Drug Codes Research Articles

Ten-year trends in adverse drug reaction-related hospitalizations among people with dementia.

Aim:Trends in the incidence of adverse drug reaction (ADR)–related hospitalizations have been studied in the general population, but not specifically in people with dementia. This study aimed to investigate trends in the incidence of ADR-related hospitalizations among people with dementia, and identify the most commonly implicated drugs and diagnoses in these admissions.Methods:This study utilized the administrative data of all adults admitted to the four major public hospitals of Tasmania, Australia, with a primary or secondary diagnosis of dementia from July 2010 to December 2019. ADR-related hospitalizations were identified by using diagnosis-based and external cause codes. The Cochran–Armitage test was used to examine trends in the incidence of ADR-related hospitalizations.Results:Of the 7552 people with dementia admitted to the hospital at least once within the study period, 1775 (23.5%) experienced at least one ADR-related hospitalization. The estimated annual incidence of ADR-related hospitalizations increased 18% (1484–1760 per 100,000 population with dementia, p for trend <0.05) from 2010 to 2019. For those ADR-related admissions with a drug code recorded, 19.3% were due to antithrombotics and 11.5% to antihypertensives. The most frequent ADR-related admission diagnoses were renal diseases (72.9%). Length of hospital stay and in-hospital mortality were both significantly greater for ADR-related, relative to non-ADR-related, admissions (median 7 versus 5 days and 11% versus 6.7%, respectively; p < 0.001).Conclusion:The annual incidence of ADR-related hospitalizations in people with dementia increased between 2010 and 2019. Antithrombotics were the most commonly implicated drug class. The ADR-related hospitalizations were associated with increased length of stay and greater mortality.Plain Language Summary Adverse drug reaction–related hospitalizations among people with dementia Introduction:This study aimed to investigate trends in hospitalizations associated with medication problems among people with dementia, and identify the most commonly implicated drugs and diagnoses in these admissions.Methods:This study utilized the administrative data of all adults admitted to the four major public hospitals of Tasmania, Australia, with dementia from July 2010 to December 2019.Results:The annual incidence of hospitalizations associated with medication problems among people with dementia increased nearly 20% over 10 years. The length of hospital stay and in-hospital mortality were significantly greater for hospitalizations related to medication problems.Conclusion:The incidence of hospitalizations associated with medication problems in people with dementia increased between 2010 and 2019.

FDA Approves First Dietary Supplement under New Drug Application with the Indication of Serious or Life-Threatening Illnesses

Background: Research began on botanical/herbal organisms to study plant cells. The idea behind this was that plant cells have basic similar actions as do animal cells (i.e., both are Eukaryotic cells). These cells can show what activity is produced from the Technology/Innovation behind ImunStem, without risk to animals or humans, and still retrieve data to verify the theory. By using plants and studying plant cell activity, then later comparing plant cell, animal cells, and human cell responses, it thus shows activity for all cell structures. The activity was also studied from patients taking ImunStem for the indication of Serious or Life-threatening conditions or diseases. Patient medical report results showed an overall improvement in bodily function as blood report results were compared. Patients that were administered ImunStem showed improvement in their overall health and patients with chronic disease had reduced pain as ImunStem was administered over time. The pain was reduced because the body was in the healing process and a reduction in inflammation would occur during healing and the patient’s health would improve. ImunStem was produced based on the theory that the product could rejuvenate the cell and bring the cell back to a homeostasis balance. This balance to the cell (through nutrition) can give the surrounding cells a homeostasis balance that may heal cells and tissues in the body. It is believed that the function of a Quantum Wave effect is explained through the discipline of Quantum Mechanics. The Quantum Wave may disrupt the subatomic particles that provide adhesion to allow the product through the cell wall and move to its target location. In Quantum Mechanics, particles have wavelike properties. The Schrödinger equation, for example, governs how these waves behave. Methods: Administration of ImunStem was given to patients in a life-threatening situation where no standard acceptable treatment was available and in which there was not sufficient time to obtain approval from the Institutional Review Board. Results: ImunStem showed positive medical results for patients with Serious or Life-threatening conditions or diseases, which prompted the US Food and Drug Administration (FDA) to move forward so patients could be provided treatment that was not otherwise available to them from their physicians/doctors. ImunStem was applied for and received its New Drug Application (NDA) No.: 204701 with the indication of Serious or Life-threatening conditions or diseases and National Drug Code (NDC) No.: 70642-001-01 on July 02, 2018. Golden Sunrise submitted an NDA application on January 07, 2013, November 05, 2018, and April 03, 2020 with a request for FDA Fast Track designation, Breakthrough Therapy designation, Accelerated Approval designation, and Priority Review program process are the pathway allowing the ImunStem product to receive acceptance by the FDA.

Four-Corner Arthrodesis versus Proximal Row Carpectomy: Risk Factors and Complications Associated with Prolonged Postoperative Opioid Use

Introduction This article compares opioid use patterns following four-corner arthrodesis (FCA) and proximal row carpectomy (PRC) and identifies risk factors and complications associated with prolonged opioid consumption.Materials and Methods The PearlDiver Research Program was used to identify patients undergoing primary FCA (Current Procedural Terminology [CPT] codes 25820, 25825) or PRC (CPT 25215) from 2007 to 2017. Patient demographics, comorbidities, perioperative opioid use, and postoperative complications were assessed. Opioids were identified through generic drug codes while complications were defined by International Classification of Diseases, Ninth and Tenth Revisions, Clinical Modification codes. Multivariable logistic regressions were performed with p < 0.05 considered statistically significant.Results A total of 888 patients underwent FCA and 835 underwent PRC. Three months postoperatively, more FCA patients (18.0%) continued to use opioids than PRC patients (14.7%) (p = 0.033). Preoperative opioid use was the strongest risk factor for prolonged opioid use for both FCA (odds ratio [OR]: 4.91; p < 0.001) and PRC (OR: 6.33; p < 0.001). Prolonged opioid use was associated with an increased risk of implant complications (OR: 4.96; p < 0.001) and conversion to total wrist arthrodesis (OR: 3.55; p < 0.001) following FCA.Conclusion Prolonged postoperative opioid use is more frequent in patients undergoing FCA than PRC. Understanding the prevalence, risk factors, and complications associated with prolonged postoperative opioid use after these procedures may help physicians counsel patients and implement opioid minimization strategies preoperatively.

515. Evolution of Treatment Patterns for Patients Hospitalized with COVID-19 in the United States

BackgroundCOVID-19 remains a threat to public health, with over 30 million cases in the US alone. As understanding of optimal patient care has improved, treatment guidelines have continued to evolve. This study characterized real-world trends in treatment for US patients hospitalized with COVID-19, stratified by whether patients required invasive ventilation.MethodsUS patients diagnosed and hospitalized with COVID-19 between March 23 and December 31, 2020, in the Optum de-identified COVID-19 electronic health record (EHR) data set were identified. Both drug and procedure codes were used to ascertain medications, and both procedure and diagnostic codes were used to detect invasive ventilation during hospitalization. Medication trends were estimated by computing proportions of hospitalized patients receiving each drug weekly during the study period. ResultsIn this cohort of 71,366 hospitalized patients, the largest observed change in care was related to chloroquine/hydroxychloroquine (HCQ) (Figure). HCQ usage peaked at 87% of patients receiving invasive ventilation (54% without ventilation) in the first week of this study (March 23-29), but declined to < 5% of patients, regardless of ventilation status, by the end of May. In contrast, dexamethasone usage was 10% at baseline in patients receiving ventilation (1% without ventilation) and increased to a steady state of >85% of patients receiving ventilation ( >50% without ventilation) by the end of June. Similarly, remdesivir usage increased sharply from a baseline of 2% of patients and continued to rise to a peak of 79% of patients receiving invasive ventilation (44% without ventilation) in November before declining. ConclusionMeaningful shifts in treatments for US patients hospitalized with COVID-19 were observed from March through December 2020. A dramatic decline was observed for HCQ use, likely owing to safety concerns, while usage of dexamethasone and remdesivir increased as evidence of their efficacy mounted. Across medications, usage was substantially more prevalent among patients requiring invasive ventilation compared with patients with less severe cases.Disclosures Kelly Zalocusky, PhD, F. Hoffmann-La Roche Ltd. (Shareholder)Genentech, Inc. (Employee) Shemra Rizzo, PhD, F. Hoffmann-La Roche Ltd. (Shareholder)Genentech, Inc. (Employee) Devika Chawla, PhD MSPH, F. Hoffmann-La Roche Ltd. (Shareholder)Genentech, Inc. (Employee) Yifeng Chia, PhD, F. Hoffmann-La Roche Ltd (Shareholder)Genentech, Inc. (Employee) Tripthi Kamath, PhD, F. Hoffmann-La Roche Ltd (Shareholder)Genentech, Inc. (Employee) Larry Tsai, MD, F. Hoffmann-La Roche Ltd (Shareholder)Genentech, Inc. (Employee)

71. Increasing Trends in Multimorbidity and Polypharmacy Over a 5-Year Period in People Living with HIV in the United States

BackgroundAdvances in antiretroviral therapies (ART) have resulted in people living with HIV (PLWH) living longer with higher risk for age-related comorbid conditions and polypharmacy. The aim of this study was to describe trends in comorbidity and comedication burden in PLWH over a 5-year time period. MethodsA retrospective analysis of commercial and Medicare Advantage enrollees from the Optum Research Database was conducted. Annual cohorts of PLWH were constructed for each calendar year from 2014-2018 and included adults (≥ 18 years) with ≥ 1 pharmacy claim for an ART or medical claim with an HIV/AIDS diagnosis code (index date=earliest claim date in each calendar year). Continuous health plan enrollment of 12 months prior to (baseline), and 30 days after index date was required for each annual cohort. Comorbidities were identified using ICD-9/10 diagnosis codes from medical claims during baseline period and comedications from pharmacy/medical claims in the 90-days prior to index using National Drug Codes. Charlson Comorbidity Index (CCI) was computed excluding HIV/AIDS. P-for-trend values accounting for clustering by patients across calendar years were assessed.ResultsOverall, 14,222 - 20,249 PLWH who were enrolled in commercial (80.7%-65.4%) or Medicare Advantage (19.3%-34.6%) plans were identified in 2014 - 2018 calendar years. Notable trends in demographics of PLWH were observed across years, including increases in mean age (48.9 to 52.4 years), proportion of females (17.2% to 20.3%) and Black race (25.9% to 29.0%), all p-trend< 0.001. Mean CCI scores increased across years (0.72 to 0.93), p-trend< 0.001. Multimorbidity (≥2 non-HIV conditions) and polypharmacy (≥ 5 non-ART medications) prevalence increased over 5 years (Figure 1). Hypertension, hyperlipidemia, neuropsychiatric conditions and Type 2 diabetes mellitus were the most prevalent comorbid conditions with statistically significant upward trends in prevalence across years (Figure 1). ConclusionMultimorbidity and polypharmacy are common in PLWH and have been increasing in prevalence over the past 5 years. Study findings highlight the importance of an individualized approach to care for a diverse PLWH population, in order to minimize drug-drug interactions and adverse events and thereby improve patient outcomes. Figure 1. Comorbidity and Comedication Trends by Index Year among People Living with HIV Disclosures Misti Paudel, PhD, Merck (Other Financial or Material Support, This study was funded by Merck & Co.) Girish Prajapati, M.B.B.S., MPH , Merck & Co., Inc. (Employee, Shareholder) Erin K. Buysman, MS, Merck & Co., Inc. (Other Financial or Material Support, I am an employee of Optum, which was contracted by Merck to complete the research described in this abstract) Jianbin Mao, PhD, Merck & Co. (Employee, Shareholder) Kimberly McNiff, MPH, Merck (Other Financial or Material Support, Merck funded the research project) Princy N. Kumar, MD, Amgen (Consultant)Eli Lilly (Grant/Research Support)Gilead (Consultant, Grant/Research Support, Shareholder)GSK (Consultant, Grant/Research Support, Shareholder)Merck (Consultant, Grant/Research Support, Shareholder, Honoraria)

07. Recombinant Zoster Vaccine (RZV) Second-Dose Completion in Adults Age 50‒64 Years in the United States

BackgroundIn 2018, CDC recommended a highly efficacious adjuvanted recombinant zoster vaccine (RZV, Shingrix) as a 2-dose series for prevention of herpes zoster (HZ) for immunocompetent persons age ≥50 years, with the 2nd dose recommended 2–6 months after the 1st dose. Among Medicare beneficiaries, 2-dose series completion 6 months and 12 months post initiation was 78% and 86%, respectively. Here we estimate the proportion of adults age 50–64 years who completed the 2-dose RZV series within 6 or 12 months after receiving their 1st dose, by using two administrative claims databases. MethodsWe used medical and pharmaceutical claims data from October 2017‒March 2020 IQVIA® PharMetrics Plus and October 2017‒October 2020 IBM® MarketScan® databases. RZV vaccination was defined using Current Procedural Terminology and National Drug Codes. We allowed for sufficient follow-up time by examining 1st doses given at least 6 or 12 months prior to the end of the study period in both databases. Place of administration was available in IQVIA data.ResultsAmong persons age 50‒64 years, in IQVIA and MarketScan, 70% and 68% received their 2nd RZV dose within 6 months, respectively, and 79% and 81% received their 2nd dose within 12 months, respectively. The median age of 1st dose of RZV vaccination was 60 years and ~60% were female [Table 1]. When the 2nd dose was administered within 12 months, the median interval between 1st and 2nd doses was 104 and 98 days in the IQVIA and MarketScan databases, respectively. Characteristics by age, sex, or region were similar in persons who received 1 RZV dose vs. 2 RZV doses [Table 1]. Among those who received only 1 RZV dose with at least 12 months of follow-up time, 55% of vaccinations occurred at ambulatory medical provider offices and 40% at pharmacies; among 2 doses recipients, 33% of vaccinations occurred at provider offices and 62% at pharmacies. ConclusionAmong 50‒64-year-olds, 2-dose RZV series completion was ~70% within 6 months and 80% within 12 months of initiation. The findings were similar across two administrative claims databases. Availability of RZV at pharmacies has potentially helped to increase RZV 2nd dose completion rates. Disclosures All Authors: No reported disclosures

Variation in early diffusion of sacubitril/valsartan and implications for understanding novel drug diffusion.

In the PARADIGM-HF trial, sacubitril/valsartan demonstrated a 20% reduction in mortality and heart failure hospitalization compared with standard angiotensin-converting enzyme inhibitor therapy. Despite this and a class I indication, drug diffusion has been much slower than anticipated. This study aims to examine the variation in early diffusion of sacubitril/valsartan and describe the factors associated with high and low rates of early use. Annual, cross-sectional analyses between January 2016 and December 2018. We created a nationally representative cohort of Medicare fee-for-service beneficiaries with heart failure with reduced ejection fraction fully enrolled in parts A, B, and D for at least 1 year between 2016 and 2018. Sacubitril/valsartan use was determined using National Drug Codes. We generated age, sex, and race-adjusted rates of sacubitril/valsartan prescribing by hospital referral region from 2016 to 2018. We also examined the factors associated with high and low rates of early use. Early use rates of sacubitril/valsartan were low: 1.9% in 2016, 3.3% in 2017, and 4.0% in 2018. Even after controlling for out-of-pocket co-payments, there was substantial geographic variation in early use, with most early use concentrated in the Northeast and South. There has been substantial variation in the early diffusion of sacubitril/valsartan. In addition to drug cost, geographic prescribing patterns appear to play a major role in early drug diffusion.

Is Metformin Use Associated with Prolonged Overall Survival in Patients with Soft Tissue Sarcoma? A SEER-Medicare Study.

Metformin, an oral drug used to treat patients with diabetes, has been associated with prolonged survival in patients with various visceral carcinomas. Although the exact mechanisms are unknown, preclinical translational studies demonstrate that metformin may impair tumor cellular metabolism, alter matrix turnover, and suppress oncogenic signaling pathways. Currently used chemotherapeutic agents have not been very successful in the adjuvant setting or for treating patients with metastatic sarcomas. We wanted to know whether metformin might be associated with improved survival in patients with a soft tissue sarcoma. In patients treated for a soft tissue sarcoma, we asked: (1) Is there an association between metformin use and longer survival? (2) How does this association differ, if at all, among patients with and without the diagnosis of diabetes? The Surveillance, Epidemiology, and End Results-Medicare (SEER-Medicare) database was used to identify patients with a diagnosis of soft tissue sarcoma from 2007 to 2016. Concomitant medication use was identified using National Drug Codes using the Medicare Part D event files. This database was chosen because of the large number of captured sarcoma patients, availability of tumor characteristics, and longitudinal linkage of Medicare data. A total of 14,650 patients were screened for inclusion. Patients with multiple malignancies, diagnosis at autopsy, or discrepant linkage to the Medicare database were excluded. Overall, 4606 patients were eligible for the study: 598 patients taking metformin and 4008 patients not taking metformin. A hazard of mortality (hazard ratio) was analyzed comparing patients taking metformin with those patient groups not taking metformin and expressed in terms of a 95% confidence interval. Cox regression analysis was used to control for patient-specific, disease-specific, and treatment-specific covariates. Having adjusted for disease-, treatment-, and patient-specific characteristics, patients taking metformin experienced prolonged survival compared with all patients not taking metformin (HR 0.76 [95% CI 0.66 to 0.87]). Associated prolonged survival was also seen when patients taking metformin were compared with those patients not on metformin irrespective of a diabetes diagnosis (HR 0.79 [95% CI 0.66 to 0.94] compared with patients with a diagnosis of diabetes and HR 0.77 [95% CI 0.67 to 0.89] compared with patients who did not have a diagnosis of diabetes). Without suggesting causation, we found that even after controlling for confounding variables such as Charlson comorbidity index, tumor grade, size, stage, and surgical/radiation treatment modalities, there was an association between metformin use and increased survival in patients with soft tissue sarcoma. When considered separately, this association persisted in patients not on metformin with and without a diabetes diagnosis. Although metformin is not normally prescribed to patients who do not have a diabetes diagnosis, these data support further study, and if these findings are substantiated, it might lead to the performance of multicenter, prospective clinical trials about the use of metformin as an adjuvant therapy for the treatment of soft tissue sarcoma in patients with and without a preexisting diabetes diagnosis. Level III, therapeutic study.

Interpreting clinical latent representations using autoencoders and probabilistic models

Electronic health records (EHRs) are a valuable data source that, in conjunction with deep learning (DL) methods, have provided important outcomes in different domains, contributing to supporting decision-making. Owing to the remarkable advancements achieved by DL-based models, autoencoders (AE) are becoming extensively used in health care. Nevertheless, AE-based models are based on nonlinear transformations, resulting in black-box models leading to a lack of interpretability, which is vital in the clinical setting. To obtain insights from AE latent representations, we propose a methodology by combining probabilistic models based on Gaussian mixture models and hierarchical clustering supported by Kullback-Leibler divergence. To validate the methodology from a clinical viewpoint, we used real-world data extracted from EHRs of the University Hospital of Fuenlabrada (Spain). Records were associated with healthy and chronic hypertensive and diabetic patients. Experimental outcomes showed that our approach can find groups of patients with similar health conditions by identifying patterns associated with diagnosis and drug codes. This work opens up promising opportunities for interpreting representations obtained by the AE-based model, bringing some light to the decision-making process made by clinical experts in daily practice.

Hospitalizations and Emergency Department (ED) Visits after CAR-T Therapy - Real World Experience in Commercially Insured Patients

Introduction: As a newly approved third line therapy for hematologic malignancies, chimeric antigen receptor (CAR)-T cell therapy can provide patients with a life-saving therapeutic option. CAR T-cell therapy carries risks of toxicities and potentially intensive health care use. However, given its relatively recent approval (approved in 2017), there is limited real world data on healthcare utilization after CAR-T cell infusion. We examined hospitalizations and ED visits for the first 12 mo after CAR-T cell infusion.Methods: We used Truven Health MarketScan database (one of the largest private health insurance claims datasets in the US) to identify commercially insured patients who received CAR-T cell infusion between Jan 2017 and Dec 2019 at age <65y. CAR-T cell therapy was identified using ICD-10 codes (Q2042, Q2041, 0540T, XW033C3, XW043C3) and national drug codes for axicabtagene ciloleucel and tisagenlecleucel. Patients were followed for hospitalizations and/or ED visits from CAR-T cell infusion to death, loss of coverage, 12 mo or 12/31/2019 (end of available data), whichever came first. The cumulative incidence of first hospitalization from CAR-T cell therapy was calculated using competing risks method. We also examined cumulative cause-specific hospitalizations per person-month at 30d, 31-90d, and >90d from infusion. Total number of ED visits and reasons for ED visits were examined by primary disease and by time from CAR-T cell infusion.Results: Overall, 204 patients (66% male) received CAR-T cell infusions (96% tisagenlecleucel) over the 3y period; median age at 1 st infusion was 55y (range 1-64). Cancer diagnoses included diffuse large B cell lymphoma (DLBCL, 62.8%), chronic lymphocytic leukemia (CLL, 12.3%), multiple myeloma (MM, 9.3%), other (15.6%). Median follow-up from CAR-T cell infusion was 3.2 mo (0-12); 11% were followed for all 12 mo. Hospitalizations: Ninety-one patients (44%) had 191 hospitalizations within 12 mo of CAR-T infusion (n=1: 47%, n=2: 24%, n >2: 28.5%); 16% of all CLL patients 12% of all DLBCL and 11% of all MM patients had >2 hospitalizations. Most prevalent reasons for hospitalization included infection (n=79; 41.3% of hospitalizations), myelosuppression (n=38; 19.9%), and management of underlying malignancy (n=35; 18.3%). The average length of stay per hospitalization was highest for infection (13.5d), followed by management of underlying malignancy (8.3d), and myelosuppression (5.9d). The cumulative incidence at 12 mo for cause-specific hospitalizations included: infection (22.2%), myelosuppression (11.9%), and managing malignancy (9.8%) (Fig 1). Overall, this cohort experienced 0.2 hospitalizations/person-mo. The majority of these hospitalizations occurred within the 1 st mo following CAR-T cell therapy (0.6/person-mo), declining to 0.11/person-mo at 31-90d, and to 0.04/person-mo at >90d (Fig 2). Infection and myelosuppression remained the most common reasons for hospitalizations across the three time periods. There were no statistically significant factors predicting hospitalization in multivariable models. ED visits: Fifty patients (25%) had 71 ED visits after CAR-T cell infusion (n=1: 76%; n=2: 14%; n>2: 10%). Reasons for ED visits included infections (n=14, 19.7%), myelosuppression (n=11, 15.5%), and cardiac emergencies (n=6, 8.5%). Median time to ED was 107d (range 8-355d). Nine ED visits occurred within the 1 st mo after CAR-T cell infusion (infection, epigastric/chest pain, thrombosis/hemorrhage [n=2 each], neutropenia, altered mental status, primary disease [n=1 each]).Conclusion: Real world data show that over the first 12 mo. after CAR-T cell therapy, 44% of the patients are re-hospitalized one or more times and 25% are seen in the emergency room. Infection is the most common reason for unplanned visits (hospitalizations or ED visits), followed by myelosuppression. The probability of these hospitalizations is highest within the first month, declining rapidly thereafter. These findings can be used to inform management strategies to mitigate unplanned healthcare utilization. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

A Real-World Study of Pre-Post Annualized Bleed Rates and All Cause Costs Among Non-Inhibitor Patients with Hemophilia a Switching from FVIII Prophylaxis to Emicizumab

BackgroundHemophilia A (HA) is a rare genetic disease characterized by a deficiency in clotting factor VIII (FVIII). Persons with HA suffer from spontaneous and traumatic bleeds which significantly impact short- and long-term quality of life. Prophylaxis treatment with FVIII replacement or non-factor replacement (e.g. emicizumab) intends to prevent bleeding episodes. To date, clinical comparisons between FVIII and emicizumab are limited to non-interventional studies and indirect comparisons. Comparisons of costs are limited to cost-effectiveness models or observational studies that include patients with and without inhibitors. An increase in availability of real-world data since emicizumab's approval in 2018 has created opportunity for comparative outcomes research in the non-inhibitor HA population.ObjectiveTo compare billed annualized bleed rates (ABR b) and all-cause costs (ACC) among non-inhibitor HA patients switching from prophylaxis with FVIII replacement to emicizumab.MethodsThis retrospective, observational, pre-post study used the IQVIA PharMetrics® Plus database (2015-2020)-a large longitudinal US commercial health plan database with over 190 million lives. International Classification of Diseases codes (ICD-10), National Drug Codes, and Healthcare Common Procedure Coding System were used to identify diagnoses, therapies, and procedures. Males with ≥1 claim for emicizumab who were on prophylaxis treatment with FVIII prior to initiating emicizumab were included in the analysis. Patients who received bypassing agents, immune tolerance induction, or rituximab were assumed to have inhibitors and were excluded. Patients with ≥2 occurrences of any of the following diagnoses were excluded: von Willebrand disease, hemophilia B, acquired HA, or other coagulation disorders.Annualized bleed rate was defined as billed ABR and represents bleeding episodes that required evaluation, treatment, or procedure resulting in an ICD-10 claim. Therefore, bleeds treated at home and untreated bleeds were not captured. A clinical review of ICD-10 codes resulted in a list of 535 codes used to identify HA-related bleeding episodes (e.g. hemarthrosis). The ACC were calculated as the mean cost per patient per year in 2020 US dollars actually paid by the insurer. Descriptive statistics were used to summarize, and Bayesian models were developed to compare, ABR b and ACC in the pre- and post-switch periods. Bayesian inferences estimated the population mean difference in ABR b and ACC after switching from FVIII prophylaxis to emicizumab. Inferences were conducted by computing posterior probabilities for hypotheses and summarized with 95% credible intervals (CrI).ResultsA total of 121 patients were included with mean age [range] of 25.9 [2-63] years. The majority of patients were over the age of 18 (60.3%), 33.1% were ≥7-18, and 6.6% were <7. The mean (SD) years on FVIII replacement (pre-switch) and emicizumab (post-switch) were 2.5 (1.5) and 1.1 (0.4), respectively (Table 1).DescriptiveIn the majority of patients, ABR b remained unchanged from pre-switch to post-switch (42%) while 38% had some magnitude of improvement, and 20% experienced a worsening of ABR b. The mean observed ABR b and ACC were 0.68 and $518,151, respectively, in the pre-switch period, and 0.55 and $652,679, respectively, in the post-switch period.Bayesian ModelThe Bayesian model demonstrated a mean change in ABR b of -0.128 [95% CrI: -0.441 to 0.184] after switch (Table 2). The mean change in ACC was +$159,680 [95% CrI: $74,842 to $247,841] after switch. The model determined there is a 21.0% probability ABR b will worsen after switch and a 99.9% probability ACC will increase after switch.ConclusionsProphylaxis with FVIII replacement and emicizumab result in similar prevention of billed bleeds in a real-world switch population. Although the population mean ABR b is more likely to fall after switching from FVIII replacement to emicizumab, there is only a 1.02% posterior probability the population mean ABR b will fall by ≥0.5 after switching to emicizumab and a 21.0% probability the ABR b will worsen after switch. Additionaly, ACC are almost certain to substantially increase after switching to emicizumab (99.9%). As additional real-world data becomes available in the non-inhibitor HA population, further research should help to strengthen clinical and economic outcomes for different prophylaxis treatment options. [Display omitted] DisclosuresBatt: Sanofi: Current equity holder in publicly-traded company; Bayer Therapeutics: Consultancy; Sprouts Consulting: Other: CEO, Principal Consultant; Merck: Current equity holder in publicly-traded company; Forma: Consultancy, Current equity holder in publicly-traded company; Precision Health: Consultancy; Takeda Pharmaceuticals U.S.A.: Consultancy. Schultz: Takeda Pharmaceuticals U.S.A., Inc.: Current Employment, Current holder of individual stocks in a privately-held company. Caicedo: Takeda Pharmaceuticals U.S.A., Inc.: Current Employment, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company. Hollenbeak: Takeda Pharmaceuticals U.S.A., Inc.: Consultancy. Agrawal: Takeda Pharmaceuticals U.S.A., Inc.: Consultancy. Chatterjee: Takeda Pharmaceuticals U.S.A., Inc.: Consultancy. Dayma: Takeda Pharmaceuticals U.S.A., Inc.: Consultancy. Bullano: Takeda Pharmaceuticals U.S.A., Inc.: Current Employment, Current holder of individual stocks in a privately-held company.

Predicting Hepatocellular Carcinoma With Minimal Features From Electronic Health Records: Development of a Deep Learning Model.

BackgroundHepatocellular carcinoma (HCC), usually known as hepatoma, is the third leading cause of cancer mortality globally. Early detection of HCC helps in its treatment and increases survival rates.ObjectiveThe aim of this study is to develop a deep learning model, using the trend and severity of each medical event from the electronic health record to accurately predict the patients who will be diagnosed with HCC in 1 year.MethodsPatients with HCC were screened out from the National Health Insurance Research Database of Taiwan between 1999 and 2013. To be included, the patients with HCC had to register as patients with cancer in the catastrophic illness file and had to be diagnosed as a patient with HCC in an inpatient admission. The control cases (non-HCC patients) were randomly sampled from the same database. We used age, gender, diagnosis code, drug code, and time information as the input variables of a convolution neural network model to predict those patients with HCC. We also inspected the highly weighted variables in the model and compared them to their odds ratio at HCC to understand how the predictive model worksResultsWe included 47,945 individuals, 9553 of whom were patients with HCC. The area under the receiver operating curve (AUROC) of the model for predicting HCC risk 1 year in advance was 0.94 (95% CI 0.937-0.943), with a sensitivity of 0.869 and a specificity 0.865. The AUROC for predicting HCC patients 7 days, 6 months, 1 year, 2 years, and 3 years early were 0.96, 0.94, 0.94, 0.91, and 0.91, respectively.ConclusionsThe findings of this study show that the convolutional neural network model has immense potential to predict the risk of HCC 1 year in advance with minimal features available in the electronic health records.

The epidemiology and etiology of adhesive capsulitis in the U.S. Medicare population

BackgroundAdhesive capsulitis (AC) of the shoulder, also known as frozen shoulder, causes substantial pain and disability. In cases of secondary AC, the inflammation and fibrosis of the synovial joint can be triggered by trauma or surgery to the joint followed by extended immobility. However, for primary AC the inciting trigger is unknown. The burden of the disorder among the elderly is also unknown leading to this age group being left out of therapeutic research studies, potentially receiving delayed diagnoses, and unknown financial costs to the Medicare system. The purpose of this analysis was to describe the epidemiology of AC in individuals over the age of 65, an age group little studied for this disorder. The second purpose was to investigate whether specific medications, co-morbidities, infections, and traumas are risk factors or triggers for primary AC in this population.MethodsWe used Medicare claims data from 2010–2012 to investigate the prevalence of AC and assess comorbid risk factors and seasonality. Selected medications, distal trauma, and classes of infections as potential inflammatory triggers for primary AC were investigated using a case–control study design with patients with rotator cuff tears as the comparison group. Medications were identified from National Drug codes and translated to World Health Organization ATC codes for analysis. Health conditions were identified using ICD9-CM codes.ResultsWe found a one-year prevalence rate of AC of approximately 0.35% among adults aged 65 years and older which translates to approximately 142,000 older adults in the United States having frozen shoulder syndrome. Diabetes and Parkinson’s disease were significantly associated with the diagnosis of AC in the elderly. Cases were somewhat more common from August through December, although a clear seasonal trend was not observed. Medications, traumas, and infections were similar for cases and controls.ConclusionsThis investigation identified the burden of AC in the US elderly population and applied case–control methodology to identify triggers for its onset in this population. Efforts to reduce chronic health conditions such as diabetes may reduce seemingly unrelated conditions such as AC. The inciting trigger for this idiopathic condition remains elusive.

MP19-11 ERECTILE DYSFUNCTION AND TREATMENT: AN ANALYSIS OF ASSOCIATED CHRONIC HEALTH CONDITIONS

You have accessJournal of UrologyHealth Services Research: Practice Patterns, Quality of Life and Shared Decision Making II (MP19)1 Sep 2021MP19-11 ERECTILE DYSFUNCTION AND TREATMENT: AN ANALYSIS OF ASSOCIATED CHRONIC HEALTH CONDITIONS Odinachi Moghalu, Joshua Horns, Rupam Das, Alexander Campbell, James Hotaling, and Alexander Pastuszak Odinachi MoghaluOdinachi Moghalu More articles by this author , Joshua HornsJoshua Horns More articles by this author , Rupam DasRupam Das More articles by this author , Alexander CampbellAlexander Campbell More articles by this author , James HotalingJames Hotaling More articles by this author , and Alexander PastuszakAlexander Pastuszak More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002004.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Erectile dysfunction (ED) is a common medical condition among men that significantly impacts quality of life. ED has several known etiologies, and has been linked to several common chronic health conditions with similar pathophysiology. However, there is no large-scale investigation of the association between ED and common chronic health conditions. This study aims evaluate the association between diagnosis and treatment of ED, and chronic health conditions METHODS: We reviewed data the Truven Health MarketScan claims and encounters database between 2008-2017 for men ≥18 years. Inclusion required an ED diagnosis, identified through ICD-9/10 codes. Those with a diagnosis of post-procedural or drug-induced ED were exclude. ED treatments were identified by National Drug Codes, (NDC) or Current Procedural Terminology, (CPT)codes. Using multiple regression models, we analyzed the association between having a diagnosis for ED and presence of 30 chronic health conditions. In the ED cohort, we further investigated the association between receiving treatment for ED and presence of chronic conditions RESULTS: Of the 2,489,069 men with ED, 954,512 (38.3%) had at least one recorded diagnosis of a chronic health condition. Depression (OR 2.875: 95% CI 2.866, 2.884; p<0.001) was observed to have the strongest association with a diagnosis of ED irrespective of treatment, while ischemic heart disease had the weakest association (OR 0.76: 95% CI 0.755, 0.773; p<0.001) (Fig. 1). Of those treated for ED, the most commonly associated health condition was bipolar disorder (OR 1.422: 95% CI 1.398, 1.447; p<0.001) (Fig 2) CONCLUSIONS: As has been reported in other studies, our study found that having ED was positively associated with having a concomitant diagnosis of depression, hypertension and diabetes. Further prospective research is needed to identify causal relationships that may be contributing to the associations observed and treatment options that can be added or modified to improve care in men with ED. Source of Funding: A.P is a National Institute of Health (NIH) K08 Scholar supported by a Mentored Career Development Award (K08DK115835-01) from the National Institute of Diabetes and Digestive and Kidney Diseases. This work is also supported in part through a Urology Care Foundation Rising Stars in Urology Award (to A.P) © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e331-e332 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Odinachi Moghalu More articles by this author Joshua Horns More articles by this author Rupam Das More articles by this author Alexander Campbell More articles by this author James Hotaling More articles by this author Alexander Pastuszak More articles by this author Expand All Advertisement Loading ...

Elementary School-Based Health Centers and Access to Preventive and Asthma-Related Care Among Publicly Insured Children With Asthma in Georgia.

We assessed the effects of 3 new elementary school-based health centers (SBHCs) in disparate Georgia communities-predominantly non-Hispanic Black semi-urban, predominantly Hispanic urban, and predominantly non-Hispanic White rural-on asthma case management among children insured by Medicaid/Children's Health Insurance Program (CHIP). We used a quasi-experimental difference-in-differences analysis to measure changes in the treatment of children with asthma, Medicaid/CHIP, and access to an SBHC (treatment, n = 193) and children in the same county without such access (control, n = 163) in school years 2011-2013 and 2013-2018. Among children with access to an SBHC (n = 193), we tested for differences between users (34%) and nonusers of SBHCs. We used International Classification of Diseases diagnosis codes, Current Procedural Terminology codes, and National Drug Codes to measure well-child visits and influenza immunization; ≥3 asthma-related visits, asthma-relief medication, asthma-control medication, and ≥2 asthma-control medications; and emergency department visits during the child-school year. We found an increase of about 19 (P = .01) to 33 (P < .001) percentage points in the probability of having ≥3 asthma-related visits per child-school year and an increase of about 22 (P = .003) to 24 (P < .001) percentage points in the receipt of asthma-relief medication, among users of the predominantly non-Hispanic Black and Hispanic SBHCs. We found a 19 (P = .01) to 29 (P < .001) percentage-point increase in receipt of asthma-control medication and a 15 (P = .03) to 30 (P < .001) percentage-point increase in receipt of ≥2 asthma-control medications among users. Increases were largest in the predominantly non-Hispanic Black SBHC. Implementation and use of elementary SBHCs can increase case management and recommended medications among racial/ethnic minority and publicly insured children with asthma.

Associations between naloxone prescribing and opioid overdose among patients with acute and chronic pain conditions.

AimsTo assess whether naloxone prescribing in clinical contexts targeted pain patients most at risk for opioid overdose.DesignA retrospective cohort study using data from the Health Facts Database.SettingOver 600 United States healthcare facilities.ParticipantsThree patient groups were followed for 2 years during 2009 to 2017: individuals with shoulder or long bone fractures (n = 252 424), chronic pain syndrome (CPS) (n = 76 141), or non‐traumatic low back pain (n = 792 956) who received an opioid prescription. Groups were chosen based on previous work.MeasurementsThe outcome was opioid overdose identified by International Classification of Diseases codes (ICDs) and the primary predictor was number of naloxone prescriptions identified by National Drug Codes (NDCs).FindingsOpioid overdoses occurred among 0.16% of fracture patients (average follow‐up time to overdose [AFU] = 240 days), 1.28% of CPS patients (AFU = 244 days), and 0.30% low back pain patients (AFU = 264 days). A total of 58 083 bone fracture patients received naloxone prescriptions, and naloxone prescription was associated with subsequent opioid overdose (hazard ratio [HR] = 1.87, 95% CI = 1.68–2.09), and number of subsequent overdoses (incidence rate ratio [IRR] = 1.89, 95% CI = 1.69–2.12). A total of 19 529 CPS patients received naloxone prescriptions, and naloxone prescription was associated with subsequent opioid overdose (HR = 1.69, 95% CI = 1.61–1.78) and number of subsequent overdoses (IRR = 1.74, 95% CI = 1.67–1.83). A total of 110 608 low back pain patients received naloxone prescriptions, and naloxone prescription was associated with subsequent opioid overdose (HR = 1.33, 95% CI = 1.27–1.40) and number of subsequent overdoses (IRR = 1.35, 95% CI = 1.29–1.41).ConclusionsReceiving a naloxone prescription appears to be associated with increased risk of subsequent opioid overdose among patients with acute and chronic pain, suggesting prescribers often identify patients most in need of naloxone.

P28. Postoperative complications of opioid alternatives in common lumbar spine procedures

<h3>BACKGROUND CONTEXT</h3> Lumbar fusions are commonly used surgical techniques for the treatment of instability and degenerative disc disease. Few studies have examined if the non-opioid analgesics Gabapentin and Pregabalin can effectively manage postoperative pain following common lumbar fusion procedures. <h3>PURPOSE</h3> This study aims to examine postoperative complications associated with the use of non-opioid analgesics (ie, Gabapentin or Pregabalin) for postoperative pain management following anterior lumbar interbody fusion (ALIF), posterior lumbar interbody fusion (PLIF), or transforaminal lumbar interbody fusion (TLIF). <h3>STUDY DESIGN/SETTING</h3> Retrospective database review. <h3>PATIENT SAMPLE</h3> Patient cohort identified using MSpine national database that includes patients of all payer types who received fusion procedures. <h3>OUTCOME MEASURES</h3> Complications examined included the following: neurologic, GI, respiratory, DVT and pulmonary embolism, pruritus, mental disorders, urinary incontinence and postoperative pain. <h3>METHODS</h3> The MSpine national database was queried with relevant Current Procedural Terminology (CPT) codes for patients who underwent an ALIF, PLIF, or TLIF between 2010 to 2019. Patients were organized into anterior approach and posterior approach groups and further queried using National Drug Codes (NDC) to form cohorts of patients who received (i) exclusively opioids, or (ii) a mix regimen, for postoperative pain management. A search of relevant International Classification of Diseases (ICD-9 and ICD-10) codes identified the postoperative surgical and medical complications. Propensity score matching for age, gender, and Charlson Comorbidity Index was performed to control for potential confounding factors. Odds ratios and CI will be used to compare postoperative complication rates between the various groups. <h3>RESULTS</h3> The anterior_opioids group included 22,581 patients (45.5% male and 54.5% female) and the anterior_mix group included 2,192 patients (37.2% male and 62.8% female). The posterior_opioids group included 22,279 patients (48.0% male and 52.0% female) and the posterior_mix group included 2,677 patients (39.4% male and 60.6% female). After propensity score matching, the anterior groups and posterior groups were 2,182 and 2,671 patients, respectively. The incidence of postoperative pain at 6 weeks was higher in anteriormix (6.0%) than anterior_opioids (3.9%); similarly, this incidence was higher in posterior_mix (8.6%) than posterior_opioids (5.6%). The incidence of mental disorders at 3 weeks was higher in anterior_opioids (6.9%) than anterior_mix (5.8%), while the incidence of GI complications at 3 weeks was lower in anterior_opioids (3.1%) than anterior_mix (3.8%). Respiratory complications at 3 weeks were higher in posterior_mix (2.5%) than posterior_opioids (1.9%). Furthermore, neurologic complications at 3 weeks were higher in posterior_mix (2.3%) than posterior_opioids (1.9%). <h3>CONCLUSIONS</h3> Patients receiving opioids and Gabapentin or Pregabalin for postoperative pain management following ALIF had higher incidence of postoperative pain and GI complications, but lower incidence of mental disorders, compared to patients who received opioids. Patients who received a mixed regimen for postoperative pain management following PLIF or TLIF were associated with a higher incidence of postoperative pain, respiratory, and neurologic complications. <h3>FDA DEVICE/DRUG STATUS</h3> This abstract does not discuss or include any applicable devices or drugs.

Hepatitis C Treatment Among Commercially or Medicaid-Insured Individuals, 2014–2018

The proportion of individuals infected with hepatitis C virus that receive direct-acting antiviral treatment is unclear. The proportion of commercially or Medicaid-insured patients receiving hepatitis C virus treatment was estimated using administrative claims data obtained from MarketScan and Multi-State Medicaid obtained on January 6, 2020. Validated algorithms derived from standardized procedures and International Classification of Diseases diagnosis codes were used to identify enrollees with chronic hepatitis C; analysis (performed November 30, 2020) was restricted to adults continuously enrolled with prescription drug coverage for >6 months before and after their index hepatitis C viral load test claim date from January 2014 through December 2018. Prescription drug claims using National Drug Codes were used for hepatitis C virus drugs. The proportion of treated patients by demographic and clinical characteristics was described, and associations with treatment were modeled using multivariable-adjusted hazard ratios and 95% CIs by insurance status. Of patients with chronic hepatitis C, 12,090 of 17,562 (69%) with commercial insurance and 8,112 of 27,328 (30%) with Medicaid were treated. Commercially insured patients with opioid use disorder (hazard ratio=0.78, 95% CI=0.72, 0.85), alcohol use disorder (hazard ratio=0.85, 95% CI=0.79, 0.91), severe mental illness (hazard ratio=0.92, 95% CI=0.87, 0.98), chronic kidney disease (hazard ratio=0.75, 95% CI=0.69, 0.82), or HIV infection (hazard ratio=0.74, 95% CI=0.66, 0.82) were less likely to be treated. Medicaid patients with opioid (hazard ratio=0.64, 95% CI=0.61, 0.68) or alcohol use disorders (hazard ratio=0.83, 95% CI=0.79, 0.88) were less likely to be treated. Hepatitis C virus treatment gaps were identified using administrative claims data among patients with commercial and Medicaid insurance.

Performance evaluation of a prescription medication image classification model: an observational cohort

Technology assistance of pharmacist verification tasks through the use of machine intelligence has the potential to detect dangerous and costly pharmacy dispensing errors. National Drug Codes (NDC) are unique numeric identifiers of prescription drug products for the United States Food and Drug Administration. The physical form of the medication, often tablets and capsules, captures the unique features of the NDC product to help ensure patients receive the same medication product inside their prescription bottle as is found on the label from a pharmacy. We report and evaluate using an automated check to predict the shape, color, and NDC for images showing a pile of pills inside a prescription bottle. In a test set containing 65,274 images of 345 NDC classes, overall macro-average precision was 98.5%. Patterns of incorrect NDC predictions based on similar colors, shapes, and imprints of pills were identified and recommendations to improve the model are provided.

The Impact of Depression and Use of Anti-Depressants on Healthcare Resource Utilization (HCRU) in Multiple Myeloma (MM) Patients

ObjectivesDepression and the use of anti-depressants are common co-existing morbidities often encountered by MM patients. Depression among MM patients is estimated at 30-50% versus 7% in the general population (Li HH et al; Blood, 2016).While approximately 11% of the general population >=12 years use antidepressants, the frequency of use in MM patients suffering from depression is unknown. We aimed to better understand real-world frequency of antidepressant use in MM patients in the contemporary era and how their use potentially impacts healthcare resource use (HCRU).MethodsNewly diagnosed MM patients initiating therapy between 01/01/2013-09/30/2016 were selected from the Inovalon Medical Outcomes Research for Effectiveness and Economics (MORE²) Registry payer claims and remittance dataset containing longitudinal information for 125 million unique covered patient lives, including more than 6 million cancer patients. Depression was ascertained using a combination of ICD9/10-CM, CPT, and HCPCS codes appropriate for behavioral health visits. Antidepressants were identified using National Drug Codes (NDC). Only patients with a diagnosis of depression following the onset of MM treatment were included in this analysis. Patients initiating antidepressants following a depression event (cases) were separated from patients never initiating antidepressants (controls). HCRU was measured from the diagnosis date of depression until the date of last claim and was measured per-patient per-month (PPPM). Patients with polyneuropathy between MM treatment and the medication onset were excluded using ICD9/10-CM codes as antidepressants are sometimes used to treat polyneuropathy. Patients having depression one year prior to initiating MM treatment were also excluded. Patients on anti-depressants were compared to patients never initiating anti-depressants across cost and utilization measures for inpatient, outpatient, office, and ER. P-values for categorical variables were generated using chi-square tests. P-values for continuous variables were calculated using Wilcoxon rank sum test since HCRU measures are often non-normally distributed.ResultsA total of 2,538 MM patients met our inclusion criteria. Depression was diagnosed in 565 patients (22.2%) after beginning a MM treatment. Of these, 129 patients (22.8%) received antidepressants (cases) and 443 patients (78.4%) did not (controls). The average length of follow-up in this cohort was 459.1 days (SD: 331.6). The most common medications prescribed were Sertraline (16.7%), Mirtazapine (15.1%), Duloxetine (12.9%), and Trazodone (12.9%). Compared to controls, cases experienced significantly shorter inpatient stays (mean: 5.02 vs 3.81 for case and control respectively, p-value 0.009). This resulted in lower, but not statistically significant, mean inpatient costs PPPM ($970.58 vs $1873.36). Both groups were otherwise comparable across other cost and utilization outcomes.ConclusionsDespite 22.2% of MM patients having depression diagnosis post-MM onset, only 22.8% of these patients with depression initiated anti-depressant therapy, resulting in an overall use of 5% of MM patients starting treatment. This is substantially lower than the 11% observed in the general population. The use of antidepressants in this context resulted in a favorable impact on HCRU and underscores the unmet need of proper mental health treatment and education for patients with MM. DisclosuresFeinberg:Cardinal Health: Employment.