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 : Unknown
Verified April 2017 by Member Companies of the Opioid PMR Consortium.
Recruitment status was: Active, not recruiting
First Posted : January 28, 2016
Last Update Posted : April 28, 2017
|Condition or disease||Intervention/treatment|
|Opioid-Related Disorders Opiate Addiction Narcotic Abuse Drug Abuse||Other: Algorithm to identify patients experiencing opioid abuse/addiction|
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|
|Estimated Enrollment :||4000 participants|
|Official Title:||An Observational Study to Develop Computable Algorithms for Identifying Opioid Abuse and Addiction Based on Administrative Claims Data|
|Estimated Primary Completion Date :||September 2017|
|Extended Release and/or Long-Acting Opioids||
Other: Algorithm to identify patients experiencing opioid abuse/addiction
- 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
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02667262
|Study Chair:||Paul Coplan, MS, ScD, MBA||Purdue Pharma LP|