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Background: Clinically important medication errors are common after hospital discharge. They include preventable or ameliorable adverse drug events (ADEs), as well as medication discrepancies or nonadherence with high potential for future harm (potential ADEs).Objective: To determine the effect of a tailored intervention on the occurrence of clinically important medication errors after hospital discharge.Design: Randomized, controlled trial with concealed allocation and blinded outcome assessors. (ClinicalTrials.gov registration number: NCT00632021)Setting: Two tertiary care academic hospitals.Patients: Adults hospitalized with acute coronary syndromes or acute decompensated heart failure.Intervention: Pharmacist-assisted medication reconciliation, inpatient pharmacist counseling, low-literacy adherence aids, and individualized telephone follow-up after discharge.Measurements: The primary outcome was the number of clinically important medication errors per patient during the first 30 days after hospital discharge. Secondary outcomes included preventable or ameliorable ADEs, as well as potential ADEs.Results: Among 851 participants, 432 (50.8%) had 1 or more clinically important medication errors; 22.9% of such errors were judged to be serious and 1.8% life-threatening. Adverse drug events occurred in 258 patients (30.3%) and potential ADEs in 253 patients (29.7%). The intervention did not significantly alter the per-patient number of clinically important medication errors (unadjusted incidence rate ratio, 0.92 [95% CI, 0.77 to 1.10]) or ADEs (unadjusted incidence rate ratio, 1.09 [CI, 0.86 to 1.39]). Patients in the intervention group tended to have fewer potential ADEs (unadjusted incidence rate ratio, 0.80 [CI, 0.61 to 1.04]).Limitation: The characteristics of the study hospitals and participants may limit generalizability.Conclusion: Clinically important medication errors were present among one half of patients after hospital discharge and were not significantly reduced by a health-literacy-sensitive, pharmacist-delivered intervention.Primary Funding Source: National Heart, Lung, and Blood Institute. [ABSTRACT FROM AUTHOR]

Objective: Familiarity with guidelines is generally thought to be associated with guideline implementation, adherence and improved quality of care. We sought to determine if self-reported familiarity with acute respiratory infection (ARI) antibiotic treatment guidelines was associated with reduced or more appropriate antibiotic prescribing for ARIs in primary care.Design: Setting: Participants: andMain Outcome Measures: We surveyed primary care clinicians about their familiarity with ARI antibiotic treatment guidelines and linked responses to administrative diagnostic and prescribing data for non-pneumonia ARI visits.Results: Sixty-five percent of clinicians responded to the survey question about guideline familiarity. There were 208 survey respondents who had ARI patient visits during the study period. Respondents reported being 'not at all' (7%), 'somewhat' (30%), 'moderately' (45%) or 'extremely' (18%) familiar with the guidelines. After dichotomizing responses, compared with clinicians who reported being less familiar with the guidelines, clinicians who reported being more familiar with the guidelines had higher rates of antibiotic prescribing for all ARIs combined (46% versus 38%; n = 11 164; P < 0.0001), for antibiotic-appropriate diagnoses (69% versus 59%; n = 3213; P < 0.0001) and for non-antibiotic appropriate diagnoses (38% versus 28%; n = 7951; P < 0.0001). After adjusting for potential confounders, self-reported guideline familiarity was an independent predictor of increased antibiotic prescribing (odds ratio, 1.36; 95% confidence interval, 1.25-1.48).Conclusions: Self-reported familiarity with an ARI antibiotic treatment guideline was, seemingly paradoxically, associated with increased antibiotic prescribing. Self-reported familiarity with guidelines should not be assumed to be associated with consistent guideline adherence or higher quality of care. [ABSTRACT FROM AUTHOR]

Background and objective: Clinical guidelines discourage antibiotic prescribing for many acute respiratory infections (ARIs), especially for nonantibiotic appropriate diagnoses. Electronic health record (EHR)-based clinical decision support has the potential to improve antibiotic prescribing for ARIs. Methods: We randomly assigned 27 primary care clinics to receive an EHR-integrated, documentationbased clinical decision support system for the care of patients with ARIs -- the ARI Smart Form -- or to offer usual care. The primary outcome was the antibiotic prescribing rate for ARIs in an intentto- intervene analysis based on administrative diagnoses. Results: During the intervention period, patients made 21 961 ARI visits to study clinics. Intervention clinicians used the ARI Smart Form in 6% of 11 954 ARI visits. The antibiotic prescribing rate in the intervention clinics was 39% versus 43% in the control clinics (odds ratio (OR), 0.8; 95% confidence interval (CI), 0.6-1.2, adjusted for clustering by clinic). For antibiotic appropriate ARI diagnoses, the antibiotic prescribing rate was 54% in the intervention clinics and 59% in the control clinics (OR, 0.8; 95% CI, 0.5-1.3). For non-antibiotic appropriate diagnoses, the antibiotic prescribing rate was 32% in the intervention clinics and 34% in the control clinics (OR, 0.9; 95% CI, 0.6-1.4). When the ARI Smart Form was used, based on diagnoses entered on the form, the antibiotic prescribing rate was 49% overall, 88% for antibiotic appropriate diagnoses and 27% for non-antibiotic appropriate diagnoses. In an as-used analysis, the ARI Smart Form was associated with a lower antibiotic prescribing rate for acute bronchitis (OR, 0.5; 95% CI, 0.3-0.8). Conclusions: The ARI Smart Form neither reduced overall antibiotic prescribing nor significantly improved the appropriateness of antibiotic prescribing for ARIs, but it was not widely used. When used, the ARI Smart Form may improve diagnostic accuracy compared to administrative diagnoses and may reduce antibiotic prescribing for certain diagnoses. [ABSTRACT FROM AUTHOR]

We designed the Pre-Admission Medication List (PAML) Builder medication reconciliation application and implemented it at two academic hospitals. We asked 1,714 users to complete a survey of their satisfaction with the application and analyzed factors associated with user efficiency. The survey was completed by 626 (36.5%) users. Most (64%) responders agreed that medication reconciliation improves patient care. Improvement requests included better medication information sources and propagation of medication information to order entry. Sixty-nine percent of admitting clinicians reported a typical time to build a PAML of <10 min. Decreased reported time to build a PAML was associated with reported experience with the application and ease of use but not the average number of medications on the PAML. Most users agreed that medication reconciliation improves patient care but requested tighter integration of the different stages of the medication reconciliation process. Further training may be helpful in improving user efficiency. [ABSTRACT FROM AUTHOR]

Clostridium difficile (C. diff) is a major nosocomial problem. Epidemiological surveillance of the disease can be accomplished by microbiological or administrative data. Microbiological tracking is problematic since it does not always translate into clinical disease, and it is not always available. Tracking by administrative data is attractive, but ICD-9 code accuracy for C. diff is unknown. By using a large administrative database of hospitalized patients with C. diff (by ICD-9 code or cytotoxic assay), this study found that the sensitivity, specificity, positive, and negative predictive values of ICD-9 coding were 71%, 99%, 87%, and 96% respectively (using micro data as the gold standard). When only using symptomatic patients the sensitivity increased to 82% and when only using symptomatic patients whose test results were available at discharge, the sensitivity increased to 88%. C. diff ICD-9 codes closely approximate true C. diff infection, especially in symptomatic patients whose test results are available at the time of discharge, and can therefore be used as a reasonable alternative to microbiological data for tracking purposes. [ABSTRACT FROM AUTHOR]

Confusion about patients' medication regimens during the hospital admission and discharge process accounts for many preventable and serious medication errors. Many organizations have begun to redesign their clinical processes to address this patient safety concern. Partners HealthCare, an integrated delivery network in Boston, Massachusetts, has answered this interdisciplinary challenge by leveraging its multiple outpatient electronic medical records (EMR) and inpatient computerized provider order entry (CPOE) systems to facilitate the process of medication reconciliation. This manuscript describes the design of a novel application and the associated services that aggregate medication data from EMR and CPOE systems so that clinicians can efficiently generate an accurate pre-admission medication list. Information collected with the use of this application subsequently supports the writing of admission and discharge orders by physicians, performance of admission assessment by nurses, and reconciliation of inpatient orders by pharmacists. Results from early pilot testing suggest that this new medication reconciliation process is well accepted by clinicians and has significant potential to prevent medication errors during transitions of care. [ABSTRACT FROM AUTHOR]

Objective: To determine the diagnostic utility of neurovascular ultrasonography (transcranial Doppler and carotid ultrasonography) in patients with syncope.Patients and Methods: We retrospectively identified consecutive patients who underwent neurovascular ultrasonography for the diagnosis of syncope or presyncope at an academic hospital in 1997 and 1998. From medical records we abstracted patient demographic and clinical information, results and consequences of testing, and follow-up data for 3 years.Results: A total of 140 patients participated in the study. The median age of the study patients was 74 years (interquartile range, 66-80 years), and 49% were male. Severe extracranial or Intracranial cerebrovascular disease was found on neurovascular ultrasonography in 20 patients (14%; 95% confidence interval [CI], 9.5%-21%). Focal neurologic signs or symptoms or carotid bruits were found in 19 (95%) of 20 patients with positive test results compared with 46 (38%) of 120 patients without severe disease (P<.001). Ultrasonography identified cerebrovascular lesions that may have contributed to the syncopal process in only 2 (1.4%) of 140 patients (95% CI, 0.39%-5.1%), but the lesions were unlikely to have been the primary cause of syncope in either patient.Conclusion: In this predominantly stroke-age population, neurovascular ultrasonography had a low yield for diagnosing vascular lesions that contributed to the pathophysiology of syncope. However, in patients with focal signs or symptoms or carotid bruits, it detected incidental lesions that typically require treatment or follow-up. In patients with syncope, neurovascular ultrasonography should be reserved for this subset. The data suggest enhancements to the American College of Physicians guideline for the use of neurovascular ultrasonography in patients with syncope. [ABSTRACT FROM AUTHOR]

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., (© 2024. The Author(s).)

Background: Serious Illness Conversations (SICs) are not consistently integrated into existing inpatient workflows., Objective: We assessed the implementation of multiple interventions aimed at encouraging SICs with hospitalized patients., Methods: We used the Consolidated Framework for Implementation Research to identify determinants for conducting SICs by interviewing providers and the Expert Recommendations for Implementing Change to develop a list of interventions. Adult patient encounters with a Readmission Risk Score (RRS) > 28% admitted to a general medicine service from January 2019 to October 2021 and without standardized SIC documentation in the prior year were included. A multivariable segmented logistic regression model, suitable for an interrupted time series analysis, was used to assess changes in the odds of standardized SIC documentation., Results: Barriers included those associated with the COVID-19 pandemic, such as extreme census. Facilitators included the presence of the Speaking About Goals and Expectations program and palliative care consultations. Key interventions included patient identification via the existing Quality and Safety Dashboard (QSD), weekly emails, in-person outreach, and training for faculty and trainees. There was no significant change in the odds of standardized SIC documentation despite interventions (change in temporal trend odds ratio (OR) 1.16, 95% Confidence Interval (CI) 0.98-1.39)., Conclusion: The lack of significant change in standardized SIC documentation may be attributed to insufficient or ineffective interventions and COVID-19-related challenges. Although patient identification is a known barrier to SICs, this issue was minimized with the use of the QSD and RRS. Further research is needed to enhance the implementation of SICs in inpatient settings., (© 2024 Society of Hospital Medicine.)

Background: Adverse event surveillance approaches underestimate the prevalence of harmful diagnostic errors (DEs) related to hospital care., Methods: We conducted a single-centre, retrospective cohort study of a stratified sample of patients hospitalised on general medicine using four criteria: transfer to intensive care unit (ICU), death within 90 days, complex clinical events, and none of the aforementioned high-risk criteria. Cases in higher-risk subgroups were over-sampled in predefined percentages. Each case was reviewed by two adjudicators trained to judge the likelihood of DE using the Safer Dx instrument; characterise harm, preventability and severity; and identify associated process failures using the Diagnostic Error Evaluation and Research Taxonomy modified for acute care. Cases with discrepancies or uncertainty about DE or impact were reviewed by an expert panel. We used descriptive statistics to report population estimates of harmful, preventable and severely harmful DEs by demographic variables based on the weighted sample, and characteristics of harmful DEs. Multivariable models were used to adjust association of process failures with harmful DEs., Results: Of 9147 eligible cases, 675 were randomly sampled within each subgroup: 100% of ICU transfers, 38.5% of deaths within 90 days, 7% of cases with complex clinical events and 2.4% of cases without high-risk criteria. Based on the weighted sample, the population estimates of harmful, preventable and severely harmful DEs were 7.2% (95% CI 4.66 to 9.80), 6.1% (95% CI 3.79 to 8.50) and 1.1% (95% CI 0.55 to 1.68), respectively. Harmful DEs were frequently characterised as delays (61.9%). Severely harmful DEs were frequent in high-risk cases (55.1%). In multivariable models, process failures in assessment, diagnostic testing, subspecialty consultation, patient experience, and history were significantly associated with harmful DEs., Conclusions: We estimate that a harmful DE occurred in 1 of every 14 patients hospitalised on general medicine, the majority of which were preventable. Our findings underscore the need for novel approaches for adverse DE surveillance., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: Post-discharge adverse events (AEs) are common and heralded by new and worsening symptoms (NWS). We evaluated the effect of electronic health record (EHR)-integrated digital tools designed to promote quality and safety in hospitalized patients on NWS and AEs after discharge., Materials and Methods: Adult general medicine patients at a community hospital were enrolled. We implemented a dashboard which clinicians used to assess safety risks during interdisciplinary rounds. Post-implementation patients were randomized to complete a discharge checklist whose responses were incorporated into the dashboard. Outcomes were assessed using EHR review and 30-day call data adjudicated by 2 clinicians and analyzed using Poisson regression. We conducted comparisons of each exposure on post-discharge outcomes and used selected variables and NWS as independent predictors to model post-discharge AEs using multivariable logistic regression., Results: A total of 260 patients (122 pre, 71 post [dashboard], 67 post [dashboard plus discharge checklist]) enrolled. The adjusted incidence rate ratios (aIRR) for NWS and AEs were unchanged in the post- compared to pre-implementation period. For patient-reported NWS, aIRR was non-significantly higher for dashboard plus discharge checklist compared to dashboard participants (1.23 [0.97,1.56], P = .08). For post-implementation patients with an AE, aIRR for duration of injury (>1 week) was significantly lower for dashboard plus discharge checklist compared to dashboard participants (0 [0,0.53], P < .01). In multivariable models, certain patient-reported NWS were associated with AEs (3.76 [1.89,7.82], P < .01)., Discussion: While significant reductions in post-discharge AEs were not observed, checklist participants experiencing a post-discharge AE were more likely to report NWS and had a shorter duration of injury., Conclusion: Interventions designed to prompt patients to report NWS may facilitate earlier detection of AEs after discharge., Clinicaltrials.gov: NCT05232656., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Analysis of documented Serious Illness Conversations (SICs) in the inpatient setting can help clinicians align management to address patient and caregiver needs., Methods: We conducted a mixed methods analysis of the first instance of standardized documentation of a SIC within a structured module among hospitalized general medicine patients from 2018 to 2019. Percentage of documentations that included a description of patient or family understanding of the patient's medical condition and use of radio buttons to answer the "prognostic information shared," "hopes," and "worries" modules are reported. Using grounded theory approach, physicians analyzed free text entries to: "What is important to the patient/family?" and "Recommendations or next steps planned.", Results: Out of 5142 patients, 59 patients had a documented SIC. Patient or family understanding of the medical condition(s) was reported in 56 (95%). For "prognostic information shared," the most frequently selected radio buttons were: 49 (83%) incurable disease and 28 (48%) prognosis of weeks to months while those for "hopes" were: 52 (88%) be comfortable and 27 (46%) be at home and for "worries" were: 49 (83%) other physical suffering and 36 (61%) pain. Themes generated from entries to "What's important to patient/family?" included being with loved ones; comfort; mentally and physically present; and reliable care while those for "Recommendations" were coordinating support services; symptom management; and support and communication., Conclusions: SIC content indicated concern about pain and reliable care suggesting the complex, intensive nature of caring for seriously ill patients and the need to consider SICs earlier in the life course of patients., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Many patients are unable to identify members of their hospital care team and experience confusion regarding some medical terminology used during hospitalization, including descriptions of the structure of their inpatient care team. This cross-sectional study sought to (1) examine inpatients' understanding of the role of a hospitalist and (2) assess inpatients' familiarity with other medical terminology commonly used in the hospital. We surveyed 172 patients admitted to the hospital medicine service at two academic medical centers. We found that almost half (47%) of respondents were unfamiliar with the term and/or role of a hospitalist, while the remaining patients had varied understanding of the role. Several other medical terms were frequently misunderstood (such as "NPO," "PA," and "Attending"). Ongoing efforts are needed to improve communication to ensure that hospitalized patients understand the hospitalist's role and the medical terms shared with them., (© 2024 Society of Hospital Medicine.)

Background: Determining which patients benefit from a serious illness conversation (SIC) is challenging. The authors sought to determine whether Epic's Risk of Readmission Score (RRS), could be combined with a simple, validated, one-question mortality prognostic screen (the surprise question: Would you be surprised if the patient died in the next 12 months?) to identify hospitalized patients with SIC needs., Methods: In this retrospective study, the authors randomly selected encounters for patients ≥ 18 years of age to a general medicine service from January 2019 to October 2021 who had an RRS > 28%. Two adjudicators independently performed chart reviews for each encounter to answer the surprise question to create two distinct prognostic groups (yes vs. no). Fisher's exact test was used to assess for statistically significant differences in standardized documentation of SICs between groups., Results: Out of 2,879 encounters, 202 patient encounters were randomly selected. Adjudicators answered "no" to the surprise question for 156 (77.2%) patients. Patients for whom adjudicators answered "no" were generally older with higher comorbidity and more often had standardized documentation of a SIC (14 [9.0%] vs. 0.[0.0%], p = 0.042) compared to patients for whom adjudicators answered "yes.", Conclusion: Approximately three quarters of patients with a high RRS were predicted to have a lifespan of less than a year. Although these patients were significantly more likely to have a SIC, rates of SICs were extremely low. Combining available electronic health record (EHR) data with a simple one-question screening tool may help identify hospitalized patients who require a SIC in quality improvement initiatives., (Copyright © 2024 The Joint Commission. Published by Elsevier Inc. All rights reserved.)

Objectives:  This study aimed to pilot an application-based patient diagnostic questionnaire (PDQ) and assess the concordance of the admission diagnosis reported by the patient and entered by the clinician., Methods:  Eligible patients completed the PDQ assessing patients' understanding of and confidence in the diagnosis 24 hours into hospitalization either independently or with assistance. Demographic data, the hospital principal problem upon admission, and International Classification of Diseases 10th Revision (ICD-10) codes were retrieved from the electronic health record (EHR). Two physicians independently rated concordance between patient-reported diagnosis and clinician-entered principal problem as full, partial, or no. Discrepancies were resolved by consensus. Descriptive statistics were used to report demographics for concordant (full) and nonconcordant (partial or no) outcome groups. Multivariable logistic regressions of PDQ questions and a priori selected EHR data as independent variables were conducted to predict nonconcordance., Results:  A total of 157 (77.7%) questionnaires were completed by 202 participants; 77 (49.0%), 46 (29.3%), and 34 (21.7%) were rated fully concordant, partially concordant, and not concordant, respectively. Cohen's kappa for agreement on preconsensus ratings by independent reviewers was 0.81 (0.74, 0.88). In multivariable analyses, patient-reported lack of confidence and undifferentiated symptoms (ICD-10 "R-code") for the principal problem were significantly associated with nonconcordance (partial or no concordance ratings) after adjusting for other PDQ questions (3.43 [1.30, 10.39], p  = 0.02) and in a model using selected variables (4.02 [1.80, 9.55], p  < 0.01), respectively., Conclusion:  About one-half of patient-reported diagnoses were concordant with the clinician-entered diagnosis on admission. An ICD-10 "R-code" entered as the principal problem and patient-reported lack of confidence may predict patient-clinician nonconcordance early during hospitalization via this approach., Competing Interests: None declared., (Thieme. All rights reserved.)

The presence of racial and ethnic disparities in interhospital transfer (IHT) within integrated healthcare systems has not been fully explored. We matched Black and Latinx patients admitted to community hospitals in our integrated healthcare system between June 2015 and December 2019 to White patients by origin hospital, age, time of year, and disease severity. We performed conditional logistic regression models to determine if race or ethnicity was associated with IHT in one of the tertiary academic medical centers in the system, adjusting for covariates. The sample contained 107,895 admissions (82.6% White, 7.8% Black, and 9.6% Latinx). Transfer rates were 2.2% versus 2.2% after the Black/White match and 1.8% versus 1.8% after the Latinx/White match. After adjusting for covariates, there was no association between race or ethnicity and IHT (Black vs. White odds ratio [OR]: 0.87, 95% confidence interval [CI]: 0.72-1.07; Latinx vs. White OR: 1.05, 95% CI: 0.79-1.40). This may be due to reduced barriers to transfer with an integrated healthcare system., (© 2024 The Authors. Journal of Hospital Medicine published by Wiley Periodicals LLC on behalf of Society of Hospital Medicine.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Importance: Timely diagnosis and treatment are of paramount importance for patients with head and neck cancer (HNC) because delays are associated with reduced survival rates and increased recurrence risk. Prompt referral to HNC specialists is crucial for the timeliness of care, yet the factors that affect the referral and triage pathway remain relatively unexplored. Therefore, to identify barriers and facilitators of timely care, it is important to understand the complex journey that patients undertake from the onset of HNC symptoms to referral for diagnosis and treatment., Objective: To investigate the referral and triage process for patients with HNC and identify barriers to and facilitators of care from the perspectives of patients and health care workers., Design, Participants, and Setting: This was a qualitative study using semistructured interviews of patients with HNC and health care workers who care for them. Participants were recruited from June 2022 to July 2023 from HNC clinics at 2 tertiary care academic medical centers in Boston, Massachusetts. Data were analyzed from July 2022 to December 2023., Main Outcomes and Measures: Themes identified from the perspectives of both patients and health care workers on factors that hinder or facilitate the HNC referral and triage process., Results: In total, 72 participants were interviewed including 42 patients with HNC (median [range] age, 60.5 [19.0-81.0] years; 27 [64%] females) and 30 health care workers (median [range] age, 38.5 [20.0-68.0] years; 23 [77%] females). Using thematic analysis, 4 major themes were identified: the HNC referral and triage pathway is fragmented; primary and dental care are critical for timely referrals; efficient interclinician coordination expedites care; and consistent patient-practitioner engagement alleviates patient fear., Conclusions and Relevance: These findings describe the complex HNC referral and triage pathway, emphasizing the critical role of initial symptom recognition, primary and dental care, patient information flow, and interclinician and patient-practitioner communication, all of which facilitate prompt HNC referrals.

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., (© 2024. The Author(s), under exclusive licence to Society of General Internal Medicine.)

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., (© 2023. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Background: Serious Illness Conversations (SICs) conducted during hospitalization can lead to meaningful patient participation in the decision-making process affecting medical management. The aim of this study is to determine if standardized documentation of a SIC within an institutionally approved EHR module during hospitalization is associated with palliative care consultation, change in code status, hospice enrollment prior to discharge, and 90-day readmissions. Methods: We conducted retrospective analyses of hospital encounters of general medicine patients at a community teaching hospital affiliated with an academic medical center from October 2018 to August 2019. Encounters with standardized documentation of a SIC were identified and matched by propensity score to control encounters without a SIC in a ratio of 1:3. We used multivariable, paired logistic regression and Cox proportional-hazards modeling to assess key outcomes. Results: Of 6853 encounters (5143 patients), 59 (.86%) encounters (59 patients) had standardized documentation of a SIC, and 58 (.85%) were matched to 167 control encounters (167 patients). Encounters with standardized documentation of a SIC had greater odds of palliative care consultation (odds ratio [OR] 60.10, 95% confidence interval [CI] 12.45-290.08, P < .01), a documented code status change (OR 8.04, 95% CI 1.54-42.05, P = .01), and discharge with hospice services (OR 35.07, 95% CI 5.80-212.08, P < .01) compared to matched controls. There was no significant association with 90-day readmissions (adjusted hazard ratio [HR] .88, standard error [SE] .37, P = .73). Conclusions: Standardized documentation of a SIC during hospitalization is associated with palliative care consultation, change in code status, and hospice enrollment., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: During the COVID-19 pandemic, hospitals were caring for increasing numbers of patients with a novel and highly contagious respiratory illness, forcing adaptations in care delivery. The objective of this study was to understand the impact of these adaptations on patient safety in hospital medicine., Methods: The authors conducted a nationwide survey to understand patient safety challenges experienced by hospital medicine clinicians during the COVID-19 pandemic. The survey was distributed to members of the Society of Hospital Medicine via an e-mail listserv. It consisted of closed- and open-ended questions to elicit respondents' experience in five domains: error reporting and communication, staffing, equipment, personal protective equipment (PPE) and isolation practices, and infrastructure. Quantitative questions were reported as counts and percentages; qualitative responses were coded and analyzed for relevant themes., Results: Of 196 total responses, 167 respondents (85.2%) were attending physicians and 85 (43.8%) practiced at teaching hospitals. Safety concerns commonly identified included nursing shortages (71.0%), limiting patient interactions to conserve PPE (61.9%), and feeling that one was practicing in a more hazardous environment (61.4%). In free-text responses, clinicians described poor outcomes and patient decompensation due to provider and equipment shortages, as well as communication lapses and diagnostic errors resulting from decreased patient contact and the need to follow isolation protocols., Conclusion: Efforts made to accommodate shortages in staff and equipment, adapt to limited PPE, and enforce isolation policies had unintended consequences that affected patient safety and created a more hazardous environment characterized by less efficient care, respiratory decompensations, diagnostic errors, and poor communication with patients., (Copyright © 2023 The Joint Commission. Published by Elsevier Inc. All rights reserved.)

Background: Heart failure (HF) affects 6.2 million Americans and is a leading cause of hospitalization. The mainstay of the management of HF is adherence to pharmacotherapy. Despite the effectiveness of HF pharmacotherapy, effectiveness is closely linked to adherence. Measuring adherence to HF pharmacotherapy is difficult; most clinical measures use indirect strategies such as calculating pharmacy refill data or using self-report. While helpful in guiding treatment adjustments, indirect measures of adherence may miss the detection of suboptimal adherence and co-occurring structural barriers associated with nonadherence. Digital pill systems (DPSs), which use an ingestible radiofrequency emitter to directly measure medication ingestions in real-time, represent a strategy for measuring and responding to nonadherence in the context of HF pharmacotherapy. Previous work has demonstrated the feasibility of using DPSs to measure adherence in other chronic diseases, but this strategy has yet to be leveraged for individuals with HF., Objective: We aim to explore through qualitative interviews the facilitators and barriers to using DPS technology to monitor pharmacotherapy adherence among patients with HF., Methods: We conducted individual, semistructured qualitative interviews and quantitative assessments between April and August 2022. A total of 20 patients with HF who were admitted to the general medical or cardiology service at an urban quaternary care hospital participated in this study. Participants completed a qualitative interview exploring the overall acceptability of and willingness to use DPS technology for adherence monitoring and perceived barriers to DPS use. Quantitative assessments evaluated HF history, existing medication adherence strategies, and attitudes toward technology. We analyzed qualitative data using applied thematic analysis and NVivo software (QSR International)., Results: Most participants (12/20, 60%) in qualitative interviews reported a willingness to use the DPS to measure HF medication adherence. Overall, the DPS was viewed as useful for increasing accountability and reinforcing adherence behaviors. Perceived barriers included technological issues, a lack of need, additional costs, and privacy concerns. Most were open to sharing adherence data with providers to bolster clinical care and decision-making. Reminder messages following detected nonadherence were perceived as a key feature, and customization was desired. Suggested improvements are primarily related to the design and usability of the Reader (a wearable device)., Conclusions: Overall, individuals with HF perceived the DPS to be an acceptable and useful tool for measuring medication adherence. Accurate, real-time ingestion data can guide adherence counseling to optimize adherence management and inform tailored behavioral interventions to support adherence among patients with HF., (©Peter R Chai, Jenson J Kaithamattam, Michelle Chung, Jeremiah J Tom, Georgia R Goodman, Mohammad Adrian Hasdianda, Tony Christopher Carnes, Muthiah Vaduganathan, Benjamin M Scirica, Jeffrey L Schnipper. Originally published in JMIR Cardio (https://cardio.jmir.org), 15.02.2024.)

Importance: Diagnostic errors contribute to patient harm, though few data exist to describe their prevalence or underlying causes among medical inpatients., Objective: To determine the prevalence, underlying cause, and harms of diagnostic errors among hospitalized adults transferred to an intensive care unit (ICU) or who died., Design, Setting, and Participants: Retrospective cohort study conducted at 29 academic medical centers in the US in a random sample of adults hospitalized with general medical conditions and who were transferred to an ICU, died, or both from January 1 to December 31, 2019. Each record was reviewed by 2 trained clinicians to determine whether a diagnostic error occurred (ie, missed or delayed diagnosis), identify diagnostic process faults, and classify harms. Multivariable models estimated association between process faults and diagnostic error. Opportunity for diagnostic error reduction associated with each fault was estimated using the adjusted proportion attributable fraction (aPAF). Data analysis was performed from April through September 2023., Main Outcomes and Measures: Whether or not a diagnostic error took place, the frequency of underlying causes of errors, and harms associated with those errors., Results: Of 2428 patient records at 29 hospitals that underwent review (mean [SD] patient age, 63.9 [17.0] years; 1107 [45.6%] female and 1321 male individuals [54.4%]), 550 patients (23.0%; 95% CI, 20.9%-25.3%) had experienced a diagnostic error. Errors were judged to have contributed to temporary harm, permanent harm, or death in 436 patients (17.8%; 95% CI, 15.9%-19.8%); among the 1863 patients who died, diagnostic error was judged to have contributed to death in 121 (6.6%; 95% CI, 5.3%-8.2%). In multivariable models examining process faults associated with any diagnostic error, patient assessment problems (aPAF, 21.4%; 95% CI, 16.4%-26.4%) and problems with test ordering and interpretation (aPAF, 19.9%; 95% CI, 14.7%-25.1%) had the highest opportunity to reduce diagnostic errors; similar ranking was seen in multivariable models examining harmful diagnostic errors., Conclusions and Relevance: In this cohort study, diagnostic errors in hospitalized adults who died or were transferred to the ICU were common and associated with patient harm. Problems with choosing and interpreting tests and the processes involved with clinician assessment are high-priority areas for improvement efforts.

Background: Few hospitals have built surveillance for diagnostic errors into usual care or used comparative quantitative and qualitative data to understand their diagnostic processes and implement interventions designed to reduce these errors., Objectives: To build surveillance for diagnostic errors into usual care, benchmark diagnostic performance across sites, pilot test interventions, and evaluate the program's impact on diagnostic error rates., Methods and Analysis: Achieving diagnostic excellence through prevention and teamwork (ADEPT) is a multicenter, real-world quality and safety program utilizing interrupted time-series techniques to evaluate outcomes. Study subjects will be a randomly sampled population of medical patients hospitalized at 16 US hospitals who died, were transferred to intensive care, or had a rapid response during the hospitalization. Surveillance for diagnostic errors will occur on 10 events per month per site using a previously established two-person adjudication process. Concurrent reviews of patients who had a qualifying event in the previous week will allow for surveys of clinicians to better understand contributors to diagnostic error, or conversely, examples of diagnostic excellence, which cannot be gleaned from medical record review alone. With guidance from national experts in quality and safety, sites will report and benchmark diagnostic error rates, share lessons regarding underlying causes, and design, implement, and pilot test interventions using both Safety I and Safety II approaches aimed at patients, providers, and health systems. Safety II approaches will focus on cases where diagnostic error did not occur, applying theories of how people and systems are able to succeed under varying conditions. The primary outcome will be the number of diagnostic errors per patient, using segmented multivariable regression to evaluate change in y-intercept and change in slope after initiation of the program., Ethics and Dissemination: The study has been approved by the University of California, San Francisco Institutional Review Board (IRB), which is serving as the single IRB. Intervention toolkits and study findings will be disseminated through partners including Vizient, The Joint Commission, and Press-Ganey, and through national meetings, scientific journals, and publications aimed at the general public., (© 2023 Society of Hospital Medicine.)

Importance: The transfer of patients between hospitals (interhospital transfer, IHT), exposes patients to communication errors and gaps in information exchange., Objective: To design and implement a standardised accept note to improve communication during medical service transfers, and evaluate its impact on patient outcomes., Design: Prospective interventional cohort study., Setting: A 792-bed tertiary care hospital., Participants: All patient transfers from any acute care hospital to the general medicine, cardiology, oncology and intensive care unit (ICU) services between August 2020 and June 2022., Interventions: A standardised accept note template was developed over a 9-month period with key stakeholder input and embedded in the electronic health record, completed by nurses within the hospital's Access Centre., Main Outcomes and Measures: Primary outcome was clinician-reported medical errors collected via surveys of admitting clinicians within 72 hours after IHT patient admission. Secondary outcomes included clinician-reported failures in communication; presence and 'timeliness' of accept note documentation; patient length of stay (LOS) after transfer; rapid response or ICU transfer within 24 hours and in-hospital mortality. All outcomes were analysed postintervention versus preintervention, adjusting for patient demographics, diagnosis, comorbidity, illness severity, admitting service, time of year, hospital COVID census and census of admitting service and admitting team on date of admission., Results: Of the 1004 and 654 IHT patients during preintervention and postintervention periods, surveys were collected on 735 (73.2%) and 462 (70.6%), respectively. Baseline characteristics were similar among patients in each time period and between survey responders and non-responders. Adjusted analyses demonstrated a 27% reduction in clinician-reported medical error rates postimplementation versus preimplementation (11.5 vs 15.8, adjusted OR (aOR) 0.73, 95% CI 0.53 to 0.99). Secondary outcomes demonstrated lower adjusted odds of clinician-reported failures in communication (aOR 0.88; 0.78 to 0.98) and rapid response/ICU transfer (aOR 0.57; 0.34 to 0.97), and improved presence (aOR 2.30; 1.75 to 3.02) and timeliness (-21.4 hours vs -8.7 hours, p<0.001) of accept note documentation. There were no significant differences in LOS or mortality., Conclusions and Relevance: Among 1658 medical patient transfers, implementing a standardised accept note was associated with improved presence and timeliness of accept note documentation, clinician-reported medical errors, failures in communication and clinical decline following transfer, suggesting that improving communication during IHT can improve patient outcomes., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: Patients with opioid use disorder (OUD) are increasingly being hospitalized for acute medical illnesses. Despite initiation of medications for OUD (MOUDs), many discontinue treatment after discharge. To evaluate whether a psychosocial intervention can improve MOUD retention after hospitalization, we conducted a pilot randomized controlled trial of a peer recovery coach intervention., Methods: An existing peer recovery coach intervention was adapted for this trial. Hospitalized adults with OUD receiving MOUD treatment were randomized to receive either a recovery coach intervention or treatment-as-usual. For those in the intervention arm, the coach guided the participant to complete a relapse prevention plan, maintained contact throughout the 6-month follow-up period, encouraged MOUD continuation, and helped to identify community resources. Those receiving treatment-as-usual were discharged with a referral to outpatient treatment. Primary outcome was retention in MOUD treatment at 6 months. Secondary outcomes were the proportion of participants readmitted to the hospital and the number of days until treatment discontinuation and to hospital readmission., Results: Twenty-five individuals who provided consent and randomized to the recovery coach intervention (n = 13) or treatment-as-usual (n = 12) were included in the analysis. No significant differences were found in the proportion of participants retained in MOUD treatment at 6 months (38.5% vs 41.7%, P = 0.87), proportion of participants readmitted at 6 months (46.2% vs 41.2%, P = 0.82), or the time to treatment discontinuation (log-rank P = 0.92) or readmission (log-rank P = 0.85)., Conclusions: This pilot trial failed to demonstrate that a recovery coach intervention improved MOUD treatment retention compared with treatment-as-usual among hospitalized individuals with OUD., Competing Interests: RDW has consulted to Analgesic Solutions, Wayland, MA; ACI Clinical, Bala Cynwyd, PA; and Alkermes, Inc, Waltham, MA. All other authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article., (Copyright © 2023 American Society of Addiction Medicine.)

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., (© 2023. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Background: Despite the high prevalence and significant health effects of intimate partner violence (IPV), little is known about its associations with hospitalization., Objective: To perform a scoping review of how IPV impacts hospitalization rates, characteristics, and outcomes in adult patients., Data Sources: A search of four databases (MEDLINE, Embase, Web of Science, and CINAHL) using a combination of terms including hospitalized patients and IPV revealed 1608 citations., Study Selection and Data Extraction: One reviewer determined eligibility based on inclusion and exclusion criteria, which a second reviewer independently verified. Data were extracted and organized a posteriori into three categories based on research aim: (1) comparative studies of hospitalization risk associated with recent IPV exposure, (2) comparative studies of hospitalization outcomes by IPV exposure, and (3) descriptive studies of hospitalizations for IPV., Results: Of the 12 included studies, 7 were comparative studies of hospitalization risk associated with IPV, 2 were comparative studies of hospitalization outcomes by IPV, and 3 were descriptive studies of hospitalizations for IPV. Nine out of 12 studies focused on specific patient populations. All but one study demonstrated that IPV was associated with increased risk of hospitalization and/or worse hospitalization outcomes. Six of the seven comparative studies showed a positive association between recent IPV and hospitalization risk., Conclusion: This review suggests that IPV exposure increases the risk of hospitalization and/or worsens inpatient outcomes in specific patient populations. Additional work is needed to characterize hospitalization rates and outcomes for persons who have experienced IPV in a broader, nontrauma population., (© 2023 Society of Hospital 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., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Background: The second Multicenter Medication Reconciliation Quality Improvement Study demonstrated a marked reduction in medication discrepancies per patient. The aim of the current analysis was to determine the association of patient exposure to each system-level intervention and receipt of each patient-level intervention on these results., Methods: This study was conducted at 17 North American Hospitals, the study period was 18 months per site, and sites typically adopted interventions after 2-5 months of preintervention data collection. We conducted an on-treatment analysis (ie, an evaluation of outcomes based on patient exposure) of system-level interventions, both at the category level and at the individual component level, based on monthly surveys of implementation site leads at each site (response rate 65%). We then conducted a similar analysis of patient-level interventions, as determined by study pharmacist review of documented activities in the medical record. We analysed the association of each intervention on the adjusted number of medication discrepancies per patient in admission and discharge orders, based on a random sample of up to 22 patients per month per site, using mixed-effects Poisson regression with hospital site as a random effect. We then used a generalised linear mixed-effects model (GLMM) decision tree to determine which patient-level interventions explained the most variance in discrepancy rates., Results: Among 4947 patients, patient exposure to seven of the eight system-level component categories was associated with modest but significant reductions in discrepancy rates (adjusted rate ratios (ARR) 0.75-0.97), as were 15 of the 17 individual system-level intervention components, including hiring, reallocating and training personnel to take a best possible medication history (BPMH) and training personnel to perform discharge medication reconciliation and patient counselling. Receipt of five of seven patient-level interventions was independently associated with large reductions in discrepancy rates, including receipt of a BPMH in the emergency department (ED) by a trained clinician (ARR 0.40, 95% CI 0.37 to 0.43), admission medication reconciliation by a trained clinician (ARR 0.57, 95% CI 0.50 to 0.64) and discharge medication reconciliation by a trained clinician (ARR 0.64, 95% CI 0.57 to 0.73). In GLMM decision tree analyses, patients who received both a BPMH in the ED and discharge medication reconciliation by a trained clinician experienced the lowest discrepancy rates (0.08 per medication per patient)., Conclusion and Relevance: Patient-level interventions most associated with reductions in discrepancies were receipt of a BPMH of admitted patients in the ED and admission and discharge medication reconciliation by a trained clinician. System-level interventions were associated with modest reduction in discrepancies for the average patient but are likely important to support patient-level interventions and may reach more patients. These findings can be used to help hospitals and health systems prioritise interventions to improve medication safety during care transitions., Competing Interests: Competing interests: JLS and ASM received remuneration from American Society of Health-System Pharmacists (ASHP) to develop their best possible medication history training curriculum. JLS received funding from Synapse Medicine for an investigator-initiated study to evaluate the effects of their medication decision support software on hospital pharmacists’ medication recommendations., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Serious Illness Conversations (SICs) explore patients' prognostic awareness, hopes, and worries, and can help establish priorities for their care during and after hospitalization. While identifying patients who benefit from an SIC remains a challenge, this task may be facilitated by use of validated prediction scores available in most commercial electronic health records (EHRs), such as Epic's Readmission Risk Score (RRS). We identified the RRS on admission for all hospital encounters from October 2018 to August 2019 and measured the area under the receiver operating characteristic (AUROC) curve to determine whether RRS could accurately discriminate post discharge 6-month mortality. For encounters with standardized SIC documentation matched in a 1:3 ratio to controls by sex and age (±5 years), we constructed a multivariable, paired logistic regression model and measured the odds of SIC documentation per every 10% absolute increase in RRS. RRS was predictive of 6-month mortality with acceptable discrimination (AUROC .71) and was significantly associated with SIC documentation (adjusted OR 1.42, 95% CI 1.24-1.63). An RRS >28% used to identify patients with post discharge 6-month mortality had a high specificity (89.0%) and negative predictive value (NPV) (97.0%), but low sensitivity (25.2%) and positive predictive value (PPV) (7.9%). RRS may serve as a practical EHR-based screen to exclude patients not requiring an SIC, thereby leaving a smaller cohort to be further evaluated for SIC needs using other validated tools and clinical assessment.

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., (© 2023. The Author(s).)

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., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objective: To describe a user-centered approach to develop, pilot test, and refine requirements for 3 electronic health record (EHR)-integrated interventions that target key diagnostic process failures in hospitalized patients., Materials and Methods: Three interventions were prioritized for development: a Diagnostic Safety Column ( DSC ) within an EHR-integrated dashboard to identify at-risk patients; a Diagnostic Time-Out ( DTO ) for clinicians to reassess the working diagnosis; and a Patient Diagnosis Questionnaire ( PDQ ) to gather patient concerns about the diagnostic process. Initial requirements were refined from analysis of test cases with elevated risk predicted by DSC logic compared to risk perceived by a clinician working group; DTO testing sessions with clinicians; PDQ responses from patients; and focus groups with clinicians and patient advisors using storyboarding to model the integrated interventions. Mixed methods analysis of participant responses was used to identify final requirements and potential implementation barriers., Results: Final requirements from analysis of 10 test cases predicted by the DSC , 18 clinician DTO participants, and 39 PDQ responses included the following: DSC configurable parameters (variables, weights) to adjust baseline risk estimates in real-time based on new clinical data collected during hospitalization; more concise DTO wording and flexibility for clinicians to conduct the DTO with or without the patient present; and integration of PDQ responses into the DSC to ensure closed-looped communication with clinicians. Analysis of focus groups confirmed that tight integration of the interventions with the EHR would be necessary to prompt clinicians to reconsider the working diagnosis in cases with elevated diagnostic error (DE) risk or uncertainty. Potential implementation barriers included alert fatigue and distrust of the risk algorithm ( DSC ); time constraints, redundancies, and concerns about disclosing uncertainty to patients ( DTO ); and patient disagreement with the care team's diagnosis ( PDQ )., Discussion: A user-centered approach led to evolution of requirements for 3 interventions targeting key diagnostic process failures in hospitalized patients at risk for DE., Conclusions: We identify challenges and offer lessons from our user-centered design process., Competing Interests: Dr. Dalal reports consulting fees from MayaMD, which makes AI software for patient engagement and decision support. Dr. Rozenblum reports having an equity in Hospitech Respiration Ltd., which makes Airway Management Solutions. Dr. Bates reports grants and personal fees from EarlySense, personal fees from CDI Negev, equity from ValeraHealth, equity from Clew, equity from MDClone, personal fees and equity from AESOP, and grants from IBM Watson Health, outside the submitted work. Authors otherwise report no conflicts of interest., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: Home hospital (HH) care is hospital-level substitutive care delivered at home for acutely ill patients who traditionally would be cared for in the hospital. Despite HH care programs operating successfully for years and scientific evidence of similar or better outcomes compared with bricks-and-mortar care, HH care outcomes in the United States for respiratory disease have not been evaluated., Research Question: Do outcomes differ between patients admitted to HH care with acute respiratory illness vs those with other acute general medical conditions?, Study Design and Methods: This was a retrospective evaluation of prospectively collected data of patients admitted to HH care (2017-2021). We compared patients requiring admission with respiratory disease (asthma exacerbation [26%], acute exacerbation of COPD [33%], and non-COVID-19 pneumonia [41%]) to all other patients admitted to HH care. During HH care, patients received two nurse and one physician visit daily, IV medications, advanced respiratory therapies, and continuous heart and respiratory rate monitoring. Main outcomes were acute and postacute health care use and safety., Results: We analyzed 1,031 patients; 24% were admitted for respiratory disease. Patients with and without respiratory disease were similar: mean age, 68 ± 17 years, 62% women, and 48% White. Patients with respiratory disease more often were active smokers (21% vs 9%; P < .001). Eighty percent of patients showed an FEV 1 to FVC ratio of ≤ 70; 28% showed a severe or very severe obstructive pattern (n = 118). During HH care, patients with respiratory disease showed less health care use: length of stay (mean, 3.4 vs 4.6 days), laboratory orders (median, 0 vs 2), IV medication (43% vs 73%), and specialist consultation (2% vs 7%; P < .001 for all). Ninety-six percent of patients completed the full admission at home with no mortality in the respiratory group. Within 30 days of discharge, both groups showed similar readmission, ED presentation, and mortality rates., Interpretation: HH care is as safe and effective for patients with acute respiratory disease as for those with other acute general medical conditions. If scaled, it can generate significant high-value capacity for health systems and communities, with opportunities to advance the complexity of care delivered., (Copyright © 2022 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)