Prevalence and Risk Factors Associated With Long-term Opioid Use After Injury Among Previously Opioid-Free Workers

Importance Using opioids for acute pain can lead to long-term use and associated morbidity and mortality. Injury has been documented as a gateway to long-term opioid use in some populations, but data are limited for injured workers. Objective To evaluate the prevalence and risk factors of long-term opioid use after injury among workers in Tennessee who were opioid free at the time of injury. Design, Setting, and Participants This cohort study identified injured workers aged 15 to 99 years who reported only 1 injury to the Tennessee Bureau of Workers’ Compensation from March 2013 to December 2015 and had no opioid prescription in the 60 days before injury. Participants were matched to their prescription history in Tennessee’s prescription drug monitoring program. Analysis was conducted from November 2017 to March 2018. Logistic regression models were used to calculate adjusted odds ratios (ORs) and 95% CIs for associations of demographic, injury, and opioid use variables with long-term use. Main Outcomes and Measures The primary outcome was long-term opioid use, defined as having an opioid supplied for 45 or more days in the 90 days after injury. Results Among 58 278 injured workers who received opioids after injury (18 977 [32.5%] aged 15-34 years, 27 514 [47.2%] aged 35-54 years, and 11 787 [20.2%] aged 55-99 years; 32 607 [56.0%] men), 46 399 (79.6%) were opioid free at the time of injury. Among opioid-free injured workers, 1843 (4.0%) began long-term opioid use. After controlling for covariates, long-term use was associated with receiving 20 or more days’ supply in the initial opioid prescription compared with receiving less than 5 days’ supply (OR, 28.94; 95% CI, 23.44-35.72) and visiting 3 or more prescribers in the 90 days after injury compared with visiting 1 prescriber (OR, 14.91; 95% CI, 12.15-18.29). However, even just 5 days’ to 9 days’ supply was associated with an increase in the odds of long-term use compared with less than 5 days’ supply (OR, 1.83; 95% CI, 1.56-2.14). Conclusions and Relevance In this study of injured workers, injury was associated with long-term opioid use. The number of days’ supply of the initial opioid prescription was the strongest risk factor of developing long-term use, highlighting the importance of careful prescribing for initial opioid prescriptions

Influenza and Pregnant Women: Hospitalization Burden, United States, 1998–2002

Women in later stages of pregnancy are at increased risk for serious influenza-related morbidity; thus, universal influenza vaccination of pregnant women is recommended. However, vaccine uptake in the United States has been suboptimal. We previously described the burden of severe influenza-related morbidity during pregnancy in the United States by examining hospitalizations of pregnant women with respiratory illness during influenza season. Nondelivery hospitalizations with respiratory illness had significantly longer lengths of stay than those without respiratory illness. Hospitalization characteristics associated with greater likelihood of respiratory illness were the presence of a high-risk condition for which influenza vaccination is recommended, Medicaid/Medicare as primary expected payer, and hospitalization in a rural area. These findings may be explained by these women being at higher risk of influenza-related morbidity or reflect disparities in receipt of influenza immunization. Universal vaccination of pregnant women to decrease influenza-related morbidity should be encouraged.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63171/1/jwh.2006.15.891.pd

Outcomes for Implementation Research: Conceptual Distinctions, Measurement Challenges, and Research Agenda

An unresolved issue in the field of implementation research is how to conceptualize and evaluate successful implementation. This paper advances the concept of “implementation outcomes” distinct from service system and clinical treatment outcomes. This paper proposes a heuristic, working “taxonomy” of eight conceptually distinct implementation outcomes—acceptability, adoption, appropriateness, feasibility, fidelity, implementation cost, penetration, and sustainability—along with their nominal definitions. We propose a two-pronged agenda for research on implementation outcomes. Conceptualizing and measuring implementation outcomes will advance understanding of implementation processes, enhance efficiency in implementation research, and pave the way for studies of the comparative effectiveness of implementation strategies

Parental report of health conditions and health care use among children with and without autism: National survey of children\u27s health

Objective: To compare parent-reported prevalence of health conditions and health care use between children with and without autism. Design: Cross-sectional analysis of the 2003 to 2004 National Survey of Children\u27s Health. Setting: Population-based sample across the United States. Participants: More than 100 000 parents. The main exposure was autism (not further defined), from response to the question: Has a doctor or health professional ever told you that your child has autism? Main Outcome Measures: Medical and mental health conditions and measures of health care use. Results: Autism prevalence among children aged 3 to 17 years was 53 per 10 000 (95% confidence interval, 45-61 per 10 000), equating to a national estimate of 324 000 children (95% confidence interval, 274 000-375 000 children). Children with autism had a significantly (P\u3c.001) higher prevalence of depression or anxiety problems (38.9% vs 4.2%) and behavioral or conduct problems (58.9% vs 5.2%) than children without autism. Respiratory, food, and skin allergies were reported by parents more often for children with autism, with food allergies having the strongest relative difference between the groups (odds ratio, 4.5; 95% confidence interval, 3.0-7.0). Children with autism had significantly (P\u3c.001) higher mean physician visits over 12 months for preventive care, nonemergency care, and hospital emergency care, and were far more likely than children without autism to receive physical, occupational, or speech therapy (76.0% vs 6.3%), to need treatment or counseling for an emotional, developmental, or behavioral problem (75.4% vs 7.0%), and, among those taking a prescribed medication, to be using a medication long-term (51.4% vs 14.5%). Conclusion: We found markedly higher reports of concurrent conditions and health care use associated with childhood autism in this study. ©2006 American Medical Association. All rights reserved

Comparison of indicators for a primary care medical home between children with autism or asthma and other special health care needs: National Survey of Children\u27s Health

Objective: To assess the extent to which parents of children with autism compared with parents of children with asthma or other special health care needs report receiving primary care for their child consistent with the American Academy of Pediatrics medical home model. Design: Population-based cross-sectional study. Setting: National Survey for Children\u27s Health 2003-2004 telephone interview. Participants: Parents of 495 children with autism, parents of 6716 children with asthma, and parents of 11403 children with other special health care needs without asthma. Main Exposures: Autism and other special health care needs including asthma. Main Outcome Measures: Medical home score and components of care, as follows: personal provider and preventive; family-centered, compassionate, and culturally appropriate; accessible; comprehensive; and coordinated. Results: The odds of parents reporting care consistent with that in a medical home were less likely for children with autism (odds ratio, 0.45; 95% confidence interval, 0.30-0.66) and more likely for children with asthma (odds ratio, 1.17;95%confidence interval, 1.06-1.30) compared with children with other special health care needs (1 [reference]). These differences persisted even after controlling for condition severity, personal characteristics, and insurance status. Specific components of a medical home less prevalent among children with autism than among children with other special health care needs included familycentered, comprehensive, and coordinated care. Conclusion: Although we could not evaluate the reasons why, a large percentage of children with autism do not receive primary care consistent with that in a medical home. ©2007 American Medical Association

Improving risk factor identification for opioid overdose deaths in Tennessee

ObjectiveTo examine specific drugs present based on postmortem toxicology for prescription opioid, heroin, and fentanyl overdoses classified based on ICD-10 coding. To compare drugs identified from postmortem toxicology with those listed on the death certificate for opioid overdoses.IntroductionUsing death certificates alone to identify contributing substances in drug overdose deaths may result in misclassification and underestimation of the burden of illicit and prescription opioids and other drugs in drug-related deaths. To enable timely and targeted prevention in Tennessee (TN), the identification and monitoring of new drugs and trends in use should utilize toxicology and medicolegal death investigation data directly, as recommended by others 1-3. These data can inform mortality outcome definitions for improved surveillance and risk factor identification 4-7. To our knowledge, this is the first analysis to use statewide linked toxicology and death certificate data in TN.MethodsWe identified 615 opioid involved overdose deaths in TN of unintentional (underlying ICD-10 codes: X40-X44) or undetermined (underlying ICD-10 codes: Y10-Y14) intent during June 1st to December 31st 2017. Utilizing the Interim Medical Examiner Database (I-MED), we identified postmortem toxicology reports for 454 cases, which were from one of three national laboratories used by a state Regional Forensic Center. Toxicology data were abstracted and independently verified by two co-authors and linked to the TN death statistical file that included cause of death information (literal text and ICD-10 codes) and demographics. The analysis focuses on cases with an available toxicology report.ResultsWe identified 171 prescription opioid overdoses, 221 fentanyl overdoses, and 113 heroin overdoses. Table 1 displays postmortem toxicology profiles for major drugs/classes. For prescription opioid deaths (excluding fentanyl and heroin), positive toxicology results for prescription opioids were as follows: methadone (11%), buprenorphine (14%), hydrocodone (14%), oxycodone (36%) and oxymorphone (also a metabolite, 47%). Benzodiazepines were present in close to 58% of prescription opioid overdoses; stimulants (cocaine, amphetamines, methamphetamines) in about 25%. For fentanyl and heroin deaths, prescription opioids were detected in about 26% and 34%, respectively; stimulants in about 57.9% and 52.2%, respectively, and benzodiazepines 36-37%. Fentanyl was present on toxicology in about half of heroin overdoses, and 6–monoacetylmorphine in 72.6%.ConclusionsUsing medical examiners’ data, including toxicology data, improves estimation of contributing drugs involved in opioid deaths. This analysis provides jurisdiction-specific data on drugs that can help with monitoring trends and informs risk factor identification. Future work includes adding information on prescribed opioid and benzodiazepines using TN’s Prescription Drug Monitoring Database and evaluating demographic variation in contributing drugs between toxicology and DC data to identify susceptible populations.References1. Slavova S, O'Brien DB, Creppage K, Dao D, Fondario A, Haile E, Hume B, Largo TW, Nguyen C, Sabel JC, Wright D, Council of S, Territorial Epidemiologists Overdose S. Drug Overdose Deaths: Let's Get Specific. Public Health Rep.2. Horon IL, Singal P, Fowler DR, Sharfstein JM. Standard Death Certificates Versus Enhanced Surveillance to Identify Heroin Overdose-Related Deaths. Am J Public Health. 2018;108(6):777-81.3. Mertz KJ, Janssen JK, Williams KE. Underrepresentation of heroin involvement in unintentional drug overdose deaths in Allegheny County, PA. J Forensic Sci. 2014;59(6):1583-5.4. Landen MG, Castle S, Nolte KB, Gonzales M, Escobedo LG, Chatterjee BF, Johnson K, Sewell CM. Methodological issues in the surveillance of poisoning, illicit drug overdose, and heroin overdose deaths in new Mexico. Am J Epidemiol. 2003;157(3):273-8.5. Davis GG, National Association of Medical E, American College of Medical Toxicology Expert Panel on E, Reporting Opioid D. Complete republication: National Association of Medical Examiners position paper: Recommendations for the investigation, diagnosis, and certification of deaths related to opioid drugs. J Med Toxicol. 2014;10(1):100-6.6. Slavova S, Bunn TL, Hargrove SL, Corey T. Linking Death Certificates, Postmortem Toxicology, and Prescription History Data for Better Identification of Populations at Increased Risk for Drug Intoxication Deaths. Pharmaceutical Medicine. 2017;31(3):155-65.7. Hurstak E, Rowe C, Turner C, Behar E, Cabugao R, Lemos NP, Burke C, Coffin P. Using medical examiner case narratives to improve opioid overdose surveillance. Int J Drug Policy. 2018;54:35-42.