Estimating and Rewarding the Value of Healthcare Interventions Beyond the Healthcare Sector: A Conceptual Framework.

BACKGROUND: Evaluating healthcare interventions for their impacts beyond health outcomes may result in recognition of changes in human capital, income level, tax revenue, and government spending, which could affect economic growth and population health. In this paper, we document instances where current health technology assessment (HTA) practices fail to account for the impacts of healthcare interventions on broader society beyond the healthcare sector. METHODS: We propose a novel conceptual framework, highlighting its three components (distributional cost-effectiveness analysis [DCEA], input-output model, and voting scheme) and their contributions to capturing the economic and societal ripple effects of healthcare interventions. This manuscript also outlines a case study in which the framework is applied to the reassessment of a previously evaluated digital health therapeutic for the treatment of opioid use disorder (OUD) compared with standard of care, demonstrating its practical application. RESULTS: The DCEA health value metric indicates that digital therapeutic is more equitable, favoring socioeconomically disadvantaged groups, while standard of care exacerbates health inequality by benefiting the already advantaged. Additionally, digital therapeutic shows potential for boosting productivity, raising income, and creating jobs, supporting its consideration by employer-sponsored health plans to optimize resource allocation for treating OUD. CONCLUSION: The conceptual framework provides insights for enhancing HTAs to incorporate the broader economic and societal impacts of healthcare interventions. By integrating DCEA, extended HTA analysis with input-output modeling, and a voting scheme, decision makers can make informed choices aligned with societal priorities, although further research and validation are necessary for practical implementation across diverse healthcare contexts.

Association between trajectories of adherence to endocrine therapy and risk of treated breast cancer recurrence among US nonmetastatic breast cancer survivors.

BACKGROUND: Endocrine therapy is the mainstay treatment for breast cancer (BC) to reduce BC recurrence risk. During the first year of endocrine therapy use, nearly 30% of BC survivors are nonadherent, which may increase BC recurrence risk. This study is to examine the association between endocrine therapy adherence trajectories and BC recurrence risk in nonmetastatic BC survivors. METHODS: This retrospective cohort study included Medicare beneficiaries in the United States (US) with incident nonmetastatic BC followed by endocrine therapy initiation in 2010-2019 US Surveillance, Epidemiology, and End Results linked Medicare data. We calculated monthly fill-based proportion of days covered in the first year of endocrine therapy. We applied group-based trajectory models to identify distinct endocrine therapy adherence patterns. After the end of the first-year endocrine therapy trajectory measurement period, we estimated the risk of time to first treated BC recurrence within 4 years using Cox proportional hazards models. RESULTS: We identified 5 trajectories of adherence to endocrine therapy in BC Stages 0-I subgroup (n = 28,042) and in Stages II-III subgroup (n = 7781). A trajectory of discontinuation before 6 months accounted for 7.0% in Stages 0-I and 5.8% in Stages II-III subgroups, and this trajectory was associated with an increased treated BC recurrence risk compared to nearly perfect adherence (Stages 0-I: adjusted hazard [aHR] = 1.84, 95% CI = 1.46-2.33; Stages II-III: aHR = 1.38, 95% CI = 1.07-1.77). CONCLUSIONS: Nearly 7% of BC survivors who discontinued before completing 6 months of treatment was associated with an increased treated BC recurrence risk compared to those with nearly perfect adherence among Medicare nonmetastatic BC survivors.

Association between trajectories of prescription opioid use and risk of opioid use disorder and overdose among US nonmetastatic breast cancer survivors.

PURPOSE: To examine the association between prescription opioid use trajectories and risk of opioid use disorder (OUD) or overdose among nonmetastatic breast cancer survivors by treatment type. METHODS: This retrospective cohort study included female nonmetastatic breast cancer survivors with at least 1 opioid prescription fill in 2010-2019 Surveillance, Epidemiology and End Results linked Medicare data. Opioid mean daily morphine milligram equivalents (MME) calculated within 1.5 years after initiating active breast cancer therapy. Group-based trajectory models identified distinct opioid use trajectory patterns. Risk of time to first OUD/overdose event within 1 year after the trajectory period was calculated for distinct trajectory groups using Cox proportional hazards models. Analyses were stratified by treatment type. RESULTS: Four opioid use trajectories were identified for each treatment group. For 38,030 survivors with systemic endocrine therapy, 3 trajectories were associated with increased OUD/overdose risk compared with early discontinuation: minimal dose (< 5 MME; adjusted hazard ratio [aHR] = 1.73 [95% CI 1.43-2.09]), very low dose (5-25 MME; 2.67 [2.05-3.48]), and moderate dose (51-90 MME; 6.20 [4.69-8.19]). For 9477 survivors with adjuvant chemotherapy, low-dose opioid use was associated with higher OUD/overdose risk (aHR = 7.33 [95% CI 2.52-21.31]) compared with early discontinuation. For 3513 survivors with neoadjuvant chemotherapy, the differences in OUD/OD risks across the 4 trajectories were not significant. CONCLUSIONS: Among Medicare nonmetastatic breast cancer survivors receiving systemic endocrine therapy or adjuvant chemotherapy, compared with early discontinuation, low-dose or moderate-dose opioid use were associated with six- to sevenfold higher OUD/overdose risk. Breast cancer survivors at high-risk of OUD/overdose may benefit from targeted interventions (e.g., pain clinic referral).

Development and validation of a tool to predict high-need, high-cost patients hospitalised with ischaemic heart disease.

OBJECTIVE: To develop and validate a tool to predict patients with ischaemic heart disease (IHD) at risk of excessive healthcare resource utilisation. DESIGN: A retrospective cohort study. SETTING: We identified patients through the State of Florida Agency for Health Care Administration (N=586 518) inpatient dataset. PARTICIPANTS: Adult patients (at least 40 years of age) admitted to the hospital with a diagnosis of IHD between 1 January 2007 and 31 December 2016. PRIMARY OUTCOME MEASURES: We identified patients whose healthcare utilisation is higher than presumed (analysis of residuals) and used logistic regression (binary and multinomial) in estimating the predictive models to classify individual as high-need, high-care (HNHC) patients relative to inpatient visits (frequency of hospitalisation), cost and hospital length of stay. Discrimination power, prediction accuracy and model improvement for the binary logistic model were assessed using receiver operating characteristic statistic, the Brier score and the log-likelihood (LL)-based pseudo-R2, respectively. LL-based pseudo-R2 and Brier score were used for multinomial logistic models. RESULTS: The binary logistic model had good discrimination power (c-statistic=0.6496), an accuracy of probabilistic predictions (Brier score) of 0.0621 and an LL-based pseudo-R2 of 0.0338 in the development cohort. The model performed similarly in the validation cohort (c-statistic=0.6480), an accuracy of probabilistic predictions (Brier score) of 0.0620 and an LL-based pseudo-R2 of 0.0380. A user-friendly Excel-based HNHC risk predictive tool was developed and readily available for clinicians and policy decision-makers. CONCLUSIONS: The Excel-based HNHC risk predictive tool can accurately identify at-risk patients for HNHC based on three measures of healthcare expenditures.

Oral fluoroquinolones and risk of aortic aneurysm or dissection: A nationwide population-based propensity score-matched cohort study.

STUDY OBJECTIVE: To investigate risk of aortic aneurysm or dissection in patients using oral fluoroquinolones compared to those using macrolides in real-world clinical practice among a large US general population. DESIGN: Retrospective cohort study design. DATA SOURCE: MarketScan commercial and Medicare supplemental databases. PATIENTS: Adults patients with at least one prescription fill for fluoroquinolone or macrolide antibiotics. INTERVENTION: Fluoroquinolone or macrolide antibiotics. MEASUREMENTS AND MAIN RESULTS: The primary outcome was estimated incidence of aortic aneurysm or dissection associated with the use of fluoroquinolones compared with macrolides during a 60-day follow-up period in a 1:1 propensity score-matched cohort. We identified 3,174,620 patients (1,587,310 in each group) after 1:1 propensity score matching. Crude incidence of aortic aneurysm or dissection was 1.9 cases per 1000 person-years among fluoroquinolone users and 1.2 cases per 1000 person-years among macrolide users. In multivariable Cox regression, compared with macrolides, the use of fluoroquinolones was associated with an increased risk of aortic aneurysm or dissection (aHR: 1.34; 95% CI: 1.17-1.54). The association was primarily driven by a high incidence of aortic aneurysm cases (95.8%). Results of sensitivity (e.g., fluoroquinolone exposure ranging from 7 to 14 days (aHR: 1.47; 95% CI: 1.26-1.71)) and subgroup analyses (e.g., ciprofloxacin (aHR: 1.26; 95% CI: 1.07-1.49) and levofloxacin (aHR: 1.44; 95% CI: 1.19-1.52)) remained consistent with main findings. CONCLUSIONS: Fluoroquinolone use was associated with a 34% increased risk of aortic aneurysm or dissection compared with macrolide use among a general US population.

Application of Machine Learning Algorithms to Predict Uncontrolled Diabetes Using the All of Us Research Program Data.

There is a paucity of predictive models for uncontrolled diabetes mellitus. The present study applied different machine learning algorithms on multiple patient characteristics to predict uncontrolled diabetes. Patients with diabetes above the age of 18 from the All of Us Research Program were included. Random forest, extreme gradient boost, logistic regression, and weighted ensemble model algorithms were employed. Patients who had a record of uncontrolled diabetes based on the international classification of diseases code were identified as cases. A set of features including basic demographic, biomarkers and hematological indices were included in the model. The random forest model demonstrated high performance in predicting uncontrolled diabetes, yielding an accuracy of 0.80 (95% CI: 0.79-0.81) as compared to the extreme gradient boost 0.74 (95% CI: 0.73-0.75), the logistic regression 0.64 (95% CI: 0.63-0.65) and the weighted ensemble model 0.77 (95% CI: 0.76-0.79). The maximum area under the receiver characteristics curve value was 0.77 (random forest model), while the minimum value was 0.7 (logistic regression model). Potassium levels, body weight, aspartate aminotransferase, height, and heart rate were important predictors of uncontrolled diabetes. The random forest model demonstrated a high performance in predicting uncontrolled diabetes. Serum electrolytes and physical measurements were important features in predicting uncontrolled diabetes. Machine learning techniques may be used to predict uncontrolled diabetes by incorporating these clinical characteristics.

Predictors of 30-day readmission, mortality, and length of stay for hospitalized U.S. patients with Alzheimer's and related dementias from 2010 to 2015.

OBJECTIVES: Examine predictors of clinical and resource utilization outcomes associated with Alzheimer's disease and related dementias (ADRD), stratified by patient severity profiles. METHODS: Cross-sectional study of adults (30+ year old) with ADRD discharged from US hospitals to home health care (HHC) and identified from the 2010-2015 Nationwide Readmissions Database (NRD) using ICD 9th-10th codes. Outcomes of interest included 30-day hospital readmissions, in-hospital mortality, and hospital length of stay (LOS). Covariates consisted of sociodemographic and clinical variables. Multiple logistic regressions (for readmissions and mortality) and generalized linear regressions (for LOS) were used to examine associations between outcomes and study covariates, stratified by patient severity profiles. RESULTS: Of 164,598 ADRD patients, 3,848 were mild, 68803 were moderate, 72428 were severe, and 19,519 were extreme. The 30-day readmission rate was 3.2%, death rate was 14.5%, and LOS was 3.0 days, (95%, CI: 15.0, 17.0) to 5.0 days, (95%, CI: 18.0, 19.0), all with a p-value<0.0001. Across outcomes and severity levels, the top predictors included number of diagnoses, gender, hospital bed size, primary and secondary diagnoses, and income size. CONCLUSIONS: Severe and extreme stages of HHC discharge may lead to increased readmissions, death, LOS, and costs. Specialized care is needed to reduce these negative outcomes in the ADRD patient population.

Trends, characteristics, race, and ethnicity associated with nonadherence to antidepressants among breast cancer survivors with depression.

BACKGROUND: Breast cancer is the most diagnosed cancer in the United States, and half of breast cancer survivors experience major depressive disorders (hereafter depression). Healthcare Effectiveness Data and Information Set (HEDIS) quality measures evaluating depression treatment practices recommend uninterrupted antidepressant treatment for 3 months in the acute phase and 3 months in the continuation phase for the general population. However, little is known about the extent of and trends in antidepressant nonadherence among breast cancer survivors with depression, which may impact adherence to breast cancer treatment, potentially leading to breast cancer recurrence and other adverse outcomes. OBJECTIVE: To examine the trends and characteristics associated with antidepressant nonadherence among breast cancer survivors with depression in the United States. METHODS: We conducted cross-sectional analyses of Surveillance, Epidemiology, and End Results linked with Medicare data (2010-2019) for women with breast cancer and depression who newly initiated antidepressant use. Using HEDIS measures of nonadherence (ie, antidepressant prescription coverage ≤84 days of the 114-day acute phase or ≤180 days of the 231-day continuation phase), we calculated the annual crude prevalence of antidepressant nonadherence and examined trends using unadjusted logistic regression. Multivariable logistic regression identified characteristics associated with antidepressant nonadherence. RESULTS: Among 9,452 eligible breast cancer survivors with depression (aged ≥65 years = 84% and White race = 82%), the crude prevalence of antidepressant nonadherence decreased from 2010 to 2019 for both the acute (49% to 40%; Ptrend<0.001) and continuation (67% to 57%; Ptrend<0.001) phases. Factors significantly associated with higher odds of antidepressant nonadherence in both the acute and continuation phases included Black race (odds ratios [ORs] [95% CI] for the acute/continuation phases: 2.0 [1.7-2.4]/2.0 [1.7-2.3]) and Hispanic ethnicity (1.5 [1.1-1.9]/2.2 [1.6-2.9]) compared with White race; receiving the first antidepressant from an oncologist vs a psychiatrist (1.4 [1.1-1.8]/1.6 [1.2-2.0]); and using antidepressants not recommended for older adults by the Beers criteria (2.2 [1.6-2.9]/2.0 [1.4-2.7]). Factors associated with lower odds of antidepressant nonadherence in both phases included receiving lymph node dissection (0.7 [0.5-0.9]/0.7 [0.5-0.9]), receiving endocrine therapy (0.9 [0.8-0.9]/0.8 [0.7-0.9]), having a higher National Cancer Institute comorbid index (0.8 [0.7-0.8]/0.9 [0.8-0.9]), having a follow-up visit with a psychiatrist (0.9 [0.8-0.9]/0.9 [0.8-0.9]), and switching to different antidepressants (0.7 [0.6-0.8]/0.7 [0.7-0.8]). CONCLUSIONS: Despite antidepressant nonadherence prevalence decreasing from 2010 to 2019, over half of breast cancer survivors with depression and Medicare were nonadherent in the continuation phase. Patients with identified nonadherence risk factors may benefit from close monitoring and targeted interventions. DISCLOSURES: Wei-Hsuan Lo-Ciganic reported grants from the National Institute on Drug Abuse (R01DA044985 and R01DA050676), the National Institute on Aging (R21AG060308), the National Institute of Mental Health (R01MH121907), Merck Sharp & Dohme, Bristol Myers Squibb, the Richard King Mellon Foundation at the University of Pittsburgh, the Clinical and Translational Science Institute of the University of Florida, the Pharmaceutical Research and Manufacturers of America (PhRMA) Foundation, and the US Department of Veterans Affairs outside the submitted work; in addition, Wei-Hsuan Lo-Ciganic has a patent pending for U1195.70174US00. Haesuk Park reported grants from Bristol Myers Squibb/Pfizer Alliance American Thrombosis Investigator Initiated Research Program (ARISTA-USA) outside the submitted work. Juan M. Hincapie-Castillo reported grants from Merck outside the submitted work. Debbie Wilson reported grants from the National Institute on Drug Abuse, the National Institute on Aging, Merck Sharp & Dohme, and Bristol Myers Squibb outside the submitted work; and serving as an editorial board member for the Journal of Pharmacy Technology. Ching-Yuan Chang's contributions to this manuscript were made while at the University of Florida College of Pharmacy. Ching-Yuan Chang is currently employed by Vertex Pharmaceuticals, Inc. Vertex did not fund or have any involvement in this study or publication. Vakaramoko Diaby is currently employed by Otsuka, Inc. Otsuka did not fund or have any involvement in this study or publication. No other disclosures were reported.

Economic Impact of Universal Hepatitis C Virus Testing for Middle-Aged Adults Who Inject Drugs.

INTRODUCTION: The objective of this study was to estimate the economic impact of providing universal hepatitis C virus testing in commercially insured middle-aged persons who inject drugs in the U.S. METHODS: This study developed a dynamic 10-year economic model to project the clinical and economic outcomes associated with hepatitis C virus testing among middle-aged adult persons who inject drugs, from a payer's perspective. Costs related to hepatitis C virus testing, direct-acting antiviral, and liver-related outcomes between the (1) current hepatitis C virus testing rate (i.e., 8%) and (2) universal hepatitis C virus testing rate (i.e., 100%) were compared. Among patients testing positive, 21% of those without cirrhosis and 48% of those with cirrhosis were assumed to initiate direct-acting antivirals. Sensitivity analyses were performed to identify variables (e.g., direct-acting antiviral drug costs, hepatitis C virus testing costs, direct-acting antiviral treatment rate) influencing this study's conclusion. RESULTS: The model predicts that during the 10-year period, universal hepatitis C virus testing will cost an additional $242 per person who injects drugs to the payers' healthcare budgets compared with the current scenario. Sensitivity analyses showed values ranging from $1,656 additional costs to $1,085 cost savings across all varied parameters and scenarios. A total of 80% of the current direct-acting antiviral costs indicated that cost savings will be $383 per person who injects drugs. CONCLUSIONS: Universal hepatitis C virus testing among persons who inject drugs would not achieve cost savings within 10 years, with the cost of direct-acting antivirals contributing the most to the spending. To promote universal hepatitis C virus testing among persons who inject drugs, decreasing direct-acting antiviral costs and sustainable funding streams for hepatitis C virus testing should be considered.

RSV testing practice and positivity by patient demographics in the United States: integrated analyses of MarketScan and NREVSS databases.

BACKGROUND: RSV-incidence estimates obtained from routinely-collected healthcare data (e.g., MarketScan) are commonly adjusted for under-reporting using test positivity reported in national Surveillance Systems (NREVSS). However, NREVSS lacks detail on patient-level characteristics and the validity of applying a single positivity estimate across diverse patient groups is uncertain. We aimed to describe testing practices and test positivity across subgroups of private health insurance enrollees in the US and illustrate the possible magnitude of misclassification when using NREVSS to correct for RSV under ascertainment. METHODS: Using billing records, we determined distributions of RSV-test claims and test positivity among a national sample of private insurance enrollees. Tests were considered positive if they coincided with an RSV-diagnosis. We illustrated the influence of positivity variation across sub-populations when accounting for untested acute respiratory infections. RESULTS: Most tests were for children (age 0-4: 65.8%) and outpatient encounters (78.3%). Test positivity varied across age (0-4: 19.8%, 5-17: 1.8%, adults: 0.7%), regions (7.6-16.1%), settings (inpatient 4.7%, outpatient 14.2%), and test indication (5.0-35.9%). When compared to age, setting or indication-specific positivity, bias due to using NREVSS positivity to correct for untested ARIs ranged from - 76% to 3556%. CONCLUSIONS: RSV-test positivity depends on the characteristics of patients for whom those tests were ordered. NREVSS-based correction for RSV-under-ascertainment underestimates the true incidence among children and overestimate rates among adults. Demographic-specific detail on testing practice and positivity can improve the accuracy of RSV-incidence estimates.

Cost Effectiveness of Dapagliflozin Added to Standard of Care for the Management of Diabetic Nephropathy in the USA.

BACKGROUND: Angiotensin-converting enzyme inhibitors have been used as the standard of care for the treatment of diabetic nephropathy. Recently, dapagliflozin has been shown to reduce diabetic nephropathy when added to the standard of care. OBJECTIVE: The objective of this study was to determine the cost effectiveness of dapagliflozin added to the standard of care in diabetic nephropathy in the United States of America (USA). METHODS: A Markov model was developed to determine the cost-effectiveness outcomes from the Medicare/Medicaid health coverage perspective. Model inputs were derived from the literature. The primary outcomes were total costs, quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio. Deterministic and probabilistic sensitivity analyses were performed to determine the robustness of our results. A willingness-to-pay threshold of $100,000 per QALY was applied, which is based on previous studies. RESULTS: Dapagliflozin yielded a lifetime QALY of 2.8. The discounted QALY associated with the standard of care was 2.6. The standard of care was the less costly treatment with a lifetime cost of $106,150.25 as compared with dapagliflozin, which costs $110,689.25. Dapagliflozin demonstrated an incremental cost-effectiveness ratio of $21,141.51 per additional QALY. The most influential parameters of the incremental cost-effectiveness ratio were the adverse drug reaction-related cost of the standard of care and dapagliflozin, the acquisition cost, and the adverse drug reaction-related cost of dapagliflozin. The effects and costs of the interventions were consistent between base-case analyses and the probabilistic model (incremental cost-effectiveness ratio: $19,023.35 [$13,637.8-$27,483.1]). CONCLUSIONS: Dapagliflozin added to the standard of care was cost effective relative to the standard of care alone in the USA for patients with diabetic nephropathy.

Real-world economic evaluation of prospective rapid whole-genome sequencing compared to a matched retrospective cohort of critically ill pediatric patients in the United States.

There is an increasing demand for supporting the adoption of rapid whole-genome sequencing (rWGS) by demonstrating its real-world value. We aimed to assess the cost-effectiveness of rWGS in critically ill pediatric patients with diseases of unknown cause. Data were collected prospectively of patients admitted to the Nicklaus Children's Hospital's intensive care units from March 2018 to September 2020, with rWGS (N = 65). Comparative data were collected in a matched retrospective cohort with standard diagnostic genetic testing. We determined total costs, diagnostic yield (DY), and incremental cost-effectiveness ratio (ICER) adjusted for selection bias and right censoring. Sensitivity analyses explored the robustness of ICER through bootstrapping. rWGS resulted in a diagnosis in 39.8% while standard testing in 13.5% (p = 0.026). rWGS resulted in a mean saving per person of $100,440 (SE = 26,497, p < 0.001) and a total of $6.53 M for 65 patients. rWGS in critically ill pediatric patients is cost-effective, cost-saving, shortens diagnostic odyssey, and triples the DY of traditional approaches.

An Umbrella Review of the Cost Effectiveness of Human Papillomavirus Vaccines.

BACKGROUND AND OBJECTIVES: Although many systematic reviews for the human papillomavirus vaccines cost effectiveness have been published, they vary in perspectives, methods, and quality. We aimed to condense systematically such evidence to facilitate locating, processing, and learning, not only about the consensus of findings but also how models were built and their evolution over time and across settings. METHODS: We conducted an umbrella review of cost-effectiveness studies for human papillomavirus vaccines using three databases (PubMed, Embase, and Cochrane). Based on their objectives, we classified studies into three groups (human papillomavirus vaccines cost effectiveness, model characteristics, and all-type vaccines, including human papillomavirus vaccines). We used the AMTAR2 to assess the quality of the studies. Additionally, we provided a summary of study findings, discussions, and evidence gaps in the literature. RESULTS: Though most studies were critically low quality and had a low quality of reporting, the human papillomavirus vaccine was consistently cost effective in young girls and men who have sex with men. Stratified analyses by rated quality did not change the results. The quality assessment of the reviews did not necessarily reflect the quality assessment of underlying studies. The human papillomavirus vaccine models became more complex over time, capturing more realistic disease transmission with different human papillomavirus strains and herd immunities. CONCLUSIONS: Additional evidence is needed for vulnerable populations (e.g., childhood cancer survivors) who are at high risk for human papillomavirus vaccine-related cancers and, therefore, may be more cost effective when receiving human papillomavirus vaccines. Quantifying human papillomavirus vaccine cost effectiveness via meta-analyses is feasible if investigators can increase the homogeneity of their populations.

Comparative cost-effectiveness of radiotherapy among older women with hormone receptor positive early-stage breast cancer.

OBJECTIVE: The aim was to examine the real-world cost-effectiveness of breast-conserving surgery (BCS) plus hormonal therapy with radiotherapy, compared to hormonal therapy alone among women 66 and older with hormone receptor positive early-stage breast cancer in the United States (US). METHODS: This study was conducted from a U.S. Centers for Medicare and Medicaid Services perspective and an eight-year time horizon. Both costs (2020 US$) and health utilities (quality-adjusted life years, QALYs) were obtained from retrospective studies using the SEER linked with Medicare and Medicare Health Outcomes Survey, respectively. The incremental cost-effectiveness ratio (ICER) of the addition of radiotherapy to hormonal therapy versus hormonal therapy alone after BCS was estimated by an unbiased doubly robust estimator. Sensitivity analyses were conducted through bootstrapping to estimate credible intervals. RESULTS: The addition of radiotherapy to hormonal therapy after BCS yielded the highest clinical benefits (2.66 QALYs) and costs ($19,424.27) compared to its hormonal therapy alone after BCS (0.77 QALYS; $2,028.58). The ICER was estimated to be $9,174.94/QALY. Sensitivity analyses did not change the direction of the findings. CONCLUSIONS: The results implicated that the combination of radiotherapy and hormonal therapy is cost-effective in the US.

Health Care Utilization and Costs Associated With Systemic First-Line Metastatic Melanoma Therapies in the United States.

PURPOSE: US Food and Drug Administration approvals of immune checkpoint inhibitors and targeted therapies revolutionized the treatment of metastatic melanoma. Our aim was to assess health care resource utilization and costs for patients with metastatic melanoma treated with systemic therapies in first line between January 2012 and December 2017. METHODS: We conducted a retrospective cohort study of patients with metastatic melanoma using MarketScan data. We included patients diagnosed with melanoma and secondary malignant neoplasm who used pembrolizumab, nivolumab, ipilimumab, ipilimumab plus nivolumab, BRAF-inhibitor (BRAF-i) plus MEK inhibitor (MEK-i), BRAF-i or MEK-i monotherapy, or chemotherapy in first line. We compared health care utilization and costs per patient per month (PPPM) using two-part and generalized linear models. RESULTS: We identified 1,870 patients, including 185 pembrolizumab, 103 nivolumab, 689 ipilimumab, 185 nivolumab plus ipilimumab, 214 BRAF-i plus MEK-i, 240 BRAF-i or MEK-i monotherapy, and 254 chemotherapy users. Highest PPPM rates of hospitalizations, emergency room visits, and outpatient visits were observed in patients with ipilimumab plus nivolumab therapy (adjusted difference v pembrolizumab [aDiff], 0.18, 0.12, and 0.88, respectively; all P < .001). Ipilimumab monotherapy users (aDiff, 0.07 and 0.93; all P < .001) and chemotherapy users (aDiff, 0.10 and 2.63; all P < .001) showed higher PPPM rates of hospitalizations and outpatient visits compared with pembrolizumab users, respectively. Utilization rates in nivolumab, BRAF-i plus MEK-i, and BRAF-i or MEK-i groups were similar to the pembrolizumab group. Highest PPPM total costs and drug-related costs were observed in the ipilimumab group ($80,139 US dollars [USD] and $70,051 USD; all P < .001), followed by the ipilimumab plus nivolumab ($71,689 USD and $56,217 USD; all P < .001) and the BRAF-i plus MEK-i group ($31,184 USD and $19,648 USD; all P < .001). PPPM costs in the nivolumab group were similar to the pembrolizumab group. CONCLUSION: Significant differences in health care resource utilization and costs were found across first-line metastatic melanoma regimens. Utilization rates were highest in patients using ipilimumab-containing therapies. High drug costs constituted a major fraction of total PPPM health care costs.

Effects, trends, costs associated with readmission in early-aged patients with suicidal ideation.

OBJECTIVE: To examine determinants, trends, and costs associated with 30-day all-cause readmission (R) for suicidal ideation (SI) in early-aged patients. METHODS: This was a retrospective cohort study using the 2010-2014 Nationwide Readmissions Database. Discharge records for those aged 5-24 with an SI diagnosis were analyzed. Hierarchical models (HMs) were used to assess factors of R, length of stay (LOS), and total costs of Rs. RESULTS: There were 197,603 SI index admissions (IAs). Of these, 2% had a R. The annualized trend of R rates for all age groups remained constant. Those aged 13-18 had the highest rate of Rs, while IA and R mean total costs were highest for those aged 5-12 (IA, $4,546-$5,822; R, $5,361-$7,113). The strongest risk factors for increasing R included nonelective admission and private hospital ownership. The strongest risk factors for increasing LOS and cost were major/extreme severity of illness and 30-day all-cause R. The intracluster correlation coefficient for the HMs were 0.06, 0.33, and 0.55 for the R, LOS, and cost model, respectively. CONCLUSIONS: The R rate was highest for those in the 13-18 age group, while the costs were highest for those aged 5-12.

Predictors of 30-day readmission and hospitalization costs of patients with hepatic encephalopathy in the US from 2010 to 2014.

BACKGROUND: Hepatic encephalopathy (HE) is a complex and reversible neuropsychiatric syndrome that is associated with growing, substantial healthcare resource utilization. We aim to examine the predictors of 30-day readmission and hospitalization cost associated with HE. RESEARCH DESIGN AND METHODS: We conducted a cross-sectional study using the Nationwide Readmissions Database from 2010 to 2014. We assessed the readmission rates using multivariate logistic regression and established temporal trends of readmission rates and hospitalization cost. Weighted hierarchical logistic regression and generalized linear mixed models were used to identify predictors for nationally representative readmissions and hospitalization costs, respectively. RESULTS: The number of index hospitalizations with HE increased with a significant trend from 34,967 in 2010 to 44,791 in 2014. 16.8% of patients were readmitted within 30 days. Predictors increasing readmission risk included female sex, Elixhauser readmission score < 25, elective admission, patient's state residential status, privately insured, number of diagnoses >13, and length of stay >4 days. CONCLUSIONS: Our results indicate there is a need to implement better management strategies to improve outcomes in patients hospitalized with HE to curb the increase in the economic burden associated with the disease.

Health care utilization and costs associated with direct-acting antivirals for patients with substance use disorders and chronic hepatitis C.

BACKGROUND: Patients with substance use disorders (SUD) and chronic hepatitis C virus infection (HCV) have limited access to direct-acting antivirals (DAAs) due to multilevel issues related to providers (eg, concern about reinfection); patients (eg, refusal); payers (eg, prior authorization); and health system structure, although clinical guidelines recommend timely DAA treatment for patients with SUD and HCV. Effects of DAAs on real-world health care utilization and costs among these patients is unknown. OBJECTIVE: To compare changes in medical service utilization and costs related to liver, SUD, and all-cause morbidity in patients with SUD and HCV treated with DAAs (DAA group) vs not treated with DAAs (non-DAA group). METHODS: We conducted a retrospective cohort study using MarketScan Commercial and Medicare Supplemental Claims databases (2012-2018) for newly diagnosed HCV treatment-naive adults with SUD. We used difference-in-differences analyses, stratified by cirrhosis status, to determine the adjusted ratio of rate ratio (RoRR) to assess the difference in the relative changes from the pre- to posttreatment periods between the 2 groups. RESULTS: 6,266 patients with SUD and HCV were identified. Of these patients who also had cirrhosis (n = 607), 49% (n = 298) initiated DAA therapy for HCV, whereas of those without cirrhosis (n = 5,659), 22% (n = 1,219) initiated DAAs. For patients with cirrhosis (n = 607), the liver-related costs decreased by $6,213 (95% CI = -$8,571, -$3,856) for the DAA group and $1,585 (95% CI = -$4,659, $1,490) for the non-DAA group. The relative decreases in the rate of liver-related costs were larger for the DAA group than for the non-DAA group, and the relative changes between groups were significantly different (RoRR = 0.37, 95% CI = 0.19-0.73). There was no difference in the relative changes after DAAs in the rate of SUD-related visits/costs or all-cause costs between the 2 groups. For patients without cirrhosis (n = 5,659), a similar association was observed. Besides, the relative decreases in the rate of SUD-related emergency department (ED) visits (RoRR = 0.54, 95% CI = 0.38-0.77); SUD-related long-term care visits (RoRR = 0.30, 95% CI = 0.13-0.73); all-cause ED visits (RoRR = 0.75, 95% CI = 0.64-0.88); and all-cause long term-care visits (RoRR = 0.36, 95% CI = 0.18-0.72) were larger in the DAA group than in the non-DAA group. CONCLUSIONS: DAAs are associated with a significant decrease in the rate of SUD-related ED visits and liver-related costs without increasing the rate of all-cause costs among patients with SUD and HCV, suggesting that the benefits of DAAs extended beyond liver-related outcomes, especially in this disadvantaged population. DISCLOSURES: Research reported in this publication was supported in part by the National Institute on Drug Abuse of the National Institutes of Health (K01DA045618). The funder did not have a role in the design, the execution, the analyses, the interpretation of the data, or the decision to submit the results of this study. The authors have no potential conflicts of interest.

Incorporating health equity into value assessment: frameworks, promising alternatives, and future directions.

Exploring methods that value diverse perspectives is critical to better understand the value of health equity in value assessment frameworks. In this paper, we examined emerging value assessment frameworks in the United States and present examples where evidence on outcomes and preferences for value do not take into consideration diverse perspectives. We identify possible solutions to improve existing value assessment methods and illustrate-using a hypothetical shared decision-making case study-an alternative to current value-assessment frameworks, "equitable multicriteria decision analysis," which could be implemented in the context of the value-based assessment of prevention choices for women at high risk of developing breast cancer. These proposed alternatives and solutions can be used by researchers and decision makers to incorporate health equity into value assessment. DISCLOSURES: No funding was received for this study. The authors have no conflicts of interest to report.

Cascade of Hepatitis C Virus Care Among Patients With Substance Use Disorders.

INTRODUCTION: Hepatitis C virus testing is recommended for people at high risk for infection, including those with substance use disorders. Little is known about the cascade of hepatitis C virus care (including testing, diagnosis, and treatments) among patients with substance use disorders in real-world clinical practice. This study aims to characterize the hepatitis C virus cascade of care and identify the factors associated with hepatitis C virus testing and diagnosis among Florida Medicaid beneficiaries with substance use disorders. METHODS: A retrospective cohort analysis of Florida Medicaid data (2013-2018) was conducted in 2020 for patients aged 18-64 years with newly diagnosed substance use disorders (year 2012 was used to ascertain 1-year previous enrollment). A generalized estimating equation identified the factors associated with hepatitis C virus testing; a multivariable logistic model identified the factors associated with hepatitis C virus diagnosis. RESULTS: Of the 156,770 patients with substance use disorders, 18% were tested for hepatitis C virus at least once. Among the tested patients, 8% had hepatitis C virus diagnoses. Among the 2,177 patients having a hepatitis C virus diagnosis, 11% initiated hepatitis C virus treatments, and 96% of them completed the hepatitis C virus treatments. Factors associated with being less likely to receive hepatitis C virus testing included being male (AOR=0.73, 95% CI=0.71, 0.75) and White (AOR=0.85, 95% CI=0.83, 0.87), whereas individuals who were male (AOR=1.49, 95% CI=1.35, 1.66) and White (AOR=2.71, 95% CI=2.38, 3.08) were more likely to be diagnosed with hepatitis C virus. The odds of receiving hepatitis C virus testing significantly increased annually (AOR=1.06, 95% CI=1.05, 1.07). CONCLUSIONS: Future studies are warranted to investigate the barriers to access hepatitis C virus testing and treatment among Florida Medicaid beneficiaries with substance use disorders, especially for White male individuals.