Jodie Tr

VA Center for Health Care E

VA Palo Alto Health Ca

and Stanford University Medi
Financial Disclosure

y No potential conflicts of interesty ATHENA‐Opioid Therapy was supported by gr

TRX 04‐402: “Decision Support for the ManagOpioid Therapy Therapy in Chronic Chronic Pain” from VA HeaService Research and Development Service.

y CRAVE was supported supported by grant RRP 07‐316:

“Validation of computerized risk assessment fo

prescription opioid abuse” from VA QUERI an

R h bili i Rehabilitation R h esearch and D l eve opment
A S i erv ce D li e very P bl ro em

y Primary care providers uncomfortable with op

prescribing and pain management

y Lack of training trainingy Lack of timey Difficult patients

y But prescribe a lot of opioid medication

y 10% of all US prescriptions are for opioidsy In VA ~15% of patients patients in primary primary care are on op

op

any given time

y 50% of patients report chronic pain and about 30% 

are prescrib de opi id o therapy for th i e r pain
Concerns

y Increasing problems

y Rates of overdose overdosey Rates of prescription medication abuse

y For example: According to the NSDUH, in 2002, 2.5 m

Americans Americans reported reported using prescription prescription opioids opioids for nonpurposes for the first time. In 1990, this number was 5

Notably, 55% were female and 56% were over 18.

y Lack of evidence of efficac

y

y No randomized trials with outcome data past

4 

(Martell, 2006)

y Patient demand

y In

a household survey, substance use problems 

3.57) or depression/anxiety (OR 4.43) in 1998 wpredictors predictors of last month opioid therapy therapy in 2001 (Sullivan, 2006)
Clinical Practice Guidelines

y Exist

y Are primarily consensus basedy Delineate Delineate good care practices practices

y Are underused

y Practices not consistently followed

y What system‐level changes can we make to en

opi id o prescribing practices that maxi i m ze safeffectiveness?
ATHENA

‐Opioid DSS

yObjective: Provide primary care

providers patient specific guidelinbased information relevant to opiprescribin

g at the time of clinical

decision making (outpatient visit

yBased on 2003 VA/DOD clinical clinical

practice guideline for opioid therafor chronic chronic non

‐cancer pain
ATHENA‐Opioid Therapy DS

y Features include:

y Patient specific recommendations

y Warning p s about patients at high risk for misusey Specific drug dosing recommendations

y Highlighted opioid therapy‐relevant patient informationy Checklist of good clinical practicesy S d di d Standardized pain assessment wi ht write‐b k ac to medi 

ca 

y Tools

y Patient education materialsy Drug conversion conversion calculator calculatory Referrals for mental health & behavioral treatments, exercise 

and self‐help

y Guidelines for use of non‐opioid pain medicationsy S td uggested responses to ab t erran medi ti ca on use bh i e av ors
Tools as drop down menus

Cautions

Patient data

Checklist Patient specific guideline- b

recommendations for opi

therapy alerts if patient is higtherapy, alerts if patient is hig

for misuse and more!
Detailed drug 

recommendation, 

displays when 

arrow is clicked

Detailed 

information about information about

patient alerts
Automatic display when CPRS is opened for all p

a visit scheduled scheduled within a 5 day window. window.If patient is on opioids, the main page pops up in 

electronic medical record

CPRS
If patient If patient is not on opioids, opioids, a stamp is automatically automatically d

d

If you click on the stamp, the main page with allrecommendations appears.

CPRS window
Pain assessment tool, is written back to electronic medical re

a note
Pain assessment note in CPRS
Conversion calculator tool
Aberrant Behavior Guide tool
Side effects management tool
Legal requirements to be met when prescribing opioid
Behavioral therapy referrals within and outside V
System Testing

y Rules Developmenty Accuracy tests on sample patient casesy Lab‐based usability usability testing testingy In‐clinic pilot testing

y Clinician feedbacky Observation

y All provid de f db k ee ac for system red i es gn a

were conducted repeatedly as system under

major modifications
Athena Opioid Therapy (OT) Architecture

CPRS 

Remote Procedure 

Typical provider desktop or client computer

CPRS

Client & GUI 

Call(RPC) Medora

Web Svc 

Progress Notes saved 

i M d WbS

Athena OT Server Computer 

T S

Dai

extracts 

mu

patie

via Medora Web Svc 

Athena Client & GUI

Tomcat Server[ Guideline Interpreter (EON)]

[ Protégé ] 

patie

custom 

progr

text fi

Serve

Web Svc.

SQLServer Database

packag

and imp
ATHENA Opioid-Therapy (OT): Operations

Patient Data Extraction

 Patients in selected clinics with appointments in a 5-day windo Every night a M(MUMPS) program extracts data into a text file then FTP'ed to the Athena OT server. SQL Server package imports this data into the predefined table

SQL Server package imports this data into the predefined table

Convertor Program Transforms data into format ready for use by guideline interpre

Precompute Program Invokes EON to calculate therapy recommendations from patiewhich are then stored as individual "p p recom ute" files.
ATHENA-OT: Operations

OT Client (process/program running on provider desktop)

 Listener: starts in background when provider logs in to Windo GUI: displays recommendations to providers. This is hidden un

listener decides to display it on the desktop screen.

CPRS: provider Log-in Listener captures Windows message and obtains provider ID.CPRS: pati t l ti b id tien

t selection 

by provider

 Listener captures Windows message and obtains patient ID. Li

if patient and provider are in the database and if so,.... 

GUI Displays recommendations, relevant clinical data and checklist ftherapy, also enabling access to various tools, such as opioid concalculator pain assessments (can be saved to VistA as an unsignecalculator, pain assessments (can be saved to VistA as an unsigne
System Rated Highly Usable Highly Usable

Table 1: System Usability Scale: 

Round Round

1 2 

 mean sd Mean 

1. I think that I would like to use this system frequently 2.75 0.50 3.25 2. I found the system unnecessarily complex 2.50 1.11 3.00 3 I thought the system was easy to use 3. I thought the system was easy to use 3 00 . 0 76 . 3 25 . 4. I think that I would need the support of a technical person to  be able to use this system 3.50 1.51 4.00 5. I found the various functions in this system were well integrated 2.50 0.82 3.00 6. I thought there was too much inconsistency in this system 3.25 0.98 3.75 7 I ld i i h l 7. I would imagine that most people would l hi ld learn to use this system

 very quickly 3.25 0.69 3.00 8. I found the system very cumbersome to use 2.75 1.11 3.75 9. I felt very confident using the system. 3.00 0.53 3.25 10. I needed to learn a lot of things before I could get going with 

this system 3.25 1.27 3.75 

Overall Score: 74.38 84 

Items scored 0-4. Total scores in the upper seventies to hig g h ei hties better products. This product would be in the top quartile of software with the SUS. Mapping of scores to adjective descriptions: 73 = good
Potential but not fully realized uti

y Main page viewed for approximately 30% of pa

y Automatic pop‐up for those on opioids plusy Click from stamp for patients not on opioids

y Additional screens rarely viewedy D il d etailed recommend i at ons rarely vi d ewey Observations indicate that system fit well into 

clinicians clinicians standard standard practice practice but was typically typically oglanced at briefly.
Issues

y Many guideline recommendations are vague a

difficult to operationalize

y Opioid prescribing is still an art, not

a science

y Meant we had to:

y Leave out some

guideline criteria that could not be reliabl

y 

records

y Provide vague recommendations to providers

y Most

guideline recommendations lay out elem

good clinical practice, but do not indicate theappropriate course of action

y Tell you to get

a good history history, document document, develop develop c

treatment plans, educate patient etc.

y We addressed by providing checklist and tools

y Do not tell you specifically specifically when to initiate, initiate, titrate titrate 

down, switch medications or discontinue

y We addressed by providing detailed OPTIONS
Issues

y Predictors of prescription opioid misuse are neithe

sensitive nor specific

y Try to encourage dialogue and monitoringy Underuse may be just as common as overuse in at risk pop

y Good practice practice and use of our DSS may increase increase rat

decrease the amount of time required for pain manby the PCP

y Brings up other problems problems that PCPs are also not comforta

comforta

(e.g. substance use disorders, mental health problems)

y Opioid prescribing decisions may require commun

among the patient patient, primary primary care providers providers, mental professionals, rehabilitation specialists, other spec

nurses, and family members

y How do you insure or f ilit t facilitate this communi ti ? ca on
Current Status

y OI&T recently banned installation of any new Clas

software.

y We received received

a Greenfield Greenfield Innovation Innovation Award to hel

existing ATHENA systems (Opioid Therapy and

Hypertension) through the Class

I software approv

process process. We are creating creating contracts contracts to get this workcompleted.

y Study team is analyzing medical record data from 

participating participating in the in

‐clinic trial before versus du

system implementation

y develop outcome measures and determine effect siz

c

hange

i

n

cli i i n

i

c

ian

bh i e

hav

ior

for

a

f t u

ture

cli i l n

ica

l

ti

r

i

a
Questions?
Id tif i Hi h Identif

y

ing Hi

g

h Ri ks

k

P ti 

a en

y Existing Existing screeners screeners include: include:

y SOAPP, ORT, assess for risk of opioid misusey COMM and PDUQ assess for current

o

pioid m

behaviors

y These screeners emphasize personal and famil

substance substance use history history, addiction addiction behavior behavior, trauhistory, age, and psychological disorders (i.e. O

ADHD, schizophrenia, bipolar and depression

y Screeners are only moderately predictive, may 

up uncomfortable content or stigmatize patiendo not assess for information information with additional additional c

c

utility
New St di u es on P di t re c ors of

Opioid Misuse

Study 1: POPS

y Led by Ian Carroll and Sean Mackey at Stanfory Assessed Assessed patients patients before entering entering surgery surgery

y Followed patients daily until they reported no opioid 

no pain

y Looked at predictors of delayed opioid discont
R l esu ts

y On‐going pain predicted only a bit more than 

variability in time to opioid cessation

y P l ersonal or f il am y history of substance or al h

co 

disorders did not predict time to opioid cessat

y After controlling controlling for pain, Self‐Assessed Assessed Vulne

Vulne

to Opioid Addiction (1 item) was a significant 

better predictor of time to opioid cessation tha

SOAPP
y Even mild depression significantly increased t

opioid cessation after controlling for pain.

Figure C2: Elevated levels of depression measured preoperatively by the Beck Elevated levels of depression measured preoperatively by the Beck

Depression Inventory (BDI) predict markedly more persistent prescription opioid use following surgery. 21% of patients with depression (BDI>13) continue taking opioids 150 days following surgery compared to 7% of patients without depression (BDI≤13). (Log Rank p<.003) 
Study 2: CRAVE

y Led by Jodie Trafton and Eleanor Lewisy Interviewed Interviewed a convenience convenience sample of 200 VA p

p

who had received opioid prescriptions in the la

about their experiences with the medication,

incl du ing risks, b he aviors and f signs of misuse

y Sample was enriched for persons with medicat

misuse risk.
Medication Non‐adherence

y Under‐use (i.e. non‐use of Rxed opioids despit

going pain) was common.

y U dn er‐using patients often did not di i scont nu

prescriptions for opioids, even though they did take the medications.

y Patients who spontaneously reported disliking 

medications during the interview were hig y hl 

under use their opioids.
Somatization and Misuse

y Somatization, conversion of anxiety into physi

symptoms, symptoms, was measured measured using the PHQ‐15.Somatization was associated with over and un

of opioid medications

70%

80%

90%

100%

40%

50%

60%

7

0%

10%

20%

30%

(Cuccaire, Oser, Lewis, Trafton, in prep

%

none low moderate severe
y Examined similar concepts (i.e. Depression an

side‐effects) that were also associated with opi

adherence

y Somatization mediated the relationship betwe

y d i epression and opi id o prescri i pt on non‐adherey side‐effects and opioid prescription non‐adhere

y Suggests that:

y Depression leads to non‐adherence primarily b

increasing p yh sical sy p m toms

y Side‐effects lead to non‐adherence when coupl

health anxiety
Conclusions

y Asking simple questions and conducting pain‐

mental health assessments assessments may help us identi

identi

patients at higher risk of opioid misuse for clos

follow‐up.

y Ask patients if they want medication‐based pai

management before prescribing. Ask them if th

taking their medication before continuing Rx.

y Ask patients if they think they are at high risk o

developing opioid addiction problems before R

y Screen for somatization somatization and depression depression problem

problem

y Provides more clinically relevant information. 

potentially stigmatizing or uncomfortable que

i ldd nc u ed in current opi id o misuse screens.
Acknowledgements

y ATHENA

‐Opioid Therapy was designed an

by Susana Martins Martins, Dan Wang, Martha MicNaquell Johnson, Denise Daniels, Mary Goand Samson Tu

y POPS was designed and conducted by Ian C

Sean Mackey, Keith Hum

p y, hre

y

s, Jarred You

Peter Barelka, Walter Cannon, Charlie Wan

y CRAVE was conducted and analy y zed

b

y Ele

Lewis, Ann Combs, Susana Martins, Mike

Cuccaire, and Megan Oser
Contact information

y Jodie Trafton, Ph.D. ‐ Principal Investigator

y Jod e. a o @ a.go ie.trafton@va.gov, 650‐493‐5000 x22474

y Dan Wang, Ph.D. – ATHENA systems enginee

y Dan.Wang g @va. ov, 650‐493‐5000 x 66567

y Susana Martins, MD – ATHENA knowledge m

y Susana.Martins@va.gov, 650‐493‐5000 x 67167

y Eleanor Lewis, Ph.D. – CRAVE project directo

y Eleanor.Lewis@va.gov, 650‐493‐5000 x 22949