Journal of Health Economics and Outcomes Research最新文献

The quality-adjusted life-year (QALY) is a metric widely used when assessing the cost-effectiveness of drugs and other health interventions. The assessments are used in the development of recommendations for pricing, formulary placement decisions, and health policy decisions. A new bill, H.R. 485, the Protecting Health Care for All Patients Act of 2023, was approved by the US House Energy and Commerce Health Subcommittee that will, if passed, end the practice of using QALYs in all federal programs.^1,2 Proponents of the ban say that QALYs undervalue the positive effects of therapeutics on people with disabilities.³ We share their concerns. Furthermore, our review of the mathematical properties of QALYs, including an analysis of quality-of-life utility (QOL utility) data recently collected from patients with inflammatory bowel disease (IBD), has led us to conclude that QALYs are an inappropriate metric of drug and treatment cost-effectiveness for all people, both disabled and nondisabled, and should not be the basis for US healthcare policy decisions.

Background: Traditional health economic evaluations of antimicrobials currently underestimate their value to wider society. They can be supplemented by additional value elements including insurance value, which captures the value of an antimicrobial in preventing or mitigating impacts of adverse risk events. Despite being commonplace in other sectors, constituents of the impacts and approaches for estimating insurance value have not been investigated. Objectives: This study assessed the insurance value of a novel gram-negative antimicrobial from operational healthcare, wider population health, productivity, and informal care perspectives. Methods: A novel mixed-methods approach was used to model insurance value in the United Kingdom: (1) literature review and multidisciplinary expert workshops to identify risk events for 4 relevant scenarios: ward closures, unavoidable shortage of conventional antimicrobials, viral respiratory pandemics, and catastrophic antimicrobial resistance (AMR); (2) parameterizing mitigable costs and frequencies of risk events across perspectives and scenarios; (3) estimating insurance value through a Monte Carlo simulation model for extreme events and a dynamic disease transmission model. Results: The mean insurance value across all scenarios and perspectives over 10 years in the UK was £718 million, should AMR remain unchanged, where only £134 million related to operational healthcare costs. It would be 50%-70% higher if AMR steadily increased or if a more risk-averse view (1-in-10 year downside) of future events is taken. Discussion: The overall insurance value if AMR remains at current levels (a conservative projection), is over 5 times greater than insurance value from just the operational healthcare costs perspective, traditionally the sole perspective used in health budgeting. Insurance value was generally larger for nationwide or universal (catastrophic AMR, pandemic, and conventional antimicrobial shortages) rather than localized (ward closure) scenarios, across perspectives. Components of this insurance value match previously published estimates of operational costs and mortality impacts. Conclusions: Insurance value of novel antimicrobials can be systematically modeled and substantially augments their traditional health economic value in normal circumstances. These approaches are generalizable to similar health interventions and form a framework for health systems and governments to capture broader value in health technology assessments, improve healthcare access, and increase resilience by planning for adverse scenarios.

Background: Targeted therapy for cancer is becoming more frequent as the understanding of the molecular pathogenesis increases. Molecular testing must be done to use targeted therapy. Unfortunately, the testing turnaround time can delay the initiation of targeted therapy. Objective: To investigate the impact of a next-generation sequencing (NGS) machine in the hospital that would allow for in-house NGS testing of metastatic non-small cell lung cancer (mNSCLC) in a US setting. Methods: The differences between 2 hospital pathways were established with a cohort-level decision tree that feeds into a Markov model. A pathway that used in-house NGS (75%) and the use of external laboratories (so-called send-out NGS) (25%), was compared with the standard of exclusively send-out NGS. The model was from the perspective of a US hospital over a 5-year time horizon. All cost input data were in or inflated to 2021 USD. Scenario analysis was done on key variables. Results: In a hospital with 500 mNSCLC patients, the implementation of in-house NGS was estimated to increase the testing costs and the revenue of the hospital. The model predicted a $710 060 increase in testing costs, a $1 732 506 increase in revenue, and a $1 022 446 return on investment over 5 years. The payback period was 15 months with in-house NGS. The number of patients on targeted therapy increased by 3.38%, and the average turnaround time decreased by 10 days when in-house NGS was used. Discussion: Reducing testing turnaround time is a benefit of in-house NGS. It could contribute to fewer mNSCLC patients lost to second opinion and an increased number of patients on targeted therapy. The model outcomes predicted that, over a 5-year period, there would be a positive return on investment for a US hospital. The model reflects a proposed scenario. The heterogeneity of hospital inputs and the cost of send-out NGS means context-specific inputs are needed. Conclusion: Using in-house NGS testing could reduce the testing turnaround time and increase the number of patients on targeted therapy. Additional benefits for the hospital are that fewer patients will be lost to second opinion and that in-house NGS could generate additional revenue.

Background: Prostate cancer is the second most common cancer in men, with up to one-third of men being diagnosed in their lifetime. Recently, novel therapies have received regulatory approval with significant improvement in overall survival for metastatic castration-resistant prostate cancer, metastatic hormone-sensitive prostate cancer, and nonmetastatic castration-resistant prostate cancer. To improve decision-making regarding the value of anticancer therapies and support standardized assessment for use by health technology assessment (HTA) agencies, the European Society for Medical Oncology (ESMO) has developed a Magnitude of Clinical Benefit Scale (MCBS). Objective: This review aimed to map HTA status, reimbursement restrictions, and patient access for 3 advanced prostate cancer indications across 23 European countries during 2011-2021. Methods: HTA, country reimbursement lists, and ESMO-MCBS scorecards were reviewed for evidence and data across 26 European countries. Results: The analysis demonstrated that only in Greece, Germany, and Sweden was there full access across all included prostate cancer treatments. Treatments available for metastatic castration-resistant prostate cancer were widely reimbursed, with both abiraterone and enzalutamide accessible in all countries. In 3 countries (Hungary, the Netherlands, and Switzerland), there was a statistically significant difference (P<.05) between status of reimbursement and ESMO-MCBS "substantial benefit" (score of 4 or 5) vs "no substantial benefit" (score <4). Conclusion: Overall, the impact of the ESMO-MCBS on reimbursement decisions in Europe is unclear, with significant variation across the countries included in this review.

Background: Research on employee care partners of patients with multiple sclerosis (MS) is limited. Objectives: The clinical and economic impact on employee care partners was evaluated by MS disease severity. Methods: Employees with spouses/domestic partners with MS from the Workpartners database (Jan. 1, 2010-Dec. 31, 2019) were eligible if: spouse/partner had at least 3 MS-related (ICD-9-CM/ICD-10-CM:340.xx/G35) inpatient/outpatient/disease-modifying therapy claims within 1 year (latest claim = index date); 6-month pre-index/1-year post-index enrollment; and age 18 to 64 years. Employee care partners' demographic/clinical characteristics and direct/indirect costs were compared across predetermined MS severity categories. Logistic and generalized linear regression modeled the costs. Results: Among 1041 employee care partners of patients with MS, 358 (34.4%) patients had mild MS, 491 (47.2%) moderate, and 192 (18.4%) severe. Mean (standard error [SE]) employee care partner age was 49.0 (0.5) for patients with mild disease, 50.5 (0.4) for moderate, 51.7 (0.6) for severe; percent female care partners was 24.6% [2.3%] mild, 19.8% [1.8%] moderate, 27.6% [3.2%] severe; and mean care partner Charlson Comorbidity Index scores 0.28 (0.05) mild, 0.30 (0.04) moderate, 0.27 (0.06) severe. More care partners of patients with moderate/severe vs mild MS had hyperlipidemia (32.6%/31.8% vs 21.2%), hypertension (29.5%/29.7% vs 19.3%), gastrointestinal disease (20.8%/22.9% vs 13.1%), depression (9.2%/10.9% vs 3.9%), and anxiety 10.6%/8.9% vs 4.2%). Adjusted mean medical costs were greater for employee care partners of patients with moderate vs mild/severe disease (P<.001). Pharmacy costs (SE) were lower for employee care partners of mild vs severe/moderate patients (P<.005). Sick leave costs (SE) were greater for employee care partners of mild/severe vs moderate patients (P<.05). Discussion: Employee care partners of patients with moderate/severe vs mild MS had more comorbidities (ie, hypertension, gastrointestinal disease, depression, and anxiety) and higher pharmacy costs. Employee care partners of patients with moderate vs mild/severe MS had higher medical and lower sick leave costs. Treatment strategies that improve patient outcomes may reduce employee care partner burden and lower costs for employers in some instances. Conclusions: Comorbidities and direct/indirect costs of employees whose spouses/partners have MS were considerable and varied with MS severity.

Highlighting other risk factors for cardiovascular disease could enhance Adeniji and Obembe's study.