EHR Stakeholder Workshop:

Toward New Interaction Models

Two Illustrative Instances and a Suggested Framework

“What’s right is what’s left when you’ve done everything else wrong.” – Robin Williams

“For every 25% increase in complexity, there is a 100% increase in effort” – Scott Woodfield

Charles N Mead, MD, MScChief Technology OfficerNational Cancer InstituteWashington, DC (USA)

Senior AssociateGlobal Health GroupBooz Allen Hamilton

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Example 1: The caBIG™ Program: “Connecting the cancer community…from bedside to bench and back.”

Now in 4th year: will release ‘first version of a product’ Feb 1, 2008

Connecting cancer researchers (basic science) and clinical trialists (clinicians) across

– 60+ cancer centers

– Multiple ‘cooperative groups’ (e.g. Centers of Excellence)

– Multiple vendors

Initially focused on static data exchange at a computational semantic interoperable level

– Top-down governance

– Bottom-up input

– Standards-based application development

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Example 1: The caBIG™ Program: Some Lessons Learned

Computable Semantic Interoperability is hard but achievable

In addition to the software engineering concerns, CSI must be based on

– Human Semantic Interoperability

• the BRIDG Model (and its siblings)

• Centralized vocabulary management

– Organizational Semantic Interoperability

• Data sharing and Intellectual Property in the clinical research setting

• Learning to collaborate in a competitive environment

• The “Common Cause” philosophy

– Motivators of change: conflicts-of-interest vs conflicts-of-conscience

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Example 1: The caBIG™ Program: Some Lessons Learned

Stepwise (iterative/incremental) approaches are essential

Connecting the ‘bench’ to the ‘clinical research’ domain was the first step

Connecting to the clinical care community is the next step

Pilot program in breast cancer enabling ‘single source’ EHR/CRF data entry now under consideration

– Robust IT infrastructure (e.g. HL7 RIM, V3 data types, standardized terminologies, run-time wizards to prompt clinicians for appropriate data to satisfy CRF in the context of clinical care

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Example 2: The Health Service Specification Project (HSSP)

Joint effort by HL7 EHR Technical Committee (EHR TC) and the Object Management Group (OMG)

– HL7 responsibility: produce semantically robust service specifications

• Driven by business cases

• Manifest as Interface specifications (implementation-independent) bound to “semantic signafiers” (e.g. BRIDG Model, terminologies, etc.)

– OMG responsibility: manage an RFP process that results in the implementation of the specified service

Overall goal is to produce a set of standardized services that can be deployed by multiple vendors across the life sciences/clinical research/clinical care continuum

E.G. Clinical Research Filtered Query (CRFQ) service

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CRFQ and its clients…

P4

I/E criteria

P2

I/E criteria

P1

I/E criteria

I/E criteria

P3

List Qualified Protocol Interface

CRFQ

CRFQ client(clinician,caregiver,

patient Clinical data set

Qualified protocols

P1

Pt data

P2

Pt dataP4

Pt data

P3

Pt data

List Qualified Patients Interface

CRFQ

CRFQ client(trial sponsor,

CRO,Pharma) Protocol

I/E criteria/

Safety criteria

Qualified patients

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An Exemplar Scenario…

A Trial Sponsor has developed a new intervention for Type I diabetes and has developed a clinical trial protocol to test this new intervention. A repository containing the Electronic Health Records (EHRs) for a number of patients is available to the Sponsor as a possible source of subjects for the protocol. The Trial Sponsor would like to compare the protocol’s inclusion/exclusion (I/E) criteria against patient-specific data in the EHR repository to see how many patients could be potentially eligible to participate in the intervention study.

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This should be easy except for issues of…

Security and Access to EHR repository

Consent of individual patient (not necessarily the same as the previous point)

Non-standard expression of I/E criteria

Non-standard expression of patient-specific data

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And those were just the ‘easy’ limitations. Also there are… Many additional steps involved in ‘recruiting a subject for a trial’ including

More finely granulated analysis of data (beyond I/E criteria)

– Lack of standards for automating this analysis, i.e. every recruitment is a one-off process

Multitude of regulatory hurdles to cross

– Local/State/regional

– National/International

Multiple stakeholders (with multiple value propositions) working from within multiple systems. For each system involved:

– Who mandates a system?

– Who pays for a system?

– Who uses (primary and secondary) the system?

– Who builds the system?

– Who regulates the system?

Differing levels of organization maturity

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Complexity “Complicated”, “Multi-faceted”, “Multi-factorial”, “Multi-layered”

Ivar Jacobson (paraphrase): “A multi-leveled, vertically hierarchical organization whose products of value are produced through one or more horizontal processes that cross vertical organizational lines.”

With cross-organization processes – whether they involve people or systems –syntactic and semantic problems occur at the vertical boundaries.

Cumulative experience in industry, art, and (cognitive) science has repeatedly shown that the best way to deal with complexity is through abstraction, layering, and the use of standards.

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The Communication Pyramid

Communication

`Free-text Documents

Structured Documents

ad hoc Drawings

Non-standard Graphics

Discussions

Standardized Models (UML)

Probl

em S

pace

Solution Space

Impl

emen

tatio

n-In

depe

nden

t

Implem

entation-Specific

Ab

stra

ctio

n

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“Protocol” – a ‘commonly used’ term…

Source: John Speakman

Symbol“Protocol”

“We need to sign off on the protocol by Friday”

Concept 1

Thing 1(Document)

“Protocol XYZ has enrolled 73 patients”

Concept 2

Thing 2(Study)

“Per the protocol, you must be at least

18 to be enrolled”

Concept 3Thing 3(Plan) Ogden/Richards

(Mead/Speakman)

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A New Interaction Model

What is “An Interaction Model”?

Candidate definition (CNM): A formal representation of a a set of activities and deliverables that occur as the result of one or more participating entities requesting or responding to well-defined events in a control flow. A given interaction has well-defined

– pre- and post-conditions

– Inputs and outputs

If this sounds like empiric process and/or software engineering, it is…

– …but only because software engineering addresses complexity management in situations of equivalent complexity to the proposed goals of this conference

Best represented in visual diagrams augmented by text (rather than the inverse)

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ad Activ ity Diagram - Load Labs In CDMS

CRA PSC caXchange Router/Transformer caXchange Persistence (CTOM db) C3PR Hospital Infor. Sys/Lab Infor Sys C3D

Relevant Labs Available in CDMS

STORYBOARD: CRA looks at the schedule of a given patient on a study for a specific visit. She identifies all the lab tests that should have been scheduled/ completed for that visit. CRA would need all the lab values in a given timeframe that would fall within the timeframe of the visit. CRA then reviews the lab tests/values and identifies which ones are relevant to be loaded into the CTMS (for example, a diabetic pt may have also had a A1C – inthis case, this values would not be stored in the CTMS)

CRA request s Patient

schedule for a specific viisit on

a study

«datastore»

PSC db

Retrieves patientschedule and list of activ ities that were

scheduled for that lastv isit date

CRA recieves

list of activities

Rev iews list and identifieslab tests

Requests all lab results recorded for

this patient between last visit

and today

Routes requests to datastore «datastore»

CTOM db

Retrieves all lab resultsbased on parameters

Routes lab results to CRA

CRA recieves all lab results for that

patient

Rev iews lab results andidentifies ones relevant to

load in CDMS

Routes selected lab results to C3D

«datastore»

C3D db

provides subject id, study id, lab test date, lab test id, lab result, uom high range, low range

«datastore»

Lab System db

Routes requests to CTOM db

Pass data elements - pt. id, study id, last visit date

Pass list of all activities (will these be activity names?)

«datastore»

C3PR db

send lab test id, lab results, UOM, LLN, HLN, (from C3PR - study id, study name, inv id, inv name and GRID id)

Pass pt. id, study id, last visit date, today's date

CRA intiates request

Is this Lab resultrelevant to theStudy?

Discard labs

Extract patient lab data onperiodic basis

Query db based on patientidentifier

Transform data into v3

Retrieve Study relatedinformation for the subjectPersists Lab domain data

into the db

pass patient id (MRN)

send lab test id, lab results, UOM, LLN, HLN,etc.

This is all the lab data for a patient,regardless of whether the patient is enrolledto a study or not)

C3PR provides study id, study name, investigator id and investigator name to which the subject is enrolled

No

Yes

Use Case 2 – Load Lab Data

A Formal Representation of an Interaction

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A New Interaction Model: Critical Components

Identify stakeholders by role

– Capability, Capacity, Competency

– Stakeholders can be systems, organizations, or persons

– Many-to-many relationships are common

– Five ‘types’ of stakeholders, multiple instances of each type

Apply ongoing risk management strategies

– Static identification on a regular (e.g. weekly) basis

– Integration of risk mitigation strategies into project planning

Proceed iteratively and incrementally

– Apply project management Best Practices and avoid the Waterfall

• RUP

• Agile

• Scrum

• Etc.

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Summary The problem we are trying is the embodiment of a (hyper) complex system apply the

appropriate tools, techniques, expertise, etc.

– “You can’t build a skyscraper by nailing together doghouses.”

The problem will not be solved ‘bottom up’ – a meaningful solution will require top-down mandates to focus bottom-up and middle-out efforts – they will not succeed on their own

Success will only occur iterative and incrementally – any attempt to solve this problem with Waterfall approaches is doomed to failure

Think architecture: business first, technology second

Success in a layered, I/I approach involves

– Continuous risk identification and management

– Multi-disciplinary teams

• Identification of discipline-specific value propositions for all stakeholders

– Prioritization of project goals and realistic expectation settting

The is a hard problem, but it is a solvable one if approached correctly

QUESTIONS & ANSWERS

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Cumulative experience in industry, art, and (cognitive) science has repeatedly shown that the best way to deal with complexity is iteratively, using abstraction and layering

Complex problems require the application of complex cognitive processes in order to achieve meaningful solutions

Cognitive processes must apply layering and chunking (“the law of 7 +- 2”)

All disciplines that routinely deal with complex problems develop either formal or de facto approaches to Layering and Chunking

– Cyclical application of core process of definition, discovery, intervention, (re)evaluation (re-definition) “iterative/incremental process”

The Nursing Process as a model of complex problem solving

http://www.chambers.com.au/glossary/chunk.htm

Nursing Process

Assessment

Nursing DiagnosisEvaluation

Implementation Planning

ADPIE

Nursing Process

Assessment

Nursing DiagnosisEvaluation

Implementation Planning

ADPIE

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Organizational Maturity

Level 1: Heroism and Passion (no defined process)

Level 2: A Set of Directions (minimal ability to deal with unexpected)

Level 3: A Map (unexpected events can be managed)

Level 4: Gathering Process Variance (parallel process improvement)

Level 5: Using Process Variance data to drive Process Improvement

Everyone wants to be Level 5

Progression to the ‘next level’ is stepwise

Level 1 does not mean incompetence! It just doesn’t scale well over time

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Complexity

“Complicated”, “Multi-faceted”, “Multi-factorial”, “Multi-layered”

Ivar Jacobson (paraphrase): “A multi-leveled, vertically hierarchical organization whose products of value are produced through one or more horizontal processes that cross vertical organizational lines.”