shanahan tdg sig meeting 3 15-11 v2.1

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Implementation of Electronic Screening and Clinical Support

into General Outpatient Medicine Practices

Christopher Shanahan MD [email protected]

Boston Medical Center

National Drug Abuse Treatment-CTN / TDG-SIG - 3/15/2011

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Objectives:• Current state: The Informatics of Substance Use

• Experience / Lessons learned from implementing SBIRT in Non-research / Primary Care settings

• Key Issues: Implementing IT innovation in Primary Care Settings

• How can NIDA help General Medical practices implement SBIRT and facilitate development & implementation of Clinical Decision Support?


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Current state: The Informatics of

Substance Use


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• Clinical Core Substance use data-set lacking.• Poor data poor reporting (Garbage in – Garbage out)• Even when accurate, lack of standardized Substance

Use Ontology, makes it difficult or nearly impossible to reliably use that data for clinical use, QI, or research.

• EHR systems generally lack care management / registries for chronic disease management

• Many EHR systems lack real-time, evidence-based clinical decision support

Despite electronic capture of clinical Substance Use data…

because captured data is not standardized, capacity to employ this data continues to lag…


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Experience / Lessons learned from implementing

SBIRT in Non-research / Primary Care settings


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Massachusetts SBIRT (MASBIRT)

• Based on the Health Promotions Advocate (HPA) model• Key Objectives:

1. Universal screening of large numbers of persons

2. Meet SAMHSA data collection/follow-up requirements

To support objectives… Designed & built a web-based, screening & tracking

application optimized to integrated into clinical workflow.


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Typical General Medical Settings are Distinct from Treatment Settings

• Low prevalence: ~80% Negative for harmful EtOH or Substance Use

• Competing Priorities / No time• Little or No Provider/Staff Training• Providers often unwilling to open Pandora’s Box• Little or No Support (SW or Treatment Counselor)• Misaligned Financial Incentives


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• Web-based and device independent (PCs, wireless tablets)

• Centrally located and managed (no data on devices)

• Seamless integration with existing data sources

• Optimized to Point-of-Care workflow

Dynamic work-lists “Hotlist”, Search-n-Screen, Follow-up/Tracking tools

• Flexible, efficient, accurate, and non-obtrusive data collection Point and click application – near zero typing

• Maximal data integrity (build-in rules enforced)

• Master Patient Index eliminated redundant screening

• Real-time management /productivity reporting

• Automated data reporting to SAMHSA

• HIPAA compliant, secure

MASBIRT and IT Infrastructure Designed for General Medical Settings/Primary Care


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The Result• 117,000+ individuals screened over last 4 years at 3

distinct Hospital systems in the Inpatient, Outpatient, Emergency Rooms and 5 FQHCs.

• After Screening scored, risk information/recommendations provided to Primary Care provider via Provider Communication Form (PCF).o Paper given to the PCP, then filed with Medical Records for

scanning to the medical record.o Electronic Document to HERo Direct entry via EHR Form.

• Separate document • Or part of the PCP visit note


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Data Collection & Handling• Providers don’t screen or input resultant data.• Provider Communication Form (PCF) containing

screening results given to Provider during visit.• Tailored recommendations presented with

Screening results (PCF)• PCF data stored in EHR / Viewed by all providers• Documentation from subsequent Brief Intervention

a/o Treatment referral of patients screened (+) stored in protected records


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Observations• Several sites that were not systematically

screening came to understand and embrace Universal Screening and are working to adopt locally with or without HPA model in anticipation of the project end.

• One practice already screening, MASBIRT presence helped enhance performance

(Positivity rates increased from 5% to 25-30%)


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Key Issues: Implementing IT innovation in Primary

Care Settings


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Implementation Lessons• Providers won’t perform screening or input data (so don’t base the

data collection strategy on it.)

• Focus, expertise, standards, & tools not enough, BOTH cultural willingness AND operational capacity required.

“the ground must be fertile”o Do not implement if willingness or capacity are lacking

• Even with willingness and capacity….o Change must ALSO be unobtrusive/fit seamlessly into existing workflow.

• Sustainability “appears” to be generated over time by production feedback & positive results.o Wow!! We have more patients at risk than we ever thought! o This is important and we need to keep doing something about it.o Lets monitor this and make sure we keep doing it well. o Et.al.


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All EHRs are not equal:

Differ in….. • Configurability of Data collection Forms• Capacity to enforce Data Integrity• Capacity to provider alerts• Capacity to provide/configure Clinical Decision Support• Capacity integrate/interoperate/exchange data with other

systems both within and outside of the local health care provider IT infrastructure / network

• Need for modifications to EHR requiring Vendor involvement (may be obstacle).


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Design & Development

Must not substantially increase work

Less is more

Standards improve usability / decrease training

Form improves function • Increased Productivity• Leads to Better Documentation & Data Quality• Leads to Better Decisions• Provides in situ Training

User Interface: Principles for Effectiveness


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How can NIDA help General

Medical practices implement

SBIRT and facilitate development

& implementation of Clinical

Decision Support?


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Baseline Assumptions

• The goal is Screening not Assessment. • Complicated Screening Instruments (i.e. Perfect) are not

acceptable and cannot be used.• Acknowledge that workflow is critical & build tools that

can integrate into it easily.• Operational Workflow (The order of things) &

Information Workflow (What is known by whom & when) are not the same.

Interaction between them is important,

must be understood & developed.


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IT as a Strategy: Cost & Benefits• Costs:

o Substantial Effort: Time, Planning, & Resources.o Long-term strategy: Difficult to sustain given temporal

trends and local shifts in focus.

• Benefits:o Not guaranteed; Dependent on executiono Increasing data granularity enhances utility of

Reporting, QI, Research, & Decision Support .o Unavoidable tradeoffs between efficiency & specificity

Only NIDA’s Leadership will make this possible


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How can NIDA become an Agent of Change and support SBIRT in Practice?

• Support Providers who want to begin SBIRT in their practices need standards based on Best practices & Best Evidence.

• Maximize adoption opportunities by lowering the effort required for change by providing standards and tool sets. o Standard Substance Use Knowledge Set (key data elements

and direct linkage to state-of-the-art screening instruments)o Training & Content tailored for Clinical Decision Support


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Supporting SBIRT in Clinical Practice

Providers need to know…• What to ask (Dataset Standards)

o Establish a Common SBIRT Dataset based on Best Evidence & Practice tailored to Clinical Settings

• How to ask it (Training)o Provide & Communicate accessible Toolkits & Just-in-Time training

at Point of Care (POC) based on Best Evidence & Practiceo EHR based tools must be simultaneously intuitive & educational

• What to do with the answer. (Decision Support)o Develop & provide POC Clinical Decision Support (CDS)

recommendation that can be easily incorporated in to standard electronic Decision support algorithms (e.g. ARDIN)


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Clinical Decision Support (CDS)“System features predict improved clinical practice”

Provided automatically in clinician workflow. p<0.00001

Provided recommendations not only assessments. p=0.02

Provided at decision making at point of care. p=0.03

Computer-based. p=0.03

Kawamoto, et.al.

Nearly all (94%) systems possessing all 4 features significantly improved clinical practice


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Thank you


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shanahan tdg sig meeting 3 15-11 v2.1

Healthcare

clinical use

captured data

clinical support

treatment counselor

automated data reporting

samhsa data collectionfollow

existing data sources

clinical workflow