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An Observational Study to Develop Algorithms for Identifying Opioid Abuse and Addiction Based on Admin Claims Data

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ClinicalTrials.gov Identifier: NCT02667262
Recruitment Status : Completed
First Posted : January 28, 2016
Last Update Posted : April 15, 2020
Sponsor:
Collaborators:
World Health Information Science Consultants, LLC
Kaiser Permanente
Information provided by (Responsible Party):
Member Companies of the Opioid PMR Consortium

Tracking Information
First Submitted Date January 18, 2016
First Posted Date January 28, 2016
Last Update Posted Date April 15, 2020
Actual Study Start Date May 20, 2015
Actual Primary Completion Date May 17, 2017   (Final data collection date for primary outcome measure)
Current Primary Outcome Measures
 (submitted: January 25, 2016)
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
Original Primary Outcome Measures Same as current
Change History
Current Secondary Outcome Measures Not Provided
Original Secondary Outcome Measures Not Provided
Current Other Pre-specified Outcome Measures Not Provided
Original Other Pre-specified Outcome Measures Not Provided
 
Descriptive Information
Brief Title An Observational Study to Develop Algorithms for Identifying Opioid Abuse and Addiction Based on Admin Claims Data
Official Title An Observational Study to Develop Computable Algorithms for Identifying Opioid Abuse and Addiction Based on Administrative Claims Data
Brief 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
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 Type Observational
Study Design Observational Model: Other
Time Perspective: Retrospective
Target Follow-Up Duration Not Provided
Biospecimen Not Provided
Sampling Method Probability Sample
Study Population Patients with at least two years continuous enrollment in Group Health integrated group practice (IGP) receiving ER/LA opioid analgesics
Condition
  • Opioid-Related Disorders
  • Opiate Addiction
  • Narcotic Abuse
  • Drug Abuse
Intervention Other: Algorithm to identify patients experiencing opioid abuse/addiction
Study Groups/Cohorts Extended Release and/or Long-Acting Opioids
Intervention: Other: Algorithm to identify patients experiencing opioid abuse/addiction
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.

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Recruitment Information
Recruitment Status Completed
Actual Enrollment
 (submitted: April 14, 2020)
1667
Original Estimated Enrollment
 (submitted: January 25, 2016)
4000
Actual Study Completion Date May 17, 2017
Actual Primary Completion Date May 17, 2017   (Final data collection date for primary outcome measure)
Eligibility Criteria

Inclusion Criteria:

  1. Age ≥ 18 years
  2. 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)
  3. Minimum of at least two years continuous enrollment in Group Health integrated group practice (IGP)

Exclusion Criteria:

  1. Residence in a nursing home at any time during the study period
  2. Enrollment in a hospice care program at any time during the study period
Sex/Gender
Sexes Eligible for Study: All
Ages 18 Years and older   (Adult, Older Adult)
Accepts Healthy Volunteers Not Provided
Contacts Contact information is only displayed when the study is recruiting subjects
Listed Location Countries Not Provided
Removed Location Countries  
 
Administrative Information
NCT Number NCT02667262
Other Study ID Numbers Observational Study 3033-7
3033-7 ( Other Identifier: Member Companies of the Opioid PMR Consortium )
Has Data Monitoring Committee Not Provided
U.S. FDA-regulated Product Not Provided
IPD Sharing Statement Not Provided
Responsible Party Member Companies of the Opioid PMR Consortium
Study Sponsor Member Companies of the Opioid PMR Consortium
Collaborators
  • World Health Information Science Consultants, LLC
  • Kaiser Permanente
Investigators
Study Chair: Paul Coplan, MS, ScD, MBA Purdue Pharma LP
PRS Account Member Companies of the Opioid PMR Consortium
Verification Date April 2020