Cowart, Jennifer B.

BACKGROUND: Publicly reported 30-day acute myocardial infarction (AMI) mortality rates are widely used to benchmark hospital performance. However, these measures may lack validity when they include deaths among patients with do-not-resuscitate (DNR) orders or those receiving palliative care—groups for whom mortality may be expected and goal-concordant. METHODS: We analyzed the national 100% Medicare Inpatient Standard Analytic File and Medicare Beneficiary Summary file to assess 30-day AMI mortality rates stratified by DNR status (absent, present-on-admission, and postadmission) and palliative care involvement. We then conducted a retrospective chart review of all 30-day AMI mortalities at a single academic medical center (2019–2025), applying Global Registry of Acute Coronary Events and a Palliative Performance Scale scores to identify unpreventable deaths, which we defined as a Global Registry of Acute Coronary Events >190.5 or Palliative Performance Scale ≤40%. Global Registry of Acute Coronary Events is a risk-stratification tool using clinical and laboratory variables whereas the Palliative Performance Scale is a bedside functional status and palliative care assessment quantifying patient’s self-care ability. RESULTS: Across n=467 259 total AMI encounters, mean (SD) age was 75.1 (10.5), and the population was 44% female. Thirty-day mortality was 10.4% (39 112/376 062) among patients without DNRs, 43.1% (26 181/60 719) in those with present-on-admission DNR, and 72.1% (21 984/30 478) in those with postadmission DNR. Among 9.2% (43 090/467 259) of encounters with palliative care, there was a 76.9% mortality rate (33 151/43 090). Hazard ratios for mortality were 5.25 (95% CI, 5.17–5.33) for present-on-admission DNR and 10.73 (95% CI, 10.55–10.91) for postadmission DNR as compared with encounters without DNRs. Among n=24 AMI mortalities at our institution, 71% (17/24) had DNRs, and 33% (8/24) met the unpreventable death criteria. CONCLUSIONS: The validity of 30-day AMI mortality metrics may be undermined by their inclusion of high-acuity, end-of-life patients, which may disincentivize hospitals from delivering appropriate, patient-centered care. Removal of DNR or palliative cases from performance measures should be explored to better identify opportunities for reducing preventable deaths.

Background: Patient safety event reporting systems are essential for identifying potential risks and improving patient outcomes. However, traditional systems frequently face issues of under-reporting, particularly concerning near-miss and no-harm events, thereby limiting opportunities for organizational learning and harm prevention. This initiative used quality improvement principles to design a new reporting system at our institution to enhance safety culture. Methods: Following extensive stakeholder feedback and multidisciplinary collaboration, a new system was implemented on July 22, 2022. Key features included streamlined reporting, centralized data analysis, and enhanced transparency. Results: Overall event reporting as well as proportional reporting of near-miss and no-harm events increased significantly from around 60% preimplementation to 80% after implementation. Staff engagement also improved, as shown by a steady rise in the number of unique event reporters and reviewers. Conclusions: The new reporting system has improved reporting overall, with increases in near-miss and no-harm events, along with increased staff engagement with the reporting and review process. Our experience offers practical lessons for institutions seeking to strengthen the learning value of event reporting systems. The principles we identified with simplifying ease of use, integrating into the EHR, improving data transparency, and encouraging greater involvement with event review, along with clear oversight protocols, apply beyond our institution and are not limited to a specific PSRS product or system. These initial outcomes support a culture of safety and bolster organizational learning, with future study needed on long-term effects on patient safety outcomes, staff involvement, and increased trust.

Abstract Boarding of admitted patients in the emergency department (ED) is increasingly common and frequently discussed as an issue related to ED throughput. However, ED boarding should instead be seen as a symptom of systemic issues relating to hospital capacity and throughput, requiring a multidisciplinary team approach locally, as well as health system-level policy intervention. Hospitalist clinicians frequently care for boarding patients and are experts in clinical care of acutely ill patients and with experience are often experts in quality improvement as well. In this commentary, we call upon hospitalists and emergency medicine (EM) physicians to tackle this problem together, along with healthcare administrators, to look for potential solutions from the local hospital level up to US federal healthcare policy.

Abstract Background Hospital‐at‐home programs (HaH) in the United States have evolved to include a virtual‐hybrid delivery model, where all physician encounters are virtual and partnered with a home care team. Objective To examine whether a virtual hybrid HaH program enabled by technology has similar clinical outcomes to traditional brick‐and‐mortar (B&M) hospital care. Methods We conducted a pragmatic trial at three hospitals, randomizing 1150 acutely ill patients requiring hospital care between July 10, 2023, and October 31, 2023 one‐to‐one into two groups: intervention (HaH) and control (B&M). The primary analysis was an intention‐to‐treat non‐inferiority analysis of the primary outcome, which was a composite of 30‐day all‐cause mortality and unplanned readmissions. Secondary outcomes included 30‐day readmission, all‐cause mortality, and patient experience. Results The mean age was 67.8 (standard deviation [SD] 16.3) years, and 52.2% were female. The primary outcome occurred in 99 (17.3%) HaH patients and 114 (19.8%) B&M patients (odds ratio [OR] 0.85, 95% confidence interval [CI] 0.63–1.14, p = .28), meeting the non‐inferiority criterion. Thirty‐day unplanned readmission occurred in 84 (14.7%) HaH patients and 101 (17.5%) B&M patients (OR 0.81, 95% CI 0.59–1.11, p = .19). Thirty‐day all‐cause mortality occurred in 25 (4.4%) HaH patients and 19 (3.3%) B&M patients (OR 1.34, 95% CI 0.73–2.46, p = .35). No HaH patients died while receiving their hospital care at home. HaH program was associated with a higher likelihood of patients reporting feeling extremely comfortable or very comfortable (84.4% HaH; 60.9% B&M, p = .001). Conclusion A hybrid HaH model is a safe and comfortable alternative to traditional B&M hospital care.

Background The COVID-19 pandemic introduced unique challenges to healthcare systems, particularly in relation to patient safety and adverse events during hospitalization. There is limited understanding of COVID-19’s association with some patient safety indicators (PSIs). Objectives This study aimed to investigate the impact of COVID-19 infection on the rate of PSI-3 events and its implications on quality metrics. We compared PSI-3 event rates between COVID-19–infected and uninfected patients and examined the clinical characteristics of COVID-19 patients experiencing PSI-3 events. Methods This is a retrospective study at Mayo Clinic hospitals between January 2020 and February 2022, analyzing patients meeting PSI-3 denominator eligibility criteria. PSI-3 events were identified using AHRQ WinQI software. Patients were categorized based on COVID-19 status. Patient demographics, characteristics, and PSI-3 rates were compared. A case series analysis described clinical details of COVID-19 patients with PSI-3 events. Results Of 126,781 encounters meeting PSI-3 criteria, 8674 (6.8%) had acute COVID-19 infection. COVID-19–infected patients were older, more likely to be male, non-white, and had private insurance. PSI-3 rates were significantly higher in COVID-19 patients (0.21% versus 0.06%, P < 0.0001), even after risk adjustment (adjusted risk ratio, 3.24, P < 0.0001). The case series of 17 COVID-19 patients with PSI-3 events showed distinctive clinical characteristics, including higher medical device–related pressure injuries, and greater predisposition for head, face, and neck region. Conclusions Acute COVID-19 infection correlates with higher PSI-3 event rates. Current quality indicators may require adaptation to address the pandemic’s complexities and impact on patient safety. Further research is needed to comprehensively understand the intricate relationship between COVID-19 and patient outcomes.

This study aims to explore how artificial intelligence can help ease the burden on caregivers, filling a gap in current research and healthcare practices due to the growing challenge of an aging population and increased reliance on informal caregivers. We conducted a search with Google Scholar, PubMed, Scopus, IEEE Xplore, and Web of Science, focusing on AI and caregiving. Our inclusion criteria were studies where AI supports informal caregivers, excluding those solely for data collection. Adhering to PRISMA 2020 guidelines, we eliminated duplicates and screened for relevance. From 947 initially identified articles, 10 met our criteria, focusing on AI’s role in aiding informal caregivers. These studies, conducted between 2012 and 2023, were globally distributed, with 80% employing machine learning. Validation methods varied, with Hold-Out being the most frequent. Metrics across studies revealed accuracies ranging from 71.60% to 99.33%. Specific methods, like SCUT in conjunction with NNs and LibSVM, showcased accuracy between 93.42% and 95.36% as well as F-measures spanning 93.30% to 95.41%. AUC values indicated model performance variability, ranging from 0.50 to 0.85 in select models. Our review highlights AI’s role in aiding informal caregivers, showing promising results despite different approaches. AI tools provide smart, adaptive support, improving caregivers’ effectiveness and well-being.

AbstractBackgroundPatient Safety Indicator (PSI)‐12, a hospital quality measure designed by Agency for Healthcare Research and Quality (AHRQ) to capture potentially preventable adverse events, captures perioperative venous thromboembolism (VTE). It is unclear how COVID‐19 has affected PSI‐12 performance.ObjectiveWe sought to compare the cumulative incidence of PSI‐12 in patients with and without acute COVID‐19 infection.Design, Setting, and ParticipantsThis was a retrospective cohort study including PSI‐12‐eligible events at three Mayo Clinic medical centers (4/1/2020‐10/5/2021).Exposure, Main Outcomes, and MeasuresWe compared the unadjusted rate and adjusted risk ratio (aRR) for PSI‐12 events among patients with and without COVID‐19 infection using Fisher's exact χ2 test and the AHRQ risk‐adjustment software, respectively. We summarized the clinical outcomes of COVID‐19 patients with a PSI‐12 event.ResultsOur cohort included 50,400 consecutive hospitalizations. Rates of PSI‐12 events were significantly higher among patients with acute COVID‐19 infection (8/257 [3.11%; 95% confidence interval {CI}, 1.35%–6.04%]) compared to patients without COVID‐19 (210/50,143 [0.42%; 95% CI, 0.36%–0.48%]) with a PSI‐12 event during the encounter (p < .001). The risk‐adjusted rate of PSI‐12 was significantly higher in patients with acute COVID‐19 infection (1.50% vs. 0.38%; aRR, 3.90; 95% CI, 2.12–7.17; p < .001). All COVID‐19 patients with PSI‐12 events had severe disease and 4 died. The most common procedure was tracheostomy (75%); the mean (SD) days from surgical procedure to VTE were 0.12 (7.32) days.ConclusionPatients with acute COVID‐19 infection are at higher risk for PSI‐12. The present definition of PSI‐12 does not account for COVID‐19. This may impact hospitals' quality performance if COVID‐19 infection is not accounted for by exclusion or risk adjustment.