Walker, Laura

Objective Understanding patients’ wishes and preferences during hospitalisation is a crucial component of care. We identified a gap related to documentation of advance directives and patient preferences for care and focused on ensuring appropriate goals of care discussions were occurring and documented. Our aim was to improve the documentation of advance care planning notes to include 80% of targeted hospitalised patients. Patients and methods Hospitalised patients in two community hospitals were included. We performed serial Plan-Do-Measure-Act cycles. The first intervention introduced the ‘surprise question’ during an afternoon huddle. Intervention 2 emphasised documentation of the advance care planning note. The third intervention used a structured approach led by administrators at daily multidisciplinary huddles and identified patients with an Elderly Risk Assessment score of 16 or greater as targets for advance care planning documentation. Results From a baseline performance under 10%, we increased to greater than 80% of patients with Elderly Risk Assessment scores of 16 or higher having documented advance care planning. We were able to sustain this performance over subsequent years. Conclusion A structured approach that identifies a targeted population at higher risk of mortality, and implementation of a checklist at a daily multidisciplinary huddle provided sustained improvement in advance care planning documentation. This provides the opportunity for improved patient care that is aligned with their values and preferences.

Objective In-person healthcare delivery is rapidly changing with a shifting employment landscape and technological advances. Opportunities to care for patients in more efficient ways include leveraging technology and focusing on caring for patients in the right place at the right time. We aim to use computer modelling to understand the impact of interventions, such as virtual consultation, on hospital census for referring and referral centres if non-procedural patients are cared for locally rather than transferred. Patients and methods We created computer modelling based on 25 138 hospital transfers between June 2019 and June 2022 with patients originating at one of 17 community-based hospitals and a regional or academic referral centre receiving them. We identified patients that likely could have been cared for at a community facility, with attention to hospital internal medicine and cardiology patients. The model was run for 33 500 days. Results Approximately 121 beds/day were occupied by transferred patients at the academic centre, and on average, approximately 17 beds/day were used for hospital internal medicine and nine beds/day for non-procedural cardiology patients. Typical census for all internal medicine beds is approximately 175 and for cardiology is approximately 70. Conclusion Deferring transfers for patients in favour of local hospitalisation would increase the availability of beds for complex care at the referral centre. Potential downstream effects also include increased patient satisfaction due to proximity to home and viability of the local hospital system/economy, and decreased resource utilisation for transfer systems.

While congenital heart disease historically was a pathology primarily restricted to specialized pediatric centers, advances in technology have dramatically increased the number of people living into adulthood, the number of complications faced by these patients, and the number of patients visiting non-specialized emergency departments for these concerns. Clinicians need to be aware of the issues specific to patients’ individual congenital defects but also have an understanding of how typical cardiac pathology may manifest in this special group of patients. This manuscript attempts to provide an overview of this diverse but increasingly common group of adult patients with congenital heart diseases, including a review of their anatomical variants, the complications they face at the highest rates, and ways that emergency physicians may need to manage these patients differently to avoid causing harm.

Abstract Objectives To compare clinical characteristics among outpatient headache clinic patients who do and do not self‐report visiting the emergency department for headache. Background Headache is the fourth most common reason for emergency department visits, compromising 1%–3% of visits. Limited data exist about patients who are seen in an outpatient headache clinic but still opt to frequent the emergency department. Clinical characteristics may differ between patients who self‐report emergency department use and those who do not. Understanding these differences may help identify which patients are at greatest risk for emergency department overutilization. Methods This observational cohort study included adults treated at the Cleveland Clinic Headache Center between October 12, 2015 and September 11, 2019, who completed self‐reported questionnaires. Associations between self‐reported emergency department utilization and demographics, clinical characteristics, and patient‐reported outcome measures (PROMs: Headache Impact Test [HIT‐6], headache days per month, current headache/face pain, Patient Health Questionnaire‐9 [PHQ‐9], Patient‐Reported Outcomes Measurement Information System [PROMIS] Global Health [GH]) were evaluated. Results Of the 10,073 patients (mean age 44.7 ± 14.9, 78.1% [7872/10,073] female, 80.3% [8087/10,073] White patients) included in the study, 34.5% (3478/10,073) reported visiting the emergency department at least once during the study period. Characteristics significantly associated with self‐reported emergency department utilization included younger age (odds ratio = 0.81 [95% CI = 0.78–0.85] per decade), Black patients (vs. White patients) (1.47 [1.26–1.71]), Medicaid (vs. private insurance) (1.50 [1.29–1.74]), and worse area deprivation index (1.04 [1.02–1.07]). Additionally, worse PROMs were associated with greater odds of emergency department utilization: higher (worse) HIT‐6 (1.35 [1.30–1.41] per 5‐point increase), higher (worse) PHQ‐9 (1.14 [1.09–1.20] per 5‐point increase), and lower (worse) PROMIS‐GH Physical Health T‐scores (0.93 [0.88–0.97]) per 5‐point increase. Conclusion Our study identified several characteristics associated with self‐reported emergency department utilization for headache. Worse PROM scores may be helpful in identifying which patients are at greater risk for utilizing the emergency department.

Objectives Establishment of code status can be challenging in the acute care setting. The primary objective of the present study was to evaluate whether patients or their surrogate decision-makers were comfortable watching an educational video about resuscitation. Methods This interventional pilot study involved a pre- and a postintervention survey of a convenience sample of emergency department (ED) patients who were admitted to the hospital. The study was conducted at an academic level-1 trauma centre within the normal flow of patient care over 4 months in 2017. Results In total, 50 patients enrolled in the study. Among them, 82% were ‘very comfortable’ and 14% were ‘moderately comfortable’ watching the video. Overall, 61% of respondents were ‘very comfortable’ recommending the video to others. Watching the video resulted in a change in code status for 9 patients. Conclusions Our results indicate that patients felt comfortable watching the video and recommending the video for further use. Watching the video did not result in a change in code status for most patients in this study. The study results indicate that a standardised patient education video on resuscitation code status was acceptable to patients and their family members and has potential for increased use in the ED.

Background Goals of care (GOC) conversations in the emergency department (ED) are often a brief discussion of code status rather than a patient-oriented dialogue. We aimed to develop a guide to facilitate conversations between ED clinicians and patients to elicit patient values and establish goals for end-of-life care, while maintaining ED efficiency. Paths of ED Care, a conversation guide, is the product of this work. Design A multidisciplinary/multispecialty group used recommended practices to adapt a GOC conversation guide for ED patients. ED clinicians used the guide and provided feedback on content, design, and usability. Patient-clinician interactions were recorded for discussion analysis, and both were surveyed to inform iterative refinement. A series of discussions with patient representatives, multidisciplinary clinicians, bioethicists, and health care designers yielded feedback. We used a process similar to the International Patient Decision Aid Standards and provide comparison to these. Results A conversation guide, eight pages with each page 6 by 6 inches in dimension, uses patient-oriented prompts and includes seven sections: 1) evaluation of patient/family understanding of disease, 2) explanation of possible trajectories, 3) introduction to different pathways of care, 4) explanation of pathways, 5) assessment of understanding and concerns, 6) code status, and 7) personalized summary. Limitations Recruitment of sufficient number of patients/providers to the project was the primary limitation. Methods are limited to qualitative analysis of guide creation and feasibility without quantitative analysis. Conclusions Paths of ED Care is a guide to facilitate patient-centered shared decision making for ED patients, families, and clinicians regarding GOC. This may ensure care concordant with patients’ values and preferences. Use of the guide was well-received and facilitated meaningful conversations between patients and providers.

Abstract Background Consolidation of healthcare in the US has resulted in integrated organizations encompassing large geographic areas, with varying services and complex patient flows. Profound changes in patient volumes and behavior have occurred during the SARS Cov2 pandemic, but understanding these changes across organizations is challenging. Network analysis provides a novel approach to address this. Methods We retrospectively evaluated hospital-based encounters with an index emergency department visit in a healthcare system comprising 18 hospitals, using patient transfer as a marker of unmet clinical need. We developed quantitative models of transfers using network analysis incorporating the level of care provided (ward, progressive care, intensive care) during pre-pandemic (May 25, 2018 to March 16, 2020) and mid-pandemic (March 17, 2020 to March 8, 2021) time periods. Results 829,455 encounters were evaluated. The system functioned as a non-small-world, non-scale-free, dissociative network. Our models reflected transfer destination diversification and variations in volume between the two time points – results of intentional efforts during the pandemic. Known hub-spoke architecture correlated with quantitative analysis. Conclusion Applying network analysis in an integrated US healthcare organization demonstrates changing patterns of care and the emergence of bottlenecks in response to the SARS Cov2 pandemic, consistent with clinical experience, providing a degree of face validity. The modeling of multiple influences can identify susceptibility to stress and opportunities to strengthen the system where patient movement is common and voluminous. The technique provides a mechanism to analyze the effects of intentional and contextual changes on system behavior.

Abstract Background On average, patients with hemolyzed potassium samples spend about 1 h longer in the emergency department (ED), regardless of acuity level or disposition. We aimed to quantify the direct expenses associated with poor-quality preanalytic blood samples collected in the ED. Methods We created a simple table with a range of direct expenses (i.e., costs) and rates of hemolyzed sample draws, allowing for identification of potential high-level cost-of-care impact analysis. We included a range of costs informed by review of literature on the topic. Those costs range from $600 to $3000 per bed-hour. This amount was inflation adjusted from 1996 to 2020 (1.68 × [direct cost per visit] × [100 000 visits per year/365 days/24 h]). We provided a range of hemolysis incidence based on previously reported data. Results We showed that for an ED with 100 000 annual visits, a 40% draw rate for routine chemistries (including potassium), and a 10% hemolysis incidence, the direct cost impact of hemolysis waste is approximately $4 million/year as a result of the 1 h of added length of stay on average for a patient with a hemolyzed blood sample. This amount represents an annualized estimated cost of caring for a patient in the ED with an avoidable extended length of stay. Conclusions The financial burden of poor-quality blood samples can be estimated using cost per bed-hour and rate of sample failure. Similar methodology may identify additional QC issues with previously invisible financial implications.