Opioid-Related DisordersNCT02667262
An Observational Study to Develop Algorithms for Identifying Opioid Abuse and Addiction Based on Admin Claims Data
An observational study of Opioid-Related Disorders and Opiate Addiction, run by Member Companies of the Opioid PMR Consortium.
Trial summary
The purpose of this study is to develop and validate a classification model based entirely on medical claims data that can be used to identify patients experiencing prescription opioid abuse/addiction among patients receiving extended-release (ER) and/or long-acting (LA) opioids Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Opioid-Related Disorders, Opiate Addiction, Narcotic Abuse
- What is being tested?
- Algorithm to identify patients experiencing opioid abuse/addiction
- How many people
- 1,667 participants
- Where
- No sites listed yet
- Study dates
- 20 May 2015to 17 May 2017
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Adult, Older adult
Study population: Patients with at least two years continuous enrollment in Group Health integrated group practice (IGP) receiving ER/LA opioid analgesics
Who may be able to join
- Age ≥ 18 years
- Receipt of at least a 60 day's supply of ER/LA opioid analgesics within a 90-day period (including transdermal or oral opioids but excluding buprenorpine)
- Minimum of at least two years continuous enrollment in Group Health integrated group practice (IGP)
Who cannot join
- Residence in a nursing home at any time during the study period
- Enrollment in a hospice care program at any time during the study period
About this study
Official title: An Observational Study to Develop Computable Algorithms for Identifying Opioid Abuse and Addiction Based on Administrative Claims Data
The purpose of this study is to develop and validate a classification model based entirely on medical claims data that can be used to identify patients experiencing prescription opioid abuse/addiction among patients receiving extended-release (ER) and/or long-acting (LA) opioids
Read the detailed description
The most widely available information about patient care and conditions is that contained in medical claims data. If such data can be used to develop a model for identifying patients experiencing prescription opioid abuse/addiction it could be widely applied to patient populations throughout the United States.
A study recently conducted at Group Health comparing International Classification of Disease, Ninth edition (ICD-9) coding for opioid abuse/addiction to textual mentions in clinical notes describing abuse/addiction found that ICD-9 codes were 64% sensitive and 96% specific in their ability to identify patients experiencing opioid abuse/addiction (compared to evidence from clinical notes). This Group Health study considered codes for abuse (305.x) and addiction (304.x) equivalent because clinicians' usage of these codes did not differentiate well between abuse and addiction.
Needed are methods that can accurately identify patients experiencing opioid abuse/addiction based on widely available claims data.
This study will not evaluate opioid misuse because this will be captured by instruments in a prospective study of pain patients (Study 1A) using a combination of adapted validated instruments, and other new instruments that will be evaluated in post-marketing requirement (PMR) Study 2, plus medical record review to supplement questionnaire-based measurement of misuse, abuse and addiction with aberrant behaviors and physician text entries in the medical records.
- Conditions
- Opioid-Related Disorders, Opiate Addiction, Narcotic Abuse, Drug Abuse
- Being tested
- Algorithm to identify patients experiencing opioid abuse/addiction
- Medical subject headings
- Opioid-Related Disorders, Narcotic-Related Disorders, Substance-Related Disorders
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Algorithm to identify patients experiencing opioid abuse/addictionOther
| Study group | Role | What they receive |
|---|---|---|
| Extended Release and/or Long-Acting Opioids | Not described Receives: Other: Algorithm to identify patients experiencing opioid abuse/addiction |
What is being measured
The primary outcome is the main question the study is designed to answer.
Opioid abuse/addiction
This will be assessed from three data sources: a diagnostic algorithm that uses coded terms in claims data, Natural Language Processing assessment of text in electronic medical records, and medical chart review by clinicians trained in chart review
Measured: Retrospective review of data from 2006 to 2015, up to 9 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Jan 2016 (estimated)
- Study start20 May 2015
- Primary completion17 May 2017
- Study completion17 May 2017
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Opioid-Related DisordersStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Retrospective
- Enrolment
- 1,667 participants (actual)
Sponsor and investigators
- Lead sponsor
- Member Companies of the Opioid PMR Consortium
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- World Health Information Science Consultants, LLC, Kaiser Permanente
- Responsible party
- Sponsor
- Investigators
- Paul Coplan, MS, ScD, MBA, Study chair, Purdue Pharma LP
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02667262
- Sponsor's protocol ID
- Observational Study 3033-7
- Other IDs
- 3033-7
- Status last verified
- Apr 2020
- First submitted
- 18 Jan 2016
- Last updated
- 15 Apr 2020
- Results posted
- No
Publications
Carrell DS, Albertson-Junkans L, Ramaprasan A, Scull G, Mackwood M, Johnson E, Cronkite DJ, Baer A, Hansen K, Green CA, Hazlehurst BL, Janoff SL, Coplan PM, DeVeaugh-Geiss A, Grijalva CG, Liang C, Enger CL, Lange J, Shortreed SM, Von Korff M. Measuring problem prescription opioid use among patients receiving long-term opioid analgesic treatment: development and evaluation of an algorithm for use in EHR and claims data. J Drug Assess. 2020 Apr 28;9(1):97-105. doi: 10.1080/21556660.2020.1750419. eCollection 2020.
PubMed 32489718
Study at a glance
From the registry record, last updated by the sponsor on 15 Apr 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- An Observational Study to Develop Computable Algorithms for Identifying Opioid Abuse and Addiction Based on Administrative Claims Data
- ClinicalTrials.gov ID
- NCT02667262
- Acronym / sponsor ID
- Observational Study 3033-7
- Conditions
- Opioid-Related Disorders, Opiate Addiction, Narcotic Abuse, Drug Abuse
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,667 participants (actual)
- Lead sponsor
- Member Companies of the Opioid PMR ConsortiumIndustry (pharma, biotech, devices)
- Collaborators
- World Health Information Science Consultants, LLC, Kaiser Permanente
- Study start
- 20 May 2015 (actual)
- Primary completion
- 17 May 2017 (actual)
- Study completion
- 17 May 2017 (actual)
- First posted
- 28 Jan 2016 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The purpose of this study is to develop and validate a classification model based entirely on medical claims data that can be used to identify patients experiencing prescription opioid abuse/addiction among patients receiving extended-release (ER) and/or long-acting (LA) opioids
Detailed description
The most widely available information about patient care and conditions is that contained in medical claims data. If such data can be used to develop a model for identifying patients experiencing prescription opioid abuse/addiction it could be widely applied to patient populations throughout the United States.
A study recently conducted at Group Health comparing International Classification of Disease, Ninth edition (ICD-9) coding for opioid abuse/addiction to textual mentions in clinical notes describing abuse/addiction found that ICD-9 codes were 64% sensitive and 96% specific in their ability to identify patients experiencing opioid abuse/addiction (compared to evidence from clinical notes). This Group Health study considered codes for abuse (305.x) and addiction (304.x) equivalent because clinicians' usage of these codes did not differentiate well between abuse and addiction.
Needed are methods that can accurately identify patients experiencing opioid abuse/addiction based on widely available claims data.
This study will not evaluate opioid misuse because this will be captured by instruments in a prospective study of pain patients (Study 1A) using a combination of adapted validated instruments, and other new instruments that will be evaluated in post-marketing requirement (PMR) Study 2, plus medical record review to supplement questionnaire-based measurement of misuse, abuse and addiction with aberrant behaviors and physician text entries in the medical records.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Extended Release and/or Long-Acting Opioids | – | Other: Algorithm to identify patients experiencing opioid abuse/addiction |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Patients with at least two years continuous enrollment in Group Health integrated group practice (IGP) receiving ER/LA opioid analgesics
Key inclusion criteria (3 listed)
- Age ≥ 18 years
- Receipt of at least a 60 day's supply of ER/LA opioid analgesics within a 90-day period (including transdermal or oral opioids but excluding buprenorpine)
- Minimum of at least two years continuous enrollment in Group Health integrated group practice (IGP)
Key exclusion criteria (2 listed)
- Residence in a nursing home at any time during the study period
- Enrollment in a hospice care program at any time during the study period
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Algorithm to identify patients experiencing opioid abuse/addiction | Other | Extended Release and/or Long-Acting Opioids |
Primary outcome
Opioid abuse/addiction
Time frame: Retrospective review of data from 2006 to 2015, up to 9 years
This will be assessed from three data sources: a diagnostic algorithm that uses coded terms in claims data, Natural Language Processing assessment of text in electronic medical records, and medical chart review by clinicians trained in chart review
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Apr 2020.
- Derived from this study: PubMed 32489718Carrell DS, Albertson-Junkans L, Ramaprasan A, Scull G, Mackwood M, Johnson E, Cronkite DJ, Baer A, Hansen K, Green CA, Hazlehurst BL, Janoff SL, Coplan PM, DeVeaugh-Geiss A, Grijalva CG, Liang C, Enger CL, Lange J, Shortreed SM, Von Korff M. Measuring problem prescription opioid use among patients receiving long-term opioid analgesic treatment: development and evaluation of an algorithm for use in EHR and claims data. J Drug Assess. 2020 Apr 28;9(1):97-105. doi: 10.1080/21556660.2020.1750419. eCollection 2020.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Paul Coplan, MS, ScD, MBA study chair
Purdue Pharma LP
Questions about this trial
What is this clinical trial studying?
An observational study of Opioid-Related Disorders and Opiate Addiction, run by Member Companies of the Opioid PMR Consortium.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 15 Apr 2020. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Opioid abuse/addiction (time frame: Retrospective review of data from 2006 to 2015, up to 9 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT02667262, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Apr 2020.