Measuring Population
Health in NYC: New
Frontier
Academy Health
Amanda Parsons, MD, MBA
Deputy Commissioner
Presentation
June 24, 2013
PRIMARY CARE INFORMATION PROJECT
PCIP started as a mayoral initiative in 2005
Mission
• Improve the quality of care in medically underserved areas through health information technology (HIT)
Success
• Over 6,200 providers receiving EHR and Meaningful Use assistance
• 915 small practices, 23 large practices
• 50 community health centers
• 54 hospitals & outpatient clinics
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PRIMARY CARE INFORMATION PROJECT
Network of prevention‐oriented EHRs.
“The Hub” allows secure exchange of data with PCIP practices.
‐ Send out queries
‐ Receive aggregate patient counts overnight
The Hub currently covers:
• 570 practices
• 1.2 M patients in 2011
• 3 M patients since 2009
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DATA OBTAINABLE THROUGH HUB QUERIES
 Chronic health conditions and clinical risk factors  Use of clinical preventive services and screening  Recommended counseling services  Chronic disease management
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THE DATA WE GET IS USED TO PROVIDE FEEDBACK TO PATIENTS AND
TO DO POPULATION HEALTH SURVEILLANCE
Provider dashboards
Population health
BMI distribution
|
THE PRESENCE OF DATA RECOGNIZED FOR AUTOMATED QUALITY
MEASUREMENT VARIED FROM 10% TO ~100%
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Obesity in New York City as Measured by the CHS, NYC HANES and PCIP
35
PCIP’s Hub
30
NYC HANES
25
20
%
15
Obese
(BMI 10
≥ 30)
5
0
2002
Community Health Survey
2003
2004
2005
2006
Year
2007
2008
2009
2010
Adults ages 20 and over. Data are age‐adjusted to the U.S. standard 2000 population. For more information about the CHS or the 2004 NYC HANES, please see www.nyc.gov/health/epiquery
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Obesity in New York City as Measured by the CHS, NYC HANES and PCIP
35
PCIP’s Hub
30
NYC HANES
25
20
%
15
Obese
(BMI 10
≥ 30)
5
0
2002
Community Health Survey
2003
2004
2005
2006
Year
2007
2008
2009
2010
Adults ages 20 and over. Data are age‐adjusted to the U.S. standard 2000 population. For more information about the CHS or the 2004 NYC HANES, please see www.nyc.gov/health/epiquery
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THANK YOU!
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PARKING LOT
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1. BREAST CANCER SCREENING DOCUMENTATION
Female patients > 40 years of age who receive a
mammogram in the past 2 years
Recognized
• Procedures (11 %)

Not Recognized
• Scanned patients docs (49%)

•
Diagnostic
imaging
(37%)

• Other (3%)
EHR Query
Mean Numerator
1.0
e-Chart review
9.5
Mean Denominator 28.7
28.7
Score
33.1%
3.5 %
* 57 of 82 eligible practices agreed to the chart review
SOURCE: Parsons et al. Validity of electronic health record-derived quality measurement for performance monitoring. J
Am Med Inform Assoc. (2012).
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1. BREAST CANCER SCREENING DOCUMENTATION
Female patients > 40 years of age who receive a
mammogram in the past 2 years
Recognized
• Procedures (11 %)

Not Recognized
• Scanned patients docs (49%)

•
Diagnostic
imaging
(37%)

• Other (3%)
Practices are not electronically
closing out referrals, just storing the
results
Due to a flaw in EHR design that
incorrectly excluded this category
from the measure (now fixed)
SOURCE: Parsons et al. Validity of electronic health record-derived quality measurement for performance monitoring. J
Am Med Inform Assoc. (2012).
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2. BODY MASS INDEX DOCUMENTATION
All patients > 18 years of age who have a BMI
measured in the past 2 years
Recognized
• Vitals (99.8 %)
Not Recognized
• Medical History (0.1%)

•
Other
(0.1%)


EHR Query
Mean Numerator
54.6
e-Chart review
54.8
Mean Denominator 71.4
71.4
Score
76.8%
76.5%
* 57 of 82 eligible practices agreed to the chart review
SOURCE: Parsons et al. Validity of electronic health record-derived quality measurement for performance monitoring. J
Am Med Inform Assoc. (2012).
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2. BODY MASS INDEX DOCUMENTATION
All patients > 18 years of age who have a BMI
measured in the past 2 years
Recognized
• Vitals (99.8 %)

Not Recognized
• Medical History (0.1%)

•
Other
(0.1%)

Incorrect documentation is rarely an
issue. Mostly clear to practices where
to document correctly
* 57 of 82 eligible practices agreed to the chart review
SOURCE: Parsons et al. Validity of electronic health record-derived quality measurement for performance monitoring. J
Am Med Inform Assoc. (2012).
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3. SMOKING STATUS DOCUMENTATION
Smoking status updated annually in patients > 18
years of age
Recognized
• Smart form (template)
(53.4 %)

Not Recognized
• Social history (45.5%)

•
Other
(0.8%)

• Medical history (0.2%)
EHR Query
Mean Numerator
31.5
e-Chart review
59.5
Mean Denominator 71.5
71.5
Score
83.2 %
44.1 %
* 57 of 82 eligible practices agreed to the chart review
SOURCE: Parsons et al. Validity of electronic health record-derived quality measurement for performance monitoring. J
Am Med Inform Assoc. (2012).
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3. SMOKING STATUS DOCUMENTATION
Smoking status updated annually in patients > 18
years of age
Recognized
• Smart form (template)
(53.4 %)

Not Recognized
• Social history (45.5%)

•
Other
(0.8%)

• Medical history (0.2%)
Even though the template is available
in social history, it’s a separate item.
Valuable feedback to EHR developersNeed to make it more obvious in this
section of the EHR where to document
smoking
* 57 of 82 eligible practices agreed to the chart review
SOURCE: Parsons et al. Validity of electronic health record-derived quality measurement for performance monitoring. J
Am Med Inform Assoc. (2012).
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