key: cord-0942497-o476dtgd authors: Ohsfeldt, Robert; Kelton, Kari; Klein, Tim; Belger, Mark; Mc Collam, Patrick L.; Spiro, Theodore; Burge, Russel; Ahuja, Neera title: Cost-effectiveness of Baricitinib Compared with Standard of Care in Hospitalized Patients With COVID-19 in the United States: A Modelling Study date: 2021-10-04 journal: Clin Ther DOI: 10.1016/j.clinthera.2021.09.016 sha: 501cb6576e279fb7cfa2d7ea9d0b5507df2ecf01 doc_id: 942497 cord_uid: o476dtgd Purpose The COV-BARRIER Phase 3 trial demonstrated that treatment with baricitinib, an oral selective Janus kinase 1/2 inhibitor, in addition to standard of care significantly reduced mortality over 28 days in hospitalized COVID-19 participants, with a similar safety profile to standard of care. We assessed the cost-effectiveness of baricitinib plus standard of care versus standard of care alone (which included systemic corticosteroids and remdesivir) in patients hospitalized in the United States with COVID-19. Methods An economic model was developed in Microsoft Excel to simulate the inpatient stay, discharge to post-acute care, and recovered patients. Costs modelled included payer costs, hospital costs, and indirect costs. Benefits modelled included life years, quality-adjusted life years, deaths avoided, and use of mechanical ventilation avoided. The primary analysis was performed from a payer perspective over a lifetime horizon; a secondary analysis was also performed from the hospital perspective. The base case analysis modelled the numerical differences in treatment effectiveness observed in the COV-BARRIER trial. Scenario analyses were also performed in which the clinical benefit of baricitinib was limited to the statistically significant reduction in mortality demonstrated in the trial. Findings In the base case payer perspective, combination treatment with baricitinib plus standard of care resulted in an incremental total cost of $17,276, a total quality-adjusted life year (QALY) gain of 0.6703, and a total life-year gain of 0.837 compared with standard of care alone. The addition of baricitinib also increased survival by 5.1% and reduced the use of mechanical ventilation by 1.6%. The base-case incremental cost-effectiveness ratios were $25,774 per QALY gained and $20,638 per life year gained; the “mortality only” scenario analysis yielded similar results of $26,862 per QALY gained and $21,433 per life year gained. For the hospital perspective, combination treatment with baricitinib plus standard of care was more effective and less costly than standard of care alone in the base case, and it resulted in an incremental cost of $38,964 per death avoided in the “mortality only” scenario. Implications Our study showed that adding baricitinib to standard of care is cost effective for hospitalized COVID-19 patients in the United States. Cost effectiveness was demonstrated for both payer and hospital perspectives. These findings were robust to sensitivity analyses and to conservative assumptions limiting the clinical benefits of baricitinib to the statistically significant reduction in mortality demonstrated in the COV-BARRIER trial. Coronavirus disease 2019 , caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first identified in Wuhan, China and reported to the World Health Organization at the end of 2019. 1 By March 2020 a global pandemic was declared by the WHO. 2 The cumulative number of confirmed global cases of COVID-19 until June 2021 is 178.8 million, leading to 3.9 million deaths. 1, 3 As of June 2021, the United States (US) reported 33.2 million confirmed cases of COVID-19 with 597,037 deaths. 3 Cost impacts and capacity constraints have proven to be a large burden to hospitals and health care system during the global pandemic. 4 As of June 2021, 65% of the US population age 18+ had received at least one dose of a COVID-19 vaccine, and 150.8 million in US were fully vaccinated. 5 Additionally, hospitalization admissions have decreased from their peak 7-day average in the US of 16,492 during January 2021 to 1, 824 in June 2021. 5 However, this does not diminish the need for effective and cost-effective treatments for hospitalized COVID-19 patients which can reduce the severity of the infection and resultant resource and cost burden on hospitals. 6 Although vaccinations are demonstrated to be clinically effective, they are not 100% effective, and not everyone can receive them (e.g., those taking immunosuppressant drugs). Also, considering the time taken to vaccinate population at large and the uncertainty with the emergence of multiple variants, 6 even with increased vaccination rates COVID-19 will continue to consume important in-hospital health care resources. proportions of patients receiving dexamethasone and remdesivir). In addition, the study demonstrated numerically lower rates of progression to noninvasive ventilation and to mechanical ventilation that did not achieve statistical significance. 8 An assessment of the clinical and economic outcomes of remdesivir for hospitalized COVID-19 patients was conducted by the Institute for Clinical and Economic Review (ICER) and was based on clinical efficacy data for remdesivir versus SOC from the Adaptive COVID Treatment Trial (ACTT-1). ICER later published an updated report that evaluated remdesivir plus standard of care for the mild population and moderate-to-severe population, separately, based on clinical evidence from several trials. [9] [10] [11] [12] [13] [14] The model by ICER did not account for the discharge status of patients requiring post-acute care or the prevalence of comorbidities among hospitalized COVID-19 patients, nor did it consider the hospital perspective. Therefore, a cost-effectiveness analysis (CEA) using a model that reflects the patient's experience within the hospital and the post-acute hospital consequences is needed to address these limitations. Moreover, the overall cost burden and impact on payers and hospitals is large, therefore, more evidence is needed to guide efficient utilization of resources. In this study, we evaluated cost-effectiveness of baricitinib + SOC versus placebo + SOC using data from the COV-BARRIER trial by replicating and extending the cost-effectiveness model (CEM) developed by ICER. A pharmacoeconomic model was developed to estimate the cost-effectiveness of baricitinib plus SOC as a treatment for hospitalized COVID-19 patients in the US. The analysis evaluated adults aged ≥18 years who were hospitalized due to COVID-19, where a proportion also had various other severe comorbidities, and who did not require invasive mechanical ventilation at admission. The model was constructed to analyze the cost effectiveness from the perspective of a payer or from the narrow perspective of a hospital. The primary analysis was performed from the payer perspective, where costs to payers were defined as payments made to hospitals, post-acute discharge care providers, longterm post recovery cost, and indirect costs due to missed work during the inpatient hospital stay. A lifetime horizon was used in the base case analysis to capture long-term all-cause healthcare costs and mortality benefits. The robustness of the base case results was evaluated using one-way and probabilistic sensitivity analyses, where key model parameters were varied. In a secondary analysis, we focused on the hospital perspective whereby the net cost impact (hospital costs less MS-DRG reimbursement) was used with the time horizon set to the length of the inpatient stay. The measures of benefit in the model were quality-adjusted life years (QALY), life years gained, number of deaths avoided and use of mechanical ventilation that were accrued during hospitalization and after discharge of patients to quantify the impact of reducing progression to greater oxygen support level of care, duration of mechanical ventilation, and COVID-19 mortality due to therapy intervention. Health outcomes represented in the model were based on the National Institute of Allergy and Infectious were simulated in the model as treatment effects derived from the baricitinib COV-BARRIER phase 3 trial results. 8, 15, 16 The CEM is structured as a sequence of three submodels: inpatient, discharged, and The discharged submodel simulates post-acute care related to COVID-19. Patients may be discharged to one of the following types of discharge care: self-care or custodial care, home health care, inpatient rehabilitation, skilled nursing facility, short-term hospital, long-term acute care hospital, or hospice. In the Premier Healthcare Database (PHD) cost analysis, the proportion of each type of discharge care was calculated for patients grouped by the highest level of oxygen support received during the inpatient stay (shown in Supplemental Table S4 ). Payer costs for post-acute care are calculated by multiplying the duration of care by the unit cost per day for each type of care. QALYs are calculated by multiplying the relative utility of each type of care by the age-based utilities for the duration of post-acute care. The base case analysis assumes that all patients discharged to hospice die at the end of their stay, and that patients discharged to any status other than self-care or custodial care are unable to work while receiving post-acute care. The recovered submodel simulates all-cause healthcare costs and all-cause mortality for a lifetime horizon. This submodel assumes that recovered COVID-19 patients incur all-cause healthcare costs, health utilities, and all-cause mortality based on the general non-COVID-19 infected population, adjusted to reflect higher rates of comorbidities in the modeled COVID population. In the secondary (hospital perspective) analysis, only costs and benefits incurred during the inpatient submodel are included, given that the costs after discharge are not covered by the hospital. The key population variables are demographics, level of care at baseline, and severe comorbidities (Table 1) . Demographic inputs were based on the intent-to-treat population for the baricitinib COV-BARRIER phase 3 trial. 8 The average age of patients who recovered in the model was imputed by assuming that the relative age of survivors compared with the age of all patients in COV-BARRIER was identical to the relative age of survivors compared with all modeled patients in ICER's CEA of remdesivir. 10 The percentage of patients with severe comorbidities was only used in the calculation of post-hospitalization costs, utilities, and post-hospitalization mortality to reflect the higher prevalence of comorbidities among hospitalized COVID-19 patients compared with the general US population. The distribution of patients by level of care at baseline (medical care w/o oxygen, supplemental oxygen, and noninvasive ventilation) was derived from the ordinal scores at baseline in the trial. Patients on mechanical ventilation at study entry were excluded from the trial and not included in the modeled population. 8 The analysis applies adjustments to the all-cause healthcare costs, health utilities, and all-cause mortality of the general population to be more representative of the higher prevalence of comorbidities among hospitalized COVID-19 patients. The estimated proportion of patients with severe comorbidities (32.1%) was derived from the prevalence of comorbidities (obesity, diabetes, chronic respiratory disease, and hypertension) in the COV-BARRIER trial population relative to the prevalence of comorbidities in the general population. 8 Multipliers were derived from the research literature to estimate higher allcause healthcare costs, reduced quality of life, and higher all-cause mortality associated with metabolic syndrome, which has comorbid risks similar to the comorbid risk factors for COVID-19 infection and severity (Table 1 ). The post-discharge cost and utility multipliers for severe comorbidities were based on the ratios of annual healthcare costs 18 and EuroQual-Five Dimension (EQ-5D) utility scores, 19 respectively, for patients with and without metabolic syndrome. The comorbid mortality multiplier was assumed to be the same as the fixed-effects estimate of relative risk for all-cause mortality (1.37, 95% CI 1.09-1.74) in a meta-analysis of studies that used the most exact World Health Organization (WHO) definition of metabolic syndrome. 20 Treatment effectiveness: Treatment effectiveness estimates for baricitinib + SOC and placebo + SOC ( Table 2) were derived from the intent-to-treat population of the COV-BARRIER phase 3 trial. 8 Standard of care was similar in both study arms and included systemic corticosteroids (79.3%) and/or remdesivir (18.9%); 91.6% of patients who received remdesivir also received corticosteroids. 8 The incidence of new use of mechanical ventilation and of noninvasive ventilation within each treatment arm were sourced from the corresponding endpoints in the COV-BARRIER trial. 15 New use of supplemental oxygen was not reported as an endpoint and thus is not modeled in the analysis (i.e., it is specified as 0% in both comparator arms). The overall time to recovery within each treatment arm was also sourced from the corresponding endpoint in the COV-BARRIER trial 21 . The duration of care at each level of oxygen support was imputed by rescaling the number of days of each level of oxygen support in ACTT-2 16 to match the total time to recovery within each treatment arm in COV-BARRIER. 8, 16, 21 Probabilities of recovery were calculated as the complements of the Kaplan-Meier estimates of all-cause mortality at day 28 in COV-BARRIER. 8 Estimates of inpatient costs were primarily sourced from an analysis of patients with a COVID-19 diagnosis in the PHD, a large and all-payer US hospital database of detailed information on inpatient discharges (henceforth referred to as the PHD cost analysis). 17 The data cover inpatient admissions from April 1, 2020 to September 15, 2020. The modeled population represents a mix of Medicare (52.9%), Medicaid (19.2%) and commercially insured (27.9%) patients ( Table 3) . 22 Uninsured patients were excluded from the analysis due to the unavailability of data regarding out-of-pocket costs for uninsured and self-insured patients. From the payer perspective, direct costs included DRG payments to hospitals for the inpatient stay, costs of post-acute care immediately following discharge, and lifetime all-cause healthcare costs among recovered patients. It was assumed that hospitals are reimbursed for COVID-19 patients through DRG payments, and that drug acquisition costs are borne by the hospital. Therefore, drug acquisition costs were excluded from the payer perspective. The analysis assumed that the primary determinant of the DRG used for reimbursement is the highest level of oxygen support provided during the inpatient stay. Table S1 ). Table S3 ). 25, 26 Payer costs for post-acute care in the discharged submodel are specified by the duration of care and the unit cost per day of care (Table 3 and Supplementary Table S4 ). It is assumed that patients discharged to self care or custodial care incur no additional payer costs for post-acute care. The duration of post-acute care for each other discharge status was sourced from the CMS post-acute care public use file for calendar year 2017 except for short-term hospitals, which are not reported in the CMS public use file. 27 For patients discharged to a short-term hospital, the mean length of inpatient hospital stay reported in the Agency for Healthcare Research and Quality 2016 National Inpatient Sample was used as a proxy estimate for the duration of post-acute care. 28 The unit cost per day of home health care was derived from the CMS national, Health utilities: Health utilities (Table 3) were modeled by extending the approach used in ICER's evaluation of remdesivir. 10 Age-adjusted health utilities for the US general population were used to represent overall quality of life absent the effects of COVID-19. 10,45 These utilities were adjusted to account for the higher prevalence of comorbidities in the modeled population (Table 1 ). In the inpatient submodel, the disutility associated with influenza in prior economic modeling 46 was used as a proxy estimate of the disutility associated with COVID-19 symptoms 10 , and disutilities associated with hospitalization and ventilation were derived from a quality of life study of French patients hospitalized for C. difficile infection. 10, 47 The ICER model did not contain a corresponding health state for supplemental oxygen, and so the disutility of this state in the CEM was interpolated as the midpoint between noninvasive ventilation and medical care without oxygen (Table 3 ). In the discharged submodel, reduced quality of life among patients requiring post-acute care was simulated by relative utility multipliers sourced from the literature (Supplementary Table S4 ). Relative utilities associated with inpatient rehabilitation and skilled nursing facilities were estimated by replicating the approaches used in a published CEM of severe chronic obstructive pulmonary disease. 48 The relative utility of inpatient rehabilitation was derived from a quality of life study of myocardial infarction patients who underwent an 8-week inpatient rehabilitation program 49, 50 , while the relative utility associated with a skilled nursing facility was derived from a CEA of osteoporosis). 50,51 A derived estimate of the relative utility of hospice was calculated as the quotient of the utility of hospice divided by the utility of progression free survival in a published CEA of ovarian cancer. 52 In the absence of available evidence, the relative utility of home health care was assumed to be identical to the relative utility of inpatient rehabilitation, and the relative utilities of a short-term hospital and a long-term acute care hospital were assumed to be the same as the relative utility of a skilled nursing facility. In the recovered submodel, the health utilities of recovered COVID-19 patients are assumed to be the same as the age-adjusted health utilities of the general US population, adjusted to account for the higher prevalence of comorbidities among hospitalized COVID-19 patients (see the earlier discussion of comorbidities in the population subsection). 45 Other inputs: Treatment dosing and administration inputs assumed that remdesivir was administered by infusion as a single loading dose of 200 mg on day 1 followed by daily doses of 100 mg while hospitalized for up to 10 days 53 , and that baricitinib was administered orally as a daily dose of 4 mg while hospitalized for up to 14 days. 8 Age-and sex-adjusted all-cause mortality rates were sourced from the Social Security Administration period life table for 2017. 54 The discount rates for costs and QALY were set to 3% per annum. [55] [56] [57] For the base case, we evaluated the cost-effectiveness of baricitinib + SOC versus placebo + SOC for hospitalized COVID-19 patients using efficacy data from the COV-BARRIER phase 3 trial, from a health payer perspective over a life-time horizon, which accounted for long-term direct medical costs. In a secondary -mortality only‖ analysis, we examined the cost-effectiveness of baricitinib + SOC versus placebo + SOC assuming the statistically significant reduction in mortality demonstrated in COV-BARRIER is the only treatment benefit with baricitinib. We tested the impact of parameter uncertainty on the results of the primary analysis through deterministic and probabilistic sensitivity analyses (PSA). We also examined the cost-effectiveness of baricitinib + SOC from the hospital perspective. Treatment with baricitinib + SOC versus placebo + SOC resulted in an incremental total cost of $17,276, a total QALY gain of 0.6703, and a total life-year gain of 0.837 ( Table 4) . When the only difference in treatment effects between baricitinib + SOC and placebo + SOC is the probability of recovery (i.e., the -mortality only‖ scenario), the incremental costeffectiveness ratios were $26,862 per QALY gained and $21,433 per life-year gained, only slightly higher than the base case (Table 4 ). The ten most sensitive inputs identified through one-way sensitivity analysis (OWSA) for the base case analysis from the payer perspective are shown in Figure 2 . The base case results are most sensitive to uncertainty regarding the lifetime all-cause healthcare costs among recovered patients, followed by progression to mechanical ventilation during the inpatient stay. The incremental cost-effectiveness ratio lies between $20,000 and $32,000 for all variables explored in the OWSA, which falls well within the threshold of $50,000 per QALY gained recommended by ICER. A PSA of the base case analysis was implemented in Microsoft Excel with 5,000 replications (Figure 3) . The results show that compared with SOC alone, adjunctive treatment with baricitinib was associated with increased cost of $17,373 (95% CI: -$3,300 to $38,306) and increased clinical effect of 0.674 QALYs (95% CI: -0.096 to 1.441). The cost-effectiveness acceptability curve indicates that adjunctive treatment with baricitinib was cost effective at a willingness to pay of $50,000 per QALY gained in 96.5% of the PSA replications. We also ran secondary analyses from a hospital perspective. In the base case hospital perspective analysis, treatment with baricitinib + SOC is both more effective and less costly than treatment with placebo + SOC. Adding baricitinib to SOC reduced total hospital expenditures by $2,436 and reduced total reimbursement payments by $503, resulting in a $1,932 reduction in net costs. It also resulted in a net gain of 0.0023 QALYs, reduced the use of mechanical ventilation by 1.6% and increased survival by 5.1% Table S6 ). In the -mortality only‖ scenario analysis, adding baricitinib to SOC increased hospital expenditures by $1,978 and increased survival by 5.1%, resulting in an incremental cost of $38,964 per death avoided (Supplementary Table S6 ). Net impacts on clinical outcomes are presented in Supplementary Figure S1 . Compared with placebo + SOC, treatment with baricitinib + SOC reduced the use of mechanical ventilation by 16 patients per 1,000 treated and reduced the use of noninvasive ventilation by 7 patients per 1,000 treated. Similarly, treatment with baricitinib + SOC reduced the total hospital days by 800 days per 1,000 patients treated, with the decrease mainly driven by a decrease of 1,580 days of mechanical ventilation per 1,000 patients treated. We conducted an economic evaluation on the use of baricitinib + SOC versus placebo + SOC among COVID-19 hospital patients in a US setting based on the outcomes of the COV-BARRIER phase 3 trial. A de novo CEM was developed by extending the methods used in ICER's evaluation of remdesivir to support a hospital perspective and to account for discharge status, post-acute care, and the higher prevalence of comorbidities among hospitalized COVID-19 patients. In the base case analysis for the payer perspective, treatment with baricitinib + SOC resulted in incremental cost per QALY gained of $25,774 and cost per life year gained of $20,638. In the -mortality only‖ scenario analysis that limited the treatment benefit of baricitinib to the statistically significant reduction in mortality demonstrated in COV-BARRIER, the incremental cost-effectiveness ratios were $26,862 per QALY gained and $21,433 per life-year gained, only slightly higher than the base case. The principal drivers of the incremental results with baricitinib are the higher lifetime all-cause medical costs and higher lifetime QALYs accrued by recovered patients due to the higher survival rate. 22 The robustness of the results in the -mortality only‖ scenario analysis, deterministic sensitivity analysis, and the probabilistic sensitivity analysis provide further evidence that baricitinib + SOC is cost effective versus SOC alone at the conservative willingness to pay threshold of $50,000 per QALY gained recommended by ICER, even when lifetime allcause medical costs are factored into the analysis. The base case analysis from the hospital perspective indicates that adjunctive treatment with baricitinib reduces total hospital expenditures, primarily by reducing the number of patients who require mechanical ventilation. Since patients requiring mechanical ventilation are reimbursed via more expensive DRGs, reimbursement payments are also reduced. However, the reduction in hospital expenditures is larger than the reduction in reimbursement payments, producing an overall savings in net costs (expenses minus reimbursement). Baricitinib + SOC also has higher QALYs and therefore is a dominant strategy (lower costs and higher effectiveness) compared with SOC alone. In the -mortality benefit only‖ scenario analysis for the hospital perspective, adjunctive treatment with baricitinib results in an incremental cost of $38,964 per death avoided. The ongoing COVID-19 pandemic continues, and new variant strains are emerging, even though the vaccinated proportion of the population is increasing. Thus, decision makers will continue to rely on CEA to assess relative value of emerging treatments. 58 Limited evidence exists on the CEA of COVID-19 treatments in the U.S. Remdesivir, which is the first FDA approved treatment for COVID-19, was evaluated by ICER using a CEM without considering discharge status or post-acute care outcomes of patients; nor was the hospital perspective evaluated. 59 While the ICER model simulated a lifetime horizon using mortality and cost and QALY estimations for the general population, the poorer health of hospitalized COVID-19 patients due to more comorbidities vis-à-vis the general population was not addressed. Our model overcomes those key limitations by considering total hospital expenditures, reimbursement payments, and net costs per QALY gained. In our model, we explicitly considered the health outcomes and costs by discharge status (self-care or custodial care, home health care, inpatient rehabilitation, skilled nursing facilities, short term hospitalization, long-term acute care hospitalization, and hospice status) to provide an overall picture of post-acute hospital consequences. Also, the mortality calculations in our Thus, our model, as well as other existing CEMs, do not consider long-term consequences of COVID-19 due to lack of data. 62 Although our model does estimate the potential impact of efficacious therapies that can reduce progression to higher levels oxygen care, and therefore reduction in use of hospital days and ICUs, these potential benefits to hospitals in terms of alternative, non-COVID-19 care are not directly quantified. Another limitation specific to our hospital data inputs is the potential lack of generalizability of these national estimates to individual hospitals. Also, our hospital costs do not include COVID-19 related hospital re-admissions. Finally, the model assumes that recovered COVID-19 patients incur all-cause healthcare costs, health utilities, and all-cause mortality based on the general non-COVID-19 infected population, adjusted to reflect higher rates of comorbidities in the modeled COVID-19 population, but not reflective of currently indeterminate long-term COVID-19 sequalae. In conclusion, our study showed that baricitinib in combination with standard of care is cost effective for patients hospitalized due to COVID-19 infection in the United States. These results were robust across multiple sensitivity analyses and scenarios in the model and were driven by the reduced risk of mortality from baricitinib treatment. A Novel Coronavirus from Patients with Pneumonia in China COVID-19) Dashboard Health outcomes and economic burden of hospitalized COVID-19 patients in the United States The potential public health and economic value of a hypothetical COVID-19 vaccine in the United States: Use of cost-effectiveness modeling to inform vaccination prioritization COVID-19) Update: FDA Authorizes Drug Combination for Treatment of COVID-19 Efficacy and safety of baricitinib in patients with COVID-19 infection: Results from the randomised, double-blind, placebo-controlled, parallel-group COV-BARRIER phase 3 trial. medRxiv Alternative Pricing Models for Remdesivir and Other Potential Treatments for COVID-19 Alternative Pricing Models for Remdesivir and Other Potential Treatments for COVID-19 Remdesivir for the Treatment of Covid-19 -Final Report Effect of Remdesivir vs Standard Care on Clinical Status at 11 Days in Patients With Moderate COVID-19: A Randomized Clinical Trial Dexamethasone in Hospitalized Patients with Covid-19 Baricitinib Phase 3 COV-BARRIER Study in COVID-19 Top-line CONFIDENTIAL Results Premier Healthcare Database white paper: Data that Informs and Performs Health care utilization and costs by metabolic syndrome risk factors Erratum: Relation of health-related quality of life to metabolic syndrome, obesity, depression, and comorbid illness Risks for all-cause mortality, cardiovascular disease, and diabetes associated with the metabolic syndrome: a summary of the evidence Eli Lilly and Company; 2021. 22. Data on file. R7207 Premier Cost v2.xlsx. In: Eli Lilly and Company; 2020. 23. Centers for M, Medicaid S. National Summary of Inpatient Charge Data by Medicare Severity Diagnosis Related Group (MS-DRG), FY 2017, Interactive Dataset Medicaid Hospital Payment: A Comparison across States and to Medicare Medicare Fee-For-Service Post-Acute Care Provider Public Use Files, Calendar Year 2017 Provider Table Overview of U.S. Hospital Stays in 2016: Variation by Geographic Region CY 2021 Home Health Prospective Payment System Rate Update, Home Health Quality Reporting Program Requirements, and Home Infusion Therapy Services and Supplier Enrollment Requirements; and Home Health Value-Based Purchasing Model Healthcare utilization and costs in ARDS survivors: a 1-year longitudinal national US multicenter study. Intensive care medicine Table 23 National Health Expenditures; Nominal Dollars, Real Dollars, Price Indexes, and Annual Percent Change: Selected Calendar Years Bureau of Economic Analysis. Table 2.3.4. Price Indexes for Personal Consumption Expenditures by Major Type of Product Long-term care hospital services Update to Hospice Payment Rates, Hospice Cap, Hospice Wage Index and Hospice Price for FY 2021 Preliminary Evidence of the Impact of Hospice Payment Reform on Social Service Visits in the Last Week of Life Medicare Cost at End of Life Alternative Pricing Models for Remdesivir and Other Potential Treatments for COVID-19 An Open Letter from Daniel O'Day, Chairman & CEO, Gilead Sciences Labor Force Statistics from the Current Population Survey Work Among Medicaid Adults: Implications of Economic Downturn and Work Requirements All Civilian Total compensation for All occupations; Cost per hour worked Preference-Based EQ-5D index scores for chronic conditions in the United States Cost-effectiveness of newer treatment strategies for influenza Quality of life and utility decrement associated with Clostridium difficile infection in a French hospital setting Informing shared decisions about advance directives for patients with severe chronic obstructive pulmonary disease: a modeling approach Economic evaluation of cardiac rehabilitation soon after acute myocardial infarction One thousand health-related quality-of-life estimates Postmenopausal estrogens in prevention of osteoporosis. Benefit virtually without risk if cardiovascular effects are considered Adding bevacizumab to single agent chemotherapy for the treatment of platinum-resistant recurrent ovarian cancer: A cost effectiveness analysis of the AURELIA trial VEKLURY (remdesivir) Prescribing Information Health and Economic Outcomes Modeling Practices: A Suggested Framework Recommendations for Conduct, Methodological Practices, and Reporting of Cost-effectiveness Analyses: Second Panel on Cost-Effectiveness in Health and Medicine A Cost-Effectiveness Framework for COVID-19 Treatments for Hospitalized Patients in the United States Long-term Health Consequences of COVID-19 Disease and healthcare burden of COVID-19 in the United States ‗Long COVID' syndrome The utility of different health states as perceived by the general public Pamela Martin, an employee of MDM Inc. provided writing support.