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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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
Small multiple tables
Small multiple tables
Small multiples tables