art and science of medicine meets quality improvement · hp 2020 objective – 11.4 deaths per...

Elliott Main, MD Medical Director, CMQCC [email protected]

Clinical Professor, Depts of OB/GYN UCSF, and

Stanford University

Art and Science of Medicine

Meets Quality improvement

mailto:[email protected]

CPQCC and CMQCC

California Perinatal Quality Care Collaborative (CPQCC)

Multi-stakeholder organization established in 1996 (providers,

state agencies, public groups like MOD) Established Perinatal Data Center in 1996, works with VON

Data submission for VON “Plus” data system with 131 out of 136

NICUs with >17,000 annual admissions;

Over 10 quality toolkits and related collaboratives

Model of working with state agencies to provide data of value

California Maternal Quality Care Collaborative (CMQCC) Expertise in maternal data analysis, MMR (2006)

Developer of QI toolkits: Early Elective Delivery, OB Hemorrhage,

Preeclampsia, CVD in Pregnancy, and First Cesarean Prevention

Host of collaborative learning sessions

Established Maternal Data Center in 2011

CMQCC Key Partner/Stakeholders State Agencies:

MCAH, Dept Public Health

OSHPD Healthcare Information Division

Office of Vital Records (OVR)

Regional Perinatal Programs of California (RPPC)

DHCS, Medi-Cal

Public Groups

California Hospital Accountability and Reporting Taskforce (CHART)

California HealthCare Foundation

Kaiser Family Foundation

March of Dimes (MOD)

Professional groups

American College of Obstetrics and Gynecology (ACOG)

Association of Women’s Health, Obstetric and Neonatal Nurses (AWHONN)

American College of Nurse Midwives (ACNM),

American Academy of Family Physicians (AAFP)

Key Medical and Nursing Leaders

Universities and Hospital Systems

Kaisers, Sutter, Sharp, Dignity, Scripps, Providence, Public hospitals,

CMQCC Key Partner/Stakeholders (con’t)

Medical Associations:

California Hospital Association

Regional Hospital Associations

California Medical Association

Payers

Aetna

Anthem Blue Cross

Blue Shield

Cigna

Health Net

Purchasers

CALPERS (State and local government employees and retirees)

Medi-Cal (for managed care plans)

Pacific Business Group on Health/ Silicon Valley Employers Forum

Cover California (ACA entity)

Maternal Mortality

and Morbidity Reduction

Maternity Quality

Measures

Large-Scale

Implement-ation

CMQCC:

Major Areas

of Activity

Maternal Data

Center

5

: Transforming Maternity Care

12- Step Program for

Quality Improvement

1) Memory v. Data

2) Defenses

3) Burning Platform

4) External Measures

5) Variation

6) Autonomy

7) Translation

8) Pressures

9) Small Risks

10) Culture

11) Normalization

12) Just Do It…


1. Memory-Driven vs.

Data-Driven QI


Limitations of

Memory-guided Practice

Hard to remember beyond the last 10 cases and the last terrible outcome

No denominators, no sense of rates

Driven by anecdote and local custom

Advantages of

Data-driven Practice

Full knowledge of rates and outcomes, of yourself, your unit and the state

Not overly influenced by isolated cases

Driven by evidence-based medicine and basic standards

Elimination of Non-medically Indicated (Elective)

Deliveries Prior to 39 Weeks

Funding

Federal Title V block grant

from the California Department

of Public Health; Maternal,

Child and Adolescent Health

Division

California Maternal Quality

Care Collaborative

March of Dimes

Adverse Neonatal Outcomes According to Completed Week of Gestation at Delivery: Absolute Risk

Tita AT, et al, NEJM 2009;360:111

0%

2%

4%

6%

8%

10%

12%

14%

16%

Any adverse

outcome or death

Adverse

respiratory

outcome(overall)

RDS TTN Admission to

NICU

Newborn Sepsis

(suspected or

proven)

Pe

rce

nt

Aff

ect

ed

37+ Weeks

38+ Weeks

39+ Weeks

Adverse Neonatal Outcomes According to Completed Week of Gestation at Delivery: Odds Ratios

Tita AT, et al, NEJM 2009;360:111

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Any adverse

outcome or death

Adverse

respiratory

outcome(overall)

RDS TTN Admission to

NICU

Newborn Sepsis

(suspected or

proven)

Treated

hypoglycemia

Hospitalization >

5 days

Od

ds

Rat

ios

37+ Weeks

38+ Weeks

39+ Weeks

2010

2014

Na onalandCaliforniaReduc onofEarlyElec veDeliveries(EED)

0

5

10

15

2010(Baseline,MOD)

2011(Baseline,LFG)

2013(JointCommission)

2013(CMS)

2014(LeapFrogGroup)

MeanEEDRate

inCalifornia(%)

>75% Reduction

Nationally, CMS estimates an 80% reduction in EED

EED

Evidence

Data-driven QI

Public advocates

Prof Orgs (Natl and

Local) Public Policy

Performance measures

Public Reporting

Payment Incentives

EED Success: Collective Impact

70-80%

Reduction

Nationally!


2. Recognize the

Defenses


Self-Defense Manual

for

Medical

Professionals

1970, 1980, 1990, 2000, 2010….


Table of Contents: “The best defense is a good offense.”

Chapter One: Attack the Data

Chapter Two: Attack the Messenger

Chapter Three: Attack the Premise

When all else fails, there is always….

Chapter Four: “My Patients are

Higher Risk”


Appendix: Counter Strategies

Data: Clean carefully before presentation-

Be very certain about case attribution

Example: every obstetrician who covers

midwives or FP’s will have higher CS rates

Premise: Good to have backing of national

organization(s)

Risk Adjustment: simple strategies best-

Risk stratification v. logistic regression

Process measures do not need risk

adjustment!

CMQCC Maternal Data Center

Chart Review (select metrics/QI projects)

PDD—Discharge

Diagnosis File (ICD9/10 Codes)

Birth Certificate (Clinical Data)

Monthly uploads:

mother and infant PDD

(participating hospitals)

Monthly uploads:

electronic files for

all CA births

Automated Linkage

of all 3 files

Limited manual data

entry for these

measures Interactive Analytics

Guide QI Practice

Maternal

Data Center

Links over 1,000,000 mother/baby records each year!


3. Build the Burning

Platform

Kotter’s Eight Steps of Change


Maternal Mortality Rate California

Residents and United States: 1991-2006

10.7

9.7

8.5

5.6

9.1

6.7

7.7

10.9

14.6

11.7

8.3

13.3

9.1

7.7 9.7

10 11.7

16.9

8.47.6

7.17.57.9 7.8

7.1

9.9 9.8

8.9

9.9 12.1

13.1

15.1

0

2

4

6

8

10

12

14

16

18

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Ra

te p

er

10

0,0

00

Liv

e B

irth

s

0

10

20

30

40

50

60

70

80

90

100

Nu

mb

er

of

Ma

tern

al D

ea

ths

California Rate

United States Rate

HP2010 Objective

SOURCE: State of California, Department of Public Health, California Birth and Death Statistical Master Files, 1991-2006. Maternal mortality for California (deaths ≤ 42

days postpartum) calculated using ICD-9 cause of death classification (codes 630-638, 640-648, 650-676 ) for 1991-1998 and ICD-10 cause of death classification (codes

A34, O00-O95,O98-O99) for 1999-2006. United States data and HP2010 Objective were calculated using the same methods. The break in the trend line represents the

change from ICD-9 to ICD-10. Produced by California Department of Public Health, Maternal, Child and Adolescent Health Program, June 2009.

ICD-10 ICD-9

HP 2010 Objective – 4.3 Deaths per 100,000 Live Births

THE CALIFORNIA

PREGNANCY-ASSOCIATED MORTALITY REVIEW

Report from 2002-2003 Maternal Death Reviews

This project was supported by federal Title V block grant funds

received from the California Department of Public Health;

Center for Family Health;

Maternal, Child and Adolescent Health Division


Causes of Maternal Mortality and Morbidity

Cause Mort. ICU Serious

Morbid

VTE and AFE 10% 5% 2%

Infection 15% 10% 5%

Hemorrhage 15% 30% 45%

Preeclampsia / CVA 20% 30% 30%

Cardiac Disease 20% 15% 10%


5 meetings in 2008-2009

Developed a Tool Kit for OB services: Set of Best Practices (short summaries of key aspects

of OB hemorrhage)

Checklist for managing OB hemorrhage

Flow-Chart and Table Chart Summaries of approach

Implementation tools such as sample policies, procedures, charting examples, implementation hints

All resources on-line at: www.cmqcc.org/ob_hemorrhage

CMQCC has sponsored an “IHI-like” Learning Collaboratives to help sites implement

CMQCC Hemorrhage Task Force:

http://www.cmqcc.org/ob_hemorrhage

CMQCC California OB Hemorrhage Project

Hemorrhage Taskforce (2008-2009)

QI Toolkit/Best Practices

CHW QI Project (2009)

1st CMQCC Statewide Collaborative (2009-

2010)

30 hospitals (110,000 annual births)

Large/small, urban/rural

New CMQCC Collaboratives (2011)

Statewide: 20+ hospitals (still open)

LA County: 11 hospitals

Systems: Kaiser North and South; Sutter

Enhanced Website resources

26

Obstetrics & Gynecology April 2015

• Pregnancy-related mortality should not be considered a single

clinical entity.

• The five leading causes exhibit different characteristics, degrees

of preventability, and contributing factors, with the greatest

improvement opportunities identified for hemorrhage and

preeclampsia.

Provider Contributing Factors in

Maternal Deaths (California)

Main EK, McClain CL, Morton CH, Holtby S, Lawton ES. Pregnancy-related mortality in

California: Causes, characteristics and improvement opportunities. Obstet Gynecol 2015

From detailed chart reviews of maternal deaths

(CA-Pregnancy Associated Mortality Review Committee;

CDPH-MCAH)

California Approach to Reduce

Maternal Mortality and SMM

•Hemorrhage Taskforce (2009)

•Hemorrhage QI Toolkit (2010)

•Multi-hospital QI Collaborative(s) (2010-11)

Test the “tools” and implementation strategies

•State-wide Implementation (2013-2014)

•Preeclampsia Taskforce (2012)

•Preeclampsia QI Toolkit (2013)

•Multi-hospital QI Collaborative (2013-2014)

•Cardiovascular Detailed Case Analysis (2013)

•Cardiovascular QI Toolkit (2015)

11.1

7.7

10.0

14.6

11.8 11.7

14.0

7.4

7.3

10.9

9.7

11.6

9.2

6.2

16.9

8.9

15.1

13.1

12.19.9

9.9

9.8

13.3

12.7

15.5 16.916.6

19.3

19.9

22.0

0.0

3.0

6.0

9.0

12.0

15.0

18.0

21.0

24.0

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Year

California Rate

United States Rate

Maternal Mortality Rate,

California and United States; 1999-2013 M

ate

rna

l D

ea

ths

per

10

0,0

00

Liv

e B

irth

s

HP 2020 Objective – 11.4 Deaths per 100,000 Live Births

SOURCE: State of California, Department of Public Health, California Birth and Death Statistical Master Files, 1999-2013. Maternal mortality for

California (deaths ≤ 42 days postpartum) was calculated using ICD-10 cause of death classification (codes A34, O00-O95,O98-O99). United States data

and HP2020 Objective use the same codes. U.S. maternal mortality data is published by the National Center for Health Statistics (NCHS) through 2007

only. U.S. maternal mortality rates from 2008 through-2013 were calculated using CDC Wonder Online Database, accessed at http://wonder.cdc.govon

March 11, 2015. Produced by California Department of Public Health, Center for Family Health, Maternal, Child and Adolescent Health Division, March,

2015.

http://wonder.cdc.govon/

National Partnership for Maternal Safety: 3 Maternal Safety Bundles in 3 Years

• Obstetric Hemorrhage

• Preeclampsia/ Hypertension

• Prevention of VTE in Pregnancy

“What every birthing facility

in the US should have…”

Note: The bundles represent outlines of highly recommended protocols and materials important to safe care BUT the specific contents and protocols should be individualized to meet local capabilities. Example materials are available from perinatal collabortives and other organizations. 31

Main EK et al. Obstet Gynecol Nov 2012;120(5):1194–1198.

5 Key Complimentary Strategies:

1) QI projects for labor management practices

2) Payment reform to eliminate negative or

perverse incentives

3) Education for the value of normal birth

(culture)

4) Transparency with Public Reporting

5) Continued public engagement


5. Variation Reflects

Opportunity

0%

10%

20%

30%

40%

50%

60%

70%

80%

1 61

11

62

12

63

13

64

14

65

15

66

16

67

17

68

18

69

19

61

01

10

61

11

11

61

21

12

61

31

13

61

41

14

61

51

15

61

61

16

61

71

17

61

81

18

61

91

19

62

01

20

62

11

21

62

21

22

62

31

23

62

41

24

62

51

Large Variation of Total CS Rate

Among 251 California Hospitals: 2013

Range: 15.0—71.4% Median: 32.5% Mean: 32.8%

Hospitals

Will this degree of variation remain after risk adjustment?

0%

10%

20%

30%

40%

50%

60%

70%

80%

1 6

11

16

21

26

31

36

41

46

51

56

61

66

71

76

81

86

91

96

10

1

10

6

11

1

11

6

12

1

12

6

13

1

13

6

14

1

14

6

15

1

15

6

16

1

16

6

17

1

17

6

18

1

18

6

19

1

19

6

20

1

20

6

21

1

21

6

22

1

22

6

23

1

23

6

24

1

24

6

Even Larger Variation of NTSV CS Rate



National Target =23.9%

36% of CA hospitals meet national target

Hospitals

Large Variation = Improvement Opportunity

CHCF Infographic

Released November 2014

CHCF reports over 11,000

page views in first week and

very positive feedback

calqualitycare.org

New National Guidelines for Defining Labor Abnormalities and Management Options

0%

10%

20%

30%

40%

50%

60%

70%

80%

1 6

11

16

21

26

31

36

41

46

51

56

61

66

71

76

81

86

91

96

10

1

10

6

11

1

11

6

12

1

12

6

13

1

13

6

14

1

14

6

15

1

15

6

16

1

16

6

17

1

17

6

18

1

18

6

19

1

19

6

20

1

20

6

21

1

21

6

22

1

22

6

23

1

23

6

24

1

24

6

Even Larger Variation of NTSV CS Rate



National Target =23.9%

36% of CA hospitals meet national target

Hospitals

Large Variation = Improvement Opportunity

3 Pilot Hospitals for Interventions

This is the same “Orange County” as

depicted in the popular television show.

This is the hospital where most of these

mothers deliver…

Not the easiest population to start with…

3 Major Drivers of the Primary CS Rate

3 Major Drivers of the NTSV CS Rate

Pro

vid

er-

Leve

l Ce

sare

an R

ate

s

G5xxxx

G6xxxx

G7xxxx

G8xxxx

A8xxxx

A6xxxx

A5xxxx

A4xxxx

A8xxxx

A9xxxx

43

32.9% 33.6%

31.2% 31.8%

15%

18%

20%

23%

25%

28%

30%

33%

35%

2011 2012 2013 Jan-14 Feb-14 Mar-14 Apr-14 May-14

Pilot Hospital: Orange County

NTSV CS Rate

National Target for NTSV CS = 23.9%

Jan-

14

Feb-14 Mar-14 Apr14 May-14

Data-Driven QI: NTSV CS

44

32.9% 33.6%

31.2% 31.8%

15%

18%

20%

23%

25%

28%

30%

33%

35%



NTSV CS Rate


QI Project Started: Jan 16

28.3%

Jan-

14



45

32.9% 33.6%

31.2% 31.8%

15%

18%

20%

23%

25%

28%

30%

33%

35%



NTSV CS Rate



28.3%

24.3%

Jan-

14


CMQCC Data-Driven QI: NTSV CS

46

32.9% 33.6%

31.2% 31.8%

15%

18%

20%

23%

25%

28%

30%

33%

35%



NTSV CS Rate



28.3%

24.3%

25.0%

Jan-

14



47

32.9% 33.6%

31.2% 31.8%

28.3%

24.3% 25.0%

23.4%

15%

18%

20%

23%

25%

28%

30%

33%

35%



NTSV CS Rate



Jan-

14



No Change in Baby Outcomes:

Rate of Unexpected Newborn Complications

Hoag Hospital

Intervention

Period

Dec -

Feb

2015

0%

10%

20%

30%

40%

50%

60%

70%

80%

1 6

11

16

21

26

31

36

41

46

51

56

61

66

71

76

81

86

91

96

10

1

10

6

11

1

11

6

12

1

12

6

13

1

13

6

14

1

14

6

15

1

15

6

16

1

16

6

17

1

17

6

18

1

18

6

19

1

19

6

20

1

20

6

21

1

21

6

22

1

22

6

23

1

23

6

24

1

24

6

Hoag Hospital

Low-Risk First-Birth (Nuliparous Term Singleton Vertex) CS Rate (endorsed by NQF, TJC PC-02, CMS, HP2020)

Among 249 California Hospitals: 2011-2012 (Source: CMQCC--California Maternal Data Center

combining primary data from OSHPD and Vital Records)

Range: 10.0—75.8%

Median: 27.0%

Mean: 27.7% National

Target =23.9%

July 24, 2013

36% of CA hospitals

meet national target

49

For the last 3 mos, the rate was 22.5%

Collaborative Action: Collective Impact

Multiple Pressure Points are much more effective than one or two alone

NTSV CS

Strong Evidence

Quality measures

Public Reporting

Clinical Leaders

Data-driven QI

Public Policy

Public advocates

Payment Incentives

Thank you, from all of us at CMQCC!

Elliott Main, MD

David Lagrew, MD

Kathryn Melsop, MS

Christine Morton PhD

Anisha Abreo, MPH

Andrew Carpenter

Jeffrey Gould, MD MPH

Barbara Murphy, RN MSN

Julie Vasher, DPN, CNS

Nancy Peterson, RN MS

Valerie Cape

Allana Moore

art and science of medicine meets quality improvement · hp 2020 objective – 11.4 deaths per...

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