Transcript Role of EHR in Healthcare Reform of Integrated Health Care

Role of the EHR in
Healthcare Reform of
Integrated Health Care
Systems
Blackford Middleton, MD, MPH, MSc
Partners HealthCare System,
Harvard Medical School
Agenda
Principal components of healthcare reform
Partners’ High Performance Medicine
Current Research & Development
Smart use of EMR: Clinical Decision Support
Quality Dashboards
Patient Activation
Clinical Decision Support Consortium
Principal Components of Healthcare
Reform
 President Obama’s FY 2010 Budget
overview:
 Reduce long-term growth of health
care costs for businesses and
government.
 Protect families from bankruptcy or
debt because of health care costs.
 Guarantee choice of doctors and health
plans.
 Invest in prevention and wellness.
 Improve patient safety and quality
care.
 Assure affordable, quality health
coverage for all Americans.
 Maintain coverage when you change or
lose your job.
 End barriers to coverage for people
with pre-existing medical conditions.
The New Healthcare
Policy “ABCDE”
Access
Best Quality
Cost
Disparities
(Comparative)
Effectiveness
Partners HealthCare System
Eleven hospitals, 7000 physicians
$6.4B in revenues
4M outpatient visits and 160,000 admissions/year
$1B in biomedical research annually
Teaching affiliate of the Harvard Medical School
Founded by the Brigham and Women’s Hospital and
the Massachusetts General Hospital
Information Systems Descriptive
Numbers
 Operating budget (FY07) =
$158M
 Capital budget (FY08) =
$45M
 Number of users = 54,000
 Devices on the network =
71,000
 Locations on the Partners
network = 140
 Electronic Medical Record
physician users = 4,000 (>
100% of AMC PCPs; ~ 75%
of Specialists)
 Patients with data in the
clinical data repository =
4,000,000
 Medical images on line =
450,000,000
 Orders entered hourly
through Computerized
Provider Order Entry (across
Partners) = 1,000
 LMR (ambulatory EMR)
transactions per day = 1M
 Calls to the Help Desk each
month = 18,000
Major Information Systems
Initiatives
Provision of electronic medical records, computerized
provider order entry, electronic medication
administration records and clinical decision support
to further the goals of High Performance Medicine
Implementation of COMPASS to standardize and
improve revenue cycle processes across Partners
Creation of the next generation of healthcare
information systems architecture through the Service
Oriented Architecture (SOA) initiative
What is High Performance Medicine?
HPM comprises five System-wide projects
with one common goal:
To deliver better care to patients.
• Care that is:
 Safer
 Better coordinated
Dr. Jim Mongan
 More reliable in delivering proven interventions
• Systems that support providers in “doing the right
thing.”
http://www.partners.org/about/hpm.htm
What are the High Performance
Medicine Initiatives?
1. Investing in quality and utilization infrastructure
 Information systems applications
Infrastructure
 Informatics Infrastructure (data, knowledge, services)
Initiative Focus
Quality
Efficiency
2. Enhancing patient safety by reducing medication errors
system-wide
3. Enhancing uniform high quality by measuring
performance to benchmark for select inpatient and
outpatient conditions
4. Expanding disease management programs by supporting
activities for certain patients with chronic illnesses
5. Improving cost effectiveness through managing utilization
trends and analysis of variance
Clinical Systems Goals
 To ensure comparability of clinical data across the
enterprise
• common data
 To facilitate enterprise clinical decision support
• common logic
 To facilitate enterprise reporting and data mining
• common reports, business intelligence
 To facilitate enterprise standard clinical practice for
providers and patients
• common workflow – reduced unwarranted variation – where
appropriate
 To enhance our development agility by creating re-usable
application components and services
• common infrastructure, 1-4 above
Quality Matters:
Diabetes Measures 2006-2008
2006 Diabetes
2007 Diabetes
2008 Diabetes
Payer 1
HbA1c Screening (2x)
LDL Screening
$2.8M
Diabetes Composite Care (4
HEDIS tests: HbA1c
screening, LDL screening,
Eye Exam, Nephropathy)
$1.87M
Develop BP baseline
$935K
7 POINT SCALE
1. Diabetes Composite Care (4 HEDIS
tests)
2. HbA1c Outcomes </= 9
3. HbA1c Outcomes < 7
4. LDL Outcomes < 130
5. LDL Outcomes < 100
6. BP Outcomes < 140/90
7. BP Outcomes <130/80
~$3.15M (6,000 patients)
Payer 2
HbA1c Outcomes </= 9
LDL Outcomes < 130
$2.1M
HbA1c Outcomes </= 9
$1.25M
LDL Outcomes < 100
$1.25M
HbA1c Outcomes < 7
~$1.32M (3,100 patients)
LDL Outcomes < 100
~$1.32M (3,100 patients)
Payer 3
HbA1c Screening (1X)
$2.1M
HbA1c Screening (1X)
$1.6M
(TAHP targets in negotiation)
HbA1c Outcomes </= 9*
LDL Outcomes < 100*
~$1.75M (2,600 patients)
Quality Measures and Requirements:
Why is EMR Data Necessary?
• Contractual measures are moving away from claims
based measures to outcomes measures, which require
clinical data elements
• E.G. Diagnoses, Lab results, Blood pressure, Weight, Medications, Eye
exam, Ejection Fraction
• Tracking of performance and management of patients
will be dependent upon data in EMRs
• Settlement of 2008 contractual measures will no longer
be dependant upon claims; we will need measure
specific clinical values for all patients
In the longer term, there will be a move to derive quality
measures directly from the EMR, rather than from
clinically enriched administrative data.
12
Discrete vs. Shared:
Data, Knowledge, Logic
Many Partners’ applications utilize discrete data, logic and knowledge or rules; most
are not integrated across sites – creating islands of information and supporting varying
levels of functionality.
CAS or Web Shell
Patient Lookup (EMPI)
Application 1
Application 2
MGH OE
BICS OE
LOGIC
Application 3
LMR
LOGIC
Dictionaries
Dictionaries
And Rules
And Rules
Dictionaries
Dictionaries
And Rules
And Rules
Patient
MGH Order
Data
LOGIC
Dictionaries
Dictionaries
And Rules
And Rules
Patient
BICS OE
Data
Enterprise Repository(s) of Patient Data
Allergies, CDR (Labs,Discharge Orders, LMR Notes)
Patient LMR
Data
The Future: Shared Data, Knowledge,
and Logic – Partners SOA Strategy
Future clinical applications will take advantage of shared repositories of
enterprise data, knowledge, and logic, in a services-oriented architecture
Common ‘Shell’ or Clinical Portal
MGH OE
BWH OE
LMR
Shared Logic, Dictionaries, and Rules (Enterprise Clinical Services,
Medication Services and Knowledge Management)
Dictionaries
And Rules Data
(Knowledgebases
)
LOGIC
(Services)
Enterprise Repository (s)
Problems, Meds, Allergies, Labs, Orders, Notes, etc.
Current Research & Development
Smart use of EMR: Clinical Decision Support
Quality Dashboards
Patient Activation
The Clinical Decision Support Consortium
How can an EHR make a
difference?
Structure
Process
Outcome
Adoption
Effective Use
Smart Use
Get an EMR
and use it
Use key EMR
features fully
Leverage
EMR
decision support
We are here
Meaningful Use
Secure Clinical Communication
And Notification of Results
Automatic Reminders
Summary Flowsheets
Intuitive Chart Summary
Coded Clinical Data
Customizable Desktop
CAD/DM Smart Form
Smart View:
Data Display
Documentation
Window
Assessment and recommendations
generated from rules engine
•
•
•
•
•
•
•
•
•
Lipids
Anti-platelet therapy
Blood pressure
Glucose control
Microalbuminuria
Immunizations
Smoking
Weight
Eye and foot examinations
Assessment,
Orders, and Plan
Preliminary Results:
Smart Form On Treatment Analysis
Smart Form Used
0%
Control
10% 20% 30% 40% 50% 60% 70% 80%
Up-to-date BP result
Change in BP therapy if above goal
Up-to-date height and weight
<0.001
0.05
0.004
Change in therapy if A1C above goal
0.006
Up-to-date foot exam documented
Up-to-date eye exam documented
# of deficiencies addressed
<0.001
<0.001
<0.001
CAD Quality Dashboard
Red, yellow, and green indicators
show adherence with targets
Zero defect care:
• Aspirin
• Beta-blockers
• Blood pressure
• Lipids
Targets are 90th percentile for
HEDIS or for Partners providers
Discrepancy
Details
Provider Activation
More medication changes in visits after diabetes journal submission:
Grant RW et al. Practice-linked Online Personal Health Records for Type 2
Diabetes: A Randomized Controlled Trial. Arch Int Med 2007, in press.
CDS Consortium Goal
To assess, define, demonstrate, and evaluate best
practices for knowledge management and clinical
decision support in healthcare information technology
at scale – across multiple ambulatory care settings and
EHR technology platforms.
http://www.partners.org/cird/cdsc
Six Specific Research
Objectives
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Knowledge management lifecycle
Knowledge specification
Knowledge Portal and Repository
CDS Knowledge Content and Public Web Services
Evaluation
Dissemination
1. Knowledge Management Life Cycle
2. Knowledge
Specification
3. Knowledge Portal and
Repository
4. CDS Public Services
and Content
5. Evaluation Process for each CDS Assessment and Research Area
6. Dissemination Process for each Assessment and Research Area
Thank you!
Blackford Middleton, MD
[email protected]