Characteristics of Admissions from the Pediatric Emergency Department Observation Unit.

OBJECTIVE: Emergency department observation units (EDOUs) are used to manage common pediatric illnesses and reduce the admission rate to the hospital. Most of these patients require a short duration of observation before a determination can be made whether they need to be admitted to the hospital or safely discharged home. The purpose of this study was to determine the characteristics of admissions from a pediatric EDOU for the top 10 diagnoses admitted to the unit. This will help standardize the disposition of such types of patients from the ED, hence improving the efficiency of the unit. METHODS: We did a retrospective surveillance study of admitted patients from 0 to 18 years of age from the EDOU for the top 10 diagnoses. Descriptive data were reported using percentages and medians with interquartile ranges. Pearson χ2 tests were used to determine significant differences (P < 0.05) between the reason for admission and medical history. RESULTS: In total, 520 patients were admitted from the EDOU during the study period. The median patient age was 3.39 years, with most being Hispanic and female. The top three primary diagnoses of all admitted patients were cellulitis and abscess, gastroenteritis, and bronchiolitis. Sixty-three percent of all admitted patients had secondary diagnoses. Most of these patients were admitted to the inpatient unit due to progression of the primary condition. CONCLUSIONS: The characteristics of admissions from the EDOU may help us to understand historical experience regarding diagnoses, timing, and indications of deterioration, resource utilization, and other metrics that resulted in transfers of EDOU patients to the intensive care unit/operating room/inpatient units.

The Brain Injury Guidelines (BIG) and emergency department observation and admission rates: A retrospective cohort study.

BACKGROUND: Emergency Department (ED) Observation Units (OU) can provide safe, effective care for low risk patients with intracranial hemorrhages. We compared current ED OU use for patients with subdural hematomas (SDH) to the validated Brain Injury Guidelines (BIG) to evaluate the potential impact of implementing this risk stratification tool. METHODS: Retrospective cohort of patients ≥18 years old with SDH of any cause from 2014 to 2020 to evaluate for potential missed OU cases. Missed OU cases were defined as patients with an initial Glasgow Coma Score (GCS) of 15 with hospital length of stays (LOS) <2 days, who did not meet the composite outcome and were not cared for in the OU or discharged from the ED. Composite outcome included in-hospital death or transition to hospice care, neurosurgical intervention, GCS decline, and worsening SDH size. Secondary outcomes were whether application of BIG would increase ED OU use or reduce CT use. RESULTS: 264 patients met inclusion criteria over 5.3 year study timeframe. Mean age was 61 years (range 19-93) and 61.4% were male. SDH were traumatic in 76.9% and 60.2% of the cohort had additional injuries. The admission rate was 81.4% (n = 215). Fourteen (6.5%) missed OU cases were identified (2.6/year). Retrospective application of BIG resulted in 82.6% (n = 217) at BIG 3, 10.2% (n = 27) at BIG 2 and 7.6% (n = 20) at BIG 1. Application of BIG would not have decreased admission rates (82.6% BIG 3) and BIG 1 and 2 admissions were often for medical co-morbidities. The composite outcome was met in 50% of BIG 3, 22% of BIG 2, and no BIG 1 patients. CONCLUSION: In a level 1 trauma center with an established observation unit, current clinical care processes missed very few patients who could be discharged or placed in ED OU for SDH. Hospital admissions in BIG 1/2 were driven by co-morbidities and/or injuries, limiting applicability of BIG to this population.

Comparison of Length of Stay Between Children Admitted to an Observation Versus Inpatient Unit.

OBJECTIVES: Many children who require hospitalization are ideal candidates for care in pediatric observation units (POUs) rather than inpatient pediatric units. Differences in outcomes between children cared for in these 2 practice settings have not been thoroughly evaluated. METHODS: In this retrospective cohort study, children aged 0 to 18 years admitted to a POU at a community hospital or inpatient unit at a children's hospital were enrolled if they met specific clinical criteria. Information regarding the current illness, medical history, and hospital course was collected. Hospital length of stay (LOS) was analyzed as the primary outcome; secondary outcomes included conversion to inpatient care for the POU group and return to pediatric emergency department within 7 days. Subgroup analysis was conducted on children presenting with respiratory illnesses. Propensity scores were used as a predictor in the final model. RESULTS: One hundred eighty-one admissions, 92 to POU and 89 to an inpatient unit, were analyzed. Mean LOS was 24.4 hours (95% confidence interval [CI], 21.7-27.1) for observation and 43.2 hours (95% CI, 37.8-48.6) for inpatient ( P < 0.01). Among the 126 children admitted for respiratory illnesses, the mean LOS was 32.3 hours (95% CI, 26.0-38.6) for observation and 48.1 hours (95% CI, 42.2-54.0) for inpatient ( P < 0.01). Survival analysis demonstrated a 1.61 (95% CI, 1.07-2.42) fold shorter time to discharge among children admitted to observation compared with inpatient ( P = 0.02) and a 1.70 (95% CI, 1.07-2.71) fold shorter time to discharge from observation compared with inpatient for respiratory illnesses ( P = 0.03). Within 7 days of discharge, 2 (2%) patients from the observation group and 1 (1%) from the inpatient group returned to the pediatric emergency department. CONCLUSIONS: These findings suggest that POU may provide the means toward efficient care for children in community settings with illnesses requiring brief hospitalizations. Future work including prospective investigations is needed to ascertain the generalizability of these findings.

The feasibility of emergency department observation units in the management of mild to moderate hyponatremia.

OBJECTIVE: To describe the feasibility of managing hyponatremia patients under outpatient observation status in an academic medical center, and compare outcomes based on the use of an emergency department observation unit (EDOU). METHODS: This is a retrospective cohort study of emergency department hyponatremic patients managed in four hospitals within a large urban academic medical center over 27 months. All patients had an admit-to-observation order, ICD-10 codes for hyponatremia, and mild (130-135 mmol/L) to moderate (121-129 mmol/L) hyponatremia. Observation settings were divided into two groups: EDOU and Non-Observation Unit (NOU) inpatient beds. Severe hyponatremia (≤120 mmol/L) was excluded. Primary clinical outcomes were inpatient admit rate, length of stay (LOS), total direct cost, the rate of adverse events and 30-day recidivism. RESULTS: 188 patients were managed as an observation patient, with 64 managed in an EDOU setting (age 74.0 yr, 70.3% female) and 124 managed in a NOU setting (age 71.5 yr, 64.5% female). Patient subgroups were similar in terms of presenting complaints, comorbidities, and medication histories. Initial and final sodium levels were similar between settings: EDOU (125.1 to 132.6 mmol/L) vs NOU (123.5 to 132.0 mmol/L). However, outcomes differed by setting for observation to inpatient admit rate (EDOU 28.1% vs NOU 37.9%, adjusted effect 0.70), overall length of stay (EDOU 19.2 h vs NOU 31.9 h; adjusted effect -10.5 h and total direct cost ($1230 vs $1531; adjusted effect -$167). EDOU sodium correction rates were faster (EDOU 0.44 mmol/L/h vs 0.24 mmol/L/h; adjusted effect 0.15 mmol/L/h) and 30-day recidivism rate was similar (EDOU 13% vs NOU 15%). There were no index visit deaths or intensive care unit admissions. CONCLUSION: Management of selected hyponatremia patients under observation status is feasible, with the EDOU setting demonstrating lower admit rates, shorter length of stay, and lower total direct costs with similar clinical outcomes.

The Value of an Emergency Medicine Virtual Observation Unit.

STUDY OBJECTIVE: We implemented a virtual observation unit in which emergency department (ED) patients receive observation-level care at home. Our primary aim was to compare this new care model to in-person observation care in terms of brick-and-mortar ED length of stay (inclusive of ED observation unit time) as well as secondarily on inpatient admission and 72-hour return visits (overall and with admission). METHODS: In a retrospective analysis of electronic health record data on ED observation patients from January 1, 2022 to December 29, 2022 from an academic urban ED, we used propensity matching to compare virtual to in-person observation patients on outcomes of interest. Patients were matched 1:1 based on age, sex, Charlson Comorbidity Index, and reason for observation. We also conducted real-time review of all virtual observation cases for potential safety concerns. RESULTS: Of 8,218 observation stays, 361 virtual observation patients were matched with 361 in-person observation patients. Virtual observation patients experienced lower median brick-and-mortar ED + EDOU LOS [14.6 (IQR 10.2, 18.9) versus 33.3 (IQR 28.1, 38.1) hours] and lower inpatient admission rates (10.2% [SD 5.0] versus 24.7% [SD 11.3]). The 72-hour return rate was higher for virtual observation patients (3.6% [SD 3.0] versus 2.5% [SD 3.0]). Among those with return visits, the rate of inpatient admission was higher among virtual observation patients (53.8% [SD 3.2] versus 11.1% [13.0]). There were no significant patient safety events recorded. CONCLUSION: Virtual observation unit patients used fewer hours in ED and ED observation relative to on-site observation patients. This new care delivery model warrants further study because it has the potential to positively impact ED capacity.

Time to diagnosis of acute complications after cardiovascular implantable electronic device insertion and optimal timing of discharge within the first 24 hours.

BACKGROUND: More than 3 million cardiovascular implantable electronic devices (CIEDs) are implanted annually. There are minimal data regarding the timing of diagnosis of acute complications after implantation. It remains unclear whether patients can be safely discharged less than 24 hours postimplantation. OBJECTIVE: The purpose of this study was to determine the precise timing of acute complication diagnosis after CIED implantation and optimal timing for same-day discharge. METHODS: A retrospective cohort analysis of adults 18 years or older who underwent CIED implantation at a large urban quaternary care medical center between June 1, 2015, and March 30, 2020, was performed. Standard of care included overnight observation and chest radiography 6 and 24 hours postprocedure. Medical records were reviewed for the timing of diagnosis of acute complications. Acute complications included pneumothorax, hemothorax, pericardial effusion, lead dislodgment, and implant site hematoma requiring surgical intervention. RESULTS: A total of 2421 patients underwent implantation. Pericardial effusion or cardiac tamponade was diagnosed in 13 patients (0.53%), pneumothorax or hemothorax in 19 patients (0.78%), lead dislodgment in 11 patients (0.45%), and hematomas requiring surgical intervention in 5 patients (0.2%). Of the 48 acute complications, 43 (90%) occurred either within 6 hours or more than 24 hours after the procedure. Only 3 acute complications identified between 6 and 24 hours required intervention during the index hospitalization (0.12% of all cases). CONCLUSION: Most acute complications are diagnosed either within the first 6 hours or more than 24 hours after implantation. With rare exception, patients can be considered for discharge after 6 hours of appropriate monitoring.

The impact of emergency department observation units on a health system.

IMPORTANCE: Protocol driven ED observation units (EDOU) have been shown to improve outcomes for patients and payers, however their impact on an entire health system is unknown. Two thirds of US hospitals do not have such units. OBJECTIVE: To determine the impact of a protocol-driven EDOU on health system length of stay, cost, and resource utilization. METHODS: A retrospective, observational, cross-sectional study of observation patients managed over 25 consecutive months in a four-hospital academic health system. Patients were identified using the "admit to observation" order and limited to adult, emergent / urgent, non-obstetric patients. Data was retrieved from a cost accounting database. The primary study exposure was the setting for observation care which was broken into three discrete groups: EDOUs (n = 3), hospital medicine observation units (HMSOU, n = 2), and a non-observation unit (NOU) bed located anywhere in the hospital. Outcomes included observation-to-inpatient admission rate, length of stay (LoS), total direct cost, and inpatient bed days saved. Unadjusted outcomes were compared, and outcomes were adjusted using multiple study variables. LoS and cost were compared using quantile regressions. Inpatient admit rate was compared using logistic regressions. RESULTS: The sample consisted of 48,145 patients who were 57.4% female, 48% Black, 46% White, median age of 58, with some variation in most common diagnoses and payer groups. The median unadjusted outcomes favored EDOU over NOU settings for admission rate (13.1% vs 37.1%), LoS [17.9 vs 35.6 h), and cost ($1279 vs $2022). The adjusted outcomes favored EDOU over NOU settings for admission rates [12.3% (95% CI 9.7-15.3) vs 26.4% (CI 21.3-32.3)], LoS differences [11.1 h (CI 10.6-11.5 h)] and cost differences [$127.5 (CI $105.4 - $149.5)]. Adjusted differences were similar and favored EDOU over HMSOU settings. For the health system, the total adjusted annualized savings of the EDOUs was 10,399 bed days and $1,329,443 in total direct cost per year. CONCLUSION: Within an academic medical center, EDOUs were associated with improved resource utilization and reduced cost. This represents a significant opportunity for hospitals to improve efficiency and contain costs.

Frequency, profile, and outcomes of patients with acute heart failure transferred directly to home hospitalization from emergency departments.

OBJECTIVE: To describe the frequency, clinical characteristics and outcomes of patients with acute heart failure (AHF) transferred directly from emergency departments to home hospitalisation (HH) and to compare them with those hospitalised in internal medicine (IM) or short-stay units (SSU). METHOD: We included patients with AHF transferred to HH by hospitals that considered this option during the Epidemiology of Acute Heart Failure in Spanish Emergency Departments (EAHFE) 4-5-6 Registries and compared them with patients admitted to IM or SSU in these centres. We compared the adjusted all-cause mortality at 1 year and adverse events 30 days after discharge. RESULTS: The study included 1473 patients (HH/IM/SSU:68/979/384). The HH rate was 4.7% (95% CI 3.8-6.0%). The patients in HH had few differences compared with those hospitalised in IM and SSUs. The HH mortality was 1.5%, and the HH median stay was 7.5 days (IQR, 4.5-12), similar to that of IM (median stay, 8 days; IQR, 5-13; p = .106) and longer than that of SSU (median stay, 4 days; IQR, 3-7; p < .001). The all-cause mortality at 1 year for HH did not differ from that of IM (HR, 0.91; 95% CI 0.73-1.14) or SSU (HR, 0.77; 95% CI 0.46-1.27); however, the emergency department readmission rate during the 30 days postdischarge was lower than that of IM (HR, 0.50; 95% CI 0.25-0.97) and SSU (HR, 0.37; 95% CI 0.19-0.74). There were no differences in the need for new hospitalisations or in the 30-day mortality rate. CONCLUSIONS: Direct transfer from the emergency department to HH is infrequent despite being a safe option for a certain patient profile with AHF.

Risk factors associated with hospital admission in COVID-19 patients initially admitted to an observation unit.

BACKGROUND: No set guidelines to guide disposition decisions from the emergency department (ED) in patients with COVID-19 exist. Our goal was to determine characteristics that identify patients at high risk for adverse outcomes who may need admission to the hospital instead of an observation unit. METHODS: We retrospectively enrolled 116 adult patients with COVID-19 admitted to an ED observation unit. We included patients with bilateral infiltrates on chest imaging, COVID-19 testing performed, and/or COVID-19 suspected as the primary diagnosis. The primary outcome was hospital admission. We assessed risk factors associated with this outcome using univariate and multivariable logistic regression. RESULTS: Of 116 patients, 33 or 28% (95% confidence interval [CI] 20-37%) required admission from the observation unit. On multivariable logistic regression analysis, we found that hypoxia defined as room-air oxygen saturation < 95% (OR 3.11, CI 1.23-7.88) and bilateral infiltrates on chest radiography (OR 5.57, CI 1.66-18.96) were independently associated with hospital admission, after adjusting for age. Two three-factor composite predictor models, age > 48 years, bilateral infiltrates, hypoxia, and Hispanic race, bilateral infiltrates, hypoxia yield an OR for admission of 4.99 (CI 1.50-16.65) with an AUC of 0.59 (CI 0.51-0.67) and 6.78 (CI 2.11-21.85) with an AUC of 0.62 (CI 0.54-0.71), respectively. CONCLUSIONS: Over 1/4 of suspected COVID-19 patients admitted to an ED observation unit ultimately required admission to the hospital. Risk factors associated with admission include hypoxia, bilateral infiltrates on chest radiography, or the combination of these two factors plus either age > 48 years or Hispanic race.

Racial and ethnic disparities in hospital observation in Maryland.

OBJECTIVES: Hospital observation is a key disposition option from the emergency department (ED) and encompasses up to one third of patients requiring post-ED care. Observation has been associated with higher incidence of catastrophic financial costs and has downstream effects on post-discharge clinical services. Yet little is known about the non-clinical determinants of observation assignment. We sought to evaluate the impact of patient-level demographic factors on observation designation among Maryland patients. METHODS: We conducted a retrospective analysis of all ED encounters in Maryland between July 2012 and January 2017 for four priority diagnoses (heart failure, chronic obstructive pulmonary disease [COPD], pneumonia, and acute chest pain) using multilevel logistic models allowing for heterogeneity of the effects across hospitals. The primary exposure was self-reported race and ethnicity. The primary outcome was the initial status assignment from the ED: hospital observation versus inpatient admission. RESULTS: Across 46 Maryland hospitals, 259,788 patient encounters resulted in a disposition of inpatient admission (65%) or observation designation (35%). Black (adjusted odds ratio [aOR]: 1.19; 95% confidence interval [CI]: 1.16-1.23) and Hispanic (aOR: 1.11; 95% CI: 1.01-1.21) patients were significantly more likely to be placed in observation than white, non-Hispanic patients. These differences were consistent across the majority of acute-care hospitals in Maryland (27/46). CONCLUSION: Black and Hispanic patients in Maryland are more likely to be treated under the observation designation than white, non-Hispanic patients independent of clinical presentation. Race agnostic, time-based status assignments may be key in eliminating these disparities.

Thirty-Day Re-observation, Chronic Re-observation, and Neighborhood Disadvantage.

OBJECTIVE: To determine whether neighborhood socioeconomic disadvantage, as determined by the Area Deprivation Index, increases 30-day hospital re-observation risk. PARTICIPANTS AND METHODS: This retrospective study of 20% Medicare fee-for-service beneficiary observation stays from January 1, 2014, to November 30, 2014, included 319,980 stays among 273,308 beneficiaries. We evaluated risk for a 30-day re-observation following an index observation stay for those living in the 15% most disadvantaged compared with the 85% least disadvantaged neighborhoods. RESULTS: Overall, 4.5% (270,600 of 6,080,664) of beneficiaries had index observation stays, which varied by disadvantage (4.3% [232,568 of 5,398,311] in the least disadvantaged 85% compared with 5.6% [38,032 of 682,353] in the most disadvantaged 15%). Patients in the most disadvantaged neighborhoods had a higher 30-day re-observation rate (2857 of 41,975; 6.8%) compared with least disadvantaged neighborhoods (13,543 of 278,005; 4.9%); a 43% increased risk (unadjusted odds ratio [OR], 1.43; 95% CI, 1.31 to 1.55). After adjustment, this risk remained (adjusted OR, 1.13; 95% CI, 1.04 to 1.22). Discharge to a skilled nursing facility reduced 30-day re-observation risk (OR, 0.63; 95% CI, 0.57 to 0.69), whereas index observation length of stay of 4 or more days (3 midnights) conferred increased risk (OR, 1.29; 95% CI, 1.09 to 1.52); those living in disadvantaged neighborhoods were less likely to discharge to skilled nursing facilities and more likely to have long index stays. Beneficiaries with more than one 30-day re-observation (chronic re-observation) had progressively greater disadvantage by number of stays (adjusted incident rate ratio, 1.08; 95% CI, 1.02 to 1.14). Observation prevalence varied nationally. CONCLUSION: Thirty-day re-observation, especially chronic re-observation, is highly associated with socioeconomic neighborhood disadvantage, even after accounting for factors such as race, disability, and Medicaid eligibility. Beneficiaries least able to pay are potentially most vulnerable to costs from serial re-observations and challenges of Medicare observation policy, which may discourage patients from seeking necessary care.

Observation Encounters and Length of Stay Benchmarking in Children's Hospitals.

BACKGROUND AND OBJECTIVES: Length of stay (LOS) is a common benchmarking measure for hospital resource use and quality. Observation status (OBS) is considered an outpatient service despite the use of the same facilities as inpatient status (IP) in most children's hospitals, and LOS calculations often exclude OBS stays. Variability in the use of OBS by hospitals may significantly impact calculated LOS. We sought to determine the impact of including OBS in calculating LOS across children's hospitals. METHODS: Retrospective cohort study of hospitalized children (age <19 years) in 2017 from the Pediatric Health Information System (Children's Hospital Association, Lenexa, KS). Normal newborns, transfers, deaths, and hospitals not reporting LOS in hours were excluded. Risk-adjusted geometric mean length of stay (RA-LOS) for IP-only and IP plus OBS was calculated and each hospital was ranked by quintile. RESULTS: In 2017, 45 hospitals and 625 032 hospitalizations met inclusion criteria (IP = 410 731 [65.7%], OBS = 214 301 [34.3%]). Across hospitals, OBS represented 0.0% to 60.3% of total discharges. The RA-LOS (SD) in hours for IP and IP plus OBS was 75.2 (2.6) and 54.3 (2.7), respectively (P < .001). For hospitals reporting OBS, the addition of OBS to IP RA-LOS calculations resulted in a decrease in RA-LOS compared with IP encounters alone. Three-fourths of hospitals changed ≥1 quintile in LOS ranking with the inclusion of OBS. CONCLUSIONS: Children's hospitals exhibit significant variability in the assignment of OBS to hospitalized patients and inclusion of OBS significantly impacts RA-LOS calculations. Careful consideration should be given to the inclusion of OBS when determining RA-LOS for benchmarking, quality and resource use measurements.

Hospital Observation Status and Readmission Rates.

BACKGROUND: In several states, payers penalize hospitals when an inpatient readmission follows an inpatient stay. Observation stays are typically excluded from readmission calculations. Previous studies suggest inconsistent use of observation designations across hospitals. We sought to describe variation in observation stays and examine the impact of inclusion of observation stays on readmission metrics. METHODS: We conducted a retrospective cohort study of hospitalizations at 50 hospitals contributing to the Pediatric Health Information System database from January 1, 2018, to December 31, 2018. We examined prevalence of observation use across hospitals and described changes to inpatient readmission rates with higher observation use. We described 30-day inpatient-only readmission rates and ranked hospitals against peer institutions. Finally, we included observation encounters into the calculation of readmission rates and evaluated hospitals' change in readmission ranking. RESULTS: Most hospitals (n = 44; 88%) used observation status, with high variation in use across hospitals (0%-53%). Readmission rate after index inpatient stay (6.8%) was higher than readmission after an index observation stay (4.4%), and higher observation use by hospital was associated with higher inpatient-only readmission rates. When compared with peers, hospital readmission rank changed with observation inclusion (60% moving at least 1 quintile). CONCLUSIONS: The use of observation status is variable among children's hospitals. Hospitals that more liberally apply observation status perform worse on the current inpatient-to-inpatient readmission metric, and inclusion of observation stays in the calculation of readmission rates significantly affected hospital performance compared with peer institutions. Consideration should be given to include all admission types for readmission rate calculation.

The financial implications of variability in decision to disposition times for patients placed in observation status.

INTRODUCTION: A host of variables beyond the control of the ED physician affect ED throughput. In-process time represents the period most directly affected by physician decision-making patterns. This study attempts to evaluate implications of variable decision-making for those patients placed in observation status for throughput and financial implications. METHODS: A retrospective review of all ED admissions to observation status over an 8-month period, for observation decision times (ODT) was performed. The average cost per patient bed hour in the ED, opportunity cost from patients not being seen during excessive ODTs, and the cost of an unfilled bed in an observation unit were estimated. RESULTS: Of 2693 observation cases reviewed, 114 (4.2%) had ODTs longer than two standard deviations above the median. These accumulated ODTs lead to an additional cost of $12,307, or $107 per admission. An additional 45 patients could have been treated during these excess ODTs, from which result an opportunity loss ranging from $32 to $1350 per hour. There is an additional cost of $8036 to maintain empty observation beds in the hospital. CONCLUSION: For those ODTs beyond two standard deviations above the median, there is a direct unreimbursed cost to the hospital, an opportunity cost for patients not seen in those occupied ED beds, and a cost of maintaining unfilled observation beds. Variability in the efficiency of decision-making suggests real consequences in terms of throughput and cost-to-treat.

Post-discharge acute care and outcomes following readmission reduction initiatives: national retrospective cohort study of Medicare beneficiaries in the United States.

OBJECTIVES: To determine whether patients discharged after hospital admissions for conditions covered by national readmission programs who received care in emergency departments or observation units but were not readmitted within 30 days had an increased risk of death and to evaluate temporal trends in post-discharge acute care utilization in inpatient units, emergency departments, and observation units for these patients. DESIGN: Retrospective cohort study. SETTING: Medicare claims data for 2008-16 in the United States. PARTICIPANTS: Patients aged 65 or older admitted to hospital with heart failure, acute myocardial infarction, or pneumonia-conditions included in the US Hospital Readmissions Reduction Program. MAIN OUTCOME MEASURES: Post-discharge 30 day mortality according to patients' 30 day acute care utilization; acute care utilization in inpatient and observation units and the emergency department during the 30 day and 31-90 day post-discharge period. RESULTS: 3 772 924 hospital admissions for heart failure, 1 570 113 for acute myocardial infarction, and 3 131 162 for pneumonia occurred. The overall post-discharge 30 day mortality was 8.7% for heart failure, 7.3% for acute myocardial infarction, and 8.4% for pneumonia. Risk adjusted mortality increased annually by 0.05% (95% confidence interval 0.02% to 0.08%) for heart failure, decreased by 0.06% (-0.09% to -0.04%) for acute myocardial infarction, and did not significantly change for pneumonia. Specifically, mortality increased for patients with heart failure who did not utilize any post-discharge acute care, increasing at a rate of 0.08% (0.05% to 0.12%) per year, exceeding the overall absolute annual increase in post-discharge mortality in heart failure, without an increase in mortality in observation units or the emergency department. Concurrent with a reduction in 30 day readmission rates, stays for observation and visits to the emergency department increased across all three conditions during and beyond the 30 day post-discharge period. Overall 30 day post-acute care utilization did not change significantly. CONCLUSIONS: The only condition with increasing mortality through the study period was heart failure; the increase preceded the policy and was not present among patients who received emergency department or observation unit care without admission to hospital. During this period, the overall acute care utilization in the 30 days after discharge significantly decreased for heart failure and pneumonia, but not for acute myocardial infarction.

Prediction of emergency department patient disposition decision for proactive resource allocation for admission.

We investigate the capability of information from electronic health records of an emergency department (ED) to predict patient disposition decisions for reducing "boarding" delays through the proactive initiation of admission processes (e.g., inpatient bed requests, transport, etc.). We model the process of ED disposition decision prediction as a hierarchical multiclass classification while dealing with the progressive accrual of clinical information throughout the ED caregiving process. Multinomial logistic regression as well as machine learning models are built for carrying out the predictions. Utilizing results from just the first set of ED laboratory tests along with other prior information gathered for each patient (2.5 h ahead of the actual disposition decision on average), our model predicts disposition decisions with positive predictive values of 55.4%, 45.1%, 56.9%, and 47.5%, while controlling false positive rates (1.4%, 1.0%, 4.3%, and 1.4%), with AUC values of 0.97, 0.95, 0.89, and 0.84 for the four admission (minor) classes, i.e., intensive care unit (3.6% of the testing samples), telemetry unit (2.2%), general practice unit (11.9%), and observation unit (6.6%) classes, respectively. Moreover, patients destined to intensive care unit present a more drastic increment in prediction quality at triage than others. Disposition decision classification models can provide more actionable information than a binary admission vs. discharge prediction model for the proactive initiation of admission processes for ED patients. Observing the distinct trajectories of information accrual and prediction quality evolvement for ED patients destined to different types of units, proactive coordination strategies should be tailored accordingly for each destination unit.

Observation unit management of low-risk emergency department patients with acute drug overdose.

Introduction: Observation units (OU) are being increasingly used within the Emergency Department (ED) to optimize care and reduce costs, but their use for management of overdose patients is unclear. The present study examined demographics, disposition and outcomes for ED overdose patients managed in an OU.Methods: This was a secondary analysis of a prospective consecutive cohort of adult overdose patients managed in an OU in a single ED from March 2015 to September 2018. The primary composite study outcome was occurrence of any advanced airway intervention, adverse cardiovascular events (ACVE), or mortality. Secondary outcomes were disposition and return visits.Results: Of 946 patients screened, 648 were included in the cohort. Of 132 patients requiring additional medical management after the ED visit, 25 (18.9%) were managed in the OU; 88% of OU patients were discharged home, no patients required airway management, one patient experienced an ACVE requiring admission, and there were no deaths. Three OU patients (12%) had 30-day return visits.Conclusion: In this study, almost one-fifth of patients requiring additional medical management after the ED visit qualified for a low-risk drug overdose OU pathway. Overdoses from a variety of substances were safely managed with acceptably low adverse event rates.

COPD Care Bundle in Emergency Department Observation Unit Reduces Emergency Department Revisits.

BACKGROUND: COPD exacerbations lead to accelerated decline in lung function, poor quality of life, and increased mortality and cost. Emergency department (ED) observation units provide short-term care to reduce hospitalizations and cost. Strategies to improve outcomes in ED observation units following COPD exacerbations are needed. We sought to reduce 30-d ED revisits for COPD exacerbations managed in ED observation units through implementation of a COPD care bundle. The study setting was an 800-bed, academic, safety-net hospital with 700 annual ED encounters for COPD exacerbations. Among those discharged from ED observation unit, the 30-d all-cause ED revisit rate (ie, the outcome measure) was 49% (baseline period: August 2014 through September 2016). METHODS: All patients admitted to the ED observation unit with COPD exacerbations were included. A multidisciplinary team implemented the COPD bundle using iterative plan-do-study-act cycles with a goal adherence of 90% (process measure). The bundle, adopted from our inpatient program, was developed using care-delivery failures and unmet subject needs. It included 5 components: appropriate inhaler regimen, 30-d inhaler supply, education on devices available after discharge, standardized discharge instructions, and a scheduled 15-d appointment. We used statistical process-control charts for process and outcome measures. To compare subject characteristics and process features, we sampled consecutive patients from the baseline (n = 50) and postbundle (n = 83) period over 5-month and 7-month intervals, respectively. Comparisons were made using t tests and chi-square tests with P < .05 significance. RESULTS: During baseline and postbundle periods, 410 and 165 subjects were admitted to the ED observation unit, respectively. After iterative plan-do-study-act cycles, bundle adherence reached 90% in 6 months, and the 30-d ED revisit rate declined from 49% to 30% (P = .003) with a system shift on statistical process-control charts. There was no difference in hospitalization rate from ED observation unit (45% vs 51%, P = .16). Subject characteristics were similar in the baseline and postbundle periods. CONCLUSIONS: Reliable adherence to a COPD care bundle reduced 30-d ED revisits among those treated in the ED observation unit.

Hospital revisits within 30 days after discharge for medical conditions targeted by the Hospital Readmissions Reduction Program in the United States: national retrospective analysis.

OBJECTIVE: To determine any changes in total hospital revisits within 30 days of discharge after a hospital stay for medical conditions targeted by the Hospital Readmissions Reduction Program (HRRP). DESIGN: Retrospective cohort study. SETTING: Hospital stays among Medicare patients for heart failure, acute myocardial infarction, or pneumonia between 1 January 2012 and 1 October 2015. PARTICIPANTS: Medicare fee-for-service patients aged 65 or over. MAIN OUTCOMES: Total hospital revisits within 30 days of discharge after hospital stays for medical conditions targeted by the HRRP, and by type of revisit: treat-and-discharge visit to an emergency department, observation stay (not leading to inpatient readmission), and inpatient readmission. Patient subgroups (age, sex, race) were also evaluated for each type of revisit. RESULTS: Our study cohort included 3 038 740 total index hospital stays from January 2012 to September 2015: 1 357 620 for heart failure, 634 795 for acute myocardial infarction, and 1 046 325 for pneumonia. Counting all revisits after discharge, the total number of hospital revisits per 100 patient discharges for target conditions increased across the study period (monthly increase 0.023 visits per 100 patient discharges (95% confidence interval 0.010 to 0.035)). This change was due to monthly increases in treat-and-discharge visits to an emergency department (0.023 (0.015 to 0.032) and observation stays (0.022 (0.020 to 0.025)), which were only partly offset by declines in readmissions (-0.023 (-0.035 to -0.012)). Increases in observation stay use were more pronounced among non-white patients than white patients. No significant change was seen in mortality within 30 days of discharge for target conditions (-0.0034 (-0.012 to 0.0054)). CONCLUSIONS: In the United States, total hospital revisits within 30 days of discharge for conditions targeted by the HRRP increased across the study period. This increase was due to a rise in post-discharge emergency department visits and observation stays, which exceeded the decline in readmissions. Although reductions in readmissions have been attributed to improvements in discharge planning and care transitions, our findings suggest that these declines could instead be because hospitals and clinicians have intensified efforts to treat patients who return to a hospital within 30 days of discharge in emergency departments and as observation stays.

Using the Boston Syncope Observation Management Pathway to Reduce Hospital Admission and Adverse Outcomes.

INTRODUCTION: In an age of increasing scrutiny of each hospital admission, emergency department (ED) observation has been identified as a low-cost alternative. Prior studies have shown admission rates for syncope in the United States to be as high as 70%. However, the safety and utility of substituting ED observation unit (EDOU) syncope management has not been well studied. The objective of this study was to evaluate the safety of EDOU for the management of patients presenting to the ED with syncope and its efficacy in reducing hospital admissions. METHODS: This was a prospective before-and-after cohort study of consecutive patients presenting with syncope who were seen in an urban ED and were either admitted to the hospital, discharged, or placed in the EDOU. We first performed an observation study of syncope management and then implemented an ED observation-based management pathway. We identified critical interventions and 30-day outcomes. We compared proportions of admissions and adverse events rates with a chi-squared or Fisher's exact test. RESULTS: In the "before" phase, 570 patients were enrolled, with 334 (59%) admitted and 27 (5%) placed in the EDOU; 3% of patients discharged from the ED had critical interventions within 30 days and 10% returned. After the management pathway was introduced, 489 patients were enrolled; 34% (p<0.001) of pathway patients were admitted while 20% were placed in the EDOU; 3% (p=0.99) of discharged patients had critical interventions at 30 days and 3% returned (p=0.001). CONCLUSION: A focused syncope management pathway effectively reduces hospital admissions and adverse events following discharge and returns to the ED.