Data Interoperability
Data Interoperability Supporting Local Agency Information Management Interoperability: The Douglas County Example
Consider
Culture
Compute
Collaborate
Capacity
Collect
Culture ONE person approach to care • We serve the same person • The person owns their data • The person owns their outcome • The funding we receive is for the person
Culture
What is data capacity? Right data, in the Right form, at the Right time, to the Right people
Capacity
Resources
Context Processes, Structure & Software
People Organizational Culture—beliefs and assumptions
Capacity: Identify purpose for interoperability
Increasing Costs Reporting and Analysis Need
Capacity
Presumptive Eligibility and Referral Need
Collaborative Work Need
TRANSFORMATIONAL
Collection Prescriptive • Case Management: Directed • Outcome: Completion • Data: Planning
Generative • Case Management: Engagement • Outcome: Change • Data: Change
UNIQUE UNIFORM Provision • Case Management: Determination • Outcome: Delivery • Data: Eligibility
Collect
TRANSACTIONAL
Navigation • Case Management: Connection • Outcome: Access • Data: Service records
Collaborate Pick your initial collaboration partners • include engaged representatives with varying perspectives into the whole of your business • Include technical expertise where you can, but don’t get into the weeds on data models yet • Focus more on data as a portable, self-contained entity and less on data modeling and its constraints
Collaborate
Collaborate Develop a shared lexicon • Agree upon “terms of art” and develop a shared definition for these terms • Avoid assuming everyone knows the definition - spell it out • Leverage off of existing industry work, if it exists
Collaborate
Collaborate Create a minimum baseline using the lexicon as a basis for shared understanding • Federal/State reporting requirements; funder requirements, and your own reporting needs can guide in this regard
Collaborate
Collaborate Test your minimum baseline for gaps (add to baseline) and extras (subtract from baseline) • Gaps are indicated when one partner may be missing a data point that most others use • Extras are indicated when one partner uses a datapoint that most others don’t need • Extras are absolutely fine in your own business processes, but for data exchange minimum baselines you don’t want to impose on others if it’s not needed
Collaborate
Collaborate • Including the Extras • Items identified as extra should still be defined in the standard as “optional” • There is not a limit to the number of extras, but be practical (consolidate if you can) • Extras should be helpful in enhancing the baseline data story • Inclusion or exclusion of extras are not enforced by the community
Collaborate
Collaborate • There is an art to negotiating the minimum baseline - be as inclusive as possible, and think outside your organizations immediate needs to the bigger picture
Collaborate
Compute Focus on what having a baseline standard and an open method of data exchange (such as Open Data) gives you in the ability to do your own work and have others check that work; also allows multiple entities to do their own research without having to be tied directly into your core systems
Compute
Compute National Standards • Consistency Lowers Risk for Vendors: Costs currently are born by individual agencies b/c vendors don’t have a rule to follow • Consistency Shortens Process: Part (not all) of costs is agreeing on file format and process rules. A data model and standards can reduce this cost • Assumes model is reasonably simple ; otherwise costs of exports can go up
• Provides a foundation for advocating with other federal funded programs such as LIHEAP, WX, HMIS related, and even Head Start
Compute
CSBG Data Model
CBMS Data Model Client And Household
Outcomes
Service
Clients & HH Communities Income
Reference List Extendable options
benefits Assessment
Client name
Reference List
Reference List
Date of Birth,
Crosswalk Data between two Models Pay ONCE for mapping and integration code
Demographics Household Members
Income Source Amount
Compute
SNAP Amount
Compute: Model to do Reporting Clients & HH Communities benefits
outcomes
service
Compute
Any Local System Producing data in the CSBG Data Standard
income
Module 3: Community Project Summary Module 4: Section C (demographics)
Module 3: Community Outcomes Module 4: Section A NPIs Module 4: Section B Service Counts
Consider • Continuous improvement • Performance • Business need • Efficiency
• Scale • Community impact
Consider
Questions? Consider
Compute
Collabor ate
Culture
Capacity
Collect
Rand Clark Community of Care Navigator Douglas County 303-660-7460 [email protected]
Consider
Culture
Compute
Collaborate
Capacity
Collect
Culture ONE person approach to care • We serve the same person • The person owns their data • The person owns their outcome • The funding we receive is for the person
Culture
What is data capacity? Right data, in the Right form, at the Right time, to the Right people
Capacity
Resources
Context Processes, Structure & Software
People Organizational Culture—beliefs and assumptions
Capacity: Identify purpose for interoperability
Increasing Costs Reporting and Analysis Need
Capacity
Presumptive Eligibility and Referral Need
Collaborative Work Need
TRANSFORMATIONAL
Collection Prescriptive • Case Management: Directed • Outcome: Completion • Data: Planning
Generative • Case Management: Engagement • Outcome: Change • Data: Change
UNIQUE UNIFORM Provision • Case Management: Determination • Outcome: Delivery • Data: Eligibility
Collect
TRANSACTIONAL
Navigation • Case Management: Connection • Outcome: Access • Data: Service records
Collaborate Pick your initial collaboration partners • include engaged representatives with varying perspectives into the whole of your business • Include technical expertise where you can, but don’t get into the weeds on data models yet • Focus more on data as a portable, self-contained entity and less on data modeling and its constraints
Collaborate
Collaborate Develop a shared lexicon • Agree upon “terms of art” and develop a shared definition for these terms • Avoid assuming everyone knows the definition - spell it out • Leverage off of existing industry work, if it exists
Collaborate
Collaborate Create a minimum baseline using the lexicon as a basis for shared understanding • Federal/State reporting requirements; funder requirements, and your own reporting needs can guide in this regard
Collaborate
Collaborate Test your minimum baseline for gaps (add to baseline) and extras (subtract from baseline) • Gaps are indicated when one partner may be missing a data point that most others use • Extras are indicated when one partner uses a datapoint that most others don’t need • Extras are absolutely fine in your own business processes, but for data exchange minimum baselines you don’t want to impose on others if it’s not needed
Collaborate
Collaborate • Including the Extras • Items identified as extra should still be defined in the standard as “optional” • There is not a limit to the number of extras, but be practical (consolidate if you can) • Extras should be helpful in enhancing the baseline data story • Inclusion or exclusion of extras are not enforced by the community
Collaborate
Collaborate • There is an art to negotiating the minimum baseline - be as inclusive as possible, and think outside your organizations immediate needs to the bigger picture
Collaborate
Compute Focus on what having a baseline standard and an open method of data exchange (such as Open Data) gives you in the ability to do your own work and have others check that work; also allows multiple entities to do their own research without having to be tied directly into your core systems
Compute
Compute National Standards • Consistency Lowers Risk for Vendors: Costs currently are born by individual agencies b/c vendors don’t have a rule to follow • Consistency Shortens Process: Part (not all) of costs is agreeing on file format and process rules. A data model and standards can reduce this cost • Assumes model is reasonably simple ; otherwise costs of exports can go up
• Provides a foundation for advocating with other federal funded programs such as LIHEAP, WX, HMIS related, and even Head Start
Compute
CSBG Data Model
CBMS Data Model Client And Household
Outcomes
Service
Clients & HH Communities Income
Reference List Extendable options
benefits Assessment
Client name
Reference List
Reference List
Date of Birth,
Crosswalk Data between two Models Pay ONCE for mapping and integration code
Demographics Household Members
Income Source Amount
Compute
SNAP Amount
Compute: Model to do Reporting Clients & HH Communities benefits
outcomes
service
Compute
Any Local System Producing data in the CSBG Data Standard
income
Module 3: Community Project Summary Module 4: Section C (demographics)
Module 3: Community Outcomes Module 4: Section A NPIs Module 4: Section B Service Counts
Consider • Continuous improvement • Performance • Business need • Efficiency
• Scale • Community impact
Consider
Questions? Consider
Compute
Collabor ate
Culture
Capacity
Collect
Rand Clark Community of Care Navigator Douglas County 303-660-7460 [email protected]
