business case for adoption: the federal perspective copyright 2009. all rights reserved. 1

Business Case for Adoption:The Federal Perspective

Copyright 2009. All Rights Reserved.1

Copyright 2009. All Rights Reserved.

Quality Improvement Opportunities Using CONNECT

A Proof of Concept for Changing theTraditional Methods of Data Exchange

Michael ReinholdActing Deputy Group Director, Information System Group, Office of Clinical Standards and Quality, Centers for Medicare and Medicaid Services

Quality Improvement

• Delivering Care in a safe, effective and efficient manner

• Ensuring great communication between health care providers and their patients

• Proper and effective stewardship of health care services

• Eliminating redundancy of care

• Ensuring care is evidence-based and outcome-driven to manage and prevent complications from disease

• Educating consumers of health care services

• Rewarding health care providers for quality improvement


The Medicare Electronic

Prescribing Program

The Medicare Electronic

Prescribing Program

The Medicare

HomeHealth Quality

Program

The Medicare

HomeHealth Quality

Program

CMS Quality Initiatives

The Medicare Outpatient Prospective Payment

System (OPPS) Program

•7 outpatient measures

•Clinical Process

•Clinical Outcome


The Reporting Hospital Quality Data for Annual Payment

Update (RHQDAPU) Program

•42 Hospital measures•Clinical Process•Clinical Outcome

The Medicare EndStage Renal Disease

(ESRD) Program

•26 Clinical Performance Measures (CPM)

•Clinical Process

•Clinical Outcome

The Physician Quality Reporting Initiative (PQRI) Program

•153 Physician Office Measures

•Clinical Process

•Clinical Outcome

Current Methods of Data Collection for Purposes of Quality Improvement

Claims Based

• Normal CMS Claims Processing

Electronic Upload (EU)

• Web interface

• Batch or shipped media


Registry or Vendor

• Sending Data to Entity to Submit on Behalf

• Usually Uses One of the Other Identified Methods – EU

Custom

• Web Based Single User Interface – DE

• Extraction Tools for Distribution

Looks Good to Me Why Change Current Methods of Data Collection?


Claims Method

Ven

do

rV

end

or 1122

3344

55

Data lag for Quality decisions and 4-5 major steps where data errors can occur on Quality Data – Never designed for Quality Purposes

BillingSoftware

Carrier/MAC

Internal Transactional

Processes

Payment

Internal Quality Processes

QualityDecisions

• Various Billing Packages not all uniform and no interoperable standards• Cost to update, train, switch and maintain• Not developed for purposes of quality reporting - but billing for payment• Step for errors to occur in data transaction around quality data

• Various systems and internal processes• Costly to update, train, switch and maintain• Not developed for purposes of quality reporting – but billing for payment• Step for errors to occur in data transaction

• Various systems and internal processes• Costly to update, change and maintain• Not intended to ensure quality data is properly captured • Step for errors to occur in data transaction around quality data

• Various systems and internal processes• Costly to update, train, switch and maintain• Not developed for purposes of quality payment– but transactional payment

• Various systems and internal processes• Costly to update, change and maintain -must change based on Claims processing systems • Performed months after initial data submitted• Step for errors to occur in data transaction

• Various systems and internal processes• Costly to update, train, switch and maintain – must change based on Claims processing systems• Performed months after the initial data submitted



Electronic Upload

Ven

do

rV

end

or 1122

3344

Data lag is far less, however, allows for duplication of data submission, training and systems in conjunction with timely submission & feedback issues. Also generally requires a

considerable amount of end user support.

ProviderSoftware

Access/System Registration

Submit Data

Data Processes


QualityDecisions

• Various Packages not all uniform and no interoperable standards

• Cost to update, train, switch and maintain• Often not developed for purposes of quality

reporting – retro fitted or manual interaction to meet program data out needs

• Various systems and processes along with file specifications depending on program • Burden/duplication on training • Feedback submission report issues• Usually limited time for submission depending on program and data required• Usually measure driven not data driven• Step for errors to occur in data transaction around quality data

• Various systems and internal processes• Duplication depending on different specifications • Costly to update, switch and maintain• Extremely resource intensive based on submission periods• Usually measure driven not data driven• Step for errors to occur in data transaction around quality data

• Various systems and internal processes• Duplication depending on different specifications • Costly to update, switch and maintain• Extremely resource intensive based on submission periods• Validation is difficult to perform efficiently

• Various systems and internal processes• Costly to update, train, switch and maintain – mostly due to duplication and lack of interoperability standards• Often does not accommodate timely feedback and data resubmission

• Usually measure driven not data driven• Step for errors to occur in data transaction around

quality data

• Various systems and processes along with file specifications depending on program

• Burden/duplication on training • Feedback submission report issues• Usually limited time for submission depending on

program and data required

• Depending on program variant file specifications must be met

• Leaves room for duplication of data and formatting particularly if participation in many programs/efforts

• Usually measure driven - not data driven• Step for errors to occur in data transaction



Usually disconnected from the Registry system

Usually disconnected from the Registry system

Registry or Vendor

1122

3344

Data lag is far less, however, allows for duplication of data submission, training and systems in conjunction with timely submission & feedback issues. Also generally requires a

considerable amount of end user support.

• Various Packages not all uniform and no interoperable standards • Cost to update, train, switch and maintain• Often not developed for purposes of quality reporting – retro fitted or manual interaction to meet program data out needs• Depending on program variant file specifications must be met• Leaves room for duplication of data and formatting particularly if participation in many programs/efforts• Step for errors to occur in data transaction

• Various Packages not all uniform and no interoperable standards • Cost to update, train, switch and maintain• Depending on program variant file specifications must be met• Quality control issues• Usually measure driven - not data driven

• Various systems and processes to follow depending on what program participation is in• Burden/duplication on training• Can create confusion depending on reporting periods and programs in in more than one

• Various systems and internal processes• Duplication depending on different specifications • Costly to update, switch and maintain• Extremely resource intensive based on submission periods• Validation is difficult to perform efficiently


• Various systems and internal processes• Duplication depending on different specifications • Costly to update, switch and maintain• Extremely resource intensive based on submission periods• Usually measure driven not data driven• Step for errors to occur in data transaction around quality data

• Various systems and processes along with file specifications depending on program • Burden/duplication on training • Feedback submission report issues• Usually limited time for submission depending on program and data required• Usually measure driven not data driven• Step for errors to occur in data transaction around quality data

ProviderSoftware

Registry orVendor


SubmitData

DataProcesses


QualityDecisions



Custom

11

Usually no data lag, however allows for duplication of data submission, training and systems. Also generally requires a considerable amount of end user support to include detailed inquiry support. The biggest con is in

most cases the provider still has to enter the data into their system – duplicate data entry

ProviderSoftware


Provider UsesSystem Interface

Data Processes


QualityDecisions

• Various Packages not all uniform and no interoperable standards • Usually does not interact with Custom interface for data entry• Cost to update, train, switch and maintain• Leaves room for duplication of data entry – The provider system and the Custom interface

• Various Packages not all uniform and no interoperable standards • Usually does not interact with Custom interface for data entry• Cost to update, train, switch and maintain• Leaves room for duplication of data entry – The provider system and the Custom interface

• Various systems and internal processes• Duplication depending on different specifications • Costly to update, switch and maintain• Extremely resource intensive based on submission requirements• Usually measure driven not data driven• Step for errors to occur in data transaction thus leading to end user frustration and increased inquiry support

• Various systems and internal processes• Duplication depending on different specifications • Costly to update, switch and maintain• Extremely resource intensive based on submission periods• Validation is difficult to perform efficiently thus leading to enormous inquiry support efforts


• Various systems and processes – may collect duplicate data • Burden/duplication on training • Data entry errors• Performance factors may arise• Usually limited time for submission depending on program and data required –manual burden • Usually measure driven not data driven

22Usually requires increased

security requirementsUsually requires increased

security requirements

Usually disconnected from the Custom interface

Usually disconnected from the Custom interface

Summary:Current

• Current methods are not wrong. They were the best way of doing business with the resources and technologies available

• Until new technologies and/or architectures are created we have to live with them

• This means cost increases as quality initiatives and data populations increases

How do we move from here to there ?

10Copyright 2009. All Rights Reserved.

ONE Answer is develop an New Architecture and Method for Data Collection

Nationwide Health Information Network (NHIN) and CONNECT Architecture

Mission

To achieve better quality, value, and affordability of health and wellness services by establishing the Nationwide Health Information Network as the common, secure, nationwide, interoperable network for exchanging health information, and provide this infrastructure with low adoption barriers.

Provides

• Ability to look up, retrieve and securely exchange health information

• Ability to apply consumer preferences for sharing information

• Ability to apply and use the NHIN for other business capabilities as authorized by the health care consumer

• Interoperability Architecture

In short provides a single architecture/method for health care data exchange


A Perfect Business Use Test Case in Practice

Use Test Case/Proof of Concept

The Physician Quality Reporting Initiative (PQRI) program

Currently uses all four current methods of data exchange–

1.Claims

2.Electronic Upload (EU)

3.Registry through EU

4.Custom Data Entry App

Develop new NHIN method to retrieve data required as needed eliminating or simplifying other methods

CMSNHIN Gateway

CMSNHIN Gateway

NHIN CONNECT or other GatewayNHIN CONNECT or other Gateway

EHR Application (Data/Structural Validation)

EHR Application (Data/Structural Validation)

QRDAQRDAHIE DEV InstanceHIE DEV Instance

NHIN GatewayNHIN

GatewayTest QRDA DocumentsTest QRDA Documents

NHINNHINNHINNHIN

DatabaseDatabase

ALS ESB (existing)ALS ESB (existing)

EHR Data Application (Data Parsing and Storage)

EHR Data Application (Data Parsing and Storage)

QRDADocument Processor

QRDADocument Processor

QRDAQRDA


Connect Proof of Concept Goals

• Embark upon a 4 step proof-of-concept:

– Increase/accelerate exposure to NHIN technology and overall business process framework and direction within CMS• Increase business understanding to better influence future design and business

process/policy use considerations

• Increase functional and technical system design – including security and scalability considerations to reduce possible future implementation risk

– Simulation of submission of QRDA data from an EMR, through an HIE, over the NHIN to CMS

• Four steps are planned during the POC:

– Test gateway-to-gateway communication

– Test QRDA exchange

– Enhance gateway to integrate and comply with current Quality systems components

– Pilot test with other HIEs and possibly other relevant stakeholders


Important Points

• Following NHIN Interoperable standards CMS should be able to integrate and enhance gateway to comply with current Quality systems components and increase overall functionality with other Quality systems/programs

• Once integration is complete and data exchange is proven from an HIE CMS can :

– Pilot test with other HIEs and possibly other relevant stakeholders

– Provide feedback on any NHIN improvement areas

– Expand testing to other Quality Programs

– Obtain and provide feedback on quality data sooner

– Lessen the burden on external stakeholders that belong to HIE’s or are an HIE that have adopted the NHIN architecture standards

– Reduce redundancy in systems and data request

– Expand quality measurement data specifications to EHR vendors

– Continue to work with standards organizations such as HL7 to expand or modify CDA templates


In Summary

“Technology does not drive change – it enables change”

Following NHIN Interoperable standards and architecture around new technology areas, CMS believes that current methods of Quality Data collection could be simplified to achieve better quality, value, and affordability. As CMS and other organizations adopt the NHIN architecture it will help lessen the burden of data exchange to all stakeholders and help increase quality improvement. CMS is working on enabling change through its various Quality, Medicare, and Medicaid programs!

“Believe you can andyou're halfway there”

“Far and away the best prize that life has to offer

is the chance to work hard at work worth doing”

Quotes byTheodore Roosevelt

Q: WHAT CAN THE SYSTEM DO?

A: WHAT DO YOU WANT IT TO DO?


Enhanced Care Delivery by CONNECTing to the NHIN:Improving Disaster Medical Care

Robert Bencic, DDS, MBACAPT USPHSDirector, QANational Disaster Medical System


Problems Caused by Disconnected Systems

Patients are removed from their typical medical providers and care plan

Inability to acquire patient care information from other Federal partners (DoD, VA, SSA, IHS, CMS)

Inability to share information among various response locations in a federally declared disaster

Inability to quickly send data to other healthcare providers


Expected Benefits from CONNECTing to the NHIN

• Access to medical data from other deployment locations

• Enable the acquisition of patient information from other federal departments (VA, CMS)

• Lay groundwork for future information sharing with non-federal government entities (hospitals, pharmacies, urgent care centers, and state programs)

• Enhance the usability of NDMS Disaster Medical Information System (DMIS)


DMIS Continuum of Care


What This Means for the Rest of the Healthcare Industry

• NDMS can leverage ONC’s standards and achieve its goal of having a standard framework for retrieving and sending patient data to other healthcare providers

• CONNECT software will minimize the in-house development time and costs

• Leveraging standard CONNECT software enhances patient care while minimizing limited implementation resources



CONNECTing the Indian Health System

James Garvie, CAPT, USPHS

Deputy Director, Division of Information Resources

Indian Health Service

IHS as a Provider of Health ServicesAmerican Indian and Alaska Native Healthcare

EXPECTEDOUTCOMES

• Information at the point of care from all Indian health system sources.

• Immediate access to patient, provider and essential health resource information.

• Secure messaging throughout the Indian health system.

SECURE EXCHANGEOF INTEROPERABLE

HEALTH INFORMATION

CONNECT Solution

Patients

PopulationHealth

Providers

• Information tends to be facility-based and is generally not available to staff at other IHS, Tribal or Urban Indian facilities.

• There is no central registry of Indian health system patients, providers and other resources.

• Secure messaging is not available among Indian health system facilities.

CHALLENGES


IHS as a Payor for Health ServicesAmerican Indian and Alaska Native Healthcare

EXPECTEDOUTCOMES

• Information at the point of care from all health system sources.

• Complete, clinically relevant information.

• Seamless sharing of health information by all healthcare providers.


HEALTH INFORMATION

CONNECT Solution

Patients

PopulationHealth

Providers

• IHS and Tribal programs purchase health services that are not available within the Indian health system.

• Information regarding purchased care conforms to financial formats and is often clinically incomplete.

• Purchased care providers generally do not have electronic health record systems.

CHALLENGES


IHS and Population HealthAmerican Indian and Alaska Native Healthcare

EXPECTEDOUTCOMES

• Increased standardization among states for notifiable disease reporting.

• Increased standardization among registry oganizations.

• Direct, bidirectional exchange of information between EHRs and reporting, registry organizations.


HEALTH INFORMATION

• Notifiable disease reporting capabilities vary considerably among states.

• Immunization and disease registry functionality is inconsistent among collecting organizations.

• Reporting is usually paper-based, sometimes via web portal and rarely from an electronic health record system.

CHALLENGES

CONNECT Solution

Patients

PopulationHealth

Providers


CONNECTing the Indian Health System

Facilities Facilities Facilities

Integration EngineMPI

IHSAdapter/Gateway

IHSAdapter/Gateway


TribalAdapter/Gateway

TribalAdapter/Gateway


UrbanAdapter/Gateway

UrbanAdapter/Gateway

Internet


A Snapshot of Success:CONNECT’s Demonstrated Achievements

Dr. Taha Kass-Hout, MD, MS

BioSense Program Manager

US Centers for Disease Control and Prevention


Web Search Volume Screenshot

Source: GI4SCopyright 2009. All Rights Reserved.27


Source: GI4S


iPhone App Store Analogy

Photos Credits: Raven Zachary and Scott Janousek


Enhanced Care Delivery: Problems Caused by Disconnected Systems

• Critical data needed for surveillance is not captured in many instances

• Acquired information is not received in a timely manner

• Public health interventions are delayed

• Ability to communicate critical messages to the medical community is impaired

• Community health programs are not designed and monitored effectively


Enhanced Care Delivery:Expected PH Benefits from CONNECTing to the NHIN

• Enhanced surveillance capabilities to support situational awareness and notifiable disease scenarios in a timely manner

• Integration of relevant public health information into decision support processes effective response

• Improved community health intervention and evaluation processes

Reduce Morbidity and Mortality and Improve Outcomes


BioSense Strategy Overview


Present Strategy:Present Strategy:

• Situational awareness

• Syndromic monitoring and electronic laboratory reporting pilots

• Centralized model with CDC stewardship of data

• State systems, national sources, & individual hospitals

Next Generation:Next Generation:

• Sharing of aggregated (summary) data across jurisdictions

• Social networking model Trust

• Federated model with joint state & CDC stewardship Feasibility

• Service Oriented Infrastructure

• Supports many surveillance needs (e.g. ELR)

• State systems, national data sources, NHIN

Biosurveillance using Summary Data

Value of Aggregate Data– Public Health surveillance/quality monitoring

– Response to natural/manmade disaster

– Cross-jurisdictional situational awareness

GIPSE Format– Provides access to data by leveraging service oriented architecture or grid methods

to expose summaries of data within state and local systems

– Each service returns a set of aggregate counts that map to a common geographic data structure

– Supports aggregation

– Supports computation and testing using spatio-temporal anomaly (e.g., SatScan) methods

– Developed as CDC-hosted open source project

Geocoded Interoperable Population Summary Exchange (GIPSE) Services


Biosurveillance using Summary Data

• CDC uses NHIN Gateway to subscribe to summarized Biosurveillance data from State Health Departments (SHD)

• SHD’s publish summarized biosurveillance data via NHIN Gateway

• CDC aggregates and visualizes summarized data using Quicksilver or other summary data viewers

Geocoded Interoperable Population Summary Exchange (GIPSE) Services

1. Subscribe to Biosurveillance Data

2. Publish Summarized Biosurveillance Data

CONNECTGateway

CONNECTGateway

CONNECTGateway

1. Subscribe to Biosurveillance Data

3. Quicksilver Viewer


Date range

Zip

co

des

1,2,3,5,0,6,…

2,1,4,7,0,3,…….….….

Aggregates (e.g.; counts, rates, or alerts)

ILI Abdominal Rash

GIPSEA set of matrices


GIPSE+ adds cross tabulation on age category and gender

Age Cat

egory

Date range

Zip

cod

es

Gender

Date range

Zip

cod

es+

ILI


National Biosurveillance Model: Summary Perspective

GIPSE SERVICESREGISTRY

GIPSE SERVICESREGISTRY

Sum

mary D

ata Bus

Systems

CLIENT VIEWER Authenticated

Partners

State Health Departments



CDC

National Poison Control Center

Regional HIE

Local Health Departments

Hospitals, Clinics, etc.

NHIN Gateway

DISTRIBUTE

BIOSENSE

ESSENSE

RODS

POISON DATA

Summary Data SourceSummary Data Source

Summary Data Source

NEDSS

Clinical Data Source


Cardea

Cardea is a platform and a set of services that build a general purpose interface to support message

transformation and workflow intelligence between a healthcare system/laboratory/health information

exchange and public health

BioSense Integrator Pilot in GA, 2009


What This Means for the Rest of the Healthcare Industry?

• Enhanced surveillance capabilities are an important component in improving the overall health of the population, serving to reduce health care costs

• Quality of care can be positively impacted when clinicians have easy access to important public health information

• Health disparities can be recognized, assessed and evaluated more effectively with more robust surveillance capabilities

Enhanced Care Delivery


Thank You!

Taha Kass-Hout, MD, MS

BioSense Program Manager

Centers for Disease Control and Prevention

Les Lenert, MD, MS, FACMI

Director, National Center for Public Health Informatics


Barry Rhodes, PhD

Division of Emergency Preparedness and Response (DEPR) Director (Acting)




Business Case for Adoption:National Cancer Institute/caBIG

George A. Komatsoulis, Ph.D.Deputy Director

NCI Center for Biomedical Informatics and

Information Technology (CBIIT)


Individualized, Targeted Cancer Care

= NCI Community Cancer Centers

NCI Cancer Research Enterprise


= NCI-Designated Cancer Centers= CCOPs

The cancer Biomedical Informatics Grid (caBIG)

was initiated in 2004 to connect the disparate parts

of the cancer community via a semantically

Interoperable Service Oriented Architecture (SOA)

Clinical Research

PathologyMolecular Biology

Imaging

caBIG® Enables All Major Functions Needed to Link Research to Care


Clinical Research

PathologyMolecular Biology

Imaging

caBIG® Enables All Major Functions Needed to Link Research to Care

• Track clinical trial registrations

• Facilitate automatic capture of clinical laboratory data

• Manage reports describing adverse events during clinical trials

• Utilize the National Cancer Imaging Archive repository for medical images including CAT scans and MRIs

• Visualize images using DICOM-compliant tools

• Annotated Images with distributed tools


• Combine proteomics, gene expression, and other basic research data

• Submit and annotate microarray data

• Integrate microarray data from multiple manufacturers and permit analysis and visualization of data

• Access a library of well characterized, clinically annotated biospecimens

• Use tools to keep an inventory of a user’s own samples

• Track the storage, distribution, and quality assurance of specimens


NCI caGrid Portal Screenshot

December caBIG/NHIN Demonstration:Partnership that Promotes Child Care

Demonstration illustrated:• Methods for physicians conducting clinical trials to obtain health

history and treatment information

• Methods for sharing details about care received during trial

• Ways to share care information with future healthcare providers

• How continuity of care can be achieved through partnerships between federal and private care providers


Integrating with the NHIN

Subject DiscoverySubject

Discovery

Document Query

Document Query

Document Retrieval

Document Retrieval

Subject DiscoverySubject

Discovery

Document Query

Document Query

Document Retrieval

Document Retrieval

NHIN Services(WSDL)

caBIG® Services(WSRF and WSDL)

INTRODUCE Generated caGrid Service Wrappers


NHIN and caBIG® Moving Forward

• A caBIG® compatible NHIN solution is simply a matter of capturing the semantics of the service

– Provides both a Grid Service and a conventional Web Service

• A “caBIG® compatible” NHIN gateway could be deployed at caBIG® participating institutions (that have significant expertise in deploying caBIG® technology)

• Similarly, caBIG® could become “NHIN compatible” by supplying caBIG® compatible versions of NHIN services


Leveraging the NHIN to Improve the Disability Determination ProcessAuthorized Release of Information

Justine PieremanSenior Advisor to the Office of the Deputy Commissioner for Systems Social Security Administration


An American First: The TelegraphHuman-to-Human Transmission of Text Over Wire

• Innovation supported by the Congress

• First test - Baltimore to Washington – 38 miles

• Standardized language (Morse Code)

• Rapid expansion by private sector

• Benefits to citizens

– Expansion of commerce

– Immediate access to news


Another American First: Live patient transfer across the NHIN

This one-way electronic transfer of patient data between MedVirginia, a regional health group, and the Social Security Administration will enable SSA, with the patient’s authorization, to obtain medical records for the disability review process in minutes instead of the current weeks and months.

NHIN

Patient Information

Patient Information


The Face of Disability


Nationwide Health Information Network

SSA NationalComputer System

Claimant Electronic Folder

Med Records

Labs

Background

SSAFieldOffice

DECISIONMADE

Auth. To ReleaseMedical Records

DemographicInformation

NHIN

InformationAvailable

About Claimant

DETERMINATION RECOMMENDATION

StateAgency

Med Records

Labs

Background

CO

NN

EC

T

Phone, Web,In-Person

St. Francis Medical Center

St. Mary’s Hospital

Richmond Community Hospital

Memorial Regional Medical Center

+Additional

Providers brought to the

NHIN throughARRA and other mechanisms in

FY2009 and beyond


Enhanced Care Delivery by CONNECTING to the NHIN

Dr. Steve Steffensen

Chief Medical Information Officer

Telemedicine & Advanced Technology

Research Center


74% 70% 59% 56%

CONUS Military Bases

1:4 military families move in a given year<50% of network consults make it back to the PCM

Department of Defense Commitment to Care

Military Beneficiaries: 9.3 million

Military Bases in US: 202

Military hospitals 63 Medical/Dental Clinics 826

Encounters/month 9 million Average outpatient visits/year/patient 4


Federal and Private Partnership

Dr. Tim Cromwell

Director, Standards and Interoperability

Office of Health Information

Veterans Health Administration

Jamie Ferguson

Executive Director of Health IT Strategy and Policy Kaiser Permanente


Introduction

• The US Department of Veterans Affairs (VA) and Kaiser Permanente (KP) have collaborated on clinical standards development and other interoperability issues prior to NHIN

• Our limited production implementation sharing standardized health information for patient care will go live late in 2009

• Our teams have been meeting regularly, working to resolve a myriad of issues in three main areas:

– Technical capability

– Operational preparedness

– Policy

• We think we have a story to tell about what we have done so far

– Lessons learned

– Challenges remaining


Outline

Introduction

Business Case

VA | KP

Challenges

Technical | Operational | Policy

Conclusion


Business Cases

Veterans Affairs

• 3 out of 4 Veterans receive care in the private sector

• More and more private sector providers will use EHRs

• Complete set of data will lead to better quality of care

• Veteran satisfaction with overall care will be higher

• Executive Order 13410 mandates use of recognized standards for Agencies

Kaiser Permanente

• Many thousands of KP members receive care from VA

• Improved information can help clinical decision-making

• Complete set of data will lead to better quality of care

• Opportunity to avoid duplicate or conflicting clinical orders

• Additional cost reduction from automation of manual processes

• Executive Order 13410 mandates use of recognized standards for FEHB carriers


VA

• Lab environment in 2008 Trial Implementation

• Internal development environment

• CONNECT Gateway received from FHA

• Adapter developed internally

• Test

• Test databases, test systems, test patients

• Production environment

• TBD

• KP

• Test environment remains from 2008 NHIN Trial Implementation

• Internal development environment

• Internally-developed NHIN Gateway (not using FHA CONNECT software)

• Shared environments with EHR systems and other internal systems

• Production environment

• TBD

Technical:Physical Environments


Technical:Interfaces to Existing Systems

VA

• Viewer: VistAWeb

• Data sources: 128 VistA instances

• Terminology translation services

• Translation to HITSP specified terminology

• CPP for consumer permissions & enterprise policies

• Will enforce authorization, auditing, authentication

• KP

• Web services interface to EHR

• Patient demographics

• Clinical data

• Separate interface for document storage subsystem

• Separate interfaces for enterprise services, e.g. audit logs, system monitoring


Technical:Content Payload

VA and KPHITSP C32 patient health summary

• Version 2.1 - Minimum data set

• Personal information

• Contacts

• Allergies

• Medications

• Problems

• Source of information

All required data elements in the

specified HITSP terminologies to the

extent possible, others optional

(pending NHIN certification criteria)


Policy:DURSA

VA and KP

•2008 test patient data

DURSA signed

•2009 live patient DURSA finalized/ in

clearance, and under review by VA

and KP management

• DURSA overview (plain English)

available


Policy:Shared Patient Population in the San Diego Area

VA and KP•Oversight by our legal and privacy officers

•Analysis indicates approximately 1400 patients

• seen within last year at VA

• a standing appointment for next year

• With a secondary insurance indicating KP

• No sensitive diagnoses

•Confirmation of the list of potential shared patients among our two organizations is working its way through permissions to share


Operational:Patient Consent

VA and KP• Emulating existing manual/paper workflow

• 1 letter

• 2 authorizations

• 1 return envelope

• 1 help desk

• Processing of return envelopes at local San Diego VAMC

• Final workflows subject to approval


Operational:Authority To Operate

• VA

• VA has formal process for certification and accreditation

• 600 Enterprise Requirements reviewed to assess which ones apply to VA NHIN solution

• Document compliance traceability

• KP

• KP not subject to internal federal agency requirements

• KP process addresses similar points somewhat differently

• Design reviews

• Project reviews

• Requirements analyses and documentation

• Solutions analyses and documentation


Operation:VA-KP Schedule


Item

Title KP date VA date Agreed date

1 VA and KP validate initial shared patients under active care - 6/12 6/12

2 Forms and letter defined 6/19 6/19 6/19

3 Patient authorization processing process defined 6/26 6/26 6/26

5 VA and KP validate final shared patients under active care 7/03 - 7/03

7 Gateway 2.1 certification by NHINC (connection to FHA) soap 1.2 - 7/17 7/17

8 Regression test of KP/VA CCD exchange across NHIN soap 1.2 complete 7/15 7/20 7/20

9 Forms and letters ready for mailing 7/24 7/24 7/24

11 KP/VA doc exchange across NHIN Kaiser C32s generated on demand 6/30 7/29 7/29

12 Patient authorizations mailed 7/31 7/31 7/31

13KP/VA subject discovery inter-gateway integration test complete (using test patients from forum)

8/14 8/14 8/14

14 San Diego face-to-face demos with KP and VA local clinical staff 8/24 8/24 8/24

15 End-to-end integration test complete (using test patients) 8/28 8/28 8/28

19 Patient authorization returns processing complete TBD TBD TBD

21 Pre-prod verification of both KP and VA environments (setup for UAT) TBD TBD TBD

22 Deployment to production TBD TBD TBD

23 KP/VA UAT begins (end-to-end using shared patients that opted-in*) 9/28 TBD TBD

24 KP/VA GO LIVE (Full Deployment) TBD TBD TBD

Operational:Local Sites Involvement

• VA

• San Diego VA Medical Center & Clinics

• Support from Chief of Staff and Director of informatics

• Assist with patient consent

• Assist with clinicians training (little training required as same GUI is used to access remote VA sites or NHIN ‘sites’)

• KP

• San Diego KP Medical Center & Clinics

• Support from Assistant Medical Director, Chief Medical Information Officer and Regional Director KP HealthConnect, local physician lead

• Clinician involvement in screen design

• Assist with patient consent

• Assist with clinicians training


VA

• Pilot in San Diego must help refine national rollout plan

• Usage metrics will be incorporated in software

• Patients count

• Clinicians count

• C32s exchanged count

• C32s content stats

• Impact on workflow

• Impact on quality

• Cost of system

KP

• NHIN membership

• Pilot in San Diego will inform national rollout plan

• Measures under development

• Care Quality

• Clinical Workflows

• Financial

• Other

Operational:Measures of Success


Operational:NHIN/FHA Support

VA and KP

• NHIN participation

• Varying roles:

• HITSP, IHE, SDOs;

• NHIN (spec factory/testing criteria);

• NIST (tools);

• CCHIT

• NHIN Cooperative workgroups

• DURSA, Specification Factory, Testing, …

• NHIN/ONC/FHA staff support

• Vanessa/Virginia, Craig/Dave, Mariann/Jeff, etc.


Operational:Stakeholders Buy In

VA

• Presentations and demonstrations

• VSO, IDMC, CPRS WG, etc.

• Regular stakeholders status report

• Business, clinical, and technical staff kept informed from national office and local San Diego VAMC

KP

• Senior leadership support

• CIO, CEO, SVP’s

• Physician leaders

• Presentations to Regional Operations staff & managers

• Governance groups

• IT

• Business

• Clinical


Next Steps:VA and KP

TESTING & CERTIFICATION

Limited Production Roll Out in San Diego

Training and Communication

Measurements

Lessons learned

SECOND, THIRD, … ADDITIONAL SITES

SCALABILITY PLAN – TOWARD NATIONAL RELEASE


Contact Information

VA contact

Tim Cromwell, RN, PhD

Director, Standards & Interoperability

Office of Health Information

[email protected]

801-588-5022

KP contact

Jamie Ferguson

Executive Director, HIT Strategy & Policy

[email protected]

510-271-5639


CONNECT Seminar

Presentations are Available

for Download Online at http://www.connectopensource.org


business case for adoption: the federal perspective copyright 2009. all rights reserved. 1

Documents

purposes of quality

quality data various

purposes of quality

quality improvement

data errors

data lag

health care providers

payment step