Crowding and quality of pediatric emergency department care for acute asthma pas 2009

Crowding and Quality of Pediatric Emergency Department Care for Acute Asthma

Crowding and Quality of Pediatric Emergency Department Care for Acute Asthma

Marion R Sills, MD, MPH, Daksha Ranade, MPH, Michael G Kahn, MD, PhD and Diane Fairclough, DrPHPediatrics, University of Colorado Denver School of Medicine; Biostatistics and Informatics, Colorado School of Public Health; Children's Outcomes

Research Group, University of Colorado Denver School of Medicine

Marion R Sills, MD, MPH, Daksha Ranade, MPH, Michael G Kahn, MD, PhD and Diane Fairclough, DrPHPediatrics, University of Colorado Denver School of Medicine; Biostatistics and Informatics, Colorado School of Public Health; Children's Outcomes

Research Group, University of Colorado Denver School of Medicine

Affiliated with

Background Objectives

Methods

Results Limitations

Conclusions

To test the association between ED crowding and measures of quality of asthma care for children in a pediatric ED population.

To test the performance of ED asthma quality measures: delay in and nonreceipt of each of 3 asthma care processes.

To test the performance of two crowding measures.

Study Design: Retrospective cohort

Data Source: Epic® electronic health record at a single, urban, 48-bed, academic children’s hospital ED

Study Subjects:age 2-21 yearsICD-9 code for asthma as first diagnostic codeED visit November 1, 2007, to October 31, 2008

Dependent Variables:Primary outcome measures: the time from ED arrival to each of 3 asthma-care-related events (<1 hr, > 1hr)first asthma severity score (scale 5-15)first beta2-agonistfirst systemic corticosteroid

Secondary outcome measures: failure to receive each of these three processes

Process-Indicated Subgroups: defined based on when each of the 3 processes is indicated. The standard for “indicated” was drawn from the hospital’s asthma care clinical guideline, based on NHLBI recommendations.

Adult emergency department (ED) studies have shown a link between quality of care and crowding.

Demonstrating the link between crowding and quality in a pediatric ED population is hampered by the paucity of objective measures of ED quality and ED crowding.

To address the lack of quality measures relevant to a pediatric ED population, we propose asthma-related quality measures.

To address the lack of an explicit definition for ED crowding in a pediatric population, we test two measures used in adult ED studies.

Figure 2 shows the distribution of study patients by subgroup and by outcome The "good” quality outcome, timely receipt of the indicated process, is in purple

The “bad” quality outcomes, non-receipt or delayed receipt of an indicated process, are shown in orange and gold, respectively. These colors are also used in Tables 2 and 3

The larger size of the steroid-indicated subgroup compared to the β-agonist-indicated subgroup suggests that the definition of the latter group is more conservative

Of the two crowding measures, percent occupancy, but not number waiting to see provider, predicted lower quality asthma care.

Significant overall proportion of patients with asthma received poor quality care (non-receipt or delayed receipt of indicated process).

This finding confirms the importance of bringing crowding measures into the evaluation of pediatric ED quality-of-care.

This finding addresses the primary complaint about crowding: that EDs are less able to provide highest quality service when crowded.

Confirms findings in adult ED populations.

The first patient-level study that reports a direct relationship between an exposure to ED crowding and poorer quality of care in a pediatric population.

Primary Independent Variables: Two measures of ED crowding, assigned

to each patient at the time of ED arrivalPercent occupancy = number of ED patients ÷ number of ED beds (48)increment: 10% change in occupancy

Number waiting to see providerprovider = resident or attendingincrement: 1 patient waiting

Other Independent Variables: Age Gender Language preferred (English, other) No insurance Public insurance Second hand smoke reported in home Initial room air pulse oximetry value

(>90%, <90%) Initial triage level in one of the 2 most

acute categories out of 4 categories Evening (4 PM - midnight) ED arrival Arrival by ambulance

Analysis: Bivariate analyses: association between

each dependent variable and the independent variables

Multivariable analyses: used the log-binomial model to estimate the relative risk of each crowding measure on each outcome

In multivariable modeling (Table 3), percent occupancy is a significant predictor of 3 outcomes. Each 10% increase in percent occupancy was associated witha 24% increased risk of not getting an indicated asthma score

a 42% increased risk of a delayed asthma scorean 80% increased risk of a delayed β-agonist

The crowding measure “number waiting to see provider” did not predict non-reciept or delay of care

Single-center study Event timestamps reflect time

of a computer event; might differ from actual event

Did not use asthma severity score in models, as it was used in defining subgroups

In bivariate analyses ( Table 2), both crowding measures are significant predictors of delay in all 3 process measures

Table 1 shows the summary statistics for independent and dependent variables. The median time to first steroid exceeds the recommended time by more than 50%

FundingAgency for Healthcare Quality and Research

Emergency Medicine FoundationAmerican Lung AssociationChildren’s Hospital Research Institute

Figure 1: Flowchart of Subgroup Definition

Full asthma study population

Asthma scoreindicatedsubgroup

Beta-agonistindicatedsubgroup

Steroidindicatedsubgroup

Initial PAS > 7Received

> 2 beta-agonist treatments

Received asthma medication

in ED

Figure 2: Distribution of Patients by Subgroup

Asthma score > 1hr

48337%

No asthma score21116%

Asthma score <1hr

62047%

Beta-agonist < 1 hr57864%

No beta-agonist

81%

Beta-agonist > 1 hr31535%

Full asthma study populationn = 1473

Asthma score indicated subgroup

n = 1314

β-agonist indicatedsubgroupn = 901

Steroid indicatedsubgroupn = 955

Steroid > 1hr63066%

No steroid12713%

Steroid < 1hr

19821%

Table 1: Characteristics of Patients With Acute Asthma

Primary Independent Variables: Crowding Measures (median, [10P, 90P])

Percent occupancy 47 [21, 83]

Number waiting to see provider 6 [5, 13]

Other Independent Variables: Patient-Level Factors

Age (median, [10P, 90P]) 6 [2, 13]

Female (%) 39.6

Preferred language English (%) 82.9

Private insurance (%) 27.7

Public insurance (%) 62.9

Has PCP (%) 89.8

2nd hand smoke in home (%) 20.8

Initial pulse-ox < 90% (%) 16.8

Initial triage level high acuity (%) 32.5

1st asthma score (median, [10P, 90P]) 9 [5, 13]

Evening ED arrival time (%) 43.2

Arrived by ambulance (%) 9.9

Dependent Variables

Denominator: All with asthma

Subjects who received the process

Measure:

Process Measures

Receipt of process [%(n)]

Receipt of process in 1st hr [%(n)]

Time to process (minutes) (median, [10P, 90P])

1st Asthma score 75% (1106) 56% (622) 51 [15, 147]

1st β-agonist 88% (1293) 55% (711) 54 [16, 139]

1st Steroid 69% (1014) 23% (233) 96 [41, 219]

Table 2: Bivariate (Unadjusted) Comparisons Of Process Measures By Crowding Measures And Patient-level Factors

Subgroup Asthma score-indicated subgroup

β-agonist-indicated subgroup

Steroid-indicated subgroup

Process Measures

No asthma score

1st asthma score in > 1 hr

No β-agonist

1st β-agonist in > 1 hr

No steroid 1st steroid in > 1 hr

Primary Independent Variables: Crowding Measures (significant RRs are in bold green font)

Percent occupancy

1.116 (1.063, 1.172)

1.041 (1.031, 1.051)

1.187 (0.904, 1.558)

1.100 (1.007, 1.012)

1.049 (0.980, 1.122)

1.017 (1.008, 1.027)

Number waiting to see provider

1.032 (1.015, 1.050)

1.010 (1.007, 1.013)

1.035 (0.938, 1.142)

1.028 (1.020, 1.036)

1.022 (0.998, 1.047)

1.005 (1.002, 1.008)

Other Independent Variables: Patient-level Factors (blank spaces indicate RR is not significant)

Age 1.064 (1.029, 1.101)

English preferred

1.786 (1.051, 3.035)

Public insurance

0.626 (0.453, 0.864)

Initial pulse-ox < 90%

0.316 (0.187, 0.534)

0.582 (0.467, 0.725)

0.532 (0.406, 0.698)

0.353 (0.194, 0.641)

0.902 (0.815, 0.998)

Initial triage level high acuity

0.481 (0.352, 0.657)

0.668 (0.573, 0.779)

0.613 (0.505, 0.744)

0.869 (0.797, 0.946)

Evening ED arrival time

1.188 (1.040, 1.357)

9.089 (1.123, 73.57)

1.215 (1.018, 1.450)

Arrived by ambulance

0.644 (0.481, 0.861)

0.653 (0.455, 0.937)

3.575 (2.548, 5.016)

Table 3: Adjusted Models Using ED Crowding Measures, Adjusting For Patient Factors To Predict Primary Outcomes (significant findings are in bold green font)

Subgroup Asthma score-indicated subgroup

β-agonist-indicated subgroup*

Steroid-indicated subgroup*

Process Measures

Predictors

No asthma score

1st asthma score in > 1 hr

No β-agonist

1st β-agonist in > 1 hr

No steroid

1st steroid in > 1 hr

Percent occupancy

1.024 (1.010, 1.038)

1.042 (1.017, 1.068)

1.080 (1.034, 1.128)

1.022 (0.991, 1.055)

Number waiting to see provider

0.968 (0.926, 1.012)

0.998 (0.990, 1.006)

0.995 (0.981, 1.009)

0.999 (0.989, 1.010)

*The number of patients with no β-agonist and the number with no steroid were too small for modeling