Study to Validate Coded Medical Terms Used to Identify Opioid-Related Overdose in Databases Used for PMR Study 1B

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Total Enrollment

2701 participants

Study Classification

OBSERVATIONAL

Study Start Date

2015-04-07

Study Completion Date

2017-05-17

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

The purpose of this study is to determine reliability of codes and data from electronic medical records to predict and measure overdose and death in patients prescribed opioid analgesics. The study will compare this electronic data to data manually obtained from medical charts.

Related Clinical Trials

Explore similar clinical trials based on study characteristics and research focus.

24-hour Oral Morphine Equivalent Based Opioid Prescribing After Surgery

NCT04043143

Opioid Use

COMPLETED NA

Double Blind Randomized, Monocentric, Cross-over, Placebo-controlled Study to Evaluate the Effect of Morphine and Naloxone on Motivation (MBBAnalgesic)

NCT02267304

Healthy

COMPLETED PHASE2

Reduced Opioid Analgesic Requirements Via Improved Endogenous Opioid Function

NCT02469077

Chronic Pain

COMPLETED NA

Characteristics and Clinical Implications of a Clinical Decision Support System

NCT03295097

Chronic Illness Opioid Use Palliative Care

COMPLETED NA

Opioid Treatment and Recovery Through a Safe Pain Management Program

NCT03889418

Depression Opioid Use Chronic Pain +1 more

COMPLETED NA

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

As part of a series of post-marketing requirement (PMR) studies for extended-release (ER) and long-acting (LA) opioid analgesics, the Food and Drug Administration (FDA) is requiring New Drug Application (NDA) holders of ER/LA opioids to conduct studies to estimate the incidence of misuse, abuse, addiction, overdose, and death among patients with chronic pain using long-term opioid therapy, and to validate the measures used to estimate the incidence of these adverse events.

The purpose of this study is to validate the measurement of opioid overdose events using diagnostic codes and data extracted from notes written in the electronic medical record (EMR), accompanied by diagnostic algorithms, to be used in a study of the incidence and predictors of opioid overdose and death (PMR Study 1B) among patients prescribed opioid analgesics. Diagnostic codes, accompanied by diagnostic algorithms, will be compared against manually abstracted medical chart reviews.

Code-based algorithms will be useful for identifying opioid overdoses in claims-based systems that include only coded data and will also find applicability in systems with EMRs. Code-based algorithms will be improved with text search of EMR clinical notations using Natural Language Processing (NLP) to identify overdose events not identified by diagnostic codes and to differentiate between intentional and unintentional overdoses. Yield from the resulting EMR-based algorithm will again be compared against manually abstracted medical chart reviews.

This EMR-based algorithm will be useful for identifying opioid overdoses in systems with EMRs, and for further differentiating between the causes of different types of overdoses. For example, overdose events can be due to misuse (e.g., therapeutic use not as indicated by a clinician), medication errors by patients, medical errors made by prescribers, abuse by patients, abuse by non-patients feigning to be patients in order to receive medications; and suicides. Overdose events therefore differ in intentionality, that is whether the person was attempting suicide or not. Unintentional overdoses can occur as a result of various causes, including misuse (therapeutic use but not consistent with clinician orders), abuse, adverse reactions to medications, anesthesia, and medication errors-both patient and provider-based. In addition, the distinction between unintentional and intentional overdoses can sometimes be unclear. This validation study will attempt to differentiate overdose by intentionality using both code-based algorithms and NLP-enhanced algorithms.

Currently, administrative databases use ICD-9 codes for nonfatal diagnoses and ICD-10 codes for fatal events. In October of 2015, ICD-10 codes are scheduled to replace ICD-9 codes for nonfatal diagnoses in administrative databases. This study will validate existing ICD-9 codes so that the study can meet the FDA-required timeline for a final report by November 2015.

This study will not evaluate misuse since this will be captured by instruments in a prospective study of patients with chronic pain (PMR Study 1A) using a combination of adapted validated instruments, and new instruments that will be evaluated in PMR Study 2. This study will not include a formal validation for opioid-related deaths, since processes for coding deaths vary from state to state, but will include some verification of opioid-related deaths relative to medical records for events with available state and national death data (there is a 12-month to 2-year lag in state death records).

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Opioid-Related Disorders Opiate Addiction Narcotic Abuse Drug Abuse

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

OTHER

Study Time Perspective

RETROSPECTIVE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Opioid overdose and poisoning

Algorithm to determine overdose from opioid abuse

Intervention Type OTHER

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

Algorithm to determine overdose from opioid abuse

Intervention Type OTHER

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

Members of the KPNW integrated healthcare system located in the states of Oregon and southwestern Washington, between August 2008 and December 2014

* Approximately 1,200 events identified based on ICD diagnostic codes for opioid poisoning, overdose or opioid-related cause of death
* A random sample of approximately 1,250 individuals at increased risk of opioid overdose identified based on ICD diagnoses for opioid-related adverse effects, pain, mental health, or substance abuse

Exclusion:

None

Eligible Sex

ALL

Accepts Healthy Volunteers

No