Transcript WORKING DRAFT Last Modified Printed Trend of quality measures following implementation of electronic health record systems amongst practices in underserved urban areas Jason Wang, Ph.D. Sr.

WORKING DRAFT
Last Modified
Printed
Trend of quality measures
following implementation of electronic health record
systems amongst practices in underserved urban areas
Jason Wang, Ph.D.
Sr. Director of Program Evaluation and Analysis
Primary Care Information Project
NYC Department of Health & Mental Hygiene
APHA 140th Annual Meeting
San Francisco, CA
October 30, 2012
Primary Care Information Project
INTRODUCTION
Objective:
Assess the overall trend for some key quality measures for practices in underserved
urban areas after implementation of EHR.
Background:
In transforming primary care, studies showing sustained improvements in the delivery
of clinical preventive services are limited. Fewer demonstrate sustained
improvements among independent practices that are not affiliated with hospital or
integrated health systems. This study examines the continued improvement in clinical
quality measures for a group of practices using electronic health records and
receiving technical support from a local public health agency.
Methods:
Clinical quality measure performance data were analyzed from a cohort of primary
care practices that implemented an electronic health record (EHR) at least three
months before baseline (October 2009). Trends were observed for four key quality
measures: antithrombotic therapy, blood pressure control, smoking cessation
intervention, and A1c testing based on monthly summary data transmitted by the
practices over a two-years period.
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Advancing NYC’s Health Priorities
1) Have a Regular Doctor or Other Health Care Provider
2) Be Tobacco-Free
3) Keep Your Heart Healthy
4) Know Your HIV Status
5) Get Help for Depression
6) Live Free of Dependence on Alcohol and Drugs
7) Get Checked for Cancer
8) Get the Immunizations You Need
9) Make Your Home Safe and Healthy
10) Have a Healthy Baby
•
•
•
Large burden, killing thousands of NYers and causing hundreds of thousands of
preventable illnesses or disabilities each year
Proven amenable to intervention
Best addressed through coordinated action by City agencies, public-private
partnerships, health care providers, businesses, individuals
Important and winnable battles that affect every New Yorker
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Primary Care Information Project (PCIP)
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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Table 1. Description of quality measures
Measure
Eligible patients (denominator)
Patient Goal (numerator)
A1c Testing
Patients 18-75 years with diabetes
Hemoglobin A1c test recorded in the past 6
months
Antithrombotic
Patients 18+ years with ischemic
Taking Antithrombotic/other Antithrombotic
Therapy
vascular disease or 40+ with diabetes
therapy
Blood Pressure
Patients 18-75 years with hypertension
Systolic <140 mmHg and Diastolic <90 mmHg
Control
and no diagnosis of ischemic vascular
disease or diabetes
Smoking Cessation
Patients 18+ years with a "current
Smoking cessation intervention (Rx or
Intervention
smoker" smoking status
Counseling) received in the past 12 months
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Table 2. Baseline Practice Characteristics
Mean Practice Values for Small Practices (SP) and Community Health Centers (CHC)
Characteristic
All Practices
SP
CHC
(n=151)
(n=140)
(n=11)
Sites
1.4
1.2
3.1
Providers
4.5
2.6
29.3*
Encounters per month
925
749
3169
Unique Patients per month
742
612
2392
33%
29.3%
81.8%**
13.7
13.8
13.0
% of Medicaid/ Self-insured >=20%
(Practice self-reported) (T1)
Months using EHR
up to Oct 2009 (T1)
*p=0.03 **p=0.0004
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Graph 1. Overall Progress in PCIP – 2 year trend
% Average Practice Performance Rate
80
74.8
70
60
66.7
64.1
58.4
59.6
57.7
55.3
50
48.9
46.4
40
30
46.2
35.0
29.30
20
Oct-09
Jan-10
Apr-10
Antithrombotic Tx
Time
Oct 2009 (T1)
Oct 2010 (T2)
Oct 2011 (T3)
Difference between T1 and T2
Difference between T2 and T3
Difference between T1 and T3
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BP Control in HTN
Antithrombotic
therapy
58.4
66.7
74.8
8.3*
8.1*
16.4**
Oct-10
Jan-11
Apr-11
Hemoglobin A1c Testing
Blood pressure
control
55.3
58.5
64.1
3.1
5.5*
8.8*
Hemoglobin A1c
Testing
46.4
50.6
57.7
4.2
7.1*
11.3*
Jul-11
Oct-11
Smoking Cess Intervention
Smoking Cessation
Intervention
29.3
34.5
46.2
5.2
11.7*
16.9**
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Table 3. Improved Quality Measure Performance over Time
Stratified by Various Practice Characteristics
Antithrombotic Therapy
Practice
BP Control
Hemoglobin A1c Testing
Smoking Cessation
n
T1
T3
p value
n
T1
T3
p value
n
T1
T3
p value
n
T1
T3
p value
Characteristics
Organization
SP
93
58.9
73.1
<.0001
102
56.6
64.3
0.002
91
48
56.1
NS
81
30.1
45.1
0.0006
Type
CHC
11
54.2
72
0.02
11
43.2
62
0.006
11
33
72.5
0.004
11
23.6
56.9
0.003
NS
NS
0.01
NS
NS
0.003
NS
NS
p value
Adoption time
Early
61
61.8
75.9
<.0001
65
57.3
62.4
NS
61
52.3
58.2
NS
52
34.9
50.4
0.001
Later
43
53.6
73.3
<.0001
48
52.6
66.2
0.0002
41
37.6
57
0.005
40
22
41.1
0.004
NS
NS
NS
NS
0.02
NS
0.01
NS
p value
% Medicaid
<20%
67
56.8
75.7
<.0001
74
57
63.9
0.017
66
44.4
55.4
0.049
61
26.7
39.3
0.008
and selfpay
>=20%
37
61.3
73.5
0.005
39
52
64.3
0.002
36
50.1
60.7
NS
31
34.5
56.9
0.002
NS
NS
NS
NS
NS
NS
NS
0.003
p value
No. of providers
Single
42
59.4
76.4
0.0005
48
55.8
66.8
0.0008
41
50.9
56.8
NS
34
32.6
48
0.04
Multiple
62
57.7
73.5
<.0001
65
54.9
61.7
0.03
61
43.3
58.3
0.007
58
27.4
44.9
0.0001
NS
NS
NS
NS
NS
NS
NS
NS
p value
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Table 4. Results of Generalized Estimating Equation (GEE) Model
Quality Measures
Antithrombotic Tx
Hemoglobin A1c
Smoking Cessation
Testing
Intervention
BP Control
Practice
Characteristics
Months Since EHR
OR (CI)
p value
OR (CI)
p value
OR (CI)
p value
OR (CI)
p value
1.03
<.0001
1.006
0.0243
1.03
<.0001
1.04
<.0001
(1.02, 1.04)
CHC
0.84
(1.0008, 1.01)
0.6027
( 0.43, 1.63)
Months Since
EHR*CHC
1.003
20%
1.21
0.7628
1.24
than one provider
(0.83, 1.85)
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1.01
0.231
1.08
0.016
0.93
(0.76, 1.13)
0.8444
1.02
0.4647
1.21
0.1447
1.12
(0.74, 1.70)
0.1414
1.006
0.7975
(0.96, 1.05)
0.3212
(0.83, 1.78)
0.4592
0.58
(0.28, 1.20)
(0.99, 1.06)
(0.89, 1.31)
0.2865
1.13
(1.02, 1.05)
(0.32, 3.98)
(1.002, 1.02)
(0.89, 1.66)
Practice has more
0.0022
(0.38, 0.81)
(0.98, 1.02)
Medicaid/Selfpay >
0.56
(1.01, 1.04)
1.78
0.0135
(1.13, 2.82)
0.5798
0.70
0.1043
(0.45. 1.08)
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DISCUSSION
Two year trends of 151 independent practices show significant gains on four quality measures.
Our findings suggest that independent small practices and community health centers, with the
assistance from a community EHR extension program such as PCIP, can achieve clinical quality
gains similar to those observed in larger, well-resourced integrated delivery systems. Our
findings are particularly relevant to independent practices serving resource-challenged urban
areas. Of the practice characteristics we analyzed, none accounted for consistent differences in
the increases observed with the exception of duration using an EHR.
In this study we observed increases of several percentage points per year, suggesting that longterm improvement can also occur. This continued progress supports the idea that urban
independent practices can drive long-term improvements in population health, a finding that is
especially promising since inner-city independent practices like those served by PCIP tend to
see a larger than average number of patients who are both uninsured and suffering from more
severe health issues.
Continued support is needed to help independent primary care practices get the most from
health IT as an investment to improve health care and focus on patient-centered, outcomes
driven care and coordination. .
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LIMITATION and NEXT STEPS
Several practices that adopted an EHR in the timeframe eligible for inclusion in the analyses
were not able to transmit data and their performance on the indicators in this study are
unknown, though practices with missing data have similar characteristics as those represented
in the study. Providers working with PCIP represent a group of EHR users who have received a
variety of assistance from PCIP staff, including training and guidance on quality improvement
strategies, technical support on EHR software (upgrades, patches, and configuration), and
connection for health information exchange. Comparable data are not available to ascertain
whether providers who do not have access to the same types of assistance would experience
similar improvement trends.
Improvement due to better documentation alone in the EHR was not tested in this study. For lab
tests where an electronic lab interface was not available and the practice does not routinely
enter results into the patient’s record, practice rates on these tests will be under reported.
Factors such as incentives, availability of CDSS alert, number of QI visits, PCMH recogization,
etc. will be put into the analysis to detect significant driving forces for the quality measures
improvement.
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OTHER PCIP STUDIES (1). Health Information Systems in Small Practices: Improving
the Delivery of Clinical Preventive Services. AJPM. November 2011.
46.3
A1c Screening*
62.4
65.5
Body Mass Index recorded*
78.3
45.9
Blood Pressure Control*
55.0
45.6
Aspirin Therapy*
53.2
77.4
Smoking Status recorded*
83.9
27.8
Breast Cancer Screening*
32.3
20.5
24.0
Influenza Vaccination*
76.6
77.9
Cholesterol Control
Smoking Cessation Intervention
31.3
31.0
A1c Control
31.3
30.4
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Pre EHR Upgrade
% eligble patients recieving CPS
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OTHER PCIP STUDIES (2). Validity of EHR Derived Quality Measurement for
Monitoring Population Health & Clinical Quality. JAMIA. Feb 2012.
5000
Captured
Patients in Denominator
Missed
4000
3000
2000
1000
0
4000
A1c control
A1c screening
Antithrombotic therapy
Blood pressure control
Breast cancer screening
Cholesterol control
Cholesterol screening
Influenza vaccination
Smoking cessation intervention
Smoking status recorded
Patients in Numerator
3000
2000
1000
0
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% eligible patients receiving service
OTHER PCIP STUDIES (3). Decline and Rebound: Population Trends in Performance on
Clinical Quality Measures in Small Practices Adopting Electronic Health Records.
Academy Health Annual Meeting,
Orlando, FL. June 2012.
100
80
60
40
20
0
2 years before EHR
1 year before EHR
EHR, no CDSS
EHR and CDSS
Antithrombotic therapy
26.3
28.0
49.6
57.1
Body mass index recorded
84.4
75.6
64.5
77.9
Blood pressure control
46.3
48.4
49.4
59.8
Cholesterol control
81.4
81.0
83.2
82.4
Cholesterol testing
80.1
80.1
45.8
63.3
Hemoglobin A1c testing
52.5
45.1
41.0
34.3
Hemoglobin A1c control
65.2
66.6
43.8
61.3
Smoking cessation intervention
Primary
Care
Smoking
status
recorded
Information Project
26.1
23.6
24.8
28.4
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OTHER PCIP STUDIES (4). Two year quality trends for independent practices adopting an EHR and
achieving PCMH recognition. AHRQ Annual Meeting, Washington DC, September 2012.
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Acknowledgments
Authors:
Jason J. Wang PhD, Kimberly M. Sebek MPH, Colleen M. McCullough BA, Sam C. Amirfar MD,
Amanda S. Parsons MD, MBA, Jesse Singer DO, MPH, Sarah C. Shih MPH
Contact:
Jason Wang, Ph.D., Sr. Director of Program Evaluation and Analysis
Primary Care Information Project, NYC Department of Health and Mental Hygiene
Long Island City (Queens), NY 11101. Tel: (347) 396-4859, Email: [email protected]
Acknowledgments:
The authors would like to acknowledge Dr. Thomas Farley, Commissioner of the New York City
Department of Health for the valuable input on this study. The authors also wish to thank the
PCIP staff for their tremendous dedication and participating practices’ commitment to improving
health in New York City.
Funding:
A portion of this study was supported by the Agency for Healthcare Research and Quality (grant
#s R18HS17059 and 17294). The funder played no role in the study design, in the collection,
analysis and interpretation of data, in the writing of the report or in the decision to submit the
paper for publication
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