Developing Open-Source Models for the US Health System: Practical Experiences and Challenges to Date with the Open-Source Value Project.

The Innovation and Value Initiative started the Open-Source Value Project with the aim to improve the credibility and relevance of model-based value assessment in the context of the US healthcare environment. As a core activity of the Open-Source Value Project, the Innovation and Value Initiative develops and provides access to flexible open-source economic models that are developed iteratively based on public feedback and input. In this article, we describe our experience to date with the development of two currently released, Open-Source Value Project models, one in rheumatoid arthritis and one in epidermal growth factor receptor-positive non-small-cell lung cancer. We developed both Open-Source Value Project models using the statistical programming language R instead of spreadsheet software (i.e., Excel), which allows the models to capture multiple model structures, model sequential treatment with individual patient simulations, and improve integration with formal evidence synthesis. By developing the models in R, we were also able to use version control systems to manage changes to the source code, which is needed for iterative and collaborative model development. Similarly, Open-Source Value Project models are freely available to the public to provide maximum transparency and facilitate collaboration. Development of the rheumatoid arthritis and non-small-cell lung cancer model platforms has presented multiple challenges. The development of multiple components of the model platform tailored to different audiences, including web interfaces, required more resources than a cost-effectiveness analysis for a publication would. Furthermore, we faced methodological hurdles, in particular related to the incorporation of multiple competing model structures and novel elements of value. The iterative development based on public feedback also posed some challenges during the review phase, where methodological experts did not always understand feedback from clinicians and vice versa. Response to the Open-Source Value Project by the modeling community and patient organizations has been positive, but feedback from US decision makers has been limited to date. As we progress with this project, we hope to learn more about the feasibility, benefits, and challenges of an open-source and collaborative approach to model development for value assessment.

Share of Oncology Versus Nononcology Spending in Episodes Defined by the Centers for Medicare & Medicaid Services Oncology Care Model.

PURPOSE: Performance-based payments to oncology providers participating in the Centers for Medicare & Medicaid Services (CMS) Oncology Care Model (OCM) are based, in part, on overall spending in 6-month episodes of care, including spending unrelated to oncology care. The amount of spending likely to occur outside of oncologists' purview is unknown. METHODS: Following the OCM definition of an episode, we used SEER-Medicare data from 2006 to 2013 to identify episodes of cancer care for the following diagnoses: breast cancer (BC), non-small-cell lung cancer, renal cell carcinoma, multiple myeloma (MM), and chronic myeloid leukemia. Claims were categorized by service type and, separately, whether the content fell within the purview of oncology providers (classified as oncology, with all other claims nononcology). We calculated the shares of episode spending attributable to oncology versus nononcology services. RESULTS: The percentage of oncology spending within OCM episodes ranged from 62.4% in BC to 85.5% in MM. The largest source of oncology spending was antineoplastic drug therapy, ranging from 21.8% of total episode spending in BC to 67.6% in chronic myeloid leukemia. The largest source of nononcology spending was acute hospitalization and inpatient physician costs, ranging from 6.6% of overall spending for MM to 10.4% for non-small-cell lung cancer; inpatient oncology spending contributed roughly similar shares to overall spending. CONCLUSION: Most spending in OCM-defined episodes was attributable to services related to cancer care, especially antineoplastic drug therapy. Inability to control nononcology spending may present challenges for practices participating in the OCM, however.

Value of expanding HCV screening and treatment policies in the United States.

OBJECTIVES: To investigate the value of expanding screening and treatment for hepatitis C virus (HCV) infection in the United States. STUDY DESIGN: Discrete-time Markov model. METHODS: We modeled HCV progression and transmission to analyze the costs and benefits of investment in screening and treatment over a 20-year time horizon. Population-level parameters were estimated using National Health and Nutrition Examination Survey data and published literature. We considered 3 screening scenarios that vary in terms of clinical guidelines and physician awareness of guidelines. For each screening scenario, we modeled 3 approaches to treatment, varying the fibrosis stage of treatment initiation. Net social value was the key model outcome, calculated as the value of benefits from improved quality-adjusted survival and reduced transmission minus screening, treatment, and medical costs. RESULTS: Expanded screening policies generated the largest value to society. However, this value is constrained by the availability of treatment to diagnosed patients. Screening all individuals in the population generates $0.68 billion in social value if diagnosed patients are treated in fibrosis stages F3-F4 compared with $824 billion if all diagnosed patients in stages F0-F4 are treated. Moreover, increased screening generates cumulative net social value by year 8 to 9 under expanded treatment policies compared with 20 years if only patients in stages F3-F4 are treated. CONCLUSIONS: Although increasing screening for HCV may generate some value to society, only when paired with expanded access to treatment at earlier disease stages will it produce considerable value. Such a "test and treat" strategy is likely to entail higher short-term costs but also yield the greatest social benefits.

Evaluating Expected Costs and Benefits of Granting Access to New Treatments on the Basis of Progression-Free Survival in Non-Small-Cell Lung Cancer.

IMPORTANCE: Surrogate end points may be used as proxy for more robust clinical end points. One prominent example is the use of progression-free survival (PFS) as a surrogate for overall survival (OS) in trials for oncologic treatments. Decisions based on surrogate end points may expedite regulatory approval but may not accurately reflect drug efficacy. Payers and clinicians must balance the potential benefits of earlier treatment access based on surrogate end points against the risks of clinical uncertainty. OBJECTIVE: To present a framework for evaluating the expected net benefit or cost of providing early access to new treatments on the basis of evidence of PFS benefits before OS results are available, using non-small-cell lung cancer (NSCLC) as an example. DESIGN, SETTING, AND PARTICIPANTS: A probabilistic decision model was used to estimate expected incremental social value of the decision to grant access to a new treatment on the basis of PFS evidence. The model analyzed a hypothetical population of patients with NSCLC who could be treated during the period between PFS and OS evidence publication. Estimates for delay in publication of OS evidence following publication of PFS evidence, expected OS benefit given PFS benefit, incremental cost of new treatment, and other parameters were drawn from the literature on treatment of NSCLC. MAIN OUTCOMES AND MEASURES: Incremental social value of early access for each additional patient per month (in 2014 US dollars). RESULTS: For "medium-value" model parameters, early reimbursement of drugs with any PFS benefit yields an incremental social cost of more than $170,000 per newly treated patient per month. In contrast, granting early access on the basis of PFS benefit between 1 and 3.5 months produces more than $73,000 in incremental social value. Across the full range of model parameter values, granting access for drugs with PFS benefit between 3 and 3.5 months is robustly beneficial, generating incremental social value ranging from $38,000 to more than $1 million per newly treated patient per month, whereas access for all drugs with any PFS benefit is usually not beneficial. CONCLUSIONS AND RELEVANCE: The value of providing access to new treatments on the basis of surrogate end points, and PFS in particular, likely varies considerably. Payers and clinicians should carefully consider how to use PFS data in balancing potential benefits against costs in each particular disease.

Cancer mortality reductions were greatest among countries where cancer care spending rose the most, 1995-2007.

Health care spending and health outcomes vary markedly across countries, but the association between spending and outcomes remains unclear. This inevitably raises questions as to whether continuing growth in spending is justified, especially relative to the rising cost of cancer care. We compared cancer care across sixteen countries over time, examining changes in cancer spending and two measures of cancer mortality (amenable and excess mortality). We found that compared to low-spending health systems, high-spending systems had consistently lower cancer mortality in the period 1995-2007. Similarly, we found that the countries that increased spending the most had a 17 percent decrease in amenable mortality, compared to 8 percent in the countries with the lowest growth in cancer spending. For excess mortality, the corresponding decreases were 13 percent and 9 percent. Additionally, the rate of decrease for the countries with the highest spending growth was faster than the all-country trend. These findings are consistent with the existence of a link between higher cancer spending and lower cancer mortality. However, further work is needed to investigate the mechanisms that underlie this correlation.

Economic burden of community-based disease-associated malnutrition in the United States.

BACKGROUND: The burden imposed by disease-associated malnutrition (DAM) on patients and the healthcare system in food-abundant industrialized countries is often underappreciated. This study measured the economic burden of community-based DAM in the United States. METHODS: The burden of DAM was quantified in terms of direct medical costs, quality-adjusted life years lost, and mortality across 8 diseases (breast cancer, chronic obstructive pulmonary disease [COPD], colorectal cancer [CRC], coronary heart disease [CHD], dementia, depression, musculoskeletal disorders, and stroke). To estimate the total economic burden, the morbidity and mortality burden was monetized using a standard value of a life year and combined with direct medical costs of treating DAM. Disease-specific prevalence and malnutrition estimates were taken from the National Health Interview Survey and the National Health and Nutrition Examination Survey. Deaths by disease were taken from the Center for Disease Control and Prevention. Estimates of costs and morbidity were taken from the literature. RESULTS: The annual burden of DAM across the 8 diseases was $156.7 billion, or $508 per U.S. resident. Nearly 80% of this burden was derived from morbidity associated with DAM; around 16% derived from mortality and the remainder from direct medical costs of treating DAM. The total burden was highest in COPD and depression, while the burden per malnourished individual was highest in CRC and CHD. CONCLUSION: DAM exacts a large burden on American society. Therefore, improved diagnosis and management of community-based DAM to alleviate this burden are needed.

Early HIV treatment in the United States prevented nearly 13,500 infections per year during 1996-2009.

In recent years, guidelines for HIV treatment have recommended initiation of combination antiretroviral therapy (cART) earlier in the course of the disease than was previously the case. These recommendations stem in part from growing evidence that treatment reduces the risk of sexual transmission. We used an epidemiological model of disease transmission and progression to assess HIV prevention through early treatment-that is, initiation of cART when CD4 white blood cell counts are in excess of 350 cells per cubic millimeter. (CD4 cells are involved in the immune system's defense against tumors and infection; the number of CD4 cells in a cubic millimeter of blood is a standard measure of immune response to antiretroviral therapy.) We estimated that the actual timing of treatment initiation in the United States prevented 188,000 HIV cases in the period 1996-2009. "Very early" treatment (at CD4 counts greater than 500) accounted for four-fifths of the prevented cases. For all of the prevented cases, the losses in life expectancy that were avoided were worth $128 billion, assuming that a life-year has a value of $150,000. These findings underscore the cost-effectiveness of early HIV treatment.