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Figure.
Distribution of Hospital-Level Means of Emergency Department Measures of Timely Care
Distribution of Hospital-Level Means of Emergency Department Measures of Timely Care

The bottom and top of the box represent the 25th and 75th percentiles of the hospital-reported mean times for that measure, with the middle line representing the median. The whiskers represent the minimum and maximum reported values for each measure.

aTime of arrival to time seen by a health care professional.

bTime of arrival to time being sent home.

cTime of arrival to time leaving the emergency department for an inpatient bed.

dTime the physician decides to admit a patient to time the patient leaves the emergency department for an inpatient bed.

Table.  
Performance on Emergency Department Measures of Timely Care by Significant Hospital Characteristics
Performance on Emergency Department Measures of Timely Care by Significant Hospital Characteristics
1.
Sun  BC, Hsia  RY, Weiss  RE,  et al.  Effect of emergency department crowding on outcomes of admitted patients. Ann Emerg Med.2013;61(6):605-611.e6. doi:10.1016/j.annemergmed.2012.10.026.
PubMedArticle
2.
Guttmann  A, Schull  MJ, Vermeulen  MJ, Stukel  TA.  Association between waiting times and short term mortality and hospital admission after departure from emergency department: population based cohort study from Ontario, Canada. BMJ. 2011;342:d2983. doi:10.1136/bmj.d2983.
PubMedArticle
3.
Centers for Medicare & Medicaid Services. Data updates. 2013. http://www.medicare.gov/hospitalcompare/Data/Data-Updates.html. Accessed October 1, 2013.
4.
Chan  TC, Killeen  JP, Kelly  D, Guss  DA.  Impact of rapid entry and accelerated care at triage on reducing emergency department patient wait times, lengths of stay, and rate of left without being seen. Ann Emerg Med. 2005;46(6):491-497.
PubMedArticle
5.
Falvo  T, Grove  L, Stachura  R,  et al.  The opportunity loss of boarding admitted patients in the emergency department. Acad Emerg Med. 2007;14(4):332-337.
PubMedArticle
6.
Fee  C, Burstin  H, Maselli  JH, Hsia  RY.  Association of emergency department length of stay with safety-net status. JAMA. 2012;307(5):476-482.
PubMedArticle
7.
Hsia  RY, Asch  SM, Weiss  RE,  et al.  Hospital determinants of emergency department left without being seen rates. Ann Emerg Med. 2011;58(1):24-32.e3. doi:10.1016/j.annemergmed.2011.01.009.
PubMedArticle
8.
American Hospital Association. AHA Annual Survey Database. Chicago, IL: American Hospital Association; 2012.
9.
US Department of Agriculture. Measuring rurality: Rural-urban commuting area codes. http://www.ers.usda.gov/data-products/rural-urban-commuting-area-codes.aspx#.U6_kDvldUWI. Accessed June 29, 2014.
Research Letter
November 2014

Timeliness of Care in US Emergency DepartmentsAn Analysis of Newly Released Metrics From the Centers for Medicare & Medicaid Services

Author Affiliations
  • 1Currently a medical student at the University of California, San Francisco, School of Medicine
  • 2Department of Emergency Medicine, University of California, San Francisco
JAMA Intern Med. 2014;174(11):1847-1849. doi:10.1001/jamainternmed.2014.3431

The relationship between increasing emergency department (ED) crowding and worse outcomes for patients has been well documented.1,2 This evidence has created growing recognition among federal policy makers that the quality of emergency care should be measured. In July 2013, the Centers for Medicare & Medicaid Services3 made several quality measures of ED timeliness publicly available online. These data provide a national portrait of the ability of EDs to provide timely care, an essential concern given the severity and time sensitivity of many acute illnesses and injuries.

We investigated how hospital EDs perform on measurements of timely care and whether certain hospital characteristics or patient populations are associated with poor timeliness of ED care. Previous literature on ED timeliness of care has been limited to investigations with non–nationally representative samples or to 1 or 2 measures of timeliness of care.1,47

Methods

This study was considered exempt by the Committee on Human Research at the University of California, San Francisco. We conducted a cross-sectional analysis using 4 aggregate hospital-level ED measures in the Centers for Medicare & Medicaid Services Hospital Compare database3 calculated from the medical records of adult ED patients between April 1, 2012, and March 31, 2013. These measures include wait time (time of arrival to time seen by a health care professional) for discharged patients, length of stay (time of arrival to time being sent home for discharged patients or leaving the ED for admitted patients), and boarding time (time the physician decides to admit a patient to time the patient leaves the ED for an inpatient bed).

We incorporated hospital predictors of interest from the 2012 American Hospital Association Annual Survey,8 Rural-Urban Commuting Area codes,9 Medicare 2011 cost reports,10 and the 2012 Medicare Impact File.11 We included only acute care, general, and nonfederal hospitals.

We provided descriptive statistics on each ED measure and the results of a multivariable model adjusting for all hospital characteristics to identify the independent relationship between these characteristics and ED timeliness. All analyses were performed using statistical software (STATA 11; StataCorp LP).

Results

Our sample consisted of 3692 hospitals with EDs that reported at least 1 ED measure to the Centers for Medicare & Medicaid Services. Most were nonteaching (72.1%), private nonprofit (63.4%) hospitals located in urban areas (52.2%). For patients discharged from the ED, the median wait time to see a health care professional was approximately half an hour, and the length of stay was just over 2 hours. For admitted patients, the median length of stay in the ED was more than 4 hours, approximately one-third of which was accounted for by boarding time. Extreme variability existed for all measures (Figure).

The characteristics that were uniformly statistically associated with the 4 measures based on multivariable models are listed in the Table. The length of stay for patients ultimately discharged was longer at large hospitals (158.2 vs 145.0 [medium] and 133.5 [small] minutes, P < .001) and at urban hospitals (149.2 vs 142.1 [suburban], 134.6 [large rural town], and 131.2 [small town or isolated rural area] minutes, P < .001). Public hospitals (149.5 vs 132.9 [for profit] and 145.4 [private nonprofit] minutes, P < .001) and major teaching hospitals (172.6 vs 145.3 [minor] and 139.2 [nonteaching] minutes, P < .001) had the longest length of stay. These findings were similar for the other 3 measures.

Discussion

Our findings provide a crucial starting point for discussion on the status quo of ED quality and on ED quality metrics. Given the variation in hospital ED performance, our results suggest a potential for improvement in ED timeliness. However, if these measures are translated into pay-for-performance incentives, the financial pressures faced by larger, urban, major teaching, public hospitals may be exacerbated.

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Article Information

Corresponding Author: Renee Y. Hsia, MD, MSc, Department of Emergency Medicine, University of California, San Francisco, 1001 Potrero Ave, Room 1E21, San Francisco, CA 94110 (renee.hsia@emergency.ucsf.edu).

Published Online: September 15, 2014. doi:10.1001/jamainternmed.2014.3431.

Author Contributions: Mr Le had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Hsia.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Le.

Obtained funding: Hsia.

Administrative, technical, or material support: Hsia.

Study supervision: Hsia.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by an American Heart Association National Clinical Research Program Award (Dr Hsia).

Role of the Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

References
1.
Sun  BC, Hsia  RY, Weiss  RE,  et al.  Effect of emergency department crowding on outcomes of admitted patients. Ann Emerg Med.2013;61(6):605-611.e6. doi:10.1016/j.annemergmed.2012.10.026.
PubMedArticle
2.
Guttmann  A, Schull  MJ, Vermeulen  MJ, Stukel  TA.  Association between waiting times and short term mortality and hospital admission after departure from emergency department: population based cohort study from Ontario, Canada. BMJ. 2011;342:d2983. doi:10.1136/bmj.d2983.
PubMedArticle
3.
Centers for Medicare & Medicaid Services. Data updates. 2013. http://www.medicare.gov/hospitalcompare/Data/Data-Updates.html. Accessed October 1, 2013.
4.
Chan  TC, Killeen  JP, Kelly  D, Guss  DA.  Impact of rapid entry and accelerated care at triage on reducing emergency department patient wait times, lengths of stay, and rate of left without being seen. Ann Emerg Med. 2005;46(6):491-497.
PubMedArticle
5.
Falvo  T, Grove  L, Stachura  R,  et al.  The opportunity loss of boarding admitted patients in the emergency department. Acad Emerg Med. 2007;14(4):332-337.
PubMedArticle
6.
Fee  C, Burstin  H, Maselli  JH, Hsia  RY.  Association of emergency department length of stay with safety-net status. JAMA. 2012;307(5):476-482.
PubMedArticle
7.
Hsia  RY, Asch  SM, Weiss  RE,  et al.  Hospital determinants of emergency department left without being seen rates. Ann Emerg Med. 2011;58(1):24-32.e3. doi:10.1016/j.annemergmed.2011.01.009.
PubMedArticle
8.
American Hospital Association. AHA Annual Survey Database. Chicago, IL: American Hospital Association; 2012.
9.
US Department of Agriculture. Measuring rurality: Rural-urban commuting area codes. http://www.ers.usda.gov/data-products/rural-urban-commuting-area-codes.aspx#.U6_kDvldUWI. Accessed June 29, 2014.
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