Protocol: changes in rates of opioid overdose and poisoning events in an integrated health system following the introduction of a formulation of OxyContin® with abuse-deterrent properties
© Janoff et al. 2016
Received: 21 May 2015
Accepted: 12 April 2016
Published: 14 May 2016
Addiction, overdoses and deaths resulting from prescription opioids have increased dramatically over the last decade. In response, several manufacturers have developed formulations of opioids with abuse-deterrent properties. For many of these products, the Food and Drug Administration (FDA) recognized the formulation with labeling claims and mandated post-marketing studies to assess the abuse-deterrent effects. In response, we assess differences in rates of opioid-related overdoses and poisonings prior to and following the introduction of a formulation of OxyContin® with abuse-deterrent properties.
To assess effects of this formulation, electronic medical record (EMR) data from Kaiser Permanente Northwest (KPNW) and Kaiser Permanente Northern California (KPNC) are linked to state death data and compared to chart audits. Overdose and poisoning events will be categorized by intentionality and number of agents involved, including illicit drugs and alcohol. Using 6-month intervals over a 10-year period, trends will be compared in rates of opioid-related overdoses and poisoning events associated with OxyContin® to rates of events associated with other oxycodone and opioid formulations. Qualitative interviews with patients and relatives of deceased patients will be conducted to capture circumstances surrounding events.
This study assesses and tracks changes in opioid-related overdoses and poisoning events prior to and following the introduction of OxyContin® with abuse-deterrent properties. Public health significance is high because these medications are designed to reduce abuse-related behaviors that lead to important adverse outcomes, including overdoses and deaths.
KeywordsOxyContin® Opioids Overdose Poisoning Prescription drug monitoring
As opioid-related risks to public health have become apparent [1–9] various efforts have been implemented to mitigate opioid-related negative outcomes. States have implemented prescription drug monitoring programs [10, 11], and the FDA now requires manufacturers of long-acting opioids to develop Risk Evaluation and Mitigation Strategies (REMS) and encourages opioid prescribers to complete REMS-compliant education programs . Manufacturers of long-acting opioids have also begun reformulating products to include abuse-deterrent properties, with the goal of reducing prescription opioid abuse . In April 2010, the FDA approved a reformulation of OxyContin® (manufactured by Purdue Pharma L.P.) with abuse-deterrent properties. The goal of the abuse-deterrent formulation was to make it difficult to crush, cut, break or liquefy pills, reducing likelihood that the medication could be snorted, smoked, or injected. The reformulated product was introduced to the market in August 2010. In April 2013, the FDA approved labeling claims that OxyContin® was expected to result in “reduced abuse through intranasal and injecting routes” , although abuse by these methods, and the oral route, is still possible . Evidence since its introduction shows that rates of abuse have diminished [16, 17] and then leveled off , as have overdoses attributed to prescription opioids . Calls to poison centers related to OxyContin® abuse, accidental exposures, and therapeutic errors were similarly reduced [19, 20]. In contrast, heroin use and heroin overdoses have increased substantially in recent years [18, 21], attributable to the prescription drug epidemic  and, in part, to switching from abuse-deterrent opioid formulations to heroin . No harms or adverse effects have been identified related to the physical/chemical properties of the reformulated medication when it is abused, though such harms have been documented in the case of other medications, including injection of temazepam gel capsules , and thrombotic thrombocytopenia purpura resulting from injection of abuse-deterrent extended-release Opana .
Despite this evidence, a comprehensive assessment of the effects of abuse-deterrent OxyContin® on overdose is lacking. The study protocol described here is a mixed methods research project designed to address that gap by using full electronic medical records of two large integrated health plans, linked to state death data, and to interviews with individuals experiencing overdoses, or their family members. We analyze overdose rates among individuals with active opioid prescriptions, classified in groups, and among individuals without opioid prescriptions. We also examine changes in heroin-related overdoses. Analyses are based on patient electronic medical record (EMR) data, chart audits, and in-depth qualitative interviews.
Assess the validity of International Classification of Diseases (ICD-9 and ICD-10) diagnoses to accurately identify and categorize opioid-related overdoses and poisonings using chart audits.
- 2)Estimate rates of, and compare trends in, opioid-related overdoses among all members of the participating health plans:
before and after the introduction of OxyContin® with abuse-deterrent properties,
among patients with and without active opioid prescriptions,
Compare the ratio of rates of opioid-related overdoses and poisoning events among patients prescribed and dispensed OxyContin® with rates in comparator opioid groups, 2 years prior to and 2 years following the introduction of the new formulation of OxyContin®.
Conduct exploratory in-depth interviews with a subset of patients who experience opioid-related overdoses and poisoning events (or their relatives) to examine and understand circumstances surrounding overdose events, and involvement of OxyContin®. Triangulate data with chart audit data to describe substances involved in overdoses, including heroin, and assess whether individuals abusing OxyContin® switch to heroin in response to the new formulation.
The setting for this study is Kaiser Permanente Northwest (KPNW) and Kaiser Permanente Northern California (KPNC), nonprofit, group model, integrated health systems serving about 3.9 million members (500,000 in KPNW and 3.4 million in KPNC). KPNW and KPNC provide outpatient and inpatient medical, mental health, and addiction treatment services and they maintain integrated EMRs that contain comprehensive administrative and treatment data on all members. Though the majority of the membership in both health plans is comprised of individuals with private insurance, both plans cover substantial numbers of Medicare members and, to a lessor extent, Medicaid members. Consistent with other settings, substance abuse and misuse are common, and the health plans’ membership is generally representative of the populations in the geographic areas they serve. The study protocol and all study procedures are reviewed, approved, and monitored by the Research Subjects Protection Office of the Institutional Review Board at KPNW.
The study population includes all members of the KPNW and KPNC health systems from February 1, 2003 through July 1, 2013. The total sample size will include approximately 7,500,000 unique individuals across the two health plans (~1,100,000 from KPNW and ~6,400,000 from KPNC).
Aims 1–3: quantitative data collection
Opioid-related overdoses and poisoning event identification and categorization
ICD poisoning codes used to identify overdosesa
ICD 9 code
ICD 10 code
Poisoning by opium (alkaloids) unspecified
Poisoning by heroin
Poisoning by methadone
Poisoning by other opiates and related narcotics
Accidental poisoning by heroin
Accidental poisoning by methadone
Accidental poisoning by other opiates and related narcotics
COD: Poisoning by opiates and related narcotics
COD: Poisoning by opium
COD: Poisoning by heroin
COD: Poisoning by other opioids
COD: Poisoning by methadone
COD: Poisoning by other synthetic narcotic
COD: Accidental poisoning by and exposure to narcotics and psychodysleptics, not elsewhere classified
COD: Intentional self-poisoning by and exposure to narcotics and psychodysleptics, not elsewhere classified
COD: Undetermined poisoning by and exposure to narcotics and psychodysleptics, not elsewhere classified
Opioid adverse effect codes used in combination with related diagnostic codes used to identify overdoses. To meet criteria, a case had to include one diagnosis from category A and one more diagnoses from category B on the same date
ICD 9 code
ICD 10 code
Adverse effects of heroin
Adverse effects of methadone
Adverse effects of other opioids and related narcotics
COD: Adverse effects of opioids and related analgesics
Mixed acid–base balance disorder
Drug-induced psychotic disordersa
Drug-induced mental disorderb
Pneumonia, organism unspecified
Chronic airway obstruction, not elsewhere classified
Acute respiratory failure
Other pulmonary insufficiency, not elsewhere classified
Alteration of consciousness
Altered mental state
Shortness of breath
Dyspnea and respiratory abnormalities—other
Asphyxia and hypoxemia
Poisoning by opiate antagonists
Suicide and self-inflicted injury
Assault by drugs and medicinal substances
Injection, Naloxone Hydrochloride
Classification structure for specific medications included in opioid medication hierarchy
Other Class REMS
fentanyl transdermal patch
Other Opioids (oxycodone MIIR)
oxycodone + acetaminophen
oxycodone + ibuprofen
oxycodone + aspirin
hydrocodone + acetaminophen
codeine + acetaminophen
State death data
State death data (ICD-10 codes for underlying cause of death, contributory cause of death, and immediate cause of death) are transferred to each site, incorporated into the site’s data warehouse (harmonized across sites) using a matching algorithm to identify health plan members, and linked to electronic medical records and administrative data for use in analyses. Only data from health plan members are retained. All death data are available for the full study period for KPNW members, though only underlying cause of death is available for the full study period for the KPNC membership. Therefore, we include only underlying cause of death in primary analyses. It is possible that deaths outside the relevant states may be missed, but believe this to be a negligible problem.
Demographic information available through administrative systems will be collected, including age, gender, race/ethnicity, Medicaid insurance, Medicare insurance. Diagnostic data for the year preceding overdose or poisoning events will also be collected for descriptive purposes (e.g., history of substance use disorders; history of psychiatric disorders).
Aim 1: data collection for opioid-related overdoses and poisoning event validation
To assess the validity of using EMR diagnoses to accurately identify and categorize opioid-related overdoses and poisoning events, chart audits are conducted with a subset of identified opioid-related overdoses and poisoning events (Aim 1). Audits are conducted for the 2 years prior to the introduction of the reformulated OxyContin® and the 2 years following its introduction (August 1, 2008 through July 31, 2012). Provided with health record numbers, event dates, and inclusion diagnoses, chart auditors review the EMR to locate the identified event for each person and then compile all associated records for that event. Records used may include history and physical records, discharge summary, medication activity report, telephone encounters, and any other related documentation. All printed material and forms are kept in confidential, locked files at all times when not in use.
Staff training begins with a sample of events reviewed by all chart audit staff, adjudicators, and project investigators at both sites to identify any issues with the chart audit form, clarify questions, and ensure consistency in review. A weekly teleconference call with chart audit staff, investigators, expert adjudicators, and administrative staff is held to identify and resolve questions related to the events and the chart audit process. At each site, 200 of the first sample of charts are adjudicated by senior research staff. Once the chart review form and associated instructions are finalized, abstractors work on individualized opioid-related overdoses and poisoning event lists. Biweekly teleconferences are convened for chart audit staff to discuss and resolve individual cases and to refine definitions and instructions as needed.
The chart audit form is completed by auditors to document the causal opioid(s), additional contributing medication(s), contributing alcohol or illicit drug use, prescription detail (dose and frequency), route of administration for each substance, source of each substance when available (e.g., prescription, friend, family member, Internet, street, etc.), and any indication of misuse, abuse, or over-administration for each substance. Auditors also use the form to record administration and response to naloxone hydrochloride and whether the event is solely related to anesthesia administered for a procedure. Events solely related to anesthesia are not abstracted further.
- 1)The extent to which substances are involved with the event (only one option is selected)
Not an opioid event (no mention of opioids).
Single opioid event (only one opiate is involved in the event; no other medications or other substances likely contribute, per documentation).
Poly-substance opioid event (at least one substance in addition to an opioid likely or possibly contributes to the event, per documentation).
Event unrelated to opioid use (there is a mention of opioids at the time of the event but opioids did not contribute to the event).
- 2)Whether the event appears to be one of the following (only one option is selected):
Miscode (diagnostic code or codes that appear to have been applied in error, or documentation of event that does not match the codes applied to that event).
Misidentification (diagnostic code or codes and medication are both correct but are not related to each other and not of interest to the study).
Neither of the above (documentation in chart is consistent with the EMR-based identification of the event).
When an event is deemed to be miscoded or misidentified, the audit is stopped and the event is sent to an expert adjudicator for confirmation and further documentation regarding the specifics of the miscode or misidentification determination. This information is logged separately from the audit form. These data are compiled and are analyzed separately to look for patterns in inconsistently or incorrectly applied ICD codes within the EMR system.
Intentional opioid-related overdose or and poisoning (EMR records are clear that the event was intentional [e.g., suicide or attempt] and involved opioids [single-opioid or poly-drug]).
Unintentional opioid-related overdoses or poisoning (EMR records are clear that the event was not intentional [e.g., trying to get high; medication error] and involved opioids [single-opioid or poly-drug]).
Adverse effect related to opioid use (event related o opioid use but did not require intervention beyond adjusting or discontinuing medication for resolution). Sensitivities to properly administered medications are coded here unless they require additional intervention to resolve symptoms.
Intentional vs unintentional: If coding documents any indication of suicide (e.g., attempt, ideation, self-inflicted) the event is determined to be “intentional”. If there is no such mention, the event is coded “unintentional”.
Single vs poly-drug: If there is an indication of more than one substance based on outside claims coding (e.g., alcohol intoxication and accidental opiate poisoning) the event is coded “poly-drug”. If only one substance is recorded as poisoning (e.g., methadone poisoning) the event is coded “single”. If only one substance is recorded but additional opiate poisoning or abuse codes are also applied (e.g., heroin poisoning and opioid abuse) the event is coded “single”.
If there is no information in the claims data related to opioid use, the event is coded as “not an opioid event”.
Each audit file is reviewed for missing data prior to data entry; if forms are incomplete, the file is returned to the staff person who collected the data for completion. Ten percent of charts are reviewed by two reviewers to assess and maintain high inter-rater reliability (>95 %). All identified errors are discussed and corrected. Once abstraction files are complete, data are entered into an electronic database using double entry verification until adequate accuracy is obtained (less than 1 error/100 entries). Once this level is achieved, 10 % of data are double-entered as a continuous check. Following entry, data files from both sites are merged for analysis.
Aim 4: qualitative data collection
To understand the circumstances surrounding opioid-related overdoses and poisoning events, we conduct in-depth interviews with a subset of patients who experience an opioid-related overdoses and poisoning event. We also conduct interviews with family members of patients who died as a result of an opioid-related overdoses and poisoning event.
Interview candidates (n = 90) are identified from the sample of KPNW member with identified opioid-related overdoses or poisoning events. Family members are identified using subscriber account information linked to the decedent’s EMR information, when such information is available.
We sample randomly from purposefully derived pools of people with and without active prescriptions for opioids and oversampling within key subgroups. Pharmacy records are reviewed to determine whether a person with an opioid-related overdose and poisoning event had an active opioid prescription at the time of the event. Because numbers of OxyContin®-associated events are small, we oversample members with active OxyContin® or sustained release oxycodone prescriptions at the time of the event. We also oversample members with no active opioid prescription (no opioid group) in order to identify people engaged in non-medical use of opioids. Members with events in the remaining three comparator groups (oxycodone SIIR, other class REMS, and other opioid) are sampled proportionally based on the number of total opioid-related overdoses and poisoning events identified in each of those categories. We also attempt to balance our sample to obtain roughly equal numbers of male and female participants in each of the opioid categories.
Potential participants are recruited using mailed letters with follow-up telephone calls inviting participation in a one-time interview and promising compensation of $50. For deceased health plan members whose medical records indicate that opioid overdose was the cause of death and who have no other members associated with their subscriber unit, we mail a letter to the deceased member’s most recent address.
To improve recall regarding the circumstances surrounding opioid-related overdoses and poisoning events, interview candidates are identified from the opioid-related overdose and poisoning event sample from the 6 months prior to the introduction of OxyContin® with abuse-deterrent properties through the years following the introduction. Individuals with more than one active opioid prescription at the time of the opioid-related overdoses and poisoning event (e.g., a sustained-release formulation and an immediate-release formulation for breakthrough pain) are sampled based on their categorization into their “highest” medication comparator group in the hierarchy.
The purpose of the qualitative interviews is to gain further insight into patients’ experiences of overdoses and poisoning events; with family members the goal is to understand as much as possible about the decedent’s experiences prior to overdose. Interviews with patients are semi-structured and focus on pain history, initiation of analgesic medications, switches in prescribed opioid medications or change in dose, misuse of opioids or other prescription medications, illegal drug use and abuse history, the circumstances leading up to and culminating in the specific overdose or poisoning event identified through the EMR, and any post-event treatment plans, medication changes or changes in drug use activity. Because many people experience more than one opioid-related overdose and poisoning event, those additional events may also be explored. We also ask about the opioids individuals were taking, other prescribed medications at the time of the events, contributing alcohol or illicit drug use, prescription details (dose and frequency), route of administration for each substance, and source of each substance (e.g., prescription, friend, family member, Internet, street, etc.). Interviewers also explore indicators of of misuse, abuse, or over-administration for each substance as well as mental health status. Interviews with family members focus on similar questions.
Interviews are conducted using a semi-structured interview guide (see Additional files 1 & 2) to ensure similar questions are asked of all participants. Additional prompts and questions are added during individual interviews to further explore important information.
Experienced master’s- and doctoral-level staff members conduct these hour-long interviews. Participants consent to participate in the interview portion of the study and are provided a copy of their signed consent form and a $50 gift card to a local supermarket chain upon interview completion.
Aim 1 analyses: assess the validity of ICD-9 and ICD-10 diagnoses to accurately identify and categorize opioid-related overdoses and poisonings using chart audits
Opioid-related overdoses and poisoning events are identified and then compared to chart audits using the following approach: We use individual and combined ICD-9 and ICD-10 codes from the KP Virtual Data Warehouse (VDW), linked to state death data. The VDW, contains comparable data across multiple participating sites, including KPNW and KPNC, for the conduct of research, including enrollment, demographics, tumor registries, pharmacy dispenses, census data, vital signs, and diagnoses and procedures. We then calculate positive predictive value of EMR-based diagnostic codes compared to chart audit determinations and describe final chart audit determinations and categorizations for each code. Overdoses are also described using chart audit-based categorizations (e.g., suicide event or attempt; polydrug event).
Aim 2 analyses: estimate rates of, and compare trends in, opioid-related overdoses before and after the introduction of OxyContin® with abuse-deterrent properties, among patients with and without active opioid prescriptions, and those involving heroin
For Aim 2, we compare trends in rates of opioid-related overdoses and poisoning events associated with OxyContin® to rates of opioid-related overdoses and poisoning events associated with other oxycodone and opioid formulations over a 10-year period (February 1, 2003-July 30, 2013). Rates are computed in 6-month intervals from the 7 years prior to the reformulation of OxyContin® and through the 3 years following the introduction of the new formulation. These rates are graphed over time for each category of opioid (immediate-release single ingredient oxycodone, other long-acting opioids for which the FDA has required REMS, and other Schedule II opioids), and well as overdoses among individuals with no active opioid prescriptions to compare trends across all categories. Prior to 2005, all extended-release (ER) oxycodone distributed in the marketplace was branded OxyContin®. In 2005, several generic manufacturers challenged the patent for branded OxyContin® and began to sell generic extended-release oxycodone. The proportion of branded ER oxycodone (OxyContin®) versus generic ER oxycodone declined rapidly. The manufacturer of OxyContin®, Purdue Pharma, L.P., won the patent back in January 2008 and the proportion of branded versus generic ER oxycodone rapidly increased to approximately 85 % of ER oxycodone used in the U.S. To address these changes in the marketplace, the rates of overdose and poisoning in the period prior to the introduction of the new formulation are calculated separately for branded and generic ER oxycodone. If similar, they will be combined and used as the pre-introduction rates, then compared to the post-introduction rates for branded ER oxycodone.
Calculation of rates
Rates will be computed for each 6-month period for immediate-release single-ingredient oxycodone, other class REMS opioids, and other Schedule II opioids. These two types of rate calculations are used as dependent variables to assess changes in rates of opioid-related overdoses and poisoning events following introduction of the new formulation and to assess secular trends in rates by comparing to the other opioid groups.
Aim 3 analyses: compare the ratio of rates of opioid-related overdoses and poisoning events among patients prescribed and dispensed OxyContin® with rates in comparator opioid groups, 2 years prior to and 2 years following the introduction of the new formulation of OxyContin®
For the rate ratio analysis for Aim 3, we examine overdose and poisoning rates calculated by dividing the number of events by the total number of person-years during pre-reformulation and post-reformulation time periods. Negative binomial regression analysis will be used to compare rates between the pre- and post- time periods. Because the same health plan members can appear both in time periods, a generalized estimating equations (GEE) approach is used to account for the correlated nature of the data. Rate ratios analysis examining change from pre- to post- reformulation will be conducted for each opioid category and heroin overdose events, per 10,000 person years. All persons in the health plans will be included in these analyses regardless of whether or not they were currently prescribed an opioid.
Sample size needed to detect various effect sizes
Reduction in rate of overdose/poisoning events
80 % power
90 % power
Aim 4: qualitative data analysis
Interviews are audio-recorded and transcribed verbatim. Study investigators and interviewers review transcripts weekly throughout data collection to ensure transcript accuracy and appropriate interviewing techniques. Coding schemes for the patient interviews and family member interviews are developed separately. Senior research staff use Atlas.ti software  to systematically apply codes to interview transcripts. We complete check coding throughout the process to ensure coder consistency; inconsistencies are discussed and resolved by the team, and code definitions revised as needed. We anticipate a coder consistency of at least 80 %, and will work to resolve discrepancies, rework code definitions, and retrain coders if this is not achieved. Once data are coded, we generate theme reports following review of code-based queries. Themes are compared within codes and across codes, and text selected to illustrate common themes. Contradictory text is also identified and collected for inclusion in reports. Interview data are then linked to EMR and chart abstraction data, triangulated and compared.
This study is designed to assess and track changes in opioid-related overdoses and poisoning events prior to and following the introduction of OxyContin® with abuse-deterrent properties. The main goals of the study are to 1) identify and assess trends in opioid-related overdoses and poisoning events during the full study period, 2) verify and validate opioid-related overdoses and poisoning events using chart audits, and 3) understand, from the patient’s or family member’s perspectives, the circumstances surrounding opioid-related overdoses and poisoning events. Findings from this study will be significant for several reasons: First, we will be able to assess the effects of OxyContin® with abuse-deterrent properties on overdose and poisoning events. Second, the study will produce validated methods of identifying opioid-related overdoses and poisoning events that can be used for public health surveillance. Third, we will have documented first-person accounts of the circumstances surrounding and leading up to opioid-related overdoses and poisoning events, and the effects of abuse-deterrent properties on the behaviors of individuals with such events.
Strengths and limitations
Strengths of the study included the comprehensive data available through electronic medical records that are linked to health plan administrative and claims data, pharmacy dispenses, and state death records. In addition, chart audits and interviews provide in-depth data that aid understanding of overdose events and circumstances surrounding overdoses. Chart audits will provide an assessment of the validity of using diagnostic codes for identifying overdoses and poisonings. Limitations of the study include that it will be carried out in insured populations, although the health plans’ populations are demographically representative of the populations in the geographic areas they serve and information about overdose in insured populations is also lacking. The health plans are likely, however, to underrepresent individuals in the poorest strata and also those with substance use disorders that would negatively affect ability to obtain or maintain insurance. Death data may be incomplete if individuals do not die in the states of Oregon, Washington, or California, where participating health plans are located. This limitation is expected to be negligible.
Implications for practice
Opioid abuse, dependence, and overdose ruin peoples’ lives, and societal costs are substantial, including lost productivity, increased healthcare costs, and greater criminal justice involvement and costs . Reducing the likelihood of opioid-related overdoses and poisoning events can help both individuals and overall population health. The results of this study will inform clinicians about the effects of adopting opioid medications with abuse-deterrent properties for chronic pain treatment.
electronic medical record
Food and Drug Administration
Kaiser Permanente Northern California
Kaiser Permanente Northwest
Risk Evaluation and Mitigation Strategy
Funding for this study was provided by Purdue Pharma, LP. The funder is provided the opportunity to review and make suggestions regarding study design, data collection, analyses, interpretation of results, and on manuscript drafts. Kaiser Permanente authors retain final control and decision making regarding whether or not any such suggestions are adopted.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Centers for Disease Control and Prevention. Adult use of prescription opioid pain medications - Utah, 2008. MMWR. 2010;59(6):153–7.Google Scholar
- Substance Abuse and Mental Health Services Administration. Results from the 2012 National Survey on Drug Use and Health: Mental Health Findings. NSDUH Series H-47, HHS Publication No. (SMA) 13–4805. In: vol. NSDUH Series H-47, HHS Publication No. (SMA) 13–4805. Rockville: Office of Applied Studies; 2013.Google Scholar
- Centers for Disease Control and Prevention. Emergency department visits involving nonmedical use of selected prescription drugs - United States, 2004–2008. MMWR. 2010;59(23):705–9.Google Scholar
- Johnson EM, Lanier WA, Merrill RM, Crook J, Porucznik CA, Rolfs RT, Sauer B. Unintentional prescription opioid-related overdose deaths: description of decedents by next of kin or best contact, Utah, 2008–2009. J Gen Intern Med. 2013;28(4):522–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Centers for Disease Control and Prevention. Overdose deaths involving prescription opioids among Medicaid enrollees - Washington, 2004–2007. MMWR. 2009;58(42):1171–5.Google Scholar
- Centers for Disease Control and Prevention. Vital signs: overdoses of prescription opioid pain relievers---United States, 1999–2008. MMWR. 2011;60(43):1487–92.Google Scholar
- Warner M, Chen LH, Makuc DM, Anderson RN, Minino AM. Drug poisoning deaths in the United States, 1980–2008. NCHS Data Brief. 2011;81:1–8.PubMedGoogle Scholar
- Warner M, Chen LH, Makuc DM. Increase in fatal poisonings involving opioid analgesics in the United States, 1999–2006. NCHS Data Brief. 2009;22:1–8.PubMedGoogle Scholar
- Birnbaum HG, White AG, Schiller M, Waldman T, Cleveland JM, Roland CL. Societal costs of prescription opioid abuse, dependence, and misuse in the United States. Pain Med. 2011;12(4):657–67.View ArticlePubMedGoogle Scholar
- Chakravarthy B, Shah S, Lotfipour S. Prescription drug monitoring programs and other interventions to combat prescription opioid abuse. West J Emerg Med. 2012;13(5):422–5.View ArticlePubMedPubMed CentralGoogle Scholar
- McCarty D, Bovett R, Burns T, Cushing J, Glynn ME, Kruse SJ, Millet LM, Shames J. Oregon’s strategy to confront prescription opioid misuse: a case study. J Subst Abuse Treat. 2015;48(1):91–5.View ArticlePubMedPubMed CentralGoogle Scholar
- U. S. Department of Health & Human Services. Guidance for Industry Abuse-Deterrent Opioids - Evaluation and Labeling DRAFT GUIDANCE. In: U.S. Department of Health and Human Services Food and Drug Administration Center for Drug Evaluation and Research (CDER). 2013.Google Scholar
- Alexander L, Mannion RO, Weingarten B, Fanelli RJ, Stiles GL. Development and impact of prescription opioid abuse deterrent formulation technologies. Drug Alcohol Depend. 2014;138:1–6.View ArticlePubMedGoogle Scholar
- FDA approves abuse-deterrent labeling for reformulated OxyContin. [http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm348252.htm]. Accessed 19 Dec 2014.
- Cicero TJ, Ellis MS. Abuse-deterrent formulations and the prescription opioid abuse epidemic in the United States: lessons learned from OxyContin. JAMA Psychiatry. 2015;72(5):424–30.View ArticlePubMedGoogle Scholar
- Havens JR, Leukefeld CG, DeVeaugh-Geiss AM, Coplan P, Chilcoat HD. The impact of a reformulation of extended-release oxycodone designed to deter abuse in a sample of prescription opioid abusers. Drug Alcohol Depend. 2014;139:9–17.View ArticlePubMedGoogle Scholar
- Butler SF, Cassidy TA, Chilcoat H, Black RA, Landau C, Budman SH, Coplan PM. Abuse rates and routes of administration of reformulated extended-release oxycodone: initial findings from a sentinel surveillance sample of individuals assessed for substance abuse treatment. J Pain. 2013;14(4):351–8.View ArticlePubMedGoogle Scholar
- Larochelle MR, Zhang F, Ross-Degnan D, Wharam JF. Rates of opioid dispensing and overdose after introduction of abuse-deterrent extended-release oxycodone and withdrawal of propoxyphene. JAMA Intern Med. 2015;175(6):978–87.View ArticlePubMedGoogle Scholar
- Coplan PM, Kale H, Sandstrom L, Landau C, Chilcoat HD. Changes in oxycodone and heroin exposures in the National Poison Data System after introduction of extended-release oxycodone with abuse-deterrent characteristics. Pharmacoepidemiol Drug Saf. 2013;22(12):1274–82.View ArticlePubMedPubMed CentralGoogle Scholar
- Severtson SG, Bartelson BB, Davis JM, Munoz A, Schneider MF, Chilcoat H, Coplan PM, Surratt H, Dart RC. Reduced abuse, therapeutic errors, and diversion following reformulation of extended-release oxycodone in 2010. J Pain. 2013;14(10):1122–30.View ArticlePubMedGoogle Scholar
- Jones CM, Logan J, Gladden RM, Bohm MK. Vital signs: demographic and substance use trends among heroin users - United States, 2002–2013. MMWR Morb Mortal Wkly Rep. 2015;64(26):719–25.PubMedGoogle Scholar
- Unick GJ, Rosenblum D, Mars S, Ciccarone D. Intertwined epidemics: national demographic trends in hospitalizations for heroin- and opioid-related overdoses, 1993–2009. PLoS One. 2013;8(2):e54496.View ArticlePubMedPubMed CentralGoogle Scholar
- Cicero TJ, Ellis MS, Surratt HL. Effect of abuse-deterrent formulation of OxyContin. N Engl J Med. 2012;367(2):187–9.View ArticlePubMedGoogle Scholar
- Dobbin M, Martyres RF, Clode D, Champion De Crespigny FE. Association of benzodiazepine injection with the prescription of temazepam capsules. Drug Alcohol Rev. 2003;22(2):153–7.View ArticlePubMedGoogle Scholar
- Centers for Disease Control and Prevention. Thrombotic thrombocytopenic purpura (TTP)-like illness associated with intravenous Opana ER abuse--Tennessee, 2012. MMWR Morb Mortal Wkly Rep. 2013;62(1):1–4.Google Scholar
- McPherson ML. Demystifying opioid conversion calculations: a guide for effective dosing. Bethesda: American Society of Health System Pharmacists; 2009.Google Scholar
- Friese S. User’s Manual for ATLAS.ti 6.0. Berlin: ATLAS.ti Scientific Software Development GmbH; 2011.Google Scholar