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1.
JAMA ; 2024 Jun 13.
Article in English | MEDLINE | ID: mdl-38869869

ABSTRACT

This cross-sectional study examines trends in naloxone dispensing by US retail pharmacies from 2019 to 2023, including prescriber specialty and product brand.

3.
JMIR Form Res ; 8: e44726, 2024 Feb 23.
Article in English | MEDLINE | ID: mdl-38393772

ABSTRACT

BACKGROUND: Health misinformation and myths about treatment for opioid use disorder (OUD) are present on social media and contribute to challenges in preventing drug overdose deaths. However, no systematic, quantitative methodology exists to identify what types of misinformation are being shared and discussed. OBJECTIVE: We developed a multistage analytic pipeline to assess social media posts from Twitter (subsequently rebranded as X), YouTube, Reddit, and Drugs-Forum for the presence of health misinformation about treatment for OUD. METHODS: Our approach first used document embeddings to identify potential new statements of misinformation from known myths. These statements were grouped into themes using hierarchical agglomerative clustering, and public health experts then reviewed the results for misinformation. RESULTS: We collected a total of 19,953,599 posts discussing opioid-related content across the aforementioned platforms. Our multistage analytic pipeline identified 7 main clusters or discussion themes. Among a high-yield data set of posts (n=303) for further public health expert review, these included discussion about potential treatments for OUD (90/303, 29.8%), the nature of addiction (68/303, 22.5%), pharmacologic properties of substances (52/303, 16.9%), injection drug use (36/303, 11.9%), pain and opioids (28/303, 9.3%), physical dependence of medications (22/303, 7.2%), and tramadol use (7/303, 2.3%). A public health expert review of the content within each cluster identified the presence of misinformation and myths beyond those used as seed myths to initialize the algorithm. CONCLUSIONS: Identifying and addressing misinformation through appropriate communication strategies could be an increasingly important component of preventing overdose deaths. To further this goal, we developed and tested an approach to aid in the identification of myths and misinformation about OUD from large-scale social media content.

5.
J Clin Med ; 12(10)2023 May 17.
Article in English | MEDLINE | ID: mdl-37240621

ABSTRACT

Primary immunodeficiencies (PIs) are a group of diseases that increase susceptibility to infectious diseases. Few studies have examined the relationship between PI and COVID-19 outcomes. In this study, we used Premier Healthcare Database, which contains information on inpatient discharges, to analyze COVID-19 outcomes among 853 adult PI and 1,197,430 non-PI patients who visited the emergency department. Hospitalization, intensive care unit (ICU) admission, invasive mechanical ventilation (IMV), and death had higher odds in PI patients than in non-PI patients (hospitalization aOR: 2.36, 95% CI: 1.87-2.98; ICU admission aOR: 1.53, 95% CI: 1.19-1.96; IMV aOR: 1.41, 95% CI: 1.15-1.72; death aOR: 1.37, 95% CI: 1.08-1.74), and PI patients spent on average 1.91 more days in the hospital than non-PI patients when adjusted for age, sex, race/ethnicity, and chronic conditions associated with severe COVID-19. Of the largest four PI groups, selective deficiency of the immunoglobulin G subclass had the highest hospitalization frequency (75.2%). This large study of United States PI patients provides real-world evidence that PI is a risk factor for adverse COVID-19 outcomes.

6.
JAMA Psychiatry ; 80(4): 331-341, 2023 04 01.
Article in English | MEDLINE | ID: mdl-36790774

ABSTRACT

Importance: During the COVID-19 pandemic, US emergency department (ED) visits for psychiatric disorders (PDs) and drug overdoses increased. Psychiatric disorders and substance use disorders (SUDs) independently increased the risk of COVID-19 hospitalization, yet their effect together is unknown. Objective: To assess how comorbid PD and SUD are associated with the probability of hospitalization among ED patients with COVID-19. Design, Setting, and Participants: This retrospective cross-sectional study analyzed discharge data for adults (age ≥18 years) with a COVID-19 diagnosis treated in 970 EDs and inpatient hospitals in the United States from April 2020 to August 2021. Exposures: Any past diagnosis of (1) SUD from opioids, stimulants, alcohol, cannabis, cocaine, sedatives, or other substances and/or (2) PD, including attention-deficit/hyperactivity disorder (ADHD), anxiety, bipolar disorder, major depression, other mood disorder, posttraumatic stress disorder (PTSD), or schizophrenia. Main Outcomes and Measures: The main outcome was any hospitalization. Differences in probability of hospitalization were calculated to assess its association with both PD and SUD compared with PD alone, SUD alone, or neither condition. Results: Of 1 274 219 ED patients with COVID-19 (mean [SD] age, 54.6 [19.1] years; 667 638 women [52.4%]), 18.6% had a PD (mean age, 59.0 years; 37.7% men), 4.6% had a SUD (mean age, 50.1 years; 61.7% men), and 2.3% had both (mean age, 50.4 years; 53.1% men). The most common PDs were anxiety (12.9%), major depression (9.8%), poly (≥2) PDs (6.4%), and schizophrenia (1.4%). The most common SUDs involved alcohol (2.1%), cannabis (1.3%), opioids (1.0%), and poly (≥2) SUDs (0.9%). Prevalence of SUD among patients with PTSD, schizophrenia, other mood disorder, or ADHD each exceeded 21%. Based on significant specific PD-SUD pairs (Q < .05), probability of hospitalization of those with both PD and SUD was higher than those with (1) neither condition by a weighted mean of 20 percentage points (range, 6 to 36; IQR, 16 to 25); (2) PD alone by 12 percentage points (range, -4 to 31; IQR, 8 to 16); and (3) SUD alone by 4 percentage points (range, -7 to 15; IQR, -2 to 7). Associations varied by types of PD and SUD. Substance use disorder was a stronger predictor of hospitalization than PD. Conclusions and Relevance: This study found that patients with both PD and SUD had a greater probability of hospitalization, compared with those with either disorder alone or neither disorder. Substance use disorders appear to have a greater association than PDs with the probability of hospitalization. Overlooking possible coexisting PD and SUD in ED patients with COVID-19 can underestimate the likelihood of hospitalization. Screening and assessment of both conditions are needed.


Subject(s)
COVID-19 , Depressive Disorder, Major , Substance-Related Disorders , Male , Humans , Adult , Female , Middle Aged , Adolescent , Analgesics, Opioid , Retrospective Studies , Cross-Sectional Studies , COVID-19 Testing , Pandemics , COVID-19/epidemiology , Substance-Related Disorders/epidemiology , Comorbidity , Depressive Disorder, Major/epidemiology , Hospitalization , Emergency Service, Hospital
7.
Drug Alcohol Depend ; 232: 109192, 2022 03 01.
Article in English | MEDLINE | ID: mdl-35065513

ABSTRACT

BACKGROUND: COVID-19 stay-at-home orders may reduce access to substance use treatment and naloxone, an opioid overdose reversal drug. The objective of this analysis was to compare monthly trends in pharmacy-based dispensing rates of medications for opioid use disorder (MOUD) (buprenorphine and extended-release [ER] naltrexone) and naloxone in the United States during March 2019-December 2020 by age and sex. METHODS: We calculated monthly prescription dispensing rates per 100,000 persons using IQVIA New to Brand. We used Joinpoint regression to calculate monthly percent change in dispensing rates and Wilcoxon Rank Sum tests to examine differences in median monthly rates overall, and by age and sex between March 2019-December 2019 and March 2020-December 2020. RESULTS: Buprenorphine dispensing increased among those aged 40-64 years and ≥ 65 years from March 2019 to December 2020. Median rates of total ER naltrexone dispensing were lower in March 2020-December 2020 compared to March 2019-December 2019 for the total population, and for females and males. From March 2019 to December 2020, ER naltrexone dispensing decreased and naloxone dispensing increased for those aged 20-39 years. CONCLUSIONS: Dispensing ER naltrexone declined during the study period. Given the increase in substance use during the COVID-19 pandemic, maintaining equivalent access to MOUD may not be adequate to accommodate rising numbers of new patients with opioid use disorder. Access to all MOUD and naloxone could be further expanded to meet potential needs during and after the public health emergency, given their importance in preventing opioid overdose-related harms.


Subject(s)
Buprenorphine , COVID-19 , Opioid-Related Disorders , Pharmacy , Adult , Analgesics, Opioid/therapeutic use , Buprenorphine/therapeutic use , Female , Humans , Male , Middle Aged , Naloxone/therapeutic use , Naltrexone/therapeutic use , Narcotic Antagonists/therapeutic use , Opioid-Related Disorders/drug therapy , Opioid-Related Disorders/epidemiology , Pandemics , SARS-CoV-2 , United States/epidemiology , Young Adult
8.
Drug Alcohol Depend ; 232: 109297, 2022 Mar 01.
Article in English | MEDLINE | ID: mdl-35033956

ABSTRACT

INTRODUCTION: Sociodemographic factors and chronic conditions associated with coronavirus disease 2019 (COVID-19) among persons with substance use disorder (PWSUD) are not well understood. We identified risk factors associated with COVID-19 among PWSUD with hospital visits. METHODS: Using the Premier Healthcare Database Special COVID-19 Release, we conducted a case-control study using ICD-10-CM codes to identify PWSUD aged 12 years and older with hospital visits for any reason during April-December 2020. Multivariable logistic regression was used to calculate adjusted odds ratios (aOR) and 95% confidence intervals (CI) to identify factors associated with COVID-19 diagnosis among PWSUD (age, sex, race/ethnicity, U.S. Census Region, urban/rural classification, insurance payor type, comorbidities, and substance use disorder [SUD] type), and then stratified by SUD type. RESULTS: From April-December 2020, 18,298 (1.3%) of 1,429,154 persons with SUD in the database had a COVID-19 diagnosis. Among PWSUD, opioid use disorder (OUD; aOR = 1.24, 95% CI = 1.18-1.32), alcohol use disorder (AUD; aOR = 1.16, 95% CI = 1.11-1.22), cocaine or other stimulant use disorder (COUD; aOR = 1.28, 95% CI = 1.22-1.34), and multiple SUDs (aOR = 1.20, 95% CI = 1.15-1.26) were associated with higher odds of COVID-19, as were comorbidities such as chronic lower respiratory disease (aOR = 1.32, 95% CI = 1.26-1.37), chronic hepatitis (aOR = 1.45, 95% CI = 1.34-1.57), and diabetes (aOR = 1.78, 95% CI = 1.71-1.86). CONCLUSIONS: Among a sample of PWSUD, OUD, AUD, COUD, multiple SUDs, and associated comorbidities were associated with COVID-19 diagnosis. Integration of COVID-related care, care of other comorbidities, and SUD treatment may benefit PWSUD. Future studies are needed to better understand COVID-19 prevention in this population and to reduce disparities among subpopulations at increased risk.


Subject(s)
COVID-19 , Opioid-Related Disorders , Substance-Related Disorders , COVID-19/epidemiology , COVID-19 Testing , Case-Control Studies , Child , Hospitals , Humans , Opioid-Related Disorders/epidemiology , Risk Factors , SARS-CoV-2 , Substance-Related Disorders/epidemiology , United States/epidemiology
9.
JAMA Netw Open ; 5(1): e2143407, 2022 01 04.
Article in English | MEDLINE | ID: mdl-35024835

ABSTRACT

Importance: People experiencing incarceration (PEI) and people experiencing homelessness (PEH) have an increased risk of COVID-19 exposure from congregate living, but data on their hospitalization course compared with that of the general population are limited. Objective: To compare COVID-19 hospitalizations for PEI and PEH with hospitalizations among the general population. Design, Setting, and Participants: This cross-sectional analysis used data from the Premier Healthcare Database on 3415 PEI and 9434 PEH who were evaluated in the emergency department or were hospitalized in more than 800 US hospitals for COVID-19 from April 1, 2020, to June 30, 2021. Exposures: Incarceration or homelessness. Main Outcomes and Measures: Hospitalization proportions were calculated. and outcomes (intensive care unit admission, invasive mechanical ventilation [IMV], mortality, length of stay, and readmissions) among PEI and PEH were compared with outcomes for all patients with COVID-19 (not PEI or PEH). Multivariable regression was used to adjust for potential confounders. Results: In total, 3415 PEI (2952 men [86.4%]; mean [SD] age, 50.8 [15.7] years) and 9434 PEH (6776 men [71.8%]; mean [SD] age, 50.1 [14.5] years) were evaluated in the emergency department for COVID-19 and were hospitalized more often (2170 of 3415 [63.5%] PEI; 6088 of 9434 [64.5%] PEH) than the general population (624 470 of 1 257 250 [49.7%]) (P < .001). Both PEI and PEH hospitalized for COVID-19 were more likely to be younger, male, and non-Hispanic Black than the general population. Hospitalized PEI had a higher frequency of IMV (410 [18.9%]; adjusted risk ratio [aRR], 1.16; 95% CI, 1.04-1.30) and mortality (308 [14.2%]; aRR, 1.28; 95% CI, 1.11-1.47) than the general population (IMV, 88 897 [14.2%]; mortality, 84 725 [13.6%]). Hospitalized PEH had a lower frequency of IMV (606 [10.0%]; aRR, 0.64; 95% CI, 0.58-0.70) and mortality (330 [5.4%]; aRR, 0.53; 95% CI, 0.47-0.59) than the general population. Both PEI and PEH had longer mean (SD) lengths of stay (PEI, 9 [10] days; PEH, 11 [26] days) and a higher frequency of readmission (PEI, 128 [5.9%]; PEH, 519 [8.5%]) than the general population (mean [SD] length of stay, 8 [10] days; readmission, 28 493 [4.6%]). Conclusions and Relevance: In this cross-sectional study, a higher frequency of COVID-19 hospitalizations for PEI and PEH underscored the importance of adhering to recommended prevention measures. Expanding medical respite may reduce hospitalizations in these disproportionately affected populations.


Subject(s)
COVID-19/epidemiology , Hospitalization/statistics & numerical data , Ill-Housed Persons/statistics & numerical data , Prisoners/statistics & numerical data , Adult , Aged , Cross-Sectional Studies , Databases, Factual , Female , Humans , Male , Middle Aged , SARS-CoV-2 , United States
10.
Prev Chronic Dis ; 18: E66, 2021 07 01.
Article in English | MEDLINE | ID: mdl-34197283

ABSTRACT

INTRODUCTION: Severe COVID-19 illness in adults has been linked to underlying medical conditions. This study identified frequent underlying conditions and their attributable risk of severe COVID-19 illness. METHODS: We used data from more than 800 US hospitals in the Premier Healthcare Database Special COVID-19 Release (PHD-SR) to describe hospitalized patients aged 18 years or older with COVID-19 from March 2020 through March 2021. We used multivariable generalized linear models to estimate adjusted risk of intensive care unit admission, invasive mechanical ventilation, and death associated with frequent conditions and total number of conditions. RESULTS: Among 4,899,447 hospitalized adults in PHD-SR, 540,667 (11.0%) were patients with COVID-19, of whom 94.9% had at least 1 underlying medical condition. Essential hypertension (50.4%), disorders of lipid metabolism (49.4%), and obesity (33.0%) were the most common. The strongest risk factors for death were obesity (adjusted risk ratio [aRR] = 1.30; 95% CI, 1.27-1.33), anxiety and fear-related disorders (aRR = 1.28; 95% CI, 1.25-1.31), and diabetes with complication (aRR = 1.26; 95% CI, 1.24-1.28), as well as the total number of conditions, with aRRs of death ranging from 1.53 (95% CI, 1.41-1.67) for patients with 1 condition to 3.82 (95% CI, 3.45-4.23) for patients with more than 10 conditions (compared with patients with no conditions). CONCLUSION: Certain underlying conditions and the number of conditions were associated with severe COVID-19 illness. Hypertension and disorders of lipid metabolism were the most frequent, whereas obesity, diabetes with complication, and anxiety disorders were the strongest risk factors for severe COVID-19 illness. Careful evaluation and management of underlying conditions among patients with COVID-19 can help stratify risk for severe illness.


Subject(s)
COVID-19 , Diabetes Complications , Hospitalization/statistics & numerical data , Multimorbidity , Noncommunicable Diseases/epidemiology , Obesity , Phobic Disorders , Age Factors , Aged , COVID-19/mortality , COVID-19/therapy , Comorbidity , Diabetes Complications/diagnosis , Diabetes Complications/epidemiology , Female , Humans , Male , Mortality , Obesity/diagnosis , Obesity/epidemiology , Phobic Disorders/diagnosis , Phobic Disorders/epidemiology , Risk Assessment/methods , Risk Assessment/statistics & numerical data , Risk Factors , SARS-CoV-2 , Severity of Illness Index , United States/epidemiology
11.
JAMA Netw Open ; 4(6): e2111182, 2021 06 01.
Article in English | MEDLINE | ID: mdl-34097050

ABSTRACT

Importance: Information on underlying conditions and severe COVID-19 illness among children is limited. Objective: To examine the risk of severe COVID-19 illness among children associated with underlying medical conditions and medical complexity. Design, Setting, and Participants: This cross-sectional study included patients aged 18 years and younger with International Statistical Classification of Diseases, Tenth Revision, Clinical Modification code U07.1 (COVID-19) or B97.29 (other coronavirus) during an emergency department or inpatient encounter from March 2020 through January 2021. Data were collected from the Premier Healthcare Database Special COVID-19 Release, which included data from more than 800 US hospitals. Multivariable generalized linear models, controlling for patient and hospital characteristics, were used to estimate adjusted risk of severe COVID-19 illness associated with underlying medical conditions and medical complexity. Exposures: Underlying medical conditions and medical complexity (ie, presence of complex or noncomplex chronic disease). Main Outcomes and Measures: Hospitalization and severe illness when hospitalized (ie, combined outcome of intensive care unit admission, invasive mechanical ventilation, or death). Results: Among 43 465 patients with COVID-19 aged 18 years or younger, the median (interquartile range) age was 12 (4-16) years, 22 943 (52.8%) were female patients, and 12 491 (28.7%) had underlying medical conditions. The most common diagnosed conditions were asthma (4416 [10.2%]), neurodevelopmental disorders (1690 [3.9%]), anxiety and fear-related disorders (1374 [3.2%]), depressive disorders (1209 [2.8%]), and obesity (1071 [2.5%]). The strongest risk factors for hospitalization were type 1 diabetes (adjusted risk ratio [aRR], 4.60; 95% CI, 3.91-5.42) and obesity (aRR, 3.07; 95% CI, 2.66-3.54), and the strongest risk factors for severe COVID-19 illness were type 1 diabetes (aRR, 2.38; 95% CI, 2.06-2.76) and cardiac and circulatory congenital anomalies (aRR, 1.72; 95% CI, 1.48-1.99). Prematurity was a risk factor for severe COVID-19 illness among children younger than 2 years (aRR, 1.83; 95% CI, 1.47-2.29). Chronic and complex chronic disease were risk factors for hospitalization, with aRRs of 2.91 (95% CI, 2.63-3.23) and 7.86 (95% CI, 6.91-8.95), respectively, as well as for severe COVID-19 illness, with aRRs of 1.95 (95% CI, 1.69-2.26) and 2.86 (95% CI, 2.47-3.32), respectively. Conclusions and Relevance: This cross-sectional study found a higher risk of severe COVID-19 illness among children with medical complexity and certain underlying conditions, such as type 1 diabetes, cardiac and circulatory congenital anomalies, and obesity. Health care practitioners could consider the potential need for close observation and cautious clinical management of children with these conditions and COVID-19.


Subject(s)
Adolescent Health , COVID-19/epidemiology , Cardiovascular Abnormalities/epidemiology , Child Health , Diabetes Mellitus, Type 1/epidemiology , Obesity/epidemiology , Severity of Illness Index , Adolescent , COVID-19/mortality , Child , Child, Preschool , Chronic Disease , Comorbidity , Cross-Sectional Studies , Emergency Service, Hospital , Female , Hospitalization , Humans , Infant , Intensive Care Units , Male , Pandemics , Premature Birth , Respiration, Artificial , SARS-CoV-2 , United States/epidemiology
12.
Open Forum Infect Dis ; 8(2): ofaa638, 2021 Feb.
Article in English | MEDLINE | ID: mdl-33553477

ABSTRACT

BACKGROUND: Older adults and people from certain racial and ethnic groups are disproportionately represented in coronavirus disease 2019 (COVID-19) hospitalizations and deaths. METHODS: Using data from the Premier Healthcare Database on 181 813 hospitalized adults diagnosed with COVID-19 during March-September 2020, we applied multivariable log-binomial regression to assess the associations between age and race/ethnicity and COVID-19 clinical severity (intensive care unit [ICU] admission, invasive mechanical ventilation [IMV], and death) and to determine whether the impact of age on clinical severity differs by race/ethnicity. RESULTS: Overall, 84 497 (47%) patients were admitted to the ICU, 29 078 (16%) received IMV, and 27 864 (15%) died in the hospital. Increased age was strongly associated with clinical severity when controlling for underlying medical conditions and other covariates; the strength of this association differed by race/ethnicity. Compared with non-Hispanic White patients, risk of death was lower among non-Hispanic Black patients (adjusted risk ratio, 0.96; 95% CI, 0.92-0.99) and higher among Hispanic/Latino patients (risk ratio [RR], 1.15; 95% CI, 1.09-1.20), non-Hispanic Asian patients (RR, 1.16; 95% CI, 1.09-1.23), and patients of other racial and ethnic groups (RR, 1.13; 95% CI, 1.06-1.21). Risk of ICU admission and risk of IMV were elevated among some racial and ethnic groups. CONCLUSIONS: These results indicate that age is a driver of poor outcomes among hospitalized persons with COVID-19. Additionally, clinical severity may be elevated among patients of some racial and ethnic minority groups. Public health strategies to reduce severe acute respiratory syndrome coronavirus 2 infection rates among older adults and racial and ethnic minorities are essential to reduce poor outcomes.

13.
MMWR Morb Mortal Wkly Rep ; 69(35): 1210-1215, 2020 Sep 04.
Article in English | MEDLINE | ID: mdl-32881845

ABSTRACT

Hydroxychloroquine and chloroquine, primarily used to treat autoimmune diseases and to prevent and treat malaria, received national attention in early March 2020, as potential treatment and prophylaxis for coronavirus disease 2019 (COVID-19) (1). On March 20, the Food and Drug Administration (FDA) issued an emergency use authorization (EUA) for chloroquine phosphate and hydroxychloroquine sulfate in the Strategic National Stockpile to be used by licensed health care providers to treat patients hospitalized with COVID-19 when the providers determine the potential benefit outweighs the potential risk to the patient.* Following reports of cardiac and other adverse events in patients receiving hydroxychloroquine for COVID-19 (2), on April 24, 2020, FDA issued a caution against its use† and on June 15, rescinded its EUA for hydroxychloroquine from the Strategic National Stockpile.§ Following the FDA's issuance of caution and EUA rescindment, on May 12 and June 16, the federal COVID-19 Treatment Guidelines Panel issued recommendations against the use of hydroxychloroquine or chloroquine to treat COVID-19; the panel also noted that at that time no medication could be recommended for COVID-19 pre- or postexposure prophylaxis outside the setting of a clinical trial (3). However, public discussion concerning the effectiveness of these drugs on outcomes of COVID-19 (4,5), and clinical trials of hydroxychloroquine for prophylaxis of COVID-19 continue.¶ In response to recent reports of notable increases in prescriptions for hydroxychloroquine or chloroquine (6), CDC analyzed outpatient retail pharmacy transaction data to identify potential differences in prescriptions dispensed by provider type during January-June 2020 compared with the same period in 2019. Before 2020, primary care providers and specialists who routinely prescribed hydroxychloroquine, such as rheumatologists and dermatologists, accounted for approximately 97% of new prescriptions. New prescriptions by specialists who did not typically prescribe these medications (defined as specialties accounting for ≤2% of new prescriptions before 2020) increased from 1,143 prescriptions in February 2020 to 75,569 in March 2020, an 80-fold increase from March 2019. Although dispensing trends are returning to prepandemic levels, continued adherence to current clinical guidelines for the indicated use of these medications will ensure their availability and benefit to patients for whom their use is indicated (3,4), because current data on treatment and pre- or postexposure prophylaxis for COVID-19 indicate that the potential benefits of these drugs do not appear to outweigh their risks.


Subject(s)
Chloroquine/therapeutic use , Hydroxychloroquine/therapeutic use , Practice Patterns, Physicians'/statistics & numerical data , Specialization/statistics & numerical data , Coronavirus Infections/drug therapy , Female , Humans , Male , Treatment Outcome , United States , COVID-19 Drug Treatment
14.
MMWR Morb Mortal Wkly Rep ; 69(11): 298-302, 2020 Mar 20.
Article in English | MEDLINE | ID: mdl-32191686

ABSTRACT

In 2017, prescription opioids were involved in 36% of opioid-involved overdose deaths in the United States (1). Prescription opioids can be obtained by prescription or through diversion (the channeling of regulated drugs from legal to illegal sources) (2). Among new heroin users, 66%-83% reported that their opioid use began with the misuse of a prescription opioid (3). "Misuse" is generally defined as drugs taken for a purpose other than that directed by the prescribing physician, in greater amounts, more often, or for a longer duration than prescribed (2). Exposure to prescription opioids can be lessened by ensuring recommended prescribing, thereby potentially reducing the risk for misuse, opioid use disorder, and overdose (4). Sex and age groups with high exposure to prescription opioids are not well defined. Using a retail pharmaceutical database from IQVIA,* nationwide trends in opioid prescription fill rates for adult outpatients by age and sex were examined during 2008-2018. Opioid prescription fill rates were disproportionately higher among men and women aged ≥65 years and women of all ages. For reasons not well understood, these disparities persisted over 11 years even as the opioid fill rate declined for each age group and sex. Interventions to improve prescribing practices by following evidence-based guidelines that include weighing the benefits and risks for using prescription opioids for each patient and adopting a multimodal approach to pain management could improve patient safety while ameliorating pain. These efforts might need to consider the unique needs of women and older adults, who have the highest opioid prescription fill rates.


Subject(s)
Ambulatory Care/statistics & numerical data , Analgesics, Opioid/therapeutic use , Drug Prescriptions/statistics & numerical data , Healthcare Disparities/statistics & numerical data , Adult , Age Factors , Aged , Female , Humans , Male , Middle Aged , Sex Factors , United States , Young Adult
15.
J Clin Med ; 8(11)2019 Oct 24.
Article in English | MEDLINE | ID: mdl-31652928

ABSTRACT

Unsterile opioid injection increases risk for infection transmission, including HIV, hepatitis B virus (HBV), or hepatitis C virus (HCV). We assess prevalence of and risk factors associated with opioid overdose and infections with HIV, HBV, or HCV among Medicare beneficiaries with opioid-related fee-for-service claims during 2015. We conducted a cross-sectional analysis to estimate claims for opioid use and overdose and HIV, HBV, or HCV infections, using data from US Medicare fee-for-service claims. Beneficiaries with opioid-related claims had increased odds for HIV (2.3; 95% confidence interval (CI), 2.3-2.4), acute HBV (6.7; 95% CI, 6.3-7.1), chronic HBV (5.0; 95% CI, 4.7-5.4), acute HCV (9.6; 95% CI, 9.2-10.0), and chronic HCV (8.9; 95% CI, 8.7-9.1). Beneficiaries with opioid-related claims and for HIV, HBV, or HCV infection, respectively, had a 1.1-1.9-fold odds for having a claim for opioid overdose. Independent risk factors for opioid overdose and each selected infection outcome included age, sex, race/ethnicity, region, and residence in a high-vulnerability county. Having opioid-related claims and selected demographic attributes were independent, significant risk factors for having HIV, HBV, or HCV claims among US Medicare beneficiaries. These results might help guide interventions intended to reduce incidences of HIV, HCV, and HBV infections among beneficiaries with opioid-related claims.

16.
JAMA Netw Open ; 2(3): e190665, 2019 03 01.
Article in English | MEDLINE | ID: mdl-30874783

ABSTRACT

Importance: Risk of opioid use disorder, overdose, and death from prescription opioids increases as dosage, duration, and use of extended-release and long-acting formulations increase. States are well suited to respond to the opioid crisis through legislation, regulations, enforcement, surveillance, and other interventions. Objective: To estimate temporal trends and geographic variations in 6 key opioid prescribing measures in 50 US states and the District of Columbia. Design, Setting, and Participants: Population-based cross-sectional analysis of opioid prescriptions filled nationwide at US retail pharmacies between January 1, 2006, and December 31, 2017. Data were obtained from the IQVIA Xponent database. All US residents who had an opioid prescription filled at a US retail pharmacy were included. Main Outcomes and Measures: Primary outcomes were annual amount of opioids prescribed in morphine milligram equivalents (MME) per person; mean duration per prescription in days; and 4 separate prescribing rates-for prescriptions 3 or fewer days, those 30 days or longer, those with a high daily dosage (≥90 MME), and those with extended-release and long-acting formulations. Results: Between 2006 and 2017, an estimated 233.7 million opioid prescriptions were filled in retail pharmacies in the United States each year. For all states combined, 4 measures decreased: (1) mean (SD) amount of opioids prescribed (mean [SD] decrease, 12.8% [12.6%]) from 628.4 (178.0) to 543.4 (158.6) MME per person, a statistically significant decrease in 23 states; (2) high daily dosage (mean [SD] decrease, 53.1% [13.6%]) from 12.3 (3.4) to 5.6 (1.7) per 100 persons, a statistically significant decrease in 49 states; (3) short-term (≤3 days) duration (mean [SD] decrease, 43.1% [9.4%]) from 18.0 (5.4) to 10.0 (2.5) per 100 persons, a statistically significant decrease in 48 states; and (4) extended-release and long-acting formulations (mean [SD] decrease, 14.7% [13.7%]) from 7.2 (1.9) to 6.0 (1.7) per 100 persons, a statistically significant decrease in 27 states. Two measures increased, each associated with the duration of prescription dispensed: (1) mean (SD) prescription duration (mean [SD] increase, 37.6% [6.9%]) from 13.0 (1.2) to 17.9 (1.4) days, a statistically significant increase in every state; and (2) prescriptions for a term of 30 days or longer (mean [SD] increase, 37.7% [28.9%]) from 18.3 (7.7) to 24.9 (10.7) per 100 persons, a statistically significant increase in 39 states. Two- to 3-fold geographic differences were observed across states, measured by comparing the ratio of each state's 90th to 10th percentile for each measure. Conclusions and Relevance: In this study, across 12 years, the mean duration and prescribing rate for long-term prescriptions of opioids increased, whereas the amount of opioids prescribed per person and prescribing rate for high-dosage prescriptions, short-term prescriptions, and extended-release and long-acting formulations decreased. Some decreases were significant, but results were still high. Two- to 3-fold state variation in 5 measures occurred in most states. This information may help when state-specific intervention programs are being designed.


Subject(s)
Analgesics, Opioid/administration & dosage , Drug Prescriptions/statistics & numerical data , Practice Patterns, Physicians'/statistics & numerical data , Cross-Sectional Studies , Humans , Time Factors , United States/epidemiology
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