Trends in central nervous system-active polypharmacy among people with multiple sclerosis.

BACKGROUND: People with multiple sclerosis (pwMS) are at risk of concurrently using multiple central nervous system (CNS)-active drugs, yet the prevalence of CNS-active polypharmacy remains unmeasured in pwMS. OBJECTIVE: The objective is to measure the prevalence of CNS-active polypharmacy in pwMS. METHODS: This serial, cross-sectional study measured CNS-active polypharmacy in people with MS in the United States from 2008 to 2021 using insurance claims data. CNS-active polypharmacy was defined as the concurrent prescription of ⩾3 CNS-active drugs for >30 continuous days. CNS-active drugs included antidepressants, antiepileptics, antipsychotics, benzodiazepines, nonbenzodiazepine benzodiazepine receptor agonist hypnotics, opioids, and skeletal muscle relaxants. RESULTS: The number of subjects included at each time point ranged from 23,917 subjects in 2008 to 55,797 subjects in 2021. In 2021, subjects with CNS-active polypharmacy were more likely to be 46-65 years of age and have CNS-related comorbidities compared to those without CNS-active polypharmacy. From 2008 to 2021, the age-adjusted prevalence of CNS-active polypharmacy among female subjects increased from 19.8% (95% confidence interval (CI) = 19.1-20.4) to 26.4% (95% CI = 25.9-26.8) versus 15.9% (95% CI = 14.8-17.0) to 18.6% (95% CI = 17.9-19.2) in male subjects. CONCLUSION: The prevalence of CNS-active polypharmacy has increased among people with MS with a growing disparity by sex.

Contemporary Analysis of Reexcision and Conversion to Mastectomy Rates and Associated Healthcare Costs for Women Undergoing Breast-Conserving Surgery.

PURPOSE: This study was designed to provide a comprehensive and up-to-date understanding of population-level reoperation rates and incremental healthcare costs associated with reoperation for patients who underwent breast-conserving surgery (BCS). METHODS: This is a retrospective cohort study using Merative™ MarketScan® commercial insurance data and Medicare 5% fee-for-service claims data. The study included females aged 18-64 years in the commercial cohort and females aged 18 years and older in the Medicare cohort, who underwent initial BCS for breast cancer in 2017-2019. Reoperation rates within a year of the initial BCS and overall 1-year healthcare costs stratified by reoperation status were measured. RESULTS: The commercial cohort included 17,129 women with a median age of 55 (interquartile range [IQR] 49-59) years, and the Medicare cohort included 6977 women with a median age of 73 (IQR 69-78) years. Overall reoperation rates were 21.1% (95% confidence interval [CI] 20.5-21.8%) for the commercial cohort and 14.9% (95% CI 14.1-15.7%) for the Medicare cohort. In both cohorts, reoperation rates decreased as age increased, and conversion to mastectomy was more prevalent among younger women in the commercial cohort. The mean healthcare costs during 1 year of follow-up from the initial BCS were $95,165 for the commercial cohort and $36,313 for the Medicare cohort. Reoperations were associated with 24% higher costs in both the commercial and Medicare cohorts, which translated into $21,607 and $8559 incremental costs, respectively. CONCLUSIONS: The rates of reoperation after BCS have remained high and have contributed to increased healthcare costs. Continuing efforts to reduce reoperation need more attention.

Indirect impact of the COVID-19 pandemic on the care and outcomes of people with MS: A combined survey and insurance claims study.

BACKGROUND: In the context of the COVID-19 pandemic, people with multiple sclerosis (pwMS) have been particularly vulnerable to adverse outcomes due to increased risk of severe infection and/or widespread disruptions in care. The CopeMS study led by The University of Texas at Austin and the MS Association of America investigates the long-term impact of the COVID-19 pandemic on healthcare access, disease modifying therapy (DMT) utilization and outcomes of pwMS. METHODS: This retrospective cohort analysis used Optum's de-identified Clinformatics® Data Mart Database (CDM), a large de-identified administrative healthcare claims database to identify pwMS who were continuously enrolled from 01/01/2019 to 12/31/2020 and assessed changes in the utilization of DMTs and healthcare services during the COVID-19 pandemic compared to the year prior. Additionally, a national survey of pwMS and healthcare providers (HCPs) was conducted to further understand the indirect impact of the pandemic on healthcare resource utilization (HCRU), outcomes and prescription patterns. RESULTS: Out of 529 pwMS in our national survey, over 47 % reported that their overall health and neurologic symptoms had deteriorated during the COVID-19 pandemic, with increased anxiety, and inability to maintain exercise habits as leading perceived causes for worsening. Survey respondents reported widespread disruption of MS-related services during the pandemic. In the Optum database, we identified 39,209 pwMS validating inclusion criteria. We observed a decrease in the utilization of MS-related services in 2020 compared to 2019. Significantly fewer pwMS had visits with their neurologist, primary care provider, physical or occupational therapist despite an increased utilization of telemedicine services. Fewer pwMS had magnetic resonance imaging (MRI) studies of the brain or spinal cord during the pandemic. Only 22.2 % of HCPs surveyed agreed that the perceived risk of more severe COVID-19 infection on a specific DMT influenced their therapeutic decisions. In the Optum database, individuals with an established diagnosis of MS prior to 2019 saw decreases in utilization of platform and moderate efficacy DMTs. In this group, those over the age of 55 saw a decrease in utilization of B-cell therapies (rate ratio 0.79, CI 0.75-0.83), whereas individuals under the age of 55 saw an increase in utilization of B-cell therapies (rate ratio 1.10, CI 1.03-1.17). We did not see any difference in rates of starting DMTs in persons diagnosed in 2019 prior to the pandemic and those diagnosed in 2020. Compared to 2019, B-cell therapies were prescribed more frequently in pwMS diagnosed in 2020 who were younger than 55 or commercially insured (rate ratio 1.35, CI 1.11-1.63). CONCLUSION: The COVID-19 pandemic was associated with perceived worsening of neurological symptoms in pwMS. Despite the expansion of telemedicine, we observed decreased access to healthcare services important to the comprehensive care of pwMS. Additionally, we observed changes in DMT utilization in pwMS during the pandemic, particularly in older adults with an established diagnosis of MS.

Trends and Seasonality of Emergency Department Visits and Hospitalizations for Suicidality Among Children and Adolescents in the US from 2016 to 2021.

Importance: The detection of seasonal patterns in suicidality should be of interest to clinicians and US public health officials, as intervention efforts can benefit by targeting periods of heightened risk. Objectives: To examine recent trends in suicidality rates, quantify the seasonality in suicidality, and demonstrate the disrupted seasonality patterns during the spring 2020 COVID-19-related school closures among US children and adolescents. Design, Setting, and Participants: This population-based, descriptive cross-sectional study used administrative claims data from Optum's deidentifed Clinformatics Data Mart Database. Participants included children aged 10 to 12 years and adolescents aged 13 to 18 years who were commercially insured from January 1, 2016, to December 31, 2021. Statistical analysis was conducted between April and November 2022. Exposures: Month of the year and COVID-19 pandemic. Main Outcomes and Measures: Rates and seasonal patterns of emergency department (ED) visits and hospitalizations for suicidality. Results: The analysis included 73 123 ED visits and hospitalizations for suicidality reported between 2016 and 2021. Among these events, 66.1% were reported for females, and the mean (SD) age at the time of the event was 15.4 (2.0) years. The mean annual incidence of ED visits and hospitalizations for suicidality was 964 per 100 000 children and adolescents (95% CI, 956-972 per 100 000), which increased from 760 per 100 000 (95% CI, 745-775 per 100 000) in 2016 to 1006 per 100 000 (95% CI, 988-10 024 per 100 000) in 2019, with a temporary decrease to 942 per 100 000 (95% CI, 924-960 per 100 000) in 2020 and a subsequent increase to 1160 per 100 000 (95% CI, 1140-1181 per 100 000) in 2021. Compared with January, seasonal patterns showed peaks in April (incidence rate ratio [IRR], 1.15 [95% CI, 1.11-1.19]) and October (IRR, 1.24 [95% CI, 1.19-1.29]) and a nadir in July (IRR, 0.63 [95% CI, 0.61-0.66]) during pre-COVID-19 years and 2021. However, during the spring of 2020, which coincided with school closures, seasonal patterns were disrupted and April and May exhibited the lowest rates. Conclusions and Relevance: The findings of this study indicated the presence of seasonal patterns and an observed unexpected decrease in suicidality among children and adolescents after COVID-19-related school closures in March 2020, which suggest a potential association between suicidality and the school calendar.

COVID-19 severity scale for claims data research.

OBJECTIVE: To create and validate a methodology to assign a severity level to an episode of COVID-19 for retrospective analysis in claims data. DATA SOURCE: Secondary data obtained by license agreement from Optum provided claims records nationally for 19,761,754 persons, of which, 692,094 persons had COVID-19 in 2020. STUDY DESIGN: The World Health Organization (WHO) COVID-19 Progression Scale was used as a model to identify endpoints as measures of episode severity within claims data. Endpoints used included symptoms, respiratory status, progression to levels of treatment and mortality. DATA COLLECTION/EXTRACTION METHODS: The strategy for identification of cases relied upon the February 2020 guidance from the Centers for Disease Control and Prevention (CDC). PRINCIPAL FINDINGS: A total of 709,846 persons (3.6%) met the criteria for one of the nine severity levels based on diagnosis codes with 692,094 having confirmatory diagnoses. The rates for each level varied considerably by age groups, with the older age groups reaching higher severity levels at a higher rate. Mean and median costs increased as severity level increased. Statistical validation of the severity scales revealed that the rates for each level varied considerably by age group, with the older ages reaching higher severity levels (p < 0.001). Other demographic factors such as race and ethnicity, geographic region, and comorbidity count had statistically significant associations with severity level of COVID-19. CONCLUSION: A standardized severity scale for use with claims data will allow researchers to evaluate episodes so that analyses can be conducted on the processes of intervention, effectiveness, efficiencies, costs and outcomes related to COVID-19.

Does hospital location matter? Association of neighborhood socioeconomic disadvantage with hospital quality in US metropolitan settings.

An aspect of a hospital's location, such as its degree of socioeconomic disadvantage, could potentially affect quality ratings of the hospital; yet, few studies have granularly explored this relationship in United States (US) metropolitan areas characterized by a wide breadth of socioeconomic disparities across neighborhoods. An understanding of the effect of neighborhood socioeconomic disadvantage on hospital quality of care is informative for targeting resources in poor neighborhoods. We assessed the association of neighborhood socioeconomic disadvantage with hospital quality of care across several areas of quality (including mortality, readmission, safety, patient experience, effectiveness of care, summary and overall star rating) in US metropolitan areas. Hospitals in the most disadvantaged neighborhoods, compared to hospitals in the least disadvantaged neighborhoods, had worse mortality scores, readmission scores, safety of care scores, patient experience of care scores, effectiveness of care scores, summary scores and overall star rating. Timeliness of care and efficient use of imaging scores were not strongly associated with neighborhood socioeconomic disadvantage; although, future studies are needed to validate this finding. Policymakers could target innovative strategies for improving neighborhood socioeconomic conditions in more disadvantaged areas, as this may improve hospital quality.

Factors Associated With COVID-19 Death in the United States: Cohort Study.

BACKGROUND: Since the initial COVID-19 cases were identified in the United States in February 2020, the United States has experienced a high incidence of the disease. Understanding the risk factors for severe outcomes identifies the most vulnerable populations and helps in decision-making. OBJECTIVE: This study aims to assess the factors associated with COVID-19-related deaths from a large, national, individual-level data set. METHODS: A cohort study was conducted using data from the Optum de-identified COVID-19 electronic health record (EHR) data set; 1,271,033 adult participants were observed from February 1, 2020, to August 31, 2020, until their deaths due to COVID-19, deaths due to other reasons, or the end of the study. Cox proportional hazards models were constructed to evaluate the risks for each patient characteristic. RESULTS: A total of 1,271,033 participants (age: mean 52.6, SD 17.9 years; male: 507,574/1,271,033, 39.93%) were included in the study, and 3315 (0.26%) deaths were attributed to COVID-19. Factors associated with COVID-19-related death included older age (80 vs 50-59 years old: hazard ratio [HR] 13.28, 95% CI 11.46-15.39), male sex (HR 1.68, 95% CI 1.57-1.80), obesity (BMI 40 vs <30 kg/m2: HR 1.71, 95% CI 1.50-1.96), race (Hispanic White, African American, Asian vs non-Hispanic White: HR 2.46, 95% CI 2.01-3.02; HR 2.27, 95% CI 2.06-2.50; HR 2.06, 95% CI 1.65-2.57), region (South, Northeast, Midwest vs West: HR 1.62, 95% CI 1.33-1.98; HR 2.50, 95% CI 2.06-3.03; HR 1.35, 95% CI 1.11-1.64), chronic respiratory disease (HR 1.21, 95% CI 1.12-1.32), cardiac disease (HR 1.10, 95% CI 1.01-1.19), diabetes (HR 1.92, 95% CI 1.75-2.10), recent diagnosis of lung cancer (HR 1.70, 95% CI 1.14-2.55), severely reduced kidney function (HR 1.92, 95% CI 1.69-2.19), stroke or dementia (HR 1.25, 95% CI 1.15-1.36), other neurological diseases (HR 1.77, 95% CI 1.59-1.98), organ transplant (HR 1.35, 95% CI 1.09-1.67), and other immunosuppressive conditions (HR 1.21, 95% CI 1.01-1.46). CONCLUSIONS: This is one of the largest national cohort studies in the United States; we identified several patient characteristics associated with COVID-19-related deaths, and the results can serve as the basis for policy making. The study also offered directions for future studies, including the effect of other socioeconomic factors on the increased risk for minority groups.

The Impact of Personal and Historical Factors That Contribute to Medicare Readmissions.

Medicare readmissions from the 5% national sample of Medicare Fee For Service claims were assessed to identify the contribution of various demographic or personal health history risk factors to the liklihood of readmission within 30 days of discharge. The Medicare population was evaluated as 2 cohorts based on their eligibility status: age (71.9%) or disability (18.1%). Roughly 12% of admissions for the aged population resulted in a readmission within 30 days, whereas ∼18% was true of the disabled population. Patients with a history of frequent emergency department visits or an urgent index admission had an increased risk for a readmission in both groups of beneficiaries. An important indicator for readmission risk was discharge status from the index hospital stay. In both categories of beneficiaries, individuals who were discharged against medical advice were 1.6 times more likely to experience a readmission. Most importantly, personal and social determinants of health (SDOH) documented preadmission and postdischarge were more evident for the disabled population than the aged. Furthermore, when pre- and postadmission spans for SDOH conditions were examined, (6 months before initial admission to 30 days postadmission), both the aged and disabled populations were statistically significantly more likely to experience readmissions if they had an SDOH diagnosis.

Analysis of COVID-19 Infection and Mortality Among Patients With Psychiatric Disorders, 2020.

Importance: People with major psychiatric disorders are more likely to have comorbidities associated with worse outcomes of COVID-19. This fact alone could determine greater vulnerability of people with major psychiatric disorders to COVID-19. Objective: To assess the odds of testing positive for and mortality from COVID-19 among and between patients with schizophrenia, mood disorders, anxiety disorders and a reference group in a large national database. Design, Setting, and Participants: This cross-sectional study used an electronic health record data set aggregated from many national sources in the United States and licensed from Optum with current and historical data on patients tested for COVID-19 in 2020. Three psychiatric cohorts (patients with schizophrenia, mood disorders, or anxiety disorders) were compared with a reference group with no major psychiatric conditions. Statistical analysis was performed from March to April 2021. Exposure: The exposures observed include lab-confirmed positivity for COVID-19 and mortality. Main Outcomes and Measures: The odds of testing positive for COVID-19 in 2020 and the odds of death from COVID-19 were measured. Results: The population studied included 2 535 098 unique persons, 3350 with schizophrenia, 26 610 with mood disorders, and 18 550 with anxiety disorders. The mean (SD) age was 44 (23) years; 233 519 were non-Hispanic African American, 1 583 440 were non-Hispanic Caucasian; and 1 580 703 (62%) were female. The schizophrenia cohort (positivity rate: 9.86%; adjusted OR, 0.90 [95% CI, 0.84-0.97]) and the mood disorder cohort (positivity rate: 9.86%; adjusted OR, 0.93 [95% CI, 0.87-0.99]) had a significantly lower rate of positivity than the anxiety disorder cohort (positivity rate: 11.17%; adjusted OR, 1.05 [95% CI, 0.98-1.12) which was closer to the reference group (11.91%). After fully adjusting for demographic factors and comorbid conditions, patients with schizophrenia were nearly 4 times more likely to die from the disease than the reference group (OR, 3.74; 95% CI, 2.66-5.24). The mood disorders COVID-19 cohort had a 2.76 times greater odds of mortality than the reference group (OR, 2.76; 95% CI, 2.00-3.81), and the anxiety disorders cohort had a 2.39 times greater odds of mortality than the reference group (OR, 2.39; 95% CI, 1.68-3.27). Conclusions and Relevance: By examining a large database while controlling for multiple confounding factors such as age, race and ethnicity, and comorbid medical conditions, the present study found that patients with schizophrenia had much increased odds of mortality by COVID-19.

Utilization and Availability of Advanced Imaging in Patients With Acute Ischemic Stroke.

BACKGROUND: Recent clinical trials have established the efficacy of endovascular stroke therapy and intravenous thrombolysis using advanced imaging, particularly computed tomography perfusion (CTP). The availability and utilization of CTP for patients and hospitals that treat acute ischemic stroke (AIS), however, is uncertain. METHODS: We performed a retrospective cross-sectional analysis using 2 complementary Medicare datasets, full sample Texas and 5% national fee-for-service data from 2014 to 2017. AIS cases were identified using International Classification of Diseases, NinthRevision and International Classification of Diseases, Tenth Revision coding criteria. Imaging utilization performed in the initial evaluation of patients with AIS was derived using Current Procedural Terminology codes from professional claims. Primary outcomes were utilization of imaging in AIS cases and the change in utilization over time. Hospitals were defined as imaging modality-performing if they submitted at least 1 claim for that modality per calendar year. The National Medicare dataset was used to validate state-level findings, and a local hospital-level cohort was used to validate the claims-based approach. RESULTS: Among 50 797 AIS cases in the Texas Medicare fee-for-service cohort, 64% were evaluated with noncontrast head CT, 17% with CT angiography, 3% with CTP, and 33% with magnetic resonance imaging. CTP utilization was greater in patients treated with endovascular stroke therapy (17%) and intravenous thrombolysis (9%). CT angiography (4%/y) and CTP (1%/y) utilization increased over the study period. These findings were validated in the National dataset. Among hospitals in the Texas cohort, 100% were noncontrast head CT-performing, 77% CT angiography-performing, and 14% CTP-performing in 2017. Most AIS cases (69%) were evaluated at non-CTP-performing hospitals. CTP-performing hospitals were clustered in urban areas, whereas large regions of the state lacked immediate access. CONCLUSIONS: In state-wide and national Medicare fee-for-service cohorts, CTP utilization in patients with AIS was low, and most patients were evaluated at non-CTP-performing hospitals. These findings support the need for alternative means of screening for AIS recanalization therapies.

The association of social determinants of health with health outcomes.

OBJECTIVES: This study explored the contributions of social determinants of health (SDOH) to measures of population health-specifically cost, hospitalization rates, rate of emergency department utilization, and health status-in Texas. STUDY DESIGN: The study associated common SDOH metrics from public data sources (county specific) with health plan enrollment data (including demographics, counties, and zip codes) and medical and pharmaceutical annual claims data. METHODS: Following correlation analyses to reduce variables, the contribution of each SDOH individually and by category to the health outcomes was evaluated. Separate matrices for age populations (under age 19, general population [all ages], and ≥ 65 years) were created with assigned weights of influence for categories and the factors within each category. RESULTS: The contributions of the categories varied by population, confirming that different SDOH influence populations to varying degrees. This was reflected in each model. The largest contributor to cost for the general population and for the group 65 years and older was factors grouped as health outcomes (such as perceived health), at 43.5% contribution and 37.7% contribution, respectively. Yet for the population younger than 19 years, the largest contributor to cost was socioeconomic factors (such as unemployment rate), at 40.2%. The other performance measures also varied by population and the mix and weight of determinants. CONCLUSIONS: This study and the developed population-based matrices can provide a valuable framework for reporting the impact of SDOH on health care quality. The variation suggests the need for further research on how age groups react to the social environment.

Tyrosine Kinase Inhibitors and the Relationship With Adherence, Costs, and Health Care Utilization in Commercially Insured Patients With Newly Diagnosed Chronic Myeloid Leukemia: A Retrospective Claims-Based Study.

OBJECTIVE: To examine the association among tyrosine kinase inhibitor (TKI) out-of-pocket costs, adherence, and health care costs and utilization in a large group of commercially insured patients with chronic myeloid leukemia (CML). MATERIALS AND METHODS: Patients with CML aged 18 to 64 years were identified using IBM MarketScan Commercial Database between April 1, 2011 and December 31, 2014. Patients were required to be continuously enrolled 3 months before and 12 months after TKI (imatinib, dasatinib, or nilotinib) initiation. TKI adherence is estimated using the proportion of days covered (PDC), defined as the percentage of the PDC by the prescription fill during the 12-month study period (adherent patients have PDC ≥80%). Health care cost differences between adherent and nonadherent patients were estimated using generalized linear models. Health care utilization was compared using negative binomial regression models. All models were controlled for potential confounding factors. RESULTS: The study sample consisted of 863 patients, where 355 (41.1%) patients were classified as adherent. Over the study period, nonadherent patients incurred US$10,974 more in medical costs (P<0.001), and US$1663 more in non-TKI pharmacy costs (P<0.01). Adherent patients incurred US$28,184 more in TKI pharmacy costs (P<0.001) that resulted in US$18,305 more in overall total health care costs (P<0.001). Adherent patients, however, were estimated to be less likely to have all-cause hospitalizations (incidence rate ratio, 0.32; P<0.001), or CML-specific hospitalizations (incidence rate ratio, 0.31; P<0.01). CONCLUSIONS: Patients with CML with better adherence experienced fewer hospitalizations, resulting in medical service cost savings. These lower medical costs, however, were more than offset by higher TKI medication costs observed during the first year of TKI therapy.

Tyrosine Kinase Inhibitors Initiation, Cost Sharing, and Health Care Utilization in Patients with Newly Diagnosed Chronic Myeloid Leukemia: A Retrospective Claims-Based Study.

BACKGROUND: For newly diagnosed chronic myeloid leukemia (CML) patients, early access to tyrosine kinase inhibitors (TKIs) is a consistent predictor of adherence and optimal response. The expense of targeted therapies, however, may result in high out-of-pocket costs for initiating therapy that could be a barrier to starting treatment. OBJECTIVE: To examine the association between TKI out-of-pocket costs, initiation, and health care utilization and costs among patients who initiated TKI within 12 months after initial CML diagnosis. METHODS: Individuals aged 18-64 years with an initial diagnosis of CML were identified in the IBM MarketScan Commercial Database between April 11, 2011, and December 31, 2014. The association between cost sharing and TKI initiation was evaluated using a multivariable logistic regression model applied to patients receiving therapy within a month of diagnosis and within 1-12 months after diagnosis. Health care utilization was compared using negative binomial regression models. Health care cost differences between the 2 patient groups were estimated using generalized linear models. All models were controlled for potential confounding factors. RESULTS: The study sample consisted of 477 patients, with 397 (83.2%) patients initiating TKI within the first month of CML diagnosis and 80 (16.8%) after the first month. Out-of-pocket costs for the initial 30-day supply of TKI medications were not found to be a significant predictor of TKI initiation time. Patients initiating therapy within a month were less likely to have all-cause hospitalizations (IRR = 0.35; P = 0.02) or CML-specific hospitalizations (IRR = 0.27; P < 0.01). Over the 12-month follow-up period, they incurred $9,923 more in TKI pharmacy costs (P < 0.05), but patients initiating therapy after the first month of diagnosis incurred $7,582 more in medical costs, $218 more in non-TKI pharmacy costs, and $2,680 more in total health care costs (P > 0.05). CONCLUSIONS: Patients with TKI initiation within the first month of diagnosis had higher TKI pharmacy costs that were partially offset by lower medical and non-TKI pharmacy costs, resulting in lower overall total health care costs. Findings suggest that earlier TKI initiation may reduce the risks of hospitalizations, which could result in potential medical cost savings in the first 12 months of treatment. DISCLOSURES: No outside funding supported this study. The authors have no relationships or financial interests to report with any entity that would pose a conflict of interest with the subject matter of this article. A poster presentation of the study was made at the 11th American Association for Cancer Research (AACR) Conference on The Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved, on November 2-5, 2018, in New Orleans, LA.

Disease modifying therapies continue to drive up health care cost among individuals with multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) is a leading cause of disability in adults and requires lifelong treatment. Specialty drugs referred to as disease-modifying therapies (DMTs) have become the standard for multiple sclerosis treatment since the 1990s as they have been shown to reduce the risk of relapses and to delay disease progression. While more DMTs became available, prices of DMTs including existing drugs continue to rise and remain very expensive. This study is to estimate recent drug costs for DMTs and examine its impact on overall health care costs among individuals with MS enrolled in commercial insurance. METHODS: This study is a population-based, retrospective study using 2011-2015 IBM MarketScan® Commercial Database. Individuals aged <65 years and with 12 months' continuous enrollment for both medical and pharmacy benefits in any of the measurement years were included. Patients were determined to have MS if they had at least three medical claims with a diagnosis for MS or one outpatient pharmacy claim for a DMT. Costs were computed using total amounts paid by insurance and patient; we report overall cost and cost by service category. All costs are reported using inflation-adjusted 2015 dollars. RESULTS: The annual health care cost per MS patient increased from $45,471 in 2011 to $62,500 in 2015, an 8.3% average annual growth rate. The annual DMT cost per MS patient increased from $26,772 to $43,606, a 13.0% average annual growth rate. During this period, inpatient and other outpatient costs remained steady or decreased. When comparing DMT users to non-DMT users, the annual health care cost per DMT user was 74% higher in 2011 ($50,352 vs $28,881), increasing to more than twice higher in 2015 ($70,683 vs $29,821). CONCLUSIONS: Annual health care costs for MS patients increased rapidly between 2011 and 2015, almost entirely due to the cost of DMTs. Older drugs as well as newly approved DMTs both drove this trend.

Rates for HEDIS Screening for Diabetic Nephropathy Quality Measure May Be Overstated.

The Healthcare Effectiveness Data and Information Set (HEDIS) is used by health plans to measure and report on quality and performance. This study evaluated the appropriateness of the prescription drug compliance step for the Medical Attention for Nephropathy quality measure for patients with diabetes. Data from national commercial claims for 28,348,363 persons were reviewed. The study applied the standard HEDIS specifications for compliance in medical attention for nephropathy for diabetic patients. Evaluation of the third and final process (evidence of angiotensin-converting enzyme [ACE] inhibitors or angiotensin II receptor blockers [ARBs]) found that the addition of this step contributed 14% to 16% of the numerator, bringing the final rate to the >80% range. Yet, presence of a prescription for an ACE inhibitor or ARB did not confirm microalbuminuria. Only 1% of the persons satisfying Step 3 had evidence of microalbuminuria in years prior and none in the reporting year. Use of these medications does not obviate the need for a nephropathy screening in diabetics. Inclusion of these medications as numerator compliance leads to overreporting and may contribute to underscreening of a population at risk.

Risk Predictors for Postcontrast Acute Kidney Injury.

OBJECTIVE: To evaluate risk predictors of acute kidney injury (AKI) after contrast-media procedures in a broader cohort of patients than previously reported. DATA SOURCES: Comprehensive medical and pharmacy commercial claims data from 2012 to 2014. DATA COLLECTION AND EXTRACTION METHODS: Claims associated with contrast-media procedures for 2,737,020 persons between January 1, 2012 and November 30, 2014, were reviewed. PRINCIPAL FINDINGS: The overall incidence of AKI after a contrast-media procedure was 0.85%. AKI occurred in 26% of cases that had two or more contrast procedures within 30 days, compared with 9% of non-AKI cases. Although the incidence of postcontrast AKI was low, 10% of patients who developed AKI had a recent previous episode of AKI. In cases when AKI had occurred within 180 days of contrast administration, the odds of subsequent kidney injury was 9.39. CONCLUSIONS: Overall, there is a low risk (0.85%) of developing an AKI after a procedure with contrast-media consistent with several recent studies. However, in adults with a recent history of AKI, physicians must consider this history as a risk factor for subsequent AKI.

Future expenditure risk of silent members: a statistical analysis.

BACKGROUND: Silent-members are members of a medical health plan who submit no claims for healthcare services in a benefit year despite 12 months of continuous-enrollment. This study was conducted to evaluate the future expenditure risk of commercial-insured members who avoid all medical care despite coverage. In order to determine if the silent-members were at greater risk, we compared them to members who received care in the anchor year (2009) but had low-expenditures. The low-expenditure members were assumed to represent persons without significant medical conditions and without care-avoidance behaviors. We examined the claims experience of a cohort of silent members in the 2 years after the silent year (2009) and compared it with the corresponding claims experience for a cohort of low-expenditure members from the same anchor year (2009). METHODS: Members of commercial health plans (BCBS of Texas) were selected based on continuous-enrollment in 2009. Two sub-groups were identified based on annual claims expenditure: Care avoiders were members with 12 months continuous-enrollment and no medical claims, and are thus referred to as "silent members" in the insurance industry. Low-Expenditure members were those with 12 months continuous-enrollment and total PMPY (per member per year) annual medical claims expenditure in the lowest 10th percentile of members with claims experience. "Low-expenditure" members served as a comparison group to the "silent members", under the assumption that such claimants were using benefits for minor healthcare issues as needed. Key variables were enrollment and expenditures. Enrollment data identified demographics and continuous-enrollment. Medical claims data were used to calculate utilization and expenditures. All claims data were de-identified and no consent was required, as approved by the Institutional Review Board. No research involved human subjects. Multivariate logistic regression models were applied. RESULTS: Silent members who seek care in subsequent years have a greater probability of becoming high-expenditure claimants than those with low-expenditure experience. CONCLUSIONS: For silent members who subsequently seek treatment, the probability of becoming high-expenditure is significantly greater than low-expenditure members from the anchor year. The implications of future high costs for silent members who become claimants may support the need for additional research to address the risks of care avoidance behaviors.

Private Carriers' Physician Payment Rates Compared With Medicare and Medicaid.

This research evaluated the 2013 published physician reimbursement rates for Medicare and Medicaid in Texas and compared the rates with the mean fees from private carriers. Physician claims data were extracted from the Truven MarketScan Commercial Claims Databases. The average allowed amounts per unit per procedure code were compiled. The 2013 Medicare physician fee schedule was obtained and filtered to Texas. The 2013 Texas Medicaid physician fee schedule was obtained. The mean commercial allowed amounts were compared with those of Medicare and Medicaid on a per-unit rate. Comparison ratios were derived for each code. The CPT© procedure codes were then grouped into the categories assigned by the American Medical Association. The ratios of private/Medicare and private/Medicaid varied greatly by procedure type and locality, with the Texas Medicaid fees well below both private and Medicare fees. The discrepancy in payment amounts demonstrates the variation in payment rates among payer sources. The practical implications demonstrate the provider challenges in managing patient mix to maintain a viable practice.