Death within 8 days after discharge to home from the emergency department

Acute patients discharged without an established diagnosis: risk of mortality and readmission of nonspecific diagnoses compared to disease-specific diagnoses

BACKGROUND

Nonspecific discharge diagnoses after acute hospital courses represent patients discharged without an established cause of their complaints. These patients should have a low risk of adverse outcomes as serious conditions should have been ruled out. We aimed to investigate the mortality and readmissions following nonspecific discharge diagnoses compared to disease-specific diagnoses and assessed different nonspecific subgroups.

METHODS

Register-based cohort study including hospital courses beginning in emergency departments across 3 regions of Denmark during March 2019-February 2020. We identified nonspecific diagnoses from the R- and Z03-chapter in the ICD-10 classification and excluded injuries, among others-remaining diagnoses were considered disease-specific. Outcomes were 30-day mortality and readmission, the groups were compared by Cox regression hazard ratios (HR), unadjusted and adjusted for socioeconomics, comorbidity, administrative information and laboratory results. We stratified into short (3-<12 h) or lengthier (12-168 h) hospital courses.

RESULTS

We included 192,185 hospital courses where nonspecific discharge diagnoses accounted for 50.7% of short and 25.9% of lengthier discharges. The cumulative risk of mortality for nonspecific vs. disease-specific discharge diagnoses was 0.6% (0.6-0.7%) vs. 0.8% (0.7-0.9%) after short and 1.6% (1.5-1.7%) vs. 2.6% (2.5-2.7%) after lengthier courses with adjusted HRs of 0.97 (0.83-1.13) and 0.94 (0.85-1.05), respectively. The cumulative risk of readmission for nonspecific vs. disease-specific discharge diagnoses was 7.3% (7.1-7.5%) vs. 8.4% (8.2-8.6%) after short and 11.1% (10.8-11.5%) vs. 13.7% (13.4-13.9%) after lengthier courses with adjusted HRs of 0.94 (0.90-0.98) and 0.95 (0.91-0.99), respectively. We identified 50 clinical subgroups of nonspecific diagnoses, of which Abdominal pain (n = 12,462; 17.1%) and Chest pain (n = 9,599; 13.1%) were the most frequent. The subgroups described differences in characteristics with mean age 41.9 to 80.8 years and mean length of stay 7.1 to 59.5 h, and outcomes with < 0.2-8.1% risk of 30-day mortality and 3.5-22.6% risk of 30-day readmission.

CONCLUSIONS

In unadjusted analyses, nonspecific diagnoses had a lower risk of mortality and readmission than disease-specific diagnoses but had a similar risk after adjustments. We identified 509 clinical subgroups of nonspecific diagnoses with vastly different characteristics and prognosis.

An explanatory machine learning framework for studying pandemics: The case of COVID-19 emergency department readmissions

One of the major challenges that confront medical experts during a pandemic is the time required to identify and validate the risk factors of the novel disease and to develop an effective treatment protocol. Traditionally, this process involves numerous clinical trials that may take up to several years, during which strict preventive measures must be in place to control the outbreak and reduce the deaths. Advanced data analytics techniques, however, can be leveraged to guide and speed up this process. In this study, we combine evolutionary search algorithms, deep learning, and advanced model interpretation methods to develop a holistic exploratory-predictive-explanatory machine learning framework that can assist clinical decision-makers in reacting to the challenges of a pandemic in a timely manner. The proposed framework is showcased in studying emergency department (ED) readmissions of COVID-19 patients using ED visits from a real-world electronic health records database. After an exploratory feature selection phase using genetic algorithm, we develop and train a deep artificial neural network to predict early (i.e., 7-day) readmissions (AUC = 0.883). Lastly, a SHAP model is formulated to estimate additive Shapley values (i.e., importance scores) of the features and to interpret the magnitude and direction of their effects. The findings are mostly in line with those reported by lengthy and expensive clinical trial studies.

Odds of return: a prospective study using provider assessment to predict short-term patient return visits to the emergency department

OBJECTIVE

Previous studies have assessed patient-level characteristics associated with emergency department (ED) return visits, but none have used provider assessment. We prospectively investigate whether clinical providers could accurately predict ED return visits.

METHODS

Prospective cohort study.

SETTING

Single academically affiliated urban county hospital.

PARTICIPANTS

Discharged ED patients over a 14-month period with a provider assessment of the likelihood of patient return within 7 days of ED discharge.

MAIN OUTCOME MEASURES

The primary outcome of interest was a return visit to the ED within 7 days. Additional outcome measures included a return visit within 72 hours and a return visit resulting in admission. We also measured the accuracy of provider gestalt, and provide measures of sensitivity, specificity, predictive values, and likelihood ratios.

RESULTS

Of the 11 922 ED discharges included in this study, providers expected 2116 (17.7%) to result in a return visit within 7 days. Providers were much more likely to perceive a return visit if the patient left against medical advice (OR: 5.97, 95% CI: 4.67 to 7.62), or was homeless (OR: 5.69, 95% CI: 5.14 to 6.29). Patients who actually returned were also more likely to be homeless, English speaking and to have left the ED against medical advice on the initial encounter. The strongest predictor of a return visit at both 72 hours and 7 days in multivariable modelling was provider assessment (OR: 3.77, 95% CI: 3.25 to 4.37; OR: 3.72, 95% CI: 3.29 to 4.21, respectively). Overall sensitivity and specificity of provider gestalt as a measure of patient return within 7 days were 47% and 87%, respectively. The positive and negative likelihood ratios were 3.51 and 0.61, respectively.

CONCLUSIONS

Clinician assessment was the strongest predictor of a return visit in this dataset. Clinician assessment may be used as a way to screen patients during the index visit and enrol them in efforts to decrease return visits.

Risk Factors and Causes of Short-Term Mortality after Emergency Department Discharge in Older Patients: Using Nationwide Health Insurance Claims Data

Background

The purpose of this study was to identify the risk factors and causes of short-term mortality after emergency department (ED) discharge in older patients.

Methods

This population-based cohort study used nationwide health insurance claims data in Korea from 2008 to 2014. The causes of death and diagnoses of patients who died within 1 week after discharge from EDs (1-week ED death) were obtained. The risk factors for 1-week ED death were calculated using Cox proportional hazard regression analyses.

Results

The rate of 1-week ED death was 0.5% among 133,251 individuals aged ≥65 years discharged from EDs. In multivariate analysis, the top five ED discharge diagnoses associated with an increased risk of 1-week ED death were hypotension and vascular disease (adjusted hazard ratio [aHR]=5.11; 95% confidence interval [CI], 3.03–8.63), neoplasm (aHR=4.89; 95% CI, 3.77–6.35), coronary artery disease (aHR=3.83; 95% CI, 2.73–5.39), dyspnea (aHR=3.41; 95% CI, 2.48–4.68), and respiratory disease (aHR=2.25; 95% CI, 1.73–2.92). The most common causes of 1-week ED death were neoplasm (14.8%), senility (13.8%), and cerebrovascular disease (11.7%).

Conclusion

Neoplasm, coronary artery disease, and respiratory disease were the discharge diagnoses associated with an increased risk of short-term mortality after ED discharge. Neoplasm was the leading cause of short-term mortality after ED discharge in older patients.

Risk of death within 7 days of discharge from emergency departments with different organizational models

OBJECTIVE

The aim of this study is to investigate the association between emergency department (ED) organizational models and the risk of death within 7 days of ED discharge.

PATIENTS AND METHODS

We included Danish ED discharges between 1 January 2011 and 24 December 2014 that led to death within 7 days of discharge. The inclusion criterion was age older than 18 years. The exclusion criterion was further in-hospital admission. First model (Virtual): other departments employ interns who perform ED tasks. They are responsible for ED patient care and prioritize their task order between their own department and the ED. Second model (Hybrid): the ED/other departments perform tasks; interns/consultants are employed by the ED/other departments. The ED/other departments have patient care responsibility. Third model (Independent): the ED performs all tasks; employs interns/consultants; and have patient care responsibility. Sex, age, Charlson Comorbidity Index score, and primary diagnosis were used to describe patient characteristics. We calculated the risk of death within 7 days of discharge using multiple logistic regression analysis.

RESULTS

In 805 out of 201 299 discharges included in the study, the patient died within 7 days. Compared with the Virtual model, the odds ratio for death within 7 days of discharge was 0.72 (95% confidence interval: 0.59-0.92) for the Independent model and 0.75 (95% confidence interval: 0.61-0.92) for the Hybrid+Virtual model. Increased risk was associated with male sex, older age, and a medium or a high Charlson Comorbidity Index score.

CONCLUSION

Compared with discharges from a Virtual model, the risk of death within 7 days of discharge was lower if the ED had an Independent or a Hybrid+Virtual model.

Short-Term Outcomes and Factors Associated With Adverse Events Among Adults Discharged From the Emergency Department After Treatment for Acute Heart Failure

BACKGROUND

Although 80% of patients with heart failure seen in the emergency department (ED) are admitted, less is known about short-term outcomes and demand for services among discharged patients.

METHODS AND RESULTS

We examined adult members of a large integrated delivery system who visited an ED for acute heart failure and were discharged from January 1, 2013, through September 30, 2014. The primary outcome was a composite of repeat ED visit, hospital admission, or death within 7 days of discharge. We identified multivariable baseline patient-, provider-, and facility-level factors associated with adverse outcomes within 7 days of ED discharge using logistic regression. Among 7614 patients, mean age was 77.2 years, 51.9% were women, and 28.4% were people of color. Within 7 days of discharge, 75% had outpatient follow-up (clinic, telephone, or e-mail), 7.1% had an ED revisit, 4.7% were hospitalized, and 1.2% died. Patients who met the primary outcome were more likely to be older, smokers, have a history of hemorrhagic stroke, hypothyroidism, and dementia, and less likely to be treated in a facility with an observation unit. In multivariable analysis, higher comorbidity scores and history of smoking were associated with a higher odds of the primary outcome, whereas treatment in a facility with an observation unit and presence of outpatient follow-up within 7 days were associated with a lower odds.

CONCLUSIONS

We identified selected hospital and patient characteristics associated with short-term adverse outcomes. Further understanding of these factors may optimize safe outpatient management in ED-treated patients with heart failure.

Poor Outcomes After Emergency Department Discharge of the Elderly: A Case-Control Study

STUDY OBJECTIVE

The emergency department (ED) is an inherently high-risk setting. Our objective is to identify the factors associated with the combined poor outcome of either death or an ICU admission shortly after ED discharge in older adults.

METHODS

We conducted chart review of 600 ED visit records among adults older than 65 years that resulted in discharge from any of 13 hospitals within an integrated health system in 2009 to 2010. We randomly chose 300 patients who experienced the combined outcome within 7 days of discharge and matched case patients to controls who did not experience the outcome. Two emergency physicians blinded to the outcome reviewed the records and identified whether a number of characteristics were present. Predictors of the outcome were identified with conditional logistic regression.

RESULTS

Of 1,442,594 ED visits to Kaiser Permanente Southern California in 2009 to 2010, 300 unique cases and 300 unique control records were randomly abstracted. Characteristics associated with the combined poor outcome included cognitive impairment (adjusted odds ratio [AOR] 2.10; 95% confidence interval [CI] 1.19 to 3.56), disposition plan change (AOR 2.71; 95% CI 1.50 to 4.89), systolic blood pressure less than 120 mm Hg (AOR 1.48; 95% CI 1.00 to 2.20), and pulse rate greater than 90 beats/min (AOR 1.66; 95% CI 1.02 to 2.71).

CONCLUSION

We found that older patients discharged from the ED with a change in disposition from "admit" to "discharge," cognitive impairment, systolic blood pressure less than 120 mm Hg, and pulse rate greater than 90 beats/min were at increased risk of death or ICU admission shortly after discharge. Increased awareness of these high-risk characteristics may improve ED disposition decisionmaking.

Characteristics and Risk Factors of Out-of-Hospital Cardiac Arrest Within 72 Hours After Discharge

OBJECTIVE

To determine the characteristics and risk factors for patients who developed out-of-hospital cardiac arrest (OHCA) within 72 hours after emergency department (ED) discharge.

METHODS

A nested case-control study (1:4 ratio) was conducted in 5 EDs from January 2002 to December 2011. The study group consisted of adults experiencing nontraumatic OHCA who revisited ED within 72 hours after discharge. Patients matched in sex, age group and chief complaints were selected for the control group. Demographic data, discharge diagnosis, discharge vital signs and laboratory result were collected. Etiologies of cardiac arrest and whether the events were expected or related to the 1st ED visit were reviewed.

RESULTS

In all, 1,657,870 patients were discharged during the study period; 109 developed OHCA within 72 hours of ED discharge (6.6/100,000 per year). The mean age was 64.7 years and 67.9% were men. After comparison with the control group, a higher heart rate (88.5 ± 18.23 versus 81.7 ± 15.93 beat per minutes, P = 0.003) and higher serum creatinine level (2.2 ± 2.30 versus 1.4 ± 1.38 mg/dL, P = 0.002) remain the statistical significant characteristics of study group by conditional logistic regression. Approximately 60% events were expected or unrelated to the 1st ED visit. Among patients whose OHCA were unexpected and related to the 1st ED visit, 71.4% had a cardiac cause. Of these, 20% had chest pain, but 40% had angina-equivalent symptoms during 1st presentation.

CONCLUSIONS

A higher discharge heart rate and higher creatinine level are risk factors in these patients.

A cross-sectional study of doctors', managers' and public representatives' views regarding acceptable level of risk in discharges from the emergency department

BACKGROUND

Discharging a patient from the emergency department (ED) always involves some risk of a poor outcome.

AIM

This study examined the hypothesis that there would be an increasing gradient of risk aversion from physicians through clinicians in management and managers to public representatives regarding an acceptable level of risk when considering discharging a patient from the ED.

METHODS

An internet survey was conducted among 180 consultant physicians, 47 clinicians involved in management, 143 senior healthcare managers and 418 public representatives in Ireland. Subjects asked to assess three clinical vignettes for the level of risk for death within the next week that could have been prevented by admission at which discharge from the ED would be acceptable. Choices ranged from 1/100 risk of death to 'no risk of death is acceptable'. The median of each subject's responses was the primary outcome measure.

RESULTS

The response rates were 64% for consultant physicians, 57% for clinicians in management, 53% for managers and 29% for public representatives. The median risk choice (interquartile range) was 1/1000 (1/500-1/5000), 1/1000 (1/500-1/10,000), 1/5000 (1/1000-1/10,000) and 1/10,000 (1/1000-0) in the respective groups (Jonckheere-Terpstra test P < 0.0001). All pairwise comparisons between doctors and managers or public representatives were significant. Older clinicians were significantly more risk tolerant than younger clinicians.

CONCLUSIONS

There are significant differences in risk tolerance when considering discharge from the ED between different groups with doctors being most risk tolerant and politicians most risk averse.

Predictors of admission after emergency department discharge in older adults

OBJECTIVES

To identify predictors of hospital inpatient admission of older Medicare beneficiaries after discharge from the emergency department (ED).

DESIGN

Retrospective cohort study.

SETTING

Nonfederal California hospitals (n = 284).

PARTICIPANTS

Visits of Medicare beneficiaries aged 65 and older discharged from California EDs in 2007 (n = 505,315).

MEASUREMENTS

Using the California Office of Statewide Health Planning and Development files, predictors of hospital inpatient admission within 7 days of ED discharge in older adults (≥65) with Medicare were evaluated.

RESULTS

Hospital inpatient admissions within 7 days of ED discharge occurred in 23,340 (4.6%) visits and were associated with older age (70-74: adjusted odds ratio (AOR) = 1.12, 95% confidence interval (CI) = 1.07-1.17; 75-79: AOR = 1.18, 95% CI = 1.13-1.23; ≥80: AOR = 1.4, 95% CI = 1.35-1.46), skilled nursing facility use (AOR = 1.82, 95% CI = 1.72-1.94), leaving the ED against medical advice (AOR = 1.82, 95% CI = 1.67-1.98), and the following diagnoses with the highest odds of admission: end-stage renal disease (AOR = 3.83, 95% CI = 2.42-6.08), chronic renal disease (AOR = 3.19, 95% CI = 2.26-4.49), and congestive heart failure (AOR = 3.01, 95% CI = 2.59-3.50).

CONCLUSION

Five percent of older Medicare beneficiaries have a hospital inpatient admission after discharge from the ED. Chronic conditions such as renal disease and heart failure were associated with the greatest odds of admission.

Patient returns to the emergency department: the time-to-return curve

OBJECTIVES

Although 72-hour emergency department (ED) revisits are increasingly used as a hospital metric, there is no known empirical basis for this 72-hour threshold. The objective of this study was to determine the timing of ED revisits for adult patients within 30 days of ED discharge.

METHODS

This was a retrospective cohort study of all nonfederal ED discharges in Florida and Nebraska from April 1, 2010, to March 31, 2011, using data from the Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP). ED discharges were followed forward to identify ED revisits occurring at any hospital within the same state within 30 days. The cumulative hazard of an ED revisit was plotted. Parametric and nonparametric modeling was performed to characterize the rate of ED revisits.

RESULTS

There were 4,782,045 ED discharges, with 7.5% (95% confidence interval [CI] = 7.4% to 7.5%) associated with 3-day revisits, and 22.4% (95% CI = 22.3% to 22.4%) associated with 30-day revisits, inclusive of the 3-day revisits. A double-exponential model fit the data best (p < 0.0001), and a single hinge point at 9 days (multivariate adaptive regression splines [MARS] model) yielded the best linear fit to the data, suggesting 9 days as the most reasonable cutoff for identification of acute ED revisits. Multiple stratified and subgroup analyses produced similar results. Future work should focus on identifying primary reasons for potentially avoidable return ED visits instead of on the revisit occurrence itself, thus more directly measuring potential lapses in delivery of high-quality care.

CONCLUSIONS

Almost one-quarter of ED discharges are linked to 30-day ED revisits, and the current 72-hour ED metric misses close to 70% of these patients. Our findings support 9 days as a more inclusive cutoff for studies of ED revisits.

All-cause mortality and suicide within 8 days after emergency department discharge

AIM

The aim of the study was to evaluate the association of death within 8-30 days after discharge home from the emergency department with a non-causative diagnosis in a prospective cohort study.

METHODS

The 227,097 visits to the emergency department were filed by personal identification number and included information on gender, age, admission, discharge, and diagnosis. The visits were classified by main diagnosis at discharge into those with non-causative diagnosis and those with other diagnoses. Mortality per 100,000 within 8, 15 and 30 days and the corresponding hazard ratio (HR) and 95% confidence intervals (CI) were calculated for all causes of death and for selected causes of death in a time-dependent analysis.

RESULTS

The HRs of all causes of death for patients with a non-causative diagnosis were 0.64 (95% CI 0.41-1.01) within 8 days, 0.70 (95% CI 0.50-0.99) within 15 days, and 0.82 (95% CI 0.65-1.04) within 30 days as compared to those with a causative diagnosis. The HRs within 30 days among those with a non-causative diagnosis at discharge were 1.48 (95% CI 1.03-2.13) for malignant neoplasm, 3.72 (95% CI 1.44-9.60) for suicide, and 0.50 (95% CI 0.32-0.79) for diseases of the circulatory system.

CONCLUSION

Death within 8 days after discharge home from the ED is a rare event. Death of patients that occur shortly after discharge who had received a non-causative diagnosis as the main diagnosis may indicate a misjudgement of the patients' condition at that time.

Qualitative factors in patients who die shortly after emergency department discharge

OBJECTIVES

Early death after emergency department (ED) discharge may signal opportunities to improve care. Prior studies are limited by incomplete mortality ascertainment and lack of clinically important information in administrative data. The goal in this hypothesis-generating study was to identify patient and process of care themes that may provide possible explanations for early postdischarge mortality.

METHODS

This was a qualitative analysis of medical records of adult patients who visited the ED of any of six hospitals in an integrated health system (Kaiser Permanente Southern California [KPSC]) and died within 7 days of discharge in 2007 and 2008. Nonmembers, visits to non-health plan hospitals, patients receiving or referred to hospice care, and patients with do not attempt resuscitation or do not intubate orders (DNAR/DNI) were excluded. Under the guidance of two qualitative research scientists, a team of three emergency physicians used grounded theory techniques to identify patient clinical presentations and processes of care that serve as potential explanations for poor outcome after discharge.

RESULTS

The source population consisted of a total of 290,092 members with 446,120 discharges from six KPSC EDs in 2007 and 2008. A total of 203 deaths occurred within 7 days of ED discharge (0.05%). Sixty-one randomly chosen cases were reviewed. Patient-level themes that emerged included an unexplained persistent acute change in mental status, recent fall, abnormal vital signs, ill-appearing presentation, malfunctioning indwelling device, and presenting symptoms remaining at discharge. Process-of-care factors included a discrepancy in history of present illness, incomplete physical examination, and change of discharge plan by a third party, such as a consulting or admitting physician.

CONCLUSIONS

In this hypothesis-generating study, qualitative research techniques were used to identify clinical and process-of-care factors in patients who died within days after discharge from an ED. These potential predictors will be formally tested in a future quantitative study.

Factors associated with short-term bounce-back admissions after emergency department discharge

STUDY OBJECTIVE

Hospitalizations that occur shortly after emergency department (ED) discharge may reveal opportunities to improve ED or follow-up care. There currently is limited, population-level information about such events. We identify hospital- and visit-level predictors of bounce-back admissions, defined as 7-day unscheduled hospital admissions after ED discharge.

METHODS

Using the California Office of Statewide Health Planning and Development files, we conducted a retrospective cohort analysis of adult (aged >18 years) ED visits resulting in discharge in 2007. Candidate predictors included index hospital structural characteristics such as ownership, teaching affiliation, trauma status, and index ED size, along with index visit patient characteristics of demographic information, day of service, against medical advice or eloped disposition, insurance, and ED primary discharge diagnosis. We fit a multivariable, hierarchic logistic regression to account for clustering of ED visits by hospitals.

RESULTS

The study cohort contained a total of 5,035,833 visits to 288 facilities in 2007. Bounce-back admission within 7 days occurred in 130,526 (2.6%) visits and was associated with Medicaid (odds ratio [OR] 1.42; 95% confidence interval [CI] 1.40 to 1.45) or Medicare insurance (OR 1.53; 95% CI 1.50 to 1.55) and a disposition of leaving against medical advice or before the evaluation was complete (OR 1.90; 95% CI 1.89 to 2.0). The 3 most common age-adjusted index ED discharge diagnoses associated with a bounce-back admission were chronic renal disease, not end stage (OR 3.3; 95% CI 2.8 to 3.8), end-stage renal disease (OR 2.9; 95% CI 2.4 to 3.6), and congestive heart failure (OR 2.5; 95% CI 2.3 to 2.6). Hospital characteristics associated with a higher bounce-back admission rate were for-profit status (OR 1.2; 95% CI 1.1 to 1.3) and teaching affiliation (OR 1.2; 95% CI 1.0 to 1.3).

CONCLUSION

We found 2.6% of discharged patients from California EDs to have a bounce-back admission within 7 days. We identified vulnerable populations, such as the very old and the use of Medicaid insurance, and chronic or end-stage renal disease as being especially at risk. Our findings suggest that quality improvement efforts focus on high-risk individuals and that the disposition plan of patients consider vulnerable populations.

Patterns and predictors of short-term death after emergency department discharge

STUDY OBJECTIVE

The emergency department (ED) is an inherently high-risk setting. Early death after an ED evaluation is a rare and devastating outcome; understanding it can potentially help improve patient care and outcomes. Using administrative data from an integrated health system, we describe characteristics and predictors of patients who experienced 7-day death after ED discharge.

METHODS

Administrative data from 12 hospitals were used to identify death after discharge in adults aged 18 year or older within 7 days of ED presentation from January 1, 2007, to December 31, 2008. Patients who were nonmembers of the health system, in hospice care, or treated at out-of-network EDs were excluded. Predictors of 7-day postdischarge death were identified with multivariable logistic regression.

RESULTS

The study cohort contained a total of 475,829 members, with 728,312 discharges from Kaiser Permanente Southern California EDs in 2007 and 2008. Death within 7 days of discharge occurred in 357 cases (0.05%). Increasing age, male sex, and number of preexisting comorbidities were associated with increased risk of death. The top 3 primary discharge diagnoses predictive of 7-day death after discharge included noninfectious lung disease (odds ratio [OR] 7.1; 95% confidence interval [CI] 2.9 to 17.4), renal disease (OR 5.6; 95% CI 2.2 to 14.2), and ischemic heart disease (OR 3.8; 95% CI 1.0 to 13.6).

CONCLUSION

Our study suggests that 50 in 100,000 patients in the United States die within 7 days of discharge from an ED. To our knowledge, our study is the first to identify potentially "high-risk" discharge diagnoses in patients who experience a short-term death after discharge.