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The E¤ects of Competition on Prescription Payments in Retail Pharmacy Markets y Jihui Chen June 2018 Abstract Using pharmacy claims from New Hampshire between 2009 and 2011, I study the extent to which pharmacy competition a¤ects prescription payments. I measure phar- macy competition by the distance to nearby rivals, as well as a xed-travel-time HHI (DunnandShapiro,2014).Aftercontrolling for various factors, including insurer, phar- macy, drug, and area characteristics, I nd higher average drug prices in more concen- trated seller (pharmacy) markets, but lower prices in more concentrated buyer (insurer) markets. The distance e¤ect is more pronounced if a nearby pharmacy belongs to the same national chain. In addition, I show heterogeneous distance e¤ects across dif- ferent drug types and areas. My analysis contributes to the empirical literature on competition measures by adding new evidence from the retail pharmaceutical market. Keywords: Market Structure; Pharmacy Competition; Insurer Concentration; Re- tail Prescription Drugs JEL codes: L11, L65, D4, I13 I am grateful to the editor, Charles Courtemanche, three anonymous reviewers, Michael R. Baye, and Rati Ram for their very helpful comments and suggestions, which have greatly improved the paper. In addition, I thank Uktamjan Kamilov, Raina Kirchner, Edna Mensah, Bryan Titzler, and Yi Wang for their excellent research assistance, as well as Adam Shapiro for generously sharing the Stata codes used to generate the xed-travel-time HHI in their papers, and Robert Picard for kindly developing Stata codes to help generate distance variables. I also thank session participants at the 2016 Southern Economic Association Annual Meetings, 2017 Midwest Economic Association Annual Meetings, and 2017 Chinese Economist Society Annual China Conference for their helpful comments. Finally, I acknowledge the New Hampshire Department of Health and Human Services, the New Hampshire Insurance Department, and their designated agencies for generously providing the pharmaceutical claim and related data used in this study. The views expressed in this study are solely mine and are not necessarily those of any agency of the State of New Hampshire. The usual caveat applies. yDepartment of Economics, Illinois State University, Campus Box 4200, Normal, IL 61790 U.S.A; Tel: (309) 438-3616; Fax: (309) 438-5228; Email: jchen4@ilstu.edu. 1 1 Introduction According to the IMS Institute for Healthcare Informatics, prescription drugs account for 1 about one- fth of total health care costs in the U.S., and are expected to continue to rise. In recent years, public concern over high drug prices has been fueled by price scandals involv- ing life-saving drugsfor example, Turing PharmaceuticalsDaraprim in 2015 and Mylans 2 3 EpiPen in 2016. However, when facing rising prices, unlike the case with other products, cheaper substitutes may not be available for medications. Both anecdotal evidence and aca- demic research (Sorensen, 2001; Chen, 2015) highlight considerable price variations across pharmacies, and suggest that consumers should search for lower prices, even those with in- 4 surance coverage. As high-deductible insurance plans become more common, the insured are required to pay out-of-pocket for prescriptions at insurersnegotiated rates before their deductible is satis ed. Moreover, depending on coverage, insured patientscosts may di¤er between in-network and out-of-network pharmacies, whether one uses a preferred pharmacy, and, to a lesser extentdue to variations in coinsurancepharmaciescosts to acquire prescrip- 5 tion drugs from manufacturers or wholesalers. This paper examines patient-level payments to pharmacies for the 200 most-prescribed drugs using data extracted from pharmacy claims collected by the state of New Hampshire (NH) from 2009 to 2011, taking into consideration both pharmacy and insurer competition. Alarge literature on health markets has developed several area-level competition mea- sures. For example, studies on hospital care construct a Her ndahl-Hirschman Index (HHI) 1Source: IMS Institute for Healthcare Informatics. (2012, February). Healthcare Spending Among Pri- vately Insured Individuals Under Age 65. 2Source: This 62-year-old drug just got 5,000% more expensive,by Laura Lorenzetti, September 21, 2015 (http://fortune.com/2015/09/21/turing-pharmaceuticals-drug-prices-daraprim/). 3Source: Mylans EpiPen Pricing Crossed Ethical Boundaries,by Daniel Kozarich, September 27, 2016 (http://fortune.com/2016/09/27/mylan-epipen-heather-bresch/). 4Studies show that insured patients may sometimes incur a lower cost without using in- surance for prescription drugs. Source: Prescription Drugs May Cost More with Insurance Than without It, by Charles Ornstein and Katie Thomas, Dec. 9, 2017, New York Time (https://www.nytimes.com/2017/12/09/health/drug-prices-generics-insurance.html). 5For an example of Mayo Medical Plans 2018 prescription drug coverage, visit: http://www.mayo.edu/pmts/mc6200-mc6299/mc6213-11.pdf. 2 basedonactualmarketshare(KesslerandMcClellan,2000; GowrisankaranandTown,2003), while others use physician density, such as the number of physicians per capita (Bradford and Martin, 2000; Richardson et al., 2003). More recent work has adopted a novel and objective measure: travel distance to competing providers (Dunn and Shapiro, 2014; Gravelle et al., 2016), which alleviates the endogeneity concern that arises from the existing alternatives, by which unobserved factors may simultaneously determine market structure and provider pricing. However, similar studies of retail pharmacy markets are scarce, largely due to data unavailability. This paper aims to ll the gap. Unlike in other product markets, physicians, rather than consumers, determine the use of prescription drugs. Meanwhile, individual patients play no role in negotiating payments between pharmacies and insurers or pharmacy bene t managers (PBMs). Furthermore, prescription drug prices have been rising at a faster rate than general ination for decades, triggering heated debate and high-pro le congressional scrutiny of the 6 pharmaceutical industry. These unique features of the pharmaceutical market make it particularly interesting to study. Myidenti cation strategy is to use both the between-area and cross-time variations that arise from payments received by pharmacies and competition among pharmacies, as well as insurers, over a three-year period. To gauge the extent to which pharmacy concentration a¤ects prices in the retail prescription drug market, I construct three competition measures. First, I examine the distance e¤ects of up to the fth nearest pharmacy on drug pricing (Gravelle et al., 2016). Second, I construct two sets of distance variables, one to rival pharmacies and the other to ones same-chain pharmacies, and explore possible business- stealing and cannibalization e¤ects, respectively (Davis, 2006). Third, I compute the so- called Fixed-Travel-Time Her ndahl-Hirschman index(FTHHI), which incorporates both the distance and travel time to competing pharmacies in the same area (Dunn and Shapiro, 6Source: How Do We Deal with Rising Drug Costs?by Jonathan D. Rocko¤, Wall Street Journal, April 10, 2016 (http://www.wsj.com/articles/how-do-we-deal-with-rising-drug-costs-1460340357, accessed August 25, 2016). 3 2014, 2018). After controlling for drug and pharmacy characteristics, locality, year, month, drug class, andmanufacturer xede¤ects,I ndthatpharmaciesreceivelowerpaymentsinmoreconcen- trated buyer (insurer) markets, but higher payments in more concentrated seller (pharmacy) markets. The latter e¤ect is more pronounced if nearby competitors belong to the same na- tional pharmacy chain. Moreover, I nd considerable business-stealing e¤ects from nearby rivals, but little evidence of cannibalization e¤ects from ones own establishments. These ndings are robust to various controls and model speci cations. Next, I perform additional analyses, and conclude that the distance e¤ects among competing pharmacies di¤er across di¤erent drug types and area types. Speci cally, the distance e¤ect is more noticeable among prescription drugs that consumers are less likely to price search, or among pharmacies located in relatively a uent areas or counties that do not border another state. 1.1 Related Literature This paper is related to previous studies on health providers (e.g., physicians and hospitals), which conclude that higher market concentration leads to higher negotiated service prices (Bakeretal., 2014; DunnandShapiro, 2014; Gravelleetal., 2016; Kleiner, White, andLyons, 2015). My analysis adds to this literature by examining the issue in the retail prescription drug market using comprehensive patient-level data. A large literature on health markets has developed various measures of competition. For example, studies on hospital care construct HHI based on market share (Kessler and McClellan, 2000; Gowrisankaran and Town, 2003; Gaynor et al., 2011), while those on physician services have used physician density (Bradford and Martin, 2000; Richardson et al., 2003), but more recent work relies on a novel and objective measure, travel distance to competitors, which alleviates the endogeneity concern that arises from alternative measures (Dunn and Shapiro, 2014, 2018; Gravelle et al., 2016). Focusing on Medicare bene ciaries, Kessler and McClellan (2000) examine hospital com- 4
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