Clinical Observations Interoperability:A Use Case Scenario

Rachel Richesson, PhD, MPH*

University of South Florida College of MedicineClinical Observations Interoperability Session

HCLSIG Face to Face, November 8, 2007

http://esw.w3.org/topic/HCLS/ClinicalObservationsInteroperability

* Acknowledgements to the members of the COI Task Force

Outline

• Motivation and Background

• Need

• Use Case Scenario– Eligibility Criteria– Sample Protocols

• Challenges

• Next Steps

Clinical Sites

Toronto,Canada

Paris, France

Edinburgh,UK

Cambridge,UK

Groningen, Netherlands

TokyoJapan

Melbourne,Australia

Sao Paulo,Brazil

Lyon,France

QuebecCanada

Bad Bramstedt,Germany

London

Motivation and Background• Identification & recruitment of eligible subjects is an

obstacle for the conduct of clinical research.

• Current screening mostly manual.

• Unlikely that all of the data required to assess eligibility for a given protocol will be available in the EMR.

• Final eligibility determined by the clinical research staff with F2F assessment.

• Applications that identify likely candidates (“probably eligible”) would help researchers target recruitment efforts.

Need for Patient Recruitment

• Ability to rapidly identify and recruit children for the right Clinical Trial– Children get access to the latest advances in medicine– Clinical researchers get cohorts to conduct studies

• Use Case Scenario:– Can we leverage existing EMR data to identify and

recruit appropriate patients for Clinical Trials?

Use Case

• Patient Recruitment for Clinical Trials using EMR data• Team effort• Several iterations• Final use-case posted to wiki (URL below):

http://esw.w3.org/topic/HCLS/ClinicalObservationsInteroperability?action=AttachFile&do=get&target=Eligibility+Screening_FINAL_10-8-2007.doc

Clinical Research ProtocolEligibility Criteria:

- Inclusion- Exclusion

EMR DATA

Meds Procedures

Diagnoses Demographics

…FailPassPass5/8 criteria met

Yes0033333

…………………

Pass

Pass

Criteria #3

(Pass/Fail/ Researcher Needs to Evaluate)

…

…

…

FailPass3/8 criteria met

No 0022222

Pass

No Criteria #2

(Pass/Fail/ Researcher Needs to Evaluate)

Pass 6/8 criteria met

Yes0011111

Criteria #1

(Pass/Fail/ Researcher Needs to Evaluate)

# Criteria Met / Total Criteria in Protocol

Potentially Eligible for Protocol

Patient MR #

Research Coordinator selects protocol for patient screening:

Research Coordinator views list of patients and selects which ones to approach in person for evaluation and recruitment.

Clinical Evaluation and Recruitment

Research Eligibility Screening Use Case, 9-24-2007

EMR DATA

Meds Procedures

Diagnoses Demographics

…FailPassPass5/8 criteria met

Yes3

…………………

Pass

Pass

Criteria #3

(Pass/Fail/ Researcher Needs to Evaluate)

…

…

…

FailPass3/8 criteria met

No 2

Pass

No Criteria #2

(Pass/Fail/ Researcher Needs to Evaluate)

Pass 6/8 criteria met

Yes1

Criteria #1

(Pass/Fail/ Researcher Needs to Evaluate)

# Criteria Met / Total Criteria in Protocol

Potentially Eligible for Protocol

Protocol #

Physician evaluates patient in clinical setting.

Physician views list of research protocols in institution for which the patient might be eligible

Further Clinical Evaluation

Secondary Scenario, (Patient-Centric) Eligibility Screening

Patient data entered in EMR.

Research Protocol #1

Eligibility Criteria:

- Inclusion- Exclusion

Research Protocol #2

Eligibility Criteria:

- Inclusion- Exclusion

Research Protocol #3

Eligibility Criteria:

- Inclusion- Exclusion

… Research Protocol #n

Eligibility Criteria:

- Inclusion- Exclusion

Available protocols mapped to EMR:

EMR

EMR instructs physician for further action

Refer re-searchers to patient

Refer patient to researcher

Variations

• EMR data-driven triggers– Certain values/clinical scenarios in the EMR data for a patient

would trigger retrieval and analysis of more EMR data

– This could lead to a dynamic identification of the patient as a recruit for an ongoing clinical trial.

• Physician-directed recruitment – Identify appropriate clinical trials for which a patient is eligible,

based on his/her data.

Sample Protocol

Ages Eligible for Study:  18 Years   -   95 Years,  Genders Eligible for Study:  Both

Inclusion Criteria:• Patients will be eligible if they are 18 years of age or older • Fluent in English • Have a known diagnosis of asthma • Will receive treatment for asthma during the current hospitalization or

emergency room visit.

Exclusion Criteria:• Cognitive deficits • Other pulmonary diseases or severe comorbidity • Do not have out-patient access to a telephone

Eligibility Criteria:Based on Sampled RDCRN Eligibility Criteria (n=452) ; Rachel Richesson, Unpublished Data – DO NOT CITE

Constructs Example  #  % 

diagnosis                                  Confirmed diagnosis of PCD.  66  15% 

consent  Is the subject or legal representative able to give informed consent?  60  13% 

finding 

Known or suspected PHA (or variant PHA), which might include elevated (or borderline) sweat Cl- values.  54  12% 

disease  Other disorders of chronic sino-pulmonary disease.  46  10% 

condition  Intercurrent infection at initiation of study drug.  31  7% 

lab  Decreased AS enzyme activity in cultured skin fibroblasts or other appropriate tissue.  34  8% 

mutation  Atypical deletion.  30  7% 

logic  One of three criteria above is met when other affected family members meet the other two criteria.   26  6% 

patient characteristic  Age between 1 day and 5 years old.  22  5% 

medication  High dose folate or derivative within last 12 months/  19  4% 

procedure done  Has had liver transplant.  15  3% 

Construct   Example  #  % 

reproductive potential  If female of child bearing potential and sexually active, agrees to use an acceptable method of birth control.  12  3% 

study arm  Group A: Low Risk.  10  2% 

procedure findings  An abnormal long exercise CMAP test.  8  2% 

administration  Sibling with AGS enrolled in study.  6  1% 

family history   Cardiac : Do any other family members have either cardiac feature?  5  1% 

mental status  IQ of at least 80.  4  1% 

anthropometry  Extreme low birth weight (<1500 g).  2  0% 

risk behaviors  10. Has the subject smoked cigarettes or marijuana at all in the prior year?  1  0% 

vitals  Patients must not have systolic blood pressure < 90mm Hg.  1  0% 

Total  452  100% 

Constructs Represented by Sampled RDCRN Eligibility Criteria (n=452)  - cont’d.

Note: This is *not* a representative sample so the #/%’s are meaningless.

Challenge: Terminology StandardsConstruct CHI CDISC HL7

Findings SNOMED CT or NCI Thesaurus

NCI Thesaurus subset ??

SNOMED CT

Procedures SNOMED CT ??? SNOMED CT ??

Labs LOINC LOINC-inspired subset; maintained by NCI

???

Medications RxNorm & NDF-RT ??? SNOMED CT ??(for some realms)

Anatomy (probably used as qualifiers for eligibility criteria)

SNOMED CT NCI Thesaurus subset ???

Vitals none CDISC defined value sets; maintained by NCI

???

Demographics Various CDISC defined value sets; maintained by NCI

various

Challenge: Information Model Standards

Info Models Clinical Research Care Delivery

CDISC Standards SDTM – dataset submission to FDA

PR – Protocol representation (eligibility criteria currently FT)

Others…. (Bron, Bo & Kirsten)

--

HL7 Standards RCRIM SIG consists of members from CDISC, NCI, FDA

Reference Information Model (RIM)

BRIDG Domain analysis model to harmonize CDISC & HL7 models; user-friendly

--

Detailed Clinical Models

-- In use at Intermountain Healthcare; real experience

Next Steps

• Seek buy-in for Use Case that represents a real world need and provides value to a wide variety of stakeholders in the Healthcare and Life Sciences

• Develop a collaborative framework comprising of Providers, Pharma and Vendors

• Work towards a POC that demonstrates the feasibility of using EMR data for Clinical Research

Next Attraction: Detailed Clinical Models by Tom Oniki

Acknowledgements

• Jeff Krischer, PhD, U. of South Florida• Office of Rare Diseases• National Center for Research Resources

(RR019259)

• DOD - Advanced Cancer Detection Systems (DAMD17-01-2-0056 )

This content does not necessarily represent the official views of NCRR or NIH or DOD.