Receipt of Diabetes Specialty Care and Management Services by Older Adults With Diabetes in the United States, 2015-2019: An Analysis of Medicare Fee-for-Service Claims.

OBJECTIVE: We characterized the receipt of diabetes specialty care and management services among older adults with diabetes. RESEARCH DESIGN AND METHODS: Using a 20% random sample of fee-for-service Medicare beneficiaries aged ≥65 years, we analyzed cohorts of type 1 diabetes (T1D) or type 2 diabetes (T2D) with history of severe hypoglycemia (HoH), and all other T2D annually from 2015 to 2019. Outcomes were receipt of office-based endocrinology care, diabetes education, outpatient diabetes health services, excluding those provided in primary care, and any of the aforementioned services. RESULTS: In the T1D cohort, receipt of endocrinology care and any service increased from 25.9% and 29.2% in 2015 to 32.7% and 37.4% in 2019, respectively. In the T2D with HoH cohort, receipt of endocrinology care and any service was 13.9% and 16.4% in 2015, with minimal increases. Age, race/ethnicity, residential setting, and income were associated with receiving care. CONCLUSIONS: These findings suggest that many older adults may not receive specialty diabetes care and underscore health disparities.

Validation of an international classification of disease, tenth revision, clinical modification (ICD-10-CM) algorithm in identifying severe hypoglycaemia events for real-world studies.

AIM: The transition to the ICD-10-CM coding system has reduced the utility of hypoglycaemia algorithms based on ICD-9-CM diagnosis codes in real-world studies of antidiabetic drugs. We mapped a validated ICD-9-CM hypoglycaemia algorithm to ICD-10-CM codes to create an ICD-10-CM hypoglycaemia algorithm and assessed its performance in identifying severe hypoglycaemia. MATERIALS AND METHODS: We assembled a cohort of Medicare patients with DM and linked electronic health record (EHR) data to the University of North Carolina Health System and identified candidate severe hypoglycaemia events from their Medicare claims using the ICD-10-CM hypoglycaemia algorithm. We confirmed severe hypoglycaemia by EHR review and computed a positive predictive value (PPV) of the algorithm to assess its performance. We refined the algorithm by removing poor performing codes (PPV ≤0.5) and computed a Cohen's κ statistic to evaluate the agreement of the EHR reviews. RESULTS: The algorithm identified 642 candidate severe hypoglycaemia events, and we confirmed 455 as true severe hypoglycaemia events, PPV of 0.709 (95% confidence interval: 0.672, 0.744). When we refined the algorithm, the PPV increased to 0.893 (0.862, 0.918) and missed <2.42% (<11) true severe hypoglycaemia events. Agreement between reviewers was high, κ = 0.93 (0.89, 0.97). CONCLUSIONS: We translated an ICD-9-CM hypoglycaemia algorithm to an ICD-10-CM version and found its performance was modest. The performance of the algorithm improved by removing poor performing codes at the trade-off of missing very few severe hypoglycaemia events. The algorithm has the potential to be used to identify severe hypoglycaemia in real-world studies of antidiabetic drugs.

Cardiovascular Outcomes of α-Blockers vs 5-α Reductase Inhibitors for Benign Prostatic Hyperplasia.

Importance: The most prescribed class of medications for benign prostatic hyperplasia (BPH) is α-blockers (ABs). However, the cardiovascular safety profile of these medications among patients with BPH is not well understood. Objective: To compare the safety of ABs vs 5-α reductase inhibitors (5-ARIs) for risk of adverse cardiovascular outcomes. Design, Setting, and Participants: This active comparator, new-user cohort study was conducted using insurance claims data from a 20% random sample of Medicare beneficiaries from 2007 to 2019 to evaluate the 1-year risk of adverse cardiovascular outcomes. Males aged 66 to 90 years were indexed into the cohort at new use of an AB or 5-ARI. Twelve months of continuous enrollment and at least 1 diagnosis code for BPH within 12 months prior to initiation were required. Data were analyzed from January 2007 through December 2019. Exposures: Exposure was defined by a qualifying prescription fill for an AB or 5-ARI after at least 12 months without a prescription for these drug classes. Main Outcomes and Measures: Follow-up began at a qualified refill for the study drug. Primary study outcomes were hospitalization for heart failure (HF), composite major adverse cardiovascular events (MACE; hospitalization for stroke, myocardial infarction, or death), composite MACE or hospitalization for HF, and death. Inverse probability of treatment and censoring-weighted 1-year risks, risk ratios (RRs), and risk differences (RDs) were estimated for each outcome. Results: Among 189 868 older adult males, there were 163 829 patients initiating ABs (mean [SD] age, 74.6 [6.2] years; 579 American Indian or Alaska Native [0.4%], 5890 Asian or Pacific Islander [3.6%], 9179 Black [5.6%], 10 610 Hispanic [6.5%], and 133 510 non-Hispanic White [81.5%]) and 26 039 patients initiating 5-ARIs (mean [SD] age, 75.3 [6.4] years; 76 American Indian or Alaska Native [0.3%], 827 Asian or Pacific Islander [3.2%], 1339 Black [5.1%], 1656 Hispanic [6.4%], and 21 605 non-Hispanic White [83.0%]). ABs compared with 5-ARIs were associated with an increased 1-year risk of MACE (8.95% [95% CI, 8.81%-9.09%] vs 8.32% [95% CI, 7.92%-8.72%]; RR = 1.08 [95% CI, 1.02-1.13]; RD per 1000 individuals = 6.26 [95% CI, 2.15-10.37]), composite MACE and HF (RR = 1.07; [95% CI, 1.03-1.12]; RD per 1000 individuals = 7.40 [95% CI, 2.88-11.93 ]), and death (RR = 1.07; [95% CI, 1.01-1.14]; RD per 1000 individuals = 3.85 [95% CI, 0.40-7.29]). There was no difference in risk for HF hospitalization alone. Conclusions and Relevance: These results suggest that ABs may be associated with an increased risk of adverse cardiovascular outcomes compared with 5-ARIs. If replicated with more detailed confounder data, these results may have important public health implications given these medications' widespread use.

Incidence, Prevalence, and Racial and Ethnic Distribution of Inflammatory Bowel Disease in the United States.

BACKGROUND & AIMS: We sought to estimate the incidence, prevalence, and racial-ethnic distribution of physician-diagnosed inflammatory bowel disease (IBD) in the United States. METHODS: The study used 4 administrative claims data sets: a 20% random sample of national fee-for-service Medicare data (2007 to 2017); Medicaid data from Florida, New York, Pennsylvania, Ohio, and California (1999 to 2012); and commercial health insurance data from Anthem beneficiaries (2006 to 2018) and Optum's deidentified Clinformatics Data Mart (2000 to 2017). We used validated combinations of medical diagnoses, diagnostic procedures, and prescription medications to identify incident and prevalent diagnoses. We computed pooled age-, sex-, and race/ethnicity-specific insurance-weighted estimates and pooled estimates standardized to 2018 United States Census estimates with 95% confidence intervals (CIs). RESULTS: The age- and sex-standardized incidence of IBD per 100,000 person-years was 10.9 (95% CI, 10.6-11.2). The incidence of IBD peaked in the third decade of life, decreased to a relatively stable level across the fourth to eighth decades, and declined further. The age-, sex- and insurance-standardized prevalence of IBD was 721 per 100,000 population (95% CI, 717-726). Extrapolated to the 2020 United States Census, an estimated 2.39 million Americans are diagnosed with IBD. The prevalence of IBD per 100,000 population was 812 (95% CI, 802-823) in White, 504 (95% CI, 482-526) in Black, 403 (95% CI, 373-433) in Asian, and 458 (95% CI, 440-476) in Hispanic Americans. CONCLUSIONS: IBD is diagnosed in >0.7% of Americans. The incidence peaks in early adulthood and then plateaus at a lower rate. The disease is less commonly diagnosed in Black, Asian, and Hispanic Americans.

Development and Validation of Claims-Based Definitions to Identify Incident and Prevalent Inflammatory Bowel Disease in Administrative Healthcare Databases.

BACKGROUND: To facilitate inflammatory bowel disease (IBD) research in the United States, we developed and validated claims-based definitions to identify incident and prevalent IBD diagnoses using administrative healthcare claims data among multiple payers. METHODS: We used data from Medicare, Medicaid, and the HealthCore Integrated Research Database (Anthem commercial and Medicare Advantage claims). The gold standard for validation was review of medical records. We evaluated 1 incidence and 4 prevalence algorithms based on a combination of International Classification of Diseases codes, National Drug Codes, and Current Procedural Terminology codes. The claims-based incident diagnosis date needed to be within ±90 days of that recorded in the medical record to be valid. RESULTS: We reviewed 111 charts of patients with a potentially incident diagnosis. The positive predictive value (PPV) of the claims algorithm was 91% (95% confidence interval [CI], 81%-97%). We reviewed 332 charts to validate prevalent case definition algorithms. The PPV was 94% (95% CI, 86%-98%) for ≥2 IBD diagnoses and presence of prescriptions for IBD medications, 92% (95% CI, 85%-97%) for ≥2 diagnoses without any medications, 78% (95% CI, 67%-87%) for a single diagnosis and presence of an IBD medication, and 35% (95% CI, 25%-46%) for 1 physician diagnosis and no IBD medications. CONCLUSIONS: Through a combination of diagnosis, procedural, and medication codes in insurance claims data, we were able to identify incident and prevalent IBD cases with high accuracy. These algorithms can be useful for the ascertainment of IBD cases in future studies.

Healthcare system engagement and algorithm-identified cancer incidence following initiation of a new medication.

PURPOSE: Implausibly high algorithm-identified cancer incidence within a new user study after medication initiation may result from increased healthcare utilization (HU) around initiation ("catch-up care") that increases diagnostic opportunity. Understanding the relationships between HU prior to and around initiation and subsequent cancer rates and timing is important to avoiding protopathic bias. METHODS: We identified a cohort of 417 458 Medicare beneficiaries (2007-2014) aged ≥66 initiating an antihypertensive (AHT) after ≥180 days of non-use. Initiators were stratified into groups of 0, 1, 2-3, and ≥4 outpatient visits (OV) 60-360 days before initiation. We calculated algorithm-identified colorectal cancer (aiCRC) rates stratified by OVs and time since AHT initiation: (0-90, 91-180, 181-365, 366-730, and 731+ days). We summarized HU -360/+60 days around AHT initiation by aiCRC timing: (0-29, 30-89, 90-179, and ≥180 days). RESULTS: AiCRC incidence (311 per 100 000 overall) peaked in the first 0-90 days, was inversely associated with HU before initiation, and stabilized ≥180 days after AHT initiation. Catch-up care was greatest among persons with aiCRCs identified <30 days in follow-up. Catch-up care magnitude decreased as time to the aiCRC date increased, with aiCRCs identified ≥180 days after AHT initiation exhibiting similar HU compared with the full cohort. CONCLUSION: Lower HU before-and increased HU around AHT initiation-seem to drive excess short-term aiCRC incidence. Person-time and case accrual should only begin when incidence stabilizes. When comparison groups within a study differ by HU, outcome-detection bias may exist. Similar observations may exist in other settings when typical HU is delayed (e.g., cancer screening during SARS-CoV-2).

Nondifferential Treatment Misclassification Biases Toward the Null? Not a Safe Bet for Active Comparator Studies.

Active comparator studies are increasingly common, particularly in pharmacoepidemiology. In such studies, the parameter of interest is a contrast (difference or ratio) in the outcome risks between the treatment of interest and the selected active comparator. While it may appear treatment is dichotomous, treatment is actually polytomous as there are at least 3 levels: no treatment, the treatment of interest, and the active comparator. Because misclassification may occur between any of these groups, independent nondifferential treatment misclassification may not be toward the null (as expected with a dichotomous treatment). In this work, we describe bias from independent nondifferential treatment misclassification in active comparator studies with a focus on misclassification that occurs between each active treatment and no treatment. We derive equations for bias in the estimated outcome risks, risk difference, and risk ratio, and we provide bias correction equations that produce unbiased estimates, in expectation. Using data obtained from US insurance claims data, we present a hypothetical comparative safety study of antibiotic treatment to illustrate factors that influence bias and provide an example probabilistic bias analysis using our derived bias correction equations.

Considerations for observational study design: Comparing the evidence of opioid use between electronic health records and insurance claims.

PURPOSE: Pharmacoepidemiology studies often use insurance claims and/or electronic health records (EHR) to capture information about medication exposure. The choice between these data sources has important implications. METHODS: We linked EHR from a large academic health system (2015-2017) to Medicare insurance claims for patients undergoing surgery. Drug utilization was characterized based on medication order dates in the EHR, and prescription fill dates in Medicare claims. We compared opioid use documented in EHR orders to prescription claims in four time periods: 1) Baseline (182 days before surgery); 2) Perioperative period; 3) Discharge date; 4) Follow-up (90 days after surgery). RESULTS: We identified 11 128 patients undergoing surgery. During baseline, 34.4% (EHR) versus 44.1% (claims) had evidence of opioid use, and 56.9% of all baseline use was reflected only in one data source. During the perioperative period, 78.8% (EHR) versus 47.6% (claims) had evidence of use. On the day of discharge, 59.6% (EHR) versus 45.5% (claims) had evidence of use, and 51.8% of all discharge use was reflected only in one data source. During follow-up, 4.3% (EHR) versus 10.4% (claims) were identified with prolonged opioid use following surgery with 81.4% of all prolonged use reflected only in one data source. CONCLUSIONS: When characterizing opioid exposure, we found substantial discrepancies between EHR medication orders and prescription claims data. In all time periods assessed, most patients' use was reflected only in the EHR, or only in the claims, not both. The potential for misclassification of drug utilization must be evaluated carefully, and choice of data source may have large impacts on key study design elements.

Trends in characteristics and outcomes among US adults hospitalised with COVID-19 throughout 2020: an observational cohort study.

OBJECTIVES: To examine the temporal patterns of patient characteristics, treatments used and outcomes associated with COVID-19 in patients who were hospitalised for the disease between January and 15 November 2020. DESIGN: Observational cohort study. SETTING: COVID-19 subset of the Optum deidentified electronic health records, including more than 1.8 million patients from across the USA. PARTICIPANTS: There were 51 510 hospitalised patients who met the COVID-19 definition, with 37 617 in the laboratory positive cohort and 13 893 in the clinical cohort. PRIMARY AND SECONDARY OUTCOME MEASURES: Incident acute clinical outcomes, including in-hospital all-cause mortality. RESULTS: Respectively, 48% and 49% of the laboratory positive and clinical cohorts were women. The 50- 65 age group was the median age group for both cohorts. The use of antivirals and dexamethasone increased over time, fivefold and twofold, respectively, while the use of hydroxychloroquine declined by 98%. Among adult patients in the laboratory positive cohort, absolute age/sex standardised incidence proportion for in-hospital death changed by -0.036 per month (95% CI -0.042 to -0.031) from March to June 2020, but remained fairly flat from June to November, 2020 (0.001 (95% CI -0.001 to 0.003), 17.5% (660 deaths /3986 persons) in March and 10.2% (580/5137) in October); in the clinical cohort, the corresponding changes were -0.024 (95% CI -0.032 to -0.015) and 0.011 (95% CI 0.007 0.014), respectively (14.8% (175/1252) in March, 15.3% (189/1203) in October). Declines in the cumulative incidence of most acute clinical outcomes were observed in the laboratory positive cohort, but not for the clinical cohort. CONCLUSION: The incidence of adverse clinical outcomes remains high among COVID-19 patients with clinical diagnosis only. Patients with COVID-19 entering the hospital are at elevated risk of adverse outcomes.

Trends in the use of disease-modifying therapies among reproductive-aged women with multiple sclerosis in the United States from 2010 to 2019.

PURPOSE: Multiple sclerosis (MS) is a chronic disease of the central nervous system that disproportionately affects women, with typical onset during reproductive age. Several disease-modifying therapies (DMTs) are FDA-approved to slow disease progression, but are not indicated for use during pregnancy. Our objective was to describe trends over time (2010-2019) in monthly point prevalence of DMT use among reproductive-age women, overall and by generic name. METHODS: This study used administrative claims data from the US during 2009-2019 to identify women age 15-44 with MS and continuous insurance coverage for ≥12 months. DMTs were identified using prescription fills and procedural claims for alemtuzumab, daclizumab, dimethyl fumarate, fingolimod, glatiramer acetate, interferon beta, mitoxantrone, natalizumab, ocrelizumab, and teriflunomide. Monthly prevalent use was defined as ≥1 days' supply of a DMT in the month. Age- and region-standardized monthly prevalence was estimated nonparametrically. RESULTS: Among 42 281 reproductive-aged women over 818 179 person-months, DMT use increased from a minimum monthly prevalence of 49.3% (February, 2011) to a maximum of 58.7% (April, 2019). In 2010, prevalence of injectable DMTs was 43.1% compared to 2.5% for oral DMTs; by 2014, however, oral DMTs (26.5%) surpassed injectable DMTs (23.7%) as the most common route of administration. In the most recent data available (December, 2019), the most common DMTs were dimethyl fumarate, glatiramer acetate, and fingolimod. CONCLUSIONS: DMT use among reproductive-aged women has rapidly evolved during the past decade. Collaborative treatment decision making between women with MS and clinicians may help optimize MS care and improve DMT uptake during reproductive years.

Perinatal morbidity and health utilization among mothers of medically fragile infants.

OBJECTIVE: To determine the burden of perinatal morbidity among mothers of medically fragile infants. STUDY DESIGN: We conducted a retrospective cohort study of 6849 mothers who delivered liveborn infants at a quaternary care hospital during a two-year period. We compared mothers of well babies with mothers of infants admitted to the Neonatal Intensive Care Unit (NICU), and we used logistic regression to model predictors of postpartum acute care utilization among NICU mothers. RESULTS: Rates of obstetric morbidity were highest for mothers of infants staying ≥72 h in the NICU; 54.2% underwent cesarean birth, 7.5% experienced severe maternal morbidity, and 6.6% required a blood transfusion. Factors independently associated with postpartum acute care use included gestational age <28 weeks, ever smoking, non-Hispanic Black race, temperature >38 °C and receiving psychiatric medication during the birth hospitalization. CONCLUSION: Focused support for mothers of NICU infants has the potential to reduce maternal morbidity and improve health.

Impacts of Initial Prescription Length and Prescribing Limits on Risk of Prolonged Postsurgical Opioid Use.

BACKGROUND: In response to concerns about opioid addiction following surgery, many states have implemented laws capping the days supplied for initial postoperative prescriptions. However, few studies have examined changes in the risk of prolonged opioid use associated with the initial amount prescribed. OBJECTIVE: The objective of this study was to estimate the risk of prolonged opioid use associated with the length of initial opioid prescribed and the potential impact of prescribing limits. RESEARCH DESIGN: Using Medicare insurance claims (2007-2017), we identified opioid-naive adults undergoing surgery. Using G-computation methods with logistic regression models, we estimated the risk of prolonged opioid use (≥1 opioid prescription dispensed in 3 consecutive 30-d windows following surgery) associated with the varying initial number of days supplied. We then estimate the potential reduction in cases of prolonged opioid use associated with varying prescribing limits. RESULTS: We identified 1,060,596 opioid-naive surgical patients. Among the 70.0% who received an opioid for postoperative pain, 1.9% had prolonged opioid use. The risk of prolonged use increased from 0.7% (1 d supply) to 4.4% (15+ d). We estimated that a prescribing limit of 4 days would be associated with a risk reduction of 4.84 (3.59, 6.09)/1000 patients and would be associated with 2255 cases of prolonged use potentially avoided. The commonly used day supply limit of 7 would be associated with a smaller reduction in risk [absolute risk difference=2.04 (-0.17, 4.25)/1000]. CONCLUSIONS: The risk of prolonged opioid use following surgery increased monotonically with increasing prescription duration. Common prescribing maximums based on days supplied may impact many patients but are associated with relatively low numbers of reduced cases of prolonged use. Any prescribing limits need to be weighed against the need for adequate pain management.

Real-world treatment patterns and clinical outcomes for inpatients with COVID-19 in the US from September 2020 to February 2021.

The objective of this retrospective cohort study was to describe pre-treatment characteristics, treatment patterns, health resource use, and clinical outcomes among adults hospitalized with COVID-19 in the United States (US) who initiated common treatments for COVID-19. The Optum® COVID-19 electronic health records database was used to identify patients >18 years, diagnosed with COVID-19, who were admitted to an inpatient setting and received treatments of interest for COVID-19 between September 2020 and January 2021. Patients were stratified into cohorts based on index treatment use. Patient demographics, medical history, care setting, medical procedures, subsequent treatment use, patient disposition, clinical improvement, and outcomes were summarized descriptively. Among a total of 26,192 patients identified, the most prevalent treatments initiated were dexamethasone (35.4%) and dexamethasone + remdesivir (14.9%), and dexamethasone was the most common subsequent treatment. At day 14 post-index, <10% of patients received any treatments of interest. Mean (standard deviation [SD]) patient age was 65.6 (15.6) years, and the most prevalent comorbidities included hypertension (44.8%), obesity (35.4%), and diabetes (25.7%). At the end of follow-up, patients had a mean (SD) 8.1 (6.6) inpatient days and 1.4 (4.1) days with ICU care. Oxygen supplementation, non-invasive, or invasive ventilation was required by 4.5%, 3.0%, and 3.1% of patients, respectively. At the end of follow-up, 84.2% of patients had evidence of clinical improvement, 3.1% remained hospitalized, 83.8% were discharged, 4% died in hospital, and 9.1% died after discharge. Although the majority of patients were discharged alive, no treatments appeared to alleviate the inpatient morbidity and mortality associated with COVID-19. This highlights an unmet need for effective treatment options for patients hospitalized with COVID-19.

Characteristics and outcomes of hospitalised adults with COVID-19 in a Global Health Research Network: a cohort study.

OBJECTIVE: To examine age, gender, and temporal differences in baseline characteristics and clinical outcomes of adult patients hospitalised with COVID-19. DESIGN: A cohort study using deidentified electronic medical records from a Global Research Network. SETTING/PARTICIPANTS: 67 456 adult patients hospitalised with COVID-19 from the USA; 7306 from Europe, Latin America and Asia-Pacific between February 2020 and January 2021. RESULTS: In the US cohort, compared with patients 18-34 years old, patients ≥65 had a greater risk of intensive care unit (ICU) admission (adjusted HR (aHR) 1.73, 95% CI 1.58 to 1.90), acute respiratory distress syndrome(ARDS)/respiratory failure (aHR 1.86, 95% CI 1.76 to 1.96), invasive mechanical ventilation (IMV, aHR 1.93, 95% CI, 1.73 to 2.15), and all-cause mortality (aHR 5.6, 95% CI 4.36 to 7.18). Men appeared to be at a greater risk for ICU admission (aHR 1.34, 95% CI 1.29 to 1.39), ARDS/respiratory failure (aHR 1.24, 95% CI1.21 to 1.27), IMV (aHR 1.38, 95% CI 1.32 to 1.45), and all-cause mortality (aHR 1.16, 95% CI 1.08 to 1.24) compared with women. Moreover, we observed a greater risk of adverse outcomes during the early pandemic (ie, February-April 2020) compared with later periods. In the ex-US cohort, the age and gender trends were similar; for the temporal trend, the highest proportion of patients with all-cause mortality were also in February-April 2020; however, the highest percentages of patients with IMV and ARDS/respiratory failure were in August-October 2020 followed by February-April 2020. CONCLUSIONS: This study provided valuable information on the temporal trends of characteristics and outcomes of hospitalised adult COVID-19 patients in both USA and ex-USA. It also described the population at a potentially greater risk for worse clinical outcomes by identifying the age and gender differences. Together, the information could inform the prevention and treatment strategies of COVID-19. Furthermore, it can be used to raise public awareness of COVID-19's impact on vulnerable populations.

Day-of-Surgery Gabapentinoids and Prolonged Opioid Use: A Retrospective Cohort Study of Medicare Patients Using Electronic Health Records.

BACKGROUND: While preoperative gabapentinoids are commonly used in surgical multimodal analgesia protocols, little is known regarding the effects this therapy has on prolonged postsurgical opioid use. In this observational study, we used data from a large integrated health care system to estimate the association between preoperative day-of-surgery gabapentinoids and the risk of prolonged postsurgical opioid use. METHODS: We identified adults age ≥65 years undergoing major therapeutic surgical procedures from a large integrated health care system from 2016 to 2019. Exposure to preoperative gabapentinoids on the day of surgery was measured using inpatient medication administration records, and the outcome of prolonged opioid use was measured using outpatient medication orders. We used stabilized inverse probability of treatment-weighted log-binomial regression to estimate risk ratios and 95% confidence intervals (CIs) of prolonged opioid use, comparing patients who received preoperative gabapentinoids to those who did not and adjusting for relevant clinical factors. The main analysis was conducted in the overall surgical population, and a secondary analysis was conducted among procedures where at least 30% of all patients received a preoperative gabapentinoid. RESULTS: Overall, 13,958 surgical patients met inclusion criteria, of whom 21.0% received preoperative gabapentinoids. The observed 90-day risk of prolonged opioid use following surgery was 0.91% (95% CI, 0.77-1.08). Preoperative gabapentinoid administration was not associated with a reduced risk of prolonged opioid use in the main analysis conducted in a broad surgical population (adjusted risk ratio [adjRR], 1.19 [95% CI, 0.67-2.12]) or in the secondary analysis conducted in patients undergoing colorectal resection, hip arthroplasty, knee arthroplasty, or hysterectomy (adjRR, 1.01 [95% CI, 0.30-3.33]). CONCLUSIONS: In a large integrated health system, we did not find evidence that preoperative gabapentinoids were associated with reduced risk of prolonged opioid use in patients undergoing a broad range of surgeries.

Fluoroquinolone Antibiotics and Tendon Injury in Adolescents.

OBJECTIVES: To estimate the association between fluoroquinolone use and tendon injury in adolescents. METHODS: We conducted an active-comparator, new-user cohort study using population-based claims data from 2000 to 2018. We included adolescents (aged 12-18 years) with an outpatient prescription fill for an oral fluoroquinolone or comparator broad-spectrum antibiotic. The primary outcome was Achilles, quadricep, patellar, or tibial tendon rupture identified by diagnosis and procedure codes. Tendinitis was a secondary outcome. We used weighting to adjust for measured confounding and a negative control outcome to assess residual confounding. RESULTS: The cohort included 4.4 million adolescents with 7.6 million fills for fluoroquinolone (275 767 fills) or comparator (7 365 684) antibiotics. In the 90 days after the index antibiotic prescription, there were 842 tendon ruptures and 16 750 tendinitis diagnoses (crude rates 0.47 and 9.34 per 1000 person-years, respectively). The weighted 90-day tendon rupture risks were 13.6 per 100 000 fluoroquinolone-treated adolescents and 11.6 per 100 000 comparator-treated adolescents (fluoroquinolone-associated excess risk: 1.9 per 100 000 adolescents; 95% confidence interval -2.6 to 6.4); the corresponding number needed to treat to harm was 52 632. For tendinitis, the weighted 90-day risks were 200.8 per 100 000 fluoroquinolone-treated adolescents and 178.1 per 100 000 comparator-treated adolescents (excess risk: 22.7 per 100 000; 95% confidence interval 4.1 to 41.3); the number needed to treat to harm was 4405. CONCLUSIONS: The excess risk of tendon rupture associated with fluoroquinolone treatment was extremely small, and these events were rare. The excess risk of tendinitis associated with fluoroquinolone treatment was also small. Other more common potential adverse drug effects may be more important to consider for treatment decision-making, particularly in adolescents without other risk factors for tendon injury.

Propensity score trimming mitigates bias due to covariate measurement error in inverse probability of treatment weighted analyses: A plasmode simulation.

BACKGROUND: Inverse probability of treatment weighting (IPTW) may be biased by influential observations, which can occur from misclassification of strong exposure predictors. METHODS: We evaluated bias and precision of IPTW estimators in the presence of a misclassified confounder and assessed the effect of propensity score (PS) trimming. We generated 1000 plasmode cohorts of size N = 10 000, sampled with replacement from 6063 NHANES respondents (1999-2014) age 40 to 79 with labs and no statin use. We simulated statin exposure as a function of demographics and CVD risk factors; and outcomes as a function of 10-year CVD risk score and statin exposure (rate ratio [RR] = 0.5). For 5% of the people in selected populations (eg, all patients, exposed, those with outcomes), we randomly misclassified a confounder that strongly predicted exposure. We fit PS models and estimated RRs using IPTW and 1:1 PS matching, with and without asymmetric trimming. RESULTS: IPTW bias was substantial when misclassification was differential by outcome (RR range: 0.38-0.63) and otherwise minimal (RR range: 0.51-0.53). However, trimming reduced bias for IPTW, nearly eliminating it at 5% trimming (RR range: 0.49-0.52). In one scenario, when the confounder was misclassified for 5% of those with outcomes (0.3% of cohort), untrimmed IPTW was more biased and less precise (RR = 0.37 [SE(logRR) = 0.21]) than matching (RR = 0.50 [SE(logRR) = 0.13]). After 1% trimming, IPTW estimates were unbiased and more precise (RR = 0.49 [SE(logRR) = 0.12]) than matching (RR = 0.51 [SE(logRR) = 0.14]). CONCLUSIONS: Differential misclassification of a strong predictor of exposure resulted in biased and imprecise IPTW estimates. Asymmetric trimming reduced bias, with more precise estimates than matching.

Postsurgical Opioid Prescriptions and Risk of Long-term Use: An Observational Cohort Study Across the United States.

OBJECTIVE: The aim of this study was to evaluate differences in risk of long-term opioid therapy after surgery among an opioid-naive population using varying cutoffs based on days supplied (DS), total morphine milligram equivalents (MME) dispensed, and quantity of pills (QTY) dispensed. BACKGROUND: In response to the US opioid crisis, opioid prescription (Rx) limits have been implemented on a state-by-state basis beginning in 2016. However, there is limited evidence informing appropriate prescribing limits, and the effect of these policies on long-term opioid therapy. METHODS: Using the MarketScan claims databases, we identified all opioid-naive patients undergoing outpatient surgery between July 1, 2006 and June 30, 2015. We identified the initial postsurgical opioid prescribed, examining the DS, total MME, and QTY dispensed. We used Poisson to estimate adjusted risk differences and risk ratios of long-term opioid use comparing those receiving larger versus smaller volume of opioids. RESULTS: We identified 5,148,485 opioid-naive surgical patients. Overall, 55.5% received an opioid for postoperative pain, with median days supply = 5 and median total MME = 240. The proportion of patients receiving prescriptions above 7 DS increased from 11% in 2006 to 19% in 2015. Among those receiving postoperative opioids, 8% had long-term opioid use, and risk of long-term use was 1.16 times [95% confidence interval (CI), 1.10-1.25] higher among those receiving >7 days compared with those receiving ≤7 days. Those receiving >400 total MME (15% of patients) were at 1.17 times (95% CI, 1.10-1.25) the risk of long-term use compared with those receiving ≤400 MME. CONCLUSIONS: Between 2005 and 2015, the amounts of opioids prescribed for postoperative pain increased dramatically, and receipt of larger volume of opioids was associated with increased risk of long-term opioid therapy.