Clinical Working Group Meeting

October 12, 2011

Agenda

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Topic Time AllottedUser Story Prioritization 12:00 – 12:30

Review Generic User Story Comments 12:30 – 12:50

Review FTF Objectives 12:50 – 1:00

User Story Prioritization Update

• Each of the User Story authors were asked a series of follow up questions to provide more criteria for selecting the User Stories to move forward with:– Is there a community or organization that has an existing infrastructure

of people and systems that supports this type of query today? Please describe.

– If this user story was selected, would that community be motivated to participate in a Query Health pilot in the first/second quarter of 2012?

– Does the data we would query exist within the clinical records today? – Assuming the availability of a reference implementation, would you

consider this User Story an easy implementation (i.e., something that could be implemented in a 1-2 month period)?

• The results to these questions were summarized and presented to ONC for a broader perspective review

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User Story Update

• The answers to the additional questions were reviewed in detail during a 10/11 meeting with ONC

• In addition, each of the User Stories were reviewed to determine if they aligned with Meaningful Use, other ONC interoperability initiatives, and cross agency goals and objectives (e.g., quality measures)

• More specifically the following questions were asked when reviewing each User Story– Are there an existing standards and terminologies outlined that can be leveraged

to help constrain the User Story?– Are there existing data sets that can be leveraged to help constrain the data

model?– Does it align with any other existing ONC programs and/or initiatives, providing a

mechanism for moving both/all forward?– Does it align with other agency goals and objectives?– Will the User Stories selected provide a robust set of actors?– Is it a simple enough starting point to be manageable (vs. unwieldy) by the time

we complete the use case?

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User Story Update

• After comparing these stories against these goals and objectives four of the User Stories were selected based on their alignment (some revisions were made to the User Story titles as well)– Expanded Analysis for Diabetic Care in an Outpatient Setting– Hospital Inpatient Quality, Reporting Program Myocardial

Infarction CQM – Vaccination Usage (previously known as Trends in Medical

Products)– Biosurveillance (previously known as All Hazards)

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User Story Update

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User Story ONC Reasons for Selecting

Expanded Analysis for Diabetic Care in an Outpatient Setting

•Aligns with ONC’s double down initiative •Aligns with CMS & NQF Clinical Quality Measures Program•Will result in CMS assist in defining how the query should be structured to meet the program goals•Focuses on a chronic disease management •Existing Standards and Terminologies can be leveraged•Will promote ONC interoperability goals •Supports MU goals and objectives

Hospital Inpatient Quality, Reporting Program Myocardial Infarction CQM

•Aligns with ONC’s double down initiative •Aligns with CMS & NQF Clinical Quality Measures Program•Will result in CMS assist in defining how the query should be structured to meet the program goals•Focuses on a chronic disease management •Aligns with ONCS 1 Million Hearts initiative •Existing Standards and Terminologies can be leveraged•Will promote ONC interoperability goals •Supports MU goals and objectives

Vaccination Usage (previously known as Trends in Medical Products)

•Existing Standards and Terminologies can be leveraged•Existing data sets that can be leveraged to help constrain the data model•Supports MU goals and objectives•Will promote ONC interoperability goals

Biosurveillance (previously known as All Hazards)

•Existing Standards and Terminologies can be leveraged•Existing data sets that can be leveraged to help constrain the data model•Aligns with CDC goals and objectives•Will promote ONC interoperability goals •Supports MU goals and objectives

Selecting the User Story

• The Working Group members are tasked with selecting one of the four User Stories to develop for the Query Health project by COB 10/14

• The remaining User Stories will be put in the backlog and addressed in later phases of the Query Health project

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Generic User Story Update

• The working group and support leads reached out to the working group members who voted no to resolve their comments and concerns

• A revised version of the User Story will be uploaded to address this feedback

• The working group members are asked to review these updates by COB 10/14

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Final Face to Face Announcements – Goals for the Working Groups

• Clinical Working Group• Complete User Stories• Complete Use Case Diagrams• Review DRAFT Functional Requirements• HOMEWORK – Review all Clinical Workgroup materials on wiki

and be prepared to discuss and comment

Note: All materials for review will be posted by COB 10/13

Next Steps

• Cast Vote on User Story by COB 10/14• Review Updates to Generic User Story by COB 10/14• Review materials for F2F meeting prior to working sessions

Appendix (Question Responses from User Story authors)

Author’s Response to Questions

User Story Name

•Is there a community or organization that has an existing infrastructure of people and systems that supports this type of query today? Please describe.

If this user story was selected, would that community be motivated to participate in a Query Health pilot in the first/second quarter of 2012?

Does the data we would query exist within the clinical records today?

Assuming the availability of a reference implementation, would you consider this User Story an “easy” implementation?

Example User Story – Case Control, Statin Efficacy (Support Team)

•Selected by IC & Support Team to align with comparative effectiveness goals utilizing NQF measures as the basis for the query.

Selected by IC & Support Team to align with comparative effectiveness goals utilizing NQF measures as the basis for the query.

Yes, the data to be queried will be based on the NQF quality measures required to be entered into an EHR based on MU.

TBD

Example User Story – Case Control, Vaccine Efficacy(Support Team)

•Selected by IC & Support Team to align with population health goals utilizing NQF measures as the basis for the query.

Selected by IC & Support Team to align with Population Health goals.

Yes, the data to be queried will be based on the NQF quality measures required to be entered into an EHR based on MU.

TBD

All Hazards User Story (Taha Kass-Hout – CDC)

No BioSense 2.0 Community (in an environment that is architecturally distributed in the cloud)

Yes In BioSense 2.0 environment it would be, otherwise DURSAs and new environment will have to be setup.

Outpatient (Michael Brody – CME Online)

Still waiting on response from authors.

Still waiting on response from authors.

Still waiting on response from authors.

Still waiting on response from authors.

Author’s Response to QuestionsUser Story Name Is there a community or

organization that has an existing infrastructure of people and systems that supports this type of query today? Please describe.

If this user story was selected, would that community be motivated to participate in a Query Health pilot in the first/second quarter of 2012?

Does the data we would query exist within the clinical records today?

Assuming the availability of a reference implementation, would you consider this User Story an “easy” implementation?

Expanded Analysis User Story (Kim Nolen – Pfizer & Lindsey Hoggle – Health Project Partners)

Yes Yes, the Diabetes Expanded analysis User story consist of quality measures that Physician are being ‘encourage’ to report and improve quality and control cost through HealthCare Reform, Accountable Care Organizations, PCMHs, and other organizations who develop quality measures (NCQA, NQF, PQRS, etc). This query would allow them to benchmark their practice with others in their city, state, &/or nationwide. They could use this information to help build a story especially to Payers in ACOs type engagement to show how they compare to others in the same geography or on a national level.

All of the data points should be in the EHR. These are clinical quality measure that physicians or provider organizations are being held to show performance and clinical quality to now. This User Case (Expanded Analysis) puts together a set (or cluster) of clinical quality measures that should help move population health management. However, dependent on how the EHR has certain fields set up or how the practice is entering certain data we will have to evaluate what percentage of data points are in discrete fields. The majority, if not all, should be available as discrete fields, however we have no control how the individual provider enters the data points. Also, we will need to determine which data points are ‘native’ vs. ‘derived’. Meaning native data points are extracted exactly from the EHR as entered and derived being some sort of calculation. An example A1c should be a native field, but screening for nephropathy may be derived from a lab test result.

I am not a technical person, more of a blended Health IT/Clinical person, so I do not have a knowledge base to answer this question from a technical standpoint. All of the fields should be available, and these are all quality measures that are recognized by national organizations. So these should be data points that are easily managed in an EHR system.

Author’s Response to Questions

User Story Name

•Is there a community or organization that has an existing infrastructure of people and systems that supports this type of query today? Please describe.

If this user story was selected, would that community be motivated to participate in a Query Health pilot in the first/second quarter of 2012?

Does the data we would query exist within the clinical records today?

Assuming the availability of a reference implementation, would you consider this User Story an “easy” implementation?

Consumer Perspective User Story (Eva Powell - National Partnerships)

•Countyhealthrankings.org•University of Wisconsin Population Health Institute•Minnesota may have something, as well. See http://www.health.state.mn.us/e-health/phphin/index.html for more info - not sure if there is info at the level of technical detail you are looking for. MNhealthscores.org may have more detail; but these tend to be report oriented, not query oriented, but perhaps the infrastructure is similar? You’d have to query something to get results for the report, right?•Community Health Data Base•This is probably the best example of a query based, population health use case.

Possibly. I would think some of these folks would be interested, especially if there was a way to link the pilot to work they are already doing under a State HIE grant, as part of a Beacon Community, or other initiatives they already have going on. For example, I know the NC Beacon Community, Community Care of Southern Piedmont, is focusing on managing population health through increased collaboration among communities, so they and the state would probably be very motivated to participate in a Pilot that uses the NC Health Query Data System (e, above) for this purpose, if they aren’t already doing so.

Yes (in my example, I’m not sure about readmission data, though, but that data is collected somewhere).

Yes (should ask those who know more about the technical issues than I, however)

Author’s Response to Questions

User Story Name Is there a community or organization that has an existing infrastructure of people and systems that supports this type of query today? Please describe.

If this user story was selected, would that community be motivated to participate in a Query Health pilot in the first/second quarter of 2012?

Does the data we would query exist within the clinical records today?

Assuming the availability of a reference implementation, would you consider this User Story an “easy” implementation?

Hypothesis Generation User Story(David McCallie – Cerner)

The category of "hypothesis generation" is very broad, so I believe that there are numerous communities who would take advantage of this type of capability. Any researcher who uses "retrospective, observational data" to generate research hypotheses would qualify. Such communities include: + academic researchers (as per the use-case story which came from Partners, Boston.)+ pharmaceutical researchers (we get many requests like this at Cerner)+ comparative effectiveness research (private and public)+ drug safety research (the Partners use-case was predominantly focused on drug safety)+ medical device manufacturers+ FDA (device safety surveillance)

• we could approach a pharmaceutical company and solicit interest? I am not sure how aggressive they could be• if the pilot includes an academic medical center, we could solicit participation from within their research community

• as the Partner's study demonstrated, certain well-focused studies can be done using the kinds of data that get captured in EHR data. There is always a need for more "structured" data, but in our experience at Cerner, the existence of labs + meds + procedures + diagnoses is sufficiently valuable to generate research interest.• clearly we need more structured data to do deeper research. This was one of the lessons from the i2b2 presentation, where they described the use of Natural Language Processing to augment the structured record. Genomic data, probably via laboratory interfaces, will also expand the range of interest.

• I suspect that it would be possible to create "proof of concept" study, but it might have to be artificially simplified if the time-frame is very short. Real-world research is hard, and often requires complicated queries and considerable post-query data processing, as per the Partner's study.

Author’s Response to Questions

User Story Name

Is there a community or organization that has an existing infrastructure of people and systems that supports this type of query today? Please describe.

If this user story was selected, would that community be motivated to participate in a Query Health pilot in the first/second quarter of 2012?

Does the data we would query exist within the clinical records today?

Assuming the availability of a reference implementation, would you consider this User Story an “easy” implementation? I.e., something that could be implemented in a 1-2 month period?

Hospital Inpatient Quality Reporting Program Myocardial Infarction CFM(Anne Kling – Mitre)

There are several ‘communities involved in clinical quality reporting. Compiling clinical quality information is done in a variety of ways (manually and electronically) across healthcare providers, payers, researchers and government agencies. Electronic reporting of quality measures is in its early period, as noted with the work of NQF and EHR meaningful use. The ability to support a distributed query for quality measuring and research would provide a needed and valuable service to support the analysis of clinical information, performance and outcome.

Providers, payers, researchers and government agencies could all benefit from the ability to support an electronic distributed query of clinical quality metrics and research.

Yes, although standardization and codification may vary across systems.

Yes, with guidance and support.

Author’s Response to QuestionsUser Story Name Is there a community or

organization that has an existing infrastructure of people and systems that supports this type of query today? Please describe.

If this user story was selected, would that community be motivated to participate in a Query Health pilot in the first/second quarter of 2012?

Does the data we would query exist within the clinical records today?

Assuming the availability of a reference implementation, would you consider this User Story an “easy” implementation?

Trends in Use of Medical Products in the Inpatient Setting User Story (Jeff Brown – Harvard Medical School)

I have in mind an implementation that uses existing people and infrastructure that *could* support this type of query (ie, not currently implementing a distributed query that meets the QueryHealth requirements, but the path forward is obvious). Implementation would require combination of resources across several organizations.

Yes. Main barriers to getting something done quickly are funding, research approvals, security/privacy approval, and timing. I'm assuming there is a need to implement the pilot in an existing health system with real data. Implementation is a test environment overcomes some barriers (privacy if not real data), but not all. It has never been clear to me if the intent is to fund pilots or hope the community would just do them.

Yes. I double-checked... Not sure what you mean by a reference implementation or the characteristics of the implementation. I'd consider the user story low hanging fruit because it can be implemented with data that is routinely collected, will not require ontology or mapping (bc we wouldn't pick a implementation that required it...), and doesn't require much in the way of algorithm or complex logic. I have in mind a very specific implementation. Happy to discuss further. I may be at a disadvantage because I'm not clear about the overall path mapped out for Query Health/ might be missing context or expectations. At its core, a distributed query needs 2 things: data and a way to send the question to the data. There are many ways to implement, even within a the guidelines set out by QueryHealth. The permutations arise in the specifications like governance, security, architecture, and query capabilities.