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Measuring Quality and Clinical Performance Indicators at Partners HealthCare System
Blackford Middleton, MD, MPH, MScCorporate Director, Clinical Informatics R&D
Chairman, Center for Information Technology LeadershipPartners HealthCare System, Inc.Brigham & Women’s Hospital
Harvard Medical School
Overview
• Partners Healthcare System, Boston— High Performance Medicine
— The HPM-X Informatics Infrastructure
• Reporting in an EMR— LMR Report Central
— Quality Dashboards
• Early experiences with Quality Dashboards
• Q&A
Partners HealthCare System
• Ten 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 = 3,800 (> 90% of AMC PCPs; ~ 50% 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
HPM comprises five System-wide projects with one common goal:
To deliver better care to patients.
• Care that is:
Safer
Better coordinated
More reliable in delivering proven interventions
• Systems that support providers in “doing the right thing.”
To deliver better care to patients.
• Care that is:
Safer
Better coordinated
More reliable in delivering proven interventions
• Systems that support providers in “doing the right thing.”
What is High Performance Medicine?
http://www.partners.org/about/hpm.htm
Dr. Jim Mongan
1. Investing in quality and utilization infrastructure Information systems applications Informatics Infrastructure (data, knowledge, services)
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
Quality
Efficiency
Init
iati
ve F
ocus
Infrastructure
What are the High Performance Medicine Initiatives?
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.
Application 1
LOGIC
MGH OE
Patient MGH Order
Data
DictionariesAnd Rules
DictionariesAnd Rules
Application 2
LOGIC
BICS OE
Patient BICS OE
Data
DictionariesAnd Rules
DictionariesAnd Rules
Application 3
LOGIC
LMR
Patient LMRData
DictionariesAnd Rules
DictionariesAnd Rules
Application 1
LOGIC
MGH OE
Patient MGH Order
Data
DictionariesAnd Rules
DictionariesAnd Rules
Application 1
LOGICLOGIC
MGH OEMGH OE
Patient MGH Order
Data
DictionariesAnd Rules
DictionariesAnd Rules
Application 2
LOGIC
BICS OE
Patient BICS OE
Data
DictionariesAnd Rules
DictionariesAnd Rules
Application 2
LOGICLOGIC
BICS OEBICS OE
Patient BICS OE
Data
DictionariesAnd Rules
DictionariesAnd Rules
Application 3
LOGIC
LMR
Patient LMRData
DictionariesAnd Rules
DictionariesAnd Rules
Application 3
LOGICLOGIC
LMRLMR
Patient LMRData
DictionariesAnd Rules
DictionariesAnd Rules
Enterprise Repository(s) of Patient DataAllergies, CDR (Labs,Discharge Orders, LMR Notes)
CAS or Web ShellPatient Lookup (EMPI)
The Future: Shared Data, Knowledge, and Logic – Partners SOA Strategy
Common ‘Shell’ or Clinical Portal
Shared Logic, Dictionaries, and Rules (Enterprise Clinical Services, Medication Services and Knowledge Management)
LOGIC(Services)
Enterprise Repository (s)Problems, Meds, Allergies, Labs, Orders, Notes, etc.
DictionariesAnd Rules Data (Knowledgebases)
DictionariesAnd Rules Data (Knowledgebases)
MGH OE BWH OE LMR
Future clinical applications will take advantage of shared repositories of enterprise data, knowledge, and logic, in a services-oriented architecture
Secure Clinical CommunicationAnd Notification of Results
Intuitive Chart Summary
Automatic Reminders
Summary Flowsheets
Coded Clinical DataCustomizable Desktop
SFQD R&D TeamAcknowledgements
• Clinical Informatics— Jonathan Einbinder, MD, MPH— Julie Greim, MSc— Tonya Hongsermeier, MD,
MBA— Qi Li , MD, MBA— Maya Olsha-Yehiav— Matvey Palchuk, MD, MSc— Alan Rose, MSc
• Clinical and Quality Analysis— Julie Fiskio— Andrea Melnikas— Svetlana Turovsky, MD— Lana Tsurikova, MA, MSc— Lynn Volk, MA— Tony Yu, MD, MSc
• Clinical Investigators— Jeff Linder, MD, MPH— Jeff Schnipper, MD, MPH— John Orav, PhD
• Application Development— Irene Galperin— Nina Plaks— Anatoly Postilnik— Boris Rudelson — Michael Vashevko
• Clinical Systems Management— Lynn Klokman— Eunice Jung
• Other— Steve Flammini, CTO— Joanne Tremblay— Cindy Spurr— Cindy Bero— Liz Mort, MD— Alan Cole, MD
AHRQ R01HS015169Blackford Middleton, PI
CAD / Diabetes Smart Form
• Integrated into a visit note• Customized views tailored to medical
condition(s) of the patient• Guided data review• Central note-writing section
— Multiple ways to document a note— “Formlets” for selected coded data entry
• Tailored Decision support section• Patient View
— Activates patient around goals of care
CAD/DM Smart FormSmart View: Data Display
Smart View: Data Display
Assessment, Orders, and Plan
Assessment, Orders, and Plan
Assessment and recommendations generated from rules engine
Assessment and recommendations generated from rules engine
Documentation Window
Documentation Window
• Lipids• Anti-platelet therapy• Blood pressure• Glucose control• Microalbuminuria• Immunizations• Smoking • Weight• Eye and foot examinations
• Lipids• Anti-platelet therapy• Blood pressure• Glucose control• Microalbuminuria• Immunizations• Smoking • Weight• Eye and foot examinations
CAD/DM Smart Form
Medication OrdersMedication Orders
Lab OrdersLab Orders
ReferralsReferrals
Handouts/EducationHandouts/Education
What is a Quality Dashboard?
• Physician feedback system
• Clinician-level view of performance on problem-oriented quality indicators
• Comparison to:— Clinic peers
— National benchmarks
• Drill-down capability— Summary measures List of Individual Patients
Patient Charts/Smart Form
ARI Quality Dashboard
Provider Name Clinic Name
CAD Quality Dashboard
Targets are 90th percentile for HEDIS or for Partners providers
Targets are 90th percentile for HEDIS or for Partners providers
Zero defect care: • Aspirin• Beta-blockers• Blood pressure• Lipids
Zero defect care: • Aspirin• Beta-blockers• Blood pressure• Lipids
Red, yellow, and green indicators show adherence with targets
Red, yellow, and green indicators show adherence with targets
CAD Quality Dashboard
CAD Quality Dashboard
SortSortPrioritize by
deficiency points
Prioritize by deficiency points
CAD Quality DashboardFilter. For example, patients with blood pressure not at goal who have had 0 or 1 visit in the past year
Filter. For example, patients with blood pressure not at goal who have had 0 or 1 visit in the past year
Clicking on name opens patient’s Smart FormClicking on name opens patient’s Smart Form
Lessons Learned: Quality Dashboards
• Biggest barriers to use are related to the health care system— What are the drivers (carrots and sticks) to
QD use?• Pay for performance
• Reimbursement for case management
— For chronic diseases, QD may be more effective as a case management tool
Lessons Learned: Quality Dashboards
• Other major barrier is related to quality of the data— Absolute need to tie patients to providers, edit
panels, deal with missing data— Won’t change behavior unless the data are
believable• Big societal trends will drive quality
measurement— Can providers be proactive? (EHR data better
than billing data)
Conclusions
• Smart Forms and Quality Dashboards offer new workflow and decision support methods to manage acute and chronic medical conditions using EHR technology
• Both have potential to improve care, demonstrate EHR value to providers, and drive EHR use
• Much work remains to be done
Where Are We?
