The Role of Spirituality on Physical Activity and Sleep Among African American Long-Term Breast Cancer Survivors.

BACKGROUND: African Americans with chronic conditions have reported the importance of spirituality in their lives. Aspects of spirituality have been shown to be related to physical activity (PA) and sleep, and PA and sleep affect quality of life (QOL). This study examined the association between spirituality, PA, and sleep in long-term African American breast cancer survivors. METHODS: This cross-sectional study included 323 breast cancer survivors who previously participated in a case-only study. During 2015-2016, participants completed a questionnaire focused on survivorship that used validated measures for spirituality, PA, and sleep. Adjusted binary and multinomial logistic regression models estimated odds ratios (aORs) and 95% confidence intervals (CIs) for the associations of spirituality with total PA, meeting PA guidelines, sleep duration, and sleep medication. RESULTS: The mean age at diagnosis was 54.8 (SD = 9.89) years. The range of spirituality scores was 7-48 (median = 44). Among participants who had a score ≥ 44, 59% had high total PA, 61% met PA guidelines, 59% had high sleep duration, and 55% did not use sleep medication. Higher spirituality score was associated with higher total PA (aOR for ≥ 681 min/week: 1.90, 95% CI: 1.03-3.50), meeting PA guidelines (aOR: 1.78, 95% CI: 1.06-2.98), sleep duration > 7 h/night (aOR: 1.72, 95% CI 1.05-2.83), and lack of sleep medication use (aOR: 0.45, 95% CI: 0.24-0.84). CONCLUSION: In African American long-term breast cancer survivors, a higher spirituality score increased the likelihood of greater PA and high sleep duration. These results indicate that interventions surrounding spirituality may benefit the QOL of African American breast cancer survivors.

Patterns of Physical Activity and the Role of Obesity and Comorbidities Among Long-term African American Breast Cancer Survivors.

PURPOSE: Physical activity (PA) has many health benefits for cancer survivors, but little research has examined patterns and correlates in African American women, who have a higher burden of comorbidities and obesity. We examined PA types and patterns overall and by obesity and comorbidities among long-term (> 5 years) breast cancer survivors. METHODS: This cross-sectional study included 323 women who were previous participants of a case-only study in three southeastern states. Women completed a survivorship-focused questionnaire using validated measures to collect data on cancer treatment, PA (recreational, household, transportation) and other lifestyle factors, and comorbidities. Logistic regression models estimated adjusted ORs and 95% CIs for total PA (all three types, categorized as tertiles) and meeting PA guidelines (> 150 min/week of exercise). RESULTS: The mean age of women was 59.1 years (range 27.9-79.5). The most frequent PA types (≥ 1/month) included routine household cleaning (92.9%), shopping (94.7%), walking slowly (42.1%), and walking briskly (40.6%). Less than 40% met PA guidelines. Women with more total comorbidities, arthritis, and obesity had lower levels of total PA (minutes/week) and/or recreational PA. In adjusted models, BMI ≥ 35 kg/m2 was associated with reduced odds of total PA (OR = 0.33, 95% CI 0.12-0.88, highest tertile). Arthritis was associated with reduced odds of meeting PA guidelines (OR = 0.61, 95% CI 36-1.05). CONCLUSIONS: Close to 60% of African American breast cancer survivors did not meet PA guidelines based on recreational PA participation. Household PA was an important source of PA. Comorbidities and obesity were associated with both reduced total PA and not meeting PA guidelines.

Physical activity in association with mortality among Black women diagnosed with breast cancer in the Southern Community Cohort Study.

PURPOSE: Physical activity (PA) is associated with many health benefits. While PA has been associated with reduced mortality after breast cancer diagnosis in many studies, few studies have examined the role of PA in breast cancer survival among underserved and minority populations, including Black women. We investigated PA in association with mortality among Black predominantly low-income breast cancer survivors in the Southern Community Cohort Study (SCCS). METHODS: Study participants were women diagnosed with incident breast cancer (n = 949) in the SCCS, which is a prospective cohort study of predominantly low-income adults aged 40-79 years recruited from 12 Southeastern states between 2002 and 2009. Participants completed a detailed baseline questionnaire, with annual follow-up for mortality via registry linkages. Cox regression models were used to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for associations of pre-diagnosis PA (measured via a validated questionnaire) with all-cause and breast cancer-specific mortality. RESULTS: Breast cancer survivors had a mean age of 61.1 years and most (79.3%) had a household income of < $25,000. In adjusted models, higher levels of total PA (MET-hours/day) were inversely associated with all-cause mortality with HRs (95% CIs): 0.79 (0.59-1.06), 0.66 (0.49-0.90), and 0.60 (0.43-0.84), for Q2, Q3, and Q4 (reference: Q1), respectively, ptrend ≤ 0.01. A similar inverse association was found for breast cancer-specific mortality. CONCLUSION: Higher levels of pre-diagnosis PA were associated with improved survival among low-income Black breast cancer survivors. Resources to reduce barriers to PA participation and increase support for education and intervention efforts to promote PA among Black women are needed.

A population-based descriptive study of neonatal abstinence syndrome using hospital discharge and birth certificate data.

BACKGROUND: Neonatal abstinence syndrome (NAS), largely a consequence of prenatal opioid exposure, results in substantial morbidity. Population-based studies of NAS going beyond Medicaid populations and hospital discharge data (HDD) alone are limited. Using statewide Tennessee (TN) HDD and birth certificate (BC) data, we examined trends and evaluated maternal and infant factors associated with NAS. METHODS: We conducted a population-based descriptive study during 2013-2017 in TN. NAS infants were identified with International Classification of Diseases (ICD)-9-Clinical Modification (CM) and ICD-10-CM codes in HDD and linked to BC data using iterative deterministic matching algorithms. Descriptive analyses were conducted for infant and maternal factors (exposures) by NAS (outcome). Multivariable logistic regression models were used to estimate adjusted ORs and 95% CIs. RESULTS: NAS incidence increased from 13.4 to 15.4 per 1,000 live births between 2013-2017 (15% increase; ptrend<0.001), but remained stable in 2017. In adjusted models, maternal factors associated with reduced odds of NAS included breastfeeding (OR:0.55, 95%CI:0.52-0.59) and prenatal care (OR:0.36, 95%CI:0.32-0.41). Smoking, preterm birth and lower birthweight were associated with increased odds of NAS. CONCLUSIONS: This study highlights the value of utilizing surveillance data to monitor trends and correlates of NAS to inform prevention efforts and targeting of public health resources.

Female fertility treatment and adverse birth outcomes: a multistate analysis of pregnancy risk assessment monitoring system data.

OBJECTIVE: The popularity of fertility treatments has continued to rise, however, the potential health risks of these treatments for both mother and infant are not fully known. Our objective was to determine the association between fertility treatments and adverse birth outcomes of intended pregnancies using the Pregnancy Risk Assessment Monitoring System (PRAMS) data. METHODS: Data from 27,018 intended pregnancies, collected from 2009 to 2018 in the United States, were included in our analysis. PRAMS data consisted of questionnaire and birth certificate data. SAS 9.4 was used for analyses accounting for complex survey weights. All analyses were conducted separately for singleton and twin births. Weighted percentages with 95% confidence intervals (CIs) were estimated for maternal characteristics and birth outcomes. Multivariable logistic regression was used to determine adjusted odds ratios (OR) and 95% CIs for associations of fertility treatment use and adverse birth outcomes. RESULTS: Close to 12% of women reported the use of any fertility treatment. Among those using fertility treatments, the most common type was assisted reproductive technology (ART) for both twin (68.7%, 95% CI: 62.3, 75.2) and singleton births (45.1%, 95% CI: 42.0, 48.1). Use of any type of fertility treatment for singleton births was associated with increased odds of a cesarean delivery (OR: 1.31, 95% CI: 1.16, 1.47), preterm birth (OR: 1.42, 95% CI: 1.20, 1.67), a small-for-gestational age infant (OR: 1.20, 95% CI: 1.00, 1.44), and an infant hospital stay >5 days (OR: 1.34, 95% CI: 1.11, 1.62). Use of fertility treatment for twin births was associated with cesarean delivery only. In analyses examining associations for specific types of treatment (medication alone, ART, insemination) with birth outcomes, results varied by treatment type. CONCLUSIONS: In this large population-based sample of women who intended to become pregnant and had a live birth, fertility treatment was associated with adverse birth outcomes. Patients seeking fertility treatment should be appropriately counseled on the risks of adverse maternal and infant birth outcomes overall and by treatment type. Maternal support and resources to prevent adverse birth outcomes among women using fertility treatments are warranted.

Trends, patterns, and maternal characteristics of opioid prescribing during pregnancy in a large population-based cohort study.

BACKGROUND: Opioid use during pregnancy has been associated with adverse maternal and infant health outcomes. Prescription drug monitoring programs (PDMP) provide a population-based source of prescription data. We linked statewide PDMP and birth certificate data in Tennessee (TN) to determine patterns of prescription opioid and benzodiazepine use during pregnancy. METHODS: We constructed a cohort of 311,217 live singleton births from 2013 to 2016 with prescription history from 90 days before pregnancy to birth. Descriptive statistics were used to describe opioid prescription patterns during pregnancy overall, by maternal characteristics and by year. Multivariable logistic regression models estimated adjusted odds ratios and 95% confidence intervals for factors associated with prescription use. RESULTS: The prevalence of prescription use during pregnancy was 14.1% for opioid analgesics, 1.6% buprenorphine for medication-assisted treatment, and 2.6% for benzodiazepines. The prevalence of opioid analgesic use decreased from 16.6% (2013) to 11.8% (2016) (ptrend< 0.001). About 25% used for > 7 and 9.7% for > 30 days' supply. The most common types were hydrocodone (9.3%), codeine (3.4%), and oxycodone (2.9%). In adjusted models, lower education, lower income, pre-pregnancy obesity and smoking during pregnancy were associated with increased odds of any opioid and opioid analgesic use. CONCLUSION(S): Despite the encouraging trend of decreasing use of prescription opioid analgesics, the overall prevalence remained close to 12% with many women using for long durations. Use was associated with lower socioeconomic status, obesity, and prenatal smoking. Findings highlight the need for maternal education and resources, and provider support for implementation of evidence-based care.

Prescription Opioid Characteristics and Nonfatal Overdose Among Patients Discharged from Tennessee Emergency Departments.

BACKGROUND: Despite increasing trends of nonfatal opioid overdoses in emergency departments (EDs), population-based studies comparing prescription opioid dosing patterns before and after nonfatal opioid overdoses are limited. OBJECTIVES: To evaluate characteristics of prescribing behaviors before and after nonfatal overdoses, with a focus on opioid dosage. METHODS: Included were 5,395 adult residents of Tennessee discharged from hospital EDs after a first nonfatal opioid overdose (2016-2017). Patients were linked to eligible prescription records in the Tennessee Controlled Substance Monitoring Database. We estimated odds ratios (OR) and 95% confidence intervals (CI) to evaluate characteristics associated with filling opioid prescriptions 90 days before overdose and with high daily dose (≥ 90 morphine milligram equivalents) 90 days after overdose. RESULTS: Among patients who filled a prescription both before and after an overdose, the percentage filling a low, medium, and high dose was 33.7%, 31.9%, and 34.4%, respectively, after an opioid overdose (n = 1,516). Most high-dose users before an overdose (>70%) remained high-dose users with the same prescriber after the overdose. Male gender, ages ≥ 35 years, and medium metro residence were associated with increased odds of high-dose filling after an opioid overdose. Patients filling overlapping opioid-benzodiazepine prescriptions and with > 7 days' supply had increased odds of filling high dose after an opioid overdose (OR 1.4, 95% CI 1.08-1.70 and OR 3.7, 95% CI 2.28-5.84, respectively). CONCLUSIONS: In Tennessee, many patients treated in the ED for an overdose are still prescribed high-dose opioid analgesics after an overdose, highlighting a missed opportunity for intervention and coordination of care between ED and non-ED providers.

Characteristics of fatal opioid overdoses with stimulant involvement in Tennessee: A descriptive study using 2018 State Unintentional Drug Overdose Reporting System Data.

PURPOSE: Opioid overdose deaths involving stimulants are on the rise. Demographic characteristics for these deaths to be used in prevention efforts have not been established. METHODS: We conducted a statewide retrospective study to evaluate the characteristics of fatal opioid overdoses with stimulant involvement using 2018 Tennessee State Unintentional Drug Overdose Reporting System data. Data sources included death certificates, autopsy reports, toxicology, and prescription drug monitoring program data. Frequencies were generated to compare demographics, circumstances, opioid history, death scene information, bystander intervention, and toxicology between fatal opioid overdoses with and without stimulant involvement. RESULTS: A total of 1183 SUDORS opioid overdose deaths occurred in Tennessee in 2018 of which 434 (36.7%) involved a stimulant. Fatal opioid overdoses involving stimulants had higher frequencies of illicit drugs on toxicology specifically marijuana, fentanyl, and heroin compared to fatal opioid overdoses without stimulants. Fatal opioid overdoses involving stimulants had higher frequencies of scene indications of injection drug use compared to fatal opioid overdoses without stimulant involvement. CONCLUSIONS: Fatal overdoses are shifting from mainly opioid to multidrug involvement and over one-third include use of stimulants. This analysis can help public health practitioners understand the circumstances around fatal opioid overdoses involving stimulants to inform tailored prevention strategies.

Prediction models for breast cancer prognosis among Asian women.

BACKGROUND: Robust and reliable prognosis prediction models have not been developed and validated for Asian patients with breast cancer, a rapidly growing yet understudied population in the United States. METHODS: We used longitudinal data from the Shanghai Breast Cancer Survival Study, a population-based prospective cohort study (n = 5042), to develop prediction models for 5- and 10-year disease-free survival (DFS) and overall survival (OS). The initial models considered age at diagnosis, tumor grade, tumor size, number of positive nodes, TNM stage, chemotherapy, tamoxifen therapy, and estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status. We then evaluated whether the addition of modifiable lifestyle factors (physical activity, soy isoflavones intake, and postdiagnostic weight change) improved the models. All final models have been validated internally and externally in the National Cancer Database when applicable. RESULTS: Our final models included age at diagnosis, tumor grade, tumor size, number of positive nodes, TNM stage, chemotherapy, tamoxifen therapy, ER status, PR status, 6-month postdiagnostic weight change, interaction between ER status and tamoxifen therapy, and interaction between age and TNM stage. The internal validation yielded C-statistics of 0.76, 0.74, 0.78, and 0.75 for 5-year DFS, 10-year DFS, 5-year OS, and 10-year OS, respectively. The external validation yielded C-statistics of 5- and 10-year OS both at 0.78 for Chinese ethnicity, 0.79 for East Asian ethnicity, and 0.75 and 0.76 for all ethnic groups combined. CONCLUSION: We developed prediction models for breast cancer prognosis from a large prospective study. Our prognostic models performed very well in women from the United States-particularly in Asian American women-and demonstrated high prediction accuracy and generalizability.

Descriptive exploration of overdose codes in hospital and emergency department discharge data to inform development of drug overdose morbidity surveillance indicator definitions in ICD-10-CM.

BACKGROUND: In October 2015, discharge data coding in the USA shifted to the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), necessitating new indicator definitions for drug overdose morbidity. Amid the drug overdose crisis, characterising discharge records that have ICD-10-CM drug overdose codes can inform the development of standardised drug overdose morbidity indicator definitions for epidemiological surveillance. METHODS: Eight states submitted aggregated data involving hospital and emergency department (ED) discharge records with ICD-10-CM codes starting with T36-T50, for visits occurring from October 2015 to December 2016. Frequencies were calculated for (1) the position within the diagnosis billing fields where the drug overdose code occurred; (2) primary diagnosis code grouped by ICD-10-CM chapter; (3) encounter types; and (4) intents, underdosing and adverse effects. RESULTS: Among all records with a drug overdose code, the primary diagnosis field captured 70.6% of hospitalisations (median=69.5%, range=66.2%-76.8%) and 79.9% of ED visits (median=80.7%; range=69.8%-88.0%) on average across participating states. The most frequent primary diagnosis chapters included injury and mental disorder chapters. Among visits with codes for drug overdose initial encounters, subsequent encounters and sequelae, on average 94.6% of hospitalisation records (median=98.3%; range=68.8%-98.8%) and 95.5% of ED records (median=99.5%; range=79.2%-99.8%), represented initial encounters. Among records with drug overdose of any intent, adverse effect and underdosing codes, adverse effects comprised an average of 74.9% of hospitalisation records (median=76.3%; range=57.6%-81.1%) and 50.8% of ED records (median=48.9%; range=42.3%-66.8%), while unintentional intent comprised an average of 11.1% of hospitalisation records (median=11.0%; range=8.3%-14.5%) and 28.2% of ED records (median=25.6%; range=20.8%-40.7%). CONCLUSION: Results highlight considerations for adapting and standardising drug overdose indicator definitions in ICD-10-CM.

Interrupted time series analysis to evaluate the performance of drug overdose morbidity indicators shows discontinuities across the ICD-9-CM to ICD-10-CM transition.

INTRODUCTION: On 1 October 2015, the USA transitioned from the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) to the International Classification of Diseases, 10th Revision (ICD-10-CM). Considering the major changes to drug overdose coding, we examined how using different approaches to define all-drug overdose and opioid overdose morbidity indicators in ICD-9-CM impacts longitudinal analyses that span the transition, using emergency department (ED) and hospitalisation data from six states' hospital discharge data systems. METHODS: We calculated monthly all-drug and opioid overdose ED visit rates and hospitalisation rates (per 100 000 population) by state, starting in January 2010. We applied three ICD-9-CM indicator definitions that included identical all-drug or opioid-related codes but restricted the number of fields searched to varying degrees. Under ICD-10-CM, all fields were searched for relevant codes. Adjusting for seasonality and autocorrelation, we used interrupted time series models with level and slope change parameters in October 2015 to compare trend continuity when employing different ICD-9-CM definitions. RESULTS: Most states observed consistent or increased capture of all-drug and opioid overdose cases in ICD-10-CM coded hospital discharge data compared with ICD-9-CM. More inclusive ICD-9-CM indicator definitions reduced the magnitude of significant level changes, but the effect of the transition was not eliminated. DISCUSSION: The coding change appears to have introduced systematic differences in measurement of drug overdoses before and after 1 October 2015. When using hospital discharge data for drug overdose surveillance, researchers and decision makers should be aware that trends spanning the transition may not reflect actual changes in drug overdose rates.

Impact of benzodiazepines and polysubstance status on repeat non-fatal drug overdoses.

Research has shown that benzodiazepines and mental health disorders can increase the likelihood of repeat overdose, but researchers have not explored this association in Tennessee (TN). We examined benzodiazepines, polysubstance overdose status with/without benzodiazepines, and mental health comorbidities with repeat overdose using statewide data in TN. This study analyzed TN hospital discharge data on nonfatal overdoses for patients ages 18-64 from 2012 to 2016 for 21,066 patients with an initial inpatient visit and 36,244 patients with an initial outpatient visit. The study assessed each patient at one year after initial overdose to determine likelihood of repeat overdose. We used a Cox proportional hazards model to compute hazard ratios (HRs) and 95% confidence intervals (CIs) to determine the factors associated with repeat nonfatal overdose. Repeat overdose rates, by one year after index overdose, were 12.9% of the sample for inpatients and 13.9% of the sample for outpatients. The visit factors (overdose characteristics and comorbidities determined from the initial visit) that the study found to be independently associated with repeat overdoses among inpatients were polysubstance status (HR: 0.88, 95% CI 0.78-0.99), benzodiazepine/polysubstance interaction (HR: 1.29, 95% CI 1.02-1.64), and presence of any mental health disorder (HR: 1.28, 95% CI: 1.18-1.39). For outpatients, the benzodiazepine/polysubstance interaction (HR: 1.21, 95% CI 1.01-1.44) was significant without adjusting for demographic factors. We found evidence that benzodiazepine/polysubstance status and mental health disorders were associated with repeat overdose for inpatients, and that benzodiazepine/polysubstance status was associated with repeat overdose for outpatients. Findings support the need to include polysubstance status and mental health in overdose prevention efforts.

Using statewide death certificate data to understand trends and characteristics of polydrug overdose deaths in Tennessee, 2013-2017.

PURPOSE: Population-based data on trends and characteristics on polydrug overdoses are critically needed to help understand the changing drug epidemic in the United States, and to identify risk patterns and targets for overdose prevention for prescription and illicit opioid deaths. We conducted a statewide study in Tennessee to evaluate characteristics and trends of polydrug overdose deaths during 2013-2017. METHODS: We identified polydrug overdose deaths using ICD-10 codes and literal cause-of-death text in the death statistical files. We evaluated trends, contributing drugs, and demographic characteristics of overdoses (n = 2567 single-drug and n = 4683 polydrug deaths). Average annual percent change estimates (AAPCs) with associated 95% CIs were estimated using Poisson regression. RESULTS: Polydrug overdoses increased annually, with higher AAPC for polydrug compared with single-drug overdoses (AAPC: 13.6%, 95% CI: 10.6%-16.7% and 5.2%, 95% CI: 2.9%-7.5%, respectively). The highest increases in polydrug overdoses were observed in males (AAPC: 15.4%, non-Hispanic blacks (AAPC: 33.3%), and decedents aged 18-34 years (AAPC: 21.3%). CONCLUSIONS: All drug and opioid polydrug deaths increased during 2013-2017, with the highest increases seen in males, blacks, and younger age groups. Over 80% of illicit opioid overdoses involved more than one drug, highlighting the need to go beyond opioids to prevent overdoses.

Record Linkage Approaches Using Prescription Drug Monitoring Program and Mortality Data for Public Health Analyses and Epidemiologic Studies.

BACKGROUND: The use of Prescription Drug Monitoring Program (PDMP) data has greatly increased in recent years as these data have accumulated as part of the response to the opioid epidemic in the United States. We evaluated the accuracy of record linkage approaches using the Controlled Substance Monitoring Database (Tennessee's [TN] PDMP, 2012-2016) and mortality data on all drug overdose decedents in Tennessee (2013-2016). METHODS: We compared total, missed, and false positive (FP) matches (with manual verification of all FPs) across approaches that included a variety of data cleaning and matching methods (probabilistic/fuzzy vs. deterministic) for patient and death linkages, and prescription history. We evaluated the influence of linkage approaches on key prescription measures used in public health analyses. We evaluated characteristics (e.g., age, education, sex) of missed matches and incorrect matches to consider potential bias. RESULTS: The most accurate probabilistic/fuzzy matching approach identified 4,714 overdose deaths (vs. the deterministic approach, n = 4,572), with a low FP linkage error (<1%) and high correct match proportion (95% vs. 92% and ~90% for probabilistic approaches not using comprehensive data cleaning). Estimation of all prescription measures improved (vs. deterministic approach). For example, frequency (%) of decedents filling an oxycodone prescription in the last 60 days (n = 1,371 [32%] vs. n = 1,443 [33%]). Missed overdose decedents were more likely to be younger, male, nonwhite, and of higher education. CONCLUSION: Implications of study findings include underreporting, prescribing and outcome misclassification, and reduced generalizability to population risk groups, information of importance to epidemiologists and researchers using PDMP data.

Prescribing patterns before and after a non-fatal drug overdose using Tennessee's controlled substance monitoring database linked to hospital discharge data.

We performed a statewide evaluation of prescribing patterns of controlled substances (CS) before and after an overdose, using Tennessee's Hospital Discharge Data System and the Controlled Substance Monitoring Database (CSMD). Adults' first non-fatal overdose discharges either from the emergency department (ED) or inpatient (IP) stay occurring between 2013 and 2016 were linked to prescriptions in the CSMD. The difference in the proportion of patients filling a prescription before versus after an overdose was calculated. Included were 49,398 patients with an overdose and a prescription record; most (60.5%) were treated in the ED. Among any drug type overdose the percentage of patients who filled a CS prescription within a year of experiencing an overdose was as follows: opioid analgesics: 59.1%, benzodiazepines: 37.3%, stimulants: 5.0%, muscle relaxants: 3.4%, concurrent opioid-benzodiazepines: 24.0% with the percent difference from before to after similar in both settings. Among patients treated for an opioid overdose, this represented a decrease in opioid analgesics filled by 9.7% (95%CI: -11.2, -8.3) among those treated in the ED, and by 7.1% (95% CI: -8.3, -5.9) among treated inpatients. Among patients treated for a heroin overdose, 12.2% (95%CI: -15.2, -9.3) fewer of those treated in the ED and 8.8% (95%CI: -15.0, -2.7%) fewer of treated inpatients filled a CS prescription in that year. The most common opioid analgesics included hydrocodone and oxycodone. The number of patients filling buprenorphine for treatment increased in the year after overdoses associated with any drug or opioids but decreased among those treated for a heroin overdose.

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.

Prescription opioid use by injured workers in Tennessee: a descriptive study using linked statewide databases.

PURPOSE: This is the first study in Tennessee to measure opioid use in injured workers and among the first nationally to use a prescription drug monitoring program to do so. We conducted a retrospective cohort study to evaluate the prevalence of opioid use after injury and associated characteristics among workers reporting one injury to Tennessee Workers' Compensation. METHODS: Injured workers identified in Workers' Compensation records 2013-2015 were linked to their prescription history in Tennessee's prescription drug monitoring database. RESULTS: Among 172,256 injured workers, the prevalence of receiving an opioid after injury was 22.8% in 1 week, 29.7% in 1 month, and 33.3% in 6 months. Receiving an opioid was associated with having a fracture (odds ratio, 4.9; 95% confidence interval, 4.64-5.11 vs. other injuries). Hydrocodone short-acting was the most commonly received opioid (69.5% of injured workers), and the mean of each worker's maximum dose was 42.8 morphine milligram equivalents (SD 39.26). Ten percent of injured workers who received opioids also received a benzodiazepine. CONCLUSIONS: Injured workers have a high prevalence of opioid use after injury, but prescribing patterns generally tend to follow Tennessee prescribing guidelines.