Cost of Cardiovascular Disease Event and Cardiovascular Disease Treatment-Related Complication Hospitalizations in the United States.

BACKGROUND: Cardiovascular disease (CVD) is among the costliest conditions in the United States, and cost-effectiveness analyses can be used to assess economic impact and prioritize CVD treatments. We aimed to develop standardized, nationally representative CVD events and selected possible CVD treatment-related complication hospitalization costs for use in cost-effectiveness analyses. METHODS: Nationally representative costs were derived using publicly available inpatient hospital discharge data from the 2012-2018 National Inpatient Sample. Events were identified using the principal International Classification of Diseases, Ninth Revision and International Classification of Diseases, Tenth Revision codes. Facility charges were converted to costs using charge-to-cost ratios, and total costs were estimated by applying a published professional fee ratio. All costs are reported in 2021 US dollars. Mean costs were estimated for events overall and stratified by age, sex, and survival status at discharge. Annual costs to the US health care system were estimated by multiplying the mean annual number of events by the mean total cost per discharge. RESULTS: The annual mean number of hospital discharges among CVD events was the highest for heart failure (1 087 000 per year) and cerebrovascular disease (800 600 per year). The mean cost per hospital discharge was the highest for peripheral vascular disease ($33 700 [95% CI, $33 300-$34 000]) and ventricular tachycardia/ventricular fibrillation ($32 500 [95% CI, $32 100-$32 900]). Hospitalizations contributing the most to annual US health care costs were heart failure ($19 500 [95% CI, $19 300-$19 800] million) and acute myocardial infarction ($18 300, [95% CI, $18 200-$18 500] million). Acute kidney injury was the most frequent possible treatment complication (515 000 per year), and bradycardia had the highest mean hospitalization costs ($17 400 [95% CI, $17 200-$17 500]). CONCLUSIONS: The hospitalization cost estimates and statistical code reported in the current study have the potential to increase transparency and comparability of cost-effectiveness analyses for CVD in the United States.

The effects of patient out-of-pocket costs on insulin use among people with type 1 and type 2 diabetes with Medicare Advantage insurance-2014-2018.

OBJECTIVE: To identify the association between insulin out-of-pocket costs (OOPC) and adherence to insulin in Medicare Advantage (MA) patients. DATA SOURCES AND STUDY SETTING: The study is based on Optum Labs Data Warehouse, a longitudinal, real-world data asset with de-identified administrative claims and electronic health record data. STUDY DESIGN: Using descriptive and multivariable logistic regression analyses, we identified the likelihood of patients with diabetes having ≥60 consecutive days between an expected insulin fill date and the actual fill date (refill lapse) by OOPC, categorized by $0, >$0-$20 (reference), >$20-$35, >$35-$50, and > $50 per 30-day supply. DATA COLLECTION/EXTRACTION METHODS: The study included MA enrollees with type 1 or type 2 diabetes and prescription claims for insulin between 2014 and 2018. PRINCIPAL FINDINGS: Those with average insulin OOPC per 30-day supply >$35 or $0 were more likely to have an insulin refill lapse versus OOPC of >$0 to $20, with odds ratios ranging 1.18 (95% CI 1.13-1.22) to 1.74 (95% CI 1.66-1.83) depending on OOPC group and diabetes type. CONCLUSIONS: Capping average insulin OOPC at $35 per 30-day supply may help avoid cost-related insulin non-adherence in MA patients; efforts to address non-cost barriers to medication adherence remain important.

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.

Cost-Effectiveness of Hypertension Treatment by Pharmacists in Black Barbershops.

BACKGROUND: In LABBPS (Los Angeles Barbershop Blood Pressure Study), pharmacist-led hypertension care in Los Angeles County Black-owned barbershops significantly improved blood pressure control in non-Hispanic Black men with uncontrolled hypertension at baseline. In this analysis, 10-year health outcomes and health care costs of 1 year of the LABBPS intervention versus control are projected. METHODS: A discrete event simulation of hypertension care processes projected blood pressure, medication-related adverse events, fatal and nonfatal cardiovascular disease events, and noncardiovascular disease death in LABBPS participants. Program costs, total direct health care costs (2019 US dollars), and quality-adjusted life-years (QALYs) were estimated for the LABBPS intervention and control arms from a health care sector perspective over a 10-year horizon. Future costs and QALYs were discounted 3% annually. High and intermediate cost-effectiveness thresholds were defined as <$50 000 and <$150 000 per QALY gained, respectively. RESULTS: At 10 years, the intervention was projected to cost an average of $2356 (95% uncertainty interval, -$264 to $4611) more per participant than the control arm and gain 0.06 (95% uncertainty interval, 0.01-0.10) QALYs. The LABBPS intervention was highly cost-effective, with a mean cost of $42 717 per QALY gained (58% probability of being highly and 96% of being at least intermediately cost-effective). Exclusive use of generic drugs improved the cost-effectiveness to $17 162 per QALY gained. The LABBPS intervention would be only intermediately cost-effective if pharmacists were less likely to intensify antihypertensive medications when systolic blood pressure was ≥150 mm Hg or if pharmacist weekly time driving to barbershops increased. CONCLUSIONS: Hypertension care delivered by clinical pharmacists in Black barbershops is a highly cost-effective way to improve blood pressure control in Black men.

Factors Associated with Diabetes-Related Clinical Inertia in a Managed Care Population and Its Effect on Hemoglobin A1c Goal Attainment: A Claims-Based Analysis.

BACKGROUND: Despite evidence showing the benefits of treatment intensification following an elevated hemoglobin A1c (A1c), clinical inertia, or failure to establish and/or escalate treatment to achieve treatment goals, is a concern among patients diagnosed with type 2 diabetes (T2DM). Clinical inertia may contribute to increased health care utilization and costs due to poor clinical outcomes in MCOs. OBJECTIVES: To (a) identify factors associated with clinical inertia in T2DM and (b) determine differences in A1c goal attainment between patients who experience clinical inertia versus treatment intensification in a commercially insured population. METHODS: Medical and pharmacy claims data were used to identify commercially insured patients in a regional MCO with a recorded A1c ≥ 8.0% between January 1, 2013, and December 31, 2015. In the 4 months following the first elevated A1c value (index date), patients were classified into 2 groups: treatment intensification or clinical inertia. Treatment intensification was defined as the addition of ≥ 1 new noninsulin antihyperglycemic medication, the addition of insulin, or a dose increase of any current noninsulin antihyperglycemic medication. Patients were required to have ≥ 1 follow-up A1c value 6-12 months after the index date and continuous enrollment in the health plan for 12 months before and after the index date. Patients were excluded if they had a diagnosis for gestational diabetes or type 1 diabetes or if they were on insulin in the pre-index period. The primary outcome of attaining A1c < 7.0% was compared between groups after propensity score matching (PSM). Factors associated with clinical inertia were identified using logistic regression. RESULTS: 3,078 patients, with a mean (SD) age of 54.4 (10.6) years and a mean (SD) baseline A1c of 9.6% (1.7), were included in the study. Of these, 1,093 patients (36%) experienced clinical inertia. After PSM, 1,760 patients remained; 880 in each group. In the clinical inertia group, 23% of patients achieved an A1c < 7.0% in the post-index period, compared with 35% in the treatment intensification group (P < 0.001). A greater likelihood of experiencing clinical inertia was associated with baseline treatment with 2 (OR = 1.51, 95% CI = 1.22-2.86; P < 0.001) or ≥ 3 (OR = 1.78, 95% CI = 1.30-2.42; P < 0.001) antihyperglycemic medications (vs. none), baseline age ≥ 65 years (OR = 2.11, 95% CI = 1.63-2.74; P < 0.001), and diagnosis of coronary heart disease (OR = 1.44, 95% CI = 1.10-1.88; P = 0.007). A baseline A1c ≥ 9.0% (vs. 8.0%-8.9%) was associated with a lower likelihood of experiencing clinical inertia (OR = 0.56, 95% CI = 0.48-0.66; P < 0.001). CONCLUSIONS: More than a third of patients in a commercially insured population with T2DM and a baseline A1c ≥ 8% experienced clinical inertia. Clinical inertia resulted in worse A1c outcomes over the 12-month follow-up period. Results of this study suggest that treatment intensification should be monitored, with efforts made to educate health care providers on strategies aimed at improving glycemic control for high-risk patients. DISCLOSURES: This study was funded by a grant from Janssen Scientific Affairs, which was involved in study design, interpretation of results, and manuscript review. Wander reports consulting fees from Sanofi Aventis outside the submitted work. McAdam-Marx reports grants from Sanofi Aventis and AstraZeneca outside the submitted work. Pesa and Bailey were employees of Janssen Scientific Affairs during the conduct of the study. Bailey also reports stock ownership in Johnson and Johnson. This study was presented as a poster at the Academy of Managed Care Pharmacy Nexus 2017; October 16-19, 2017; Grapevine, TX.

Cost-Effectiveness of Treatment Options for Neuropathic Pain: a Systematic Review.

BACKGROUND: Neuropathic pain significantly reduces an individual's quality of life and places a significant economic burden on society. As such, many cost-effectiveness analyses (CEAs) have been published for treatments available for neuropathic pain. OBJECTIVES: The primary objective of this systematic review was to provide a detailed summary of the estimates of cost-effectiveness from published CEAs comparing available treatments for neuropathic pain. The secondary objectives were to identify the key drivers of cost-effectiveness and to assess the quality of published CEAs in neuropathic pain. METHODS: We searched Embase, MEDLINE, Cochrane CENTRAL and seven other databases to identify CEAs reporting the costs, health benefits (e.g., quality-adjusted life-years or disability-adjusted life-years) and summary statistics, such as incremental cost-effectiveness ratios, of treatments for neuropathic pain. We excluded studies reporting diseases other than neuropathic pain, those for which the full text was not available (e.g., conference abstracts), studies not written in English or not published in peer-reviewed journals, and narrative reviews, editorials and opinion papers. Titles and abstract reviews, full-text reviews, and data extraction were all performed by two independent reviewers, with disagreement resolved by a third reviewer. Mean costs, health benefits, and summary statistics were reported and qualitatively compared across studies, stratified by time horizon. Drivers of cost-effectiveness were assessed using reported one-way sensitivity analyses. The quality of all included studies was evaluated using the Tufts CEA Registry Quality Score and study reporting using the CHEERS (Consolidated Health Economic Evaluation Reporting Standards) checklist. RESULTS: A total of 22 studies were identified and included in this systematic review. Included studies were heterogeneous in the treatments compared, methodology and design, perspectives, and time horizons considered, making cross-study comparisons difficult. No single treatment was consistently the most cost-effective across all studies, but tricyclic antidepressants were the preferred treatment at a willingness-to-pay threshold of $US50,000 per quality-adjusted life-year in several studies with a short time horizon and a US payer perspective. Among the 14 studies reporting one-way sensitivity analyses, drivers of cost-effectiveness included utility values for health states and the likelihood of pain relief with treatment. The quality of the identified CEAs was moderate to high, and overall reporting largely met CHEERS recommendations. LIMITATIONS: To assess drivers of cost-effectiveness and quality, we only included studies with the full text available and thus excluded some CEAs that reported cost-effectiveness results. The heterogeneity of the included studies meant that the study results could not be synthesized and comparison across studies was limited. CONCLUSIONS: Though many pulished studies have evaluated the cost-effectiveness of treatments for neuropathic pain, significant heterogeneity between CEAs prevented synthesis of the results. Standardized methodology and improved reporting would allow for more reliable comparisons across studies.

Cost-Effectiveness of Intensive versus Standard Blood-Pressure Control.

BACKGROUND: In the Systolic Blood Pressure Intervention Trial (SPRINT), adults at high risk for cardiovascular disease who received intensive systolic blood-pressure control (target, <120 mm Hg) had significantly lower rates of death and cardiovascular disease events than did those who received standard control (target, <140 mm Hg). On the basis of these data, we wanted to determine the lifetime health benefits and health care costs associated with intensive control versus standard control. METHODS: We used a microsimulation model to apply SPRINT treatment effects and health care costs from national sources to a hypothetical cohort of SPRINT-eligible adults. The model projected lifetime costs of treatment and monitoring in patients with hypertension, cardiovascular disease events and subsequent treatment costs, treatment-related risks of serious adverse events and subsequent costs, and quality-adjusted life-years (QALYs) for intensive control versus standard control of systolic blood pressure. RESULTS: We determined that the mean number of QALYs would be 0.27 higher among patients who received intensive control than among those who received standard control and would cost approximately $47,000 more per QALY gained if there were a reduction in adherence and treatment effects after 5 years; the cost would be approximately $28,000 more per QALY gained if the treatment effects persisted for the remaining lifetime of the patient. Most simulation results indicated that intensive treatment would be cost-effective (51 to 79% below the willingness-to-pay threshold of $50,000 per QALY and 76 to 93% below the threshold of $100,000 per QALY), regardless of whether treatment effects were reduced after 5 years or persisted for the remaining lifetime. CONCLUSIONS: In this simulation study, intensive systolic blood-pressure control prevented cardiovascular disease events and prolonged life and did so at levels below common willingness-to-pay thresholds per QALY, regardless of whether benefits were reduced after 5 years or persisted for the patient's remaining lifetime. (Funded by the National Heart, Lung, and Blood Institute and others; SPRINT ClinicalTrials.gov number, NCT01206062 .).