Background

With the recent increase use of observation care, it is important to understand the characteristics of patients that utilize this care and either have a prolonged observation care stay or require admission.

Methods

We a conducted a retrospective cohort study utilizing 5% sample data from Medicare patients age ≥65 years that was nationally representative in the year 2013. We performed a generalized estimating equation (GEE) logistic regression analysis to evaluate the relationship between an unsuccessful observation stay (defined as either requiring an inpatient admission from observation or having a prolonged observation stay) compared to having successful observation care. Observation cut offs of "successful" vs. "unsuccessful" were based on the CMS 2 midnight rule.

Results

Of 154,756 observation stays in 2013, 19 percent (n = 29,604) were admitted to the inpatient service and 34,275 (22.2%) had a prolonged observation stay. The two diagnoses most likely to have an unsuccessful observation stay were intestinal infections (OR 1.56, 95% CI 1.32⁻1.83) and pneumonia (OR 1.26, 95% CI 1.13⁻1.41).

Conclusion

We found patients placed in observation care with intestinal infections and pneumonia to have the highest odds of either being admitted from observation or having a prolonged observation stay.

OBJECTIVE: Emergency department (ED) crowding is linked with poor quality of care and worse outcomes, including higher mortality. With the growing emphasis on hospital performance measures, there is additional concern whether inadequate care during crowded periods increases a patients likelihood of subsequent inpatient admission. We sought to determine if ED crowding during the index visit was associated with these bounceback admissions. METHODS: We used comprehensive, nonpublic, statewide ED and inpatient discharge data from the California Office of Statewide Health Planning and Development from 2007 to identify index outpatient ED visits and bounceback admissions within 7 days. We further used ambulance diversion data collected from California local emergency medical services agencies to identify crowded days using intrahospital daily diversion hour quartiles. Using a hierarchical logistic regression model, we then determined if patients visiting on crowded days were more likely to have a subsequent bounceback admission. RESULTS: We analyzed 3,368,527 index visits across 202 hospitals, of which 596,471 (17.7%) observations were on crowded days. We found no association between ED crowding and bounceback admissions. This lack of relationship persisted in both a discrete (high/low) model (OR, 1.01; 95% CI, 0.99, 1.02) and a secondary model using ambulance diversion hours as a continuous predictor (OR, 1.00; 95% CI, 1.00, 1.00). CONCLUSIONS: Crowding as measured by ambulance diversion does not have an association with hospitalization within 7 days of an ED visit discharge. Therefore, bounceback admission may be a poor measure of delayed or worsened quality of care due to crowding.

Objective

Vital signs are critical markers of illness severity in the emergency department (ED). Providers need to understand the abnormal vital signs in older adults that are problematic. We hypothesized that in patients age > 65 years discharged from the ED, there are abnormal vital signs that are associated with an admission to an inpatient bed within 7 days of discharge.

Methods

We conducted a retrospective cohort study using data from a regional integrated health system of members age > 65 years during the years 2009 to 2010. We used univariate contingency tables to assess the relationship between hospital admission within 7 days of discharge and vital sign (including systolic blood pressure [sBP], heart rate [HR], body temperature, and pulse oximetry [SpO₂ ] values measured closest to discharge) using standard thresholds for abnormal and thresholds derived from the study data.

Results

Of 104,025 ED discharges, 4,638 (4.5%) were followed by inpatient admission within 7 days. Vital signs had a greater odds of admission beyond a single cutoff. The vital signs with at least twice the odds of admission were sBP < 97 mm Hg (odds ratio [OR] = 2.02, 95% CI = 1.57-2.60), HR > 101 beats/min (OR = 2.00 95% CI = 1.75-2.29), body temperature > 37.3°C (OR = 2.14, 95% CI = 1.90-2.41), and pulse oximetry < 92 SpO₂ (OR = 2.04, 95% CI = 1.55-2.68). Patients with two vital sign abnormalities per the analysis had the highest odds of admission. A majority of patients discharged with abnormal vital signs per the analysis were not admitted within 7 days of ED discharge.

Conclusion

While we found a majority of patients discharged with abnormal vital signs as defined by the analysis, not to be admitted after discharge, we identified vital signs associated with at least twice the odds of admission.

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.

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.

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.

Objective

Emergency department (ED) crowding is linked with poor quality of care and worse outcomes, including higher mortality. With the growing emphasis on hospital performance measures, there is additional concern whether inadequate care during crowded periods increases a patient's likelihood of subsequent inpatient admission. We sought to determine if ED crowding during the index visit was associated with these "bounceback" admissions.

Methods

We used comprehensive, nonpublic, statewide ED and inpatient discharge data from the California Office of Statewide Health Planning and Development from 2007 to identify index outpatient ED visits and bounceback admissions within 7 days. We further used ambulance diversion data collected from California local emergency medical services agencies to identify crowded days using intrahospital daily diversion hour quartiles. Using a hierarchical logistic regression model, we then determined if patients visiting on crowded days were more likely to have a subsequent bounceback admission.

Results

We analyzed 3,368,527 index visits across 202 hospitals, of which 596,471 (17.7%) observations were on crowded days. We found no association between ED crowding and bounceback admissions. This lack of relationship persisted in both a discrete (high/low) model (OR, 1.01; 95% CI, 0.99, 1.02) and a secondary model using ambulance diversion hours as a continuous predictor (OR, 1.00; 95% CI, 1.00, 1.00).

Conclusions

Crowding as measured by ambulance diversion does not have an association with hospitalization within 7 days of an ED visit discharge. Therefore, bounceback admission may be a poor measure of delayed or worsened quality of care due to crowding.

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.

Syncope is a common reason for emergency department (ED) visits, and patients are often admitted to exclude syncope of cardiovascular origin. Population-based data on patterns and predictors of cardiac outcomes may improve decision-making. Our objective was to identify patterns and predictors of short-term cardiac outcomes in ED patients with syncope. Administrative data from an integrated health system of 11 Southern California EDs were used to identify cardiac outcomes after ED presentation for syncope from January 1, 2002, to December 31, 2005. Syncope and cause of death were identified by codes from the International Classification of Disease, Ninth Revision. Cardiac outcomes included cardiac death and hospitalization or procedure consistent with ischemic heart disease, valvular disease, or arrhythmia. Predictors of cardiac outcomes were identified through multivariate logistic regression. There were 35,330 adult subjects who accounted for 39,943 ED visits for syncope. Risk of cardiac outcome sharply decreased following the 7 days after syncope. A 7-day cardiac outcome occurred in 893 cases (3%). Positive predictors of 7-day cardiac outcomes included age > or =60 years, male gender, congestive heart failure, ischemic heart disease, cardiac arrhythmia, and valvular heart disease. Negative predictors included dementia, pacemaker, coronary revascularization, and cerebrovascular disease. There was an age-dependent relation between 7-day cardiac outcomes and arrhythmia and valvular disease, with younger patients (<60 years of age) having greater risk of an event compared to their same-age counterparts. In conclusion, ED decision-making should focus on risk of cardiac event in the first 7 days after syncope and special attention should be given to younger patients with cardiac co-morbidities.