Role of the EHR in Role of the EHR in Healthcare Reform of Healthcare Reform of

Integrated Health Care Integrated Health Care Systems Systems

Blackford Middleton, MD, MPH, MSc Partners HealthCare System,

Harvard Medical School

AgendaAgenda

Principal components of healthcare reformPartners’ High Performance MedicineCurrent Research & Development

Smart use of EMR: Clinical Decision SupportQuality DashboardsPatient ActivationClinical Decision Support Consortium

Principal Components of Healthcare Principal Components of Healthcare ReformReform

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”AccessBest QualityCostDisparities(Comparative)

Effectiveness

Partners HealthCare SystemPartners HealthCare System

Eleven hospitals, 7000 physicians$6.4B in revenues4M outpatient visits and 160,000 admissions/year$1B in biomedical research annuallyTeaching affiliate of the Harvard Medical SchoolFounded by the Brigham and Women’s Hospital and

the Massachusetts General Hospital

Information Systems Descriptive Information Systems Descriptive NumbersNumbers

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 Major Information Systems InitiativesInitiatives

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

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?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

Initi

ativ

e F

ocus

Infrastructure

What are the High Performance What are the High Performance Medicine Initiatives?Medicine Initiatives?

Clinical Systems GoalsClinical 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:Quality Matters:Diabetes Measures 2006-2008Diabetes 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:Quality Measures and Requirements:Why is EMR Data Necessary?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

12

In the longer term, there will be a move to derive quality measures directly from the EMR, rather than from

clinically enriched administrative data.

Discrete vs. Shared: Discrete vs. Shared: Data, Knowledge, LogicData, 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, The Future: Shared Data, Knowledge, and Logic – Partners SOA Strategyand 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

Current Research & DevelopmentCurrent Research & Development

Smart use of EMR: Clinical Decision SupportQuality DashboardsPatient ActivationThe Clinical Decision Support Consortium

Adoption

Get an EMRand use it

Adoption

Get an EMRand use it

Effective Use

Use key EMRfeatures fully

Effective Use

Use key EMRfeatures fully

Smart Use

Leverage EMR

decision support

Smart Use

Leverage EMR

decision support

We are here

How can an EHR make a How can an EHR make a difference?difference?

Meaningful Use

Structure Process Outcome

Secure Clinical CommunicationAnd Notification of Results

Intuitive Chart Summary

Automatic Reminders

Summary Flowsheets

Coded Clinical DataCustomizable Desktop

CAD/DM Smart FormCAD/DM Smart Form

Smart 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

Preliminary Results: Preliminary Results: Smart Form On Treatment AnalysisSmart Form On Treatment Analysis

<0.001

<0.001

<0.001

<0.001

<0.001

0.05

0.004

0.006

CAD Quality DashboardCAD 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

Discrepancy

Details

Provider Activation Provider Activation

Grant RW et al. Practice-linked Online Personal Health Records for Type 2 Diabetes: A Randomized Controlled Trial. Arch Int Med 2007, in press.

More medication changes in visits after diabetes journal submission:

CDS Consortium GoalCDS 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 Six Specific Research ObjectivesObjectives

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

Knowledge management lifecycle Knowledge specification Knowledge Portal and Repository CDS Knowledge Content and Public Web Services Evaluation Dissemination

Thank you!

Blackford Middleton, MDbmiddleton1@partners.org