Electronic Chronic Pain Questions (eCPQ) - Pfizer · 2017-03-24 · Electronic Chronic Pain...
Transcript of Electronic Chronic Pain Questions (eCPQ) - Pfizer · 2017-03-24 · Electronic Chronic Pain...
Electronic Chronic Pain Questions (eCPQ)
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Background Situation
• No structured, systematic means for capturing chronic pain data that is widely adopted*
‐ Viewed as a symptom of multiple conditions and never a disease in itself
‐ Internists and multiple HCP specialists diagnose and treat chronic pain conditions
‐ The 3 main types of pain are not easily assessed—no simple test or widely adopted PRO tool
‐ Multiple guidelines by painful condition and/or by class of drug (eg, for opioids)
• Validated scales for pain assessment are not broadly utilized
• Existing EHR data capture solutions offered by some EHR vendors fall short of health system needs
‐ Integrated delivery networks and medical groups view existing EHR pain modules as too long and cumbersome
‐ The modules are not used because they do not offer a clear path on integrationinto current workflows
The Problem With Capturing Chronic Pain Data Today
EHR, electronic health record; HCP, health care providers; PRO, patient-reported outcome.
*Masters ET et al. ISPOR CONNECTIONS. 2013;2(19):8-10.
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Pain data are rarely recorded. When done, it is usually in the
open notes fields in most EHRs, making extraction,
reporting, and analysis difficult
Structured data fields exist for diabetes information
in most EHRs, making extraction, reporting, and
analysis easy
Diabetes patient visit to HCP
Captured
in structured data fields
HbA1c
Blood pressure
LDL
Retinopathy
Nephropathy
Neuropathy
NOT Captured
in structured data fields1
Pain severity or intensity2
Pain location and duration2
Impact of pain on patient’s
function, mood, and sleep2
Pathophysiologic type
of pain (nociceptive,
neuropathic, or sensory
hypersensitivity)2
Unlike Patient Data in Other Chronic Diseases, Chronic Pain Assessment and Data Are Not Captured Systematically in EHRs
1. Masters ET et al. ISPOR CONNECTIONS. 2013;2(19):8-10.
2. IOM. Relieving Pain in America: A Blueprint for Transforming Prevention, Care, Education, and Research. Washington, DC: National Academies Press; 2011.
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Chronic Pain Conditions Can Be Classified Based Upon Type of Pain Pathophysiology
Three Main Typesof Pain Pathophysiology
NOCICEPTIVE
PAIN
NEUROPATHIC
PAIN
SENSORY
HYPERSENSITIVITY
Pain related to
damage of somatic or
visceral tissue, due to
trauma or inflammation
EXAMPLES:
rheumatoid arthritis,
osteoarthritis, gout
Pain related to
damage of peripheral
or central nerves
EXAMPLES:
painful diabetic
peripheral neuropathy,
postherpetic neuralgia
Pain without identifiable
nerve or tissue damage;
thought to result from
persistent neuronal
dysregulation
EXAMPLE:
fibromyalgia
Phillips K, Clauw DF. Best Pract Res Clin Rheumatol. 2011;25(2):141-154.
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Types of Pain
First
line(based on
strength
of clinical
evidence)
Nonsteroidal anti-inflammatory
drugs (NSAIDs), acetaminophen1-5
Treatment of underlying
inflammatory condition may include
corticosteroids, biologics and
disease-modifying agents
Antiepileptic drugs,
serotonin-norepinephrine reuptake inhibitors,
tricyclic antidepressants1,3,5-8
Opioid
use
When other treatment options are inadequate,
opioids should be considered for the management of pain severe
enough to require daily, around-the-clock, long-term treatment3,5,6,8-12
Opioids should be avoided
in patients with sensory hypersensitivity13,14
Recommended Medication Classes forDifferent Conditions/Types of Chronic Pain
1. Phillips K, Clauw DJ. Best Pract Res Clin Rheumatol. 2011;25(2):141-154.
2. ACR Subcommittee on RA Guidelines. Arthritis Rheum. 2002;46(2):328-346.
3. Hochberg M et al. Arthritis Care Res (Hoboken). 2012;64(4):465-474.
4. Khanna D et al. Arthritis Care Res. 2012;64(10):1447-1461.
5. Passik SD. Mayo Clin Proc. 2009;84(7):593-601.
6. Dworkin RH et al. Pain. 2007;132(3):237-251.
7. Attal N et al. Eur J Neurol. 2010;17(9):1113-1123.
8. Carville SF et al. Ann Rheum Dis. 2008;67(4):536-541.
9. Chou R et al. J Pain. 2009;10(2):113-130.
10. VA//DoD. Clinical Practice Guideline for Management of Opioid Therapy for Chronic Pain.
Version 2.0. Washington, DC: US Dept of Veteran Affairs, US Dept of Defense; 2010.
11. Manchikanti L et al. Pain Physician. 2012;15(3 suppl):S67-S116.
12. US FDA. http://www.fda.gov/downloads/Drugs/DrugSafety/InformationbyDrugClass/
UCM367697.pdf. Accessed February 4, 2016.
13. Painter JT, Crofford LJ. J Clin Rheumatol. 2013;19(2):72-77.
14. Franklin GM. Neurology. 2014;83(14):1277-1284.
NEUROPATHIC PAIN1
Pain related to
damage of peripheral
or central nerves
Examples:
Painful DPN, PHN
NOCICEPTIVE PAIN1
Pain related to
damage of somatic or
visceral tissue, due to
trauma or inflammation
Examples:
RA, OA, gout
SENSORY
HYPERSENSITIVITY1
Pain without
identifiable nerve or
tissue damage; thought to
result from persistent
neuronal dysregulation
Example:
FM
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Identifying the Key Concepts in Chronic Pain From Literature and Guidelines
Source Details
Pain
Ph
ysical F
un
ction
ing
So
cial F
un
ction
ing
Em
otio
nal
Fu
nctio
nin
g
Glo
bal
Imp
rovem
ent/
Tx S
atisfaction
Sym
pto
ms
and
AE
s
Sleep
/Fatig
ue
IMMPACT Turk et al 2003
• Core outcome recommendations for chronic pain clinical trials
• Consensus meeting with 27 experts from academia, government agencies, and pharmaceutical industry
(Supplemental)
IMMPACT Turk et al 2008
• IMMPACT patient input – focus groups to identify domains, survey to evaluate importance
S-TOPSHaroutiunian et al 2012
• University of Utah – Pain Management Center Treatment Outcomes in Pain Survey
National Pain Audit 2012
• UK audit – quality of specialist pain services for people with long-term pain
WHO 2008• Scoping document – treatment
guidelines for chronic pain
CPAIN • Chronic Pain Impact Network
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Electronic Chronic Pain Questions (eCPQ) Module Overview
• A recommended set of questions to
help support chronic pain
assessment
• An electronic module/workflow
for data capture
• Based on existing guidelines
Objectives
• Designed to enable systematic, structured collection of discrete data
on pain in a format that allows for extraction, analysis, and aggregation
• Designed to enable physicians to more appropriately and efficiently
assess chronic pain and to help clinicians better diagnose, treat, and
monitor patients with chronic pain
• A clinical diagnostic tool or
treatment pathway
• A mobile device
What it IS What it IS NOT
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Electronic Chronic Pain Questions (eCPQ)*
Score: ≥ 3Score: < 3
Consider
Neuropathic Pain
Consider
Nociceptive Pain
“Mostly Yes”Consider
Sensory Hypersensitivity
What was your
average pain over
the last week?
(0–10 NRS Scale)
Thinking of the past week…
How much did pain interfere with your usual activities?
How much did pain interfere with your sleep?
How much did pain interfere with your mood?
(0–10 NRS Scale for each item)
CHRONIC PAIN? PAIN INTENSITY & LOCATION IMPACT ON FUNCTION, SLEEP, & MOOD
No = Exit
Yes
Other information to help diagnose sensory hypersensitivity can be
derived from medical history and other eCPQ questions. It includes:
• Widespread pain from body map image / locations? (Y/N)
• Marked impairment of mood, sleep, and function? (Y/N)
• Medical history of ≥1 other sensory hypersensitivity condition? (Y/N)
PAIN QUALITY & TYPE
Where is your pain?
(Diagram)
Have you had
pain most days in
the past 3 months?
(Y/N)
ID PAIN® Screener
Did the pain feel like pins and needles? (Y/N)
Did the pain feel hot/burning? (Y/N)
Did the pain feel numb? (Y/N)
Did the pain feel like electrical shocks? (Y/N)
Is the pain made worse with the touch of clothing or bed sheets? (Y/N)
Is the pain limited to your joints? (Y/N)
“Sensory Hypersensitivity” or Fibromyalgia-like Pain
Did you have trouble thinking or remembering in the past week?
Were you sensitive to bright lights, loud noises, or smells in the past week?
(0–10 NRS Scale for each item)
*For the purposes of this presentation, the eCPQ questions have been paraphrased. NRS, numeric rating scale.
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Prospective Psychometric Validation of eCPQ at William Beaumont Health
• Study Design: Prospective validation of eCPQ
in a primary care setting. This study had both
quantitative and qualitative components. No
investigational drugs, devices, or invasive
procedures were administered or evaluated as
part of this study.
• Quantitative Component:
‐ Study staff administered eCPQ
‐ Physician reviewed and discussed with patients
• Patients completed paper-based: POQ-SF; SF-36 Version
1 Acute; HADS; MOS Sleep Problem Index I; FSQ
‐ Patients invited to complete eCPQ online at home
• Qualitative Component:
‐ 1-on-1 interview following patients’ clinic visit
‐ Subset of study staff were invited to take part in
1-on-1 interview
• To assess the feasibility usability and potential
benefits of integrating the eCPQ into an
existing EHR system
• To evaluate the psychometric properties, test-
retest reliability and performance of the eCPQ
‐ Redundancy of Measurement
• Are any questions redundant
‐ Concurrent Validity
• Is the instrument measuring the purported construct that it
aims to measure
‐ Discriminative Validity
• Does the measure distinguish among groups known to
differ on a relevant dimension
Objectives Methods
FSQ, Fibromyalgia Survey Questionnaire; HADS, Hospital Anxiety and Depression Scale; MOS, Medical Outcomes Survey;
POQ-SF, Pain Outcomes Questionnaire-Short Form; SF-36, MOS 36-Item Short Form Health Survey.
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Disposition of Study Subjects
Patients Consented/Enrolled
(N = 455)
Partially or Fully CompletedDataFax Packets
(n = 429)
Unique eCPQ IDs
(n = 397)
Partially or Fully Completed w/Demographic Data
(n = 419)
Unique eCPQ IDs w/ Partially or Fully Completed eCPQ Data in EHR
(n = 395)
eCPQ IDs w/ Partially or Fully Completed Web Survey #1
(n = 115)
eCPQ IDs w/ Partially or Fully Completed Web Survey #2
(n = 84)
eCPQ IDs w/ Partially or Fully Completed eCPQ Data
AND
Partially or Fully Completed DataFax Packets
(n = 392)
Lost Packet/Not in DataFax (n = 5)
Blank DataFax Packet (n = 21)
• Ran out of time (n = 5)
• Withdrew (n = 11)
• Went to ER (n = 2)
• Language barrier (n = 1)
• Unknown (n = 2)
No demographic data in packet (n = 10)
No eCPQ data (n = 2)
eCPQ not administered (n = 45)
Duplicate/triplicate IDs assigned (n = 13)
AnalysisSample
No DataFaxdata (n = 3)
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Demographics of Study Subjects
Variable Total (N = 395)
Age, Years
Mean (SD) 43.4 (16.4)
Range (min, max) 18-95
Gender, n (%)
Female 269 (68.1)
Race, n (%)
White or Caucasian 277 (70.1)
Black or African American 53 (13.4)
Asian 16 (4.1)
Other 28 (7.1)
Missing 21 (5.3)
Employment, n (%)
Employed, Full-time 153 (38.7)
Employed, Part-time 54 (13.7)
Homemaker 36 (9.1)
Student 17 (4.3)
Unemployed 36 (9.1)
Retired 41 (10.4)
On Disability 33 (8.4)
Other 5 (1.3)
Missing 20 (5.1)
Variable Total (N = 395)
Education
Elementary/Primary School 5 (1.3)
Secondary/High School 109 (27.6)
Some College 115 (29.1)
College Degree 101 (25.6)
Postgraduate Degree 33 (8.4)
Other 12 (3.0)
Missing 20 (5.1)
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5.7
1.1
4.7 4.6
4.0
2.02.2
1.7
0.2
1.1 1.20.9
0.4 0.4
Average Pain (Q2)
ID Pain Score (Q4)
UsualActivites
(Q5.1)
Sleep(Q5.2)
Mood(Q5.3)
Thinking/Remembering
(Q6)
Hyper-sensitivity
(Q7)
Chronic Pain
No Chronic Pain
Mean Scores for eCPQ Questions 2–7 Among Subjects whoSelf-Reported Chronic Pain for Most Days or Every Day for the Past 3 Months on Question 1 and Those who Did not Self-Report Chronic Pain
*
*
*
**
* *
*P <0 .0001.
In addition, nearly 19% of patients with chronic pain had
an ID Pain score of 3 (likely indicative of neuropathic pain),
whereas only 1.7% of patients without chronic pain had an ID Pain score of 3
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15.4
26.2
4.1
8.2
6.1
14.5
0.6
3.9
% Meeting Moderate Depression
Cutpoint (>11)
% MeetingModerate Anxiety
Cutpoint (>11)
% MeetingSevere Depression
Cutpoint (>15)
% MeetingSevere AnxietyCutpoint (>15)
Chronic Pain (n=195)
No Chronic Pain (n=179)
Percentage of Subjects with HADS Scores Indicating Moderate or Severe Depression and Anxiety Among Those Who Self-Reported Chronic Pain Versus Those Who Did not Report Chronic Pain
*
*
*
†
* P < 0.05.
† P = 0.08.
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Psychometric Validation: Conclusions
eCPQ displayed concurrent validity by aligning with ancillary measures
eCPQ showed evidence of being a valid, reliable and reproducible measure for identifying patients
experiencing chronic pain
Patients and staff generallyviewed the eCPQ favorably
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Patient completes paper
eCPQ in waiting room when
checking in at each visit
Nurse/MA inputs
patient answers into
eCPQ form in EHR
Provider can see individual
longitudinal eCPQ results
during each patient visit
eCPQ Workflow Case ExampleImplementation at a large integrated pain clinic in the Midwest
Office feedback: Does not interrupt normal workflow
and takes only a few minutes
Integration into GE Centricity EHR System
• Results beneficial at individual patient visits, as well as from a population perspective
‐ Periodically (every 6 months) eCPQ aggregate results analyzed from an entire clinic population perspective
‐ Results provide information on how well clinic is managing patients with chronic pain, (pain, functioning, mood, and sleep)
Note: This is one example of how an office has implemented the eCPQ into its EHR system; the process can be customized for
individual practices, institutions, and EHR systems.
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• eCPQ was designed to address an existing gap in collecting data in patients with chronic pain
‐ ID Pain questionnaire helps to identify the pain type
• Developed in a multicenter study of 586 patients with chronic pain of nociceptive, mixed, or neuropathic etiology
• Validated in a multicenter study of 308 patients
‐ Additional questions, combined with other information already collected, help to identify patients with sensory hypersensitivity conditions such as fibromyalgia
• This portion of the eCPQ is currently under further study
• Psychometric validation of eCPQ in 397 patients with chronic pain was completed in the primary care setting (Beaumont Health)
• Used in a number of different settings, easy to complete, well received by patients and staff
‐ Allows clinicians to efficiently identify patients with chronic pain and systematically assess and monitor their symptoms over time
‐ May help to enhance patient care, facilitate patient-provider communication, and improve evidence-based treatment planning
Summary
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