Risk Assessment 2.0 Steve Passik, PhD Ted Jones, PhD
Disclosures Steven D. Passik, PhD – Consultant/Independent Contractor: Ameritox, Cephalon, Covidien, Endo, Janssen, Millennium, Pharmacofore, Purdue Pharma, Quest – Speakers Bureau: Jannssen, Cephalon, Quest, and Millennium
Ted Jones, PhD – Consultant/Independent Contractor: AFTS Pain Center of Arizona – Grant/Research Support: Dominion Diagnostics, AFTS Pain Center of Arizona – Honoraria: AFTS, Alere Inc.
Learning Objectives 1. 2. 3.
Participants will be able to name three validated risk assessment tools Participants will be able to state the value of risk assessment as a part of prescribing opioids Participants will be able to state two areas of risk that are not addressed by common risk assessment tools
Risk Assessment Is Important
Prescription Drug Abuse Is A Big Problem CDC report of November 2011 finds: –The number of deaths from rx overdose tripled from 1999 to 2008 –In 2009 nearly 500,000 ER visits were due to rx overdose
In our state of Tennessee rx overdose kills more people than MVA’s annually
Opioid Risk Assessment: The Current Standard of Care “A thorough risk assessment and stratification is appropriate in every case” “Risk stratification pertaining to outcomes associated with the abuse liability of opioids - misuse, abuse, addiction and diversion - is a vital but relatively undeveloped skill for many clinicians” American Pain Society and the American Academy of Pain Medicine, 2009.
Risk assessment is a legislated requirement for all patients seen at a registered pain clinic in Tennessee, as of 2012
Let’s see some potential risk  Add video here
We Started With “Red Flag” Lists Smoking On welfare Normal blood pressure Does not have a PCP Has had an MVA, fall or fire Leaves blanks on forms Calls staff by first name
Multiple dose escalations Obtains medications from multiple sources Sells medications Steals another patient’s medications Forges prescriptions
Current Written Risk Assessment Tools Opioid Risk Tool (ORT) Screener and Opioid Assessment for Patients with Pain (SOAPP); Screener and Opioid Assessment for Patients with Pain Short Form SOAPP-SF); Revised Screener and Opioid Assessment for Patients with Pain (SOAPP-R) Pain Medication Questionnaire (PMQ) Screening Instrument for Substance Abuse Potential (SISAP) Drug Use Questionnaire (DAST-20)
Then Came formal risk tools The Screener and Opioid Assessment for Patients with Pain (SOAPP) was published in 2003 The Pain Medication Questionnaire (PMQ) was published in 2004 The Opioid Risk Tool (ORT) was published in 2005 The Diagnosis, Intractability, Risk, Efficacy (DIRE) was published in 2006 The Screener and Opioid Assessment for Patients with Pain Revised (SOAPP-R) was published in 2007
And Clinical Judgment The clinical interview – one’s “gut” – has been a widely used tool since the beginning of risk assessment # missing teeth + # of tattoos + # family in the waiting room / age However, some data (Bronstein & Passik) shows it is not always accurate And other data (Brown et al 2001) shows that practitioners tend to assign lower risk to patients than a practice protocol using a written questionnaire calls for
UDT’s? Katz et al 2003 found that an inappropriate UDT at the first visit did not predict future misuse of medications So a UDT, while important and perhaps mandated by state law, is not in and of itself a good predictor of future behavior in treatment
There Are Four Ways Risk Tools Vary 1. They tap different content areas (see chart later) 2. They gather data in different ways (interview, staff rating, or written questionnaire) 3. They weigh the data gathered differently
– ORT shows this as it weighs some risk data more heavily based on gender – In a clinical interview you interview someone who is a recovering alcoholic. Does it matter how long he or she has been continuously sober? One year? Five years? Ten years? What weight would you give each of these?
4. They vary in opaqueness – how clear it is what the “right” answer is. With most current written measures it is easy to see what the “right” answer is
The False Dichotomy Almost all current risk assessment tools were based on the original dichotomous thinking: “Real Pain Patients” versus “Drug Addicts.” Thus, “We need something to tell the difference between the two” This dichotomous thinking leads to: – “If a patient has ‘real’ pain, then they are not an addict and I can treat him or her without worry” – Also: “If the patient is an addict or alcoholic, then I should not treat him or her at all. I’d be feeding his/her addiction”
Almost all risk assessment tools were created to identify addicted persons and those with substance abuse disorders
So What Do We Know So Far?
There Is Limited Data There are very few studies that have: –Compared different risk tools for accuracy –Used risk tools in a variety of geographic settings –Used risk tools with a variety of patient populations
Clearly more research and data is needed on this important area of clinical practice
The Findings To Date*
(Sensitivity & “Apples To Apples”)% Discharged For Aberrant Behavior After Six Months
The Findings To Date (cont’d)
Range Under The Curve: The Combination Of Sensitivity & Selectivity
Why? At Least Two Reasons Content Tapped by Each Risk Measure
It’s Not As Simple As “Finding The Bad Guys” Remember? “Risk stratification pertaining to outcomes associated with the abuse liability of opioids - misuse, abuse, addiction and diversion - is a vital but relatively undeveloped skill for many clinicians” American Pain Society and the American Academy of Pain Medicine, 2009
Addicts are only one part of the problem. Misuse, abuse and diversion of opioids are also significant problems, and are driven by other factors While at most only 10% of pain patients are addicted, medication aberrant behavior is seen in at least 45% of pain patients
Data On Overdoses Finds Hall et al 2008 found:
– That the majority of fatal overdoses involved people who did NOT have an rx for opioids. Doctor shopping is less common but involves a different subset of patients: female, older, and not engaging in illegal activities
Dunn et al 2010 found:
– Overdoses (both fatal and serious) are associated with: • older age (>65) • hx of depression • hx of substance abuse • being prescribed a higher dose of opioids
In Sum, Studies Show Misuse and overdose involve people who have or have had a history of drug addiction But the problem ALSO involves people with:
e.g., Ives et al, 2006
– Hx of alcohol abuse – Hx of criminal charges – Older persons – Depression, and – Diversion
So there is not ONE set or type of “bad guys” to look for. The problem is multi-faceted
And The Method Used:
Interview Data May Be Superior Written Measures Remember ORT written versus ORT asked? – 30% correct versus 57% correct
In that study, looking at the ORT items that were discrepant, – Personal Hx of Substance Abuse was discrepant – But also Family Hx of Substance Abuse and Depression were significantly discrepant – Age was discrepant 14% of the time (“Mark box if between 16-45”)
BOTH literacy/carefulness AND non-revealing/lying were factors
Summarizing The Data There are different types of patients that contribute to problems of medication misuse and overdose Written risk tools vary significantly in predicting risk Clinical interviews may – or may not – be superior to written risk tools in identifying patients at risk for medication aberrant behavior No risk assessment tool yet developed shows consistently good validation and accuracy (sensitivity AND specificity) data There needs to be more validation studies in different settings with different patient populations
Where Do We Go From Here? The Future Of Risk Assessment
Issues We Expect The Field To Be Grappling With In The Near Future We need short, easily understood, accurate written questionnaires to assess risk We need clinical interviews, when used, to be valid and more standardized We need treatment and monitoring to be tied to risk level We need practice methods developed to reevaluate risk as treatment goes forward We need to ensure that risk status is not a barrier to treatment
Written Questionnaires We need more data on current written risk measures to assess their accuracy across patient populations A written risk measure needs to be short, easily understood, easily scored, and accurate across patient populations If a patient questionnaire is given, it needs to be discussed and reviewed with the patient. Otherwise, literacy and omissions are likely to decrease its accuracy
Clinical Interviews As Risk Measures Many clinicians use interview data to assess risk If interview data - or clinical “intuition” or “gut feelings” – are used, they need to be more standardized and not based on stereotypes and unvalidated characteristics Interviews need to be short, accurate and, hopefully, reimbursable
Integrating Risk With Treatment Clinicians will be increasingly doing an initial risk evaluation on patients, if for no other reason than they are mandated to do so However, the field needs to promote the practice of actually using risk level to make treatment (medication) decisions and to determine monitoring levels (UDT’s, PMP checks, pill counts, etc) The intent of doing risk assessment is to guide treatment (medication) decisions. It is not meant to be a simply a box to be checked as “done” for audit purposes
Risk Assessment Is Like the NCAA Basketball tournament You seed the teams based on many sources of data (risk assessment) You then put the seeds in different parts of the bracket (titrating monitoring and treatment based on risk) Then you play the tournament. Sometimes you get upsets. Might be because you seeded wrong, or it might be because of some other unforeseen event. You deal with what happens But the seeding and bracket placement usually works out. It’s much better than random seedings or random bracket placement
Risk Needs To Be Reevaluated To date the focus has been on assessing risk before opioids are initiated – a very appropriate focus The field needs to also develop and promote methods of reevaluating risk as treatment moves forward This is particularly true for patients assessed as higher risk levels initially. For example, we likely should not be ordering UDT’s every visit on a high risk patient after 6-12 months of successful treatment We need to “ratchet down” monitoring based on “time for good behavior,” and perhaps widening the treatment (medication) options for such patients of they show success
Whatever Risk Method You Use It should not be framed as a “pass-fail” for opioids While there a very few patients for whom opioids are not indicated, the vast majority can be treated with opioids (if clinically indicated) IF monitoring and treatment are titrated to risk Similarly, evidence of a medication aberrant behavior should not necessarily be used for immediate discharge We need to move from an “all or nothing” approach to opioids to tailoring treatment (and monitoring) to the patient’s needs
Other Data Tied To Risk
Monitoring Methods In Treatment  There are four methods of monitoring a patient after a risk assessment is made: 1. Specimen testing (urine or saliva) 2. Checking the state PMP (you should be hoping for one if you don’t have it) 3. Pill counts – at the visit, mid-months, or random 4. Information from the patient at the visit (patients are remarkably forthcoming about their behavior)
These Other Data PMP’s and UDT’s and pill counts tend to be a “gold standard” for patient monitoring. That is, they speak for themselves, and are usually seen as preemptive over other measures So if a patient states she is doing well and not misusing medications, but there is a problem seen on a UDT or pill count or PMP, those measures “win” Current risk assessment tools need to be integrated with these other monitoring tools in some way that makes sense