electronic health records: what’s in the pot of gold at the end of the rainbow ?

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Electronic Health Records: What’s in the pot of gold at the end of the rainbow ?. Neil S. Calman, MD. The Goals…. Improve Quality, Safety, Efficiency and Reduce Health Disparities Increase Engagement of Patients and Families Improve Care Coordination Improve Population and Public Health - PowerPoint PPT Presentation

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1

Electronic Health Records:

What’s in the pot of gold at the end of the rainbow ?

Neil S. Calman, MD

2

The Goals….

Improve Quality, Safety, Efficiency and Reduce Health Disparities

Increase Engagement of Patients and Families

Improve Care Coordination

Improve Population and Public Health

Ensure Privacy and Security Protections of Personal Health Information

3

! ! !

ClinicalDecision

Support 2003

Progression of HIT at the Institute

EHR/PMS Implementation

2002

HIE/ Patient Portal

2008

Quality Reporting/ Improvement 2004

EHR = Electronic Health Record

PMS = Practice Management System

HIE = Health Information Exchange

4

Supporting population based care

1

5

Major Congenital Malformations

after First-Trimester

Exposure to ACE Inhibitors

6

Colon Cancer Risk Scoring

7

Linking to the Nation’s public health surveillance system

2

8

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Release

Nu

mb

er o

f C

ases

Symptom Onset Severe Illness

Days

The Benefit of Early Detection of Syndromes

t

9

Single patient visit yields complex EHR data

• Patient Address• Race / Age / Gender• Medical history

• Provider Location• Reason for visit• Problem list

• Temperature• Height/weight• Respirations

• Procedures• Medications• Lab results• Diagnoses

10

EHR Fever

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

7/8/03 8/8/03 9/8/03 10/8/03 11/8/03 12/8/03 1/8/04 2/8/04 3/8/04 4/8/04 5/8/04 6/8/04

Pe

rce

nta

ge

of

fev

er/

flu

ch

ief

co

mp

lain

ts

0.000

0.010

0.020

0.030

0.040

0.050

0.060

Pe

rce

nta

ge

of

me

as

ure

d t

em

pe

ratu

resBlue = ER “flu/fever”

Purple = EHR Fever >100 F

Red = Flu “A” isolates

Violet = Flu “B” isolates

11

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

7/8/03 8/8/03 9/8/03 10/8/03 11/8/03 12/8/03 1/8/04 2/8/04 3/8/04 4/8/04 5/8/04 6/8/04

Perc

enta

ge o

f Fev

Flu

chie

f com

plai

nts

0.000

0.005

0.010

0.015

0.020

0.025

Perc

enta

ge o

f com

bina

tion

synd

rom

e

Fever AND respiratory syndrome

Blue = ER “flu/fever”

Brown = EHR T≥ 100o and

Respiratory Syndrome

12

Institute patient fevers peaked 13 days before ER visits for Fever and Flu – this indicates that health center data may be the first “signal” of an impending epidemic.

Patients of the Institute for Urban Family Health

Institute fever data responded to Flu B outbreak-ED data did not

13

14

15

Bringing public health information to the point of

care in real time

3

16

Practice Alert in EHR for this center only if patient presents with cough – matched to Legionella order set to assist provider in Dx and Tx

DOH sends alert to community re Legionella cases in Parkchester community in the Bronx

17

18

19

20

21

Developing Clinical Decision Supports

over a Broad Range of Measures

4

22

Clinical Decision Support – Impact on Vaccine Administration in Adults

23

24

10 Take New York Indicators1. Have a Regular Doctor or Other Health Care

Provider2. Be Tobacco-Free3. Keep Your Heart Healthy4. Know Your HIV Status5. Get Help for Depression6. Live Free of Dependence on Alcohol and Drugs7. Get Checked for Cancer8. Get the Immunizations You Need9. Make Your Home Safe and Healthy10. Have a Healthy Baby

25

Developing the EHR to monitor quality of care across practice sites

5

26

Patients Seen at Least Once by Their Primary Care Provider

27

Men >35; Women>45 Who have had their cholesterol tested

28

Men >35; Women>45 Who have had their cholesterol tested

29

Depression Screen with PHQ2

30

Depression Screen with PHQ2

31

PARKCHESTER DEPRESSION SCREENING RATE

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

PARKCHESTER

NURSING

PERSONNEL SHORTAGE

NURSING SHORTAGE RESOLVED

STEPPED UP VIGILANCE TO BPA ADHERENCE

32

South Campus Depression Screening

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Amsterdam

East 13th

Homeless

Mount Hope

Parkchester

Phillips

Sidney Hillman

Urban Horizons

Walton

Phase II spread at all sites other than SHHC

E13th PHQ2 CQI Project starts

33

Recorded Smoking History

34

Recorded Smoking History

35

Pneumococcal Vaccine >65yrs old

36

Pneumococcal Vaccine >65yrs old

37

38

39

Using EHR data to determine primary care

practices that are associated with

improved outcomes

6

40

Provider Nutritionist Referral Rate vs. Pts Average HgBA1c

6.5

7

7.5

8

8.5

9

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0%

Rate of Nutrition Referral

Mo

st

Re

ce

nt

Hg

bA

1C

22

12

1

9

0.9

41

Using EHR data to elucidate and help

eliminate racial disparities in health

outcomes

7

42

Last Hemoglobin A1c by Race

White 7.03

n=423

Black 7.44

n=2122

Latino 7.86

n=1555

Asian 7.12n=76

6.6

6.8

7

7.2

7.4

7.6

7.8

8

HgbA1c

43

0

10

20

30

40

50

60

70

80

90

Insulin/SensAgent %

1 HgbA1c % 2 HgbA1c % LDL test %

White

Black

Latino

Asian

44

Reductions in HgbA1c with Treatment by Race /Language

6.5

7

7.5

8

8.5

White 7.23 6.95

Black 7.80 7.44

Latino-Eng 8.02 7.75

Latino- Span 8.12 7.81

Other 7.82 7.48

1st HgbA1C Most Recent

45

Five-year Cancer (all sites) Survival Rate

SOURCE: CDC/NCHS, Health, United States, 2004

30

3540

4550

55

6065

70

1970 1975 1980 1985 1990 1995 2000Year

Pe

rce

nt

Su

rviv

al

Ra

te White

Black

46

Life Expectancy at Birth

60.0

65.0

70.0

75.0

80.0

1950 1960 1970 1980 1990 2000Year

Lif

e E

xp

ecta

ncy (

Years

)

White

Black

SOURCE: CDC/NCHS, Health, United States, 2004

47

Infant Mortality Rates

0

5

10

15

20

25

30

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Year

Infa

nt

dea

ths

per

1,0

00 li

ve

bir

ths

White

Black

SOURCE: CDC/NCHS, Health, United States, 2004

48

Age-adjusted death rates for diseases of the heart per 100,000 males

0.0

100.0

200.0

300.0

400.0

500.0

600.0

Year

De

ath

Ra

tes

pe

r 1

00

,00

0 M

ale

s

White

Black

SOURCE: CDC/NCHS, Health, United States, 2004

49

Dissemination of Results; Credits

50

Authored Publications

• Calman NS, Kitson K, Hauser D “Using Health Information Technology to Improve Health Quality and Safety in Community Health Centers”. Journal of Progress in Community Health Partnerships: Research Education and Action.1(1):83-88. Spring 2007

• Calman, NS, Golub M, Kitson K, Ruddock C. Electronic Health Records: The Use of Technology to Eliminate Racial Disparities in Health Outcomes. In: Medical Informatics: An Executive Primer. Health Information and Management Systems Society, Chicago, IL. Kenneth Ong, MD, Editor. January 2007.

51

Authored Publications

• Sengupta S, Calman NS, Hripcsak G. A Model for Expanded Public Health Reporting in the Context of HIPAA. J. Am. Med. Inform. Assoc. 25 June 2008

52

Our work has been featured in a number of publications by others and has been used as the foundation for others to build upon

53

Commonwealth Fund

“Quality Matters”

May 2006

54

Miller RH and Ward CE

Health Affairs Jan-Feb 2007

55

Awards

2007

Public Health Award

HIMSS Physician

IT Leadership

Award

2005

Partner in NYCDOH

CDC Center of Excellence

in Public Health

Informatics

Non-profitExcellence Award 2008

Technology and Focus on Mission

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