Attacking the Hard Problems of IAIMS

James Cimino

Problems in Clinical IAIMS

• Heterogeneous systems and dataHeterogeneous systems and data

• Tower of BabelTower of Babel

• SustenanceSustenance

Heterogeneous Systems and Data

• Legacy systemsLegacy systems

• Future systemsFuture systems

• MergersMergers

• ““I” stands for “IntegratedI” stands for “Integrated– AccessAccess– Data sharingData sharing– Data aggregationData aggregation

Tower of Babel

• Each system has its own terminologyEach system has its own terminology

• ““Data reusers” need to know the terminologyData reusers” need to know the terminology

• No unifying terminologyNo unifying terminology

• Terminologies changeTerminologies change

Sustenance

• Pilot systems become production systemsPilot systems become production systems

• Temporary solutions become permanentTemporary solutions become permanent

• What to do when the money runs outWhat to do when the money runs out

Joyce Niland

The Hard Problems of IAIMS:The Hard Problems of IAIMS:Information Integration Information Integration across Multiple Systemsacross Multiple Systems

• Authoritative Data Sources Authoritative Data Sources

• Data StewardsData Stewards

• Quality Control ProcessesQuality Control Processes

• Meta DataMeta Data

Authoritative Data SourcesAuthoritative Data Sources

• Myriad sources of overlapping dataMyriad sources of overlapping data

• Differing levels of qualityDiffering levels of quality

• How to identify most authoritative sources?How to identify most authoritative sources?

• Participation of key stakeholdersParticipation of key stakeholders

Identifying Data “Stewards”Identifying Data “Stewards”

• Parties responsible for data Parties responsible for data integrity/securityintegrity/security

• Stewardship rather than ownershipStewardship rather than ownership

• How to obtain “buy-in” to the sharing of How to obtain “buy-in” to the sharing of such data sources?such data sources?

Quality Control ProcessesQuality Control Processes

• Processes in place within data source?Processes in place within data source?

• Quality assurance across data sources?Quality assurance across data sources?

• ““GIGO” magnified exponentially with GIGO” magnified exponentially with integrated data sourcesintegrated data sources

Meta DataMeta Data• Data about the dataData about the data

• How to identify who’s collecting what?How to identify who’s collecting what?

• Elements of the meta data:Elements of the meta data:– Technical directoryTechnical directory– Business directoryBusiness directory

• Content experts criticalContent experts critical

Joyce Mitchell

The Hard Problems of IAIMS

• Organizational issues of the IT/IS GroupOrganizational issues of the IT/IS Group

• Process changes when implementing Process changes when implementing new systems to realize benefits of IT new systems to realize benefits of IT

Organizational issues• One organization for the health sciences One organization for the health sciences

enterprise?enterprise?• Virtual organization for the HSC?Virtual organization for the HSC?• What about autonomous technical people?What about autonomous technical people?• Where should IT unit sit in the HSC Where should IT unit sit in the HSC

hierarchy?hierarchy?• How to create a responsive IT organization?How to create a responsive IT organization?

Organization of IT/IR unit

• Culture of the unitCulture of the unit

• Structure of the unitStructure of the unit

• Internal Economy for funding Internal Economy for funding deliverablesdeliverables

• Methods and Tools Methods and Tools

• Metrics and RewardsMetrics and Rewards

• How it relates to Informatics ResearchHow it relates to Informatics Research

Process Changes to Achieve Benefits

• Analysis of current stateAnalysis of current state• Analysis of future stateAnalysis of future state• What is value of moving to another stateWhat is value of moving to another state• What kind of IT leadership vs process What kind of IT leadership vs process

owner leadership do you need to owner leadership do you need to change processeschange processes

• How to measure benefits of systems How to measure benefits of systems and changes in processand changes in process

Neal Ryan

Research vs. Engineering• ResearchResearch

– Demonstration Demonstration projectsprojects

– ProgrammingProgramming– Experiments that we Experiments that we

don’t know the don’t know the answer toanswer to

– The productive The productive anarchy of academic anarchy of academic competitioncompetition

• EngineeringEngineering– Projects that you bet Projects that you bet

your system onyour system on– Architecture to last Architecture to last

decades and work decades and work robustlyrobustly

– Consensus, Consensus, stakeholders, stakeholders, management by management by objectives, etc.objectives, etc.

Other hard problems

• Brief listing of some other “hard Brief listing of some other “hard problems” brought up at this problems” brought up at this conference.conference.