Pharmacist, nurse, and physician perspectives on the implementation of the pharmacist discharge care (pharm-dc) intervention: A qualitative study.

BACKGROUND: The PHARMacist Discharge Care (PHARM-DC) intervention is a pharmacist-led Transitions of Care (TOC) program intended to reduce 30-day hospital readmissions and emergency department visits which has been implemented at two hospitals in the United States. The objectives of this study were to: 1) explore perspectives surrounding the PHARM-DC program from healthcare providers, leaders, and administrators at both institutions, and 2) identify factors which may contribute to intervention success and sustainability. METHODS: Focus groups and interviews were conducted with pharmacists, physicians, nurses, hospital leaders, and pharmacy administrators at two institutions in the Northeastern and Western United States. Interviews were audio recorded and transcribed, with transcriptions imported into NVivo for qualitative analysis. Thematic analysis was performed using an iterative process, with two study authors independently coding transcripts to identify themes. RESULTS: Overall, 37 individuals participated in ten focus groups and seven interviews. The themes identified included: 1) Organizational, Pharmacist, and Patient Factors Contributing to Transitions of Care, 2) Medication Challenges in Transitions of Care at Admission and Discharge, 3) Transitions of Care Communication and Discharge Follow-up, and 4) Opportunities for Improvement and Sustainability. The four themes were mapped to the constructs of the CFIR and RE-AIM frameworks. Some factors facilitating intervention success and sustainability were accurate medication histories collected on admission, addressing medication barriers before discharge, coordinating discharge using electronic health record discharge features, and having a structured process for intervention training and delivery. Barriers to intervention implementation and sustainability included gaps in communication with other care team members, and variable pharmacist skills for delivering the intervention. This study identified that using educational resources to standardize the TOC process addressed the issue of variations in pharmacists' skills for delivering TOC interventions. CONCLUSIONS: Nurses, physicians, pharmacists, pharmacist leaders, and hospital administrators were in agreement regarding the usefulness of the PHARM-DC intervention, while acknowledging challenges in its implementation and opportunities for improvement. Future research should focus on developing training materials to standardize and scale the intervention, eliminating barriers to medication access pre-discharge, coordinating discharge across care team members, and communicating medication changes to primary care providers post-discharge.

Surgical appropriateness nudges: Developing behavioral science nudges to integrate appropriateness criteria into the decision making of spine surgeons.

BACKGROUND: Substantial variation exists in surgeon decision making. In response, multiple specialty societies have established criteria for the appropriate use of spine surgery. Yet few strategies exist to facilitate routine use of appropriateness criteria by surgeons. Behavioral science nudges are increasingly used to enhance decision making by clinicians. We sought to design "surgical appropriateness nudges" to support routine use of appropriateness criteria for degenerative lumbar scoliosis and spondylolisthesis. METHODS: The work reflected Stage I of the NIH Stage Model for Behavioral Intervention Development and involved an iterative, multi-method approach, emphasizing qualitative methods. Study sites included two large referral centers for spine surgery. We recruited spine surgeons from both sites for two rounds of focus groups. To produce preliminary nudge prototypes, we examined sources of variation in surgeon decision making (Focus Group 1) and synthesized existing knowledge of appropriateness criteria, behavioral science nudge frameworks, electronic tools, and the surgical workflow. We refined nudge prototypes via feedback from content experts, site leaders, and spine surgeons (Focus Group 2). Concurrently, we collected data on surgical practices and outcomes at study sites. We pilot tested the refined nudge prototypes among spine surgeons, and surveyed them about nudge applicability, acceptability, and feasibility (scale 1-5, 5 = strongly agree). RESULTS: Fifteen surgeons participated in focus groups, giving substantive input and feedback on nudge design. Refined nudge prototypes included: individualized surgeon score cards (frameworks: descriptive social norms/peer comparison/feedback), online calculators embedded in the EHR (decision aid/mapping), a multispecialty case conference (injunctive norms/social influence), and a preoperative check (reminders/ salience of information/ accountable justification). Two nudges (score cards, preop checks) incorporated data on surgeon practices and outcomes. Six surgeons pilot tested the refined nudges, and five completed the survey (83%). The overall mean score was 4.0 (standard deviation [SD] 0.5), with scores of 3.9 (SD 0.5) for applicability, 4.1 (SD 0.5) for acceptability, and 4.0 (SD 0.5), for feasibility. Conferences had the highest scores 4.3 (SD 0.6) and calculators the lowest 3.9 (SD 0.4). CONCLUSIONS: Behavioral science nudges might be a promising strategy for facilitating incorporation of appropriateness criteria into the surgical workflow of spine surgeons. Future stages in intervention development will test whether these surgical appropriateness nudges can be implemented in practice and influence surgical decision making.

Structure and Funding of Clinical Informatics Fellowships: A National Survey of Program Directors.

BACKGROUND: In 2011, the American Board of Medical Specialties established clinical informatics (CI) as a subspecialty in medicine, jointly administered by the American Board of Pathology and the American Board of Preventive Medicine. Subsequently, many institutions created CI fellowship training programs to meet the growing need for informaticists. Although many programs share similar features, there is considerable variation in program funding and administrative structures. OBJECTIVES: The aim of our study was to characterize CI fellowship program features, including governance structures, funding sources, and expenses. METHODS: We created a cross-sectional online REDCap survey with 44 items requesting information on program administration, fellows, administrative support, funding sources, and expenses. We surveyed program directors of programs accredited by the Accreditation Council for Graduate Medical Education between 2014 and 2021. RESULTS: We invited 54 program directors, of which 41 (76%) completed the survey. The average administrative support received was $27,732/year. Most programs (85.4%) were accredited to have two or more fellows per year. Programs were administratively housed under six departments: Internal Medicine (17; 41.5%), Pediatrics (7; 17.1%), Pathology (6; 14.6%), Family Medicine (6; 14.6%), Emergency Medicine (4; 9.8%), and Anesthesiology (1; 2.4%). Funding sources for CI fellowship program directors included: hospital or health systems (28.3%), clinical departments (28.3%), graduate medical education office (13.2%), biomedical informatics department (9.4%), hospital information technology (9.4%), research and grants (7.5%), and other sources (3.8%) that included philanthropy and external entities. CONCLUSION: CI fellowships have been established in leading academic and community health care systems across the country. Due to their unique training requirements, these programs require significant resources for education, administration, and recruitment. There continues to be considerable heterogeneity in funding models between programs. Our survey findings reinforce the need for reformed federal funding models for informatics practice and training.

Cumulative Update of a Systematic Overview Evaluating Interventions Addressing Polypharmacy.

Importance: Polypharmacy is associated with mortality, falls, hospitalizations, and functional and cognitive decline. The study of polypharmacy-related interventions has increased substantially, prompting the need for an updated, more focused systematic overview. Objective: To systematically evaluate and summarize evidence across multiple systematic reviews (SRs) examining interventions addressing polypharmacy. Evidence Review: A search was conducted of MEDLINE, the Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effects for articles published from January 2017-October 2022, as well as those identified in a previous overview (January 2004-February 2017). Systematic reviews were included regardless of study design, setting, or outcome. The evidence was summarized by 4 categories: (1) medication-related process outcomes (eg, potentially inappropriate medication [PIM] and potential prescribing omission reductions), (2) clinical and functional outcomes, (3) health care use and economic outcomes, and (4) acceptability of the intervention. Findings: Fourteen SRs were identified (3 from the previous overview), 7 of which included meta-analyses, representing 179 unique published studies. Nine SRs examined medication-related process outcomes (low to very low evidence quality). Systematic reviews using pooled analyses found significant reductions in the number of PIMs, potential prescribing omissions, and total number of medications, and improvements in medication appropriateness. Twelve SRs examined clinical and functional outcomes (very low to moderate evidence quality). Five SRs examined mortality; all mortality meta-analyses were null, but studies with longer follow-up periods found greater reductions in mortality. Five SRs examined falls incidence; results were predominantly null save for a meta-analysis in which PIMs were discontinued. Of the 8 SRs examining quality of life, most (7) found predominantly null effects. Ten SRs examined hospitalizations and readmissions (very low to moderate evidence quality) and 4 examined emergency department visits (very low to low evidence quality). One SR found significant reductions in hospitalizations and readmissions among higher-intensity medication reviews with face-to-face patient components. Another meta-analysis found a null effect. Of the 7 SRs without meta-analyses for hospitalizations and readmissions, all had predominantly null results. Two of 4 SRs found reductions in emergency department visits. Two SRs examined acceptability (very low evidence quality), finding wide variation in the adoption of polypharmacy-related interventions. Conclusions and Relevance: This updated systematic overview noted little evidence of an association between polypharmacy-related interventions and reduced important clinical and health care use outcomes. More evidence is needed regarding which interventions are most useful and which populations would benefit most.

Comprehensive Pharmacist-led Transitions-of-care Medication Management around Hospital Discharge Adds Modest Cost Relative to Usual Care: Time-and-Motion Cost Analysis.

Optimal medication management is important during hospitalization and at discharge because post-discharge adverse drug events (ADEs) are common, often preventable, and contribute to patient harms, healthcare utilization, and costs. Conduct a cost analysis of a comprehensive pharmacist-led transitions-of-care medication management intervention for older adults during and after hospital discharge. Twelve intervention components addressed medication reconciliation, medication review, and medication adherence. Trained, experienced pharmacists delivered the intervention to older adults with chronic comorbidities at 2 large U.S. academic centers. To quantify and categorize time spent on the intervention, we conducted a time-and-motion analysis of study pharmacists over 36 sequential workdays (14 519 min) involving 117 patients. For 40 patients' hospitalizations, we observed all intervention activities. We used the median minutes spent and pharmacist wages nationally to calculate cost per hospitalization (2020 U.S. dollars) from the hospital perspective, relative to usual care. Pharmacists spent a median of 66.9 min per hospitalization (interquartile range 46.1-90.1), equating to $101 ($86 to $116 in sensitivity analyses). In unadjusted analyses, study site was associated with time spent (medians 111 and 51.8 min) while patient primary language, discharge disposition, number of outpatient medications, and patient age were not. In this cost analysis, comprehensive medication management around discharge cost about $101 per hospitalization, with variation across sites. This cost is at least an order of magnitude less than published costs associated with ADEs, hospital readmissions, or other interventions designed to reduce readmissions. Work is ongoing to assess the current intervention's effectiveness.

Microvascular Aging and Eicosanoids-Women's Evaluation of Systemic Aging Tenacity ("You are never too old to become younger!") Specialized Center of Research Excellence on Sex Differences Career Enhancement Core: Building the Future.

The objective of the National Institutes of Health Office of Research in Women's Health (NIH/ORWH) Specialized Center of Research and Career Enhancement (SCORE) program is to expedite the development and application of new knowledge that affect women, to learn more about the etiology of these diseases, and to foster improved approaches to treatment and/or prevention. Each SCORE has a Career Enhancement Core (CEC) that serves to meet the career enhancement needs of translational science in the study of sex differences. The Microvascular Aging and Eicosanoids-Women's Evaluation of Systemic aging Tenacity (MAE-WEST) ("You are never too old to become younger!") Specialized Center of Research Excellence (SCORE) on Sex Differences will study pro- and anti-inflammatory responses and small vessel aging traits. As part of our SCORE CEC, we have advanced several initiatives to embed consideration of sex as a biological variable (SABV) into the infrastructure of our two CEC institutions. Unlike other professions, ongoing physician education through continuing medical education (CME) activities is required and embedded in the practice of medicine. The MAE-WEST SCORE in collaboration with the CSMC Clinical Scholars Program, the Center for Research in Women's Health and Sex-differences and the CSMC CME Office requires SABV and as Diversity, Equity, and Inclusion components in all CSMC CME programs. Clinical practice is also increasingly guided by evidence-based guidelines, with Class I recommendations resulting from clinical trials rather than expert consensus. It is essential that women be included in clinical trials proportionate to the prevalence and burden of disease. The MAE-WEST SCORE has developed our own unique CEC for providing novel educational, networking, funding opportunities, and translation to practice support. The developed best practices have found novel ways to enhance studies of women's health and SABV. We welcome visitors on-site and virtual to share with the broader academic and practicing community.

Identifying barriers and facilitators to deprescribing benzodiazepines and sedative hypnotics in the hospital setting using the Theoretical Domains Framework and the Capability, Opportunity, Motivation and Behaviour (COM-B) Model: a qualitative study.

OBJECTIVES: Geriatric guidelines strongly recommend avoiding benzodiazepines and non-benzodiazepine sedative hypnotics in older adults. Hospitalisation may provide an important opportunity to begin the process of deprescribing these medications, particularly as new contraindications arise. We used implementation science models and qualitative interviews to describe barriers and facilitators to deprescribing benzodiazepines and non-benzodiazepine sedative hypnotics in the hospital and develop potential interventions to address identified barriers. DESIGN: We used two implementation science models, the Capability, Opportunity and Behaviour Model (COM-B) and the Theoretical Domains Framework, to code interviews with hospital staff, and an implementation process, the Behaviour Change Wheel (BCW), to codevelop potential interventions with stakeholders from each clinician group. SETTING: Interviews took place in a tertiary, 886-bed hospital located in Los Angeles, California. PARTICIPANTS: Interview participants included physicians, pharmacists, pharmacist technicians, and nurses. RESULTS: We interviewed 14 clinicians. We found barriers and facilitators across all COM-B model domains. Barriers included lack of knowledge about how to engage in complex conversations about deprescribing (capability), competing tasks in the inpatient setting (opportunity), high levels of resistance/anxiety among patients to deprescribe (motivation), concerns about lack of postdischarge follow-up (motivation). Facilitators included high levels of knowledge about the risks of these medications (capability), regular rounds and huddles to identify inappropriate medications (opportunity) and beliefs that patients may be more receptive to deprescribing if the medication is related to the reason for hospitalisation (motivation). Potential modes of delivery included a seminar aimed at addressing capability and motivation barriers in nurses, a pharmacist-led deprescribing initiative using risk stratification to identify and target patients at highest need for deprescribing, and the use of evidence-based deprescribing education materials provided to patients at discharge. CONCLUSIONS: While we identified numerous barriers and facilitators to initiating deprescribing conversations in the hospital, nurse- and pharmacist-led interventions may be an appropriate opportunity to initiate deprescribing.

Effect of the population health inpatient Medicare Advantage pharmacist intervention on hospital readmissions: A quasi-experimental controlled study.

BACKGROUND: The population health inpatient Medicare Advantage pharmacist (PHIMAP) intervention is a pharmacist-led, transitions-of-care intervention that aims to reduce hospital readmissions among Medicare Advantage beneficiaries. PHIMAP includes inpatient pharmacist participation in interdisciplinary rounds, admission and discharge medication reconciliation, pharmacy staff delivery of discharge medications to the bedside, personalized discharge medication lists and counseling, and communication with outpatient pharmacists through an electronic health record. OBJECTIVE: To evaluate the effect of the PHIMAP intervention on unplanned 30-day same-hospital readmissions among Medicare Advantage patients. METHODS: Those included were patients admitted to a large urban academic medical center between May 2018 and March 2020 who had a Medicare Advantage plan and were aged at least 18 years. A 2-group, quasi-experimental design was utilized. Control patients received the usual care, which included a best possible medication history and a postdischarge phone call. A multivariable logistic regression model was estimated to predict unplanned 30-day same-hospital readmissions. This study was a Hypothesis Evaluating Treatment Effectiveness study. RESULTS: In total, 884 patients were included. The majority were White (59.0%), non-Hispanic (87.7%), English speaking (90.5%), and older adults (median age, 75 years; interquartile range, 70-83 years). We detected no statistically significant association between the PHIMAP intervention and unplanned 30-day same-hospital readmissions (odds ratio [OR] = 0.91, 95% CI = 0.56-1.52). After adjusting for patient demographics and clinical covariates, significant predictors of 30-day readmissions included the number of emergency department/inpatient visits within 180 days prior to index admission (OR = 1.40, 95% CI = 1.11-1.77); discharge to a post-acute care facility, such as an inpatient rehabilitation facility, long-term acute care facility, or skilled nursing facility (OR = 1.69, 95% CI = 1.06-2.66); hospital length of stay in days (OR = 1.04, 95% CI=1.01-1.07); and the Agency for Healthcare Research and Quality Elixhauser Comorbidity Index score (OR = 1.01, 95% CI = 1.01-1.02). CONCLUSIONS: Significant predictors of readmissions among Medicare Advantage beneficiaries were consistent with greater illness severity, including a recent history of prior hospital utilization, a discharge to post-acute care facility (vs home), a longer length of hospital stay, and a higher comorbidity burden. Although we detected no statistically significant association between PHIMAP and unplanned 30-day same-hospital readmissions, differences in study group assignment based on the day of hospital discharge (weekend vs weekday) was a noted limitation of this study. Future studies of inpatient pharmacist-led interventions should plan to minimize the risk of selection bias due to differences in the time of patient discharge. DISCLOSURES: This study was supported in part by the National Institute on Aging under award number R01AG058911 (to Pevnick) and the UCLA Clinical Translational Science Institute (UL1 TR001881). The sponsor had no role in the design and conduct of the study, nor the writing of this report.

Implementation of an Electronic Health Records-Based Safe Contrast Limit for Preventing Contrast-Associated Acute Kidney Injury After Percutaneous Coronary Intervention.

BACKGROUND: Contrast-associated acute kidney injury (CA-AKI) after percutaneous coronary intervention is associated with increased mortality. We assessed the effectiveness of an electronic health records safe contrast limit tool in predicting CA-AKI risk and reducing contrast use and CA-AKI. METHODS: We created an alert displaying the safe contrast limit to cardiac catheterization laboratory staff prior to percutaneous coronary intervention. The alert used risk factors automatically extracted from the electronic health records. We included procedures from June 1, 2020 to October 1, 2021; the intervention went live February 10, 2021. Using difference-in-differences analysis, we evaluated changes in contrast volume and CA-AKI rates after contrast limit tool implementation compared to control hospitals. Cardiologists were surveyed prior to and 9 months after alert implementation on beliefs, practice patterns, and safe contrast estimates for example patients. RESULTS: At the one intervention site, there were 508 percutaneous coronary interventions before and 531 after tool deployment. At 15 control sites, there were 3550 and 3979 percutaneous coronary interventions, respectively. The contrast limit predicted CA-AKI with an accuracy of 64.1%, negative predictive value of 93.3%, and positive predictive value of 18.7%. After implementation, in high/modifiable risk patients (defined as having a calculated contrast limit <500ml) there was a small but significant -4.60 mL/month (95% CI, -8.24 to -1.00) change in average contrast use but no change in CA-AKI rates (odds ratio, 0.96 [95% CI, 0.84-1.10]). Low-risk patients had no change in contrast use (-0.50 mL/month [95% CI, -7.49 to 6.49]) or CA-AKI (odds ratio, 1.24 [95% CI, 0.79-1.93]). In assessing CA-AKI risk, clinicians heavily weighted age and diabetes but often did not consider anemia, cardiogenic shock, and heart failure. CONCLUSIONS: Clinicians often used a simplified assessment of CA-AKI risk that did not include important risk factors, leading to risk estimations inconsistent with established models. Despite clinician skepticism, an electronic health records-based contrast limit tool more accurately predicted CA-AKI risk and was associated with a small decrease in contrast use during percutaneous coronary intervention but no change in CA-AKI rates.

Digital Tools Designed to Obtain the History of Present Illness From Patients: Scoping Review.

BACKGROUND: Many medical conditions, perhaps 80% of them, can be diagnosed by taking a thorough history of present illness (HPI). However, in the clinical setting, situational factors such as interruptions and time pressure may cause interactions with patients to be brief and fragmented. One solution for improving clinicians' ability to collect a thorough HPI and maximize efficiency and quality of care could be to use a digital tool to obtain the HPI before face-to-face evaluation by a clinician. OBJECTIVE: Our objective was to identify and characterize digital tools that have been designed to obtain the HPI directly from patients or caregivers and present this information to clinicians before a face-to-face encounter. We also sought to describe outcomes reported in testing of these tools, especially those related to usability, efficiency, and quality of care. METHODS: We conducted a scoping review using predefined search terms in the following databases: MEDLINE, CINAHL, PsycINFO, Web of Science, Embase, IEEE Xplore Digital Library, ACM Digital Library, and ProQuest Dissertations & Theses Global. Two reviewers screened titles and abstracts for relevance, performed full-text reviews of articles meeting the inclusion criteria, and used a pile-sorting procedure to identify distinguishing characteristics of the tools. Information describing the tools was primarily obtained from identified peer-reviewed sources; in addition, supplementary information was obtained from tool websites and through direct communications with tool creators. RESULTS: We identified 18 tools meeting the inclusion criteria. Of these 18 tools, 14 (78%) used primarily closed-ended and multiple-choice questions, 1 (6%) used free-text input, and 3 (17%) used conversational (chatbot) style. More than half (10/18, 56%) of the tools were tailored to specific patient subpopulations; the remaining (8/18, 44%) tools did not specify a target subpopulation. Of the 18 tools, 7 (39%) included multilingual support, and 12 (67%) had the capability to transfer data directly into the electronic health record. Studies of the tools reported on various outcome measures related to usability, efficiency, and quality of care. CONCLUSIONS: The HPI tools we identified (N=18) varied greatly in their purpose and functionality. There was no consensus on how patient-generated information should be collected or presented to clinicians. Existing tools have undergone inconsistent levels of testing, with a wide variety of different outcome measures used in evaluation, including some related to usability, efficiency, and quality of care. There is substantial interest in using digital tools to obtain the HPI from patients, but the outcomes measured have been inconsistent. Future research should focus on whether using HPI tools can lead to improved patient experience and health outcomes, although surrogate end points could instead be used so long as patient safety is monitored.

Applying Automated Machine Learning to Predict Mode of Delivery Using Ongoing Intrapartum Data in Laboring Patients.

OBJECTIVE: This study aimed to develop and validate a machine learning (ML) model to predict the probability of a vaginal delivery (Partometer) using data iteratively obtained during labor from the electronic health record. STUDY DESIGN: A retrospective cohort study of deliveries at an academic, tertiary care hospital was conducted from 2013 to 2019 who had at least two cervical examinations. The population was divided into those delivered by physicians with nulliparous term singleton vertex (NTSV) cesarean delivery rates <23.9% (Partometer cohort) and the remainder (control cohort). The cesarean rate among this population of lower risk patients is a standard metric by which to compare provider rates; <23.9% was the Healthy People 2020 goal. A supervised automated ML approach was applied to generate a model for each population. The primary outcome was accuracy of the model developed on the Partometer cohort at 4 hours from admission to labor and delivery. Secondary outcomes included discrimination ability (receiver operating characteristics-area under the curve [ROC-AUC]), precision-recall AUC, and calibration of the Partometer. To assess generalizability, we compared the performance and clinical predictors identified by the Partometer to the control model. RESULTS: There were 37,932 deliveries during the study period; after exclusions, 9,385 deliveries were included in the Partometer cohort and 19,683 in the control cohort. Accuracy of predicting vaginal delivery at 4 hours was 87.1% for the Partometer (ROC-AUC: 0.82). Clinical predictors of greatest importance in the stacked Intrapartum Partometer Model included the Admission Model prediction and ongoing measures of dilatation and station which mirrored those found in the control population. CONCLUSION: Using automated ML and intrapartum factors improved the accuracy of prediction of probability of a vaginal delivery over both previously published models based on logistic regression. Harnessing real-time data and ML could represent the bridge to generating a truly prescriptive tool to augment clinical decision-making, predict labor outcomes, and reduce maternal and neonatal morbidity. KEY POINTS: · Our ML-based model yielded accurate predictions of mode of delivery early in labor.. · Predictors for models created on populations with high and low cesarean rates were the same.. · A ML-based model may provide meaningful guidance to clinicians managing labor..

Will Apple devices' passive atrial fibrillation detection prevent strokes? Estimating the proportion of high-risk actionable patients with real-world user data.

OBJECTIVE: Utilizing integrated electronic health record (EHR) and consumer-grade wearable device data, we sought to provide real-world estimates for the proportion of wearers that would likely benefit from anticoagulation if an atrial fibrillation (AFib) diagnosis was made based on wearable device data. MATERIALS AND METHODS: This study utilized EHR and Apple Watch data from an observational cohort of 1802 patients at Cedars-Sinai Medical Center who linked devices to the EHR between April 25, 2015 and November 16, 2018. Using these data, we estimated the number of high-risk patients who would be actionable for anticoagulation based on (1) medical history, (2) Apple Watch wear patterns, and (3) AFib risk, as determined by an existing validated model. RESULTS: Based on the characteristics of this cohort, a mean of 0.25% (n = 4.58, 95% CI, 2.0-8.0) of patients would be candidates for new anticoagulation based on AFib identified by their Apple Watch. Using EHR data alone, we find that only approximately 36% of the 1802 patients (n = 665.93, 95% CI, 626.0-706.0) would have anticoagulation recommended even after a new AFib diagnosis. DISCUSSION AND CONCLUSION: These data suggest that there is limited benefit to detect and treat AFib with anticoagulation among this cohort, but that accessing clinical and demographic data from the EHR could help target devices to the patients with the highest potential for benefit. Future research may analyze this relationship at other sites and among other wearable users, including among those who have not linked devices to their EHR.

A qualitative dual-site analysis of the pharmacist discharge care (PHARM-DC) intervention using the CFIR framework.

INTRODUCTION: Older adults face several challenges when transitioning from acute hospitals to community-based care. The PHARMacist Discharge Care (PHARM-DC) intervention is a pharmacist-led Transitions of Care (TOC) program intended to reduce 30-day hospital readmissions and emergency department visits at two large hospitals. This study used the Consolidated Framework for Implementation Research (CFIR) framework to evaluate pharmacist perceptions of the PHARM-DC intervention. METHODS: Intervention pharmacists and pharmacy administrators were purposively recruited by study team members located within each participating institution. Study team members located within each institution coordinated with two study authors unaffiliated with the institutions implementing the intervention to conduct interviews and focus groups remotely via telecommunication software. Interviews were recorded and transcribed, with transcriptions imported into NVivo for qualitative analysis. Qualitative analysis was performed using an iterative process to identify "a priori" constructs based on CFIR domains (intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation) and to create overarching themes as identified during coding. RESULTS: In total, ten semi-structured interviews and one focus group were completed across both hospitals. At Site A, six interviews were conducted with intervention pharmacists and pharmacists in administrative roles. Also at Site A, one focus group comprised of five intervention pharmacists was conducted. At Site B, interviews were conducted with four intervention pharmacists and pharmacists in administrative roles. Three overarching themes were identified: PHARM-DC and Institutional Context, Importance of PHARM-DC Adaptability, and Recommendations for PHARM-DC Improvement and Sustainability. Increasing pharmacist support for technical tasks and navigating pharmacist-patient language barriers were important to intervention implementation and delivery. Identifying cost-savings and quantifying outcomes as a result of the intervention were particularly important when considering how to sustain and expand the PHARM-DC intervention. CONCLUSION: The PHARM-DC intervention can successfully be implemented at two institutions with considerable variations in TOC initiatives, resources, and staffing. Future implementation of PHARM-DC interventions should consider the themes identified, including an examination of institution-specific contextual factors such as the roles that pharmacy technicians may play in TOC interventions, the importance of intervention adaptability to account for patient needs and institutional resources, and pharmacist recommendations for intervention improvement and sustainability. TRIAL REGISTRATION: NCT04071951 .

Incidence of interruptive penicillin allergy alerts in patients with previously documented beta-lactam exposure: Potential for leveraging the electronic health record to identify erroneous allergies.

BACKGROUND: Approximately 10% of patients report allergies to penicillin, yet >90% of these allergies are not clinically significant. Patients reporting penicillin allergies are often treated with second-line, non-ß-lactam antibiotics that are typically broader spectrum and more toxic. Orders for ß-lactam antibiotics for these patients trigger interruptive alerts, even when there is electronic health record (EHR) data indicating prior ß-lactam exposure. OBJECTIVE: To describe the rate that interruptive penicillin allergy alerts display for patients who have previously had a ß-lactam exposure. DESIGN: Retrospective EHR review from January 2013 through June 2018. SETTING: A nonprofit health system including 1 large tertiary-care medical center, a smaller associated hospital, 2 emergency departments, and ˜250 outpatient clinics. PARTICIPANTS: All patients with EHR-documented of penicillin allergies. METHODS: We examined interruptive penicillin allergy alerts and identified the number and percentage of alerts that display for patients with a prior administration of a penicillin class or other ß-lactam antibiotic. RESULTS: Of 115,081 allergy alerts that displayed during the study period, 8% were displayed for patients who had an inpatient administration of a penicillin antibiotic after the allergy was noted, and 49% were displayed for patients with a prior inpatient administration of any ß-lactam. CONCLUSIONS: Many interruptive penicillin allergy alerts display for patients who would likely tolerate a penicillin, and half of all alerts display for patients who would likely tolerate another ß-lactam.

Personal Electronic Records of Medications (PERMs) for medication reconciliation at care transitions: a rapid realist review.

BACKGROUND: Medication reconciliation (MedRec), a process to reduce medication error at care transitions, is labour- and resource-intensive and time-consuming. Use of Personal Electronic Records of Medications (PERMs) in health information systems to support MedRec have proven challenging. Relatively little is known about the design, use or implementation of PERMs at care transitions that impacts on MedRec in the 'real world'. To respond to this gap in knowledge we undertook a rapid realist review (RRR). The aim was to develop theories to explain how, why, when, where and for whom PERMs are designed, implemented or used in practice at care transitions that impacts on MedRec. METHODOLOGY: We used realist methodology and undertook the RRR between August 2020 and February 2021. We collaborated with experts in the field to identify key themes. Articles were sourced from four databases (Pubmed, Embase, CINAHL Complete and OpenGrey) to contribute to the theory development. Quality assessment, screening and data extraction using NVivo was completed. Contexts, mechanisms and outcomes configurations were identified and synthesised. The experts considered these theories for relevance and practicality and suggested refinements. RESULTS: Ten provisional theories were identified from 19 articles. Some theories relate to the design (T2 Inclusive design, T3 PERMs complement existing good processes, T7 Interoperability), some relate to the implementation (T5 Tailored training, T9 Positive impact of legislation or governance), some relate to use (T6 Support and on-demand training) and others relate iteratively to all stages of the process (T1 Engage stakeholders, T4 Build trust, T8 Resource investment, T10 Patients as users of PERMs). CONCLUSIONS: This RRR has allowed additional valuable data to be extracted from existing primary research, with minimal resources, that may impact positively on future developments in this area. The theories are interdependent to a greater or lesser extent; several or all of the theories may need to be in play to collectively impact on the design, implementation or use of PERMs for MedRec at care transitions. These theories should now be incorporated into an intervention and evaluated to further test their validity.

Using body temperature and variables commonly available in the EHR to predict acute infection: a proof-of-concept study showing improved pretest probability estimates for acute COVID-19 infection among discharged emergency department patients.

OBJECTIVES: Obtaining body temperature is a quick and easy method to screen for acute infection such as COVID-19. Currently, the predictive value of body temperature for acute infection is inhibited by failure to account for other readily available variables that affect temperature values. In this proof-of-concept study, we sought to improve COVID-19 pretest probability estimation by incorporating covariates known to be associated with body temperature, including patient age, sex, comorbidities, month, and time of day. METHODS: For patients discharged from an academic hospital emergency department after testing for COVID-19 in March and April of 2020, we abstracted clinical data. We reviewed physician documentation to retrospectively generate estimates of pretest probability for COVID-19. Using patients' COVID-19 PCR test results as a gold standard, we compared AUCs of logistic regression models predicting COVID-19 positivity that used: (1) body temperature alone; (2) body temperature and pretest probability; (3) body temperature, pretest probability, and body temperature-relevant covariates. Calibration plots and bootstrap validation were used to assess predictive performance for model #3. RESULTS: Data from 117 patients were included. The models' AUCs were: (1) 0.69 (2) 0.72, and (3) 0.76, respectively. The absolute difference in AUC was 0.029 (95% CI -0.057 to 0.114, p=0.25) between model 2 and 1 and 0.038 (95% CI -0.021 to 0.097, p=0.10) between model 3 and 2. CONCLUSIONS: By incorporating covariates known to affect body temperature, we demonstrated improved pretest probability estimates of acute COVID-19 infection. Future work should be undertaken to further develop and validate our model in a larger, multi-institutional sample.

The Pharmacist Discharge Care (PHARM-DC) study: A multicenter RCT of pharmacist-directed transitional care to reduce post-hospitalization utilization.

BACKGROUND: Older adults commonly face challenges in understanding, obtaining, administering, and monitoring medication regimens after hospitalization. These difficulties can lead to avoidable morbidity, mortality, and hospital readmissions. Pharmacist-led peri-discharge interventions can reduce adverse drug events, but few large randomized trials have examined their effectiveness in reducing readmissions. Demonstrating reductions in 30-day readmissions can make a financial case for implementing pharmacist-led programs across hospitals. METHODS/DESIGN: The PHARMacist Discharge Care, or the PHARM-DC intervention, includes medication reconciliation at admission and discharge, medication review, increased communication with caregivers, providers, and retail pharmacies, and patient education and counseling during and after discharge. The intervention is being implemented in two large hospitals: Cedars-Sinai Medical Center and the Brigham and Women's Hospital. To evaluate the intervention, we are using a pragmatic, randomized clinical trial design with randomization at the patient level. The primary outcome is utilization within 30 days of hospital discharge, including unforeseen emergency department visits, observation stays, and readmissions. Randomizing 9776 patients will achieve 80% power to detect an absolute reduction of 2.5% from an estimated baseline rate of 27.5%. Qualitative analysis will use interviews with key stakeholders to study barriers to and facilitators of implementing PHARM-DC. A cost-effectiveness analysis using a time-and-motion study to estimate time spent on the intervention will highlight the potential cost savings per readmission. DISCUSSION: If this trial demonstrates a business case for the PHARM-DC intervention, with few barriers to implementation, hospitals may be much more likely to adopt pharmacist-led peri-discharge medication management programs. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04071951.

Patient Use and Clinical Practice Patterns of Remote Cardiology Clinic Visits in the Era of COVID-19.

Importance: The COVID-19 pandemic has led to an unprecedented shift in ambulatory cardiovascular care from in-person to remote visits. Objective: To understand whether the transition to remote visits is associated with disparities in patient use of care, diagnostic test ordering, and medication prescribing. Design, Setting, and Participants: This cross-sectional study used electronic health records data for all ambulatory cardiology visits at an urban, multisite health system in Los Angeles County, California, during 2 periods: April 1, 2019, to December 31, 2019 (pre-COVID) and April 1 to December 31, 2020 (COVID-era). Statistical analysis was performed from January to February 2021. Exposure: In-person or remote ambulatory cardiology clinic visit at one of 31 during the pre-COVID period or COVID-era period. Main Outcomes and Measures: Comparison of patient characteristics and frequencies of medication ordering and cardiology-specific testing across 4 visit types (pre-COVID in-person (reference), COVID-era in-person, COVID-era video, COVID-era telephone). Results: This study analyzed data from 87 182 pre-COVID in-person, 74 498 COVID-era in-person, 4720 COVID-era video, and 10 381 COVID-era telephone visits. Across visits, 79 572 patients were female (45.0%), 127 080 patients were non-Hispanic White (71.9%), and the mean (SD) age was 68.1 (17.0) years. Patients accessing COVID-era remote visits were more likely to be Asian, Black, or Hispanic individuals (24 934 pre-COVID in-person visits [28.6%] vs 19 742 COVID-era in-person visits [26.5%] vs 3633 COVID-era video visits [30.4%] vs 1435 COVID-era telephone visits [35.0%]; P < .001 for all comparisons), have private insurance (34 063 pre-COVID in-person visits [39.1%] vs 25 474 COVID-era in-person visits [34.2%] vs 2562 COVID-era video visits [54.3%] vs 4264 COVID-era telephone visits [41.1%]; P < .001 for COVID-era in-person vs video and COVID-era in-person vs telephone), and have cardiovascular comorbidities (eg, hypertension: 37 166 pre-COVID in-person visits [42.6%] vs 31 359 COVID-era in-person visits [42.1%] vs 2006 COVID-era video visits [42.5%] vs 5181 COVID-era telephone visits [49.9%]; P < .001 for COVID-era in-person vs telephone; and heart failure: 14 319 pre-COVID in-person visits [16.4%] vs 10 488 COVID-era in-person visits [14.1%] vs 1172 COVID-era video visits [24.8%] vs 2674 COVID-era telephone visits [25.8%]; P < .001 for COVID-era in-person vs video and COVID-era in-person vs telephone). After adjusting for patient and visit characteristics and in comparison with pre-COVID in-person visits, during video and telephone visits, clinicians had lower odds of ordering any medication (COVID-era in-person: odds ratio [OR], 0.62 [95% CI, 0.60-0.64], COVID-era video: OR, 0.22 [95% CI, 0.20-0.24]; COVID-era telephone: OR, 0.14 [95% CI, 0.13-0.15]) or tests, such as electrocardiograms (COVID-era in-person: OR, 0.60 [95% CI, 0.58-0.62]; COVID-era video: OR, 0.03 [95% CI, 0.02-0.04]; COVID-era telephone: OR, 0.02 [95% CI, 0.01-0.03]) or echocardiograms (COVID-era in-person: OR, 1.21 [95% CI, 1.18-1.24]; COVID-era video: OR, 0.47 [95% CI, 0.42-0.52]; COVID-era telephone: OR, 0.28 [95% CI, 0.25-0.31]). Conclusions and Relevance: Patients who were Asian, Black, or Hispanic, had private insurance, and had at least one of several cardiovascular comorbidities used remote cardiovascular care more frequently in the COVID-era period. Clinician ordering of diagnostic testing and medications consistently decreased when comparing pre-COVID vs COVID-era and in-person vs remote visits. Further studies are needed to clarify whether these decreases represent a reduction in the overuse of tests and medications vs an underuse of indicated testing and prescribing.

Association between operational positive depression symptom screen scores on hospital admission and 30-day readmissions.

BACKGROUND: Positive scores on inpatient depression symptom screens have been found to be associated with readmissions, yet most studies have used depression screens collected as part of research studies. OBJECTIVE: We evaluated whether the relationship between depression severity and readmission persisted when depression screening data was obtained for operational purposes. DESIGN: Retrospective analysis studying prospective use of PHQ data. SETTING: Large academic medical center. INTERVENTION: Ward nurses obtained depression screens from patients soon after admission. Patients who answered 'yes' to at least one Patient Health Questionnaire (PHQ)-2 question were screened using the PHQ-9. MAIN OUTCOMES AND MEASURES: We examined the association between depression severity and 30-day readmissions using logistic regression, adjusting for known predictors of hospital readmission. RESULTS: From July 2014-June 2016, 18,792 discharged adult medicine inpatients received an initial depression screen (PHQ-2) and 1105 patients (5.90%) had at least one positive response. Of this group, 3163 patients (6.32%) were readmitted within 30 days. 1128 patients received the PHQ-9. Compared to patients with no depression, patients with moderately-severe depression had 3.03 higher odds (95%CI, 1.44-6.38) and patients with severe depression had 1.63 higher odds (95%CI, 0.70-3.78) of being readmitted, after adjusting for known predictors of hospital admission. Adding PHQ-9 results did not significantly improve the predictive power of a readmissions model. CONCLUSIONS: Our mixed results call into question whether PHQ data obtained for operational purposes may differ compared to data obtained for research purposes. Differences in training of screening staff or patient discomfort with discussing depression in the hospital could explain our findings.