ED Admission Research Articles

Protecting high-risk oncology patients during the pandemic of COVID-19 by creating an outpatient cancer clinic for febrile neutropenia (California clinic).

191 Background: Delivering care for vulnerable cancer patients during a pandemic is challenging given the competing risks of death from cancer versus the high case fatality rates from SARS-COV-2 (CV-19). Data currently available suggests a total fatality rate close to 30%-50% with CV-19 in active malignancy patients. In addition to adapting guidelines from national organizations to reduce the social footprint of patients in order to minimize risk of exposure of CV-19, our cancer center implemented an isolated clinic with personal protective equipment (PPE) and direct access to a CV-19 rule out floor (if admission warranted) in order to manage those with febrile neutropenia (FN) who otherwise would have been triaged to the emergency room (ED). Methods: We implemented an outpatient isolated extended hour clinic with access to PPE, blood work, intravenous antibiotics and fluids for FN patients as a pilot project from mid-April with expected duration during the pandemic with the aim to decrease the ED admissions for FN by 50%. We used the Multinational Association of Support Care in Cancer (MASCC) validated tool to assist with outpatient versus inpatient management of these patients. All patients were screened via polymerase chain reaction nasal swab for CV-19 to identify CV-19 in a high-risk population. Our PDSA (Plan Do Study Act) cycles have been in 2-week sessions with constant re-education to multiple providers. Results: Prior to CV-19, our databases show an approximate 15 to 20 FN hematology and oncology patients per month who are triaged to ED during the business hours. Since the implementation of our clinic in the last 45 days, we have screened 8 patients, of which 2 were discharged home with oral antibiotics on isolation until CV-19 testing returned, 6 were directly admitted to CV-19 rule out floor avoiding ED. Our overall patient numbers were low during the peak of the pandemic and we expect to see increasing number of patients utilizing the clinic over the next few months. Conclusions: Implementing the California clinic has thus far successfully decreased the social footprint of our highest-risk cancer patients, those with FN, in hopes of decreasing their possible exposure to CV-19 as well as the unnecessary exposure of the clinical personnel. [Table: see text]

169 Emergency Department Utilization Trends during the COVID-19

With COVID-19 cases and fatalities increasing globally, health officials implemented many policies and restrictions to slow the rate of infection. In California, a statewide stay-at-home order was issued on March 19, 2020. Subsequently, individuals avoided gatherings and public places, which potentially increased their risk of contracting the virus, including emergency departments. There is concern that delaying preventive and emergent care could have negative health consequences, especially among those managing chronic conditions and the elderly. The objective of this study was to assess patterns of ED utilization during the initial COVD-19 pandemic, as compared to utilization during the prior year. We conducted a multi-center, retrospective study among adult patients (>=18 years) presenting to two emergency departments (urban level 1 trauma center and suburban academic hospital with combined annual census of ∼83,000). We compared weekly ED utilization between two distinct time periods: March 1 to May 30 in 2019 (n=21,226 visits) and 2020 (n=15,927 visits). We calculated the percent change in ED utilization from 2019 to 2020 for each of the 13 weeks, assessing trends over time by patient age, sex, race/ethnicity, homelessness, presence of chronic conditions, and primary reason for ED visit. Compared to 2019, weekly ED volume and admissions in 2020 decreased by as much as 41.8% and 37.2%, respectively. While weekly ED volume in 2020 did not return to 2019 levels (-17.0% at the highest), admissions did (-0.8% at the highest). Patients 65-74 year of age saw the highest weekly decrease at 50.8% below 2019, and while weekly admissions also decreased for this group by up to 48.3%, admissions spiked to an average of 23.0% above the previous year during the last two weeks of the study period. On average, ED visits by females decreased in 2020 by 30.1%, compared to 20.2% for males. ED visits by Non-Hispanic Asians were at least 30% below the prior year for 9/13 weeks, compared to Non-Hispanic Blacks who only surpassed a 30% decrease during one week. ED volume was relatively unaffected among patients experiencing homelessness, with an average weekly decrease of 4.5%. Patients with diabetes saw a high of 45.1% decrease in admission compared to 2019, but were within 5% of the previous year during 3 of the final 4 weeks of the study period. Psychiatric-related visits and alcohol and substance-related visits decreased as much as 50.6% and 32.0%, respectively; however, alcohol and substance-related visits averaged only 6.8% below 2019 volumes during the last 4 weeks of the study period compared to -26.0% among psychiatric visits. Visits for skin and subcutaneous tissue infections decreased up to 44.4%, but also saw volume above 2019 levels for 5 different weeks (range +2.2% to +34.1%). Similarly, weekly sepsis-related and cardiac dysrhythmia visits were at least 15% higher than 2019 for 2 of the last 4 weeks, and, 3 out of the last 4 weeks, respectively. This study of ED utilization trends during the COVID-19 pandemic demonstrated that ED volume and admissions decreased dramatically compared to the prior year. However, there was much variation among the patient population, and unfortunately elderly patients and those with chronic conditions may be paying the price for initially avoiding the ED. Further study with a longer follow-up period is needed to evaluate potential health consequences for patients who may be delaying care.

Evaluation of the frequency of patients with cancer presenting to an emergency department

This study aims to determine the demographic characteristics of cancer patients admitted to an emergency department and determine the relationship between the frequency of admission to the emergency department and oncological emergencies and their effect on mortality. This observational, prospective, diagnostic accuracy study was performed in the ED of a tertiary care hospital. Patients over the age of 18 who were previously diagnosed with cancer and admitted to the emergency service for medical reasons were included in the study. We recorded baseline characteristics including age, gender, complaints, oncological diagnosis, metastasis status, cancer treatments received, the number of ED admissions, structural and metabolic oncological emergency diagnoses in the ED, discharge status, length of hospital stay, and mortality status. In our study, 1205 applications related to the oncological diagnosis of 261 patients were examined. 55.6% of the patients were male, and 44.4% were female. The most common metabolic oncological emergency was anemia (19.5%), and the most common structural oncological emergency was bone metastasis-fracture (4.6%.) The mean score of admission of patients to the emergency department was four times (min: 1 max: 29) during the study period. A total of 49.4% (n: 129) of the patients included in the study died during follow-up, and the median time of death was 13 days after the last ED admission. The palliation of patient symptoms in infusion centers that will be established in the palliative care center will contribute to the decrease in the frequency of use of emergency services.

Emergency department visits and hospitalisations for asthma, COPD and respiratory tract infections: what is the role of respiratory viruses, and return to school in September, January and March?

BackgroundAsthma exacerbations increase in September coinciding with children returning to school. The aim of this study was to investigate whether this occurs 1) for COPD and respiratory tract infections (RTIs); 2) after school resumes in January and March; and 3) identify which viruses may be responsible.MethodsEmergency department (ED) visits and admissions for asthma, COPD and RTIs and the prevalence of viruses in Ontario, Canada were analysed daily between 2003 and 2013. ED visits and admissions were provided by the Canadian Institute for Health Information. Viral prevalence was obtained from the Centre for Immunisation and Respiratory Infectious Diseases.ResultsED visits and admissions rates demonstrated a biphasic pattern. Lowest rates occurred in July and August and the highest rates in September for asthma, and after December for COPD and RTI. The increase in rates for 30 days before and after school return in September was greatest for children with asthma <15 years (2.4–2.6×). Event rates fell after school return in January for all three conditions ranging from 10–25%, and no change followed March break for asthma and COPD. Human rhinovirus was prevalent in summer with a modest relationship to asthma rates in September. The prevalence of respiratory syncytial virus, influenza A and coronavirus was associated with sustained event rates for COPD and RTIs.ConclusionsAsthma, COPD and RTIs increase in September but do not occur after return to school in January and March. Human rhinovirus is associated with ED visits and admissions only in September.

The Patterns and Outcomes of Inter-Hospital Transfer Among Medicare Patients with Ischemic Stroke

Background and PurposeInter-hospital transfer for ischemic stroke is an essential part of stroke system of care. This study aimed to understand the national patterns and outcomes of ischemic stroke transfer. Methods and ResultsThis retrospective study examined Medicare beneficiaries aged ≥65 years undergoing inter-hospital transfer for ischemic stroke in 2012. Cox proportional hazards model was used to compare 30-day and one-year mortality between transferred patients and direct admissions from the emergency department (ED admissions). Among 312,367 ischemic stroke admissions, 5.7% underwent inter-hospital transfer. Using this value as cut-off, the hospitals were classified into receiving (n = 411), sending (n = 559), and low-transfer (n = 1863) hospitals. Receiving hospitals were larger than low-transfer and sending hospitals as demonstrated by the median bed number (371, 189, and 88, respectively, p < 0.001); more frequently to be certified stroke centers (75%, 47%, and 16%, respectively, p < 0.001); and less commonly located in the rural area (2%, 7%, and 24%, respectively, p < 0.001). For receiving hospitals, transfer-in patients and ED admissions had comparable mortality at 30 days (10% vs 10%; adjusted HR [aHR]=1.07; 95% CI, 0.99–1.14) and 1 year (23% vs 24%; aHR=1.03; 95% CI, 0.99–1.08). For sending hospitals, transfer-out patients, compared to ED admissions, had higher mortality at 30 days (14% vs 11%; aHR=1.63; 95% CI, 1.39–1.91) and 1 year (30% vs 27%; aHR=1.33; 95% CI, 1.20–1.48). For low-transfer hospitals, overall transfer-in and transfer-out patients, compared to ED admissions, had higher mortality at 30 days (13% vs 10%; aHR=1.46; 95% CI, 1.33–1.60) and 1 year (28% vs 25%; aHR=1.27; 95% CI, 1.19–1.36). ConclusionsHospitals in the US, based on their transfer patterns, could be classified into 3 groups that shared distinct characteristics including hospital size, rural vs urban location, and stroke certification. Transferred patients at sending and low-transfer hospitals had worse outcomes than their ED admission counterpart.

Does prolonged emergency department length of stay(EDLOS) affect the outcomes of acute ischemic stroke patients?

The effect of emergency department length of stay (EDLOS) on outcomes of patients with acute ischemic stroke (AIS) remains largely unexamined. We aimed to investigate the association between EDLOS and outcomes in AIS patients. 618 AIS patients were enrolled. Baseline demographics, vascular risk factors, ED admission information, hyperacute treatment of AIS and stroke severity were collected. Stroke progression was defined as any new neurological symptoms/signs or any neurological worsening within 7days after stroke onset and poor prognosis was defined as modified Rankin Scale(mRS) scores>2 at 30day. The effect of EDLOS on stroke progression and prognosis was assessed. The median EDLOS was 2.5h (1.4-6.9h). On multivariable linear regression, presentation month between Apr. and Jun., admission at the ED between 7am to 3pm(P=0.036), transferring to stroke unit, receiving endovascular interventional treatment, onset on holidays, and progressive stroke were associated with shorter EDLOS(all P<0.05). A shorter EDLOS was significantly associated with an increased risk of stroke progression (P=0.007). Patients with the lowest EDLOS (≤1.35h) were 2-3 fold more likely to have stroke progression, compared with those with the highest EDLOS (>6.93h) (OR, 2.52; 95% CI, 1.29-4.93; P=0.043). However, no significant association between EDLOS and stroke prognosis was revealed. In AIS patients, shorter EDLOS was associated with the increased risk of stroke progression, possibly reflecting prioritized admission of more severely affected patients at high risk of stroke progression. EDLOS alone might be an insufficient indicator of stroke care in the ED.

Diaphragmatic excursion measurement in emergency department patients with acute dyspnea to predict mechanical ventilation use

IntroductionUltrasound is a feasible and reproducible method for measuring right diaphragmatic excursion (RDE) in ED patients with acute dyspnea (AD). In AD patients, the correlation between the RDE value and the need for mechanical ventilation (MV) is not known. MaterialsThis was a bicentric, observational prospective study. The RDE measurement was done at admission. The need for MV was defined by the use of MV within 4 h of AD management. An optimal threshold for RDE was determined as the value that minimized the incorrect predictions of the use of MV in the first 4 h as the highest Youden index. ResultsWe analyzed 102 patients (79 [70; 86] years), 38 (37%) of whom had been ventilated. The RDE value was 1.7 cm [1.4; 2.0] and 2.2 cm [1.8; 2.6] in the ventilated and non-ventilated groups, respectively (p = 0.06). The AUC was 0.68 95% CI [0.57; 0.80]. With a threshold of 2 cm, the sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) were 76% [60%; 89%], 59% [46%; 71%], 81% [67%; 91%], and 53% [39%; 66%], respectively. In the non-COPD patients, the RDE values were 1.5 cm [1.2; 1.9] and 2.2 cm [1.8; 2.6] (p < 0.01) in the ventilated and not-ventilated groups, respectively. The AUC was 0.77 95% CI [0.64; 0.90]. With a threshold of 2.18 cm, the sensitivity, specificity, NPV, and PPV were 91% [71%; 99%], 51% [36%; 66%], 92% [75%; 99%], and 54% [38%; 69%], respectively. ConclusionThe RDE values at ED admission were unable to define a prognostic threshold value associated with subsequent MV need in the AD patients. In non-COPD patients, the NPV was 92%.

Emergency Department and Out-of-Hospital Emergency System (112-AREU 118) integrated response to Coronavirus Disease 2019 in a Northern Italy centre.

Since December 2019, the world has been facing the life-threatening disease, named Coronavirus disease-19 (COVID-19), recognized as a pandemic by the World Health Organization. The response of the Emergency Medicine network, integrating “out-of-hospital” and “hospital” activation, is crucial whenever the health system has to face a medical emergency, being caused by natural or human-derived disasters as well as by a rapidly spreading epidemic outbreak. We here report the Pavia Emergency Medicine network response to the COVID-19 outbreak. The “out-of-hospital” response was analysed in terms of calls, rescues and missions, whereas the “hospital” response was detailed as number of admitted patients and subsequent hospitalisation or discharge. The data in the first 5 weeks of the Covid-19 outbreak (February 21–March 26, 2020) were compared with a reference time window referring to the previous 5 weeks (January 17–February 20, 2020) and with the corresponding historical average data from the previous 5 years (February 21–March 26). Since February 21, 2020, a sudden and sustained increase in the calls to the AREU 112 system was noted (+ 440%). After 5 weeks, the number of calls and missions was still higher as compared to both the reference pre-Covid-19 period (+ 48% and + 10%, respectively) and the historical control (+ 53% and + 22%, respectively). Owing to the overflow from the neighbouring hospitals, which rapidly became overwhelmed and had to temporarily close patient access, the population served by the Pavia system more than doubled (from 547.251 to 1.135.977 inhabitants, + 108%). To minimize the possibility of intra-hospital spreading of the infection, a separate “Emergency Department—Infective Disease” was created, which evaluated 1241 patients with suspected infection (38% of total ED admissions). Out of these 1241 patients, 58.0% (n = 720) were admitted in general wards (n = 629) or intensive care unit (n = 91). To allow this massive number of admissions, the hospital reshaped many general ward Units, which became Covid-19 Units (up to 270 beds) and increased the intensive care unit beds from 32 to 60. In the setting of a long-standing continuing emergency like the present Covid-19 outbreak, the integration, interaction and team work of the “out-of-hospital” and “in-hospital” systems have a pivotal role. The present study reports how the rapid and coordinated reorganization of both might help in facing such a disaster. AREU-112 and the Emergency Department should be ready to finely tune their usual cooperation to respond to a sudden and overwhelming increase in the healthcare needs brought about by a pandemia like the current one. This lesson should shape and reinforce the future.

914-P: Predictors of ED and Inpatient Admissions after Hypo- and Hyperglycemic Events: Leveraging Remote Monitoring Data of People with Diabetes

Background: Predictive models to identify people with diabetes mellitus (DM) at high-risk for future ED visits and inpatient admissions (IA) are an area of clinical interest. The models do not include self-monitoring blood glucose (SMBG) levels. Livongo, the leader in Applied Health Signals, includes cellular-enabled BG meter that allows instantaneous uploading of SMBG values into the cloud with millions of values in people with DM. Methods: Leveraging data collected via the Livongo program with medical and pharmacy claims, machine learning techniques were used to identify the 25 most predictive variables of severe hypo- and hyperglycemia (BG ≤54 mg/dL and ≥400 mg/dL, respectively) resulting in an ED or IA encounter within three days. Four models were constructed for DM (type 1 and type 2) and encounter (ED and IA). Participants had to be enrolled for at least 12 months with continuous medical benefits eligibility for 24 months. Variable categories included in modeling were demographics, comorbidities based on ICD-10 codes, prior HCU, new and current medications, 30-days SMBG patterns with mean BG levels, and months on program. Area under the curve (AUC) was used to assess model performance. Results: There were 7,633 people selected. They had a mean age of 54 years, 48% were female, and 11% had type 1 DM. In this group, 924 and 1,518 severe hypo- and hyperglycemic with ED or IA encounters occurred. Random forest models had the highest AUC with values greater than 98% and sensitivity and specificity above 93% and 99%, respectively. HCU variables were the most predictive variables in all 4 models. Mean 7-day BG level, 30-day count of BG checks, and before-breakfast checking were also highly predictive. Conclusions: SMBG variables are independent predictors of hypo- and hyperglycemia with ED and IA encounters. Real-time BG remote monitoring programs have the capability to identify people at high-risk of costly HCU and develop interventions to improve care. Disclosure W. Lu: Employee; Self; Livongo Health. R. James: Advisory Panel; Self; AstraZeneca. Employee; Self; Livongo Health. S.L. Painter: Employee; Self; Livongo Health. B. Shah: Employee; Self; Livongo Health.

A Glimpse Into the Future.

The novel coronavirus will forever change the world in ways we have yet to realize What will our lives look like when the crisis abates? Will we still shake hands? Will my Italian relatives still kiss me on both cheeks (or just give air kisses)? When this is over there may be fewer elderly, more guns, less movie theaters and greater paranoia in America but perhaps more generosity and kindness as well Most of what will change after the pandemic is beyond my ability to guess However, I see more clearly the changes that will come to Emergency Medicine once the Hot Zone has cooled Let's pull back the curtain of time and glimpse into the future for our specialty after the Time of COVID

An analysis of inpatient and ED admissions within 30 days of chemotherapy: An OP-35 review.

e19302 Background: To evaluate patients who were within 30 days of outpatient chemotherapy infusion for an admission or ED visit associated with a primary or secondary diagnosis of anemia, dehydration, diarrhea, emesis, fever, nausea, neutropenia, pain, pneumonia or sepsis. Methods: A review of Epic was performed on all Mercy patients with cancer who received at least one outpatient chemotherapy between 1/1/16-12/31/18. Non leukemia patients ≥ 18 years of age with an inpatient admission(IPA) or ED visit (EDV) were further evaluated for either the primary or secondary diagnosis for referral with at least one of the following diagnoses: anemia, dehydration, diarrhea, emesis, fever, nausea, neutropenia, pain, pneumonia, or sepsis. Univariate and multivariable analyses were performed to identify significant clinical variables associated with the risk of referral. Adjusted Odds Ratios were calculated for the significant variables with a p value &lt; 0.05 being significant. Results: Of the 9,590 cancer patients who presented to an outpatient infusion center during the study interval, there were 8,319 eligible patients excluding those with leukemia or age &lt; 18 (n = 503) or for a presentation in which a chemotherapy agent was not infused. There were 90,030 eligible chemotherapy encounters of which 16.8% of patients (n = 1400) had an IPA and 11.8% (n = 980) had an EDV within 30 days of infusion. Age, social deprivation status, NCI comorbidity index, Epic readmission score, ECOG performance score, smoking, and malnutrition were significantly associated with either an IPA or EDV in both settings. Sepsis, pneumonia, and anemia were the most common OP35 related diagnoses for an IPA at 47.2%, 26.9%, and 23.2%, respectively. Similarly, pain, dehydration and nausea were the most common OP35 related diagnosis for an EDV at 48.1%, 14.2%, and 14.1% respectively. Factors having the strongest association with an IPA were malnutrition (OR: 2.34 2.08-2.65; p &lt; 0.00001) and an antibiotic type of chemotherapy (OR: 2.16 1.72-2.72; p &lt; 0.0001). Factors having strongest association with an EDV were severe pain score (OR: 2.56 2.21-2.97; p &lt; 0.0001) and moderate to most deprived social deprivation status (OR: 2.10 1.62-2.72; p &lt; 0.0001). ER referrals for pain, dehydration, and anemia most commonly occurred during clinic hours. Conclusions: Many clinical variables were found to be significantly associated with an IPV or EDV. These variables are opportunities for outpatient interventional algorithms to enhance patient care.

Predicting hospital admission for older emergency department patients: Insights from machine learning

BackgroundEmergency departments (ED) are a portal of entry into the hospital and are uniquely positioned to influence the health care trajectories of older adults seeking medical attention. Older adults present to the ED with distinct needs and complex medical histories, which can make disposition planning more challenging. Machine learning (ML) approaches have been previously used to inform decision-making surrounding ED disposition in the general population. However, little is known about the performance and utility of ML methods in predicting hospital admission among older ED patients. We applied a series of ML algorithms to predict ED admission in older adults and discuss their clinical and policy implications. Materials and methodsWe analyzed the Canadian data from the interRAI multinational ED study, the largest prospective cohort study of older ED patients to date. The data included 2274 ED patients 75 years of age and older from eight ED sites across Canada between November 2009 and April 2012. Data were extracted from the interRAI ED Contact Assessment, with predictors including a series of geriatric syndromes, functional assessments, and baseline care needs. We applied a total of five ML algorithms. Models were trained, assessed, and analyzed using 10-fold cross-validation. The performance of predictive models was measured using the area under the receiver operating characteristic curve (AUC). We also report the accuracy, sensitivity, and specificity of each model to supplement performance interpretation. ResultsGradient boosted trees was the most accurate model to predict older ED patients who would require hospitalization (AUC = 0.80). The five most informative features include home intravenous therapy, time of ED presentation, a requirement for formal support services, independence in walking, and the presence of an unstable medical condition. ConclusionTo the best of our knowledge, this is the first study to predict hospital admission in older ED patients using a series of geriatric syndromes and functional assessments. We were able to predict hospital admission in older ED patients with good accuracy using the items available in the interRAI ED Contact Assessment. This information can be used to inform decision-making about ED disposition and may expedite admission processes and proactive discharge planning.

Pancreatic Cancer Surgery Following Emergency Department Admission: Understanding Poor Outcomes and Disparities in Care

BackgroundThe impact of emergency department admission prior to pancreatic resection on perioperative outcomes is not well described. We compared patients who underwent pancreatic cancer surgery following admission through the emergency department (ED-surgery) with patients receiving elective pancreatic cancer surgery (elective) and outcomes. Study DesignThe Nationwide Inpatient Sample database was used to identify patients undergoing pancreatectomy for cancer over 5 years (2008–2012). Demographics and hospital characteristics were assessed, along with perioperative outcomes and disposition status. ResultsA total of 8158 patients were identified, of which 516 (6.3%) underwent surgery after admission through the ED. ED-surgery patients were more often socioeconomically disadvantaged (non-White 39% vs. 18%, Medicaid or uninsured 24% vs. 7%, from lowest income area 33% vs. 21%; all p < .0001), had higher comorbidity (Elixhauser score > 6: 44% vs. 26%, p < .0001), and often had pancreatectomy performed at sites with lower annual case volume (< 7 resections/year: 53% vs. 24%, p < .0001). ED-surgery patients were less likely to be discharged home after surgery (70% vs. 82%, p < .0001) and had higher mortality (7.4% vs. 3.5%, p < .0001). On multivariate analysis, ED-surgery was independently associated with a lower likelihood of being discharged home (aOR 0.55 (95%CI 0.43–0.70)). ConclusionPatients undergoing pancreatectomy following ED admission experience worse outcomes compared with those who undergo surgery after elective admission. The excess of socioeconomically disadvantaged patients in this group suggests factors other than clinical considerations alone drive this decision. This study demonstrates the need to consider presenting patient circumstances and preoperative oncologic coordination to reduce disparities and improve outcomes for pancreatic cancer surgery.

PIN14 UPDATING THE CMS MAJOR DIAGNOSTIC CATEGORIES (MDC) TO ALIGN WITH A PATHOPHYSIOLOGICAL MODEL OF DISEASE: IMPLICATIONS FOR RESEARCH AND CLINICAL CARE RESOURCE ALLOCATION

To evaluate the top causes of unplanned admissions and readmissions by number of encounters and average total payments (ATP) using a novel Major Diagnostic Categories (MDC) framework that categorizes hospitalizations according to pathophysiology. Medicare Severity-Diagnosis Related Groups (MS-DRG) were reviewed and recategorized into new MDCs to group conditions with similar pathophysiology. Recategorization was applied to Medicare Fee-For-Service inpatient claims from 2017. ED admissions were used as a proxy for unplanned admissions and ED readmissions within 30 days of any discharge were a proxy for unplanned readmissions. Volume of discharges and readmissions and total payments by the current and new MDCs were calculated. Medicare FFS beneficiaries had 7,375,322 ED admissions and 1,637,657 ED readmissions in 2017. After MDC recategorization, 3,102,532 admissions and 725,946 readmissions changed categories. Circulatory conditions are the top cause of unplanned admissions (1,473,335; 20%) with average total payments (ATP) exceeding $18 billion and readmissions (331,119; 20.2%; ATP: $4.03 billion) under current MDC categorization. After recategorization, infectious diseases were the top cause of admissions (1,581,294; 21.4%; ATP: $19.7 billion) and readmissions (364,041; 22.2%; ATP: $5 billion). Governmental agencies and health services researchers use Medicare’s Major Diagnostic Categories (MDCs), which combine disease conditions in 26 groups, including Pre-MDC, to measure burden of disease and rank healthcare expenditures. Without a distinct MDC category, subspecialties without a specific organ focus, such as infectious diseases or oncology, might be excluded from burden of diseases estimates or other rankings and could therefore receive fewer resources or attention. A pathophysiological approach to disease categorization is necessary to better reflect diagnostic and therapeutic modalities and to improve resource allocation for clinical care and research, particularly for infectious diseases.

Evaluating the consequences of health policy decisions

Uncertainty about intended and possible unintended side effects makes it important to evaluate changes following health policy decisions. A recent IJHPR article by Greenberg et al. evaluated changes in emergency department care following a directive of the Israeli Ministry of Health to limit occupancy in internal medicine wards. Over a six-year observation period, they found that one-month mortality and one-week readmissions after ED visits remained unchanged, while increases in average ED visit length, as well as increased delay time from ED admission to ward were observed. These findings help to assess the impact of the occupancy limit directive and may support future health policy decisions.However, the study by Greenberg et al. was limited by the unavailability of diagnostic data, and this illustrates a significant issue that transcends this particular study. In many countries, policy-relevant administrative data are not sufficiently available on a timely basis. Data availability is the prerequisite for monitoring developments in patterns of care following health policy changes. Besides conducting retrospective studies, timely availability of data makes it possible to establish monitoring systems which may help decision makers assess the impact of policy changes, identify undesired developments early, and recognize changes in need or demand of health services within the population.

The Center for Trauma Survivorship: Addressing the great unmet need for posttrauma center care.

Returning patients to preinjury status is the goal of a trauma system. Trauma centers (TCs) provide inpatient care, but postdischarge treatment is fragmented with clinic follow-up rates of <30%. Posttraumatic stress disorder (PTSD) and depression are common, but few patients ever obtain necessary behavioral health services. We postulated that a multidisciplinary Center for Trauma Survivorship (CTS) providing comprehensive care would meet patient's needs, improve postdischarge compliance, deliver behavioral health, and decrease unplanned emergency department (ED) visits and readmissions. Focus groups of trauma survivors were conducted to identify issues following TC discharge. Center for Trauma Survivorship eligible patients are aged 18 to 80 years and have intensive care unit stay of >2 days or have a New Injury Severity Score of ≥16. Center for Trauma Survivorship visits were scheduled by a dedicated navigator and included physical and behavioral health care. Patients were screened for PTSD and depression. Patients screening positive were referred for behavioral health services. Patients were provided 24/7 access to the CTS team. Outcomes include compliance with appointments, mental health visits, unplanned ED visits, and readmissions in the year following discharge from the TC. Patients universally felt abandoned by the TC after discharge. Over 1 year, 107 patients had 386 CTS visits. Average time for each appointment was >1 hour. Center for Trauma Survivorship "no show" rate was 17%. Eighty-six percent screening positive for PTSD/depression successfully received behavioral health services. Postdischarge ED and hospital admissions were most often for infections or unrelated conditions. Emergency department utilization was significantly lower than a similarly injured group of patients 1 year before the inception of the CTS. A CTS fills the vast gaps in care following TC discharge leading to improved compliance with appointments and delivery of physical and behavioral health services. Center for Trauma Survivorship also appears to decrease ED visits in the year following discharge. To achieve optimal long-term recovery from injury, trauma care must continue long after patients leave the TC. Therapeutic, Level III.

Rise in multiple ED admissions of people with dementia

UK charity says 850,000 have age-related mental health problems

Combined Use of the National Early Warning Scores (News), TnI and NT-proBNP increased predictive performance of NEWS in patients with Cardiovascular Disease

Introduction: National Early Warning Score (NEWS) is able to evaluate the integral stress level and function status of the body through vital signs, TnI and NTproBNP can reflect the degree of myocardial injury and cardiac function to a certain extent. Whereas, there is no study working on the estimate value of the combined index of NEWS and TnI or NTproBNP in patients with cardiovascular disease so far. We assumed that the combined index was more strongly associated with prognosis compared to NEWS alone. Method: This was a prospective observational cohort study of adult admissions to emergency department with the diagnosis of cardiovascular disease. NEWS was calculated respectively and combined with TnI and NTproBNP in multivariable logistic regression models. The primary outcome was 30-day mortality after ED arrival, capturing all patients with cardiac arrest at our institution. Result: All of 221 cases were followed up in 30 days, the mortality in 30-day was 19.5% (43/221). 56 patients (25.3%) died or were admitted to ICU within 48h of ED admission. The area under receiver operator characteristic curve (AUROC) of combined index as NT, NP, NTP for 30d mortality were higher than NEWS alone (0.75, 0.77, 0.79 vs 0.67, p&lt;0.05 respectively). The predictive value of NT, NTP were superior to the NEWS alone (AUROC: 0.76, 0.78 vs 0.67; p&lt;0.05). Conclusion: Combined indexes showed better able to predict values for 30-day mortality than the NEWS alone in cardiovascular disease. The combinations of NT, NTP also had better evaluating ability for ICU admission and mortality in 48 hours than NEWS

Does prescribing of immediate release oxycodone by emergency medicine physicians result in persistence of Schedule 8 opioids following discharge?

To identify the prevalence of oxycodone immediate release (IR) prescribed during an ED admission and the persistence of Schedule 8 (S8) opioids following an ED admission. A retrospective cross-sectional audit was undertaken reviewing all admission at the ED of the Royal Hobart Hospital, Tasmania, between 1 August and 30 September 2016. The admissions lists for ED were cross matched with the narcotic registers for oxycodone IR (the most commonly supplied S8 in ED) to identify how many patients received IR oxycodone during their ED admissions. Determination of the persistence of opioid use in opioid naïve patients was then undertaken using the Tasmanian real time reporting database of all S8 opioid dispensed in Tasmania (DAPIS). There were 8432 ED admissions for 7065 patients aged over 13 years. IR oxycodone was prescribed during 1049 of these admissions (12.4%). Of the patients who were not taking regularly prescribed S8 opioids prior to their ED admission (n = 853), 48 patients (5.6%) were taking S8 opioids at both 2 and 6 months following their ED admission. Thirty patients (2.8%) were approved for authorities for long-term opioids for non-cancer pain. These findings suggest that prescribing of IR oxycodone within ED is lower than previous studies. Additionally, the progression to regular chronic opioid use following an ED admission where IR oxycodone was given was relatively low with 3.0% of opioid naïve patients being approved for indications related to chronic non-cancer pain in the following 6 months.

Effect of Age on Healthcare Utilization in Patients with Sickle Cell

Background: The median life expectancy of patients with sickle cell disease surpassed 40 years of age in the last two decades. While sickle cell patients overall are known to have high utilization of health services due to vaso-occlusive pain crises (VOC), few studies have focused on the impact of age on utilization pattern. Due to this, our understanding of the patient population is frequently skewed based on data on younger patients. This study examines the utilization of healthcare in patients in two groups: below 40 years of age, and 40 years and over. We also examined the impact on these two cohorts of a home-based primary care program. Methods: All patients were enrolled in a home-based primary care program in which their primary care doctor visited their home every 4-6 weeks. Health utilization data were collected retrospectively, through chart review for one year prior to joining the home-based primary care program, and prospectively for one year after joining the program. Primary care appointments, reported crises, Sickle Cell Day Hospital visits, ED visits, admissions, 30-day readmissions, and total admission days were recorded. Results: A total of 30 patients was enrolled in the study, and 58 years of data were collected. There were 16 patients between 18 and 39, and 14 patients aged 40 and over. 50% of the 40 and over age group was SS genotype and 50% SC compared to only one patient in the below 40 population had genotype SC. The groups were not significantly different regarding gender distribution (57% female in the 40 and over population vs 50% female in the below 40 population). The 40 and over population had on average more comorbidities per patient. The 40 and over population had significantly more primary care visits every year both before and after the start of the home visits compared to the below 40 population,. The 40 and over population, also had significantly lower overall rates of acute care utilization than the patients under 40: number of crises, ED visits, admissions, 30-day readmissions, and total hospital admission days. When comparing pre and post home visiting within the 40 and older population, there was an increase in primary care visits and a decrease in in reported crises, ED visits, admissions and readmissions. There was no change in these parameters in the 18-39 year old patient group. Discussion: As sickle cell patients age, they are more likely to have cumulative co-morbidities due to their sickle cell disease. Despite their more advanced age and their increase in co-morbid conditions, patients 40 and above were shown in our study to have fewer ED visits and admissions than younger patients, and to further reduce ED visits and admissions when provided with home-based primary care. The younger group had higher utilization at baseline, and did not show improvement when receiving home-based primary care. The reduced acute care utilization in the older group could be due to increased use of primary care, which was further enhanced by enrollment in the home-based primary care program; better adherence to medical treatment; more skill and experience in disease self-management; better social support; or fewer vaso-occlusive crises despite a higher number of co-morbid conditions. The higher prevalence of SC disease in the older cohort is a possible confounder. Those patients with higher utilization at a younger age may be higher risk of mortality, thereby leading to a survivor effect in the older population. Research in the general medical population has shown that home-based primary care reduces acute care utilization in high-utilizing patients with multiple chronic conditions, but more research is needed on the impact in sickle cell patients. Conclusion: This is the first study, to our knowledge, of the impact of home-based primary care on adults with sickle cell disease. In this study, sickle cell patients aged 40 and under showed overall more acute care utilization than those over age 40. The older population had an increase in primary care visits, and overall a significant decrease in healthcare utilization after enrollment in the home visiting program. We did not see a significant decrease in utilization in the younger population with home visits. Disclosures Desai: Global Blood Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Ironwood: Other: Adjudication Board; University of Pittsburgh: Research Funding; Novartis: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Potomac: Speakers Bureau.