HL7 CIC – Joint Meeting: CIMI/CIGLocation: Orlando, FL

Date: 11 Jan 2016 MondayTime Q1

Facilitator Anita Walden Note taker(s) Anita Walden

Attendee Name AffiliationAnita WaldenEd HammondVirginia Riehl CIMI

Quorum Requirements Met:

CIMI is a structure of Data Data Elements is a business rule that pulls from the CIMI Models There will be a repository of models

HL7 CIC – EMS Ballot ReconciliationLocation: Orlando, FL

Date: 11 Jan 2016 MondayTime Q2

Facilitator Pt. Care Hosted Note taker(s) Mitra Rocca

Attendee Name AffiliationSee Roster

Quorum Requirements Met:

Negative comment on masking in a CDA section: Even if a section is masked in a CDA document, there might be other data elements that are still

required. Discharge summary needs a document code, if the mask sections off, it is not usable as a

discharge summary. Approach:

Remove masking.If the Document code will no longer be needed. A ballot re-circulation might be needed.

The CIC WG members votes on the disposition for the negative comments.

Affirmative = 7 Negative = 0 Abstain = 0

HL7 CIC – EMS Outcomes Ballot Reconciliation

Location: Orlando, FL

Date: 11 Jan 2016 MondayTime Q3

Facilitator Jay Lyle Note taker(s) Anita Walden

Attendee Name AffiliationJay Lyle

Quorum Requirements Met:

Reviewed Negative Votes 1st Masking of the Discharge Summary is a problem with some of the commenters. Strong preference for removing the masking. The focus should be conformance. A footnote in

the implementation document that masking is left up to the agreement to the users. Don’t add a note.

If masking is not used the discharge summary can be used as is a specific code may not be needed. Use the exact same structure with the external document section, an attachment to other documents such as FHIR and patient care reports.

Will also withdraw the new code request which means this may require a recirculation ballot.

ACTION – Jay may need to review the masking approach with Structure Documents

Vote:Nos.: 1, 2, 3, 4, 5, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 20, 24, 25, 31, 32, 33MOTION: Jay request a vote on the above dispositions for EMS Pt. OutcomesCrystal seconds Abstain – 0 Negative – 0 Affirmative -7

Affirmative Comments Vote on the Affirmatives next Wednesday – Mitra will join the call for the vote.

Meeting 4pm Eastern

Not sure if they need to meet in May.

HL7 CIC – Trauma Ballot ReconciliationLocation: Orlando, FL

Date: 11 Jan 2016, MondayTime Q4

Facilitator Note taker(s)

Attendee Name Affiliation

Quorum Requirements Met:

Notes from Mitra Rocca - II has 2 parts (OID and extension) OID is required and extension is only used only when you need new version.

Notes from Anita Walden – Negative comments were reviewed 1st

ACTION - Crystal will look into the OMB standard for race to decide if more than two races can be selected for their standard. She will have internal discussions about the use of OMB.

OMB Standard for race

https://www.whitehouse.gov/omb/fedreg_race-ethnicity

Need a value set of the drugs that fall into the category for VTE Prophylaxis drug category. The question is RXNORM the code set. NCD codes are produced by the EHR systems so this should be used instead of RXNORM. Question was raised if the NDC codes have classifications.

Trauma will provide a code list of acceptable drugs expected from the providers.

VoteAbdul Malik Shakir: Motion- to vote on the negatives dispositions for Trauma

Nos.: 3, 4, 5, 6, 7, 31, 36, 37Sarah second the motion Approve - 5 Abstain - 0 Negative -0

Will review the other comments on the Wed, Jan 27 4pm (ET). Mitra will attend the meeting for the vote.

Will need to reballot to constrain the code list and address other items. Will need to complete the NIB

HL7 CIC – RCRIM & BRIDG – Joint MeetingLocation: Orlando, FL

Date: 12 Jan 2016 TuesdayTime Q1

Facilitator Anita Walden Note taker(s) Mitra Rocca

Attendee Name Affiliation

Quorum Requirements Met:

Anita provided an overview to the CIC agenda for the week. CIC balloted the Bipolar and Generalized Anxiety Disorder, R1. However only the Bipolar DAM

was balloted. CIC is interested in discussing development of a common model with the BRIDG WG. Anita provided an overview to the ballot tally details for the Bipolar standard as well as break

down of participants in this ballot by organization. The Bipolar DAM team also received comments from ISCTM, ASCP and clinical expert review

committee. All the professional societies agreed on which data elements to keep and FDA reviewers also agreed.

The data elements came from CRFs and other data elements. DSM-V codes have not yet made it to the Bipolar Disorder DAM, they will be added prior to

publishing this standard. FDA provided the Duke team with a list of professional societies who provided comments for

bipolar disorder.o ISCTM += clinical trialso ASCP

Comment: To say, it is a Bipolar DAM is not fully correct. Clinicians who see patients need to be included.

FDA reviewer also treats patients. NIH experts also reviewed this DAM. With HL7, healthcare professionals cannot vote and have to pay $50 for each ballot. This is

discouraging, if HL7 is interested in input from clinicians. This standard is for FDA.

o Question: When you collect requirements, did you collect information from SDTM TA groups.

o Answer: we collect the clinical content and send it over to CDISC. CDISC started with developing or enhancing SCTM for Schizophrenia and also MDD.

Common Model Discussion

We have 120 data elements. 73 are common between both Schizophrenia and MDD. We would like to have a common model.

o Question: Do you do all models in the same EA package?o Answer: We started schizophrenia in EA, and added data elements. o These TAs are not one EA model, due to time constraint.

o We have a similar dilemma and found a way for togetherness and keeping everything separate in other cases.

o We went thru a list of pros and cons. How to maintain specificity. We took the OMG’s guidelines and applied it.

o Ballot package includes, 126 data elements, (73 common data elements), class diagram, activity model, use case and storyboards and list of assessments/scales.

o Which scales are top 10 or 20 most important, which are being used in clinical trials.

Next steps: SCID for DSM V Reconciliation Review comments with CERC Publish

Ballot Comments:o 163 comments o 55 negative comments focusing on:

DSM V suggestionsModeling comments.

Update on the general anxiety disorder Synthesis of data elements Meeting with CERC Development of models Ballot September 2016

RCRIM

RCRIM co-chairs provided an update on the ongoing RCRIM projects: RCRIM has been busy with SPL R7. SPL is under Common Product Model. RCRIM and FDA are proposing to develop SPL for food and standardize labels for food. At RCRIM we are looking at FHIR. Using ICSR as a base line as a FHIR resource. RPS work is also ongoing.

BRIDG We started the BRIDG WG in 2014. Brought the BRIDG back to HL7, since it was not balloted since May 2010. Outside BRIDG,

CDISC presented BRIDG to ISO and it was BRIDG 3.2, but the HL7 balloted version of BRIDG was older.

We are taking BRIDG. 4.0 into the HL7 May 2016 ballot. o Question: What is BRIDG?o Answer: BRIDG is originated as a DAM for regulatory clinical research. It also includes

life sciences. It has 4 main stakeholders are FDA, NCI, CDISC and HL7.

There are multiple implementations of BRIDG at NCI, FDA and Biopharma. CDISC offers training for BRIDG. All of CDISC standards have been harmonized with BRIDG. A few of HL7 Standards have been harmonized with the BRIDG model (ICSR, Study participation

and study design)o Question: There are commonalities between mental illness DAMs. Should BRIDG do

this or do we need a new DAM for mental health disorders?o Answer: When the TA DAMS are provided to CDISC, it will be part of SDTM and then

harmonized with the BRIDG Model. NCI has formed a workgroup called Clinical Informatics for cancer. Challenges with a Common Model are that they are not granular enough.

o Question: What are your plans with BRIDG re-modeling and how to ask SMEs to review BRIDG in small chucks?

NCI is looking at a real use case of BRIDG focusing on imaging. With the model, data managers need to build a CRFs or data elements, and are

only interested in MDD. o Answer: HL7 V3 is complex and BRIDG is also complex. We are building layers of the

model (working on OMG layers). Here is the model and lets walk thru it. Walk thru is written and uses the words

that you can use with SMEs. When we take the time to do that and do terminology binding, helps with working with the model.

How to build CRFs is another level of issue. Julie James has been developing a MDR and data elements are BRIDG based. You get BRIDG definition and you get SDTM and AdaM transformation as well.

Do SMEs need to see the BRIDG, a small team from SMEs who use MDR need to be able to see and understand the BRIDG, but not the rest of the SMEs.

Comment: Having a detailed walk thru is very helpful, we did this for RPS. Tie the walk thru to what is in the EA. Making the models and implementations simple enough.

o Question: We have models layers used by CDM. How do we maintain the consistencies?

o Answer: Models layers used by CDM – example: from RIM to DIM (Narrow Domain) to PIM (use case specific) to PSM – platform specific and physical – XML Schema, database definition.

o BRIDG is at RIM level. The common mental model should be at DIM level. Have a domain friendly view. o Question: Is there terminologies in BRIDG?o Answer: No. At DIM level, we build use case specific DIM. Terminologies are what the

SMEs would like to see.

o Question: Have you talked to the terminology team?o Answer: No, you need to talk to the vocabulary and HTA members.

o Question: Do all these models (DSM-IV or V) are for billing.

o Answer: There are audiences for clinical trials, for billing and also for clinicians?

o Question: Does the model take this into account?o Answer: if it coming from AE, bind it to MedDRA and from HIS, in UK it is ICD-10 or

SNOMED CT.

Action items: Reach out to HTA. Talk to what they are doing. RCRIM, BRIDG and CIC will meet on Tuesday Q1 in Montreal.

HL7 CIC – Electronic HR Usability Location: Orlando, FL

Date: 12 Jan 2016 TuesdayTime Q2

Facilitator Hosted: Electronic Health Records

Note taker(s) Mitra Rocca

Attendee Name Affiliation

Quorum Requirements Met:

We are writing functional profile. You cannot untie the 2. When you develop functional requirements, admit a patient, display a lab (those are functions).

How well a clinician does it, is usability. You can have a system but the way to do it might be troublesome. If it takes 10 screens, then it is not doing well Talking to the users and repeatedly talking to the user. You show them the design. That is

what is not happening. Involve them with testing. It is not enough. Meaningful Use (MU) has a problem with functionalities, it is for primary care, but not usable

for other specialists. Comment:

This is huge, mixed with quality issues. Take sub-set of that, a narrow scope on usability vs. boiling the ocean. Who are the users of this profile?Address the response from community; “throw this laptop in the ocean” why are users frustrated. Response time is relevant. Optimize response. Cross systems, these are guiding principles; some of the usability issues are not testable. What is in scope and draw a box around it. Standards community has no way to create functions.

Comment: Latency is good place to startFocus on one area, scope it down, and take a gentle first step.Is the reason to have this functionality prior to production?Review harm or severe harm on Health IT systems. Read the FDASIA health IT safety report. In most scenarios, the clinicians think, that the hospitals have set up these systems. Is it true, should we get the latest version? Should someone govern the latest terminologies? Yes

o Question: Is terminology stuff important to usability?o Answer: Yes. Sometimes multiple terminologies might apply to one term. Differences

that result from dif. Terminologies should be tested prior to putting it into production and it should be tested by usability experts.

How is terminology mapping evaluated?For the information resource, that references a terminology and where there is optionality for terminologyThis body of information will include some obscure terminologyTerminology mapping is not User Centered design and is a system usability

HL7 CIC – Max Tool Update & BriefingLocation: Orlando, FL

Date: 13 Jan 2016 WednesdayTime Q4

Facilitator Michael van der Zel Note taker(s) Mitra Rocca

Attendee Name Affiliation

Quorum Requirements Met:

Anita provided an overview to the agenda to the CIC members and provided an overview to the registry efforts project with AHRQ, Patient care and registries.

o Question: Do these patient registries are focusing on data or metadata?o Answer: It is about data, they collect

Belgium Registry efforts: They use data that is available in EHRs and did derivations to get data in to registry data.

Updates on the Max Tools: Working on transform to get it working. Max tools exports in XML, however we need to get attributes aligned and make it exportable to

Excel. James provided a demo on how he exports from Max tools into Excel.

o Question: James has to have the XSLT statement in the directory, where he does the transformation?

o Answer: It will be fixed.

o Question: What are the next steps to roll this out to other users?o Answer: We need to document it and create a test bed. We can work on this in May

2016.o Idea: Present the Max tools at the Co-chair meeting.

o Question: Can we have a Max tools Quarter prior to the co-chair dinner?o Answer: Yes.

Max Tools update will be on Monday Q3 in Montreal. JD from Sparks should also see the Max tools. Review Healthdata.be to learn more about registries in Belgium.

HL7 CIC – CIC Business Meeting & Report on CIC Projects

Location: Orlando, FL

Date: 14 Jan 2016 ThursdayTime Q1

Facilitator Note taker(s)

Attendee Name Affiliation

Quorum Requirements Met:

Igor provided an overview to Roche Diagnostics on diabetes use case. Focusing on patient care, mobile health, mobile data and life style. Goal: Define a FHIR interface for mhealth to communicate diabetes information from self-monitored glucose monitoring device to EHR/PHR or to a FHIR server.

There was an overview to Continua Health Alliance/PCHA to the CIC members. Continua works on how to use Meaningful standards.

We have a regular process in Continua. We have a use case process for that, when there is a new use case, it will be discussed and evaluated. Then we review the requirements, and we look at standards selection. Then we look at if we need a new standard or not. Then we will work with SDOs, and then we use the standards.

o Question: Have you imported the Continua data into EHRs? o Answer: No

FHIR is becoming an easy to develop solution. Recommendation by HL7 CIC co-chairs:

Create a Project Scope Statement. Create a track for the FHIR Connect-a-thon and create a profile.

HL7 CIC – New DAM Project – THEMES(Exercise Standards)

Location: Orlando, FL

Date: 14 Jan 2016 ThursdayTime Q2

Facilitator Anita Walden Note taker(s) Mitra Rocca

Attendee Name Affiliation

Quorum Requirements Met:

Anita provided an overview to THEMES, Exercise project. Funded by CTSA to UC Irvine.o They are interested in standards and build a committee with national experts. o They are also talking to someone from Netherlands or Germany. o The clinicians and domain experts are trying to understand the concept of data elements. o They will have a kick off meeting on March 24th. o They are planning to go to the HL7 WGM in Montreal.

Recommendation: Include functionality assessments and identify steps needed for wellness. Look at functionality assessment by CMS (work done CMS for the past 10 years). Then make a decision, if the work from CMS can be augmented.

o What is the general scope besides biomarkers? o How much of this project will focus on biomarkers. Then we will need to work with the HL7

genomics WG as well. o Main thing is VO2 Max, Oxygen Consumption, Peak VO2 result, …

Comment: No metadata about patient (18 year old going to military or elderly). They do not provide context to use it in a knowledge-based system.

If you are going to develop a CIMI model, it will include metadata. CIMI provides context of care as well as measurements you are doing.

The team is developing the data elements, a standard definition and permissible values. Degree of Fitness is a conclusion. We have found that this process forces to create a value or standard and fits nicely with the

model. This should be part of treatment plan. This is a good time to add these data elements, even without the definitions and ask SMEs to add definitions.

o Question: Are you putting together an exercise protocol?

Presentation by Steve Hufnagel: Common Health Interoperability Model (CHIM) Using the Open Group IT4IT Value chain and create a common logical interoperability model, it

is not creating a new model but informing all other modelso Question: Are you defining a logical model?o Answer: Conceptual model but it does not get into details of logical models, (Metadata

and other models) The physical model is what is used in systems and systems specific. Ideally using a tool, it can

be transformed into another model. (Metadata, provenance, so that data is useful).

o Question: H how does it compare to generic models?o Answer: Steve is looking at Federal Health Information Model (FHIM), a common logical

information model and has all the attributes and metadata and CIMI is bottom-up. CIMI has metadata and context

CIMI defines context for each domain. FHIM is clinical and also includes functional models.

o Take a use case (S&I frame work: Simplification tool) based on HITSP and have events and activities.

o Encounter is an event and immunization is an activity within an event. o It will be tied to a functional model and also to information to claims. o It needs to link to NIST Risk and Security framework and also to IHE Technical framework.

FHIM uses MDHT and MDMI to transform your information model into information exchange such as NIEM, FHIR, CDA/C-CDA and XML (JSON). (which are also models).

It could be a model based on XML or generate XML or schemas. You will have a consistent set of data. NIEM message from A to B and a FHIR message from C to D, as long as you have the same metadata, it does not matter.

With FHIR resources, you have a similar problem as the z-segment problem with HL7 V2.x. Have a consistent information model.

Start with business architectures, legislation policy (like CLIA for labs), NIST and HHS standards advisories and activity models, which will lead to business architecture.

Then we get to information architecture and develop interoperability specifications or component, such as EHR-S FM, FHIR or NIEM, CDA and C-CDA, LEGO (Semantics) using SNOMED CT, SNOMED extension including LOIINC and RxNorm, XML JSON.

Use MDHT to develop the CDA and CCDA (what OMG calls model-driven architecture). This is what is used to build a Common Health Interoperability Model. Make this

comprehensive. In CIMI they are planning to have 30,000 to 50,000 models.

DAMs are close to logical model.

o Question: Do you leverage Services Aware Interoperability Framework (SAIF)?o Answer: Yes.

There are Models at HL7 everywhere and how to use models is important. This project will take all the models and put them in a tooling environment and will have

traceability to EHR-S FM and data models within the logical data models. o Question: How does this shorten the time?o Answer: You have all these models and have these models to develop all these tools, how

to take all these clinical information and make it useful In Veterans Health Information Model (VHIM), we start with process models, and use Business

Process Modeling Notation (BPMN), and it has data objects or user flow. All data objects, FHIM is normalized and if you find an attribute in FHIM. In general is where that attribute is stored.

o There is a place for everything with our business information model,

o Take the FHIM concept and apply it widely. o Look at Standards and Interoperability frameworks and see if there is a use case that aligns

with that. o Create a new event and activities and look at Fed. Models and see what is needed. o DAM is a business architecture and list of information exchange requirementso Some are used in 100 dif. Use cases (HITSP C32 and you need CCD message to send it)o Or define something new. o ONC Objective is structure, semantic, security, service, and transporto Create a profile and create a new FHIR resource. o Exchange it with a mobile device talking to an EHR server. o Identify what is there and where the gaps are. From OMG or HL7.

o Question: Many of initiatives like PCORI, OMOP and Sentinel are not in here. o Answer: Key thing is reuse. If one person does mapping ever, everyone else can benefit

from it. FHIM has done a lot of mapping and a lot of mapping done for SNOMED, which will be leveraged

here. Clinical Decision Support (CDS) is not included. RDF is being supported but not listed.

o Question: Will it be useful for ICD-9 to 10 mapping? o Answer: Implicit proposal here is that after the investigator study it will be provided to FHA

and others.

o Question: Is there any emerging technology relevant to EHRs?o Answer: Yes. CIMI uses Archetype ADL. You can start with a universal model.

Health IT4IT. Vote for the PSS (From Steve Hufnagel)Mitra did the motion to approve PSS.Ed Hammond approved

Affirmative: 6 Abstain: 0Negative: 0

It will be completed in September 2016. Steve is also working with patient care, EHR and SOA Steve needed support from both technical and clinical domain experts.

HL7 CIC – CIMILocation: Orlando, FL

Date: 11 Jan 2016 ThursdayTime Q3

Facilitator Anita Walden Note taker(s) Anita Walden

Attendee Name AffiliationGalen MulroonyJackie Mulroony

Anita WaldenAMSMVZ

Harold SolorigJD Baker

JDTQuorum Requirements Met:

Anita gave an overview of the CIC group and its purpose and history. Discussion of patient registries- Galen was interested in registries being a subset of EHR data. AMS

discussed how across registries often pull across EHR, states, countries, and that is not feasible to pull from an EHR. Data can be derived, but still reliant on data being storied consistently. Some of the Registry standards may then be useful to identify what the gaps are in the network. Galen asked what the overlap was with DAF- Data access framework, extension of FHIR profile. EG Cancer patients. Currently, some comes from EHR, sometimes with cleaning protocols, others are manually entered. 3rd party vendors sometimes provide support.

Harold talked about CIMI- ontology of information. Attempt to come up with a description of information that comes through a hospital setting and makes sense to someone in the clinical space. Vision is to come up with a growing repository of these descriptions in a particular clinical context, but to do it formally so that it is translatable to information models. 11179 guided the models created but not exclusively. Data elements, definition, data type. Loosely been focusing on the abstract vs data element halves of the data element modeling under the term terminology binding. Purpose is to describe the components of data so that you know what they are referring to. One system may capture measured in mm HG, another might collect information about hypertensive status- same information, different manner of expression. CIMI built on the principles of open air AML. Does not intend to be an IT standard. In the short term, decided that the open air tooling was sufficient for use that CIMI could start representing the data. VA and others pushed back against this idea. No guarantee that the tool couldn’t be purchased and disappear from public domain. At point now that hope that vendors produce tools that would allow UML representation.

Sparks has implemented AML. Comments close Jan 29.

Profile has been created- question is what are the next steps.

CIMI emerging with tooling. With content, have been working with LOINC tools, but not solidified. Quite a ways to go. Open air community has built something called CKM (Clinical Knowledge Manager)

and supports registration of comments. Vendor said they would make it open but would need work to be modified for CIMI. Just labs for right now

Also a rich meta data model. Some data has been modeled, but is now part of an ISO standard and unavailable for unrestricted use.

None of these standards have gone through a process. Not sure all who want to give their say have been able to give their say.

Thinking that models CIC has worked on would become candidates for CIMI models. CIMI models go the next step beyond in tying elements to SNOMED. CIC has not done this in order to be agnostic and not tie them to specific use cases. CIMI requires connection to codes and will create new local ones if required.

CIMI has made the strong statement is that everything will be coded to SNOMED, although in practice there are not codes for every data element. CIC doesn’t code to SNOMED currently, partly because FDA doesn’t map to SNOMED

Some discussion of the use of modifiers such as recent

Next steps-Interested in getting examples of BPD elements and models since there are more than just observations in the model as it stands now. Based on discussions here, request for time to meet in Montreal. Tentatively Q3 Thursday, joint meeting hosted by CIC. Their regular meetings are Thursday at 4EST. CIC is the 28th jan or 25th feb. Plan to discuss at the February meeting

Clinicalelement.com/simi-browser—can see raw CIMI models from intermountain health care.

FHIMS.org-- fim website—come out from the FIM.

HL7 CIC – Patient RegistriesLocation: Orlando, FL

Date: 14 Jan 2016 ThursdayTime Q4

Facilitator Anita Walden Note taker(s) Anita Walden

Attendee Name Affiliation

Quorum Requirements Met:

Registry Tour

List of standards or package of guidelines may be useful for new registry setups. Driven by meaningful use and whether the ability to pull EHR data directly can be done Sometimes registries can be collecting data at a higher level than the EHR and be able to follow a

rules based alorgithm. In some cases it can’t come from EHR directly due to governance and or legacy providence when an established registry has exacting definitions and rely upon them in analysis.

National program of cancer registries (NPCR) Structure documents has a template called the HARE () Cancer Trauma and Immunization IG- need to add IGs to list. IHE has profiles for cardiology Is the answer to refer them to the list or for it to be an encyclopedic collection that bears further

explanation to pinpoint connections and overlaps Repository of element collection may help to make the connections. Framework or taxonomy of

outcomes that will let one achieve whatever the stated goals are. Single model to share the connections? AHRQ project exists on patient registries. Idea is a place

for all registries fed by clinicaltrials. Gov. In all of them the level of data elements is still quite poor.

Among 85 registries, no clear definition of what outcomes we are looking at. AMS- standards driven registry development guide. Another approach-where 5 different definitions exist, how to harmonize or consensus can happen?

Would this be a somethings HL7 would do? CIMI is in the definitions as it applies to FHIR profiles. AMS- different uses. Combining like registries, combining disparate registries Definitely want a generic model about registries. Registry for evaluation patient outcomes, a user’s guide. Maybe start with that and AMS to sketch out the beginnings of a DAM System functions would done in a functional model and it would be part of the DAM. Could still be

a project, but no plans to ballot in May. Do it later? Ever? Credibility? Consensus builds credibility.

Harmonization. AMS to do limited volunteer of DAM.How does FHIR integrate with registries? Maybe ahead of the curve. Need to put FHIR in perspective.Inclusion of VendorsCraig Parker made a motion to create a PSS.

Russ seconded. 15 for. Decided to make it universal. Thursday 28th at 2. Will need to be moved. Thursday Q4Invite CDS and CQI. Room size based on responses.

PLEASE YOUR NAME AND UPDATE INFORMATION

NameAffiliation E-mail Address

MON TUES WED THURS Last First Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

Acker Beth VA beth.acker@med.va.gov Allard Crystal FDA crystal.allard@fda.hhs.gov Baker JD Sparx Systems jbaker@sparxsystems.com Beeler George Beeler Consulting woody@beelers.com Bennett John Lancet Technology John.Bennett@LancetTechnology.com Berger Stacy COH sberger@coh.org

Bojicic SashaCanada Health Infoway sbojicic@infoway-inforoute.ca

Bolte Scott GE Healthcare scott.bolte@ge.com Boone Keith GE keith.boone@ge.com Briggs Bonnie Wolters Kluwer Bonnie.Briggs@Wolierskluwer.com Brown Andy ESO/Nemsis Andy.brown@esosolutions.com Case Jim NIH james.case@mail.nih.gov Change Wo NIST wchange@nist.gov Cote Danielle Zoll dcote@zoll.com Daoust Norman Daoust Assoc. norman@daoustassociates.com Datta Gora Cal2Cal gora@cal2cal.com Daviss Steven APA drdaviss@gmail.com DeYoung Lizzie MITRE/OASIS edeyoung@mitre.org Dickinson Gary Centri Health gary.dickinson@ehr-standards.com

Dittloff MargaretAcademy Nutrition & Dietetics MKD@CBORD.com

Dittmer Grant ACS gdittmer@dicorp.com Doss Christopher NCAT cdoss@ncat.edu Duteau Jean DDI Jean@Duteaudesign.com Eisenberg Floyd NQF feisenberg@qualityforum.org Evans Julie CDISC jevans@cdisc.org Fendt Kaye Duke kaye.fendt@duke.edu Gabriel Davera UC Davis davera@ucdavis.edu Gallego Evelyn ONC/SDC PM evelyn.gallego@siframework.org Gonzaga Zabrina Lantana Zabrina.gonzaga@lantaragroup.com Gonzales- Suzanne VA Suzanne.Gonzales-Webb@va.gov

WebbGoosseu William Results4Care wgoossou@results4care.nl Graham Matthew Mayo Clinic Graham.Matthew@Mayo.edu Greim Patricia VHA Patricia.Greim@va.gov Hale Richard ESO/NEMSIS Richard.Hale@esosolution.com Hammond Ed Duke william.hammond@dm.duke.edu Hastak Smita SceuPro Shastak@sceupro.com Havener Lori NAACCR lhavener@naaccr.org Helton Edward NIH/NCI Edward.helton@nih.gov Hobbs Allen Kaiser allen.hobbs@kp.org Hoeft Chris AS NTDB choeff@facs.org Hufnagee Steve DOD Hufnagee@ACM.org Isler Maria ACC?AHA misler@acc.org Jaccard Don FDA donald.jaccard@fda.hhs.gov James Lenel BCBSA lenel.james@bubsa Janky Justin Zoll jjanky@zoll.com Jones Elysa Oasis elysajones@yahoo.com Kahn Hetty CDC/NCHS hdk1@acc.org Kallem Crystal AHIMA crystal.kallem@ahima.org Kallas Nichole ACC nkallas@acc.org Kennedy Mary SAICF/caHUB kennedy@mail.nih.gov Khalid Arsalan ACC arsalank@hotmail.com

Kirnak AleanAm Immunization Registry Assoc akirnak@swpartners.com

Kiser John Abbvie John.Kiser@abbvie.com Kisler Bron CDISC bkisler@cdisc.org Klemn Juli NCI Iklemmj@mail.nih.gov Kretz Jim SAMHSA/HHS Jim.Kretz@samhsa.hhs.gov Kubrek Wayne CDISC wkubrek@cdisc.org Kuhn Thomason ACP tkuhn@acponline.org Kush Bart CDISC rkush@cdisc.org Leftwich Russell TN eHealth cmiotn@gmail.com Lyle Jay Ockham jay@lyle.net Maddux Suzanne ASCO suzanne.maddux@asco.org Mann Clay NEMSIS TAC clay.mann@hsc.Utah.edu

McCourt Brian Duke brian.mccourt@duke.edu McDonald Clement NLM Clemmcdonald@nlm.nih.gov Mears Greg EMSPIC gmears@emspic.org Milius Bob MNDP bmilius@nmdp.org Miller Holly VA holly.miller@va.gov

Mukesh SharmaWash Univ in St. Louis sharman@wustl.edu

Mulrooney Jackie JP Systems info@jpsys.com Mulrooney Galen JP Systems Galen.mulrooney@va.gov Mungal Salvatore Duke salvatore.mungal@duke.edu Nahm Meredith Duke Meredith.Nahm@dm.duke.edu Neal Melanie ACS NTDB mneal@facs.org Nelson Rene Zoll rnelson@zoll.com Oliva Armando FDA armando.Oliva@fda.hhs.gov Patock Michael Image Trend mpatock@imagetrend.com Perkins Vada FDA Vada.Perkins@FDA.HHS.gov Price Chrystal ACS NTDB cprice@facs.org Raaen Marquerite IBM Mraaen@us.ibm.com Reeves Dianne NCI reevesd@mail.nih.gov Rhodes Harry harry.rhodes@ahima.org Ritter John johnritter1@verizon.net Roberts John TN DOH john.a.roberts@tn.gov Rocca Mitra FDA mitra.rocca@fda.hhs.gov Ryan Sarah Ockham ryansaraha1@earthlink.net Salyards Kenneth SAMHSA/HHS Kenneth.Salyards@SAMHSA.HHS.gov Savage Rob MGC/CDC h2u3@cdc.gov Schick Lisa SeenPro Ischick@scenpro.com Shah Vijay JBS International vshah@Jbsinternational.com Shakir Abdul-Malik COH ashakir@coh.org Shakir Salimah Shakir Consulting Salimahshakirconsulting.com Shanbhag Nandam ACC nshanbha@acc.org

Simon LoriAm.Psychiatric Assoc. LoriR.Simon@gmail.com

Singuream Ioana Eversolve joana@eversolve.com Sisto Jennifer Accenture Jennifer.t.sisto@accenturefederal.com Slack Maryanne FDA

Solgrig Harris Mayo Clinic Spellman Lisa Ahima-ISOTC215 lisa.spellman@ahima.org

Spiro ShelleyPharmacy HIT Collaborative shelly@spiroconsulting.net

Srinivasan Ganesan ACC gsriniva@acc.org Stevens Helen Stevens Healthcare helen.stevens@shaw.com

Summers JodyClinical Data Managment jody@c-d-m.com

Telonis Panagiotis EMA Panagiotis.Telonis@EMA.Europa.EU Tewey Rob Digital Innovation rtwewy@drcorp.com Tolk Chris CDISC ctolk@cdisc.org Topping James Duke james.topping@duke.edu Tripp Ed Tripp & Asssoc Edward.Tripp@ESTRIPP.com Van der Zel Michael UMCG m.van.der.zel@umcg.nl Vreeman Daniel Regenstrief Institute dvreeman@regenstrief.org Walden Anita Duke anita.walden@duke.edu Walker Max Health Vic Max.Walker@dhs.vic.gov.au Walker Mead MWC dmead@comcast.net Ward Steve Eli Lilly stw@lilly.com Washington Lycia AHIMA lydia.washington@ahima.org Whipple Troy Image Trend twhippel@imagetrends.com Wilgus Rebecca DCRI warli001@mc.duke.edu

Wood GrantIntermountain Healthcare grant.wood@imail.org

Woyak Andrew GE Healthcare andy.woyak@med.ge.com Younes Maryam Duke Maryam.younes@duke.edu Zozus, Jr Robert Private Practice Zozus@icloud.com