Variation in interstage weight gain among surgical centers in single ventricle infants:

Identification of strategies to improve growth

Jeffrey B. Anderson, MD MPHThe Heart Institute

Cincinnati Children’s Hospital Medical Center

Introduction

• Harvey Hamrick, MD

Introduction

• Pediatric Academic Society 2006

Competition has been shown to be useful up to a certain point and no further, but cooperation,

which is the thing we must strive for today, begins where competition leaves off.

~ Franklin D. Roosevelt

Outline

• Definition of rare diseases

• Cooperation to understand these patients

• Specific example of how this works

• Call to arms for working together

Introduction

• Chronic kidney disease requiring dialysis ~5,600 • Duchene Muscular Dystrophy ~15,000• Cystic fibrosis ~ 30,000• Complex congenital heart disease ~ 180,000 and rising• Most of the patients we care for fall under the classification of

rare disease

Where can we find solutions?

• Traditional clinical research limited by small numbers• We often rely on the findings from case reports or

case series to guide our management decisions• Because of the rarity of many complex pediatric

problems it is difficult for any one center to see enough cases to adequately study and determine best care

• Organized systems of care help alleviate this problem

What is an organized system?

Organized systems of care are groups that allow for collaborative, integrated care among a

group of caregivers who are accountable for the quality, cost and overall care of a defined

population of patients.

Collaborative Care and Improvement

Organized systems of care that have resulted in profound patient improvements: • Children’s Oncology Group• Northern New England Cardiovascular Group• End Stage Renal Disease Network• Neonatology (Vermont Oxford Network, California Perinatal

Quality Care Collaborative, others)• National Health Services primary care collaborative• Cystic Fibrosis Collaborative• NACHRI Catheter Related Blood Stream Infections Collaborative

10

Models for Collaborative Improvement• Successful system models of improving care have common

features:– Multicenter shared data collection with transparency – Multidisciplinary involvement, including patients and

parents– Definition and implementation of standardized care

practices– Systems to support sharing evidence/knowledge– Collaborative learning across practice sites

Acute Lymphoblastic Leukemia

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Simone J., Lyons, J: J Clin Oncology 1998 Sep;16(9):2904-5

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It is instructive to learn that the cure rate forchildhood acute lymphoblastic leukemia rose from about 40% in the early-1970’s to about 70% in the mid-1990’s without a single new frontline therapeutic agent. In leukemia and other cancers, improvements came largely from trial-and-error adjustments of therapeutic dosages and schedules made possible by the large pool of patients participating in clinical trials.

Joseph Simone, MDChildren’s Oncology GroupIn report to Institute of Medicine

Where are we in cardiology?

Diffusion of Innovations, 1962, Everett Rogers

Area under the curverepresents number ofpractitioners usingInnovation.

How do Cardiologists make decisions?

• 10 pediatric cardiologists• Reasons for every clinical decision• Variety of clinical situations

Darst et al. Cong Heart Dis. 2011

How do we make medical decisions?

• Experience/anecdote 37.1%• Arbitrary/Instinct 14.7%• Trained to do it 14.6%• General study 12.3%• First principles/physiology 12.3%• Limited study 5.1%• Specific study 2.9%• Parenteral preference 0.5%• For research 0.3%• Avoid a lawsuit 0.2%Darst et al. Cong Heart Dis. 2011

How do we do this better?

Background: Hypoplastic left heart syndrome

Palliative surgical procedures

Norwood procedure Fontan completionBidirectional Glenn

INTERSTAGE

Background• Infants with a single ventricle have poor growth

prior to their bidirectional Glenn procedure (Stage 2)

• Lower preoperative weight-for-age z-score is associated with increased hospital length of stay following BDG procedure

Anderson, JACC 2008; 51(10 Suppl A): A83-97

Results: Weight distribution (n=100)

0

10

20

30

40

50

-3 -2 -1 z=0 +1 +2 +3 +4

Weight z-scores at BirthN

umbe

r of p

atien

tsMean -0.2

0

10

20

30

40

50

-3 -2 -1 z=0 +1 +2 +3 +4

Weight z-scores at BDG

Num

ber o

f pati

ents

Mean -1.3

Growth of the NPC-QIC

NPC-QIC Participating Sites

Children’s Hospital and Research Center, Omaha

Mayo Clinic, Rochester

Primary Children’s Medical Center

Arizona Pediatric Cardiology Consultants

Monroe Carrell Jr. Children’s Hospital

at Vanderbilt

Seattle Children’s Hospital

Doernbecher Children’s Hospital

UC Davis Children’s Hospital

Children’s Hospital and Research Center, Oakland

Lucile S. Packard Children’s Hospital at Stanford

Mattel Children’s Hospital UCLA

Children’s Hospital, Los Angeles

Methodist Children’s Hospital

CHRISTUS Santa Rosa Children's Hospital

Children’s Medical Center Dallas

Texas Children’s Hospital All Children’s

Hospital

Miami Children’s Hospital

Arnold Palmer Children’s Hospital

Children’s Healthcare of Atlanta

Medical University of South Carolina

Duke University Medical Center

University of Virginia Children’s Hospital

CHOP

Johns Hopkins

University of MarylandInova Fairfax

Children’s Hospital Boston

Montefiore

Yale New Haven Children’s Hospital

Children’s National

NYU Cohen Children’s

Penn State Hershey Children’s

Cleveland Clinic

Nationwide

University of Chicago Comer Children’s Hospital

Children’s Memorial

Children’s Hospital Wisconsin

Advocate Hope

Riley Children’s Hospital

Children’s Hospital - Denver

Cincinnati Children’s Hospital Medical Center

University of

Louisville

Arkansas Children’s Hospital

St. Louis

Children’s

Hospital

Levine Children’s Hospital

Le Bonheur Children's Hospital

Purpose

• Identify variation in growth outcomes among NPC-QIC centers

• Identify nutritional practices that are associated with better interstage growth

• Use this evidence to spread these practices to institutions within the collaborative

Methods

• Retrospective analysis of patients in the NPC-QIC registry – Inclusion:

• Patients who had presented for stage 2 (S2) surgical repair• From centers who had enrolled > 4 patients who had

presented for S2

Methods: Nutritional processes

• Registry information regarding nutritional practices

• Blinded structured interviews to gain more detailed information– Designed and reviewed by

• Cardiologist• Two separate registered dieticians• Epidemiologist with survey expertise

Methods: Outcomes

• Primary outcome – Change in weight-for-age z-score (WAZ) between

discharge following neonatal Norwood (S1) and presentation for Bidirectional Glenn (S2), ie during the interstage

Analysis

• Variation in WAZ among centers was identified

• Centers with a median increase in WAZ were selected

• Nutritional processes were identified that were associated with an increase in WAZ between S1 and S2

Results: patient characteristics (n=132)

Characteristic n (percentage) Median (range) Male gender 84 (64%) Race White African-American Native American Other

93 (70%) 16 (12%) 2 (1.5%) 21 (16%)

Gestational age (weeks) 39 (32 to 41) Birth WAZ -0.5 (-2.5 to 3.3) Age at stage 1 palliation (days) 5 (1 to 54) Stage 1 hospital length of stay (days) 31 (9-126) Stage 1 discharge WAZ -0.9 (-4.4 to 2.5) Age at stage 2 palliation (months) 5.0 (2.6 to 12.6) Stage 2 WAZ -1.1 (-4.2 to 1.3)

Results: variation among centers

Results• Nutritional processes common to centers with a

positive median WAZ change– use of home scales for interstage weight monitoring – specific weight gain/loss “red flags” to identify patients

with growth failure in the interstage period – regular phone contact with families during the

interstage period regarding nutrition and growth – dietitian available for each cardiology outpatient visit

during the interstage period– standard post-Norwood feeding evaluation

Conclusions

• There is considerable variation in growth of infants with HLHS among sites caring for these infants

• There are specific nutritional practices used at centers with better infant growth

• A combination of these “best practices” is associated with an effective increase in weight for age z-score of 0.98

What next??

• Prospectively implement these best nutrition practices

• Next week, at the NPC-QIC fall learning session, we will begin enrolling centers who commit to implement these nutritional practices and follow their patient’s growth over time

Strengths and Limitations

• This type of work could not be done by a single individual or institution

• We learn incrementally more as we share methods and experiences among centers

• This specific work is limited by the data we gather• Yet to be determined whether these findings are

generalizable beyond the very small number of infants with a single ventricle

Conclusions

• Infants and children have rare diseases• Individuals and even individual institutions do

not care for enough patients to allow for adequate understanding of disease processes or treatment effectiveness

• Collaboratives/Registries a powerful tool to moving forward in our understanding of these rare problems.

Incentives to participate in collaboration

• Allow unique approaches to problem solving• Exposure to different ways to treat patients• ABP stance on collaborative work

– The American Board of Pediatrics (ABP) was created to advance the science, study, and practice of pediatrics by a series of credentialing and certifying activities. Requirements for maintenance of certification now emphasize assessing quality of care and demonstrating systematic improvement of care for children

Character is like a tree and reputation like its shadow. The shadow is what we think of

it; the tree is the real thing.

~Abraham Lincoln

Cincinnati, the Queen City

Results: Daily weight gain (n=100)Average daily weight gain, birth to BDG

0

5

10

15

20

25

30

Individual patients

Gra

ms

per d

ay

Median 16.4 g/day

CDC recommendation

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