Evolving EHealth Business Processes Around Accessible Data Warehouses

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Evolving E-Health Business Processes Around
Accessible Data Warehouses

• Background information for demonstrations
• January 24, 2007

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Agenda

• Overview of ORNEC
• Overview of project and team
• Discussion of major activities and
  accomplishments
• Simulation of Ottawa Hospital Data Warehouse and
  environment
• Business Intelligence prototype Infection
  control data mart
• Business Process Modeling Discharge process
• Requirements engineering Quality indicator
  survey
• Others
• Challenges Obtaining access to real data/real
  users

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Description of ORNEC

• Ontario Research Network for Electronic Commerce
• Partnership between 4 universities and 40
  corporations
• Funded in part by the Ontario government
• Interdisciplinary research involving
• Information and communications technologies
• Business and administration
• Law and ethics
• Goals
• Creation of scientific knowledge, business
  models, and best practices
• Training of highly qualified academic and
  business leaders
• Transfer of knowledge and innovation
• Research Themes
• E-Government, E-Commerce Transactions, E-Learning
  and Collaborative Environments, E-Governance,
  E-Health, and others
• http//www.ornec.ca/

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Project Description

• Evolving E-Health Business Processes Around
  Accessible Data Warehouses
• 2-year project (Jan. 2006 Dec. 2007)
• Funding 525,000, with half this amount in
  in-kind contributions
• Goals
• Process improvement to take advantage of
  e-technologies and DW
• Having good methodologies to describe, analyze,
  evolve, manage, support, and automate
  DW-oriented, e-health processes
• Promoting the access to DWs and managing changes
• All goals consider privacy, confidentiality,
  quality, and consent, as well as heavy legacy
  (and often manual) processes and regulatory
  environments

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Project Investigators

• Daniel Amyot (Principal Investigator), Assistant
  ProfessorSchool of Information Technology and
  Engineering (SITE), uOttawa
• Doug Angus, ProfessorSchool of Management, and
  Director, Ph.D. program in Population Health,
  uOttawa
• Alan Forster, Associate ProfessorDepartment of
  Medicine, uOttawa, and Scientist, Clinical
  Epidemiology, Ottawa Health Research Institute
• Michael Weiss, Assistant ProfessorSchool of
  Computer Science, Carleton University
• Liam Peyton, Assistant Professor School of
  Information Technology and Engineering (SITE),
  uOttawa

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Project Partners

• Provides Cognos 8 (most tools)
• with setup, training, and consulting
• Contacts Rupert Bonham-Carter, Gerry Leavy
• Provides (discounted) Adaptive Server Enterprise
  and IQ
• with setup and training
• Contacts Dan Murphy, Ahmadou Monfopa
• Provides DOORS and FocalPoint
• with training and support
• Contacts Frank J. Araby, Chris Sibbald

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Students, Staff and Collaborators

• Students involved in this project
• Saeed Behnam, PhD Computer Science
• Pengfei Chen, MSc Computer Science
• Sepideh Ghanavati, MSc Systems Science
• Jason Kealey, MSc Computer Science
• Sarah Musavi, Masters in Health Administration
• Gunter Mussbacher, PhD Computer Science
• Alireza Pourshahid, MSc E-business Technologies
• Jean-François Roy, MSc Computer Science
• Pierre Seguin, MSc. Computer Science
• Bo Zhan, MSc Computer Science
• uOttawa staff and collaborators
• Jacques Sincennes, System analyst
• Greg Richards, Cognos Professor of Performance
  Management
• TOH collaborators
• Cameron Keyes, Director (Acting), Decision
  Support
• Richard Ciavaglia, Decision Support
• Laurie Strano, Decision Support
• Sylvain Paquette, Consultant

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Research Focus

• Develop new methods to model, analyze, and evolve
  business goals (why) and business processes
  (what/who/when/where) based on the use of goals,
  scenarios, and aspects, and adapted to
  DW-oriented e-Health services.
• This will in particular lead to suitable ways of
  exploiting the DW for trends and goal-driven
  decision support, and allow us to determine how
  the right data can be made available by the right
  individuals in the chain of care at the right
  level of detail, and how this data can best be
  accessed.

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Project Tasks

• Study goal-driven and quality-driven decision
  making in an e-health context
• How to map goals to business processes to data
  requirements in a DW, and goals to reports or
  analytics
• Goal example improve patient safety at a
  teaching hospital
• Study the suitability and relevance of recent
  developments in requirements engineering,
  decision support, and business intelligence
• Study how best to combine goal-, scenario-, and
  aspect-oriented modeling for process modeling and
  requirements engineering
• Study and model relevant processes
• For example providing data to the DW, managing
  changes in the DW requirements, secure access for
  various stakeholders, etc.
• Replication of TOH work environment for lab study
• Prototyping support for some of the processes
  using the lab facilities

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Description of DW Project _at_ TOH

• Multiphase project
• Collaboration between OHRI scientists, TOH
  Information Systems
• Phase 1 Building the DW for researchers
• Funded through a CFI grant
• Nearing completion
• Phase 2 Using DW for administrative purposes
• Investigation now underway
• Identify key users
• Access through a BI toolkit

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Combining Healthcare and IT

• Examples of Clinical / Healthcare Issues
• Nosocomial infections
• Drug costs
• Bed utilization
• Improving the safety of the discharge process
• Information Technology Issues
• Data needs, integration, quality, access, and
  reporting
• Information Technology Opportunities
• Data Warehouse (for integration and access)
• Business Intelligence tools (for reporting)
• Requirements Engineering (for needs and
  surrounding processes)

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Agenda

• Overview of ORNEC
• Overview of project and team
• Discussion of major activities and
  accomplishments
• Simulation of Ottawa Hospital Data Warehouse and
  environment
• Business Intelligence prototype Infection
  control data mart
• Business Process Modeling Discharge process
• Requirements engineering Quality indicator
  survey
• Others

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Data Warehouse Simulation

• Intelligent Data Warehouse Lab (U. Ottawa)
• CFI grant with IBM provides
• Powerful servers and software
• 10 Terabyte Storage Area Network (SAN)
• ORNEC project with Ottawa Hospital provides
• Cognos 8 BI, Metrics Studio, Sybase IQ ASE
• Telelogic DOORS and FocalPoint, jUCMNav
• Same database schema as The Ottawa Hospital
• Test data generator
• Apply for an anonymous data extract

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Demonstration / Learning Vehicle

• Students, Researchers (and Ottawa Hospital) have
  access to
• Configuring and designing the environment
• Hands-on training and mentoring (from Cognos)
• Courses
• Creation of sample applications and processes
• Antibiotics Tracking
• Discharge process

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Integrating Data Warehouse
Data Marts
End-User Access
Operational Feedback
Data Extraction Transformation
Data Warehouse
Data Extraction Transformation
Operational Systems
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Agenda

• Overview of ORNEC
• Overview of project and team
• Discussion of major activities and
  accomplishments
• Simulation of Ottawa Hospital Data Warehouse and
  environment
• Business Intelligence prototype Infection
  control data mart
• Business Process Modeling Discharge process
• Requirements engineering Quality indicator
  survey
• Others
• Challenges Obtaining access to real data/real
  users
• Next steps

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Data Mart Extract For Infection Control
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Performance Management Portal
Key Metrics
News Feed
Important Links
Antibiotics Tracking
Campus Dashboard
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Drill into General Campus
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Drill into Surgery
Drill into Most Prescriptions
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Drill into metric
Balanced Scorecard
Metric History
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Dimensional Model
Report Authoring
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Performance Management Infrastructure

• Data Mart cubes or extracts
• Multi-dimensional snapshot with drill up and
  drill down
• Pre-packaged security roles
• Ethics and privacy review
• Performance Management Portal
• Dashboards, flexible end-user tools for
  reporting, exploration, and metrics
• Operational Integration
• Data collection, data quality
• Timely effect reports support decision making and
  track targets, Service-Level Agreements (SLAs)
• Business process improvements, transformations

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Assessment Framework Tied to Operational Systems,
Performance MGT Data Warehouse Strategy
Stakeholders
Use Case Maps
Goals
Reports
PIQ
Tasks
Business Systems Processes
Performance Mgt Systems Processes
PIQ measures the effectiveness of Reports to
measure effectiveness of Organization in meetings
its goals.
Data Warehouse
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Assessment Framework Tied to Operational Systems,
Performance MGT Data Warehouse Strategy

• Identify stakeholders, goals, tasks and use case
  maps to capture requirements and specify
  operational systems
• Identify reports needed to measure attainment of
  goals, inform tasks
• Measure importance of reports (related to goals)
• Measure quality of reports (related to tasks,
  goals)
• Measure penetration of reports (related to
  stakeholders, goals)
• Measure effort, cost, timeliness, scalability,
  reliability etc. of data collection, report
  creation, and distribution (effectiveness and
  efficient)
• Performance MGT/Data Warehouse strategy and
  implementation defined and driven by Reports PIQ

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Agenda

• Overview of ORNEC
• Overview of project and team
• Discussion of major activities and
  accomplishments
• Simulation of Ottawa Hospital Data Warehouse and
  environment
• Business Intelligence prototype Infection
  control data mart
• Business Process Modeling Discharge process
• Requirements engineering Quality indicator
  survey
• Others

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Overview of Approach
Which reports to generate?
What data to collect?
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Goal Patient Safety
Governance Process
Discharge Process
Medical Management
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Approach BPM
Redesign
Collect
Monitor
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Process Design and Evolution

• Identify goals and indicators (GRL)
• Model the process (UCM)
• Monitor process execution (DW)
• Generate data mart (DM) and reports (BI)
• Redesign process (redesign patterns)

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jUCMNav Goal model editor/analyzer(GRL)
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jUCMNav Process model editor/analyzer(UCM)
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Goals and Indicators
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Monitoring and Redesign
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Discharge Process
Start
End
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Discharge to Other Process
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Dictate Process

• Indicators
• Delay between dictation and transcription time
• Delay between discharge and dictation time
• Percentage of patients that are delayed over
  three months (one month, one week)
• Percentage of incomplete dictations

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Report Time Lag in Campuses
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Drilling Down General Campus
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Report Time Lag in Services
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Drilling Down General Medicine
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Drilling Down Guimarães Rosa, João
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Predefined Reports
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Agenda

• Overview of ORNEC
• Overview of project and team
• Discussion of major activities and
  accomplishments
• Simulation of Ottawa Hospital Data Warehouse and
  environment
• Business Intelligence prototype Infection
  control data mart
• Business Process Modeling Discharge process
• Requirements engineering Quality indicator
  survey
• Others

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Quality Indicator Survey

• Identified 78 quality of care indicators.
• These indicators consist of a patient population
  and a treatment. Examples
• Patients with atrial fibrillation should be
  prescribe warfarin unless there is an important
  contraindication
• Patients hospitalized due to an asthma
  exacerbation should be treated with beta-agonists
  
• 14 participants from TOH
• Asked to determine which indicators were the most
  important
• A quality of care indicator is important if
• the patient population is large (i.e.
  diagnosis/condition is highly prevalent)
• the treatment is highly effective and easily
  available to most patients
• there are few patients in whom the treatment is
  contraindicated and,
• in your role as an attending physician on CTU,
  you frequently treat this population.
• Survey performed with the help of a new Web-based
  tool we developed
• Answer collection and prioritization
• Analysis of actual data vs. goal satisfaction
  using clustering
• Reports (on-line and PDF) generated via Cognos BI
  tools

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Online Survey Tool Allows for secure questionnaire
s to be filled and answers (indicators,
requirements, etc.) to be prioritized
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Some Survey Results

• Quality indicators reflecting treatment decisions
  were rated higher than those reflecting
  investigation decisions
• Example For myocardial infarction, internal
  medicine physicians felt it was more important to
  prescribe ASA than to order lipid profiling
• Good agreement on the main indicators for
  Civic/General campuses
• Top 5 very similar
• Not all diseases surveyed have important
  indicators
• For instance, pneumonia is very common yet its
  current indicators scored second last
• We also received feedback to improve the survey
  tool itself.

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Survey Next Steps

• Go back to the doctors to discuss and validate
  the results
• Design appropriate data marts for the top
  priorities
• Create portals for these indicators
• Get access to the real data and deploy the
  portals/reports

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Overview of Other Activities Using DWs

• Literature survey on uses and challenges of DW in
  the health sector
• Report available (S. Musavi)
• Joined the Health Data Warehouse Association
  (HDWA)
• Excellent networking opportunity
• Attended their annual conference in June (J.
  Blackburn)
• External peer survey
• Experience from peer organizations in HDWA and
  Canada
• Approved by the TOH Research Ethics Board.
• Comparative study
• Approaches for implementation of DW in
  publicly-funded healthcare organizations (S.
  Musavi)
• Canadian Blood Services and The Ottawa Hospital
• Look at effectiveness of current reports (G.
  Richards)
• Coming soon pharmacy technician to clean data in
  DW
• Drug frequencies, routes, names

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Overview of Other Activities Compliance

• Modelled governance process to access patient
  data via the DW
• Goals/processes documented with jUCMNav (S.
  Ghanavati)
• Linked to Personal Health Information Protection
  Act (PHIPA)
• Establish compliance and check compliance as the
  law and the business process evolve over time.
• Integration of model with Telelogic DOORS

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Overview of Other Activities Tools

• Tool support for business goal/process models
• Improved jUCMNav tool substantially editing,
  analysis, export (J. Kealey)
• Improved the User Requirements Notation itself to
  explore aspect-oriented modelling (G. Mussbacher)
• Might ease the description and analysis of
  evolving goals / processes
• Business Intelligence tools
• Training of students and partners on Cognos BI
  tools
• Created tool to generate fake but representative
  data to simulate existing DW (B. Zhan)
• Performance evaluation of Cognos BI tools
• Heavy usage of DW, growing/evolving DW, etc.
• New descriptor tool, based on SAS (A. Forster)
• Could be used as a preprocessor for BI tools
  (e.g. Cognos)
• New graduate course on the use of databases for
  measuring healthcare quality
• To be offered for the first time in January 2007
  (A. Forster)

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Agenda

• Overview of ORNEC
• Overview of project and team
• Discussion of major activities and
  accomplishments
• Simulation of Ottawa Hospital Data Warehouse and
  environment
• Business Intelligence prototype Infection
  control data mart
• Business Process Modeling Discharge process
• Requirements engineering Quality indicator
  survey
• Others

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For Further Information

• Daniel AmyotAssistant ProfessorSITE, University
  of Ottawa(613) 562-6800 ext. 6947damyot_at_site.uot
  tawa.ca
• Web sitehttp//cserg0.site.uottawa.ca/twiki/bin/
  view/EHealth/WebHome