1 

UNITED STATES DISTRICT COURT

FOR THE DISTRICT OF COLUMBIA

SCAN HEALTH PLAN,

Plaintiff,

v. Civil Action No. 1:23-cv-03910 (CJN)

DEPARTMENT OF HEALTH AND 

HUMAN SERVICES, et al.,

Defendants.

MEMORANDUM OPINION

Plaintiff SCAN Health Plan is a California-based nonprofit health organization that 

provides health insurance to Medicare beneficiaries. SCAN claims that the government 

improperly calculated its 2024 Star Rating—a quality assessment that affects both its federal 

funding and how it is viewed by consumers. The Court agrees with SCAN that the only reasonable 

interpretation of the relevant regulations requires a different calculation, and therefore grants 

SCAN’s Motion for Summary Judgment and denies the government’s. 

I. Background 

A. The Regulations 

Medicare is a federal health insurance program for seniors and people with disabilities. See

42 U.S.C. § 1395 et seq. Beneficiaries can receive coverage from the federal government directly 

or by enrolling in private health insurance plans that are reimbursed by the government. See 42 

U.S.C. §§ 1395c to 1395i-6, 1395j to 1395w-6, 1395w-21 to 1395w-28. The private option is 

known as Medicare Advantage or Medicare Part C. See Parts of Medicare, Medicare.gov, https://

www.medicare.gov/basics/get-started-with-medicare/medicare-basics/parts-of-medicare (last 
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accessed June 2, 2024). Beneficiaries who choose either option may also choose to supplement 

their benefits by enrolling in a prescription drug benefit plan known as Medicare Part D. See 42 

U.S.C. § 1395w-101 et seq. Those Part D plans are also operated by private insurers. See id.

§ 1395w-101(a)(1).

The Centers for Medicare and Medicaid Services is the federal agency that runs the 

Medicare program. About CMS, https://www.cms.gov/about-cms (last accessed June 2, 2024). As 

part of its duties, CMS calculates and publishes something called a “Star Rating” for each private 

Medicare plan. See 42 C.F.R. §§ 422.162(b), 423.182(b). Star Ratings are designed to provide 

beneficiaries with information about a plan’s quality and to enable them and the agency to evaluate 

a plan’s performance. See id. §§ 422.160(b), 423.180(b); see also ECF No. 20-1 (“Decl.”) ¶ 19

(noting that the agency “lists plans on its online Medicare Plan Finder tool in order of highest to 

lowest Star Ratings” to “steer [beneficiaries] toward higher-rated plans”). CMS is also obligated 

by statute to offer additional funding to plans with better Star Ratings. See 42 U.S.C. § 1395w23(o), 1395w-24(b)(1)(C). Those higher-rated plans can then use those extra funds to lower costs 

for their beneficiaries or to provide them with additional benefits. See 85 Fed. Reg. 33,796, 

33,855–56 (2020). The upshot is that Star Ratings are quite important for private Medicare plans.

Every October, CMS publishes new Star Ratings for the upcoming calendar year. ECF 

No. 26 (“SCAN Mot.”) at 13; ECF No. 23 (“Gov. Mot.”) at 5. (So, for example, the agency

published the 2024 Star Ratings in October 2023). CMS calculates its Star Ratings not unlike the 

way that a teacher might calculate final grades for his or her students. See SCAN Mot. At 10–12

(making this analogy).

First, CMS determines each plan’s raw scores on various quality “measure[s].” See 42 

C.F.R. §§ 422.162(a), 422.166(a), 423.182(a), 423.186(a). To give just one example, Measure 
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C15 (“Plan All-Cause Readmissions”) is the “[p]ercent of plan members aged 18 and older 

discharged from a hospital stay who were readmitted to a hospital within 30 days, either for the 

same condition as their recent hospital stay or for a different reason.” CMS, Medicare 2024 Part 

C & D Star Ratings Technical Notes (“2024 Technical Notes”) at 60 (March 13, 2024), https://

www.cms.gov/files/document/2024-star-ratings-technical-notes.pdf (last accessed June 2, 2024).

In the grading analogy, this is like a teacher’s giving students raw scores on a variety of homework 

assignments, quizzes, essays, and exams.

Second, CMS converts each raw score into a star score. See 42 C.F.R. § 422.166(a),

423.186(a). The rating is on a five-star scale in whole-star increments. Id. §§ 422.166(a)(4), 

423.186(a)(4). The key thing to understand about the conversion process is that it grades plans on 

a curve. For the kind of measures at issue here,1 CMS runs a statistical “clustering” analysis to 

group the data set “such that the [raw scores] within a group are as similar as possible to each 

other, and as dissimilar as possible to [raw scores] in any other group.” Id. §§ 422.162(a), 

422.166(a), 423.182(a), 423.186(a). CMS then identifies the dividing lines—or “cut points”—

between the groups and assigns star scores accordingly. See id. §§ 422.166(a), 423.186(a). In the 

grading analogy, this is like a teacher’s analyzing all students’ scores on a quiz; determining that 

(for this particular quiz) a student needs to score at least 86% to receive an “A,” at least 78% to 

receive a “B,” at least 71% to receive a “C,” and so forth; and then giving students the letter grades 

that correspond to their raw scores. In the parlance of Star Ratings, 86%, 78% and 71% would be 

the “cut points” reflecting the dividing lines between the different letter grades.

1 CMS has two types of measures: CAHPS measures (which are based on data from surveys) and 

non-CAHPS measures (which are based on data from other sources). See 42 C.F.R. §§ 422.162(a), 

423.182(a). “Only non-CAHPS [measures] are at issue in this case.” SCAN Mot. at 12 n.5.
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Third, CMS calculates a plan’s overall Star Rating by running a weighted average of all 

measures. 42 C.F.R. § 422.166(c)(1), (d)(1); id. § 423.186(c)(1), (d)(1). The rating is again on a 

five-star scale but in half-star increments. 42 C.F.R. § 422.166(c)(3), (d)(2)(iv); id. 

§ 423.186(c)(3), (d)(2)(iv). In the grading analogy, this is like a teacher’s determining a student’s 

final letter grade by calculating a weighted average of the student’s letter grades on the various 

homework, quizzes, essays, and exams completed in the course. 

This suit relates to two recent changes to the way that CMS calculates Star Ratings. The 

first is what the Court will call the Guardrail Rule. “To increase the predictability of the cut 

points,” 84 Fed. Reg. 15,680, 15,754 (2019), CMS decided in April 2019 to place a 5% cap on 

how much cut points could change from year to year:

[CMS will apply] a guardrail so that the measure-threshold-specific cut points for 

non-CAHPS measures do not increase or decrease more than the value of the cap 

from one year to the next. The cap is equal to 5 percentage points for measures 

having a 0 to 100 scale (absolute percentage cap) or 5 percent of the restricted range 

for measures not having a 0 to 100 scale (restricted range cap).

Id. at 15,830, 15,842 (amending 42 C.F.R. §§ 422.166(a)(2)(i) (Part C) and 423.186(a)(2)(i) 

(Part D)). In the grading analogy, this would be like a teacher’s deciding to increase the 

predictability of the score required for a student to get an “A” on the final exam. Accordingly, if 

students in Year One needed to score at least 86% on the exam to receive an “A,” students in Year 

Two would need to score no more than 91% to merit the same letter grade—no matter the actual 

distribution of their scores. (In other words, all students in Year Two scoring above 91% on the 

final exam would receive an “A” on the final even if that resulted in many more students receiving 

an “A” on the final in Year Two than in Year One.) CMS first implemented the Guardrail Rule in 

October 2022 when it calculated the 2023 Star Ratings. See 85 Fed. Reg. 19,230, 19,274–75 

(2020).
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The second change is what the Court will call the Tukey Outlier Rule. In layman’s terms, 

Tukey outliers are extreme outliers on the high and low ends of a data set. See 42 C.F.R. 

§§ 422.162(a), 423.182(a)). In June 2020, CMS decided to clean such outliers from the raw data 

before calculating cut points in order “to stabilize cut points and prevent large year-to-year 

fluctuations in cut points caused by the scores of a few contracts.” 85 Fed. Reg. 33,796, 33,833 

(2020). CMS therefore added the following text to the same subsections of the Code of Federal 

Regulations containing the Guardrail Rule: “[P]rior to applying mean resampling with hierarchal 

clustering, Tukey outer fence outliers are removed.” Id. at 33,907, 33,911 (amending 42 C.F.R. 

§§ 422.166(a)(2)(i) (Part C) and 423.186(a)(2)(i) (Part D)). In the grading analogy, this is like a 

teacher’s throwing out perfect scores and very poor scores before calculating the curve for a quiz. 

The agency first implemented the Tukey Outlier Rule in October 2023 when it calculated the 2024 

Star Ratings. See id. at 33,836.

Accordingly, at the time that SCAN’s 2024 Star Rating was published in October 2023, 

the relevant CFR subsections read as follows:

The method maximizes differences across the star categories and minimizes the 

differences within star categories using mean resampling with the hierarchal 

clustering of the current year’s data. Effective for the Star Ratings issued in 

October 2023 and subsequent years, prior to applying mean resampling with 

hierarchal clustering, Tukey outer fence outliers are removed. Effective for the Star 

Ratings issued in October 2022 and subsequent years, CMS will add a guardrail so 

that the measure-threshold-specific cut points for non-CAHPS measures do not 

increase or decrease more than the value of the cap from 1 year to the next. The 

cap is equal to 5 percentage points for measures having a 0 to 100 scale (absolute 

percentage cap) or 5 percent of the restricted range for measures not having a 0 to 

100 scale (restricted range cap). New measures that have been in the Part C and D 

Star Rating program for 3 years or less use the hierarchal clustering methodology 

with mean resampling with no guardrail for the first 3 years in the program.

42 C.F.R. §§ 422.162(a)(2)(i) (Part C), 423.182(a)(2)(i) (Part D).

In the long run, these two changes complement each other. The Tukey Outlier Rule 

increases the stability and predictability of cut points by removing extreme, fleeting outliers from 
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the data before those outliers can skew the curve. And the Guardrail Rule increases the stability 

and predictability of cut points by imposing a limit on their ability to change from year to year.

In the short run, however, the story is different. That is because the agency implemented 

the Guardrail Rule before it implemented the Tukey Outlier Rule. Although the latter removes 

extreme outliers in both directions, there tend to be more such outliers on the lower end of the data 

sets at issue here than the higher end. See, e.g., 85 Fed. Reg. 9,002, 9,044 (2020). As a result, 

removing Tukey outliers resulted in significant changes in some cut points—in other words, 

removing Tukey outliers in a particular year would tend to increase certain cut points much more 

than the 5% limit contained in the Guardrail Rule. Compare 2024 Technical Notes at 36–110, 

with CMS, Medicare 2023 Part C & D Star Ratings Technical Notes (“2023 Technical Notes”) at 

26–104 (January 19, 2023), https://www.cms.gov/files/document/2023-star-ratings-technicalnotes.pdf (last accessed June 2, 2024). The Guardrail Rule would thus dampen the effect of the 

Tukey Outlier Rule if cut points calculated from data sets without outliers were tied to older cut 

points calculated from data sets with outliers—meaning that it might take years for the Tukey 

Outlier Rule to take full effect.

To address this issue, CMS determined to essentially waive the application of the Guardrail 

Rule for one year. In particular, rather than applying the Guardrail Rule to the actual cut points 

from the previous year, CMS would apply the Guardrail Rule to hypothetical cut points for the 

previous year, which it would calculate using the previous year’s data but with Tukey outliers 

removed. The problem is that CMS never amended its regulations to reflect that decision, at least 

not expressly. Instead, CMS announced that approach in two preambles contained exclusively in 

the Federal Register. Specifically, when CMS first proposed the Tukey Outlier Rule in February 

2020, it stated that “In the first year that [Tukey outlier deletion] would be implemented, the prior 
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year’s thresholds would be rerun, including mean resampling and Tukey outer fence deletion so 

that the guardrails would be applied such that there is consistency between the years.” 85 Fed. 

Reg. at 9,044. And when CMS finalized the Tukey Outlier Rule several months later, it made 

similar statements. 85 Fed. Reg. at 33,833 (“We explained that under our proposal in the first year 

of implementing this process, the prior year’s thresholds would be rerun, including mean 

resampling and Tukey outer fence deletion so that the guardrails would be applied such that there 

is consistency between the years.”); id. at 33,835 (“As noted in the NPRM, for the first year (2024 

Star Ratings), we will rerun the prior year’s thresholds, using mean resampling and Tukey outer 

fence deletion so that the guardrails would be applied such that there is consistency between the 

years.”).2

B. The Present Controversy

SCAN is a nonprofit health organization that offers Part C and Part D coverage to Medicare 

beneficiaries in California, Arizona, Nevada, New Mexico, and Texas. Decl. ¶¶ 5–8, 15. Between 

2018 and 2023, it enjoyed a Star Rating of 4.5 stars. Id. ¶ 23. SCAN used the additional funding

it received for being a highly rated provider to reduce costs for its members and offer them 

additional benefits, such as dental and vision. Id. ¶ 27. 

In September 2023, however, CMS informed SCAN that its 2024 Star Rating would drop 

to 3.5 stars. Decl. ¶ 33. After reviewing the agency’s calculations, SCAN determined that part of 

the change in its Star Rating could be attributed to CMS’s decision not to apply the guardrail to 

2 One quirk about the regulatory history bears mentioning. In May 2022, CMS accidentally

removed the Tukey Outlier Rule from the Code of Federal Regulations when it finalized separate

regulatory changes related to the COVID-19 pandemic. See 87 Fed. Reg. 27,704, 27,809–14, 

27,895 (2022). CMS eventually realized its mistake and in April 2023 put the relevant language 

back into the Code. See 88 Fed. Reg. 22,120, 22,295, 22,332, 22,338 (2023). Although the Parties 

dispute the significance of those changes, the Court need not address them because it concludes 

that SCAN would prevail even if they had not occurred.
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the previous year’s actual cut points. See id. ¶ 34. Had CMS done so, SCAN would have received 

a higher rating on two measures and an overall Star Rating of 4 stars—a rating that would make 

the organization eligible for approximately $250 million in additional funding from the federal 

government. See id. ¶¶ 41–45, 57. (In other words, the removal by CMS of Tukey outliers in 

recalculating the prior year’s cut points resulted in SCAN’s star rating being half of a star lower 

than it would have been otherwise.) SCAN therefore informally requested that CMS recalculate 

SCAN’s Star Rating. See id. ¶¶ 35–40.3

 CMS refused on the ground that applying the guardrail 

to hypothetical cut points that it recalculated after removing Tukey outliers from the previous 

year’s data was consistent with its regulations. See id.

In December 2023, SCAN filed this suit. ECF No. 1 (“Compl.”) ¶¶ 123–31. It argues that 

CMS failed to follow its own regulation in calculating the organization’s Star Rating and that its 

action was therefore arbitrary and capricious. See id. ¶¶ 127–29.4 Since then, SCAN and the 

government have cross-moved for summary judgment. Following a hearing on May 24, 2024, 

these motions are now ready to be resolved.

II. Legal Standards

Under the Administrative Procedure Act, the Court “shall . . . hold unlawful and set aside 

agency action, findings, and conclusions found to be . . . arbitrary, capricious, an abuse of 

discretion, or otherwise not in accordance with law.” 5 U.S.C. § 706. “Although it is within the 

3 Although CMS offers a process for plans to appeal their eligibility for a certain kind of additional 

funding, it does not allow them to challenge “the methodology for calculating the star ratings” or 

“the cut-off points for determining measure thresholds.” 42 C.F.R § 422.260(c)(3)(ii). CMS does 

not argue here that it did not take final agency action with respect to SCAN’s 2024 Star Rating.

4 SCAN has also raised a challenge to the way that CMS rated the organization on another measure 

related to interpreter availability in call centers. SCAN Mot. at 3–5. The Court declines to resolve 

that issue because its decision with respect to the guardrail issue is sufficient to provide SCAN the 

relief it seeks. See SCAN Mot. at 5; ECF No. 27 (“SCAN Reply”) at 5.
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power of an agency to amend or repeal its own regulations, an agency is not free to ignore or 

violate its regulations while they remain in effect.” Nat’l Env’t Dev. Assn.’s Clean Air Project v. 

EPA, 752 F.3d 999, 1009 (D.C. Cir. 2014) (quotation omitted and alterations adopted). 

Accordingly, “an agency action may be set aside as arbitrary and capricious if the agency fails to 

comply with its own regulations” in taking that action. Id. (quotation omitted). 

III. Analysis

Although the Medicare regulations at issue here can appear daunting, the question 

presented in this case is ultimately a simple one. As the Parties acknowledged during the hearing, 

SCAN does not challenge CMS’s statutory authority to remove Tukey outliers, to apply the 

Guardrail Rule to hypothetical cut points for one year, see Tr. at 4–6, 26–28, or perhaps even to 

change or eliminate the guardrail altogether. Instead, the sole question is whether the agency’s

current regulations permit it to apply the guardrail to a prior year’s recalculated hypothetical cut 

points instead of actual cut points.

The plain text of the Guardrail Rule forecloses the government’s position. The Guardrail 

Rule states that CMS will apply “a guardrail so that the measure-threshold-specific cut points for 

non-CAHPS measures do not increase or decrease more than the value of the cap from 1 year to 

the next.” 42 C.F.R. §§ 422.166(a)(2)(i), 423.186(a)(2)(i). The rule therefore instructs the agency 

to look at the “cut points . . . from 1 year” when calculating the “cut points” for “the next” year. 

The best and most natural reading is that this regulation refers to the actual cut points in the initial

year just as it refers to the actual cut points that will be created for the next year. Indeed, in 

calculating the 2023 Star Ratings, CMS applied the guardrail to the “prior year’s [actual] cut 

point.” 2023 Technical Notes at 139; see also id. at 9 (“[E]ach 1 to 5 star level cut point is 

compared to the prior year’s value and capped . . . .” (emphasis added)).
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In fact, the relevant definitions repeatedly provide that the guardrail is applied to “the prior 

year’s . . . cut point”—a phase that can only be reasonably read to refer to the prior year’s actual

cut point. 42 C.F.R. §§ 422.162(a), 423.182(a). “Guardrail,” for example, is defined as a

“bidirectional cap that restricts both upward and downward movement of a measure-thresholdspecific cut point for the current year’s measure-level Star Ratings as compared to the prior year’s 

measure-threshold-specific cut point.” Id. (emphases altered). “Cut point cap,” in turn, is defined 

as “a restriction on the change in the amount of movement a measure-threshold-specific cut point 

can make as compared to the prior year’s measure-threshold-specific cut point.” Id. (emphases 

altered). And “[a]bsolute percentage cap” is “a cap applied to non-CAHPS measures that are on a 

0 to 100 scale that restricts movement of the current year’s measure-threshold-specific cut point 

to no more than the stated percentage as compared to the prior year’s cut point.” Id. (emphases 

altered). Again, these definitions can only be reasonably read to refer to the prior year’s actual

cut point.

The government contends that these provisions do not state that they were referring to a 

prior year’s “actual, unadjusted cut points.” Gov. Mot. at 26. But that is the meaning that any

ordinary English speaker would take from an unqualified reference to “the prior year’s cut point.” 

Had CMS wanted to apply a policy designed to increase the predictability of cut points to anything 

other than actual cut points, one might have expected it to say so explicitly. Indeed, the regulation 

shows that CMS knew how to waive the application of the guardrail for limited periods. The

sentence immediately following the definition of the guardrail states: “New measures that have 

been in the Part C and D Star Rating program for 3 years or less use the hierarchal clustering 

methodology with mean resampling with no guardrail for the first 3 years in the program.” 42 
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C.F.R. §§ 422.166(a)(2)(i), 423.186(a)(2)(i) (emphasis added). And again, there is no dispute that 

CMS had the statutory authority to do so. See Tr. at 4–6, 26–28. 

In other places, the regulations even explicitly exclude Tukey outliers from a prior year’s 

data before applying the guardrail. The guardrail applies differently to two types of non-CAHPS 

measures: “measures having a 0 to 100 scale” and “measures not having a 0 to 100 scale.” 42 

C.F.R. §§ 422.166(a)(2)(i), 423.186(a)(2)(i). The guardrail for the latter type is “5 percent of the 

restricted range,” id., which is defined as the difference between the minimum and maximum raw 

score from the prior year—but only after Tukey outliers have been excluded from the data, id. 

§ 422.162(a) (“Restricted range is the difference between the maximum and minimum measure 

score values using the prior year measure scores excluding outer fence outliers (first 

quartile−3*Interquartile Range (IQR) and third quartile + 3*IQR).”); id. § 423.182(a) (same); see 

also id. § 422.162(a) (defining “Tukey outer fence outliers” as “measure scores that are below a 

certain point (first quartile−3.0 × (third quartile−first quartile)) or above a certain point (third 

quartile + 3.0 × (third quartile−first quartile)).”); id. § 423.182(a) (same). In contrast, the relevant 

regulations here do not state anywhere that the guardrail would be applied to hypothetical cut 

points.

Against this backdrop, the government advanced (for the first time at the motions hearing)

a reading of the regulations that would permit it to apply the guardrail to hypothetical cut points. 

According to the government, the Tukey Outlier Rule—which provides that “Effective for the Star 

Ratings issued in October 2023 and subsequent years, . . . Tukey outer fence outliers are removed,”

42 C.F.R. §§ 422.166(a)(2)(i), 423.186(a)(2)(i) (emphasis added)—requires (or at least authorizes) 

the “remov[al]” of Tukey outliers in all data sets, including those corresponding to previous years, 

Tr. at 7–8, 11–12. There are at least two problems with this theory. First, the sentence immediately 
12

preceding the sentence on which the government now relies states that “[t]he [clustering] method 

maximizes differences across the star categories and minimizes the differences within star 

categories using mean resampling with the hierarchal clustering of the current year’s data.” 42 

C.F.R. §§ 422.166(a)(2)(i), 423.186(a)(2)(i) (emphasis added). The “remov[al]” of Tukey outliers 

is therefore best understood to mean the “remov[al]” of Tukey outliers in “the current year’s data.” 

And that says nothing about whether and how Tukey outliers might be removed from the prior 

year’s data. Second, the guardrail is applied to cut points (not the underlying data), cf. Tr. at 10 

(acknowledging that there are “actual cut points” that exist for the previous year), and the language 

on which the government relies makes no reference to cut points—let alone a reference that is 

express enough to make ambiguous the otherwise unambiguous regulatory language discussed 

above.

Alternatively, the government argues that its preamble statements (which are certainly 

more express than the regulations) are legally binding and permit it to apply the 5% guardrail to 

hypothetical cut points. Gov. Mot. at 22–27. It appears to argue that any statement in a preamble 

that goes through notice and comment and that is clearly intended to be binding is a legislative 

rule with the force of law. See Tr. at 6–7, 14–17; Gov. Mot. at 22; ECF No. 30 (“Gov. Reply”) 

at 2. But that is not the law in this Circuit. As the Court of Appeals put it in AT&T Corp. v. FCC, 

“[p]ublication in the Federal Register does not suggest that the matter published was meant to be 

a regulation.” 970 F.3d 344, 350 (D.C. Cir. 2020) (quotation omitted). Instead, “the real dividing 

point between the portions of a final rule with and without legal force is designation for publication 

in the Code of Federal Regulations.” Id. (quotation omitted). As a result, when “there is a 

discrepancy between the preamble and the Code, it is the codified provisions that control.” Id. at 

351. To be sure, the Court of Appeals has “reserved a possibility that statements in a preamble 
13

may in some unique cases constitute binding, final agency action susceptible to judicial review,” 

but it has made clear that “this is not the norm.” Id. at 350 (quotation omitted). And here, the 

government has not demonstrated that this case is the exception rather than the rule. After all, as 

discussed above, the text of the regulation leaves only one reasonable interpretation.

5

Finally, the government raises two non-merits challenges. First, it argues that SCAN 

waived this issue because it failed to raise it during a comment in any rulemaking. Gov. Mot. at 

34–35. But a party may raise such issues on an as-applied basis when a regulation is applied to it, 

as here. See Koretoff v. Vilsack, 707 F.3d 394, 399 (D.C. Cir. 2013). Second, the government 

argues that any errors made by CMS were harmless because SCAN had notice of CMS’s intent to 

apply the guardrail based on hypothetical cut points and an opportunity to comment on that 

proposed policy. Gov. Mot. at 35–37. But the test whether an error is harmless depends on 

whether the error will “prejudice” the regulated party. Jicarilla Apache Nation v. U.S. Dep’t of 

Interior, 613 F.3d 1112, 1121 (D.C. Cir. 2010) (quotation omitted). That standard is met here 

because CMS’s failure to follow its own regulation led it to give SCAN an incorrect Star Rating 

that will cost the organization millions of dollars. See Decl. ¶ 57.

That leaves only the proper remedy. SCAN argues that this Court should “set aside” Scan’s 

rating and “enjoin the Defendants from using CMS’s unlawful 3.5-star Star Rating in determining 

SCAN’s eligibility for quality bonus payments” (one form of the additional funding that the federal 

government offers highly rated Medicare plans). SCAN Mot. At 43. The government does not 

5 Accordingly, the government’s passing request to defer to its interpretation of the regulation fails. 

See Gov. Mot. at 27. Even assuming that these preamble statements are the sort of interpretations 

that are eligible for deference, the Court must exhaust the “traditional tools of construction” to 

determine whether there is a correct “answer” to the interpretative question—i.e., the only 

“reasonable construction of [the] regulation”—before deferring. Kisor v. Wilkie, 588 U.S. 558, 

575 (2019). The Court has done so here and determined that SCAN’s interpretation of the 

regulation is the only reasonable one.
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appear to contest that SCAN is entitled that relief if the Court grants its summary-judgment motion. 

Accordingly, the Court will treat SCAN’s remedy arguments as conceded and grant SCAN the 

relief it requests. Am. Waterways Operators v. Regan, 590 F. Supp. 3d 126, 138 (D.D.C. 2022). 

IV. Conclusion 

For the foregoing reasons, the Court grants SCAN’s Motion for Summary Judgment and 

denies the government’s Motion. An order will issue contemporaneously with this opinion. 

DATE: June 3, 2024 

CARL J. NICHOLS

United States District Judge