Post-Hospitalization Home Monitoring Programs During the COVID-19 Pandemic: Survey Results from the Hospital Medicine Re-engineering Network (HOMERuN).

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic, hospitals and healthcare systems launched innovative responses to emerging needs. The creation and use of programs to remotely follow patient clinical status and recovery after COVID-19 hospitalization has not been thoroughly described. OBJECTIVE: To characterize deployment of remote post-hospital discharge monitoring programs during the COVID-19 pandemic METHODS: Electronic surveys were administered to leaders of 83 US academic hospitals in the Hospital Medicine Re-engineering Network (HOMERuN). An initial survey was completed in March 2021 with follow-up survey completed in July 2022. RESULTS: There were 35 responses to the initial survey (42%) and 15 responses to the follow-up survey (43%). Twenty-two (63%) sites reported a post-discharge monitoring program, 16 of which were newly developed for COVID-19. Physiologic monitoring devices such as pulse oximeters were often provided. Communication with medical teams was often via telephone, with moderate use of apps or electronic medical record integration. Programs launched most commonly between January and June 2020. Only three programs were still active at the time of follow-up survey. CONCLUSIONS: Our findings demonstrate rapid, ad hoc development of post-hospital discharge monitoring programs during the COVID-19 pandemic but with little standardization or evaluation. Additional study could identify the benefits of these programs, instruct their potential application to other disease processes, and inform further development as part of emergency preparedness for upcoming crises.

Racial and Ethnic Disparities in Opioid Prescribing on Hospital Discharge Among Older Adults: A National Retrospective Cohort Study.

BACKGROUND: Disparities in opioid prescribing among racial and ethnic groups have been observed in outpatient and emergency department settings, but it is unknown whether similar disparities exist at discharge among hospitalized older adults. OBJECTIVE: To determine filled opioid prescription rates on hospital discharge by race/ethnicity among Medicare beneficiaries. DESIGN: Retrospective cohort study. PARTICIPANTS: Medicare beneficiaries 65 years or older discharged from hospital in 2016, without opioid fills in the 90 days prior to hospitalization (opioid-naïve). MAIN MEASURES: Race/ethnicity was categorized by the Research Triangle Institute (RTI), grouped as Asian/Pacific Islander, Black, Hispanic, other (American Indian/Alaska Native/unknown/other), and White. The primary outcome was an opioid prescription claim within 2 days of hospital discharge. The secondary outcome was total morphine milligram equivalents (MMEs) among adults with a filled opioid prescription. KEY RESULTS: Among 316,039 previously opioid-naïve beneficiaries (mean age, 76.8 years; 56.2% female), 49,131 (15.5%) filled an opioid prescription within 2 days of hospital discharge. After adjustment, Black beneficiaries were 6% less likely (relative risk [RR] 0.94, 95% CI 0.91-0.97) and Asian/Pacific Islander beneficiaries were 9% more likely (RR 1.09, 95% CI 1.03-1.14) to have filled an opioid prescription when compared to White beneficiaries. Among beneficiaries with a filled opioid prescription, mean total MMEs were lower among Black (356.9; adjusted difference - 4%, 95% CI - 7 to - 1%), Hispanic (327.0; adjusted difference - 7%, 95% CI - 10 to - 4%), and Asian/Pacific Islander (328.2; adjusted difference - 8%, 95% CI - 12 to - 4%) beneficiaries when compared to White beneficiaries (409.7). CONCLUSIONS AND RELEVANCE: Black older adults were less likely to fill a new opioid prescription after hospital discharge when compared to White older adults and received lower total MMEs. The factors contributing to these differential prescribing patterns should be investigated further.

Analysis of Clinical Criteria for Discharge Among Patients Hospitalized for COVID-19: Development and Validation of a Risk Prediction Model.

BACKGROUND: Patients hospitalized with COVID-19 can clinically deteriorate after a period of initial stability, making optimal timing of discharge a clinical and operational challenge. OBJECTIVE: To determine risks for post-discharge readmission and death among patients hospitalized with COVID-19. DESIGN: Multicenter retrospective observational cohort study, 2020-2021, with 30-day follow-up. PARTICIPANTS: Adults admitted for care of COVID-19 respiratory disease between March 2, 2020, and February 11, 2021, to one of 180 US hospitals affiliated with the HCA Healthcare system. MAIN MEASURES: Readmission to or death at an HCA hospital within 30 days of discharge was assessed. The area under the receiver operating characteristic curve (AUC) was calculated using an internal validation set (33% of the HCA cohort), and external validation was performed using similar data from six academic centers associated with a hospital medicine research network (HOMERuN). KEY RESULTS: The final HCA cohort included 62,195 patients (mean age 61.9 years, 51.9% male), of whom 4704 (7.6%) were readmitted or died within 30 days of discharge. Independent risk factors for death or readmission included fever within 72 h of discharge; tachypnea, tachycardia, or lack of improvement in oxygen requirement in the last 24 h; lymphopenia or thrombocytopenia at the time of discharge; being ≤ 7 days since first positive test for SARS-CoV-2; HOSPITAL readmission risk score ≥ 5; and several comorbidities. Inpatient treatment with remdesivir or anticoagulation were associated with lower odds. The model's AUC for the internal validation set was 0.73 (95% CI 0.71-0.74) and 0.66 (95% CI 0.64 to 0.67) for the external validation set. CONCLUSIONS: This large retrospective study identified several factors associated with post-discharge readmission or death in models which performed with good discrimination. Patients 7 or fewer days since test positivity and who demonstrate potentially reversible risk factors may benefit from delaying discharge until those risk factors resolve.

A Public Health Critical Race Praxis Informed Congestive Heart Failure Quality Improvement Initiative on Inpatient General Medicine.

BACKGROUND: Prior evaluation at our hospital demonstrated that, compared to White patients, Black and Latinx patients with congestive heart failure (CHF) were less likely to be admitted to the cardiology service rather than the general medicine service (GMS). Patients admitted to GMS (compared to cardiology) had inferior rates of cardiology follow-up and 30-day readmission. OBJECTIVE: To develop and test the feasibility and impacts of using quality improvement (QI) methods, in combination with the Public Health Critical Race Praxis (PHCRP) framework, to engage stakeholders in developing an intervention for ensuring guideline-concordant inpatient CHF care across all patient groups. METHODS: We compared measures for all patients admitted with CHF to GMS between September 2019 and March 2020 (intervention group) to CHF patients admitted to GMS in the previous year (pre-intervention group) and those admitted to cardiology during the pre-intervention and intervention periods (cardiology group). Our primary measures were 30-day readmissions and 14- and 30-day post-discharge cardiology follow-up. RESULTS: There were 79 patients admitted with CHF to GMS during the intervention period, all of whom received the intervention. There were similar rates of Black and Latinx patients across the three groups. Compared to pre-intervention, intervention patients had a significantly lower 30-day readmission rate (18.9% vs. 24.8%; p=0.024), though the cardiology group also had a decrease in 30-day readmissions from the pre-intervention to intervention period. Compared to pre-intervention, intervention patients had significantly higher 14-day and 30-day post-discharge follow-up visits scheduled with cardiology (36.7% vs. 24.8%, p=0.005; 55.7% vs. 42.3%, p=0.0029), but no improvement in appointment attendance. CONCLUSION: This study provides a first test of applying the PHCRP framework within a stakeholder-engaged QI initiative for improving CHF care across races and ethnicities. Our study design cannot evaluate causation. However, the improvements in 30-day readmission, as well as in processes of care that may affect it, provide optimism that inclusion of a racism-conscious framework in QI initiatives is feasible and may enhance QI measures.

Inpatient Understanding of Their Care Team and Receipt of Mixed Messages: a Two-Site Cross-Sectional Study.

BACKGROUND: Patient understanding of their care, supported by physician involvement and consistent communication, is key to positive health outcomes. However, patient and care team characteristics can hinder this understanding. OBJECTIVE: We aimed to assess inpatients' understanding of their care and their perceived receipt of mixed messages, as well as the associated patient, care team, and hospitalization characteristics. DESIGN: We administered a 30-item survey to inpatients between February 2020 and November 2021 and incorporated other hospitalization data from patients' health records. PARTICIPANTS: Randomly selected inpatients at two urban academic hospitals in the USA who were (1) admitted to general medicine services and (2) on or past the third day of their hospitalization. MAIN MEASURES: Outcome measures include (1) knowledge of main doctor and (2) frequency of mixed messages. Potential predictors included mean notes per day, number of consultants involved in the patient's care, number of unit transfers, number of attending physicians, length of stay, age, sex, insurance type, and primary race. KEY RESULTS: A total of 172 patients participated in our survey. Most patients were unaware of their main doctor, an issue related to more daily interactions with care team members. Twenty-three percent of patients reported receiving mixed messages at least sometimes, most often between doctors on the primary team and consulting doctors. However, the likelihood of receiving mixed messages decreased with more daily interactions with care team members. CONCLUSIONS: Patients were often unaware of their main doctor, and almost a quarter perceived receiving mixed messages about their care. Future research should examine patients' understanding of different aspects of their care, and the nature of interactions that might improve clarity around who's in charge while simultaneously reducing the receipt of mixed messages.

Prevalence and Causes of Diagnostic Errors in Hospitalized Patients Under Investigation for COVID-19.

BACKGROUND: The COVID-19 pandemic required clinicians to care for a disease with evolving characteristics while also adhering to care changes (e.g., physical distancing practices) that might lead to diagnostic errors (DEs). OBJECTIVE: To determine the frequency of DEs and their causes among patients hospitalized under investigation (PUI) for COVID-19. DESIGN: Retrospective cohort. SETTING: Eight medical centers affiliated with the Hospital Medicine ReEngineering Network (HOMERuN). TARGET POPULATION: Adults hospitalized under investigation (PUI) for COVID-19 infection between February and July 2020. MEASUREMENTS: We randomly selected up to 8 cases per site per month for review, with each case reviewed by two clinicians to determine whether a DE (defined as a missed or delayed diagnosis) occurred, and whether any diagnostic process faults took place. We used bivariable statistics to compare patients with and without DE and multivariable models to determine which process faults or patient factors were associated with DEs. RESULTS: Two hundred and fifty-seven patient charts underwent review, of which 36 (14%) had a diagnostic error. Patients with and without DE were statistically similar in terms of socioeconomic factors, comorbidities, risk factors for COVID-19, and COVID-19 test turnaround time and eventual positivity. Most common diagnostic process faults contributing to DE were problems with clinical assessment, testing choices, history taking, and physical examination (all p < 0.01). Diagnostic process faults associated with policies and procedures related to COVID-19 were not associated with DE risk. Fourteen patients (35.9% of patients with errors and 5.4% overall) suffered harm or death due to diagnostic error. LIMITATIONS: Results are limited by available documentation and do not capture communication between providers and patients. CONCLUSION: Among PUI patients, DEs were common and not associated with pandemic-related care changes, suggesting the importance of more general diagnostic process gaps in error propagation.

Early Expected Discharge Date Accuracy During Hospitalization: A Multivariable Analysis.

INTRODUCTION: Accurate estimation of an expected discharge date (EDD) early during hospitalization impacts clinical operations and discharge planning. METHODS: We conducted a retrospective study of patients discharged from six general medicine units at an academic medical center in Boston, MA from January 2017 to June 2018. We retrieved all EDD entries and patient, encounter, unit, and provider data from the electronic health record (EHR), and public weather data. We excluded patients who expired, discharged against medical advice, or lacked an EDD within the first 24 h of hospitalization. We used generalized estimating equations in a multivariable logistic regression analysis to model early EDD accuracy (an accurate EDD entered within 24 h of admission), adjusting for all covariates and clustering by patient. We similarly constructed a secondary multivariable model using covariates present upon admission alone. RESULTS: Of 3917 eligible hospitalizations, 890 (22.7%) had at least one accurate early EDD entry. Factors significantly positively associated (OR > 1) with an accurate early EDD included clinician-entered EDD, admit day and discharge day during the work week, and teaching clinical units. Factors significantly negatively associated (OR < 1) with an accurate early EDD included Elixhauser Comorbidity Index ≥ 11 and length of stay of two or more days. C-statistics for the primary and secondary multivariable models were 0.75 and 0.60, respectively. CONCLUSIONS: EDDs entered within the first 24 h of admission were often inaccurate. While several variables from the EHR were associated with accurate early EDD entries, few would be useful for prospective prediction.

Predictors and Reasons Why Patients Decline to Participate in Home Hospital: a Mixed Methods Analysis of a Randomized Controlled Trial.

BACKGROUND: Acute care at home ("home hospital") compared to traditional hospital care has been shown to lower cost, utilization, and readmission and improve patient experience and physical activity. Despite these benefits, many patients decline to enroll in home hospital. OBJECTIVE: Describe predictors and reasons why patients decline home hospital. DESIGN: Mixed methods evaluation of a randomized controlled trial. PARTICIPANTS: Patients in the emergency department who required admission and were accepted for home hospital by the home hospital attending, but ultimately declined to enroll. INTERVENTION: Home hospital care, including nurse and physician home visits, intravenous medications, remote monitoring, video communication, and point-of-care testing. APPROACH: We conducted a thematic content analysis of verbatim reasons for decline. We performed bivariate comparisons then multivariable logistic regression to identify patient characteristics associated with declining participation. KEY RESULTS: Two hundred forty-eight patients were eligible to enroll, and 157 (63%) declined enrollment. Patients who declined and enrolled were of similar age (median age, 74 vs 75 years old; p = 0.27), sex (32% vs 36% female; p = 0.49), and race/ethnicity (p = 0.26). In multivariable analysis, patients were significantly more likely to decline if they initially presented at the community hospital compared to the academic medical center (53% vs 42%; adjusted OR, 2.2 [95% CI, 1.2 to 4.2]) and if single (37% v 24%; adjusted OR, 2.5 [95% CI, 1.2 to 5.1]). We formulated 10 qualitative categories describing reasons patients ultimately declined. Many patients declined because they felt it was easier to remain in the hospital (20%) or felt safer in the hospital than in their home (20%). CONCLUSIONS: Patients who declined to enroll in a home hospital intervention had similar sociodemographic characteristics as enrollees except partner status and declined most often for perceptions surrounding safety at home and the ease of remaining in the hospital. TRIAL REGISTRATION: NCT03203759.

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 .

An electronic pillbox intervention designed to improve medication safety during care transitions: challenges and lessons learned regarding implementation and evaluation.

BACKGROUND: Adverse drug events are common during transitions of care. As part of the Smart Pillbox study, a cluster-randomized controlled trial of an electronic pillbox designed to reduce medication discrepancies and improve medication adherence after hospital discharge, we explored barriers to successful implementation and evaluation of this intervention. METHODS: Eligible patients were those admitted to a medicine service of a large teaching hospital with a plan to be discharged home on five or more chronic medications. The intervention consisted of an electronic pillbox with pre-filled weekly blister pack medication trays given to patients prior to discharge. Pillbox features included alarms to take medications, detection of pill removal from each well, alerts to patients or caregivers by phone, email, or text if medications were not taken, and adherence reports accessible by providers. Greater than 20% missed doses for three days in a row triggered outreach from a pharmacist. To identify barriers to implementation and evaluation of the intervention, we reviewed patient exit surveys, including quantitative data on satisfaction and free-text responses regarding their experiences; technical issue logs; and team meeting minutes. Themes were derived by consensus among the study authors and organized using the Consolidated Framework for Implementation Research. RESULTS: Barriers to implementation included intervention characteristics such as perceived portability issues with the pillbox and time required by pharmacists to enter medication information into the software; external policies such as lack of insurance coverage for early refills and regulatory prohibitions on repackaging medications; implementation climate issues such as the incompatibility between the rushed nature of hospital discharge with the time required to deploy the intervention; and patient issues such as denial of previous problems with medication adherence. We founds several obstacles to conducting the study, including patients declining study enrollment and limited attempts by the hospital to streamline logistics by building the intervention into usual care. Several solutions to address many of these challenges were implemented or planned. Despite these challenges, many patients with the pillbox were pleased with the service and believed the intervention worked well for them. CONCLUSIONS: In this evaluation, several barriers to implementing and conducting a study of the effectiveness of the intervention were identified. Our findings provide lessons learned for others wishing to implement and evaluate HIT-related interventions designed to improve medication safety during care transitions. TRIAL REGISTRATION: Clinicaltrials.gov NCT03475030.

How Do Care Transitions Work?: Unraveling the Working Mechanisms of Care Transition Interventions.

BACKGROUND: Failure of safe care transitions after hospital discharge results in unnecessary worsening of symptoms, extended period of illness or readmission to the hospital. OBJECTIVE: The objective of this study was to add to the understanding of the working of care transition interventions between hospital and home through unraveling the contextual elements and mechanisms that may have played a role in the success of these interventions, and by developing a conceptual model of how these components relate to each other. RESEARCH DESIGN: This was a qualitative study using in-person, semi-structured interviews, based on realist evaluation methods. SUBJECTS: A total of 26 researchers, designers, administrators, and/or practitioners of both current "leading" care transitions interventions and of less successful care transition intervention studies or practices. MEASURES: The contextual elements and working mechanisms of the different care transition intervention studies or practices. RESULTS: Three main contextual factors (internal environment, external environment, and patient population) and 7 working mechanisms (simplifiying, verifiying, connecting, translating, coaching, monitoring, and anticipating) were found to be relevant to the outcome of care transition interventions. Context, Intervention, Mechanism, and Outcome (CIMO) configurations revealed that, in response to these contextual factors, care transition interventions triggered one or several of the mechanisms, in turn generating outcomes, including a safer care transition. CONCLUSION: We developed a conceptual model which explains the working of care transition interventions within different contexts, and believe it can help support future successful implementation of care transition interventions.

Implementation of Complex Interventions: Lessons Learned From the Patient-Centered Outcomes Research Institute Transitional Care Portfolio.

BACKGROUND: Despite the well-documented risks to patient safety associated with transitions from one care setting to another, health care organizations struggle to identify which interventions to implement. Multiple strategies are often needed, and studying the effectiveness of these complex interventions is challenging. OBJECTIVE: The objective of this study was to present lessons learned in implementing and evaluating complex transitional care interventions in routine clinical care. RESEARCH DESIGN: Nine transitional care study teams share important common lessons in designing complex interventions with stakeholder engagement, implementation, and evaluation under pragmatic conditions (ie, using only existing resources), and disseminating findings in outlets that reach policy makers and the people who could ultimately benefit from the research. RESULTS: Lessons learned serve as a guide for future studies in 3 areas: (1) Delineating the function (intended purpose) versus form (prespecified modes of delivery of the intervention); (2) Evaluating both the processes supporting implementation and the impact of adaptations; and (3) Engaging stakeholders in the design and delivery of the intervention and dissemination of study results. CONCLUSION: These lessons can help guide future pragmatic studies of care transitions.

Hospital-Level Care at Home for Acutely Ill Adults: a Qualitative Evaluation of a Randomized Controlled Trial.

BACKGROUND: Substitutive hospital-level care in a patient's home ("home hospital") has been shown to lower cost, utilization, and readmission compared to traditional hospital care. However, patients' perspectives to help explain how and why interventions like home hospital accomplish many of these results are lacking. OBJECTIVE: Elucidate and explain patient perceptions of home hospital versus traditional hospital care to better describe the different perceptions of care in both settings. DESIGN: Qualitative evaluation of a randomized controlled trial. PARTICIPANTS: 36 hospitalized patients (19 home; 17 control). INTERVENTION: Traditional hospital ("control") versus home hospital ("home"), including nurse and physician home visits, intravenous medications, remote monitoring, video communication, and point-of-care testing. APPROACH: We conducted a thematic content analysis of semi-structured interviews. Team members developed a coding structure through a multiphase approach, utilizing a constant comparative method. KEY RESULTS: Themes clustered around 3 domains: clinician factors, factors promoting healing, and systems factors. Clinician factors were similar in both groups; both described beneficial interactions with clinical staff; however, home patients identified greater continuity of care. For factors promoting healing, home patients described a locus of control surrounding their sleep, activity, and environmental comfort that control patients lacked. For systems factors, home patients experienced more efficient processes and logistics, particularly around admission and technology use, while both noted difficulty with discharge planning. CONCLUSIONS: Compared to control patients, home patients had better experiences with their care team, had more experiences promoting healing such as better sleep and physical activity, and had better experiences with systems factors such as the admission processes. Potential explanations include continuity of care, the power and familiarity of the home, and streamlined logistics. Future improvements include enhanced care transitions and ensuring digital interfaces are usable. TRIAL REGISTRATION: NCT03203759.

Discharge Practices for COVID-19 Patients: Rapid Review of Published Guidance and Synthesis of Documents and Practices at 22 US Academic Medical Centers.

BACKGROUND: There are currently no evidence-based guidelines that provide standardized criteria for the discharge of COVID-19 patients from the hospital. OBJECTIVE: To address this gap in practice guidance, we reviewed published guidance and collected discharge protocols and procedures to identify and synthesize common practices. DESIGN: Rapid review of existing guidance from US and non-US public health organizations and professional societies and qualitative review using content analysis of discharge documents collected from a national sample of US academic medical centers with follow-up survey of hospital leaders SETTING AND PARTICIPANTS: We reviewed 65 websites for major professional societies and public health organizations and collected documents from 22 Academic Medical Centers (AMCs) in the US participating in the HOspital MEdicine Reengineering Network (HOMERuN). RESULTS: We synthesized data regarding common practices around 5 major domains: (1) isolation and transmission mitigation; (2) criteria for discharge to non-home settings including skilled nursing, assisted living, or homeless; (3) clinical criteria for discharge including oxygenation levels, fever, and symptom improvement; (4) social support and ability to perform activities of daily living; (5) post-discharge instructions, monitoring, and follow-up. LIMITATIONS: We used streamlined methods for rapid review of published guidance and collected discharge documents only in a focused sample of US academic medical centers. CONCLUSION: AMCs studied showed strong consensus on discharge practices for COVID-19 patients related to post-discharge isolation and transmission mitigation for home and non-home settings. There was high concordance among AMCs that discharge practices should address COVID-19-specific factors in clinical, functional, and post-discharge monitoring domains although definitions and details varied.

Hospital-Level Care at Home for Acutely Ill Adults: A Randomized Controlled Trial.

Background: Substitutive hospital-level care in a patient's home may reduce cost, health care use, and readmissions while improving patient experience, although evidence from randomized controlled trials in the United States is lacking. Objective: To compare outcomes of home hospital versus usual hospital care for patients requiring admission. Design: Randomized controlled trial. (ClinicalTrials.gov: NCT03203759). Setting: Academic medical center and community hospital. Patients: 91 adults (43 home and 48 control) admitted via the emergency department with selected acute conditions. Intervention: Acute care at home, including nurse and physician home visits, intravenous medications, remote monitoring, video communication, and point-of-care testing. Measurements: The primary outcome was the total direct cost of the acute care episode (sum of costs for nonphysician labor, supplies, medications, and diagnostic tests). Secondary outcomes included health care use and physical activity during the acute care episode and at 30 days. Results: The adjusted mean cost of the acute care episode was 38% (95% CI, 24% to 49%) lower for home patients than control patients. Compared with usual care patients, home patients had fewer laboratory orders (median per admission, 3 vs. 15), imaging studies (median, 14% vs. 44%), and consultations (median, 2% vs. 31%). Home patients spent a smaller proportion of the day sedentary (median, 12% vs. 23%) or lying down (median, 18% vs. 55%) and were readmitted less frequently within 30 days (7% vs. 23%). Limitation: The study involved 2 sites, a small number of home physicians, and a small sample of highly selected patients (with a 63% refusal rate among potentially eligible patients); these factors may limit generalizability. Conclusion: Substitutive home hospitalization reduced cost, health care use, and readmissions while increasing physical activity compared with usual hospital care. Primary Funding Source: Partners HealthCare Center for Population Health and internal departmental funds.

Identifying Racial/Ethnic Disparities in Interhospital Transfer: an Observational Study.

BACKGROUND: Interhospital transfer (IHT) is often performed to provide patients with specialized care. Racial/ethnic disparities in IHT have been suggested but are not well-characterized. OBJECTIVE: To evaluate the association between race/ethnicity and IHT. DESIGN: Cross-sectional analysis of 2016 National Inpatient Sample data. PATIENTS: Patients aged ≥ 18 years old with common medical diagnoses at transfer, including acute myocardial infarction, congestive heart failure, arrhythmia, stroke, sepsis, pneumonia, and gastrointestinal bleed. MAIN MEASURES: We performed a series of logistic regression models to estimate adjusted odds of transfer by race/ethnicity controlling for patient demographics, clinical variables, and hospital characteristics and to identify potential mediators. In secondary analyses, we estimated adjusted odds of transfer among patients at community hospitals (those more likely to transfer patients) and performed subgroup analyses by region and primary medical diagnosis. KEY RESULTS: Of 5,774,175 weighted hospital admissions, 199,015 (4.5%) underwent IHT, including 4.7% of White patients, compared with 3.9% of Black patients and 3.8% of Hispanic patients. Black (OR 0.83, 95% CI 0.78-0.89) and Hispanic (OR 0.81, 95% CI 0.75-0.87) patients had lower crude odds of transfer compared with White patients, but this became non-significant after adjusting for hospital-level characteristics. In secondary analyses among patients hospitalized at community hospitals, Hispanic patients had lower adjusted odds of transfer (aOR 0.89, 95% CI 0.79-0.98). Disparities in IHT by race/ethnicity varied by region and medical diagnosis. CONCLUSIONS: Black and Hispanic patients had lower odds of IHT, largely explained by a higher likelihood of being hospitalized at urban teaching hospitals. Racial/ethnic disparities in transfer were demonstrated at community hospitals, in certain geographic regions and among patients with specific diseases.

Impact of Medications for Opioid Use Disorder on Discharge Against Medical Advice Among People Who Inject Drugs Hospitalized for Infective Endocarditis.

BACKGROUND AND OBJECTIVES: The impact of medications for opioid use disorder (MOUD) on against medical advice (AMA) discharges among people who inject drugs (PWID) hospitalized for endocarditis is unknown. METHODS: A retrospective review of all PWID hospitalized for endocarditis at our institution between 2016 and 2018 (n = 84). RESULTS: PWID engaged with MOUD at admission, compared with those who were not, were less likely to be discharged AMA but this did not reach statistical significance in adjusted analysis (odds ratio [OR], 0.22; 95% confidence interval [CI], 0.033-1.41; P = .11). Among out-of-treatment individuals, newly initiating MOUD did not lead to significantly fewer AMA discharges (OR, 0.98; 95% CI, 0.26-3.7; P = .98). CONCLUSION AND SCIENTIFIC SIGNIFICANCE: PWID hospitalized for endocarditis are at high risk for discharge AMA but more research is needed to understand the impact of MOUD. (Am J Addict 2020;29:155-159).

Patterns of multimorbidity associated with 30-day readmission: a multinational study.

BACKGROUND: Multimorbidity is associated with higher healthcare utilization; however, data exploring its association with readmission are scarce. We aimed to investigate which most important patterns of multimorbidity are associated with 30-day readmission. METHODS: We used a multinational retrospective cohort of 126,828 medical inpatients with multimorbidity defined as ≥2 chronic diseases. The primary and secondary outcomes were 30-day potentially avoidable readmission (PAR) and 30-day all-cause readmission (ACR), respectively. Only chronic diseases were included in the analyses. We presented the OR for readmission according to the number of diseases or body systems involved, and the combinations of diseases categories with the highest OR for readmission. RESULTS: Multimorbidity severity, assessed as number of chronic diseases or body systems involved, was strongly associated with PAR, and to a lesser extend with ACR. The strength of association steadily and linearly increased with each additional disease or body system involved. Patients with four body systems involved or nine diseases already had a more than doubled odds for PAR (OR 2.35, 95%CI 2.15-2.57, and OR 2.25, 95%CI 2.05-2.48, respectively). The combinations of diseases categories that were most strongly associated with PAR and ACR were chronic kidney disease with liver disease or chronic ulcer of skin, and hematological malignancy with esophageal disorders or mood disorders, respectively. CONCLUSIONS: Readmission was associated with the number of chronic diseases or body systems involved and with specific combinations of diseases categories. The number of body systems involved may be a particularly interesting measure of the risk for readmission in multimorbid patients.

Design of MARQUIS2: study protocol for a mentored implementation study of an evidence-based toolkit to improve patient safety through medication reconciliation.

BACKGROUND: The first Multi-center Medication Reconciliation Quality Improvement Study (MARQUIS1) demonstrated that implementation of a medication reconciliation best practices toolkit decreased total unintentional medication discrepancies in five hospitals. We sought to implement the MARQUIS toolkit in more diverse hospitals, incorporating lessons learned from MARQUIS1. METHODS: MARQUIS2 is a pragmatic, mentored implementation QI study which collected clinical and implementation outcomes. Sites implemented a revised toolkit, which included interventions from these domains: 1) best possible medication history (BPMH)-taking; 2) discharge medication reconciliation and patient/caregiver counseling; 3) identifying and defining clinician roles and responsibilities; 4) risk stratification; 5) health information technology improvements; 6) improved access to medication sources; 7) identification and correction of real-time discrepancies; and, 8) stakeholder engagement. Eight hospitalists mentored the sites via one site visit and monthly phone calls over the 18-month intervention period. Each site's local QI team assessed opportunities to improve, implemented at least one of the 17 toolkit components, and accessed a variety of resources (e.g. implementation manual, webinars, and workshops). Outcomes to be assessed will include unintentional medication discrepancies per patient. DISCUSSION: A mentored multi-center medication reconciliation QI initiative using a best practices toolkit was successfully implemented across 18 medical centers. The 18 participating sites varied in size, teaching status, location, and electronic health record (EHR) platform. We introduce barriers to implementation and lessons learned from MARQUIS1, such as the importance of utilizing dedicated, trained medication history takers, simple EHR solutions, clarifying roles and responsibilities, and the input of patients and families when improving medication reconciliation.