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1.
Ann Emerg Med ; 68(1): 43-51.e2, 2016 07.
Article in English | MEDLINE | ID: mdl-26947799

ABSTRACT

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.


Subject(s)
Emergency Service, Hospital/statistics & numerical data , Patient Discharge/statistics & numerical data , Aged , Blood Pressure , Case-Control Studies , Cognitive Dysfunction/mortality , Cognitive Dysfunction/therapy , Female , Heart Rate , Humans , Intensive Care Units/statistics & numerical data , Logistic Models , Male , Mortality , Retrospective Studies , Risk Factors , Treatment Outcome
2.
Ann Emerg Med ; 66(5): 483-492.e5, 2015 Nov.
Article in English | MEDLINE | ID: mdl-26003004

ABSTRACT

STUDY OBJECTIVE: We assess whether a panel of emergency department (ED) crowding measures, including 2 reported by the Centers for Medicare & Medicaid Services (CMS), is associated with inpatient admission and death within 7 days of ED discharge. METHODS: We conducted a retrospective cohort study of ED discharges, using data from an integrated health system for 2008 to 2010. We assessed patient transit-level (n=3) and ED system-level (n=6) measures of crowding, using multivariable logistic regression models. The outcome measures were inpatient admission or death within 7 days of ED discharge. We defined a clinically important association by assessing the relative risk ratio and 95% confidence interval (CI) difference and also compared risks at the 99th percentile and median value of each measure. RESULTS: The study cohort contained a total of 625,096 visits to 12 EDs. There were 16,957 (2.7%) admissions and 328 (0.05%) deaths within 7 days. Only 2 measures, both of which were patient transit measures, were associated with the outcome. Compared with a median evaluation time of 2.2 hours, the evaluation time of 10.8 hours (99th percentile) was associated with a relative risk of 3.9 (95% CI 3.7 to 4.1) of an admission. Compared with a median ED length of stay (a CMS measure) of 2.8 hours, the 99th percentile ED length of stay of 11.6 hours was associated with a relative risk of 3.5 (95% CI 3.3 to 3.7) of admission. No system measure of ED crowding was associated with outcomes. CONCLUSION: Our findings suggest that ED length of stay is a proxy for unmeasured differences in case mix and challenge the validity of the CMS metric as a safety measure for discharged patients.


Subject(s)
Crowding , Emergency Service, Hospital/organization & administration , Length of Stay/statistics & numerical data , Patient Discharge , California , Female , Humans , Male , Retrospective Studies , Waiting Lists
3.
Med Care ; 52(7): 602-11, 2014 Jul.
Article in English | MEDLINE | ID: mdl-24926707

ABSTRACT

BACKGROUND: Emergency department (ED) crowding has been identified as a major threat to public health. OBJECTIVES: We assessed patient transit times and ED system crowding measures based on their associations with outcomes. RESEARCH DESIGN: Retrospective cohort study. SUBJECTS: We accessed electronic health record data on 136,740 adults with a visit to any of 13 health system EDs from January 2008 to December 2010. MEASURES: Patient transit times (waiting, evaluation and treatment, boarding) and ED system crowding [nonindex patient length-of-stay (LOS) and boarding, bed occupancy] were determined. Outcomes included individual inpatient mortality and admission LOS. Covariates included demographic characteristics, past comorbidities, severity of illness, arrival time, and admission diagnoses. RESULTS: No patient transit time or ED system crowding measure predicted increased mortality after control for patient characteristics. Index patient boarding time and lower bed occupancy were associated with admission LOS (based on nonoverlapping 95% CI vs. the median value). As boarding time increased from none to 14 hours, admission LOS increased an additional 6 hours. As mean occupancy decreased below the median (80% occupancy), admission LOS decreased as much as 9 hours. CONCLUSIONS: Measures indicating crowded ED conditions were not predictive of mortality after case-mix adjustment. The first half-day of boarding added to admission LOS rather than substituted for it. Our findings support the use of boarding time as a measure of ED crowding based on robust prediction of admission LOS. Interpretation of measures based on other patient ED transit times may be limited to the timeliness of care.


Subject(s)
Emergency Service, Hospital/statistics & numerical data , Hospital Mortality , Length of Stay/statistics & numerical data , Waiting Lists , Adolescent , Adult , Aged , Aged, 80 and over , Electronic Health Records , Female , Humans , Male , Middle Aged , Retrospective Studies , Time Factors , Young Adult
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