10th annual utah's health services research conference - data from ehrs in outpatient practice...
TRANSCRIPT
Data from EHRs in Outpatient
Practice Settings: An Emerging
but Immature Resource
Deepthi Rajeev and Jeff Black
March 16th, 2015
10th Annual Utah Health Services Research Conference
Objectives
• Present an overview of the scope of our
collaborations in the community
• Describe real-world challenges in deriving
meaningful information from EHRs of
outpatient practices
• Share lessons learned
• Future implications in the community
Who is HealthInsight?
• A private, non-profit, community based organization dedicated to improving health and health care in Utah, New Mexico, and Nevada
• We currently serve as: – Medicare Quality Innovation Network / Quality
Improvement Organization (UT, NV, NM, OR)
– State External Quality Review Organization (NM)
– Regional Extension Center for HIT (UT, NV)
– NRHI Regional Health Improvement Collaborative
– AHRQ-designated Chartered Value Exchange (UT, NV)
– RWJ Foundation Aligning Forces for Quality community (NM)
Scope in the Community
• 353 clinics and 1256
providers
• Quality Improvement
• Assistance with
Meaningful Use and
HIT
Project Examples
• Beacon cooperative agreement – In 2010, the Office of the National Coordinator
awarded 17 Beacon communities across the US
– Improve care provided to adult patients with Diabetes in the Salt Lake MSA
• Quality Improvement Task – Aligned with the Million Hearts Initiative
– Focused on ABCS: Aspirin therapy, Blood pressure control, Cholesterol management , Smoking cessation
EMR Systems of Beacon and Cardiac Participants
22 19
16 7 7 7
5 4 4 4 4 4
2 2 2 2 2
1 1 1 1 1 1 1 1
eClinicalWorks (eClinicalworks, LLC)
Epic Care EHR (Epic, Inc)
Help2 (Intermountain Healthcare)
Amazing Charts (Amazing Charts)
e-MDs (e-MDs, Inc)
PrimeSuite (Greenway)
Vitera Intergy EHR (Vitera Healthcare)
AllScripts Enterprise (AllScripts)
Aprima (Aprima Medical Software)
GE Centricity Enterprise (GE Healthcare)
Other
Practice Partner (McKesson)
AllScripts Professional (AllScripts)
Care360 EHR (MedPlus, Inc)
NextGen EHR (NextGen)
Practice Fusion (Practice Fusion)
Red Planet EHR (ArcSys)
Advanced MD (Advanced MD)
AltaPoint (AltaPoint)
CADURx (CADURx)
MyWay (AllScripts)
Noteworthy (Noteworthy Medical)
Sevocity EHR (Sevocity)
SOAPware (SOAPware, Inc.)
Spring Charts (Spring Medical Systems)
8 Diabetes Quality Measures
• HbA1c screening
• Diabetes in control (HbA1c<8%)
• LDL-C screening
• LDL-C in control (<100mg/dl)
• BP in control (<140/90)
• Medical attention for nephropathy
• Retinal eye exams
• Foot exams
9% 2% 2% 2% 5%
25%
39%
16%
5% 2% 2% 2%
57%
32%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8
Number of the 8 Diabetes CQMs Available
Clinic Count by Number of Number of Diabetes CQMs Available
Clinic Count Initial Clinic Count Final
65%
76% 82% 82%
65%
82% 76%
88% 94%
100%
94%
100%
82%
94%
76%
100%
0%
20%
40%
60%
80%
100%
17 Independent Clinics Count of Clinics By Quality Measure
Cardiac Measures • BP Control
– NQF #0073 - Ischemic Vascular Disease (IVD): Blood Pressure Management
– NQF #0061 - Diabetes: Blood Pressure Management
– NQF #0018 - Controlling High Blood Pressure
• Lipid Control – NQF #0075 - Ischemic Vascular Disease (IVD): Complete Lipid Panel and LDL
Control
– NQF #0064 - Diabetes: Low Density Lipoprotein (LDL) Management and Control
• Aspirin Therapy – NQF #0068 - Ischemic Vascular Disease (IVD): Use of Aspirin or Another
Antithrombotic
– NQF #0067 - Coronary Artery Disease (CAD): Oral Antiplatelet Therapy Prescribed for Patients with CAD
• Smoking Cessation – NQF 0028b - Preventive Care and Screening Measure Pair: b. Tobacco
Cessation Intervention
– NQF #0027 - Smoking and Tobacco Use Cessation, Medical assistance
4%
13%
31%
52%
2%
11%
45% 41%
0%
10%
20%
30%
40%
50%
60%
1 2 3 4
Number of Measures available
Percentage of Cardiac Clinics Who Could Report up to 4 measures
Initial Collection Period
Final Collection Period
Cardiac Measure Availability
63% 57% 60%
40%
90%
70% 70%
23%
0%
20%
40%
60%
80%
100%
BloodPressure
Lipid Control Aspirin Smoking
Pe
rce
nt
of
Clin
ics
Initial Final
MOGE (Moved or Gone
Elsewhere) Filtering Patient Lists
Clinical Workflow: Lessons
Learned • Improving data documentation critical to
measure calculation and subsequently QI
• Workflow changes may be needed:
– Use of standard templates vary across
clinics using the same EHR system
– Free text (e.g., DM foot exam, DM eye
exam, L/R to denote the side BP was
measured)
– Identification of ‘inactive’ patients and
classification of ‘urgent care’
Measures: Lessons Learned-1
• Interpretation of measure specifications
vary across vendors
• Trial and error and reverse
engineering to calculate valid
denominators and numerators
• Custom reporting is usually possible but
complex
– Often doesn’t meet standard measure
specifications (e.g., 2 visits in two years for
diabetes denominators)
Measures: Lessons Learned-2
• Measures that are not core ‘MU’: less likely
to be available (e.g., A1c and LDL
screening)
• Vitals based measures more likely to be
available and valid (e.g., BP)
• Measures relying on lab test results require
substantial effort
– Point of care entry for in-house tests and
multiple lab interfaces
MU and QI: Lessons Learned
• Most EHR systems (even MU-certified) are
not designed to support analysis for QI and
population management
• MU reports helpful for provider-level data
but limited capability to present data at the
clinic-level
– Clinic level reporting may not be valid due to
duplication of patients among providers
• Burden on clinics to create run charts and
generate patient lists
Implications for the Community
• EHRs have the potential to be rich data sources but important to recognize their limitations
• Move towards Transparency and Accountability in healthcare outcomes
– Practices need to assess and improve their capacity in using EHRs to support population health and care management
• Growing awareness of the value of data integration
Acknowledgements
• All participating outpatient practices
• Kimberly Mueller, Health care Analyst
Team Lead
• HealthInsight Utah staff
