Medication Safety Events After Acute Myocardial Infarction Among Veterans Treated at VA Versus Non-VA Hospitals.

INTRODUCTION: Fragmentation of health care across systems can contribute to mistakes in prescribing and filling medications among patients treated for myocardial infarction (MI). We sought to compare omissions, duplications, and delays in outpatient medications used for secondary prevention among veterans treated for MI at Veterans Affairs (VA) versus non-VA hospitals. METHODS: We utilized national VA and Centers for Medicare and Medicaid Services data (2012-2018) to identify veterans 65 years or older hospitalized for MI and measured the use of outpatient medications for secondary prevention in the 30 days after MI among those treated at VA versus non-VA hospitals. RESULTS: A total of 118,456 veterans experiencing MI were included; of which 102,209 were hospitalized at non-VA hospitals. An omission in any medication class occurred more frequently among veterans treated at non-VA versus VA hospitals (82.8% vs 67.8%, P < 0.001). In multivariable modeling, the odds of omissions in any medication class were higher among those treated at non-VA versus VA hospitals (odds ratio: 3.04; 95% CI: 2.88-3.20). Duplications occurred more frequently in veterans treated at non-VA versus VA hospitals: 1.9% versus 1.6% had 1 or more for non-VA versus VA hospitals ( P < 0.001). Veterans treated at non-VA hospitals were more likely to have delays of 3 days or more in prescription fills after hospital discharge (88.4% vs 70.6% across all classes, P < 0.001). CONCLUSIONS: Omissions, duplications, and delays in outpatient prescribing of secondary prevention medications were more common among 118,456 veterans treated at non-VA versus VA hospitals for MI. Interventions aimed at improving care transitions and optimizing medication use among veterans treated at non-VA hospitals should be implemented.

Who tests for lead and why? A 10-year analysis of blood lead screening, follow-up and CNS outcomes in a statewide US healthcare system.

OBJECTIVES: This study aims to determine (1) which providers in US healthcare systems order lead tests, why and at what frequency and (2) whether current patient population lead levels are predictive of clinical outcomes. METHODS: Retrospective medical record study of all blood lead tests in the Medical University of South Carolina healthcare system 2012-2016 and consequent evidence of central nervous system (CNS)-related disease across a potential 10-year window (2012-2022). RESULTS: Across 4 years, 9726 lead tests resulted for 7181 patients (49.0% female; 0-94 years), representing 0.2% of the hospital population. Most tests were for young (76.6%≤age 3) and non-Hispanic black (47.2%) and Hispanic (26.7%) patients. A wide variety of providers ordered tests; however, most were ordered by paediatrics, psychiatry, internal medicine and neurology. Lead levels ranged from ≤2.0 µg/dL (80.8%) to ≥10 µg/dL (0.8%; max 36 µg/dL). 201 children (3.1%) had initial lead levels over the reference value for case management at the time (5.0 µg/dL). Many high level children did not receive follow-up testing in the system (36.3%) and those that did often failed to see levels fall below 5.0 µg/dL (80.1%). Non-Hispanic black and Hispanic patients were more likely to see lead levels stay high or go up over time. Over follow-up, children with high lead levels were more likely to receive new attention-deficit/hyperactivity disorder and conduct disorder diagnoses and new psychiatric medications. No significant associations were found between lead test results and new CNS diagnoses or medications among adults. CONCLUSIONS: Hospital lead testing covers a small portion of patients but includes a wide range of ages, presentations and provider specialities. Lack of lead decline among many paediatric patients suggests there is room to improve provider guidance around when to test and follow-up.

Results of a multicenter cluster-randomized controlled clinical trial testing the effectiveness of a bioinformatics-enabled pharmacist intervention in transplant recipients.

An ambulatory medication safety dashboard was developed to identify missing labs, concerning labs, drug interactions, nonadherence, and transitions in care. This system was tested in a 2-year, prospective, cluster-randomized, controlled multicenter study. Pharmacists at 5 intervention sites used the dashboard to address medication safety issues, compared with usual care provided at 5 control sites. A total of 2196 transplant events were included (1300 intervention vs 896 control). During the 2-year study, the intervention arm had a 11.3% (95% confidence interval, 7.1%-15.5%) absolute risk reduction of having ≥1 emergency department (ED) visit (44.2% vs 55.5%, respectively; P < .001, respectively) and a 12.3% (95% confidence interval, 8.2%-16.4%) absolute risk reduction of having ≥1 hospitalization (30.1% vs 42.4%, respectively; P < .001). In those with ≥1 event, the median ED visit rate (2 [interquartile range (IQR) 1, 5] vs 2 [IQR 1, 4]; P = .510) and hospitalization rate (2 [IQR 1, 3] vs 2 [IQR 1, 3]; P = .380) were similar. Treatment effect varied by comorbidity burden, previous ED visits or hospitalizations, and heart or lung recipients. A bioinformatics dashboard-enabled, pharmacist-led intervention reduced the risk of having at least one ED visit or hospitalization, predominantly demonstrated in lower risk patients.

Airflow limitation and mortality during cancer screening in the National Lung Screening Trial: why quantifying airflow limitation matters.

IMPORTANCE: Current eligibility criteria for lung cancer (LC) screening are derived from randomised controlled trials and primarily based on age and smoking history. However, the individual benefits of screening are highly variable and potentially attenuated by co-morbidities such as advanced airflow limitation (AL). OBJECTIVE: To examine the relationship between the presence and severity of AL and screening outcomes. METHODS: This was a secondary analysis of 18 463 high-risk smokers, a substudy from the National Lung Screening Trial, who underwent pre-bronchodilator spirometry at baseline and median follow-up of 6.1 years. We used descriptive statistics and a competing risk proportional hazards model to examine differences in screening outcomes by chronic obstructive pulmonary disease severity group. RESULTS: The risk of developing LC increased with worsening AL (effect size=0.34, p<0.0001), as did the risk of dying of LC (effect size=0.35, p<0.0001). While those with severe AL (Global Initiative for Obstructive Lung Disease, GOLD grade 3-4) had the highest risk of LC and the highest LC mortality, they also had fewer adenocarcinomas (effect size=-0.20, p=0.008) and a lower surgery rate (effect size=-0.16, p=0.014) despite comparable staging, and greater non-LC mortality relative to LC mortality (effect size=0.30, p<0.0001). In participants with no AL, screening with CT was associated with a significant reduction in LC deaths relative to chest X-ray (30.3%, 95% CI 4.5% to 49.2%, p<0.05). The clinically relevant but attenuated reduction in those with AL (18.5%, 95% CI -8.4% to 38.7%, p>0.05) could be attributed to GOLD 3-4, where no appreciable mortality reduction was observed. CONCLUSION: Despite a greater risk of LC, severe AL was not associated with any apparent reduction in LC mortality following screening.

Diffusion MRI detects early brain microstructure abnormalities in 2-month-old 3×Tg-AD mice.

The 3×Tg-AD mouse is one of the most studied animal models of Alzheimer's disease (AD), and develops both amyloid beta deposits and neurofibrillary tangles in a temporal and spatial pattern that is similar to human AD pathology. Additionally, abnormal myelination patterns with changes in oligodendrocyte and myelin marker expression are reported to be an early pathological feature in this model. Only few diffusion MRI (dMRI) studies have investigated white matter abnormalities in 3×Tg-AD mice, with inconsistent results. Thus, the goal of this study was to investigate the sensitivity of dMRI to capture brain microstructural alterations in 2-month-old 3×Tg-AD mice. In the fimbria, the fractional anisotropy (FA), kurtosis fractional anisotropy (KFA), and radial kurtosis (K┴ ) were found to be significantly lower in 3×Tg-AD mice than in controls, while the mean diffusivity (MD) and radial diffusivity (D┴ ) were found to be elevated. In the fornix, K┴ was lower for 3×Tg-AD mice; in the dorsal hippocampus MD and D┴ were elevated, as were FA, MD, and D┴ in the ventral hippocampus. These results indicate, for the first time, dMRI changes associated with myelin abnormalities in young 3×Tg-AD mice, before they develop AD pathology. Morphological quantification of myelin basic protein immunoreactivity in the fimbria was significantly lower in the 3×Tg-AD mice compared with the age-matched controls. Our results demonstrate that dMRI is able to detect widespread, significant early brain morphological abnormalities in 2-month-old 3×Tg-AD mice.

Joint effect of race/ethnicity or location of residence and sex on low density lipoprotein-cholesterol among veterans with type 2 diabetes: a 10-year retrospective cohort study.

BACKGROUND: Cardiovascular (CV) disease is the leading cause of death among United States women. Rural residence and ethnic-minority status are individually associated with increased CV mortality. Managing dyslipidemia is important in the prevention of CV mortality. However, the impact of race/ethnicity and location of residence on sex differences in dyslipidemia management is not well understood. Therefore, we sought to understand the joint effects of race/ethnicity and location of residence on lipid management differences between veteran men and women with type 2 diabetes (T2D). METHODS: Veterans Health Administration and Centers for Medicare and Medicaid Services data were used to perform a longitudinal cohort study of veterans with T2D (2007-2016). Mixed effects logistic regression with a random intercept was used to model the association between sex and low-density lipoprotein (LDL) > 100 mg/dL and its interaction with race/ethnicity and location of residence after adjusting for all measured covariates. RESULTS: When female sex and rural location of residence were both present, they were associated with an antagonistic harmful effect on LDL. Similar antagonistic harmful effects on LDL were observed when the joint effect of female sex and several minority race/ethnicity groups were evaluated. After adjusting for measured covariates, the odds of LDL > 100 mg/dL were higher for urban women (OR = 2.66, 95%CI 2.48-2.85) and rural women (OR = 3.26, 95%CI 2.94-3.62), compared to urban men. The odds of LDL > 100 mg/dL was the highest among non-Hispanic Black (NHB) women (OR = 5.38, 95%CI 4.45-6.51) followed by non-Hispanic White (NHW) women (OR = 2.59, 95%CI 2.44-2.77), and Hispanic women (OR = 2.56, 95%CI 1.79-3.66). CONCLUSION: Antagonistic harmful effects on LDL were observed when both female sex and rural location of residence were present. These antagonistic effects on LDL were also present when evaluating the joint effect of female sex and several minority race/ethnicity groups. Disparities were most pronounced in NHB and rural women, who had 5.4 and 3.3 times the odds of elevated LDL versus NHW and urban men after adjusting for important covariates. These striking effect sizes in a population at high cardiovascular risk (i.e., older with T2D) suggest interventions aimed at improving lipid management are needed for individuals falling into one or more groups known to face health disparities.

Rates of substance use disorder treatment seeking visits after emergency department-initiated buprenorphine.

BACKGROUND: Emergency department-initiated buprenorphine (EDIB) programs have been shown to improve treatment outcomes for patients with opioid use disorders (OUD); however, little is known about how EDIB implementation impacts the patient census at participating hospitals. OBJECTIVES: To determine if implementation of an EDIB program was associated with changes in the number of patients presenting to the ED seeking treatment for substance use disorder (SUD). METHODS: We conducted a retrospective evaluation at a single academic ED that began offering EDIB in December 2017. Data span the period of December 2016 to April 2019, All ED visits with a chief complaint of addiction problem, detoxification, drug/alcohol assessment, drug problem, or withdrawal charted by nursing at the time of triage were eligible for inclusion. Charts were reviewed to determine: (1) treatment status and (2) substance(s) for which the patient was seeking treatment. An interrupted time series analysis was used to compare the pre- and post-EDIB rates for all-substance, as well as opioid-specific, treatment-seeking visits. RESULTS: For all-substance visits, the predicted level change in the treatment-seeking rate after EDIB was implemented was positive but not significant (0.000497, p = 0.53); the trend change after EDIB was also not significant (-0.00004, p = 0.73). For visits involving opioids, the predicted level change was (0.000638, p = 0.21); and the trend change was (0.000047, p = 0.49). CONCLUSION: Implementation of an EDIB program was not associated with increased rates of presentation by patients requesting treatment for a substance use disorder in the participating ED setting.

Approaches for missing covariate data in logistic regression with MNAR sensitivity analyses.

Data with missing covariate values but fully observed binary outcomes are an important subset of the missing data challenge. Common approaches are complete case analysis (CCA) and multiple imputation (MI). While CCA relies on missing completely at random (MCAR), MI usually relies on a missing at random (MAR) assumption to produce unbiased results. For MI involving logistic regression models, it is also important to consider several missing not at random (MNAR) conditions under which CCA is asymptotically unbiased and, as we show, MI is also valid in some cases. We use a data application and simulation study to compare the performance of several machine learning and parametric MI methods under a fully conditional specification framework (MI-FCS). Our simulation includes five scenarios involving MCAR, MAR, and MNAR under predictable and nonpredictable conditions, where "predictable" indicates missingness is not associated with the outcome. We build on previous results in the literature to show MI and CCA can both produce unbiased results under more conditions than some analysts may realize. When both approaches were valid, we found that MI-FCS was at least as good as CCA in terms of estimated bias and coverage, and was superior when missingness involved a categorical covariate. We also demonstrate how MNAR sensitivity analysis can build confidence that unbiased results were obtained, including under MNAR-predictable, when CCA and MI are both valid. Since the missingness mechanism cannot be identified from observed data, investigators should compare results from MI and CCA when both are plausibly valid, followed by MNAR sensitivity analysis.

The Impact of Dual Health Care System Use for Obtaining Prescription Medications on Nonadherence in Veterans With Type 2 Diabetes.

BACKGROUND: Dual health system use may provide increased access to physicians, medications, and other health care resources but may also increase the complexity and coordination of medication regimens. Thus, it is important to elucidate the impact of dual use on medication adherence. OBJECTIVE: The objective of this study was to evaluate the impact on medication adherence for veterans with dual health care system use (VA and Medicare) when obtaining prescription antihyperglycemic medications to treat diabetes. METHODS: This was a longitudinal cohort study using VA and Medicare data from 2006 to 2010. Medication adherence was estimated by calculating annualized drug class-level proportion of days covered (PDC), where PDC >80% was considered adherent. Generalized linear models were used for estimations, accounting for correlation over time. RESULTS: In total, 254 267 veterans with diabetes were included, with 71 057 (27.9%) defined as pharmacy system dual users. Mean age was 77.5 years, and nearly all had multiple comorbidities (mean count 10.2). During follow-up, 75% of VA-only users were deemed adherent to diabetes prescriptions, compared with 63% of dual users. In adjusted models, dual prescription benefit use from VA/Medicare was associated with 39% lower odds of medication adherence (odds ratio [OR] = 0.61; 95% CI = 0.60-0.61). Medication adherence significantly worsened with each additional diabetes medication (OR = 0.65; 95% CI = 0.64-0.65) and significantly decreased over time (OR = 0.95 per year; 95% CI = 0.95-0.96). Conclusion and Relevance: These data suggest that veterans utilizing VA and Medicare to obtain diabetes prescriptions are significantly less likely to be adherent.

Creating a 13-year National Longitudinal Cohort of veterans with chronic kidney disease.

BACKGROUND: The development of large-scale chronic kidney disease (CKD) cohorts within the Veterans Affairs (VA) system has been limited by several factors, including the high proportion of missing race data etc. The goal of this study is to address the limitations of prior studies by creating a large cohort utilizing robust KDIGO recommendations for identifying and staging CKD. METHODS: Multiple patient and administrative files from the Veterans Health Administration (VHA) National Patient Care were linked to create a national cohort of Veterans with chronic kidney disease (CKD) between January 2000 - December 2012; patients identified during this period were followed until 2015. CKD was defined for stages 1 through 5 if markers of kidney damage, specifically proteinuria, were present for at least 3 months. Estimated glomerular filtration rate (eGFR) values were calculated based on serum creatinine levels and the patient's age, gender, and race using both the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas. RESULTS: About 50 million observations were collected that supported a CKD diagnosis during the study period; these observations corresponded to 3,051,001 unique veterans; 80.9% were non-Hispanic white (NHW), 13.4% were non-Hispanic black (NHB), 3.6% were Hispanic, and 2.0% were in other groups. The mean age 76.7, about 97% were male and 50.2% died prior to January 2016. Among those with stage 3, 12.3% progressed to stage 4, 21.6% of those with stage 4 progressed to stage 5. We found that eGFR values calculated from serum creatinine levels identified about 98% of all patients, while about 11.4% of patients could be identified through ICD-9 codes; only 6.4% could be identified through both sources. CONCLUSION: This 13-year national cohort provides an important resource for answering numerous research questions in the future such as racial/ethnic disparities questions, tracking health service utilization, medication adherence, cost and health outcomes in veterans with CKD.

Conscious Perception of Facial Asymmetry in a Unilateral Cleft Lip Model.

OBJECTIVE: Lip asymmetry after a unilateral cleft lip repair can be perceived as an unsatisfactory result. The objective of this study is to determine the degree of upper lip asymmetry and/or nasal alar hooding required for recognition of asymmetry in a simulated model of unilateral cleft lip. DESIGN: A model of unilateral cleft lip was created using digital morphing software to simulate asymmetries in vermilion height and nasal hooding in photographs of children. Volunteers were shown photographs for different time intervals and with varying degrees of asymmetry. Ability to detect facial asymmetry was recorded and analyzed. SETTING: This study was conducted by surveying layperson volunteers in public community settings. PARTICIPANTS: 108 layperson volunteers were randomly surveyed. MAIN OUTCOME MEASURES: The primary outcome measure was a reported lip or nose asymmetry by the volunteers. Proportions and corresponding 95% confidence intervals were obtained to estimate the probability of reporting an asymmetry at 3- and 10-second intervals. RESULTS: After 3- and 10-second exposure, labial asymmetry was perceived by ≥50% of subjects at 2 mm (62%, P = .001) and 1 mm (89%, P < .0001), respectively. Nasal asymmetry was detected by <50% of subjects at 3 seconds, but ≥50% perceived a 3-mm alteration at 10 seconds (64%, P < .0001). Photographs with combined nasal and labial modification did not lower the threshold for asymmetry perception compared to either deformity alone. CONCLUSIONS: This study is the first to determine a predictable millimeter threshold for perceived asymmetry in cleft lip deformity using a digital model.

Trends in Veteran hospitalizations and associated readmissions and emergency department visits during the MISSION Act era.

OBJECTIVE: To examine changes in hospitalization trends and healthcare utilization among Veterans following Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act implementation. DATA SOURCES AND STUDY SETTING: VA Corporate Data Warehouse and Centers for Medicare and Medicaid Services datasets. STUDY DESIGN: Retrospective cohort study to compare 7- and 30-day rates for unplanned readmission and emergency department visits following index hospital stays based on payor type (VHA facility stay, VA-funded stay in community facility [CC], or Medicare-funded community stay [CMS]). Segmented regression models were used to compare payors and estimate changes in outcome levels and slopes following MISSION Act implementation. DATA COLLECTION/EXTRACTION METHODS: Veterans with active VA primary care utilization and ≥1 acute hospitalization between January 1, 2016 and December 31, 2021. PRINCIPAL FINDINGS: Monthly index stays increased for all payors until MISSION Act implementation, when VHA and CMS admissions declined while CC admissions accelerated and overtook VHA admissions. In December 2021, CC admissions accounted for 54% of index admissions, up from 25% in January 2016. From adjusted models, just prior to implementation (May 2019), Veterans with CC admissions had 47% greater risk of 7-day readmission (risk ratio [RR]: 1.47, 95% confidence interval [CI]: 1.43, 1.51) and 20% greater risk of 30-day readmission (RR: 1.20, 95% CI: 1.19, 1.22) compared with those with VHA admissions; both effects persisted post-implementation. Pre-implementation CC admissions were also associated with higher 7- and 30-day ED visits, but both risks were substantially lower by study termination (RR: 0.90, 95% CI: 0.88, 0.91) and (RR: 0.89, 95% CI: 0.87, 0.90), respectively. CONCLUSIONS: MISSION Act implementation was associated with substantial shifts in treatment site and federal payor for Veteran hospitalizations. Post-implementation readmission risk was estimated to be higher for those with CC and CMS index admissions, while post-implementation risk of ED utilization following CC admissions was estimated to be lower compared with VHA index admissions. Reasons for this divergence require further investigation.

Evaluation of a non-pharmacological interdisciplinary pain rehabilitation and functional restoration program for chronic pain in veterans.

OBJECTIVE: To conduct a quality improvement evaluation of the Empower Veterans Program (EVP), an interdisciplinary pain rehabilitation/functional restoration program option for functional restoration for high-impact chronic pain, offered in a large metro-area Veterans Health Administration (VHA) system. DATA SOURCES: VHA Corporate Data Warehouse electronic medical record data for patients treated by EVP between 2015 and 2019. EVALUATION DESIGN: This retrospective design first compared EVP patients considered engaged or not engaged in completing treatment in terms of demographic characteristics and post-treatment changes in clinical measures related to opioid use and mental health. We then compared mortality risk between matched groups of treated and untreated patients with chronic pain and concurrent opioid prescriptions using propensity score matching and Cox proportional hazards methods. "Treated" in the matched groups was defined as any level of EVP participation (i.e., both engaged and not engaged). DATA COLLECTION/EXTRACTION METHODS: We first identified 1053 EVP patients with 1 year of pre-and post-treatment follow-time and determined their engagement level. From those with chronic pain and prescription opioids, we matched 237 EVP patients to 375 untreated patients. PRINCIPAL FINDINGS: Engaged patients (57.4% of treated patients), were somewhat older than the non-engaged (mean age 57.1 vs. 53.7, Cohen's D = 0.30), and achieved lower mean PHQ9 depression scores in the post-treatment year (9.2 vs. 10.6, Cohen's D = 0.20). Participation in EVP was associated with a 65% lower mortality risk among Veterans with chronic pain and opioid use when compared to the untreated patients: (HR: 0.35, 95% CI: 0.17, 0.75). CONCLUSIONS: EVP was associated with a large reduction in mortality risk for Veterans with both chronic pain and opioid use. This result could inform the decision process in a VA station or region when considering providing or expanding access to an interdisciplinary rehabilitation/functional restoration program for chronic pain.

Impact of Race and Ethnicity on Severe Hypoglycemia Associated with Sulfonylurea Use for Type 2 Diabetes among Veterans.

Sulfonylureas are associated with hypoglycemia. Whether a racial/ethnic disparity in this safety outcome exists is unknown. We sought to assess the impact of race/ethnicity on severe hypoglycemia associated with sulfonylurea use for type 2 diabetes (T2D). Using Veterans Affairs and Medicare data, Veterans initially receiving metformin monotherapy for T2D between 2004 and 2006 were identified. Sulfonylurea use (either alone or via the addition of a prescription for a sulfonylurea to metformin) was captured and compared to remaining on metformin alone during the follow-up period (2007-2016). Hazard ratios (HR) and 95% confidence intervals (CI) from longitudinal competing risk Cox models were used to measure the association between sulfonylurea use and severe hypoglycemia defined as hospitalization for hypoglycemia. A total of 113,668 Veterans with T2D were included. A higher risk of severe hypoglycemia was associated with the receipt of sulfonylurea prescriptions versus remaining on metformin alone across all groups. The effect was largest among Hispanic Veterans (HR: 7.59, 95%CI:4.32-13.33), followed by Veterans in the other race/ethnicity cohort (HR: 4.57, 95%CI:2.50-8.36) and Non-Hispanic Black Veterans (HR: 3.67, 95%CI:2.78-4.85). The effect was smallest among Non-Hispanic White Veterans (HR: 3.11, 95%CI:2.77-3.48). In conclusion, a higher risk of severe hypoglycemia associated with sulfonylurea prescriptions was observed across all analyses. The relationship was most pronounced for Hispanic Veterans, who had nearly 8 times the risk of severe hypoglycemia with sulfonylureas versus remaining on metformin alone.

Opioid Use Patterns in a Statewide Adult Medicaid Population Undergoing Elective Lumbar Spine Surgery.

STUDY DESIGN: Retrospective administrative database review. OBJECTIVE: Analyze patterns of opioid use in patients undergoing lumbar surgery and determine associated risk factors in a Medicaid population. SUMMARY OF BACKGROUND DATA: Opioid use in patients undergoing surgery for degenerative lumbar spine conditions is prevalent and impacts outcomes. There is limited information defining the scope of this problem in Medicaid patients. MATERIALS AND METHODS: Longitudinal cohort study of adult South Carolina (SC) Medicaid patients undergoing lumbar surgery from 2014 to 2017. All patients had continuous SC Medicaid coverage for 15 consecutive months, including six months before and nine months following surgery. The primary outcome was a longitudinal assessment of postoperative opioid use to determine trajectories and group-based membership using latent modeling. Univariate and multivariable modeling was conducted to assess risk factors for group-based trajectory modeling and chronic opioid use (COU). RESULTS: A total of 1455 surgeries met inclusion criteria. Group-based trajectory model demonstrated patients fit into five groups; very low use (23.4%), rapid wean following surgery (18.8%), increasing use following surgery (12.9%), slow wean following surgery (12.6%) and sustained high use (32.2%). Variables predicting membership in high opioid use included preoperative opioid use, younger age, longer length of stay, concomitant medications, and readmissions. More than three quarter of patients were deemed COUs (76.4%). On bivariate analysis, patients with degenerative disk disease were more likely to be COUs (24.8% vs. 18.6%; P =0.0168), more likely to take opioids before surgery (88.5% vs. 61.9%; P <0.001) and received higher amounts of opioids during the 30 days following surgery (mean morphine milligram equivalents 59.6 vs. 25.1; P <0.001). CONCLUSIONS: Most SC Medicaid patients undergoing lumbar elective lumbar spine surgery were using opioids preoperatively and continued long-term use postoperatively at a higher rate than previously reported databases. Preoperative and perioperative intake, degenerative disk disease, multiple prescribers, depression, and concomitant medications were significant risk factors.

Factors Associated With Smoking Cessation Attempts in Lung Cancer Screening: A Secondary Analysis of the National Lung Screening Trial.

BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality in the United States. The National Lung Screening Trial (NLST) demonstrated a 20% reduction in lung cancer mortality resulting from lung cancer screening (LCS) with an additive reduction from smoking abstinence. However, successful smoking cessation within LCS is variable. RESEARCH QUESTION: What patient and treatment factors are associated with attempts to quit smoking among those screened for lung cancer? STUDY DESIGN AND METHODS: In a secondary analysis of the American College of Radiology Imaging Network arm of the NLST, patient demographics, patient smoking behaviors, and tobacco treatment variables were stratified by patient smoking status. The Cox proportional hazards ratio was used to evaluate each variable's effect on attempting to quit smoking. RESULTS: Seven thousand three hundred sixty-nine patients were smoking actively at enrollment in the NLST. Of the patients who reported they were smoking, 73.4% did not receive any pharmacologic tobacco treatment. More patients who attempted to quit received pharmacologic tobacco treatment than those who continued to smoke: (nicotine replacement therapy [NRT], 18.0% vs 12.4% [P < .01]; bupropion, 7.9% vs 6.9% [P = .02]; both NRT and bupropion, 5.6% vs 3.9% [P < .01]). Stable users were more likely to be women (47.8% vs 43.8%; P < .01), to be African American (8.2% vs 6.3%; P = .007), to be unmarried (43.2% vs 36.9% [P < .01]), and to have less than a college education (47.7% vs 42.3%; P < .01). Patients with high dependence who received dual therapy with bupropion and NRT showed the highest likelihood of quit attempt (hazard ratio, 2.07; 95% CI, 1.75-2.44). INTERPRETATION: In this analysis, only one-quarter of patients who underwent LCS and who smoked were treated with pharmacologic therapy, which is associated with increased likelihood of attempting to quit. Certain characteristics are associated with difficulty with attempting to quit smoking. Those with high nicotine dependence benefitted most from dual pharmacologic therapy.

The effectiveness of a noninterruptive alert to increase prescription of take-home naloxone in emergency departments.

OBJECTIVE: Opioid-related overdose (OD) deaths continue to increase. Take-home naloxone (THN), after treatment for an OD in an emergency department (ED), is a recommended but under-utilized practice. To promote THN prescription, we developed a noninterruptive decision support intervention that combined a detailed OD documentation template with a reminder to use the template that is automatically inserted into a provider's note by decision rules. We studied the impact of the combined intervention on THN prescribing in a longitudinal observational study. METHODS: ED encounters involving an OD were reviewed before and after implementation of the reminder embedded in the physicians' note to use an advanced OD documentation template for changes in: (1) use of the template and (2) prescription of THN. Chi square tests and interrupted time series analyses were used to assess the impact. Usability and satisfaction were measured using the System Usability Scale (SUS) and the Net Promoter Score. RESULTS: In 736 OD cases defined by International Classification of Disease version 10 diagnosis codes (247 prereminder and 489 postreminder), the documentation template was used in 0.0% and 21.3%, respectively (P < .0001). The sensitivity and specificity of the reminder for OD cases were 95.9% and 99.8%, respectively. Use of the documentation template led to twice the rate of prescribing of THN (25.7% vs 50.0%, P < .001). Of 19 providers responding to the survey, 74% of SUS responses were in the good-to-excellent range and 53% of providers were Net Promoters. CONCLUSIONS: A noninterruptive decision support intervention was associated with higher THN prescribing in a pre-post study across a multiinstitution health system.

Sulfonylureas as second line therapy for type 2 diabetes among veterans: Results from a National Longitudinal Cohort Study.

AIMS: To assess if switching to or adding sulfonylureas increases major adverse cardiovascular events (MACE) or severe hypoglycemia versus remaining on metformin alone. MATERIALS AND METHODS: This was a retrospective, longitudinal cohort utilizing United States Veterans Health Administration and Medicare data. Veterans with type 2 diabetes on metformin monotherapy between 2004 and 2006 were identified. Follow-up occurred through 2016. Those treated with either metformin plus a second-generation sulfonylurea (N = 45,305) or converted from metformin to a second-generation sulfonylurea (N = 2813) were compared to those receiving metformin monotherapy (N = 65,550). Hazard ratios (HR) and 95%CI from longitudinal competing risk Cox models were used to measure the association between sulfonylureas and outcomes. RESULTS: Switching to or adding a sulfonylurea to metformin was associated with 3 times the risk of severe hypoglycemia versus metformin monotherapy (HR:3.44, 95% CI: 3.06,3.85 and HR: 3.08, 95% CI: 2.77,3.42, respectively). Switching to or adding a sulfonylurea to metformin was associated with a 7-19% higher risk of MACE versus metformin monotherapy (HR: 1.07, 95% CI: 1.00,1.14 and HR: 1.19, 95% CI: 1.13,1.25, respectively). CONCLUSIONS: Switching to and adding second-generation sulfonylureas was associated an increase in severe hypoglycemia and MACE versus remaining on metformin alone. In an era where guidelines recommend diabetes therapies based on compelling indications, safety outcomes should be a key consideration when selecting therapy.

Surgical prescription opioid trajectories among state Medicaid enrollees.

OBJECTIVE: The objective of this study was to evaluate opioid use trajectories among a sample of 10,138 Medicaid patients receiving one of six index surgeries: lumbar spine, total knee arthroplasty, cholecystectomy, appendectomy, colon resection, and tonsillectomy. DESIGN: Retrospective cohort. SETTING: Administrative claims data. PATIENTS AND PARTICIPANTS: Patients, aged 13 years and older, with 15-month continuous Medicaid eligibility surrounding index surgery, were selected from single-state Medicaid medical and pharmacy claims data for surgeries performed between 2014 and 2017. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Baseline comorbidities and presurgery opioid use were assessed in the 6 months prior to admission, and patients' opioid use was followed for 9 months post-discharge. Generalized linear model with log link and Poisson distribution was used to determine risk of chronic opioid use for all risk factors. Group-based trajectory models identified groups of patients with similar opioid use trajectories over the 15-month study period. RESULTS: More than one in three (37.7 percent) patients were post-surgery chronic opioid users, defined as the dichotomous outcome of filling an opioid prescription 90 or more days after surgery. Key variables associated with chronic post-surgery opioid use include presurgery opioid use, 30-day post-surgery opioid use, and comorbidities. Latent trajectory modeling grouped patients into six distinct opioid use trajectories. Associates of trajectory group membership are reported. CONCLUSIONS: Findings support the importance of surgeons setting realistic patient expectations for post-surgical opioid use, as well as the importance of coordination of post-surgical care among patients failing to fully taper off opioids within 1-3 months of surgery.

Enhanced phenotypes for identifying opioid overdose in emergency department visit electronic health record data.

Background: Accurate identification of opioid overdose (OOD) cases in electronic healthcare record (EHR) data is an important element in surveillance, empirical research, and clinical intervention. We sought to improve existing OOD electronic phenotypes by incorporating new data types beyond diagnostic codes and by applying several statistical and machine learning methods. Materials and Methods: We developed an EHR dataset of emergency department visits involving OOD cases or patients considered at risk for an OOD and ascertained true OOD status through manual chart reviews. We developed and validated prediction models using Random Forest, Extreme Gradient Boost, and Elastic Net models that incorporated 717 features involving primary and second diagnoses, chief complaints, medications prescribed, vital signs, laboratory results, and procedural codes. We also developed models limited to single data types. Results: A total of 1718 records involving 1485 patients were manually reviewed; 541 (36.4%) patients had one or more OOD. Prediction performance was similar for all models; sensitivity varied from 94% to 97%; and area under the receiver operating characteristic curve (AUC) was 98% for all methods. The primary diagnosis and chief complaint were the most important contributors to AUC performance; primary diagnoses and medication class contributed most to sensitivity; chief complaint, primary diagnosis, and vital signs were most important for specificity. Models limited to decision support data types available in real time demonstrated robust prediction performance. Conclusions: Substantial prediction performance improvements were demonstrated for identifying OODs in EHR data. Our e-phenotypes could be applied in surveillance, retrospective empirical applications, or clinical decision support systems.