Clinical Decision Support Services

Tonya Hongsermeier, MD, MBA

CMIO

Agenda

• About Clinical Decision Support Services

• Experience of the Clinical Decision Support Consortium

• Standards Efforts Underway to Make Them Widely Available

• Opportunities and Challenges

About Clinical Decision Support Services (CDSS)

Outside the Cloud Inside the Cloud

CDSS Firewall

Data Normalization and Classification

Services

Cloud-based Clinical

Decision Support Services

CDSS EHR

Consumer

PATIENT DATA

ASSESSMENTS and

RECOMMENDATIONS

1) Externalizes application of CDS Logic that can provide assessments and guidance

2) Externalizes curation of clinical knowledge to a CDSS provider or their respective content supplier

3) EHR vendor is responsible for making it possible to send data in the appropriate workflow context and receive assessments and recommendations from CDSS

4) EHR vendor is responsible for making it possible to insert CDSS guidance into the appropriate EHR workflow context

5) Implementing consumer still needs to determine insertion, support ongoing semantic harmonization

Clinical Decision Support Consortium (CDSC)

1. Knowledge Management Life Cycle

2. Knowledge

Specification

3. Knowledge Portal and

Repository

4. CDS Public Services

and Dashboard

5. Evaluation Process for each CDS Assessment and Research Area

6. Dissemination Process for each Assessment and Research Area

• Knowledge management lifecycle • Knowledge specification • Knowledge Portal and Repository • CDS Knowledge Content and Public Web Services • Evaluation • Dissemination

Led by Dr. Blackford Middleton AHRQ funded from 2008-2013

CDSC Conceptual Approach

CDSC Evidence-based Guidelines (e.g., DM, HTN, CAD)

Level 1

Translation

DisseminationLevel 2 and Level 3

Specifications

CDS Services

Provider

Dashboard

Developer

Dashboard

KM Portal and

Repository

EMR End user

accessRefinement

Performance Measures

Collaboration Collaboration

NextGen Centricity Regenstrief Partners LMR

Reminders

Partners HealthCare EHR Regenstrief Medical Record System®

Two Examples of CDSC Implementation of

CDS services

©CDS Consortium

Legal Agreements Developed to Address Liability Points of Failure

• CDS manufacturing defect

– Software does not perform as designed

– i.e. alerts fail to notify due to gap in software or service Device

– CDS supplier must be able to audit/trace all guidance provided

• CDS implementation defect

– Customer implementation of software results in defective functioning

– i.e. alerts fail to fire because customer has incorrectly implemented services insertion or failed to notify CDS supplier that their dictionary changed

• CDS user error

– Software performs as designed, customer has implemented correctly, however user does not utilize correctly

– i.e. user ignores alert, turns off alerts, fails to notice alert

– Blurred distinctions here because users typically blame CDS manufacturer or implementation team for creating unusable CDS.

– Legal precedent to date still renders the Provider accountable for determining if the CDS guidance is appropriate because the Provider has the richer context of the patient to interpret the relevance of the guidance

CDSC Services Rule Building Blocks

Problem Classes Drug Classes Classes of Observations

And Test Results

Indication State

Inferences

Goal State

Inferences

Contraindication State

Inferences

Infobutton Knowledge

Access

Diagnostic Testing

Care Management

Observation Dictionaries

LOINC or SNOMED

Order Classes

Drug Dictionaries

RX Norm

Order Catalogues

Patient

Assessment

Problem Dictionaries SNOMED

Risk State

Inferences

Recommendations

Guideline Context

Family History

Patient Preference

Phenotypic State

Genotypic State

Classes Of

Raw Data

Inferred Patient Context (Clinical State

Rules)

Patient Education

Qualifying for ACEI

ARB Drug Class

ACEi Drug Class

Contra Indication

To ACEi/ARB

Allergy to ACEi/ARB

Clinical State Rule

Pregnant Clinical State

Rule

Pregnant Prob

Class Subset

Preg. Complications

Prob Class Subset

Low BP Clinical State

Rule

Low BP Prob

Class Subset

Hyperkalemia Disease

State Rule

Hyperkalemia Prob

Class Subset

NOT NOT NOT Non-Gest

DM Disease State Rule

DM Disease State Rule

DM Prob Class Subset

DM Complications Prob Class Subset

Gest DM Disease

State Rule

Gest DM Prob Class Subset

NOT

Simple Rules are NOT Simple:

IF in non-gestational DM pt with non-ESRD qualifying for ACEi

Key:

___ AND

. . . OR Non-ESRD

CRF Disease State Rule

CRF Prob

Class Subset

Creat >2 w/in 12 mo Calc Rule

GFR<50 Calc Rule

Proteinuria Disease State

Rule

Malb/cre>30 Calc Rule

Proteinuria Prob Class

Subset

ESRD Disease

State Rule

ESRD Prob Class Subset

Dialysis Comp Prob

Class Subset

&NOT O

R

CDSC, ACDS, HL7 and Other Standards

ONC S&I Health eDecisions Use Case 1

– Data Model for CDS Artifact

Authoring – Knowledge Representation for

CDS Artifacts – Artifacts can be value sets

(groupers), rules, order sets, documentation templates, etc

– Enable interoperable knowledge sharing

CDS Artifact Sharing Use Case

FR & Data Elements

VMR GEM

eRECS CDSC

L3

HL7 Order

Set Model

SHARP ARDEN

Inputs

Use Case 1: CDS Artifact Sharing

HeD Artifact Sharing

Standard

Harmonization and Modeling for 3 Artifact

Types

CREF

CDSC, Open CDS, HL7

ONC S&I Health eDecisions Use Case 2

• Use Case 2: CDS Guidance Services

– CDS Services Insertion

– Patient Data Output by EHR/PHR system to CDS Guidance Service

CDS Guidance Services Use Case

FR & Data Elements

HL7

Consolidated CDA

Other

Standards

HL7 DSS

Services

Inputs

HeD CDS Guidance Services

Standards

Harmonization and Modeling

HL7 Context Aware

Information Retrieval

Opportunities and Challenges

• EHR vendors can’t expect their customers to curate all this knowledge inside their EHR walls Immunizations, Genetics, Genomics, Personalized Medicine

• Few EHR CDS systems can actually execute the kind of inferencing required for personalized medicine

• Hence, Memorial Sloan Kettering is training IBM Watson Personalized Cancer Rx service

• We need to advocate for EHR vendors to move beyond “walled gardens of simple CDS”