Providing the Best Quality Care for Children
Medical/Dental Homes and Networks of CareTexas Medicaid Meeting
Austin, TXNovember 26, 2007
Paul V. Miles, MD, FAAPVice President, Director of Quality and Practice Assessment
American Board of Pediatrics
What do we mean by : “Best Quality?”
• Quality = Best science + Context (what the patient wants and needs)
• Quality = the gap between what we deliver and what we could deliver
• IOM six dimensions of quality: safe, timely, effective, efficient, equitable, patient centered
Quality: What our patients see
• 54% of the time adults receive recommended appropriate care (McGlynn)
• 46% of the time children receive recommended appropriate care (Mangione-Smith)
• There is a gap between knowing and doing (“every system is perfectly designed to give the results it gets”)
Pediatric Quality - Underuse
• Immunization rate 75%• Speech and language evaluation 66%• Adolescent health behavior <50%• Chlamydia screening 25%• Long acting asthma meds 75%• Similar problems with overuse and misuse
including patient safety
The Commonwealth Fund: Chart book 2004
Partnering with Pediatric Practices to Improve Asthma Care
Keith Mandel, MDVice President of Medical Affairs, Physician-Hospital Organization
Cincinnati Children’s Hospital Medical Center
Copyright © 2005 Cincinnati Children’s Hospital Medical Center; all rights reserved
“Perfect Care”: composite measure of severity classified, identified management plan, and controller medications for patients with persistent asthma
Copyright © 2005 Cincinnati Children’s Hospital Medical Center; all rights reserved
ImprovementCollaborative on
Reliability|q
PerformanceFeedback Reports
|q
P4PProgram
|q
qP4P
Deadline
zSelf -
ManagementCollaborative
Initiated
qWeb-based
RegistryLaunched
ProjectInception
|q
q"Perfect Care"
IncludingFlu Shot
Long Term Goal = 95%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Oct 0
3
Nov 0
3
Dec 0
3
Jan
04
Feb
04
Mar
04
Apr 0
4
May
04
Jun
04
Jul 0
4
Aug 0
4
Sep 0
4
Oct 0
4
Nov 0
4
Dec 0
4
Jan
05
Feb
05
Mar
05
Apr 0
5
May
05
Jun
05
Jul 0
5
Aug 0
5
Sep 0
5
Oct 0
5
Nov 0
5
OVPCA Network Practice 1 Practice 2 Practice 3 Practice 4 Practice 5 Practice 6
Cumulative % of Asthma Population with "Perfect Care": Network and Select Practices
13,000 children, 160 pediatricians in 44 practices
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%Oc
t 03
Nov 0
3
Dec 0
3
Jan 0
4
Feb 0
4
Mar 0
4
Apr 0
4
May 0
4
Jun 0
4
Jul 0
4
Aug 0
4
Sep 0
4
Oct 0
4
Nov 0
4
Dec 0
4
Jan 0
5
Feb 0
5
Mar 0
5
Apr 0
5
May 0
5
Jun 0
5
Jul 0
5
Aug 0
5
Sep 0
5
Oct 0
5
Commercially Insured Medicaid/Uninsured
Cumulative % of Asthma Population with "Perfect Care":Commercial vs. Medicaid/Uninsured
Copyright © 2005 Cincinnati Children’s Hospital Medical Center; all rights reserved
44% decrease in hospital admissions for asthma22% decrease in urgent care/ED visits30% decrease in missed school days
Models for Quality
• Successful sustained models of improving care have had common features:– Multicenter shared data collection– Standardization of care– Systems to support sharing evidence/knowledge– Collaborative learning across practice sites
• Complex pediatric problems occur relatively infrequently making it difficult for any one center to see enough cases to adequately study and determine best care
Improving Care for Children
• Interdisciplinary teams• Measure performance and share data
transparently• Work together across practice sites to improve
processes of care (participate in collaboratives such as VON, NACHRI BSI, CF, CPQCC
• Involve parents/patients• Use improvement science• Population based networks of Medical Homes• Commit to ongoing professional development• “every child treated is a child studied”
Shared Data and Collaborative Practice(institutional autonomy is a barrier)
Identified organized systems of care that have
resulted in profound improvements • Children’s Oncology Group• Northern New England Cardiovascular Group• End Stage Renal Disease Network• Neonatal efforts, (VON, CPQCC, others)• NHS primary care collaborative• Cystic Fibrosis Collaborative• NACHRI Catheter Related Blood Stream Infections • PIBDnet, Cardiology effort, IPIP
Why Prospective Multicenter Improvement Studies are Essential
• Small sample size• Problems with attribution• Difficulty adjusting for confounding factors• Trust and buy in from clinicians• Opportunity to learn from “best” practices
Acute Lymphoid Leukemia
0%
20%
40%
60%
80%
100%
1960-63 70-73 74-76 77-79 80-82 83-90
Simone J., Lyons, J: J Clin Oncology 1998 Sep;16(9):2904-5
5 ye
ar s
urv
ival
rat
e
Eliminating Bloodstream Infections
In the first 6 months, 29 children’s hospitalsreduced infection ratesin the PICU by nearly70 percent by adhering to a rigid set of evidence-based practices shown to prevent infections in children.
Monthly Aggregate PICU CA-BSI Rate
0
1
2
3
4
5
6
7
8
01/0
4 n=
23
02/0
4 n=
23
03/0
4 n=
23
04/0
4 n=
25
05/0
4 n=
23
06/0
4 n=
25
07/0
4 n=
27
08/0
4 n=
27
09/0
4 n=
27
10/0
4 n=
27
11/0
4 n=
26
12/0
4 n=
26
01/0
5 n=
27
02/0
5 n=
27
03/0
5 n=
28
04/0
5 n=
28
05/0
5 n=
28
06/0
5 n=
28
07/0
5 n=
28
08/0
5 n=
28
09/0
5 n=
28
10/0
5 n=
28
11/0
5 n=
28
12/0
5 n=
28
01/0
6 n=
29
02/0
6 n=
29
03/0
6 n=
29
04/0
6 n=
27
05/0
6 n=
27
06/0
6 n=
27
07/0
6 n=
23
08/0
6 n=
22
09/0
6 n=
22
10/0
6 n=
29
11/0
6 n=
29
12/0
6 n=
29
01/0
7 n=
28
02/0
7 n=
28
03/0
7 n=
28
04/0
7 n=
28
BS
I R
ate
pe
r 1,
00
0 L
ine
Da
ys
Monthly BSI Rate Center Line Control Limits
Notes:1) Prior to October 2006, the aggregate monthly collaborative rate is the average of the rates from all PICUs due to unavailability of line days data. Beginning in October 2006 the aggregate rate is calculated by dividing the total number of infections for the entire collaborative by the total number of line days.2) Begining November 2006 control limits have been recalculated to illustrate the apparent change in the process of care. The new control limits are variable, taking into account the number of line days for each month (u-chart) while the previous control limits were constant, only taking into account the change in average BSI rate from month to month (XmR chart)
BSI Collaborative Began Oct 2006
70% improvement: estimated 20 lives saved, 160 infections prevented, $6.4 million not spent in the first 6 months
For comparison, the US cystic fibrosis Foundation Registry survival curve for 1998 shows median survival of 32 years of age and our median survival is 46 years of age.
CF Foundation/NCHQ Collaborative
CYSTIC FIBROSIS
Univ. Minnesota Survival Data
Pediatric Pulmonology (Cystic Fibrosis)Median FEV1 CF Patients 6-12 yrs
0
20
40
60
80
100
Per
cent
Pre
dict
ed
All Care Centers Your Center National Average
40
50
60
70
80
90
100
2000 2001 2002 2003 2004
Per
cent
Pre
dict
ed
Ten Highest Centers University of Cincinnati
CFF National Patient Registry, 2004*Wang & Hankinson equations
CCHMC
Vermont Oxford Neonatal Network
Jeff Horbar Standard for Part 4
Infections
Lung function
Medical errors
Nutrition
Jaundice
HIV prevention
Resuscitation
Retinopathy
NICU Quality Improvement
Neonatal Improvement
Percent of Patients Meeting the NKF-DOQI Target Urea Reduction Ratio of 65%
figure 4.25, prevalent hemodialysis patients, 1999, by HSAfigure 4.25, prevalent hemodialysis patients, 1999, by HSA
Percent of patients
91.2 + (93.1)89.2 to 91.287.1 to 89.283.6 to 87.1below 83.6 (81.0)
USRDS Atlas
Quality of Care (ESRD)
0
5
10
15
20
25
30
35
<50% 50-54% 55-59% 60-64% 65-69% 70-74% 75-79% 80+%
Urea Reduction Ratio (URR)
perc
ent
of p
atie
nts
Oct-Dec '93Oct-Dec '94Oct-Dec '95Oct-Dec '96Oct-Dec '97
Average URR1993: 62.7%1994: 63.8% 1995: 65.5%1996: 66.8%1997: 68.0%
* Sixteen Network areas participated in the first ESRD Core Indicators assessment (Oct-Dec 1993); all Networkareas participated in subsequent years.
Adequacy of HemodialysisHemodialysis Dose by Race
4653
6270 73 76
85 87
3643
5463
69 70
83 84
0
20
40
60
80
100
1993 1994 1995 1996 1997 1998 1999 2000Ade
quat
e H
emod
ialy
sis
Dos
e, %
WhitesBlacks
Sehgal A, JAMA 2003;289:1996-1000Sehgal A, JAMA 2003;289:1996-1000
“the plural of anecdote is not data”
“the plural of data is not knowledge”
“measurement is not action”
Improving Care
Brent James Patient Safety Reporting Systems and Applications IOM
Looking for Bad Apples
Brent James Patient Safety Reporting Systems and Applications IOM
Improving Good Apples
“We take the data very seriously and I don’t know why we’re outside the normal range” Dr. Robert Schott, a cardiologist who is director of medical affairs for the Sutter Medical Center in Sacramento
“Isn't it amazing — 4,477 hospitals that treat heart attacks are all the same?" asks Richard Lange, chief of clinical cardiology at Johns Hopkins University.
“I think we just try very hard” said Dr. Herbert Pardes, NewYork-Presbyterian’s president and chief executive.
Report Rates Hospitals on Their Heart TreatmentBy GARDINER HARRISPublished: June 22, 2007
WASHINGTON, June 21 — The federal government has gingerly stepped back into rating the care delivered by the nation’s hospitals, releasing for the first time in nearly two decades a list of hospitals where heart patients are most likely to die.
Medicare and Hospital P4P
Maintenance of Certification (MOC) A New Approach to Standard Setting
• Looking for Bad Apples
(historic approach to physician quality)
• Helping Good Apples Improve (new ABP focus)1. Valid License
2. Lifelong commitment to learning
3. Demonstration of knowledge
4. Measure and improve quality of care
Health Care Quality
From “trust me, I am a physician, nurse, etc.” to “show me the data”
Care teams, (physicians included) have a professional obligation to measure and continually improve the quality of the care they deliver
And, they have a professional obligation to assess and continually improve their professional development
ABP and AAP related efforts
Primary Care:
• Asthma, ADHD, preventive services, Medical Home
Subspecialty Care
• Pediatric Inflammatory Bowel Disease – PIBDnet with NASPGHAN – research network then collaborative
• Pediatric Cardiology
• Efforts beginning in rheumatology, nephrology, hematology/oncology, infectious disease
• Participation in approved VON and CPQCC projects qualifies for credit for Part 4 of MOC
• CF, regional or local efforts
• Blood stream infections
1. Patient Safety
NACHRI Blood Stream Infection Collaborative (IP)
2. NeonatologyNational Collaborative (Vermont Oxford Network, California Perinatal Quality Care Collaborative, Pediatrix, State Coalitions)
3. Children with Special Needs (chronic care)
Tri-State Asthma Collaborative
Improving Performance in Practice (IPIP) (OP)
Other Asthma Improvement efforts
Cystic Fibrosis Foundation Collaborative (cross setting)
Improve First The Action Plan for Pediatric Quality
The Alliance for Pediatric Quality (AAP, ABP, NACHRI, CHCA)
Improving Care for Children
• Interdisciplinary teams• Measure performance and share data
transparently• Work together across practice sites to improve
processes of care (participate in collaboratives such as VON, NACHRI BSI, CF, CPQCC
• Involve parents/patients• Use improvement science• Population based networks of Medical Homes• Commit to ongoing professional development• “every child treated is a child studied”