Building Enterprise Portals for knowledgebased, integrated, patientcentered Healthcare systems in IR

1
(No Transcript)
2
Building Enterprise Portals for knowledge-based,
integrated, patient-centered Healthcare systems
in IRANStrategy and Methodology

• A.Zamani
• DDS MSc
• (MCSD)
• Takfab Advisor,
• Health information architecture

3
Information Data
requirments
Educational data
Statistics
Menal health
Customer registry
Human res.
Connection with other provinces
Public health
Continuing care
Clinical documentation
Financial sys
offices
Pharm acies
EMS
Specialist info
labs
Labs
E commerce
Standards
Documen tation
Radio logy
EMS
outpatients
Radiology
EMPI
EMPI
Patient admin
Registration
Rehabili tation
pharmacy
Other Adminstrative Sys.
Regist ration
Images
Drug management
Primary Health Care
Related gov. organizations
Financial estimations
Care Follow up
Program Reg.
Care projects
Registraion
EMPI
EMS
City centers
Labs/Private sector
National registries
NGO in health
4
What we need to overcome the interoperability and
project management problems in this complicated
area
5
Business as is
6
Architecture Frameworks
7
The architecture must embrace technology that
optimizes business units processes -LMC ITAF
Vol3
An architecture is the structure of
components, their relationships, and the
principles and guidelines governing their design
and evolution over time. -C4ISR Architecture
Framework, Version 2.0
Top-level operational goals, constraints, and
guidance to enable a more coherent and consistent
approach to individual system design and
implementation -FEAD Arch. Terry Mayfield,
Institute for Defense Analysis
8
Frameworks EA Reference Model
IT Architecture Framework
People who Where
Process How When
Technology what
Governance Change Management (Why)
9
Zachman EA Framework

• Row 1 Scope
• External Requirements Definition of the
  Enterprise
• Business Function Modeling

• Row 2 Enterprise Model
• Business Process Modeling and
• Function Allocation

• Row 3 System Model
• Logical Models
• Requirements Definition

• Row 4 Technology Model
• Physical Models
• Solution Definition and Development

• Row 5 As Built
• As Built
• Deployment

• Row 6 Functioning Enterprise
• Functioning Enterprise
• Evaluation

10
Source FEAF
11
Federal Enterprise Architecture (FEA) Reference
Models
12
Methodology UML Mapping
Business Object Class, Use Case Business
Channel Deployment Workflow Activity Rule -
Class
Entity, Relationships, ER Class Fact Tables
Class CRUD Matrix Use Case
User Interface Component Rules - Class
Use Case
Use Case
Object Class
Deployment
Activity
Statechart
OCL
Sequence
Collaboration
Security Class
Tables Class Distributed Component Subject
Area - Package
Component
Declarative Rule Tool Workflow Products Content
Frameworks, etc.
SQL Delete Sequence
Source Equifax
13

• A large government agency found gt20 of the
  applications running on its networks hand no
  users, 80 of data in their data bases was
  duplicated, and 95 of their applications were
  functionally redundant

14
Medical Informatics
National Application Layer
MIS reports
Portal
National
Infrastructure Layer
Local
15
Electronic health record
MIS Shared financial services Electronic staff
record E commerce
KM systems Digital libraries National
information sites Public education
systems Special education systems Online clinical
references
Health systems and services HIS E
prescription Online EMS Telemedicine
The core of the health network ( health portal)
standard HL7
Security standards
Connection standards
application standards
Physical network infrastructure
16
(No Transcript)
17
Modeling
18
Objectives of a Model

• Challenge traditional views of what health
  information is and how it is captured
• Provide a shared understanding across national
  and organizational bias
• Provide tools and methodology to align and bridge
  health information across national and functional
  areas

19
Why We Model Information

• The information gathered in the health sector is
  overwhelming in quantity and variety
• All organizations have processes ( manual or
  automated) that collect data and then transform
  that data into information
• Many of these processes have evolved separately
  at different times, resulting in
• - Compartmentalization and subsequent
  duplication (on a massive scale)
• - inconsistency in representation, meaning, and
  interpretation

20
Model for Many Purposes

• Specification of information for understanding
  meaning
• Specification of data to be shared
• Specification to be managed with a single
  enterprise
• Specification of data for data warehouse or data
  mart
• Specification of data for systems development
• Specification of data base design

21
(No Transcript)
22
Role Link Has Authority Has Part Has Replacement
Act Relationship Has Condition Has
Component Has Outcome Has Relevance Has Sequel
Entity Living Subject Organization Place Material
Role Patient Licensed Entity Access Employee . .
.
Act Observation Procedure Substance
Administration Patient Encounter Account . . .
Participation Ancillary Participant Direct
Target Indirect Target Information
Generator Information Recipient Location Performer
Verifier Custodian Responsible Party
23
(No Transcript)
24
(No Transcript)
25
Tobe
As is
Terminology Stable
Terminology Ontology
26
(No Transcript)
27
Standards
Enhanced
Enhanced
Enhanced
Enhanced
Enhanced
Enhanced
Enhanced
EnhancedHealthand Health Care
Health and
Health
Health and
Health
Health and
Health
Health and
and Health Care
and Health Care
Health Care
Health Care
and Health Care
Health Care
Health Care
Improved
Improved
Improved
ImprovedHealth Information
Improved
Improved
Improved
Improved
Health Information
Health Information
Health Information
Health Information
Health Information
Health Information
Health Information
Health Data Standards
Health Data Standards
Health Data Standards
Health Data Standards
Health Data Standards
Health Data Standards
Health Data Standards
Health Data Standards
28
Metadata Registry Overview
Methods of Finding Data Elements
References to Authoritative Sources

• A metadata registry is a place to keep facts
  about characteristics of data that are necessary
  to clearly describe, inventory, analyze, and
  classify data.
• A metadata registry supports data sharing with
  cross-system and cross-organization descriptions
  of common units of data.
• A metadata registry assists users of shared data
  to have a common understanding of a unit of
  datas meaning, representation, and
  identification.

NCPDP (National Council for Prescription Drug
Program)
Data Elements
ABCDEFGH..
Data Element
Initiatives
Identifying and Definitional Attributes
Data Element ID 07-329-4837.00000692.v1
Name Gender Code
Context X12 Data
Dictionary Definition
Code indicating the sex of the individual
Status Received as of
01/19/1999 Example
Synonyms/Keywords
Comment Data Collection Methods Relational
and Representational Attributes
Data Type ID Representational Form
Representational Layout
Minimum Size 1 Maximum Size 1
Unit Of Measure
Precision Minimum Range
Maximum Range Data Domain
Permissible value Domain Meaning Name
Domain Meaning

Definition Text A
Not Provided B
Not Applicable F
Female M Male
N Non-sexed
U Unknown X
Unsexable Related Data
References Object Relationship
Related Item Type
Gender Code is composite part of X12 Data
Dictionary Standards Alternate Names and
Contexts Name
Context Gender Code X12 Data
Dictionary 1068 X12 Data
Element Number
X12 (American Standards Committee)
Health Insurance Portability and Accountability
Act...
Transaction Set -Data Element
-Composite Data Element
Data Collections
Person_Sex Gender Sex_Category Code ...
Birth Date Hair Color Eye Color Sex ...
HCFA Long Term Care BRFSS
HL7 (Health Level Seven)
Reference Information Model -Subject Area
-Class -Attributes
Data Agreements
What data elements are used?
Where are data elements defined?
X12 NCVHS Core Data NCPDP
NHIM (Australian National Health Information
Model )
Organizations
Model -Model Subtype -Information Model
Subtype -Data Element -Data
Concept -Composite Data Element
-Derived Data Element
CDC AHCPR NCVHS
Codes can be downloaded for use in applications.
Data elements are described in common format.
Source USNHK
29
HUPO Proteomics Standards Initiative
Pharmaco-genomics Standards Initiative
Integrating the Healthcare Enterprise
x12
OMG-LSR
I3C
CDISC
Development Clinical Trial
Healthcare
Research
Clinical/ EHR/ Clinical Genomics
Medical Imaging
HL7
GGF
MGED
HL7
DICOM
30
(No Transcript)
31
Ontology
32
(No Transcript)
33
UMLS Semantic Net
Entity
Event
34
PRM Structure Is Designed to ClearlyArticulate
Line of Sight
Line of Sight is the cause-and-effect
relationship between inputs, outputs and outcomes.
35
A Performance Management Framework
Enables decision-makers to choose the right
initiatives and investments to support
organizational outcomes (through strategy and
budgeting activities)
Ex. Initiatives Business Case Analysis PB
Budgeting Logic Modeling ROI Analysis
Select
Creates the basisfor understanding theimpact of
factors(processes and initiatives)
onorganizational performance (outputs and
outcomes)
Provides the capability to effectively implement
selected initiatives, programs, and other
investments (through project and quality
management activities)
Evaluate
Control
Ex. Initiatives Balanced Scorecard
Ex. Initiatives SEI CMM EVM ISO 9001 PMBOK/PM ABC
36
Example IT Measures

• Service Quality
• Reliability
• Responsiveness
• Competence
• Accessibility
• Courtesy
• System Quality
• Reliability
• Response Time
• Ease of Use
• Usefulness
• Accessibility
• Information Quality
• Currency
• Accuracy
• Timeliness
• Conciseness
• Convenience
• Relevance

• Use
• Subsystem Use
• Relative Usage
• Increases in Usage
• Frequency of Use
• User Satisfaction
• Business Process Impact
• Effectiveness Efficiency Impact
• Service, System, Information Quality

• Workgroup Impact
• Improved Participation
• Improved Communication
• Solution Effectiveness
• Solution Quality
• Organizational Impact
• Outcomes
• Cost Savings
• Improved Service
• Improved Productivity
• Return on Investment

Functional Value
Technical Value
Business Value
37
Building a Performance Culture - Rollout
Mobilize
Manage
Motivate

• Objective
• Initiate change. Gain consensus and
  momentum at the top.
• Communicate!
• Establish Need for Change
• Build Executive Team
• Align the Organization

• Objective
• Disseminate change. Create focus and
  establish new norms throughout.
• Communicate!
• Align the Workforce
• Educate
• Automate
• Feedback, Learn, Reward

• Objective
• Institutionalize change. Use new management
  processes.
• Communicate!
• Evaluate and Analyze
• Plan Budget
• Focus Initiatives
• Review Performance

Rollout activities should correspond to HOW
people change, the STAGES of change, and the best
change LEVERS
38
Evolution of the CIS
39
Different Kinds of Standards

• Company
• Dos
• Windows
• Consortium
• Unix
• Linux
• Industry
• DICOM

• Government
• NIST
• CMS (UB92)
• HIPAA
• Voluntary consensus
• ASTM
• HL7
• NCPDP

40
4. CollabNet Enabling collaborative software
development strategies and communities

Effective Collaborative Software Development
Environments
project workspace
software development applications
technical communication
knowledge management

• - mailing lists
• - discussion
• forums
• document
• and file
• management

- scm - issue tracking - ide integration

• knowledge
• archive
• (lists, forums, code)
• - power search
• - news
• - notification

project administration
application security, role-based permissions
41
PHDSCs Mission (abridged)
PHDSC is committed to bring a common voice from
the public health community to the national
efforts of standardization of health and
healthcare information
Enhanced
Enhanced
Enhanced
Enhanced
Enhanced
Enhanced
Enhanced
EnhancedHealthand Health Care
Health and
Health
Health and
Health and
Health
Health and
Health
and Health Care
and Health Care
Health Care
Health Care
and Health Care
Health Care
Health Care
Improved
Improved
Improved
ImprovedHealth Information
Improved
Improved
Improved
Improved
Health Information
Health Information
Health Information
Health Information
Health Information
Health Information
Health Information
Health Data Standards
Health Data Standards
Health Data Standards
Health Data Standards
Health Data Standards
Health Data Standards
Health Data Standards
Health Data Standards
42
(No Transcript)
43
HL7 Messaging HL7 Standards and Their Uses
ArdenSyntax
V2Messaging
V3Messaging
CCOW
CDA
(XML)
XML
XML
Legend ANSIStandard InBalloting
44
What we need to overcome the interoperability and
project management problems in this complicated
area

• Architecture
• Modeling
• Standards
• Ontologies
• Leading edge technology

45
(No Transcript)
46
(No Transcript)
47
(No Transcript)
48
(No Transcript)
49
The new enterprise vision is about more than
technology
Ensure executive sponsorship strategic
commitment
Establish integrated business processes
Strategic
Processes
Direction
Enterprise
Establish an enterprise culture
Organization/
Technology
People
Provide a new enterprise infrastructure
50
Move beyond the traditional service delivery and
decision making framework
Enterprise to be
Business as is
51
What Every CIO Needs to Know About Metadata

• Quotes from a CIO recommendation paper written by
  the federal government CIO council's
  interoperability committee
• Metadata is one of the biggest critical success
  factors to sharing information and storing
  information cost-effectively. Metadata can make
  your information sharing and storage efforts
  great successes, or great failures.
• Simply put, metadata management is making
  metadata do more things for more people in more
  ways, more economically.
• The alternative to metadata management is
  information chaos.
• http//www.cio.Gov/documents/metadata_cio_knowledg
  e_feb_1999.html

52
Cycle of Necessity
53
The Gartner Enterprise Architecture Framework
54
How complicated and vast is our domain

• All health sectors
• Hospitals
• Education
• Libraries
• EBM
• Change Management
• Cultural issures

55
Modeling

• Information for stakeholders
• Data that is required
• The need of modeling for integration
• Example CHDM Canada

56
Standards

• Different standards
• HL7 v. 3
• RIM ( as a data model)
• Guarantees semantic interoperability
• Is it all that we need for semantic
  interoperability?

57
(No Transcript)
58
(No Transcript)
59
(No Transcript)
60
(No Transcript)
61
Architecture

• Why
• Make everything explicit
• Know to start from where and how
• What
• Zachman
• FEAF
• TOGAF
• Compound