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

Study Overview
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Brief Summary
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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
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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.

Official Title
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An Observational Study to Develop Computable Algorithms for Identifying Opioid Abuse and Addiction Based on Administrative Claims Data

Conditions
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Opioid-Related Disorders, Opiate Addiction, Narcotic Abuse, Drug Abuse

Intervention / Treatment
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* Other: Algorithm to identify patients experiencing opioid abuse/addiction


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: 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) Exclusion Criteria: 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

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Extended Release and/or Long-Acting Opioids<br> | Other: Algorithm to identify patients experiencing opioid abuse/addiction<br> <br> |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 | Retrospective review of data from 2006 to 2015, up to 9 years |