PerspectiveHEALTH ECONOMICS

Buying cures versus renting health: Financing health care with consumer loans

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Science Translational Medicine  24 Feb 2016:
Vol. 8, Issue 327, pp. 327ps6
DOI: 10.1126/scitranslmed.aad6913
  • Fig. 1. HCL fund: Cash flow diagram.

    (A) During the investment period, the investors buy the notes issued by the SPE, and using the cash raised from the sale of the notes, the SPE pays a portion of the drug’s price. (B) During the repayment period, the patients make their annual loan payments, and the investors receive cash payments based on the seniority of their notes. The losses, if any, propagate from the bottom to the top (red arrow).

  • Fig. 2. Assumptions used in the simulations.

    (A) The cumulative distribution function (CDF) of the annual household income for patients with chronic HCV (blue line and left axis) and the estimated expected default probability as a function of income for three different scenarios (right axis). (B) The CDF of annual default probability, in the baseline scenario, for multiple incomes as well as the whole patient population (income >$35,000). The numbers in parentheses denote the expected default probability associated with that category. (C) The U.S. Census Bureau’s projected numbers for the baby-boomer generation as well as our estimated postmedication survival curve for each patient (16). (D) The annual probability of death based on the survival curve in (C) over the 9-year HCL term.

  • Table 1. Unresolved issues and perceived complications.

    Each of these issues must be addressed in order to implement a comprehensive HCL strategy that increases the availability of trasformative therapies and incentivizes their development.

    IssueComment
    Low median income and/or poor credit of
    some patients
    A subset of patients would continue to “fall through the cracks” that exist in any multipayer system. Government guarantees, rebates, or incentives could address this gap, as in the case of mortgages, student loans, and other forms of consumer finance.
    Economic externalities of infections such
    as HCV
    An “externality” refers to a cost or a benefit affecting an individual who has not chosen that cost or benefit. An infectious disease imposes a negative externality on infected individuals, and eradicating such a disease provides a positive externality on all who would be exposed to infection. These externalities have implications for policy decisions and have not been considered in our analysis.
    Differences between U.S. and foreign pricingU.S. drug prices are among the highest in the world. Thus, proposing that U.S. patients assume larger copayments seems even more inequitable. There are many factors that cause U.S. prices to be higher than those in other countries, including the fact that our multipayer health care system is based on principles of competition and free-market pricing. One benefit of such a system is that transformative therapies are often available first to U.S. patients and, in some cases, unavailable in single-payer countries. The consequence of such access is higher U.S. prices, which can be interpreted as U.S. patients subsidizing drugs for non-U.S. patients. These price differences have political and ethical implications that are outside the scope of our analysis.
    Impact of price increases owing to a larger market resulting from HCLsHCLs could cause drug prices to increase in the short term because of increased demand for therapies that were previously unaffordable. Over longer terms, the price impact of HCLs is unclear given countervailing forces, such as increased competition due to greater incentives for producing transformative therapies, greater negotiating power via HCL lenders, and cheaper financing of copayments. There may also be unintended income-distributional consequences of the emergence of liquid HCL markets—for example, the lowest-income patients getting priced out of certain therapies, even as middle-class patients gain greater access. These effects must be monitored carefully and may require government intervention, as in other consumer-finance contexts such as housing and education.
    Limitations of consumer credit risk modelOur proposed statistical model for the financial risk of HCLs can be improved by use of proprietary data available only to payers. For example, one regional insurer may tend to attract healthier policyholders, whereas another insurer may be subject to the opposite tendency; such selection biases could affect statistical estimates of HCL default rates. Publicly available data on student loans and other consumer financing might not fully capture such risks of HCLs.
    Misaligned incentivesTo avoid problematic practices from the recent financial crisis, approaches such as a risk-retention policy should be considered. This would impose partial ownership of each securitization on the issuer (the bank) and thereby align stakeholder interests.
    Limitations on defaultSince the passage of the Bankruptcy Abuse Prevention and Consumer Protection Act of 2005, consumers with student loans are prevented from defaulting by excluding them from bankruptcy proceedings except in cases of “undue hardship.” This feature of the student loan market has received mixed reviews from various stakeholders. Some argue that it is essential protection for consumers who are unable to afford the legal expense of bankruptcy proceedings. Others counter that it is tantamount to indentured servitude and subsidizes lenders by reducing default risk at the expense of borrowers and taxpayers. Almost by definition, many patients face “undue hardship”; hence, preventing those with HCLs from declaring bankruptcy is unlikely to be either practical or socially acceptable.
    Tracking value over the
    amortization period
    Systems, metrics, and legal frameworks currently do not exist for determining ongoing patient benefit, but are necessary for the implementation of health-contingent amortization payment agreements. These elements are likely to emerge rapidly to support HCL markets as they grow and become more liquid. Privacy issues must be balanced with requirements for tracking individual outcomes.

Supplementary Materials

  • www.sciencetranslationalmedicine.org/cgi/content/full/8/327/327ps6/DC1

    Portfolio theory: A simple example

    Securitization

    HCL portfolio assumptions

    Credit enhancement techniques

    HCL default assumptions

    Post-treatment survival curve estimation

    HCL fund performance results

    Table S1. Model parameters

    Table S2. Simulated performance results

    Fig. S1. Risk, return, diversification, and securitization

    Fig. S2. HCL default model

    Fig. S3. Student-loan data

    Fig. S4. Goodness-of-fit of default models

    Fig. S5. Estimated post-treatment survival rates

    Fig. S6. Sensitivity analysis of simulated performance

    References (2131)

  • Supplementary Material for:

    Buying cures versus renting health: Financing health care with consumer loans

    Vahid Montazerhodjat, David M. Weinstock,* Andrew W. Lo*

    *Corresponding author. E-mail: alo-admin{at}mit.edu (A.W.L.); dweinstock{at}partners.org (D.M.W.)

    Published 24 February 2016, Sci. Transl. Med. 8, 327ps6 (2016)
    DOI: 10.1126/scitranslmed.aad6913

    This PDF file includes:

    • Portfolio theory: A simple example
    • Securitization
    • HCL portfolio assumptions
    • Credit enhancement techniques
    • HCL default assumptions
    • Post-treatment survival curve estimation
    • HCL fund performance results
    • Table S1. Model parameters
    • Table S2. Simulated performance results
    • Fig. S1. Risk, return, diversification, and securitization
    • Fig. S2. HCL default model
    • Fig. S3. Student-loan data
    • Fig. S4. Goodness-of-fit of default models
    • Fig. S5. Estimated post-treatment survival rates
    • Fig. S6. Sensitivity analysis of simulated performance
    • References (21–31)

    [Download PDF]

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