A welfare-theoretic model consistent with the practice of cost-effectiveness analysis and its implications

Gene Therapy Versus Common Care for Eligible Individuals With Sickle Cell Disease in the United States : A Cost-Effectiveness Analysis

BACKGROUND

Sickle cell disease (SCD) and its complications contribute to high rates of morbidity and early mortality and high cost in the United States and African heritage community.

OBJECTIVE

To evaluate the cost-effectiveness of gene therapy for SCD and its value-based prices (VBPs).

DESIGN

Comparative modeling analysis across 2 independently developed simulation models (University of Washington Model for Economic Analysis of Sickle Cell Cure [UW-MEASURE] and Fred Hutchinson Institute Sickle Cell Disease Outcomes Research and Economics Model [FH-HISCORE]) using the same databases.

DATA SOURCES

Centers for Medicare & Medicaid Services claims data, 2008 to 2016; published literature.

TARGET POPULATION

Persons eligible for gene therapy.

TIME HORIZON

Lifetime.

PERSPECTIVE

U.S. health care sector and societal.

INTERVENTION

Gene therapy versus common care.

OUTCOME MEASURES

Incremental cost-effectiveness ratios (ICERs), equity-informed VBPs, and price acceptability curves.

RESULTS OF BASE-CASE ANALYSIS

At an assumed $2 million price for gene therapy, UW-MEASURE and FH-HISCORE estimated ICERs of $193 000 per QALY and $427 000 per QALY, respectively, under the health care sector perspective. Corresponding estimates from the societal perspective were $126 000 per QALY and $281 000 per QALY. The difference in results between models stemmed primarily from considering a slightly different target population and incorporating the quality-of-life (QOL) effects of splenic sequestration, priapism, and acute chest syndrome in the UW model. From a societal perspective, acceptable (>90% confidence) VBPs ranged from $1 million to $2.5 million depending on the use of alternative effective metrics or equity-informed threshold values.

RESULTS OF SENSITIVITY ANALYSIS

Results were sensitive to the costs of myeloablative conditioning before gene therapy, effect on caregiver QOL, and effect of gene therapy on long-term survival.

LIMITATION

The short-term effects of gene therapy on vaso-occlusive events were extrapolated from 1 study.

CONCLUSION

Gene therapy for SCD below a $2 million price tag is likely to be cost-effective when applying a societal perspective at an equity-informed threshold for cost-effectiveness analysis.

PRIMARY FUNDING SOURCE

National Heart, Lung, and Blood Institute.

Mapping the EORTC QLQ-C30 and QLQ H&N35 to the EQ-5D-5L and SF-6D for papillary thyroid carcinoma

PURPOSE

Empirical evidence for the EORTC QLQ C30 scale in thyroid cancer mapping algorithms has not been found in China, which limits the cost-utility analysis of patients with papillary thyroid carcinoma (PTC) population. We developed mapping algorithms that use the EORTC QLQ-C30 and QLQ H&N35 to predict EQ-5D-5L and SF-6D health utility scores for PTC patients.

METHODS

Data from 1050 Chinese PTC patients who completed the EORTC QLQ-C30, QLQ H&N35, EQ-5D-5L and SF-6D instruments were collected. Direct mapping (OLS, Tobit, Betamix) and indirect mapping functions (Order Probit) were used to estimate algorithms. The goodness-of-fit of mapping performance was assessed by MAE, RMSE, AIC, BIC, AE, and ICC. A fivefold cross-validation and random sample validation approach were used to test the stability of the models.

RESULTS

The mean EQ-5D-5L and SF-6D utility scores were 0.8704 and 0.6368, respectively. We recommend the Betamix model for the EQ-5D-5L (MAE = 0.0363, RMSE = 0.0505, AIC = -3458.73, BIC = -3096.91, AE > 0.05(%) = 48.38, AE > 0.1(%) = 8.67, ICC = 0.8288 for the full sample dataset) and the Betamix model for the SF-6D (MAE = 0.0328, RMSE = 0.0417, AIC = -2788.91, BIC = -2605.51, AE > 0.05(%) = 42.76, AE > 0.1(%) = 3.62, ICC = 0.8657 for the full sample dataset), with EORTC QLQ-C30 all items, QLQ H&N35 all items, age and gender as the predicted variables showing the best performance.

CONCLUSION

In the absence of preference-based quality of life tools, the mapping algorithms reported here are effective alternative for predicting the health utility of PTC patients, contributing to the cost-utility analysis studies.

Associating Health-Related Quality-of-Life Score with Time Uses to Inform Productivity Measures in Cost-Effectiveness Analysis

BACKGROUND

The Second Panel on Cost Effectiveness in Health and Medicine recommended that cost-effectiveness analyses (CEA) explicitly incorporate the valuation of productive time from a societal perspective. We developed a new approach to capture productivity impacts in CEA without direct evidence on these impacts by associating varying levels of health-related quality-of-life (HrQoL) score with different time uses in the United States.

METHODS

We conceptualized a framework that estimates the association between HrQoL score with productivity through time uses. We used the American Time-Use Survey (ATUS) from year 2012-2013, when data on a Well-Being Module (WBM) was additionally collected alongside ATUS. The WBM measured the quality of life (QoL) score using a visual analog scale. To operationalize our conceptual framework, we employed an econometric approach that addressed three technical issues in the observed data: (i) distinction between overall QoL and HrQoL, (ii) correlation across different categories of time use and the share structure of time-use data, and (iii) reverse causality between time uses and HrQoL score in a cross-sectional setting. Furthermore, we developed a metamodel-based algorithm to summarize the numerous estimates from the primary econometric model efficiently. Finally, we illustrated the use of our algorithm to calculate productivity and time spent seeking care costs in an empirical CEA of a prostate cancer treatment.

RESULTS

We provide the estimates of the metamodel algorithm. Incorporating these estimates into the empirical CEA reduced the incremental cost-effectiveness ratio by 27%.

CONCLUSION

Our estimates can facilitate the inclusion of productivity and time spent seeking care in CEA as recommended by the Second Panel.

The Value of Health in a Cost-Effectiveness Analysis: Theory Versus Practice

A cost-effectiveness analysis has become an important method to inform allocation decisions and reimbursement of new technologies in healthcare. A cost-effectiveness analysis requires a threshold to which the cost effectiveness of a new intervention can be compared. In principle, the threshold ought to reflect opportunity costs of reimbursing a new technology. In this paper, we contrast the practical use of this threshold within a CEA with its theoretical underpinnings. We argue that several assumptions behind the theoretical models underlying this threshold are violated in practice. This implies that a simple application of the decision rules of CEA using a single estimate of the threshold does not necessarily improve population health or societal welfare. Conceptual differences regarding the interpretation of the threshold, widely varying estimates of its value, and an inconsistent use within and outside the healthcare sector are important challenges in informing policy makers on optimal reimbursement decision and setting appropriate healthcare budgets.

Avoiding Opportunity Cost Neglect in Cost-Effectiveness Analysis for Health Technology Assessment

Despite being a fundamental tenet of economic analysis there is a lack of clarity regarding the relevance of opportunity costs to cost-effectiveness analysis for health technology assessment. We argue that this is due, in part, to the importance of the decision context in understanding the nature of opportunity costs. Taking the example of the National Institute of Health and Care Excellence (NICE) on behalf of the National Health Service (NHS) in England and Wales, we explore the implications of existing discrepancies between policy thresholds and emerging empirical evidence of health opportunity costs. In particular, we consider analysts communicating the results of cost-effectiveness analysis, and recommend that analysts provide analysis according to both the policy threshold and the latest empirical evidence until the discrepancies are better understood or resolved. A number of conceptually related, but distinct, issues are discussed and clarified.

A Cost Decision Model Supporting Treatment Strategy Selection in BRCA1/2 Mutation Carriers in Breast Cancer

In this paper, a cost decision-making model that compares the healthcare costs for diverse treatment strategies is built for BRCA-mutated women with breast cancer. Moreover, this model calculates the cancer treatment costs that could potentially be prevented, if the treatment strategy with the lowest total cost, along the entire lifetime of the patient, is chosen for high-risk women with breast cancer. The benchmark of the healthcare costs for diverse treatment strategies is selected in the presence of uncertainty, i.e., considering, throughout the lifetime of the patient, the risks and complications that may arise in each strategy and, therefore, the costs associated with the management of such events. Our results reveal a clear economic advantage of adopting the cost decision-making model for benchmarking the healthcare costs for various treatment strategies for BRCA-mutated women with breast cancer. The cost savings were higher when all breast cancer patients underwent counseling and genetic testing before deciding on any diagnostic-therapeutic path, with a probability of obtaining savings of over 75%.

Catalog of Age- and Medical Condition-Specific Healthcare Costs in the United States to Inform Future Costs Calculations in Cost-Effectiveness Analysis

OBJECTIVES

This study aims to develop a catalog of annual age- and medical condition-specific healthcare costs per capita among those who are living at a certain age (survivors) and the costs attributable to death itself for those who die at that age (decedents) in the United States. These estimates can be used to inform future cost calculations in cost-effectiveness analysis (CEA).

METHODS

We discussed a theoretical framework to incorporate futures costs in CEA. We used the nationally representative Medical Expenditure Panel Survey data to estimate costs among survivors and death costs. For survivors, we obtained cost estimates nonparametrically using kernel-based regression and locally weighted scatterplot smoothing. We estimated costs attributable to death using inverse probability weights comparing decedents with appropriately weighted survivors at a given age after controlling for more than 270 clinical condition classifications, demographics, and interactions. Cost estimates were expressed in 2019 US dollar and also separately by sex and specific clinical conditions.

RESULTS

Average healthcare costs per capita among survivors, expectedly, rose over age from $2062 (95% confidence interval [CI] $1553-$2478) during the first year of life to $14 307 (95% CI $13 706-$14 956) at 85 years or older. Average costs of death were $44 569 (95% CI $14 304-$67 369) during the first year of life and declined by -$321 (95% CI -$620 to -$22) per 1 year older.

CONCLUSIONS

The US catalog of healthcare costs among survivors and decedents can facilitate calculations of future costs in CEA as recommended by the Second Panel on Cost-Effectiveness in Health and Medicine.

RACE-IT - Rapid Acute Coronary Syndrome Exclusion using the Beckman Coulter Access high-sensitivity cardiac troponin I: A stepped-wedge cluster randomized trial

BACKGROUND

Protocols utilizing high-sensitivity cardiac troponin (hs-cTn) assays for the evaluation of suspected acute coronary syndrome (ACS) in the emergency department (ED) have been gaining popularity across the US and the world. These protocols more rapidly rule-out ACS and more accurately identify the presence of acute myocardial injury. At this time, few randomized trials have evaluated the safety and operational impact of these assays, resulting in limited evidence to guide the use and implementation of hs-cTn in the ED.

OBJECTIVE

The main study objective is to test the effectiveness of a rapid ACS rule-out pathway using hs-cTnI in safely discharging patients from the ED for whom clinical suspicion for ACS exists.

DESIGN

This prospective, implementation trial (n = 11,070) will utilize a stepped wedge cluster randomized trial design. The design will allow for all participating sites to capture benefit from the implementation of the hs-cTnI pathway while providing data evaluating the effectiveness in providing safe and rapid evaluation of patients with clinical suspicion for ACS.

SUMMARY

Demonstrating that clinical pathways using hs-cTnI can be effectively implemented to rapidly rule-out ACS while conserving costly hospital resources has significant implications for the care of patients with possible acute cardiac conditions in EDs across the US.

CLINICALTRIALSGOV IDENTIFIER

NCT04488913.

A Health Opportunity Cost Threshold for Cost-Effectiveness Analysis in the United States

BACKGROUND

Cost-effectiveness analysis is an important tool for informing treatment coverage and pricing decisions, yet no consensus exists about what threshold for the incremental cost-effectiveness ratio (ICER) in dollars per quality-adjusted life-year (QALY) gained indicates whether treatments are likely to be cost-effective in the United States.

OBJECTIVE

To estimate a U.S. cost-effectiveness threshold based on health opportunity costs.

DESIGN

Simulation of short-term mortality and morbidity attributable to persons dropping health insurance due to increased health care expenditures passed though as premium increases. Model inputs came from demographic data and the literature; 95% uncertainty intervals (UIs) were constructed.

SETTING

Population-based.

PARTICIPANTS

Simulated cohort of 100 000 individuals from the U.S. population with direct-purchase private health insurance.

MEASUREMENTS

Number of persons dropping insurance coverage, number of additional deaths, and QALYs lost from increased mortality and morbidity, all per increase of $10 000 000 (2019 U.S. dollars) in population treatment cost.

RESULTS

Per $10 000 000 increase in health care expenditures, 1860 persons (95% UI, 1080 to 2840 persons) were simulated to become uninsured, causing 5 deaths (UI, 3 to 11 deaths), 81 QALYs (UI, 40 to 170 QALYs) lost due to death, and 15 QALYs (UI, 6 to 32 QALYs) lost due to illness; this implies a cost-effectiveness threshold of $104 000 per QALY (UI, $51 000 to $209 000 per QALY) in 2019 U.S. dollars. Given available evidence, there is about 14% probability that the threshold exceeds $150 000 per QALY and about 48% probability that it lies below $100 000 per QALY.

LIMITATIONS

Estimates were sensitive to inputs, most notably the effects of losing insurance on mortality and of premium increases on becoming uninsured. Health opportunity costs may vary by population. Nonhealth opportunity costs were excluded.

CONCLUSION

Given current evidence, treatments with ICERs above the range $100 000 to $150 000 per QALY are unlikely to be cost-effective in the United States.

PRIMARY FUNDING SOURCE

None.