months between arms; secondary outcomes include changes in disparities and other clinical outcomes.REDUCE-BP will provide important insights into whether an EHR-based intervention designed using behavioral science can improve hypertension control and reduce disparities.

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.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.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.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.

IntroductionAchieving optimal diabetes control requires several daily self-management behaviours, especially adherence to medication. Evidence supports the use of text messages to support adherence, but there remains much opportunity to improve their effectiveness. One key limitation is that message content has been generic. By contrast, reinforcement learning is a machine learning method that can be used to identify individuals’ patterns of responsiveness by observing their response to cues and then optimising them accordingly. Despite its demonstrated benefits outside of healthcare, its application to tailoring communication for patients has received limited attention. The objective of this trial is to test the impact of a reinforcement learning-based text messaging programme on adherence to medication for patients with type 2 diabetes.Methods and analysisIn the REinforcement learning to Improve Non-adherence For diabetes treatments by Optimising Response and Customising Engagement (REINFORCE) trial, we are randomising 60 patients with suboptimal diabetes control treated with oral diabetes medications to receive a reinforcement learning intervention or control. Subjects in both arms will receive electronic pill bottles to use, and those in the intervention arm will receive up to daily text messages. The messages will be individually adapted using a reinforcement learning prediction algorithm based on daily adherence measurements from the pill bottles. The trial’s primary outcome is average adherence to medication over the 6-month follow-up period. Secondary outcomes include diabetes control, measured by glycated haemoglobin A1c, and self-reported adherence. In sum, the REINFORCE trial will evaluate the effect of personalising the framing of text messages for patients to support medication adherence and provide insight into how this could be adapted at scale to improve other self-management interventions.Ethics and disseminationThis study was approved by the Mass General Brigham Institutional Review Board (IRB) (USA). Findings will be disseminated through peer-reviewed journals, clinicaltrials.gov reporting and conferences.Trial registration numberClinicaltrials.gov (NCT04473326).

ImportanceHypertension control remains suboptimal, particularly for Black and Hispanic or Latino patients. A need exists to improve hypertension management and design effective strategies to efficiently improve the quality of care in primary care, especially for these at-risk populations. Few studies have specifically explored perspectives on blood pressure management by primary care providers (PCPs) and patients.ObjectiveTo examine clinician and patient perspectives on barriers and facilitators to hypertension control within a racially and ethnically diverse health care system.Design, Setting, and ParticipantsThis qualitative study was conducted in a large urban US health care system from October 1, 2020, to March 31, 2021, among patients with a diagnosis of hypertension from a racially and ethnically diverse population, for a range of hypertension medication use hypertension control, as well as practicing PCPs. Analysis was conducted between June 2021 and February 2022 using immersion-crystallization methods.Main Outcomes and MeasuresPerspectives on managing blood pressure, including medication adherence and lifestyle, considerations for intensification, and experiences and gaps in using health information technology tools for hypertension, were explored using semistructured qualitative interviews. These cycles of review were continued until all data were examined and meaningful patterns were identified.ResultsInterviews were conducted with 30 participants: 15 patients (mean [SD] age, 58.6 [16.2] years; 10 women [67%] and 9 Black patients [60%]) and 15 clinicians (14 PCPs and 1 medical assistant; 8 women [53%]). Eleven patients (73%) had suboptimally controlled blood pressure. Participants reported a wide range of experiences with hypertension care, even within the same clinics and health care system. Five themes relevant to managing hypertension for racially and ethnically diverse patient populations in primary care were identified: (1) difficulty with self-management activities, especially lifestyle modifications; (2) hesitancy intensifying medications by both clinicians and patients; (3) varying the timing and follow-up after changes in medication; (4) variation in blood pressure self-monitoring recommendations and uptake; and (5) limited specific functionality of current health information technology tools.Conclusions and RelevanceIn this qualitative study of the views of PCPs and patients on hypertension control, the participants felt that more focus should be placed on lifestyle modifications than medications for hypertension, particularly for patients from racial and ethnic minority groups. Participants also expressed concerns about the existing functionality of health information technology tools to support increasingly asynchronous hypertension care. More intentional ways of supporting treatment intensification, self-care, and follow-up care are needed to improve hypertension management for racially and ethnically diverse populations in primary care.

While implicated in causing depression, no studies have examined the impact of montelukast on antidepressant effectiveness. We examined whether existing montelukast therapy was associated with acute antidepressant treatment failure (objective 1), and whether montelukast initiation was associated with depression relapse during maintenance antidepressant therapy (objective 2), relative to inhaled corticosteroid (ICS).Patients with asthma and depression were identified using national Veterans Health Administration data from 2007 to 2019. Objective 1: 12,109 patients initiated an antidepressant after receiving montelukast or ICS for 6 months. The primary outcome was acute antidepressant treatment failure, defined as subsequent initiation of a new antidepressant or augmenting agent within 6 months. Objective 2: 14,673 patients initiated montelukast or ICS after receiving stable antidepressant monotherapy for 6 months. The primary outcome of depression relapse was defined by a subsequent change in the pre-existing maintenance antidepressant regimen within 6 months. Both objectives employed a retrospective cohort design with log-binomial regression.Objective 1: Acute antidepressant failure was observed in 21.3% (628/2943) and 22.3% (2044/9166) of patients receiving montelukast versus ICS, respectively. Relative risk in adjusted analyses was 0.98 (95% CI: 0.90, 1.07). Objective 2: Depression relapse was observed in 24.4% (288/1182) and 22.4% (3027/13,491) of patients initiating montelukast versus ICS, respectively. Relative risk in adjusted analyses was 1.08 (95% CI: 0.96, 1.20) within 6 months and 1.50 (95% CI: 1.16, 1.93) within 45 days.Discontinuation of existing montelukast therapy is unnecessary when initiating antidepressants. However, potential evidence for depression relapse following montelukast initiation warrants additional investigation.

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. CLINICALTRIAL ClinicalTrials.gov NCT04668248; https://clinicaltrials.gov/ct2/show/NCT04668248 INTERNATIONAL REGISTERED REPORT PRR1-10.2196/31464

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

BACKGROUND Individuals with diabetes need regular support to help them manage their diabetes on their own, ideally delivered via mechanisms that they already use, such as their mobile phones. One reason for the modest effectiveness of prior technology-based interventions may be that the patient perspective has been insufficiently incorporated. OBJECTIVE This study aims to understand patients’ preferences for mobile health (mHealth) technology and how that technology can be integrated into patients’ routines, especially with regard to medication use. METHODS We conducted semistructured qualitative individual interviews with patients with type 2 diabetes from an urban health care system to elicit and explore their perspectives on diabetes medication–taking behaviors, daily patterns of using mobile technology, use of mHealth technology for diabetes care, acceptability of text messages to support medication adherence, and preferred framing of information within text messages to support diabetes care. The interviews were digitally recorded and transcribed. The data were analyzed using codes developed by the study team to generate themes, with representative quotations selected as illustrations. RESULTS We conducted interviews with 20 participants, of whom 12 (60%) were female and 9 (45%) were White; in addition, the participants’ mean glycated hemoglobin A1c control was 7.8 (SD 1.1). Overall, 5 key themes were identified: patients try to incorporate cues into their routines to help them with consistent medication taking; many patients leverage some form of technology as a cue to support adherence to medication taking and diabetes self-management behaviors; patients value simplicity and integration of technology solutions used for diabetes care, managing medications, and communicating with health care providers; some patients express reluctance to rely on mobile technology for these diabetes care behaviors; and patients believe they prefer positively framed communication, but communication preferences are highly individualized. CONCLUSIONS The participants expressed some hesitation about using mobile technology in supporting diabetes self-management but have largely incorporated it or are open to incorporating it as a cue to make medication taking more automatic and less burdensome. When using technology to support diabetes self-management, participants exhibited individualized preferences, but overall, they preferred simple and positively framed communication. mHealth interventions may be improved by focusing on integrating them easily into daily routines and increasing the customization of content.