Prevalence and Expenses of Outpatient Opioid Prescriptions, With Associated Sociodemographic, Economic, and Work Characteristics.
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SUBMITTER: Asfaw A
PROVIDER: S-EPMC8039912 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND AND OBJECTIVES:Little is known about opioid prescribing for children without severe conditions. We studied the prevalence of and indications for outpatient opioid prescriptions and the incidence of opioid-related adverse events in this population. METHODS:This retrospective cohort study between 1999 and 2014 included Tennessee Medicaid children and adolescents aged 2 to 17 without major chronic diseases, prolonged hospitalization, institutional residence, or evidence of a substance use disorder. We estimated the annual prevalence of outpatient opioid prescriptions and incidence of opioid-related adverse events, defined as an emergency department visit, hospitalization, or death related to an opioid adverse effect. RESULTS:There were 1?362?503 outpatient opioid prescriptions; the annual mean prevalence of opioid prescriptions was 15.0%. The most common opioid indications were dental procedures (31.1% prescriptions), outpatient procedure and/or surgery (25.1%), trauma (18.1%), and infections (16.5%). There were 437 cases of opioid-related adverse events confirmed by medical record review; 88.6% were related to the child's prescription and 71.2% had no recorded evidence of deviation from the prescribed regimen. The cumulative incidence of opioid-related adverse events was 38.3 of 100?000 prescriptions. Adverse events increased with age (incidence rate ratio = 2.22; 95% confidence interval, 1.67-2.96; 12-17 vs 2-5 years of age) and higher opioid doses (incidence rate ratio = 1.86 [1.45-2.39]; upper versus lower dose tertiles). CONCLUSIONS:Children without severe conditions enrolled in Tennessee Medicaid frequently filled outpatient opioid prescriptions for acute, self-limited conditions. One of every 2611 study opioid prescriptions was followed by an opioid-related adverse event (71.2% of which were related to therapeutic use of the prescribed opioid).
| S-EPMC6072590 | biostudies-literature
Project description:Data on all outpatient opioid prescriptions (N = 71,647) to youth below age 21 (N = 42,020) from 2005 to 2016 were extracted from electronic medical records within a university hospital system in New Mexico (NM) as were demographic details and markers of morbidity/mortality. Relative risk was calculated for markers of morbidity/mortality based on sociodemographic characteristics. The sample was primarily male (55.0%), Hispanic/Latinx (50.1%), English-speaking (88.9%), and publicly insured (50.1%). Mean age was 13.54 (SD = 6.50). From 2005 to 2016, overall frequency of opioid prescriptions increased by 86.6% (from 2470 to 4610) with the largest increase (206.2%) observed from 2005 to 2008 (2470-7562). Patients who were older, white, and non-Hispanic were more likely to receive multiple opioid prescriptions. Large relative increases in morbidity and mortality were documented, although base rates remained low. The percentage of individuals within the sample who experienced an overdose increased steadily from 0 in 2005 to 1.09% in 2016. Incidence of mortality increased from 0.12% of the sample to 1.39% in 2016. The proportion of individuals who received a medication for the treatment of opioid dependence increased from 0.06% in 2005 to 0.44% in 2016. Significantly increased risk of adverse outcomes was observed in patients receiving multiple opioid prescriptions, and in patients who were older, of minority race, received their first prescription in an outpatient clinic, and publicly insured or uninsured. Results add to the growing literature concerning opioid prescription rates over time. They also provide important information on potential additive risks of adverse outcomes when pediatric patients receive multiple opioid prescriptions.
| S-EPMC7347211 | biostudies-literature
Project description:ObjectivesThe aim of this study was to investigate the relationship between participants' sociodemographic characteristics and the degree to which they stigmatize people with an opioid addiction.MethodsA randomized, between-subjects case vignette study (n = 2605) was conducted with a nationwide online survey. We investigated how the stigmatization toward a hypothetical individual who misused prescription opioids differed across participants' sociodemographic factors (ie, age, gender, education, race, and income).ResultsOur results showed that study participants who were male, white, low-income, college graduates, and younger rated the hypothetical individual with an opioid addiction with lower stigma. In addition, we showed that participant gender moderated the relationship between information given about initiation of opioid use (received prescription opioids from a doctor vs took prescription opioids from a friend) and opioid stigma perceptions.ConclusionsOur results support previous findings that stigmatizing attitudes towards drug use vary across participant sociodemographic characteristics. The findings from our study provide a better understanding of how stigmatizing attitudes towards prescription opioid use differ across sociodemographic characteristics and can serve to improve negative perceptions of those with an opioid addiction.
| S-EPMC7495887 | biostudies-literature
Project description:BACKGROUND:This paper concerns public health crises today-the problem of opioid prescription access and related abuse. Inspired by Case and Deaton's seminal work on increasing mortality among white Americans with lower education, this paper explores the relationship between opioid prescribing and local economic factors. OBJECTIVE:We examined the association between county-level socioeconomic factors (median household income, unemployment rate, Gini index) and opioid prescribing. SUBJECTS:We used the complete 2014 Medicare enrollment and part D drug prescription data from the Center for Medicare and Medicaid Services to study opioid prescriptions of disabled Medicare beneficiaries without record of cancer treatment, palliative care, or end-of-life care. MEASURES AND RESEARCH DESIGN:We summarized the demographic and geographic variation, and investigated how the local economic environment, measured by county median household income, unemployment rate, Gini index, and urban-rural classification correlated with various measures of individual opioid prescriptions. Measures included number of filled opioid prescriptions, total days' supply, average morphine milligram equivalent (MME)/day, and annual total MME dosage. To assess the robustness of the results, we controlled for individual and other county characteristics, used multiple estimation methods including linear least squares, logistic regression, and Tobit regression. RESULTS AND CONCLUSIONS:Lower county median household income, higher unemployment rates, and less income inequality were consistently associated with more and higher MME opioid prescriptions among disabled Medicare beneficiaries. Geographically, we found that the urban-rural divide was not gradual and that beneficiaries in large central metro counties were less likely to have an opioid prescription than those living in other areas.
| S-EPMC6300050 | biostudies-literature
Project description:While against recommendations, long-term opioid therapy (LTOT) for chronic pain is common. This study aimed to describe the prevalence of opioid prescriptions and to study the association of patient characteristics (demographics, pain characteristics, anxiety, depressive symptoms and pain coping) with future LTOT. The sample included N = 1334 chronic musculoskeletal pain patients, aged 18-65, who were assessed for Interdisciplinary Multimodal Pain Rehabilitation (IMMR) in Swedish specialist rehabilitation. Prescriptions were tracked across a two-year target period after assessment. In total, 9100 opioid prescriptions were prescribed to 55% of the sample (Mmedian = 6, IQR = 14). Prediction of LTOT was analyzed separately for those who did (24%) and did not (76%) receive IMMR. The odds of receiving opioids was similar for these subsamples, after controlling for differences in baseline characteristics. In both samples, there were significant associations between patient characteristics and future opioid prescriptions. Dysfunctional pain coping was a unique predictor of LTOT in those who received IMMR while pain intensity and depressive symptoms were unique predictors in those who did not receive IMMR. The results underscore that opioid treatment is common among patients in chronic pain rehabilitation and relates to pain and psychological factors. Understanding in detail why these factors relate to opioid prescription patterns is an important future study area as it is a prerequisite for better management and fundamental for preventing overuse.
| S-EPMC8155870 | biostudies-literature
Project description:BackgroundTo describe characteristics of patients, providers, and clinics associated with opioid or non-opioid pain medication prescribing patterns for patients who received lower spine imaging in primary care clinics.MethodsIn these secondary analyses of the Lumbar Imaging with Reporting of Epidemiology (LIRE) study, a randomized controlled trial conducted in 4 health systems in the United States, we evaluated characteristics associated with receipt of pain medication prescriptions. The outcomes were receipt of prescriptions for opioid or, separately, non-opioid pain medications within 90 days after imaging. Among patients who received opioid or non-opioid prescriptions, we evaluated receipt of multiple prescriptions in the year following imaging. Mixed models were used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs).ResultsCompared with whites, patients identified as Asian (OR, 0.53; 95% CI, 0.51-0.56), Native Hawaiian/Pacific Islander (OR, 0.73; 95% CI, 0.64-0.83), multiracial (OR, 0.84; 95% CI, 0.71-0.98) or Black (OR, 0.92; 95% CI, 0.89-0.96) had significantly reduced odds for receiving prescriptions for opioids within 90 days. Patients identified as Native American/Alaska Native had greater odds for receiving prescriptions for non-opioid pain medications within 90 days (OR, 1.12; 95% CI, 1.01-1.24). Receipt of pain prescriptions 120 days before imaging was strongly predictive of subsequent receipt of pain prescriptions across all categories.ConclusionsAfter adjusting for factors that could affect prescribing, the strongest differences observed in pain-medication prescribing were across racial categories and for patients with previous pain prescriptions. Further research is needed to understand these differences and to optimize prescribing.
| S-EPMC9746536 | biostudies-literature
Project description:ImportancePatterns of preoperative opioid use are not well characterized across different surgical services, and studies in this patient population have lacked important self-reported data of pain and affect.ObjectivesTo assess the prevalence of preoperative opioid use and the characteristics of these patients in a broadly representative surgical cohort.Design, setting, and participantsCross-sectional, observational study of patients undergoing surgery at a tertiary care academic medical center. Data were collected as a part of large prospective institutional research registries from March 1, 2010, through April 30, 2016.ExposuresPreoperative patient and procedural characteristics, including prospectively assessed self-reported pain and functional measures.Main outcomes and measuresPatient-reported opioid use before surgery.ResultsOf the total 34 186 patients recruited (54.2% women; mean [SD] age, 53.1 [16.1] years), preoperative opioid use was reported in 7894 (23.1%). The most common opioids used were hydrocodone bitartrate (4685 [59.4%]), tramadol hydrochloride (1677 [21.2%]), and oxycodone hydrochloride (1442 [18.3%]). Age of 31 to 40 years (adjusted odds ratio [aOR], 1.26; 95% CI, 1.10-1.45), tobacco use (former use aOR, 1.32 [95% CI, 1.22-1.42]; current use aOR, 1.62 [95% CI, 1.48-1.78]), illicit drug use (aOR, 1.74; 95% CI, 1.16-2.60), higher pain severity (aOR, 1.33; 95% CI, 1.31-1.35), depression (aOR, 1.22; 95% CI, 1.12-1.33), higher Fibromyalgia Survey scores (aOR, 1.06, 95% CI, 1.05-1.07), lower life satisfaction (aOR, 0.95, 95% CI, 0.93-0.96), and more medical comorbidities (American Society of Anesthesiology score aOR, 1.47 [95% CI, 1.37-1.58]; Charlson Comorbidity Index aOR, 1.29 [95% CI, 1.18-1.41]) were all independently associated with preoperative opioid use. Preoperative opioid use was most commonly reported by patients undergoing orthopedic (226 [65.1%]) and neurosurgical spinal (596 [55.1%]) procedures and least common among patients undergoing thoracic procedures (244 [15.7%]). After adjusting for patient characteristics, the patients undergoing lower extremity procedures were most likely to report preoperative opioid use (aOR, 3.61; 95% CI, 2.81-4.64), as well as those undergoing pelvic (excluding hip) (aOR, 3.09; 95% CI, 1.88-5.08), upper extremity (aOR, 3.07; 95% CI, 2.12-4.45), and spinal or spinal cord (aOR, 2.68; 95% CI, 2.15-3.32) procedures, with the group undergoing intrathoracic surgery as the reference group.Conclusions and relevanceIn this large study of preoperative opioid use that includes patient-reported outcome measures, more than 1 in 4 patients presenting for surgery reported opioid use. These data provide important insights into this complicated patient population that would appear to help guide future preoperative optimization and perioperative opioid-weaning interventions.
| S-EPMC6233789 | biostudies-literature
Project description:Objective The increased use of opioids to treat chronic pain in the past 20 years has led to a drastic increase in opioid prescribing in the United States. The Centers for Disease Control and Prevention's (CDC's) Guideline for Prescribing Opioids for Chronic Pain recommends the use of nonopioid therapy as the preferred treatment for chronic pain. This study analyzes the prevalence of nonopioid prescribing among commercially insured patients with chronic pain. Design Data from the 2014 IBM® MarketScan® databases representing claims for commercially insured patients were used. International Classification of Diseases, Ninth Revision, codes were used to identify patients with chronic pain. Nonopioid prescriptions included nonsteroidal anti-inflammatory drugs (NSAIDs), analgesics/antipyretics (e.g., acetaminophen), anticonvulsants, and antidepressant medications. The prevalence of nonopioid and opioid prescriptions was calculated by age, sex, insurance plan type, presence of a depressive or seizure disorder, and region. Results In 2014, among patients with chronic pain, 16% filled only an opioid, 17% filled only a nonopioid prescription, and 28% filled both a nonopioid and an opioid. NSAIDs and antidepressants were the most commonly prescribed nonopioids among patients with chronic pain. Having prescriptions for only nonopioids was more common among patients aged 50-64 years and among female patients. Conclusions This study provides a baseline snapshot of nonopioid prescriptions before the release of the CDC Guideline and can be used to examine the impact of the CDC Guideline and other evidence-based guidelines on nonopioid use among commercially insured patients with chronic pain.
| S-EPMC6536362 | biostudies-literature
Project description:ImportanceCannabis use has increased, but there are few studies on frequent and daily cannabis use among US adults. Individuals who engage in higher frequency use may suffer more health consequences.ObjectiveTo examine frequency of cannabis use and associated factors among US adults.Design, setting, and participantsThis survey study included data from 21 US states and 2 US territories reported in the Behavioral Risk Factor Surveillance System surveys from 2016 to 2019. Cross-sectional data on US adults ages 18 years and older were used to estimate demographic, socioeconomic, and behavioral risk factors for cannabis use, taking into account the survey strata and sampling weights for the 4 years of combined data. Using a multivariable ordinal logistic analysis, the association of demographic, socioeconomic status, and behavioral risk factors with past month cannabis frequency were examined.ExposuresSociodemographic characteristic, ie, age, gender, race and ethnicity, educational attainment, employment status, and annual household income.Main outcomes and measuresOrdinal categorization of number of days of cannabis use in the past 30 days in terms of nonuse, infrequent use (1-5 days), frequent use (6-29 days), and daily use.ResultsAmong the 387 179 respondents, 58 009 (27.9%) were ages 18 to 34 years, 186 923 (50.3%) were ages 35 to 64 years, and 142 225 (21.8%) were age 65 years or older (mean [SD] age, 48.3 [0.1] years). The sample included 28 345 (9.8%) Black, 36 697 (22.6%) Hispanic, and 292 210 (57.3%) White respondents. Smoking was the most common form of cannabis use. The frequency of cannabis use varied significantly by age, gender, race, marital status, education, and employment. Higher frequency cannabis use was associated with younger age (ages 18-34 years: adjusted odds ratio [aOR],4.12; 95% CI, 3.63-4.68; ages 35-64 years: aOR,2.22; 95% CI, 1.98-2.49), Black (aOR, 1.46; 95% CI, 1.33-1.71) and Native American (aOR, 1.25; 95% CI, 1.04-1.52) race, and less educational attainment (high school or less: aOR,1.09; 95% CI, 1.02-1.17; some college: aOR,1.27; 95% CI, 1.19-1.35). Being married (aOR, 0.54; 95% CI, 0.51-0.58) or identifying as Asian (aOR, 0.60; 95% CI, 0.51-0.71) or Hispanic (aOR, 0.71; 95% CI, 0.65-0.77) was associated with lower-frequency cannabis use after accounting for other baseline factors.Conclusions and relevanceThis nationally based study found that higher-frequency cannabis use is more common among young and racial minority populations, as well as respondents with low socioeconomic status. Given the known and emerging negative health effects of cannabis use, more attention may need to be paid to high-frequency use among underserved populations in the form of screening, risk stratification, and treatment.
| S-EPMC8634054 | biostudies-literature
Project description:Purpose To identify the mean morphine milligram equivalent (MME) opioid prescriptions for opioid-naïve patients undergoing isolated anterior cruciate ligament reconstruction (ACLR) between 4 weeks before surgery and the first 90 days after surgery and to describe opioid prescriptions filled per patient and mean MMEs per year within 90 days following ACLR. Methods Exclusion criteria were patients having concurrent other cruciate or collateral ligament repair or reconstruction, meniscus procedures (repair and debridement), any cartilage procedure, lower-extremity osteotomy, or knee procedures for fracture, infection, or neoplasms; patients with substance use disorder or chronic pain also were excluded. Opioid use between 4 weeks before surgery and the first 90 days after surgery was recorded. Prescribing physician specialty also was tracked. The correlation of patient factors and prescriber specialty of MME were compared using the Student’s t-test. Significance was defined at P < .05. Results Opioid-naïve patients undergoing isolated ACLR were included. Isolated arthroscopic ACLRs performed between 2010 and Q3 2020 in opioid-naïve patients were identified within the PearlDiver M91 national database. A total of 37,200 patients were identified. Mean MME per patient was 340.9 ± 198.2, with an average MME per day of 59.9. Factors associated with increased opioid use during the 90 days following ACLR were older age (P < .001) and preoperative diagnosis of depression (P < .001). Orthopaedic surgeons were primarily responsible for the number of opioid prescriptions after ACLR (n = 29,326, 73.0%) but 27% (n = 10,797) of prescriptions came from nonorthopaedic surgeon medical providers who prescribed significantly greater MMEs of opioids than orthopaedic surgeons (456.5 vs 339.2, P < .001) per patient. Lastly, decreasing yearly opioid prescriptions per patient (2.4 to 1.6 prescriptions) and the mean MME per patient (428.4 to 257.1) occurred from 2010 to 2020. Conclusions Older age and preoperative diagnosis of depression are associated with greater opioid doses after ACLR. In addition, the vast majority of opioid prescriptions are written by orthopaedic surgeons on the day of ACLR and decreased considerably by four weeks after surgery. Patients receiving opioid prescriptions by nonorthopaedic surgeon medical providers receive significantly greater doses. Level of Evidence Level IV, retrospective cohort study.
| S-EPMC10461142 | biostudies-literature