• Reading list

    Optimal cost reimbursement of health insurers to reduce risk selection, by Mathias Kifmann and Normann Lorenz (Health Economics)

    In the absence of a perfect risk adjustment scheme, reimbursing health insurers’ costs can reduce risk selection in community-rated health insurance markets. In this paper, we develop a model in which insurers determine the cost efficiency of health care and have incentives for risk selection. We derive the optimal cost reimbursement function, which balances the incentives for cost efficiency and risk selection. For health cost data from a Swiss health insurer, we find that an optimal cost reimbursement scheme should reimburse costs only up to a threshold.

    Hospital competition and financial performance: the effects of ambulatory surgery centers, by Kathleen Carey, James F. Burgess, and Gary J. Young (Health Economics)

    Ambulatory surgery centers (ASCs), limited-service alternatives for treating surgery patients not requiring an overnight stay, are a health-care service innovation that has proliferated in the U.S. and other countries in recent years. This paper examines the effects of ASC competition on revenues, costs, and profit margins of hospitals that also provided these services as a subset of their general services in Arizona, California, and Texas during the period 1997–2004. We identified all ASCs operating during the period in the 49 Dartmouth Hospital Referral Regions in the three states. The results of fixed effects models suggested that ASCs are meaningful competitors to general hospitals. We found downward pressure on revenues, costs, and profits in general hospitals associated with ASC presence.

    Internationally comparable health indices, by Erik Meijer, Arie Kapteyn, and Tatiana Andreyeva (Health Economics)

    One of the most intractable problems in international health research is the lack of comparability of health measures across countries or cultures. We develop a cross-country measurement model for health, in which functional limitations, self-reports of health, and a physical measure are interrelated to construct health indices. To establish comparability across countries, we define the measurement scales by the physical measure while other parameters vary by country to reflect cultural and linguistic differences in response patterns. We find significant cross-country variation in response styles of health reports along with variability in genuine health that is related to differences in national income. Our health indices achieve satisfactory reliability of about 80% and their gradients by age, income, and wealth for the most part show the expected patterns. Moreover, the health indices correlate much more strongly with income and net worth than self-reported health measures.

    Evidence of a causal link between health outcomes, insurance coverage, and a policy to expand access: experimental data from children in the Philippines, by Stella A. Quimbo, John W. Peabody, Riti Shimkhada, Jhiedon Florentino, and Orville Solon (Health Economics)

    In this paper, we present evidence on the health effects of a health insurance intervention targeted to poor children using data from a randomized policy experiment known as the Quality Improvement Demonstration Study. Among study participants, using a difference-in-difference regression model, we estimated a 9–12 and 4–9 percentage point reduction in the likelihood of wasting and having an infection, respectively, as measured by a common biomarker C-reactive Protein. Interestingly, these benefits were not apparent at the time of discharge; the beneficial health effects were manifest several weeks after release from the hospital.

    Regulating the Medical Loss Ratio: Implications for the Individual Market, by Jean M. Abraham and Pinar Karaca-Mandic (Am J Manag Care)

    Objective: To provide state-level estimates of the size and structure of the US individual market for health insurance and to investigate the potential impact of new medical loss ratio (MLR) regulation in 2011, as indicated by the Patient Protection and Affordable Care Act (PPACA).

    Study Design: Using data from the National Association of Insurance Commissioners, we provided state-level estimates of the size and structure of the US individual market from 2002 to 2009. We estimated the number of insurers expected to have MLRs below the legislated minimum and their corresponding enrollment. In the case of noncompliant insurers exiting the market, we estimated the number of enrollees that may be vulnerable to major coverage disruption given poor health status.

    Results: In 2009, using a PPACA-adjusted MLR definition, we estimated that 29% of insurer-state observations in the individual market would have MLRs below the 80% minimum, corresponding to 32% of total enrollment. Nine states would have at least one-half of their health insurers below the threshold. If insurers below the MLR threshold exit the market, major coverage disruption could occur for those in poor health; we estimated the range to be between 104,624 and 158,736 member-years.

    Conclusion: The introduction of MLR regulation as part of the PPACA has the potential to significantly affect the functioning of the individual market for health insurance.

    Healthcare Spending and Preventive Care in High-Deductible and Consumer-Directed Health Plans, by Melinda Beeuwkes Buntin, Amelia M. Haviland, Roland McDevitt, and Neeraj Sood (Am J Manag Care)

    Objective: To investigate the effects of highdeductible health plans (HDHPs) and consumerdirected health plans (CDHPs) on healthcare spending and on the use of recommended preventive care.

    Study Design: Retrospective study.

    Methods: We analyzed claims and enrollment data for 808,707 households from 53 large US employers, 28 of which offered HDHPs or CDHPs. We estimated the effects of HDHP or CDHP enrollment on healthcare cost growth between 2004 and 2005 using a difference-in-difference method that compared cost growth for families who were enrolled in HDHPs or CDHPs for the first time in 2005 with cost growth for families who were not offered HDHPs or CDHPs. Control families were weighted using propensity score weights to match the treatment families. Using similar methods, we examined the effects of HDHP or CDHP enrollment on the use of preventive care and the effects of HDHP or CDHP offering by employers on the mean cost growth.

    Results: Families enrolling in HDHPs or CDHPs for the first time spent 14% less than similar families enrolled in conventional plans. Families in firms offering an HDHP or a CDHP spent less than those in other firms. Significant savings for enrollees were realized only for plans with deductibles of at least $1000, and savings decreased with generous employer contributions to healthcare accounts. Enrollment in HDHPs or CDHPs was also associated with moderate reductions in the use of preventive care.

    Conclusions: The HDHPs or CDHPs with at least a $1000 deductible significantly reduced healthcare spending, but they also reduced the use of preventive care in the first year. This merits additional study because of concerns about enrollee health.

    Physician Response to Pay-for-Performance: Evidence from a Natural Experiment, by Jinhu Li, Jeremiah Hurley, Philip DeCicca, Gioia Buckley (NBER working paper)

    Explicit financial incentives, especially pay-for-performance (P4P) incentives, have been extensively employed in recent years by health plans and governments in an attempt to improve the quality of health care services. This study exploits a natural experiment in the province of Ontario, Canada to identify empirically the impact of pay-for-performance (P4P) incentives on the provision of targeted primary care services, and whether physicians’ responses differ by age, practice size and baseline compliance level. We use an administrative data source which covers the full population of the province of Ontario and nearly all the services provided by practicing primary care physicians in Ontario. With an individual-level data set of physicians, we employ a difference-in-differences approach that controls for both “selection on observables” and “selection on unobservables” that may cause estimation bias in the identification. We also implemented a set of robustness checks to control for confounding from the other contemporary interventions of the primary care reform in Ontario. The results indicate that, while all responses are of modest size, physicians responded to some of the financial incentives but not the others. The differential responses appear related to the cost of responding and the strength of the evidence linking a service with quality. Overall, the results provide a cautionary message regarding the effectiveness of pay-for-performance schemes for increasing quality of care.

    Economics of Individualization in Comparative Effectiveness Research and a Basis for a Patient-Centered Health Care, Anirban Basu (NBER working paper)

    The United States aspires to use information from comparative effectiveness research (CER) to reduce waste and contain costs without instituting a formal rationing mechanism or compromising patient or physician autonomy with regard to treatment choices. With such ambitious goals, traditional combinations of research designs and analytical methods used in CER may lead to disappointing results. In this paper, I study how alternate regimes of comparative effectiveness information help shape the marginal benefits (demand) curve in the population and how such perceived demand curves impact decision-making at the individual patient level and welfare at the societal level. I highlight the need to individualize comparative effectiveness research in order to generate the true (normative) demand curve for treatments. I discuss methodological principles that guide research designs for such studies. Using an example of the comparative effect of substance abuse treatments on crime, I use novel econometric methods to salvage individualized information from an existing dataset.

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    • It seems like almost every study involving HDHPs involve the potential for significant selection bias. I sometimes wonder if we even need studies since we are conducting the natural experiment right now, with more and more plans going to higher deductibles.