Clinicians' use of Health Information Exchange technologies for medication reconciliation in the U.S. Department of Veterans Affairs: a qualitative analysis.

BACKGROUND: Medication reconciliation is essential for optimizing medication use. In part to promote effective medication reconciliation, the Department of Veterans Affairs (VA) invested substantial resources in health information exchange (HIE) technologies. The objectives of this qualitative study were to characterize VA clinicians' use of HIE tools for medication reconciliation in their clinical practice and to identify facilitators and barriers. METHODS: We recruited inpatient and outpatient prescribers (physicians, nurse practitioners, physician assistants) and pharmacists at four geographically distinct VA medical centers for observations and interviews. Participants were observed as they interacted with HIE or medication reconciliation tools during routine work. Participants were interviewed about clinical decision-making pertaining to medication reconciliation and use of HIE tools, and about barriers and facilitators to use of the tools. Qualitative data were analyzed via inductive and deductive approaches using a priori codes. RESULTS: A total of 63 clinicians participated. Over half (58%) were female, and the mean duration of VA clinical experience was 7 (range 0-32) years. Underlying motivators for clinicians seeking data external to their VA medical center were having new patients, current patients receiving care from an external institution, and clinicians' concerns about possible medication discrepancies among institutions. Facilitators for using HIE software were clinicians' familiarity with the HIE software, clinicians' belief that medication information would be available within HIE, and their confidence in the ability to find HIE medication-related data of interest quickly. Six overarching barriers to HIE software use for medication coordination included visual clutter and information overload within the HIE display; challenges with HIE interface navigation; lack of integration between HIE and other electronic health record interfaces, necessitating multiple logins and application switching; concerns with the dependability of HIE medication information; unfamiliarity with HIE tools; and a lack of HIE data from non-VA facilities. CONCLUSIONS: This study is believed to be the first to qualitatively characterize clinicians' HIE use with respect to medication reconciliation. Results inform recommendations to optimize HIE use for medication management activities. We expect that healthcare organizations and software vendors will be able to apply the findings to develop more effective and usable HIE information displays.

Effect of Ventilator Mode on Ventilator-Free Days in Critically Ill Adults: A Randomized Trial.

Rationale: For critically ill adults receiving invasive mechanical ventilation, the ventilator mode determines how breaths are delivered. Whether the choice of ventilator mode affects outcomes for critically ill patients is unknown. To compare the effects of three common ventilator modes (volume control, pressure control, and adaptive pressure control) on death and duration of mechanical ventilation. Methods: We conducted a pragmatic, cluster-randomized, crossover trial among adults receiving invasive mechanical ventilation in a medical ICU between November 1, 2022 and July 31, 2023. Each month, patients in the participating unit were assigned to receive volume control, pressure control, or adaptive pressure control during continuous mandatory ventilation. The primary outcome was ventilator-free days through 28 days. Results: Among 566 patients included in the primary analysis, the median number of ventilator-free days was 23 [IQR, 0-26] in the volume control group, 22 [0-26] in the pressure control group, and 24 [0-26] in the adaptive pressure control group (P=0.60). The median tidal volume was similar in the three groups, but the percentage of breaths larger than 8mL/kg of predicted body weight differed between volume control (median, 4.0%; IQR, 0.0-14.1), pressure control (10.6%; 0.0-31.5), and adaptive pressure control (4.7%; 0.0-19.2). Incidences of hypoxemia, acidemia, and barotrauma were similar in the three groups. Conclusions: Among critically ill adults receiving invasive mechanical ventilation, the use of volume control, pressure control, or adaptive pressure control did not affect the number of ventilator-free days, however, confidence intervals included differences that may be clinically meaningful.

Days Not at Home: Association of Vulnerability with Healthcare Utilization After Hospitalization for Heart Failure.

BACKGROUND: Heart failure (HF) hospitalizations are characterized by vulnerability in functioning and frequent post-discharge healthcare utilization in both acute and post-acute settings. OBJECTIVE: To determine, in patients hospitalized for decompensated HF, the association of vulnerability with (1) detailed forms of post-discharge healthcare utilization, and (2) days spent away from home after initial hospital discharge. DESIGN: Secondary analysis of a prospective longitudinal cohort study from a single-center academic institution in the USA. PARTICIPANTS: Adults admitted with acute decompensated HF who were discharged alive. MAIN MEASURES: The Vulnerable Elders Survey 13 (VES-13) measured functional vulnerability at baseline. The primary outcome was the Highest Healthcare Utilization (HHU) 90 days post-discharge, from the following ordered categories: at home, emergency room visit, skilled nursing facility stay, hospital readmission, or death. The secondary outcome was the proportion of days not at home (DNAH) within the first 90 days. Analyses were performed using a partial proportional odds model with adjustment for demographics and health characteristics. KEY RESULTS: A total of 806 patients were included with median age 65, interquartile range [IQR] 55-73 years. Fewer than half (N = 345 [43%]) of patients remained alive and at home during 90-day follow-up. There were 286 [35%] hospital readmissions and 70 [8.7%] participants died. The median DNAH was 3 [IQR 0-16]. Increased vulnerability was associated with (1) HHU, (2) higher odds of utilizing healthcare or dying versus being at home alive 90 days post-discharge (OR 1.81 [95% CI, 1.35, 2.42]), and (3) higher odds of DNAH in the first 90 days (OR 1.55 [95% CI, 1.27, 1.89]). CONCLUSIONS: In this cohort of patients hospitalized for decompensated HF, vulnerability predicted higher levels of healthcare utilization, as well as total days not at home in the 90 days following hospitalization. Vulnerability may have clinical applications to identify patients at greatest need for comprehensive, patient-centered discharge planning.

A real-time prognostic model for venous thromboembolic events among hospitalized adults.

Background: Hospital-acquired venous thromboembolism (HA-VTE) is a leading cause of morbidity and mortality among hospitalized adults. Guidelines recommend use of a risk-prediction model to estimate HA-VTE risk for individual patients. Extant models do not perform well for broad patient populations and are not conducive to automation in clinical practice. Objectives: To develop an automated, real-time prognostic model for venous thromboembolism during hospitalization among all adult inpatients using readily available data from the electronic health record. Methods: The derivation cohort included inpatient hospitalizations ("encounters") for patients ≥16 years old at Vanderbilt University Medical Center between 2018 and 2020 (n = 132,330). HA-VTE events were identified using International Classification of Diseases, 10th Revision, codes. The prognostic model was developed using least absolute shrinkage and selection operator regression. Temporal external validation was performed in a validation cohort of encounters between 2021 and 2022 (n = 62,546). Prediction performance was assessed by discrimination accuracy (C statistic) and calibration (integrated calibration index). Results: There were 1187 HA-VTEs in the derivation cohort (9.0 per 1000 encounters) and 864 in the validation cohort (13.8 per 1000 encounters). The prognostic model included 25 variables, with placement of a central line among the most important predictors. Prediction performance of the model was excellent (C statistic, 0.891; 95% CI, 0.882-0.900; integrated calibration index, 0.001). The model performed similarly well across subgroups of patients defined by age, sex, race, and type of admission. Conclusion: This fully automated prognostic model uses readily available data from the electronic health record, exhibits superior prediction performance compared with existing models, and generates granular risk stratification in the form of a predicted probability of HA-VTE for each patient.

Determinants of appropriate antibiotic and NSAID prescribing in unscheduled outpatient settings in the veterans health administration.

BACKGROUND: Despite efforts to enhance the quality of medication prescribing in outpatient settings, potentially inappropriate prescribing remains common, particularly in unscheduled settings where patients can present with infectious and pain-related complaints. Two of the most commonly prescribed medication classes in outpatient settings with frequent rates of potentially inappropriate prescribing include antibiotics and nonsteroidal anti-inflammatory drugs (NSAIDs). In the setting of persistent inappropriate prescribing, we sought to understand a diverse set of perspectives on the determinants of inappropriate prescribing of antibiotics and NSAIDs in the Veterans Health Administration. METHODS: We conducted a qualitative study guided by the Consolidated Framework for Implementation Research and Theory of Planned Behavior. Semi-structured interviews were conducted with clinicians, stakeholders, and Veterans from March 1, 2021 through December 31, 2021 within the Veteran Affairs Health System in unscheduled outpatient settings at the Tennessee Valley Healthcare System. Stakeholders included clinical operations leadership and methodological experts. Audio-recorded interviews were transcribed and de-identified. Data coding and analysis were conducted by experienced qualitative methodologists adhering to the Consolidated Criteria for Reporting Qualitative Studies guidelines. Analysis was conducted using an iterative inductive/deductive process. RESULTS: We conducted semi-structured interviews with 66 participants: clinicians (N = 25), stakeholders (N = 24), and Veterans (N = 17). We identified six themes contributing to potentially inappropriate prescribing of antibiotics and NSAIDs: 1) Perceived versus actual Veterans expectations about prescribing; 2) the influence of a time-pressured clinical environment on prescribing stewardship; 3) Limited clinician knowledge, awareness, and willingness to use evidence-based care; 4) Prescriber uncertainties about the Veteran condition at the time of the clinical encounter; 5) Limited communication; and 6) Technology barriers of the electronic health record and patient portal. CONCLUSIONS: The diverse perspectives on prescribing underscore the need for interventions that recognize the detrimental impact of high workload on prescribing stewardship and the need to design interventions with the end-user in mind. This study revealed actionable themes that could be addressed to improve guideline concordant prescribing to enhance the quality of prescribing and to reduce patient harm.

Protocol and Statistical Analysis Plan for the Mode of Ventilation During Critical Illness (MODE) Trial.

BACKGROUND: For every critically ill adult receiving invasive mechanical ventilation, clinicians must select a mode of ventilation. The mode of ventilation determines whether the ventilator directly controls the tidal volume or the inspiratory pressure. Newer hybrid modes allow clinicians to set a target tidal volume; the ventilator controls and adjusts the inspiratory pressure. A strategy of low tidal volumes and low plateau pressure improves outcomes, but the optimal mode to achieve these targets is not known. RESEARCH QUESTION: Can a cluster-randomized trial design be used to assess whether the mode of mandatory ventilation affects the number of days alive and free of invasive mechanical ventilation among critically ill adults? STUDY DESIGN AND METHODS: The Mode of Ventilation During Critical Illness (MODE) trial is a cluster-randomized, multiple-crossover pilot trial being conducted in the medical ICU at an academic center. The MODE trial compares the use of volume control, pressure control, and adaptive pressure control. The study ICU is assigned to a single-ventilator mode (volume control vs pressure control vs adaptive pressure control) for continuous mandatory ventilation during each 1-month study block. The assigned mode switches every month in a randomly generated sequence. The primary outcome is ventilator-free days to study day 28, defined as the number of days alive and free of invasive mechanical ventilation from the final receipt of mechanical ventilation to 28 days after enrollment. Enrollment began November 1, 2022, and will end on July 31, 2023. RESULTS: This manuscript describes the protocol and statistical analysis plan for the MODE trial of ventilator modes comparing volume control, pressure control, and adaptive pressure control. INTERPRETATION: Prespecifying the full statistical analysis plan prior to completion of enrollment increases rigor, reproducibility, and transparency of the trial results. CLINICAL TRIAL REGISTRATION: The trial was registered with clinicaltrials.gov on October 3, 2022, before initiation of patient enrollment on November 1, 2022 (ClinicalTrials.gov identifier: NCT05563779).

Emergency department visits and hospital readmissions after a deprescribing intervention among hospitalized older adults.

BACKGROUND: Deprescribing is the planned/supervised method of dose reduction or cessation of medications that might be harmful, or no longer be beneficial. Though benefits of deprescribing are debatable in improving clinical outcomes, it has been associated with decreased number of potentially inappropriate medications, which may potentially reduce the risk of adverse events among hospitalized older adults. With unclear evidence for deprescribing in this population, this study aimed to examine time-to-first unplanned healthcare utilization, which included 90-day emergency department (ED) visits or hospital readmission and associated predictors, during a deprescribing intervention. METHODS: A secondary data analysis of a clinical trial (Shed-MEDS NCT02979353) was performed. Cox regression was used to compare the time-to-first 90-day ED visit/readmission/death from hospital discharge for the intervention and control groups. Additionally, we performed exploratory analysis of predictors (comorbidities, functional health status, drug burden index (DBI), hospital length of stay, health literacy, food insecurity, and financial burden) associated with the time-to-first 90-day ED visit/readmission/death. RESULTS: The hazard of first 90-day ED visits/readmissions/death was 15% lower in the intervention versus the control group (95% CI: 0.61-1.19, p = 0.352, respectively); however, this difference was not statistically significant. For every additional number of comorbidities (Hazard ratio (HR): 1.12, 95% CI: 1.04-1.21) and each additional day of hospital length of stay (HR: 1.04, 95% CI: 1.01-1.07) were significantly associated with a higher hazard of 90-day ED visit/readmission/death in the intervention group; whereas for each unit of increase in pre-hospital DBI score (HR: 1.08 and HR 1.16, respectively) was significantly associated with a higher hazard of 90-day ED visit/readmission/death in the control group. CONCLUSIONS: The intervention and control groups had comparable time-to-first 90-day ED visit/readmission/death during a deprescribing intervention. This finding suggests that deprescribing did not result in a higher risk of ED visit/readmission/death during the 90-day period following hospital discharge.

Medication Discrepancies among Older Hospitalized Adults Discharged from Post-Acute Care Facilities to Home.

OBJECTIVES: The epidemiology of medication discrepancies during transitions from post-acute care (PAC) to home is poorly described. We sought to describe the frequency and types of medication discrepancies among hospitalized older adults transitioning from PAC to home. DESIGN: A nested cohort analysis. SETTING AND PARTICIPANTS: Included participants enrolled in a patient-centered deprescribing trial, for patients (aged ≥50 years and taking at least 5 medications) transitioning from one of 22 PACs to home. METHODS: We assessed demographic and medication measures at the initial hospitalization. The primary outcome measure was medication discrepancies, with the PAC discharge list serving as reference for comparison to the participant's self-reported medication list at 7 days following PAC discharge. Discrepancies were categorized as additions, omissions, and dose discrepancies and were organized by common medication classes and risk of harm (eg, 2015 Beers Criteria). Ordinal logistic regression assessed for patient risk factors for PAC discharge discrepancy count. RESULTS: A total of 184 participants had 7-day PAC discharge medication data. Participants were predominately female (67%) and Caucasian (83%) with a median of 16 prehospital medications [interquartile range (IQR) 11, 20]. At the 7-day follow-up, 98% of participants had at least 1 medication discrepancy, with a median number of 7 medication discrepancies (IQR 4, 10) per person, 4 (IQR 2, 6) of which were potentially inappropriate medications as defined by the Beers Criteria. Higher medication discrepancies at index hospital admission and receipt of caregiver assistance with medications were 2 key predictors of medication discrepancies in the week after PAC discharge to home. CONCLUSIONS AND IMPLICATIONS: Older patients transitioning home from a PAC facility are at high risk for medication discrepancies. This study underscores the need for interventions targeted at this overlooked transition period, especially as patients resume responsibility for managing their own medications after both a hospital and PAC stay.

Patient-reported predictors of postdischarge mortality after cardiac hospitalization.

BACKGROUND: Adults hospitalized for cardiovascular events are at high risk for postdischarge mortality. Screening of psychosocial risk is prioritized by the Joint Commission. We tested whether key patient-reported psychosocial and behavioral measures could predict posthospitalization mortality in a cohort of adults hospitalized for a cardiovascular event. METHODS: We conducted a prospective cohort study to test the prognostic utility of validated patient-reported measures, including health literacy, social support, health behaviors and disease management, and socioeconomic status. Cox survival analyses of mortality were conducted over a median of 3.5 years. RESULTS: Among 2977 adults hospitalized for either acute coronary syndrome or acute decompensated heart failure, the mean age was 53 years, and 60% were male. After adjusting for demographic, clinical, and other psychosocial factors, mortality risk was greatest among patients who reported being unemployed (hazard ratio [HR]: 1.99, 95% confidence interval [CI]): 1.30-3.06), retired (HR: 2.14, 95% CI: 1.60-2.87), or unable to work due to disability (HR: 2.36, 95% CI: 1.73-3.21), as compared to those who were employed. Patient-reported perceived health competence (PHCS-2) and exercise frequency were also associated with mortality risk after adjusting for all other variables (HR: 0.86, 95% CI: 0.73-1.00 per four-point increase in PHCS-2; HR: 0.86, 95% CI: 0.77-0.96 per 3-day increase in exercise frequency, respectively). CONCLUSIONS: Patient-reported measures of employment status, perceived health competence, and exercise frequency independently predict mortality after a cardiac hospitalization. Incorporating these brief, valid measures into hospital-based screening may help with prognostication and targeting patients for resources during post-discharge transitions of care.

Health Literacy-Informed Communication to Reduce Discharge Medication Errors in Hospitalized Children: A Randomized Clinical Trial.

Importance: Inadequate communication between caregivers and clinicians at hospital discharge contributes to medication dosing errors in children. Health literacy-informed communication strategies during medication counseling can reduce dosing errors but have not been tested in the pediatric hospital setting. Objective: To test a health literacy-informed communication intervention to decrease liquid medication dosing errors compared with standard counseling in hospitalized children. Design, Setting, and Participants: This parallel, randomized clinical trial was performed from June 22, 2021, to August 20, 2022, at a tertiary care, US children's hospital. English- and Spanish-speaking caregivers of hospitalized children 6 years or younger prescribed a new, scheduled liquid medication at discharge were included in the analysis. Interventions: Permuted block (n = 4) randomization (1:1) to a health literacy-informed discharge medication communication bundle (n = 99) compared with standard counseling (n = 99). A study team member delivered the intervention consisting of a written, pictogram-based medication instruction sheet, teach back (caregivers state information taught), and demonstration of dosing with show back (caregivers show how they would draw the liquid medication in the syringe). Main Outcome and Measures: Observed dosing errors, assessed using a caregiver-submitted photograph of their child's medication-filled syringe and expressed as the percentage difference from the prescribed dose. Secondary outcomes included caregiver-reported medication knowledge. Outcome measurements were blinded to participant group assignment. Results: Among 198 caregivers randomized (mean [SD] age, 31.4 [6.5] years; 186 women [93.9%]; 36 [18.2%] Hispanic or Latino and 158 [79.8%] White), the primary outcome was available for 151 (76.3%). The observed mean (SD) percentage dosing error was 1.0% (2.2 percentage points) among the intervention group and 3.3% (5.1 percentage points) among the standard counseling group (absolute difference, 2.3 [95% CI, 1.0-3.6] percentage points; P < .001). Twenty-four of 79 caregivers in the intervention group (30.4%) measured an incorrect dose compared with 39 of 72 (54.2%) in the standard counseling group (P = .003). The intervention enhanced caregiver-reported medication knowledge compared with the standard counseling group for medication dose (71 of 76 [93.4%] vs 55 of 69 [79.7%]; P = .03), duration of administration (65 of 76 [85.5%] vs 49 of 69 [71.0%]; P = .04), and correct reporting of 2 or more medication adverse effects (60 of 76 [78.9%] vs 13 of 69 [18.8%]; P < .001). There were no differences in knowledge of medication name, indication, frequency, or storage. Conclusions and Relevance: A health literacy-informed discharge medication communication bundle reduced home liquid medication administration errors and enhanced caregiver medication knowledge compared with standard counseling. Routine use of these standardized strategies can promote patient safety following hospital discharge. Trial Registration: ClinicalTrials.gov Identifier: NCT05143047.

Challenges in Deprescribing among Older Adults in Post-Acute Care Transitions to Home.

OBJECTIVES: Medications with a higher risk of harm or that are unlikely to be beneficial are used by nearly all older patients in home health care (HHC). The objective of this study was to understand stakeholders' perspectives on challenges in deprescribing these medications for post-acute HHC patients. DESIGN: Qualitative individual interviews were conducted with stakeholders involved with post-acute deprescribing. SETTING AND PARTICIPANT: Older HHC patients, HHC nurses, pharmacists, and primary/acute care/post-acute prescribers from 9 US states participated in individual qualitative interviews. MEASURES: Interview questions were focused on the experience, processes, roles, training, workflow, and challenges of deprescribing in hospital-to-home transitions. We used the constant comparison approach to identify and compare findings among patient, prescriber, and pharmacist and HHC nurse stakeholders. RESULTS: We interviewed 9 older patients, 11 HHC nurses, 5 primary care physicians (PCP), 3 pharmacists, 1 hospitalist, and 1 post-acute nurse practitioner. Four challenges were described in post-acute deprescribing for HHC patients. First, PCPs' time constraints, the timing of patient encounters after hospital discharge, and the lack of prioritization of deprescribing make it difficult for PCPs to initiate post-acute deprescribing. Second, patients are often confused about their medications, despite the care team's efforts in educating the patients. Third, communication is challenging between HHC nurses, PCPs, specialists, and hospitalists. Fourth, the roles of HHC nurses and pharmacists are limited in care team collaboration and discussion about post-acute deprescribing. CONCLUSIONS AND IMPLICATIONS: Post-acute deprescribing relies on multiple parties in the care team yet it has challenges. Interventions to align the timing of deprescribing and that of post-acute care visits, prioritize deprescribing and allow clinicians more time to complete related tasks, improve medication education for patients, and ensure effective communication in the care team with synchronized electronic health record systems are needed to advance deprescribing during the transition from hospital to home.

Deprescribing medications among patients with multiple prescribers: A socioecological model.

Deprescribing is the intentional dose reduction or discontinuation of a medication. The development of deprescribing interventions should take into consideration important organizational, interprofessional, and patient-specific barriers that can be further complicated by the presence of multiple prescribers involved in a patient's care. Patients who receive care from an increasing number of prescribers may experience disruptions in the timely transfer of relevant healthcare information, increasing the risk of exposure to drug-drug interactions and other medication-related problems. Furthermore, the fragmentation of healthcare information across health systems can contribute to the refilling of discontinued medications, reducing the effectiveness of deprescribing interventions. Thus, deprescribing interventions must carefully consider the unique characteristics of patients and their prescribers to ensure interventions are successfully implemented. In this special article, an international working group of physicians, pharmacists, nurses, epidemiologists, and researchers from the United States Deprescribing Research Network (USDeN) developed a socioecological model to understand how multiple prescribers may influence the implementation of a deprescribing intervention at the individual, interpersonal, organizational, and societal level. This manuscript also includes a description of the concept of multiple prescribers and outlines a research agenda for future investigations to consider. The information contained in this manuscript should be used as a framework for future deprescribing interventions to carefully consider how multiple prescribers can influence the successful implementation of the service and ensure the intervention is as effective as possible.

Model-Guided Decision-Making for Thromboprophylaxis and Hospital-Acquired Thromboembolic Events Among Hospitalized Children and Adolescents: The CLOT Randomized Clinical Trial.

Importance: Rates of hospital-acquired venous thromboembolism (HA-VTE) are increasing among pediatric patients. Identifying at-risk patients for whom prophylactic interventions should be considered remains challenging. Objective: To determine whether use of a previously validated HA-VTE prognostic model, together with pediatric hematologist review, could reduce pediatric inpatient rates of HA-VTE. Design, Setting, and Participants: This pragmatic randomized clinical trial was performed from November 2, 2020, through January 31, 2022, at a single-center academic children's hospital (Monroe Carell Jr Children's Hospital at Vanderbilt). All pediatric hospital admissions (aged <22 years) under inpatient status were included and randomized. Intervention: All patients had an HA-VTE probability automatically calculated daily, which was visible to the hematology research team for patients in the intervention group. Patients with an elevated risk (predicted probability ≥2.5%) underwent additional medical record review by the research team to determine eligibility for thromboprophylaxis. Main Outcomes and Measures: The primary outcome was rate of HA-VTE. Secondary outcomes included rates of prophylactic anticoagulation and anticoagulation-associated bleeding events. Results: A total of 17 427 hospitalizations met eligibility criteria, were randomized, and were included in the primary analysis: patients had a median (IQR) age of 1.7 (0 to 11.1) years; there were 9143 (52.5%) female patients and 8284 (47.5%) male patients, and there were 445 (2.6%) Asian patients, 2739 (15.9%) Black patients, and 11 752 (67.4%) White patients. The 2 groups were evenly balanced in number (8717 in the intervention group and 8710 in the control group) and patient characteristics. A total of 58 patients (0.7%) in the control group and 77 (0.9%) in the intervention group developed HA-VTE (risk difference: 2.2 per 1000 patients; 95% CI, -0.4 to 4.8 per 1000 patients; P = .10). Recommendations to initiate thromboprophylaxis were accepted by primary clinical teams 25.8% of the time (74 of 287 hospitalizations). Minor bleeding events were rare among patients who received anticoagulation (3 of 74 [4.1%]), and no major bleeding events were observed during the study period. Among patients randomized to the control group, the model exhibited high discrimination accuracy (C statistic, 0.799, 95% CI, 0.725 to 0.856). Conclusions and Relevance: In this randomized clinical trial of the use of a HA-VTE prognostic model to reduce pediatric inpatient rates of HA-VTE, despite the use of an accurate and validated prognostic model for HA-VTE, there was substantial reluctance by primary clinical teams to initiate thromboprophylaxis as recommended. In this context, rates of HA-VTE between the control and intervention groups were not different. Future research is needed to identify improved strategies for prevention of HA-VTE and to overcome clinician concerns regarding thromboprophylaxis. Trial Registration: ClinicalTrials.gov Identifier: NCT04574895.

Patient-reported predictors of post-discharge mortality after cardiac hospitalization.

Background: Adults hospitalized for cardiovascular events are at high risk for post-discharge mortality. Hospital-based screening of health-related psychosocial risk factors is now prioritized by the Joint Commission and the National Quality Forum to achieve equitable, high-quality care. We tested our hypothesis that key patient-reported psychosocial and behavioral measures could predict post-hospitalization mortality in a cohort of adults hospitalized for a cardiovascular event. Methods: This was a prospective cohort of adults hospitalized at Vanderbilt University Medical Center. Validated patient-reported measures of health literacy, social support, disease self-management, and socioeconomic status were used as predictors of interest. Cox survival analyses of mortality were conducted over a median 3.5-year follow-up (range: 1.25 - 5.5 years). Results: Among 2,977 adults, 1,874 (63%) were hospitalized for acute coronary syndrome and 1,103 (37%) were hospitalized for acute decompensated heart failure; 60% were male; and the mean age was 53 years. After adjusting for demographic, clinical, and other psychosocial factors, mortality risk was greatest among patients who reported being unable to work due to disability (Hazard Ratio (HR) 2.36, 95% Confidence Interval (CI): 1.73-3.21), who were retired (HR 2.14, 95% CI 1.60-2.87), and who reported unemployment (HR 1.99, 95% CI 1.30-3.06) as compared to those who were employed. Patient-reported measures of disease self-management, perceived health competence and exercise frequency, were also associated with mortality risk after full covariate adjustment (HR 0.86, 95% CI 0.73-1.00 per four-point increase), (HR 0.86, 95% CI 0.77-0.96 per three-day change), respectively. Conclusions: Patient-reported measures of employment status independently predict post-discharge mortality after a cardiac hospitalization. Measure of disease self-management also have prognostic modest utility. Hospital-based screening of psychosocial risk is increasingly prioritized in legislative policy. Incorporating brief, valid measures of employment status and disease self-management factors may help target patients for psychosocial, financial, and rehabilitative resources during post-discharge transitions of care.

Using intervention mapping to design and implement a multicomponent intervention to improve antibiotic and NSAID prescribing.

Successfully changing prescribing behavior to reduce inappropriate antibiotic and nonsteroidal anti-inflammatory drug (NSAID) prescriptions often requires combining components into a multicomponent intervention. However, multicomponent interventions often fail because of development and implementation complexity. To increase the likelihood of successfully changing prescribing behavior, we applied a systematic process to design and implement a multicomponent intervention. We used Intervention Mapping to create a roadmap for a multicomponent intervention in unscheduled outpatient care settings in the Veterans Health Administration. Intervention Mapping is a systematic process consisting of six steps that we grouped into three phases: (i) understand behavioral determinants and barriers to implementation, (ii) develop the intervention, and (iii) define evaluation plan and implementation strategies. A targeted literature review, combined with 25 prescriber and 25 stakeholder interviews, helped identify key behavioral determinants to inappropriate prescribing (e.g. perceived social pressure from patients to prescribe). We targeted three desired prescriber behaviors: (i) review guideline-concordant prescribing and patient outcomes, (ii) manage diagnostic and treatment uncertainty, and (iii) educate patients and caregivers. The intervention consisted of components for academic detailing, prescribing feedback, and alternative prescription order sets. Implementation strategies consisted of preparing clinical champions, conducting readiness assessments, and incentivizing use of the intervention. We chose a mixed-method study design with a commonly used evaluation framework to assess effectiveness and implementation outcomes in a subsequent trial. This study furthers knowledge about causes of inappropriate antibiotic and NSAID prescribing and demonstrates how theoretical, empirical, and practical information can be systematically applied to develop a multicomponent intervention to help address these causes.

Reducing adverse drug events from antibiotics and nonsteroidal anti-inflammatory drugs (NSAIDs) is a patient safety priority. Successfully changing prescribing behavior to reduce inappropriate prescriptions can require combining intervention components, each with different mechanisms for behavior change, into a multicomponent intervention. However, multicomponent interventions often fail because of development and implementation complexity. To increase the chance of successfully changing antibiotic and NSAID prescribing, the objective this study was to apply a systematic process to design and implement a multicomponent intervention. Three desired prescriber behaviors were targeted: (i) review guideline-concordant prescribing and patient outcomes, (ii) manage diagnostic and treatment uncertainty, and (iii) educate patients and caregivers. The designed intervention consisted of components for prescribing feedback, academic detailing, and alternative prescription order sets. Strategies to improve use of the intervention consisted of preparing clinical champions, conducting readiness assessments prior to study onset, and incentivizing use of the intervention. We chose a mixed-method study design with a commonly used evaluation framework to assess effectiveness and implementation outcomes of the multicomponent intervention in a subsequent trial.

Protocol and statistical analysis plan for the Mode of Ventilation During Critical IllnEss (MODE) trial.

Introduction: For every critically ill adult receiving invasive mechanical ventilation, clinicians must select a mode of ventilation. The mode of ventilation determines whether the ventilator directly controls the tidal volume or the inspiratory pressure. Newer hybrid modes allow clinicians to set a target tidal volume, for which the ventilator controls and adjusts the inspiratory pressure. A strategy of low tidal volumes and low plateau pressure improves outcomes, but the optimal mode to achieve these targets is not known. Methods and analysis: The Mode of Ventilation During Critical Illness (MODE) trial is a cluster-randomized, multiple-crossover pilot trial being conducted in the medical intensive care unit (ICU) at an academic center. The MODE trial compares the use of volume control, pressure control, and adaptive pressure control. The study ICU is assigned to a single ventilator mode (volume control versus pressure control versus adaptive pressure control) for continuous mandatory ventilation during each 1-month study block. The assigned mode switches every month in a randomly generated sequence. The primary outcome is ventilator-free days (VFDs) to study day 28, defined as the number of days alive and free of invasive mechanical ventilation from the final receipt of mechanical ventilation to 28 days after enrollment. Enrollment began November 1, 2022 and will end on July 31, 2023. Ethics and dissemination: The trial was approved by the Vanderbilt University Medical Center institutional review board (IRB# 220446). Results of this study will be submitted to a peer-reviewed journal and presented at scientific conferences. Trial registration number: The trial was registered with clinicaltrials.gov on October 3, 2022, prior to initiation of patient enrollment on November 1, 2022 (ClinicalTrials.gov identifier: NCT05563779).

How to Deprescribe Potentially Inappropriate Medications During the Hospital-to-Home Transition: Stakeholder Perspectives on Essential Tasks.

PURPOSE: Nearly all older patients receiving postacute home health care (HHC) use potentially inappropriate medications (PIMs) that carry a risk of harm. Deprescribing can reduce and optimize the use of PIMs, yet it is often not conducted among HHC patients. The objective of this study was to gather perspectives from patient, practitioner, and HHC clinician stakeholders on tasks that are essential to postacute deprescribing in HHC. METHODS: A total of 44 stakeholders, including 14 HHC patients, 15 practitioners (including 9 primary care physicians, 4 pharmacists, 1 hospitalist, and 1 nurse practitioner), and 15 HHC nurses, participated. The stakeholders were from 12 US states, including New York (n = 29), Colorado (n = 2), Connecticut (n = 1), Illinois (n = 2), Kansas (n = 2), Massachusetts (n = 1), Minnesota (n = 1), Mississippi (n = 1), Nebraska (n = 1), Ohio (n = 1), Tennessee (n = 1), and Texas (n = 2). First, individual interviews were conducted by experienced research staff via video conference or telephone. Second, the study team reviewed all interview transcripts and selected interview statements regarding stakeholders' suggestions for important tasks needed for postacute deprescribing in HHC. Third, concept mapping was conducted in which stakeholders sorted and rated selected interview statements regarding importance and feasibility. A content analysis was conducted of data collected in the individual interviews, and a mixed-method analysis was conducted of data collected in the concept mapping. FINDINGS: Four essential tasks were identified for postacute deprescribing in HHC: (1) ongoing review and assessment of medication use, (2) patent-centered and individualized plan of deprescribing, (3) timely and efficient communication among members of the care team, and (4) continuous and tailored medication education to meet patient needs. Among these tasks, developing patient-centered deprescribing considerations was considered the most important and feasible, followed by medication education, review and assessment of medication use, and communication. IMPLICATIONS: Deprescribing during the transition of care from hospital to home requires the following: continuous medication education for patients, families, and caregivers; ongoing review and assessment of medication use; patient-centered deprescribing considerations; and effective communication and collaboration among the primary care physician, HHC nurse, and pharmacist.

Why do older adults decline participation in research? Results from two deprescribing clinical trials.

BACKGROUND: Heterogenous older adult populations are underrepresented in clinical trials, and their participation is necessary for interventions that directly target them. The purpose of this study was to evaluate reasons why hospitalized older adults declined participation in two deprescribing clinical trials. METHODS: We report enrollment data from two deprescribing trials, Shed-MEDS (non-Veterans) and VA DROP (Veterans). For both trials, inclusion criteria required participants to be hospitalized, age 50 or older, English-speaking, and taking five or more home medications. Eligible patients were approached for enrollment while hospitalized. When an eligible patient or surrogate declined participation, the reason(s) were recorded and subsequently analyzed inductively to develop themes, and a chi-square test was used for comparison (of themes between Veterans and non-Veterans). RESULTS: Across both trials, 1226 patients (545 non-Veterans and 681 Veterans) declined enrollment and provided reasons, which were condensed into three themes: (1) feeling overwhelmed by their current health status, (2) lack of interest or mistrust of research, and (3) hesitancy to participate in a deprescribing study. A greater proportion of Veterans expressed a lack of interest or mistrust in research (42% vs 26%, chi-square value = 36.72, p < .001), whereas a greater proportion of non-Veterans expressed feeling overwhelmed by their current health status (54% vs 35%, chi-square value = 42.8 p < 0.001). Across both trials, similar proportion of patients expressed hesitancy to participate in a deprescribing study, with no significant difference between Veterans and non-Veterans (23% and 21%). CONCLUSIONS: Understanding the reasons older adults decline participation can inform future strategies to engage this multimorbid population.