OptumLabs Data Warehouse Research Articles

Longitudinal Cost of Septal Myectomy Versus Alcohol Septal Ablation for Hypertrophic Cardiomyopathy

ObjectiveTo compare the postprocedural health care utilization and cost of septal myectomy (SM) and alcohol septal ablation (ASA). Patients and MethodsUsing the OptumLabs Data Warehouse, we analyzed de-identified claims data of adult patients undergoing SM and ASA for obstructive hypertrophic cardiomyopathy from January 1, 2006, through December 31, 2018. We used propensity score weighting to compare the 2-year incidence rates of emergency department visits and rehospitalizations after SM and ASA. ResultsWe identified 953 patients in total: 660 underwent SM and 293 underwent ASA. There was no difference in the risk (odds ratio, 1.1; 95% CI, 0.6 to 1.8) or frequency (incidence rate ratio, 1.1; 95% CI, 0.8 to 1.5) of emergency department visits, but the annual risk of hospital readmission was 10.8% after SM and 25.9% after ASA during the second postoperative year (P=.004). In those who were ever readmitted, the average length of hospital stay within the first 2 years after ASA was 1.6 times as long as that after SM (incidence rate ratio, 1.6; 95% CI, 1.0 to 2.4). Overall, the 2-year cumulative postprocedural cost was significantly higher after ASA (P<.001). ConclusionCompared with ASA, SM is associated with fewer hospital readmissions and lower 2-year postprocedural health care cost.

State-Level Variation In Low-Value Care For Commercially Insured And Medicare Advantage Populations

Low-value care is a major source of health care inefficiency in the US. Our analysis of 2009-19 administrative claims data from OptumLabs Data Warehouse found that low-value care and associated spending remain prevalent among commercially insured and Medicare Advantage enrollees. The aggregated prevalence of twenty-three low-value services was 1,920 per 100,000 eligible enrollees, which amounted to $3.7 billion in wasteful expenditures during the study period. State-level variation in spending was greater than variation in utilization, and much of the variation in spending was driven by differences in average procedure prices. If the average price for twenty-three low-value services among the top ten states in spending were set to the national average, their spending would decrease by 19.8percent (from $735,000 to $590,000 per 100,000 eligible enrollees). State-level actions to improve the routine measurement and reporting of low-value care could identify sources of variation and help design state-specific policies that lead to better patient-centered outcomes, enhanced equity, and more efficient spending.

Effect of the 2012 US Preventive Services Task Force Recommendations on Prostate-Specific Antigen Screening in a Medicare Advantage Population.

In 2012, the US Preventive Service Task Force revised its recommendations for prostate-specific antigen (PSA) screening from "insufficient evidence" to "do not recommend" for men aged 70-74 while maintaining "do not recommend" for men aged 75+. Using the difference-in-difference approach, we evaluated whether the rate of change in the use of low-value PSA screening differed between the control group (men aged 75+, N=7,856,204 person-years) and the intervention group (men aged 70-74, N=5,329,192 person-years) enrolling in the Medicare Advantage plan without a history of prostate cancer within the OptumLabs Data Warehouse claims data (2009-2019). A generalized estimating equation logistic model was specified with independent variables: an intervention group indicator, a pre- and post-period (after 2012 Q2) indicator, index time, and interaction terms. We assumed a 12-month dissemination period. Before the revised recommendation in 2012, the trends did not significantly differ between the 2 age groups with the odds of receiving PSA screening decreasing by 1.2% (95% confidence interval [1.0, 1.4%]) per quarter. However, the odds of receiving PSA screening increased by 3.0% [2.8, 3.2%] per quarter across both groups since the revision. There was no significant additional change in the trend for those aged 70-74 (0.1% [-0.2, 0.5%]). Although the 2012 US Preventive Service Task Force's recommendations were expected to only change behaviors among men aged 70-74, our analysis found that men aged 70-74 and aged 75+ exhibited similar trends from 2009 to 2019, including the increased use of low-value PSA screening since 2016. Multifaceted efforts to discourage low-value PSA screening would be important for a sustained impact.

Association Between State Opioid Prescribing Cap Laws and Receipt of Opioid Prescriptions Among Children and Adolescents

High-dose and long-duration opioid prescriptions remain relatively common among children and adolescents, but there is insufficient research on the association of state laws limiting the dose and/or duration of opioid prescriptions (referred to as opioid prescribing cap laws) with opioid prescribing for this group. To examine the association between state opioid prescribing cap laws and the receipt of opioid prescriptions among children and adolescents. This repeated cross-sectional study used a difference-in-differences approach accounting for staggered policy adoption to assess the association of state opioid prescribing cap laws in the US from January 1, 2013, to December 31, 2019, with receipt of opioid prescriptions among children and adolescents. Analyses were conducted between March 22 and December 15, 2021. Data were obtained from the OptumLabs Data Warehouse, a national commercial insurance claims database. The analysis included 482 118 commercially insured children and adolescents aged 0 to 17 years with full calendar-year continuous insurance enrollment between 2013 and 2019. Individuals were included for every year in which they were continuously enrolled; they did not need to be enrolled for the entire 7-year study period. Those with any cancer diagnosis were excluded from analysis. Implementation of a state opioid prescribing cap law between January 1, 2017, and July 1, 2019. This date range allowed analysis of the same number years for both pre-cap and post-cap data. Outcomes of interest included receipt of any opioid prescription and, among those with at least 1 opioid prescription, the mean number of opioid prescriptions, mean morphine milligram equivalents (MMEs) per day, and mean days' supply. Among 482 118 children and adolescents (754 368 person-years of data aggregated to the state-year level), 245 178 (50.9%) were male, with a mean (SD) age of 9.8 (4.8) years at the first year included in the sample (data on race and ethnicity were not collected as part of this data set, which was obtained from insurance billing claims). Overall, 10 659 children and adolescents (2.2%) received at least 1 opioid prescription during the study period. Among those with at least 1 prescription, the mean (SD) number of filled opioid prescriptions was 1.2 (0.8) per person per year. No statistically significant association was found between state opioid prescribing cap laws and any outcome. After opioid prescribing cap laws were implemented, a -0.001 (95% CI, -0.005 to 0.002) percentage point decrease in the proportion of youths receiving any opioid prescription was observed. In addition, percentage point decreases of -0.01 (95% CI, -0.10 to 0.09) in high-dose opioid prescriptions (>50 MMEs per day) and -0.02 (95% CI, -0.12 to 0.08) in long-duration opioid prescriptions (>7 days' supply) were found after cap laws were implemented. In this cross-sectional study, no association was observed between state opioid prescribing cap laws and the receipt of opioid prescriptions among children and adolescents. Alternative strategies, such as opioid prescribing guidelines tailored to youths, are needed.

Effects of state opioid prescribing cap laws on opioid prescribing after surgery.

To evaluate the effects of state opioid prescribing cap laws on opioid prescribing after surgery. OptumLabs Data Warehouse administrative claims data covering all 50 states from July 2012 through June 2019. We included individuals from 20 states that had implemented prescribing cap laws without exemptions for postsurgical pain by June 2019 and individuals from 16 control states plus the District of Columbia. We used a difference-in-differences approach accounting for differential timing in law implementation across states to estimate the effects of state prescribing cap laws on postsurgical prescribing of opioids. Outcome measures included filling an opioid prescription within 30 days after surgery; filling opioid prescriptions of specific doses or durations; and the number, days' supply, daily dose, and pill quantity of opioid prescriptions. To assess the validity of the parallel counterfactual trends assumption, we examined differences in outcome trends between law-implementing and control states in the years preceding law implementation using an equivalence testing framework. We included the first surgery in the study period for opioid-naïve individuals undergoing one of eight common surgical procedures. State prescribing cap laws were associated with 0.109 lower days' supply of postsurgical opioids on the log scale (95% Confidence Interval [CI]: -0.139, -0.080) but were not associated with the number (Average treatment effect on the treated [ATT]: -0.011; 95% CI: -0.043, 0.021) or daily dose of postsurgical opioid prescriptions (ATT: -0.013; 95% CI: -0.030, 0.005). The negative association observed between prescribing cap laws and the probability of filling a postsurgical opioid prescription (ATT: -0.041; 95% CI: -0.054, -0.028) was likely spurious, given differences between law-implementing and control states in the pre-law period. Prescribing cap laws appear to have minimal effects on postsurgical opioid prescribing.

Anticoagulation After Bioprosthetic Aortic Valve Replacement: Are We Following the Guidelines?

BackgroundGuideline-directed medication adherence is considered an important quality measure after cardiac surgery. We evaluated compliance with the American College of Cardiology/American Heart Association guidelines for warfarin use after surgical aortic valve replacement (sAVR) using bioprostheses and examined potential variations in anticoagulation practice over time. MethodsUsing the OptumLabs Data Warehouse, we investigated adult patients having bioprosthetic sAVR with or without coronary artery bypass (2007-2019). Early postoperative warfarin use was defined as ≥30 days of continuous prescription coverage after sAVR. ResultsAmong 10 730 adult patients having sAVR, 3071 (28.6%) received warfarin early postoperatively. Median length of warfarin prescription coverage was 4.5 months (interquartile range, 3.0-8.9 months). However, only 11.1% (736/6634) had warfarin prescription coverage of 3 to 6 months in compliance with the most recent guidelines. Yearly warfarin prescription rate did not change significantly during the 13-year period (P = .386). Compared with patients from the non-warfarin group, those receiving warfarin prescriptions were older and more likely to be male and to have atrial fibrillation, congestive heart failure, chronic pulmonary disease, and CHA2DS2-VASc score ≥2; warfarin use was also greater in patients receiving prescriptions for other cardiac medications (P < .05). ConclusionsAnticoagulation after sAVR as reflected by warfarin prescriptions may be underused; the rates of warfarin use have not changed in the last decade. Although additional studies are needed to confirm the benefit of early anticoagulation after sAVR, these results indicate that guideline recommendations are not followed by most clinicians. The findings highlight a potentially important area for quality improvement.

Surveillance mammography after treatment for male breast cancer.

To identify the practice patterns related to use of surveillance mammography in male breast cancer (MaBC) survivors. Using administrative claims data from OptumLabs Data Warehouse, we identified men who underwent surgery for breast cancer during 2007-2017. We calculated the proportion of men who had at least one mammogram (a) within 13months for all patients and (b) within 24months amongst those who maintained their insurance coverage for at least that length of time after surgery. Multivariate logistic regression modeling was used to identify factors associated with mammography within each timeframe. Out of 729 total MaBC survivors, 209 (29%) underwent mammography within 13months after surgery. Among those who had lumpectomy, 41% underwent mammography, whereas among those who had mastectomy, 27% had mammography. Amongst 526 men who maintained consistent insurance coverage for 24months after surgery, 215 (41%) underwent mammography at least once during that 24-month period. In this cohort, the proportion who had at least one mammogram during the 24-month period was 49% after lumpectomy and 40% after mastectomy. In a multivariate logistic regression model, more recent diagnosis (2015+) and older age at diagnosis were associated with lower odds of undergoing mammography, while receipt of radiation was associated with higher odds of undergoing mammography. Although recent ASCO guidelines recommend surveillance mammography after lumpectomy, a minority of MaBC survivors undergo surveillance mammography, even after lumpectomy. This is likely due to the paucity of data regarding the true benefits and harms of surveillance/screening mammography for MaBC.

Long-term Risk of Overdose or Mental Health Crisis After Opioid Dose Tapering

Patients prescribed long-term opioid therapy are increasingly undergoing dose tapering. Recent studies suggest that tapering is associated with short-term risks of substance misuse, overdose, and mental health crisis, although lower opioid dose could reduce risks of adverse events over the longer term. To assess the longer-term risks of overdose or mental health crisis associated with opioid dose tapering. This is a cohort study using an exposure-crossover analysis. Data were obtained from the OptumLabs Data Warehouse, which includes deidentified medical and pharmacy claims and enrollment records for commercial insurance and Medicare Advantage enrollees, representing a diverse mixture of ages, races, ethnicities, and geographical regions across the US. Participants were US adults who underwent opioid dose tapering from 2008 to 2017 after a 12-month baseline period of stable daily dosing of 50 morphine milligram equivalents or higher and who had at least 1 month of long-term follow-up during a postinduction period beginning 12 months after taper initiation. Data analysis was performed from October 2021 to April 2022. Opioid tapering, defined as 15% or more relative reduction in mean daily dose during any of 6 overlapping 60-day windows within a 7-month follow-up period after the stable baseline period. Emergency or hospital encounters for drug overdose or withdrawal and mental health crisis (depression, anxiety, or suicide attempt). Outcome counts were assessed in pretaper and postinduction periods (from 12 to 24 months after taper initiation). The study included 21 515 tapering events among 19 377 patients with a mean (SD) of 9.1 (2.7) months of postinduction follow-up per event (median [IQR], 10 [8-11] months). Patients had a mean (SD) age of 56.9 (11.2) years, 11 581 (53.8%) were female, and 8217 (38.2%) had commercial insurance (vs Medicare Advantage). In conditional negative binomial regression analyses, adjusted incidence rate ratios for the postinduction period compared with the pretaper period were 1.57 (95% CI, 1.42-1.74) for overdose or withdrawal and 1.52 (95% CI, 1.35-1.71) for mental health crisis. These findings suggest that opioid tapering was associated with increased rates of overdose, withdrawal, and mental health crisis extending up to 2 years after taper initiation.

Actual immune checkpoint inhibitor drug use in U.S. patients with cancer.

2608 Background: By 2018, seven Immune Checkpoint Inhibitor (ICI) drugs had gained FDA approval in nine cancers and the number of indications has continued to increase. Haslam et al. estimated that between 36.1 and 38.5% of US patients with cancer were eligible for ICI therapy in 2019. We report the use of ICI dugs in the first-line of therapy (LOT1) and second-line (LOT2) among enrollees treated for 9 cancers with an FDA indication approval in or before 2017. Methods: A cohort of patients treated for one of the nine most common cancers with an FDA indication for ICI drugs in 2017 was identified using de-identified data from the OptumLabs Data Warehouse, and clinical information from the Optum Cancer Guidance Program’s electronic prior authorization (ePA) platform. De-identified administrative claims data were then linked to ePA information (cancer type &amp; diagnosis date) at the patient level to identify details of treatment received. Eligible patients were enrolled in a commercial or Medicare Advantage (MA) plan and initiated treatment within six months of diagnosis, enrolled at least six months prior to diagnosis date (ensuring this was the LOT1) and at least thirty days after start of first identified treatment regimen (to identify the full treatment regimen). LOT1 treatment initiation ranged from 1/1/2017 to 12/31/2020 for those who were diagnosed before 6/30/2020. ICI regimens are defined as those with an ICI drug received within first thirty days of the LOT start date. Results: In this population, we identified 17,283 eligible patients treated for non-small cell lung cancer (4654), melanoma (705), renal cell carcinoma (554), bladder cancer (1974), colorectal (4502), hepatocellular carcinoma (673), gastric cancer (1786), head and neck cancer (1923), or Hodgkin lymphoma (512) in 2018, 2019, and 2020. Overall, 3,291 (19%) of these patients received an ICI in LOT1 with rates increasing over time. The highest rates of ICI use in LOT1 are for the treatment of melanoma, remaining consistent over time, while ICI use in LOT2 is highest for the treatment of non-small cell lung cancer although evidence from 2020 suggests this may be waning. Among patients being treated for renal cell carcinoma, ICI use in LOT2 decreased from 43% (2018) to 15% (2020) while LOT1 ICI use increased to 81% in 2020. Conclusions: Overall, ICI use has changed over time in both the first- and second-line setting. In particular, we observe a shift in ICI use from LOT2 to LOT1, consistent with the more recent FDA approvals in earlier lines of therapy.[Table: see text]

Cost effectiveness of reduced intensity conditioning and transplantation of unrelated umbilical cord blood versus HLA haploidentical related bone marrow for adults with hematologic malignancies.

6591 Background: BMT CTN 1101 was a Phase III randomized controlled trial evaluating the comparative effectiveness of unrelated umbilical cord blood (UCB) versus HLA-haploidentical related donor bone marrow (haplo-BM) cell sources for hematopoietic cell transplantation (HCT) in patients with high-risk hematologic malignancies (leukemias, lymphomas). We report results of an economic evaluation conducted as part of the clinical trial. Methods: 368 patients (90% of planned accrual) enrolled from 33 centers in the U.S. were randomly assigned to unrelated UCB (n=186) or haplo-BM (n=182) transplant. Healthcare utilization and costs were estimated using propensity-score matched cohorts of BMT patients in the OptumLabs Data Warehouse for trial participants &lt;65 years, and Medicare claims for trial participants ≥65 years. Cost-effectiveness was calculated from payer perspectives (commercial, Medicare) over a 20-year time horizon from time of transplant. Weibull models (best fit based on AIC/BIC) were used to extrapolate survival from 5-year trial follow-up data. Trial participant surveys (EQ-5D) were used to derive health state utilities for estimating Quality-Adjusted Life Years (QALYs). One-way and probabilistic sensitivity analyses were conducted to assess uncertainty in results. Outcomes were discounted at 3% annually. Results: At 5-year follow-up, overall survival was 42% for haplo-BM versus 36% for UCB (P=.06). Over a 20-year time horizon, haplo-BM is expected to be more effective and more costly for &lt;65 year-olds and in ≥65 year-olds it is expected to be more effective and less costly. In one-way uncertainty analyses, for persons &lt;65, the cost/QALY result was most sensitive to life years and health state utilities. For persons ≥65, life years were more influential than costs and health state utilities. Using probabilistic sensitivity analysis, for persons &lt;65 there was a 43% chance that haplo-BM was cost-effective using a willingness to pay threshold of $150k/QALY and 52% at a $200K/QALY threshold. Conclusions: Results from a large national clinical trial indicate that compared to UCB, haplo-BM was moderately cost-effective for patients aged &lt;65 years, and less costly and more effective for persons ≥65 years. Haplo-BM is a fair value choice for commercially insured patients with high-risk leukemia and lymphoma who require HCT. For Medicare enrollees, haplo-BM is a preferred choice when considering costs and outcomes. [Table: see text]

Teleophthalmology Using Remote Retinal Imaging During the COVID-19 Pandemic.

Introduction: Lower insurance reimbursements have limited the financial sustainability of remote eye screening programs. Greater utilization and insurance coverage for teleophthalmology screening during the coronavirus disease 2019 (COVID-19) pandemic in 2020 may enhance awareness and expand remote retinal imaging services. This retrospective cross-sectional study evaluates utilization and insurance coverage for remote retinal imaging in the United States in 2020. Methods: We analyzed teleretinal imaging utilization and insurance payments from January 1 to December 31, 2020, using the Optum Labs Data Warehouse, a comprehensive national database of deidentified administrative claims for commercial and Medicare Advantage enrollees in the United States. We evaluated frequency of claims and insurance payment for services using the Current Procedural Terminology codes 92227 and 92228 for remote eye imaging by any provider, and 92250 for fundus photography by non-eye care providers. Results: The use of remote retinal imaging in the United States declined rapidly during the initial COVID-19 lockdown from 3,627 claims in February 2020 to 1,414 claims in April 2020, but returned to 3,133 claims by December 2020, similar to mean prepandemic levels in 2019 (2,841 ± 174.8 claims). The proportion of insurance payments for remote imaging increased temporarily from 47.4% in February to 56.7% in April, and then returned to 45.9% in December of 2020. Discussion: Utilization of remote retinal imaging declined steeply, while the insurance coverage increased during the initial COVID-19 lockdown in 2020, but returned to prepandemic levels by end of the year. Changes in utilization and relaxed restrictions on insurance reimbursements for teleophthalmology during the COVID-19 pandemic were not sustained.

Association between Immunosuppressive Drugs and Coronavirus Disease 2019 Outcomes in Patients with Noninfectious Uveitis in a Large US Claims Database

PurposeTo determine the dose-dependent risk of systemic corticosteroids (SCs) and the risk of other immunosuppressive therapies on coronavirus disease 2019 (COVID-19) infection, hospitalization, and death in patients with noninfectious uveitis (NIU).DesignA retrospective cohort study from January 20, 2020, to December 31, 2020 (an era before widespread COVID-19 vaccination), using the Optum Labs Data Warehouse, a US national de-identified claims database.ParticipantsPatients who had at least 1 NIU diagnosis from January 1, 2017.MethodsUnadjusted and adjusted hazard ratios (HRs) were estimated for each variable and COVID-19 outcome using Cox proportional hazards models, with time-updated dichotomous indicators for outpatient immunosuppressive medication exposure. To assess the dose-dependent effect of SC exposure, the average daily dose of prednisone over the exposed interval was included in the adjusted models as a continuous variable, in addition to the dichotomous variable.Main Outcome MeasuresIncidence rates of COVID-19 infection, COVID-19–related hospitalization, and COVID-19–related in-hospital death.ResultsThis study included 52 286 NIU patients of whom 12 000 (23.0%) were exposed to immunosuppressive medications during the risk period. In adjusted models, exposure to SCs was associated with increased risk of COVID-19 infection (HR, 2.66; 95% confidence interval [CI], 2.19–3.24; P < 0.001), hospitalization (HR, 3.26; 95% CI, 2.46–4.33; P < 0.001), and in-hospital death (HR, 1.99; 95% CI, 0.93–4.27; P = 0.08). Furthermore, incremental increases in the dosage of SCs were associated with a greater risk for these outcomes. Although tumor necrosis factor-α (TNF-α) inhibitors were associated with an increased risk of infection (HR, 1.48; 95% CI, 1.08–2.04; P = 0.02), other immunosuppressive treatments did not increase the risk of COVID-19 infection, hospitalization, or death.ConclusionsThis study from an era before widespread COVID-19 vaccination demonstrates that outpatient SC exposure is associated with greater risk of COVID-19 infection and severe outcomes in patients with NIU. Future studies should evaluate the impact of immunosuppression in vaccinated NIU patients. Limiting exposure to SCs and use of alternative therapies may be warranted.

MO486: Comparison of Hospitalization Lengths of Stay Among a National Cohort of Advanced CKD Patients Treated With Conservative Management Vs. Dialysis

Abstract BACKGROUND AND AIMS While dialysis has been the prevailing treatment paradigm in advanced CKD patients progressing to ESRD, this treatment approach may lead to a decline in physical function, loss of independence, and greater healthcare utilization among certain subgroups. We sought to compare the impact of dialysis versus conservative dialysis-free management on hospitalization lengths of stay (LOS) in advanced CKD patients. METHOD We examined a national cohort of advanced CKD patients (≥2 eGFRs &amp;lt;25 mL/min/1.73 m2 separated by ≥90 days) treated with conservative management (CM) versus dialysis over 1 January 2007—30 June 2020 from the OptumLabs® Data Warehouse (OLDW), which contains de-identified administrative claims, including medical and pharmacy claims and enrollment records for commercial and Medicare Advantage enrollees, as well as electronic health record data. In primary analyses, patients were categorized according to receipt of CM, defined as those who did not receive dialysis within 2-years of the index eGFR (1st eGFR &amp;lt;25 mL/min/1.73 m2), versus receipt of dialysis. In secondary analyses, we examined finer gradations of the timing of dialysis, defined as late versus early transition (eGFRs &amp;lt;15 versus ≥15 mL/min/1.73 m2 respectively, at the time of dialysis initiation). We compared LOS among patients treated with CM versus dialysis who were hospitalized within 2 years of their index eGFR using linear mixed effects models that separately considered a fixed age of the cohort (65-years old), with varying times of hospitalization from the index eGFR date, as well as a fixed time of hospitalization from the index eGFR date (12 months) with varying age. RESULTS Among 169 479 advanced CKD patients who were hospitalized within 2-years of their index eGFR, there were a total of 620 168 hospitalizations over this time period. In primary analyses that considered a fixed age of the cohort, dialysis patients experienced longer average LOS versus those treated with CM, with differences attenuating over time (∆ of + 1.5-days for hospitalizations 1-month from the index eGFR; Fig. 1A, upper panel). In secondary analyses, differences in average LOS were even greater for those treated with early dialysis versus CM (∆ of + 2-days for hospitalizations 1-month from the index eGFR, Fig. A, lower panel). In primary analyses that considered a fixed time of hospitalization from the index eGFR, dialysis patients &amp;gt;20-years old had longer average LOS versus those treated with CM, with differences increasing with older age (∆ of + 1.25-days for hospitalizations for patients 70-years old; Fig. 1B, upper panel). In secondary analyses, differences in average LOS were even greater for those treated with early dialysis versus CM (∆ of + 1.87-days for patients 70-years old, Fig. 1B, lower panel). CONCLUSION In a nationally representative CKD cohort, compared with dialysis, those treated with CM as an alternative patient-centered treatment strategy had shorter LOS across varying time points and age groups. Further studies are needed to examine the comparative effectiveness of CM versus dialysis transition on CKD outcomes.

MP39-06 EVALUATING THE REAL-WORLD PAYER AND PATIENT COSTS OF BPH SURGICAL MANAGEMENT

You have accessJournal of UrologyCME1 May 2022MP39-06 EVALUATING THE REAL-WORLD PAYER AND PATIENT COSTS OF BPH SURGICAL MANAGEMENT Kevin Wymer, Gopal Narang, Austen Slade, Vidit Sharma, Viengneesee Thao, Bijan Borah, Marcelino Rivera, Scott Cheney, and Mitchell Humphreys Kevin WymerKevin Wymer More articles by this author , Gopal NarangGopal Narang More articles by this author , Austen SladeAusten Slade More articles by this author , Vidit SharmaVidit Sharma More articles by this author , Viengneesee ThaoViengneesee Thao More articles by this author , Bijan BorahBijan Borah More articles by this author , Marcelino RiveraMarcelino Rivera More articles by this author , Scott CheneyScott Cheney More articles by this author , and Mitchell HumphreysMitchell Humphreys More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002599.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: A multitude of surgical treatment options exist for BPH - with differences in the level of invasiveness, complications, and durability. Despite the high prevalence of BPH treatment and its significant economic impact, limited data are available comparing the financial burden of specific surgical interventions. We therefore sought to compare out-of-pocket (OOP) and health plan paid (HPP) costs of common surgical treatments for BPH. METHODS: We conducted a retrospective cohort study using administrative claims data from the OptumLabs Data Warehouse, which includes data for commercially insured and Medicare Advantage enrollees. Our cohort consisted of patients with a BPH diagnosis who underwent simple prostatectomy (SP), TURP, HoLEP, PVP, UroLift, or Rezum from 2015-2019. Unadjusted average OPP and HPP costs for different follow-up timeframes by treatment type were included. Our analysis was limited to patients continuously enrolled in their health plan for at least 1 year pre- and post-procedure, ages 30-80. Costs were inflation-adjusted to 2020 U.S. dollars using the Consumer Price Index. One-way ANOVA was performed to evaluate for differences in cost. RESULTS: In total, 21,946 patients were included in the analysis. Total HPP and OOP costs for each treatment type by follow-up year are shown in Figure 1. For year 1 (which included the index procedure), there was significant variation in both HPP and OPP costs, with SP associated with highest costs followed by TURP, HoLEP, PVP, UroLift, and Rezum (p <.001). These differences decreased with longer follow up in year 2 and years 3–5, with minimal differences in costs for all procedures except for Rezum which was associated with significantly lower HPP costs (p <.01). There was no significant difference in patient OOP costs among all procedures at 3-5 years (p=.055). CONCLUSIONS: BPH treatment modality has a significant impact on patient and system level costs. These differences are most pronounced within the first year of surgical management, likely related to index procedural costs, complications, and convalescence, and decrease with further follow up. Minimally invasive options, such as Rezum, may offer initial cost reductions; however, such data must be interpreted cautiously without correlation to clinical information, including gland size. Source of Funding: None © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e666 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Kevin Wymer More articles by this author Gopal Narang More articles by this author Austen Slade More articles by this author Vidit Sharma More articles by this author Viengneesee Thao More articles by this author Bijan Borah More articles by this author Marcelino Rivera More articles by this author Scott Cheney More articles by this author Mitchell Humphreys More articles by this author Expand All Advertisement PDF DownloadLoading ...

Artificial Intelligence for Inflammatory Bowel Diseases (IBD); Accurately Predicting Adverse Outcomes Using Machine Learning

BackgroundInflammatory Bowel Diseases with its complexity and heterogeneity could benefit from the increased application of Artificial Intelligence in clinical management.AimTo accurately predict adverse outcomes in patients with IBD using advanced computational models in a nationally representative dataset for potential use in clinical practice.MethodsWe built a training model cohort and validated our result in a separate cohort. We used LASSO and Ridge regressions, Support Vector Machines, Random Forests and Neural Networks to balance between complexity and interpretability and analyzed their relative performances and reported the strongest predictors to the respective models. The participants in our study were patients with IBD selected from The OptumLabs® Data Warehouse (OLDW), a longitudinal, real-world data asset with de-identified administrative claims and electronic health record (EHR) data.ResultsWe included 72,178 and 69,165 patients in the training and validation set, respectively. In total, 4.1% of patients in the validation set were hospitalized, 2.9% needed IBD-related surgeries, 17% used long-term steroids and 13% of patients were initiated with biological therapy. Of the AI models we tested, the Random Forest and LASSO resulted in high accuracies (AUCs 0.70–0.92). Our artificial neural network performed similarly well in most of the models (AUCs 0.61–0.90).ConclusionsThis study demonstrates feasibility of accurately predicting adverse outcomes using complex and novel AI models on large longitudinal data sets of patients with IBD. These models could be applied for risk stratification and implementation of preemptive measures to avoid adverse outcomes in a clinical setting.

A methodology for identifying behavioral health advanced practice registered nurses in administrative claims.

Advanced practice registered nurses (APRNs) play an increased role in mental illness treatment. Health services research that uses claims to study mental health is often limited because behavioral health nurse practitioners (i.e., APRNs who specialize in mental illness, also known as psychiatric mental health APRNs) cannot be easily identified in claims data. We describe two methodologies to identify behavioral health APRNs in administrative claims. DATA SOURCES/STUDY SETTING (W/ HOSPITAL/INSTITUTION SETTING ANONYMIZED): We use 2010-2018 claims from the traditional Medicare fee-for-service program along with 2010-2019 commercial claims and Medicare Advantage data from the OptumLabs Data Warehouse (OLDW). Self-reported specialty data from the National Plan & Provider Enumeration System (NPPES) were used for validation. For each APRN, we calculated the percentage of visit diagnoses and of prescriptions in each database that were for mental health and classified those with ≥80% as behavioral health APRNs. We validated our definition with NPPES self-reported specialty for Medicare data. Not applicable. Among APRNs with 10+ visits, 10,978 (8.1%) in Medicare and 9829 (11.7%) in commercial claims data met our visit-based criteria as behavioral health APRNs. Among APRNs with 10+ prescriptions, 8160 (6.2%) in Medicare and 16,538 (9.0%) in commercial claims data met our prescription-based criteria as behavioral health APRNs. Among the APRNs who self-reported they were behavioral health APRNs, 92.8% and 90.5% met our visit-based and prescription-based criteria, respectively. We present and validate two methods of identifying behavioral health APRNs in claims that can be used by other researchers.

The effects of patient out-of-pocket costs for insulin on medication adherence and health care utilization in patients with commercial insurance; 2007-2018.

BACKGROUND: High out-of-pocket costs (OOPCs) for insulin can lead to cost-related nonadherence and poor outcomes, prompting payers to limit insulin OOPCs. However, data are scarce on whether insulin OOPCs at policy-relevant levels is associated with improved adherence and outcomes. OBJECTIVE: To identify associations between insulin OOPCs and insulin adherence, noninsulin antihyperglycemic (AHG) medication adherence, and diabetes-related emergency department (ED) visits and hospitalizations. METHODS: This retrospective cohort study was conducted using OptumLabs Data Warehouse, a longitudinal, real-world data asset with deidentified administrative claims and electronic health record data. Individuals with type 1 diabetes (T1D) or type 2 diabetes (T2D), insulin use on January 1 of a study year (index date: 2007-2018), continuous commercial health plan eligibility 12 months pre-index and post-index date, and at least 1 insulin claim during the 12-month follow-up period were included. Average insulin OOPCs per 30-day supply in the follow-up period was identified and categorized ($0, > $0-$20 [referent group], > $20-$35, > $35-$50, and > $50). The proportion of patients with a gap in insulin supply of 60 or more continuous days, AHG nonadherence per modified proportion of days covered less than 0.80, and a diabetes-related ED visit or hospitalization were identified and compared by insulin OOPC category vs more than $0 to $20 using pairwise chi-square tests and multivariable logistic regression. RESULTS: The study included 21,085 individuals with T1D and 72,512 with T2D. Patients with average OOPCs more than $50 were more likely to have a gap in insulin supply vs those with OOPCs more than $0 to $20, with an odds ratio (OR) of 1.14 (95% CI =1.05-1.24) and 1.38 (95% CI = 1.32-1.45) for T1D and T2D, respectively. Those with T2D and OOPCs more than $35 were also more likely to have a 60-day gap in insulin supply (OR 1.17; 95% CI = 1.11-1.23). Odds of having a diabetes-related hospitalization or ED visit did not increase with higher OOPCs; rather, associations tended to be inverse. Nonadherence to AHG medications in the T2D cohort was higher with insulin OOPCs more than $20 vs those more than $0-$20 (P < 0.05 for all). CONCLUSIONS: Individuals with T2D were more likely to have a 60-day gap in insulin supply when the OOPC was more than $35 per 30-day supply and with the OOPC more than $50 in those with T1D. These findings suggest that health plans can facilitate adherence to insulin therapy and possibly to noninsulin AHG medications by protecting patients with diabetes from experiencing high insulin OOPC. A study with a longer follow-up period is warranted to fully assess ED and hospitalization outcomes. DISCLOSURES: This study was funded by the Robert Wood Johnson Foundation, Health Data for Action Research Program. The study sponsor played no role in the design or conduct of this study. The views expressed here do not necessarily reflect the views of the Foundation.

Association of Mood Disorders, Substance Abuse, and Anxiety Disorders in Children and Teens With Serious Structural Eye Diseases

We sought to evaluate the association between 5 eye diseases (including glaucoma, cataract, congenital optic nerve disease, congenital retinal disease, and blindness/low vision) and mental illness in a pediatric population. Cross-sectional study. A de-identified commercial insurance claims database, OptumLabs Data Warehouse, between January 1, 2007, and December 31, 2018, was used. Children and teens less than 19 years of age at the time of eye diagnosis were included. Demographics and mental illness claims were compared, looking at the association of mental illness and eye disease claims. A total of 11,832,850 children and teens were included in this study with mean age of 8.04 ± 5.94 years at the first claim. Of the patients with at least 1 of the 5 eye diseases (n=180,297), 30.5% had glaucoma (n=54,954), 9.5% had cataract (n=17,214), 21.4% had congenital optic nerve disease (n=38,555), 26.9% had congenital retinal disease (n=48,562), and 25.9% had blindness or low vision (n=46,778). There was a statistically significant association, after adjusting for confounding variables, between at least 1 of the 5 eye diseases and schizophrenia disorder (OR=1.54, 95% CI=1.48-1.61, P < .001), anxiety disorder (OR=1.45, 95% CI=1.43-1.48, P < .001), depressive disorder (OR=1.27, 95% CI=1.25-1.29, P < .001), and bipolar disorder (OR=1.27, 95% CI=1.21-1.31, P < .001), but a reversed association with substance use disorder (OR=0.88, 95% CI=0.86-0.90, P < .001). We found associations between eye disease in children and teens and mental illness. Understanding these relationships may improve mental illness screening and treatment in the pediatric population.

Association of Strabismus With Mood Disorders, Schizophrenia, and Anxiety Disorders Among Children

Children with strabismus have poorer functional vision and decreased quality of life than those without strabismus. To evaluate the association between strabismus and mental illness among children. This cross-sectional study analyzed claims data from the OptumLabs Data Warehouse, a longitudinal deidentified commercial insurance claims database, from 12 005 189 patients enrolled in the health plan between January 1, 2007, and December 31, 2017. Eligibility criteria included age younger than 19 years at the time of strabismus diagnosis, enrollment in the health plan between 2007 and 2018, and having at least 1 strabismus claim based on International Classification of Diseases, Ninth Revision, Clinical Modification and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Clinical Modification codes. Controls were children in the same database with no eye disease codes other than refractive error reported. Demographic characteristics and mental illness claims were compared. Statistical analysis was conducted from December 1, 2018, to July 31, 2021. Presence of mental illness claims. Among the 12 005 189 patients (6 095 523 boys [50.8%]; mean [SD] age, 8.0 [5.9] years) in the study, adjusted odds ratios for the association of mental illnesses with strabismus were 2.01 (95% CI, 1.99-2.04) for anxiety disorder, 1.83 (95% CI, 1.76-1.90) for schizophrenia, 1.64 (95% CI, 1.59-1.70) for bipolar disorder, 1.61 (95% CI, 1.59-1.63) for depressive disorder, and 0.99 (95% CI, 0.97-1.02) for substance use disorder. There was a moderate association between each strabismus type (esotropia, exotropia, and hypertropia) and anxiety disorder, schizophrenia, bipolar disorder, and depressive disorder; odds ratios ranged from 1.23 (95% CI, 1.17-1.29) for the association between esotropia and bipolar disorder to 2.70 (95% CI, 2.66-2.74) for the association between exotropia and anxiety disorder. This cross-sectional study suggests that there was a moderate association between strabismus and anxiety disorder, schizophrenia, bipolar disorder, and depressive disorder but not substance use disorder. Recognizing that these associations exist should encourage mental illness screening and treatment for patients with strabismus.

Association Between Generic-to-Generic Levothyroxine Switching and Thyrotropin Levels Among US Adults

Switching among generic levothyroxine sodium products made by different manufacturers typically occurs at the pharmacy and may affect serum thyrotropin (TSH) levels. To compare TSH levels between patients who continued taking the same sourced generic levothyroxine product and those who switched. This comparative effectiveness research study with 1:1 propensity matching used data from OptumLabs Data Warehouse, a national administrative claims database linked to laboratory test results. Adults aged 18 years or older were included if they filled a generic levothyroxine prescription between January 1, 2008, and June 30, 2019, and had a stable drug dose, the same drug manufacturer, and a normal TSH level (0.3-4.4 mIU/L) for at least 3 months before either continuing to take the same product or switching among generic levothyroxine products (index date). Patients were excluded if they were pregnant, had diagnosed hypopituitarism or hyperthyroidism, or had a medical condition or used medications that could affect thyrotropin levels. They were also excluded if they filled a prescription for other forms of thyroid replacement therapy between 6 months before the index date and when the first TSH level was obtained 6 weeks to 12 months after the index date. Data were analyzed from December 1, 2019, to November 24, 2021. Proportion of individuals with a normal (0.3-4.4 mIU/L) or markedly abnormal (<0.1 or >10.0 mIU/L) TSH level using the first available laboratory result 6 weeks to 12 months after the index date. A propensity score model was developed to minimize confounding using logistic regression with the binary outcome of continuing the same sourced levothyroxine product vs switching generic levothyroxine. Covariates were demographics, comorbidities, and baseline TSH level. The balance among the treatment groups was evaluated by comparing standardized mean differences of baseline covariates between the groups. A total of 15 829 patients filled generic levothyroxine (mean [SD] age, 58.9 [14.6] years; 73.4% [11 624] were women; 4.5% [705] were Asian, 10.2% [1617] were Black, 11.4% [1801] were Hispanic, and 71.4% [11 295] were White individuals); of these patients, 56.3% [8905] received a daily levothyroxine dose of 50 μg or less. A total of 13 049 patients (82.4%) continued taking the same sourced preparation, and 2780 (17.6%) switched among generic levothyroxine preparations. Among 2780 propensity-matched patient pairs, the proportion of patients with a normal TSH level after the index date was 82.7% (2298) among nonswitchers and 84.5% (2348) among switchers (risk difference, -0.018; 95% CI, -0.038 to 0.002; P = .07). The proportion of patients with a markedly abnormal TSH level after the index date was 3.1% (87) among nonswitchers and 2.5% (69) among switchers (risk difference, 0.007; 95% CI, -0.002 to 0.015; P = .14). The mean (SD) TSH levels after the index date were 2.7 (2.3) mIU/L among nonswitchers and 2.7 (3.3) mIU/L among switchers (P = .94). Results of this comparative effectiveness research study suggest that switching among different generic levothyroxine products was not associated with clinically significant changes in TSH level. These findings conflict with the current guideline recommendation that warns clinicians about potential changes in TSH level associated with switching among levothyroxine products sourced from different manufacturers.