A Quality Improvement Collaborative to Improve the Discharge Process for Hospitalized ChildrenSusan Wu, MD, a, b Amy Tyler, MD, c, d Tina Logsdon, MS, e Nicholas M. Holmes, MD, MBA, f, g Ara Balkian, MD, MBA, a, b Mark Brittan, MD, MPH, c, d LaVonda Hoover, BSN, CPN, MS, b Sara Martin, RN, BSN, d Melisa Paradis, MSN, RN, CPN, h Rhonda Sparr-Perkins, RN, MBA, g Teresa Stanley, DNP, RN, i Rachel Weber, MSIE, g Michele Saysana, MDi, j

Although discharge from the hospital

for many pediatric patients means the

child is clinically improving, it also

creates potential risk because of the

transition of care. 1 At a minimum this

care may include medications and

follow-up appointments, but it may

also include home care, wound care,

or therapy. The discharge process

has historically been fragmented

and variable, leading to errors. 2 – 4

In 1 adult study, as many as 49% of

patients had ≥1 medication error at

discharge, which could increase their

likelihood for readmission.5 In other

studies, 10% to 20% of patients had

an adverse event after discharge, with

about half of these events deemed to

be preventable. 6, 7

Most of the work on improving

discharge processes to date has

abstractOBJECTIVE: To assess the impact of a quality improvement collaborative on

quality and efficiency of pediatric discharges.

METHODS: This was a multicenter quality improvement collaborative including

11 tertiary-care freestanding children’s hospitals in the United States,

conducted between November 1, 2011 and October 31, 2012. Sites selected

interventions from a change package developed by an expert panel. Multiple

plan–do–study–act cycles were conducted on patient populations selected

by each site. Data on discharge-related care failures, family readiness for

discharge, and 72-hour and 30-day readmissions were reported monthly

by each site. Surveys of each site were also conducted to evaluate the use of

various change strategies.

RESULTS: Most sites addressed discharge planning, quality of discharge

instructions, and providing postdischarge support by phone. There was

a significant decrease in discharge-related care failures, from 34% in the

first project quarter to 21% at the end of the collaborative (P < .05). There

was also a significant improvement in family perception of readiness for

discharge, from 85% of families reporting the highest rating to 91%

(P < .05). There was no improvement in unplanned 72-hour (0.7% vs 1.1%,

P = .29) and slight worsening of the 30-day readmission rate (4.5% vs 6.3%,

P = .05).

CONCLUSIONS: Institutions that participated in the collaborative had lower

rates of discharge-related care failures and improved family readiness

for discharge. There was no significant improvement in unplanned

readmissions. More studies are needed to evaluate which interventions are

most effective and to assess feasibility in non–children’s hospital settings.

QUALITY REPORTPEDIATRICS Volume 138 , number 2 , August 2016 :e 20143604

To cite: Wu S, Tyler A, Logsdon T, et al. A Quality

Improvement Collaborative to Improve the

Discharge Process for Hospitalized Children.

Pediatrics. 2016;138(2):e20143604

aDepartment of Pediatrics, University of Southern

California Keck School of Medicine, Los Angeles, California; bChildren’s Hospital Los Angeles, Los Angeles, California; cDepartment of Pediatrics, University of Colorado School of

Medicine, Denver, Colorado; dChildren’s Hospital Colorado,

Aurora, Colorado; eChildren’s Hospital Association,

Overland Park, Kansas; fDepartment of Surgery, Division

of Urology, University of California San Diego, San Diego,

California; gRady Children’s Hospital San Diego, San

Diego, California; hChildren’s Hospital & Medical Center,

Omaha, Nebraska; iRiley Hospital for Children at Indiana

University Health, Indianapolis, Indiana; and jDepartment

of Pediatrics, Indiana University School of Medicine,

Indianapolis, Indiana

Dr Wu conceptualized and designed the study,

participated in data collection, assisted in data

analysis, drafted the initial manuscript, and

critically reviewed and revised the manuscript;

Drs Tyler, Brittan, and Saysana and Ms Hoover,

Ms Martin, and Ms Stanley conceptualized and

designed the study, participated in data collection,

drafted the initial manuscript, and critically

reviewed and revised the manuscript; Ms Logsdon

conceptualized and designed the study, supervised

data collection and analysis, drafted the initial

manuscript, and critically reviewed and revised

the manuscript; Dr Holmes conceptualized and

designed the study, participated in development of

data collection instruments, and drafted the initial

manuscript; Dr Balkian, Ms Paradis, and Ms Sparr-

Perkins conceptualized and designed the study,

participated in data collection, and drafted the

initial manuscript; Ms Weber conceptualized and

designed the study, participated in development of

data collection instruments, participated in data

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focused on the adult population.

Examples of these projects include

the Better Outcomes for Older Adults

Through Safe Transitions Project,

sponsored by the Society for Hospital

Medicine; Project Re-Engineered

Discharge, sponsored by the Agency

for Healthcare Research and Quality,

National Heart, Lung and Blood

Institute, Blue Cross Blue Shield

Foundation, and the Patient-Centered

Outcomes Research Institute; and

the State Action on Avoidable

Rehospitalizations initiative of

the Commonwealth Fund and the

Institute for Healthcare Improvement

(IHI). All these projects recommend

strategies to improve the discharge

process, including scheduling

follow-up appointments before

discharge, medication plans, written

patient discharge instructions,

patient education about diagnosis

and medications, follow-up telephone

calls to the patient, communication

to the outpatient primary provider

at discharge, and others. 8 – 11 Recently

White et al12 improved discharge

efficiency in a children’s hospital by

creating a common set of discharge

goals for 11 different pediatric

diseases. Although this intervention

did decrease the length of stay, the

readmission rate was not changed.

To date, the only published pediatric

discharge improvement collaborative

focused on improving communication

to primary care providers after

hospital discharge. 13

About 20% of older Medicare

patients who are hospitalized are

readmitted to the hospital within 30

days after discharge. 14 Because of

the high cost of readmissions, adult

hospitals with high readmission rates

receive reduced Medicare payments

under the Affordable Care Act. 15

Reimbursement rate penalties for

Medicaid patients, including children,

are already being implemented

in some states. In an analysis of

>550 000 pediatric admissions in 72

hospitals, Berry et al 16 found that the

30-day unplanned readmission rate

in pediatric patients was 6.5%, which

is much lower than in adults. Recent

publications have reported that most

children who were readmitted had an

underlying chronic disease, and only

a small percentage of readmissions

were found to be preventable. 17, 18

Interestingly, 1 study suggested that

children who had a documented

follow-up scheduled with their

primary care provider were more

likely to be readmitted to the hospital

than those who did not. 19

Because of the potential for errors

and variability in the discharge

process, Children’s Hospital

Association (CHA) formed the first

pediatric improvement collaborative

to examine whether shared

improvement strategies would affect

discharge-related care failures,

parent-reported readiness for

discharge, and readmission.

METHODS

Setting

The CHA invited its members

to participate in a multicenter

collaborative project addressing

the discharge process for pediatric

inpatients. Eleven hospitals

participated in the collaborative.

One hospital did not submit data

on interventions and therefore was

excluded from analysis. All hospitals

were tertiary-care freestanding

children’s hospitals in the United

States that were members of the

CHA. A specified target population

was selected at the discretion of

the participating site ( Table 1). The

participants selected populations by

specific disease processes, level of

clinical complexity, or specific units

in the hospital.

Intervention

The study was patterned after the

standard methods used by the CHA

in many of its other collaborative

projects. 20 –24 The model for this

improvement process was based

on previous work developed by

the IHI and has been used

successfully in pediatric settings. 25 –29

A multidisciplinary advisory panel

of experts with previous experience

in discharge processes was recruited

from across the CHA. The panel

evaluated the existing literature

and adopted tools and change

concepts from previous discharge

programs. 2, 3, 8 – 11, 30 They also

incorporated lessons learned

e2

TABLE 1 Participating Hospitals and Areas of Project Focus

Site Target Patient Population

Nationwide Children’s Hospital, Columbus, OH Patients with sickle cell disease readmitted within

30 d for acute chest pain or pain crisis

Children’s Hospital Colorado, Aurora, CO Patients with asthma and seizure managed by

hospitalists

Riley Hospital for Children at Indiana University

Health, Indianapolis, IN

Unit-based patients on 7W managed by

hospitalists, complex care patients on 8E

Children’s Hospital Los Angeles, Los Angeles, CA Medical/surgical unit, cystic fi brosis admissions

and cardiovascular acute unit

New York–Presbyterian Morgan Stanley Children’s

Hospital, New York, NY

NICU and oncology–bone marrow transplant

Children’s Hospital & Medical Center, Omaha, NE Nonchronic patients on medical/surgical unit

Children’s Hospital of Pittsburgh of UPMC,

Pittsburgh, PA

Patients scheduled for discharge on medical and

surgical unit

The Children’s Hospital of Philadelphia, Philadelphia,

PA

All patients scheduled for discharge

Rady Children’s Hospital San Diego, San Diego, CA Patients with asthma on medical unit,

appendectomy on surgical unit, cardiac surgery

in critical care unit, all patients on hematology/

oncology, and all patients in NICU

Children’s National Medical Center, Washington, DC Medical patients managed by resident trainees

and hospitalists

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PEDIATRICS Volume 138 , number 2 , August 2016

from previous CHA collaboratives,

including the “Improving Inpatient

Throughput” and “Improving Patient

Handoffs” programs. 20 This panel

developed a change package covering

6 broad areas, which included the

following strategies:

• Proactive discharge planning

throughout the hospitalization.

• Improve throughput.

• Arrange postdischarge treatment.

• Communicate postdischarge plan

to providers.

• Communicate postdischarge plan

to patients and families.

• Postdischarge support.

Sites formed multidisciplinary

teams and were required to

have an executive-level sponsor.

The collaborative held 4 virtual

learning sessions and monthly Web

conferences. In between the learning

sessions were 3 action periods,

during which each site performed

small tests of change using the plan–

do–study–act method. During the

learning sessions, training on quality

improvement methods was provided

by national experts. High performers

also shared their successes, and

participants were given opportunities

to ask questions. Sites also presented

their progress and challenges during

monthly Web conferences. Teams

could communicate with each other

and share tools and resources via

an electronic mailing list and a

shared Web site. Teams were guided

through improvement efforts by an

experienced improvement coach.

Measures and Data Collection

The primary aim of the study was

to reduce discharge-related care

failures by 50% in 12 months.

Discharge-related care failures were

measured by using phone calls to

families 2 to 7 days after discharge.

Failure was a composite all-or-none

measure; if any problem related to

discharge occurred, the discharge

was counted as a failure. Required

components of the measure included

understanding of diagnosis, receiving

discharge instructions, receiving

discharge education, compliance

with instructions, receiving

necessary equipment, having a

plan to follow up pending tests,

receiving help with appointments,

and not needing a related unplanned

visit. A discharge phone call script

adapted by the expert panel from

Project Re-Engineered Discharge

was provided, and each site was

permitted to modify the script to

meet their local needs and capacity. 10

All other measures were

optional and selected by the

individual sites depending on

the change strategies targeted

(see Supplemental Information

and Supplemental Tables 1–6 for

definition of measures). Readiness

for discharge and readmission

rates were priority measures

and were highly recommended

although not required. Patient

and family readiness for discharge

was defined as the percentage of

families rating the highest category

on the hospital’s standard patient

satisfaction survey. Readmission at

72 hours and 30 days was defined

as unplanned rehospitalization for

the same diagnosis. Baseline data

were collected from August through

October 2011 if available. If baseline

data were not available (eg, outreach

calls), the first 3 months of project

data were used as baseline. From

November 2011 to October 2012,

the hospitals participated by using

Deming’s plan–do–study–act cycles to

perform tests of change, implement

improvements, and sustain results.

Each site selected changes based

on local capabilities and priorities.

Standardized reporting of data

occurred on a monthly basis via an

electronic data repository managed

by The CHA and did not include

any patient identifiers. Monthly

reports also included a narrative

section that included information

on successes, challenges, and next

steps. In addition to collecting project

measures, CHA staff scored each

site based on improvement activity

and performance by using the IHI

Assessment Scale for Collaboratives.

The scale rates teams between 0.5

and 5.0, with 0.5 defined as being

signed up to participate and 5.0

demonstrating major change in all

areas, outcome measures at national

benchmark levels, and spread under

way. (See Supplemental Table 7 for

rating scale.) 31

Data Analysis

Measures were plotted on run charts

(Minitab version 17.1, State College,

PA), with the first 3 months of data

reported used as baseline. Only

months where ≥3 sites reported

data were included. Run charts were

interpreted according to standard

probability-based rules for α level

P < .05. 32, 33 Data for both individual

hospital and overall hospital were

also aggregated to the quarterly level

for analysis in SAS version 9.3 (SAS

Institute, Inc, Cary, NC). Comparisons

between the entire baseline period

and postbaseline values for the

aggregated hospital data were

made with χ2 tests. Within each

quarter, first observation carried

forward or last observation carried

back imputation was conducted for

missing data in SAS.

This study was determined to be

exempt by the Children’s Hospital Los

Angeles Institutional Review Board

(CHLA-14-00111).

RESULTS

Elements of the collaborative change

package were adopted by each

institution at varying levels ( Table 2).

All sites chose to work on educating

families on diagnosis and plans for

discharge. Several sites also used

discharge checklists, with discharge

milestones and barriers. Eight out

of 10 sites improved the written

discharge instructions given to

families. Some of these improvements

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included designing standardized

discharge instructions for certain

diagnoses, making instructions more

user-friendly, and creating new

discharge instruction forms in the

electronic medical record. Almost all

sites (9 of 10) used postdischarge

follow-up phone calls to reinforce

discharge instructions. Most sites also

reported working on identifying and

obtaining discharge medications. Few

sites addressed communication with

primary care providers.

Aggregate data for all hospitals

combined are depicted in monthly

run charts. Run charts with individual

hospital trends are available online

(Supplemental Figures 4–8).

Eight hospitals reported rates of

discharge-related care failures.

Because precollaborative data

were not available at most sites,

the first quarter of the project was

used as baseline data. The run

chart demonstrated a shift, with 10

consecutive points below the baseline

median line (Supplemental Figure 4).

The statistical process control chart

( Fig 1B) also confirms this finding,

with 9 postintervention points below

the baseline mean and the final

postintervention point below the

lower control limit. The aggregate

rate of care failures was overall 34%

in the first project quarter; the rate at

the end of the collaborative was 21%,

or a reduction of 40% (P < .05). Top-

performing hospitals were able to

achieve even lower care failure rates

with the use of varying interventions

( Fig 1B).

Only 4 hospitals reported data on

family feeling ready for discharge

( Fig 2). For these hospitals, there

was a statistically significant

increase in the percentage of

patients who rated the readiness for

discharge in the highest category.

The precollaborative baseline was

85% of patients giving the highest

rating; during the last quarter of the

collaborative it was 91% (P < .05).

The run chart showed a shift of 6

points above the median line in the

last 2 quarters.

Five hospitals reported unplanned

readmission rates for the same

diagnosis, at 72 hours ( Fig 3A) and

at 30 days ( Fig 3B). Four hospitals

reported both rates. There was no

improvement in unplanned 72-hour

(0.7% vs 1.1%, P = .29) and slight

worsening of the 30-day readmission

rate (4.5% vs 6.3%, P = .05).

Of the 11 participating sites, 4

achieved an IHI Assessment Scale

for Collaboratives score of 5.0

at the end of the collaborative

(Hospitals A, B, C, D), indicating

outstanding improvement. One site

obtained a score of 4.5 (sustainable

improvement, Hospital E), and 4

sites achieved a 4.0 (significant

improvement, Hospitals F, G, H, I).

Two sites were able to test

changes but did not demonstrate

measurable improvement. Common

characteristics of the sites that

achieved a score of 5.0 included

strong multidisciplinary involvement;

close collaboration with electronic

medical record (EMR) teams;

dedicated staff time for discharge

phone calls, discharge education,

and discharge rounding; and use of

discharge checklists.

e4

TABLE 2 Change Strategies Used by Participating Sites

Change Strategy Change Ideas Number of Sites Using Strategy

Proactive discharge planning throughout

hospitalization.

Educate the patient and family about diagnosis and plans for discharge. 10

Include discharge planning in rounds and other staff communication. 7

Establish and continuously update anticipated discharge date and time. 4

Ensure fi nancial problems will not impede discharge. 3

Improve throughput. Complete the discharge process promptly. 7

Create specifi c conditional or contingency discharge orders. 7

Proactively prevent and manage delays. 5

Work with essential partners (eg, laboratory, radiology, social work). 4

Spread discharges across the day. 3

Arrange for postdischarge treatment. Identify the correct medicines and a plan to obtain and take them. 9

Make appointments for follow-up medical appointments and postdischarge

tests.

7

Organize postdischarge home-based services and medical equipment. 6

Plan for the follow-up of results from laboratory tests or studies that are

pending at discharge.

3

Anticipate planned readmissions for additional treatment (eg, chemotherapy

treatments).

2

Communicate postdischarge plans to

providers.

Transmit discharge summary to clinicians accepting care of the patient. 5

Develop physician discharge summary for next providers. 4

Initiate verbal communication with outpatient caregivers as needed. 2

Communicate postdischarge plans to

patients and families.

Create or improve written discharge instructions for the patient and family. 8

Review the written discharge instructions with the patient and family. 6

Review with the patient and family what to do if a problem arises. 6

Postdischarge support. Provide telephone reinforcement of the discharge plan via outreach calls. 9

Provide opportunities for patients and families to ask questions after

discharge.

4

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PEDIATRICS Volume 138 , number 2 , August 2016

DISCUSSION

Adverse events related to poor

hospital discharge planning are well

described, 34 and to our knowledge

this is the first multicenter

collaborative to target the hospital

discharge process for pediatric

inpatients. Because the discharge

process is complex, involving

multiple clinical microsystems,

achieving large-scale change is

particularly challenging. Although the

collaborative did not meet its target

of 50% reduction in care failures,

significant progress was made. We

found a decrease in discharge care

failures and improvement in patient

readiness for discharge. However,

there was no impact on 72-hour

unplanned readmissions and even

a slight increase in the 30-day

readmission rate.

A wide variety of change strategies

were adopted by the participating

sites to achieve results. One of the

most commonly adopted strategies

was proactive discharge planning

throughout the hospitalization.

Several change ideas were used to

accomplish this planning, such as

educating the patient and family

about diagnosis and plans for

discharge, including discharge

planning in rounds, establishing and

continuously updating anticipated

discharge time, and ensuring that

financial problems did not impede

discharge. Other key change areas

were improving communication

of postdischarge plans to families

and providing postdischarge

support via outreach phone calls.

Previous studies have shown that

postdischarge contacts via home

visits or follow-up phone calls were

effective in decreasing health care

utilization and improving satisfaction

with care. 35 – 38 Although most sites

made postdischarge phone calls

during the collaborative period, not

all were able to continue doing so.

The standardized phone call script

used during the collaborative could

take <5 minutes to 20 minutes,

depending on the patient. If

interpretation was needed, the call

could take even longer. Some sites

found this script unworkable and

shortened it significantly. Follow-up

studies must be done to evaluate

the cost and benefit of phone calls to

support their sustainability. Few sites

e5

FIGURE 1Discharge-related care failures (n = 8 sites reporting; 5895 discharges). Percentage of discharges where ≥1 discharge-related care failure was identifi ed during postdischarge phone call. First 3 months of available data used as baseline. A, Statistical process control p-chart. B, Annotated run chart, top-performing hospitals. Horizontal line represents the hospital’s baseline from the fi rst 3 months of data collection. LCL, lower confi dence level (3 standard deviations below the mean); NP, nurse practitioner; RN, registered nurse; UCL, upper confi dence level (3 standard deviations above the mean).

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chose to implement interventions

related to communication and

coordination with outpatient

primary care physicians. Future

efforts focused on this strategy may

demonstrate more improvements in

discharge-related outcomes.

Despite improvements in discharge-

related outcome measures, there

was no improvement in readmission

rates during the collaborative. In

fact, we saw a slight increase in

30-day unplanned readmissions.

This could result from seasonal

variability in readmissions. Also,

readmission rates vary by diagnosis,

leading to high variability in this

measure. For example, 1 site focused

on management of patients with

sickle cell disease, who have 30-day

readmission rates between 10%

and 20%, and another site focused

on patients with asthma, with much

lower readmission rates of <2%. 39 – 41

Also, our method was able to assess

only revisits to the same facility. 42

Another possibility is that improving

throughput and discharge timeliness

led to earlier discharge, with the

unintended consequence of

increased readmission; however,

we did not collect data on length

of stay. There is also significant

variability in the definition

of readmissions. We defined

readmissions as unplanned

readmissions for the same condition;

however, even within these

parameters, each site used different

methods to collect the

data. Even unplanned readmission

may be unavoidable and therefore

an insensitive measure for discharge

quality. The 3M Potentially

Preventable Readmissions algorithm

is a promising tool that can be

used in future improvement

efforts, but it has not yet been

prospectively evaluated and may

still overestimate preventability.43

Average unplanned readmission

rates were very low in the population

studied: <1% for 3 days and 5% for

30 days. This finding adds to recent

evidence that readmissions may

not be a good indicator of hospital

quality in the pediatric setting. 44

Readmission rates are not solely an

indicator of discharge quality; they

are a measure of the entire health

system, as well as socioeconomic

factors and patient disease. 38, 45, 46

There is also no consensus on the

optimal readmission interval. The

Centers for Medicare and Medicaid

Services uses 30 days for adult

readmissions measures; however,

some studies have used 7, 14, or

15 days. Future studies should

establish standardized frameworks

and measures for evaluating

discharge care quality.47, 48

The limitations of this collaborative

are consistent with other initiatives

to improve care across multiple

sites. 49, 50 First, the participating sites

were all tertiary-care freestanding

children’s hospitals, so the results

may not be generalizable to

community hospitals or pediatric

care provided in general hospitals.

Second, we were not able to measure

the impact of specific change

strategies, because each site chose

different targets and implemented

a bundle of several strategies

simultaneously. Randomization

of the interventions across

sites would have increased our

ability to draw conclusions about

the effectiveness of individual

interventions but would not

have allowed sites to choose the

strategies most relevant to their

populations and feasible in their

local environments. Third, for most

measures sites did not have baseline

data before implementing changes.

In addition, charts had only 11 to 15

data points, with the first 3 points

serving as baseline, leaving only

8 to 12 postintervention points.

Therefore, we had insufficient points

to accurately calculate control limits.

Also, because prestudy baseline

data were not available for most

measures, it is possible that the teams

may have made early improvements

that were not reflected in the

data. This discrepancy is likely

to underestimate the true effect

of the project. Nearly every site

had difficulty obtaining data, and

some sites were ultimately not

able to submit data on some of the

measures. Hospitals need better data

systems and analytic resources to

e6

FIGURE 2Proportion of families who felt ready for discharge (n = 4 sites reporting; 2824 discharges). Percentage of families giving the highest rating of readiness for discharge on hospital patient satisfaction surveys.

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PEDIATRICS Volume 138 , number 2 , August 2016

more effectively plan and monitor

progress of quality improvement

work. Finally, each site used different

patient populations and different

tools to collect data, making the

data heterogeneous and difficult to

compare.

Participating sites reported several

benefits of the collaborative model

that were consistent with previous

studies. 51, 52 Teams enjoyed the

opportunity to learn from national

experts, share challenges and

successes, learn and adapt from

different settings and patient

populations, and share tools such

as checklists and call scripts.

The collaborative approach also

helped sites develop urgency for

change at the institutional level

and fostered friendly competition

and accountability. Teams were

also able to leverage collaborative

participation to secure financial

resources and staff time. Several

innovations were also developed

and tested during the collaborative

period and made available to

others. Some examples include

sickle cell action plans, seizure

actions plans, a “discharge lounge, ”

whiteboards in patient rooms

with home schedules, and peer

mentoring programs. Although

teams cited difficulties in making

timely modifications in the EMR,

many sites shared the same EMR

platform and were able to exchange

technical assistance and screen

shots of changes made such as

automated discharge readiness

reports, conditional discharge

order sets, and standardized

discharge instructions.

CONCLUSIONS

This study shows the potential

benefit of the collaborative

approach to improve quality of

inpatient discharges by using an

intervention bundle implemented

in pediatric hospital settings. The

spread of such interventions has the

potential to improve care transition

outcomes for all hospitalized

children.

ACKNOWLEDGMENTS

Expert panel members: Lori

Armstrong, MSN, RN, NEA-BC; Mary

Daymont, RN, MSN, CCM, CPUR;

Pamela Kiessling, RN, MSN; Cheryl

Missildine, RN, MSN, NEA-BC; Karen

Tucker, MSN, RN. Data analysis: Cary

Thurm, PhD, Children’s Hospital

Association.

ABBREVIATIONS

CHA:  Children’s Hospital

Association

EMR:  electronic medical record

IHI:  Institute for Healthcare

Improvement

e7

FIGURE 3Unplanned readmission for the same condition. A, Within 72 hours; B, within 30 days (n = 5 sites reporting; 7654 discharges).

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collection, assisted with data analysis, drafted the initial manuscript, and critically reviewed and revised the manuscript; and all authors approved the fi nal

manuscript as submitted.

DOI: 10.1542/peds.2014-3604

Accepted for publication Mar 14, 2016

Address correspondence to Susan Wu, MD, Division of Hospital Medicine, Department of Pediatrics, Children’s Hospital Los Angeles, 4650 Sunset Blvd, Los Angeles,

CA 90027. E-mail: suwu@chla.usc.edu

PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).

Copyright © 2016 by the American Academy of Pediatrics

FINANCIAL DISCLOSURE: The authors have indicated they have no fi nancial relationships relevant to this article to disclose.

FUNDING: Funding for the collaborative was provided by the Children’s Hospital Association and participating member hospitals.

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential confl icts of interest to disclose.

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