# Patient Protection and Affordable Care Act; HHS Notice of Benefit and Payment Parameters for 2015 > Briefs, arguments, decisions, and more. URL: https://www.frixlaw.com/law-library/documents/fr%3A2013-28610 ## Record - **Collection:** Federal Register - **Document type:** Proposed Rule - **Published:** December 2, 2013 - **Citation:** 78 FR 72322 ## Text DEPARTMENT OF HEALTH AND HUMAN SERVICES 45 CFR Parts 144, 147, 153, 155, and 156 [CMS-9954-P] RIN 0938-AR89 Patient Protection and Affordable Care Act; HHS Notice of Benefit and Payment Parameters for 2015 AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS. ACTION: Proposed rule. SUMMARY: This proposed rule sets forth payment parameters and oversight provisions related to the risk adjustment, reinsurance, and risk corridors programs; cost-sharing parameters and cost-sharing reductions; and user fees for Federally-facilitated Exchanges. It also proposes additional standards with respect to composite rating, privacy and security of personally identifiable information, the annual open enrollment period for 2015, the actuarial value calculator, the annual limitation in cost sharing for stand-alone dental plans, the meaningful difference standard for qualified health plans offered through a Federally-facilitated Exchange, patient safety standards for issuers of qualified health plans, and the Small Business Health Options Program. DATES: To be assured consideration, comments must be received at one of the addresses provided below, no later than 5 p.m. on December 26, 2013. ADDRESSES: In commenting, please refer to file code CMS-9954-P. Because of staff and resource limitations, we cannot accept comments by facsimile (FAX) transmission. You may submit comments in one of four ways (please choose only one of the ways listed): 1. Electronically. You may submit electronic comments on this regulation to http://www.regulations.gov . Follow the “Submit a comment” instructions. 2. By regular mail. You may mail written comments to the following address ONLY: Centers for Medicare & Medicaid Services, Department of Health and Human Services, Attention: CMS-9954-P, P.O. Box 8016, Baltimore, MD 21244-8016. Please allow sufficient time for mailed comments to be received before the close of the comment period. 3. By express or overnight mail. You may send written comments to the following address ONLY: Centers for Medicare & Medicaid Services, Department of Health and Human Services, Attention: CMS-9954-P, Mail Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-1850. 4. By hand or courier. Alternatively, you may deliver (by hand or courier) your written comments ONLY to the following addresses prior to the close of the comment period: a. For delivery in Washington, DC— Centers for Medicare & Medicaid Services, Department of Health and Human Services, Room 445-G, Hubert H. Humphrey Building, 200 Independence Avenue SW., Washington, DC 20201. (Because access to the interior of the Hubert H. Humphrey Building is not readily available to persons without Federal government identification, commenters are encouraged to leave their comments in the CMS drop slots located in the main lobby of the building. A stamp-in clock is available for persons wishing to retain a proof of filing by stamping in and retaining an extra copy of the comments being filed.) b. For delivery in Baltimore, MD— Centers for Medicare & Medicaid Services, Department of Health and Human Services, 7500 Security Boulevard, Baltimore, MD 21244-1850. If you intend to deliver your comments to the Baltimore address, call telephone number (410) 786-7195 in advance to schedule your arrival with one of our staff members. Comments erroneously mailed to the addresses indicated as appropriate for hand or courier delivery may be delayed and received after the comment period. For information on viewing public comments, see the beginning of the SUPPLEMENTARY INFORMATION section. FOR FURTHER INFORMATION CONTACT: For general information: Sharon Arnold, (301) 492-4286; Laurie McWright, (301) 492-4311; or Jeff Wu, (301) 492-4305. For matters related to student health insurance coverage and composite rating: Jacob Ackerman, (301) 492-4179. For matters related to the risk adjustment program generally, the small group counting requirements, the risk adjustment methodology, and the methodology for determining the reinsurance contribution rate and payment parameters: Kelly Horney, (410) 786-0558. For matters related to reinsurance generally, oversight of the premium stabilization programs, distributed data collection, and administrative appeals: Adrianne Glasgow, (410) 786-0686. For matters related to reinsurance contributions: Adam Shaw, (410) 786-1019. For matters related to risk corridors: Jaya Ghildiyal, (301) 492-5149. For matters related to cost-sharing reductions, the premium adjustment percentage, and Federally-facilitated Exchange user fees: Johanna Lauer, (301) 492-4397. For matters related to the annual limitation on cost sharing for stand-alone dental plans, privacy and security of personally identifiable information, the annual open enrollment period for the 2015 benefit year, and the meaningful difference standard: Leigha Basini, (301) 492-4380. For matters related to the Small Business Health Options Program: Scott Dafflitto, (301) 492-4198. For matters related to the actuarial value calculator: Allison Wiley at (410)786-1740. For matters related to patient safety standards for issuers of qualified health plans: Nidhi Singh Shah, (301) 492-5110. For matters related to netting of payments and charges: Pat Meisol, (410) 786-1917. SUPPLEMENTARY INFORMATION: Inspection of Public Comments: All comments received before the close of the comment period are available for viewing by the public, including any personally identifiable or confidential business information that is included in a comment. We post all comments received before the close of the comment period on the following Web site as soon as possible after they have been received: http://www.regulations.gov . Follow the search instructions on that Web site to view public comments. Comments received timely will also be available for public inspection as they are received, generally beginning approximately 3 weeks after publication of a document, at the headquarters of the Centers for Medicare & Medicaid Services, 7500 Security Boulevard, Baltimore, Maryland 21244, Monday through Friday of each week from 8:30 a.m. to 4 p.m. To schedule an appointment to view public comments, phone 1-800-743-3951. Table of Contents I. Executive Summary II. Background A. Legislative Authority B. Stakeholder Consultation and Input C. Structure of Proposed Rule III. Provisions of the Proposed HHS Notice of Benefit and Payment Parameters for 2015 A. Part 144—Requirements Relating to Health Insurance Coverage B. Part 147—Health Insurance Reform Requirements for the Group and Individual Health Insurance Markets 1. Composite Rating 2. Student Health Insurance Coverage C. Part 153—Standards Related to Reinsurance, Risk Corridors, and Risk Adjustment under the Affordable Care Act 1. Provisions and Parameters for the Permanent Risk Adjustment Program a. Risk adjustment user fees b. HHS risk adjustment methodology considerations c. Small group determination for risk adjustment d. Risk adjustment data validation e. HHS audits of issuers of risk adjustment covered plans 2. Provisions and Parameters for the Transitional Reinsurance Program a. Major medical coverage b. Self-insured plans without third party administrators c. Uniform reinsurance contribution rate d. Uniform reinsurance payment parameters e. Adjustment options f. Deducting cost-sharing reduction amounts from reinsurance payments g. Audits h. Same covered life i. Reinsurance contributions and enrollees residing in the territories j. Form 5500 counting method 3. Provisions for the Temporary Risk Corridors Program a. Definitions b. Compliance with risk corridors standards c. Participation in the risk corridors program e. Adjustment options for transitional policy 4. Distributed Data Collection for the HHS-operated Risk Adjustment and Reinsurance Programs a. Discrepancy resolution process b. Default risk adjustment charge D. Part 155—Exchange Establishment Standards and Other Related Standards under the Affordable Care Act 1. Election to Operate an Exchange after 2014 2. Ability of States to Permit Agents and Brokers to Assist Qualified Individuals, Qualified Employers, or Qualified Employees Enrolling in Qualified Health Plans 3. Privacy and Security of Personally Identifiable Information 4. Annual Open Enrollment Period for 2015 5. Functions of a Small Business Health Options Program 6. Eligibility Determination Process for SHOP 7. Application Standards for SHOP E. Part 156—Health Insurance Issuer Standards under the Affordable Care Act, Including Standards Related to Exchanges 1. Provisions Related to Cost Sharing a. Premium adjustment percentage b. Reduced maximum annual limitation on cost sharing c. Design of cost-sharing reduction plan variations d. Advance payments of cost-sharing reductions 2. Provisions on User Fees for a Federally-facilitated Exchange a. FFE user fee for the 2015 benefit year b. Adjustment of FFE user fee 3. Actuarial Value Calculation for Determining Level of Coverage 4. National Annual Limit on Cost Sharing for Stand-alone Dental Plans in an Exchange 5. Additional Standards Specific to SHOP 6. Meaningful Difference Standard for Qualified Health Plans in the FFEs 7. Quality Standards: Establishment of Patient Safety Standards for QHPs Issuers 8. Financial Programs a. Netting of payments and charges b. Confirmation of HHS payment and collections reports c. Administrative appeals IV. Collection of Information Requirements V. Response to Comments VI. Regulatory Impact Analysis A. Statement of Need B. Overall Impact C. Impact Estimates of the Payment Notice Provisions D. Regulatory Flexibility Act E. Unfunded Mandates F. Federalism G. Congressional Review Act VII. Regulations Text Acronyms Affordable Care Act—The collective term for the Patient Protection and Affordable Care Act (Pub. L. 111-148) and the Health Care and Education Reconciliation Act of 2010 (Pub. L. 111-152) AV—Actuarial Value CFR—Code of Federal Regulations CMS—Centers for Medicare & Medicaid Services EHB—Essential Health Benefits ERISA—Employee Retirement Income Security Act of 1974 (Pub. L. 93-406) FFE—Federally-facilitated Exchange FF-SHOP—Federally-facilitated Small Business Health Options Program FPL—Federal poverty level HCC—Hierarchical condition category HHS—United States Department of Health and Human Services HIPAA—Health Insurance Portability and Accountability Act of 1996 (Pub. L. 104-191) IRS—Internal Revenue Service MLR—Medical Loss Ratio NAIC—National Association of Insurance Commissioners OMB—Office of Management and Budget OPM—United States Office of Personnel Management PHS Act—Public Health Service Act PII—Personally identifiable information PSO—Patient Safety Organization PRA—Paperwork Reduction Act of 1985 PSES—Patient safety evaluation system QHP—Qualified health plan SHOP—Small Business Health Options Program The Code Internal Revenue Code of 1986 I. Executive Summary Qualified individuals and qualified employers are now able to purchase private health insurance coverage that begins as early as January 1, 2014, through competitive marketplaces called Affordable Insurance Exchanges, or “Exchanges” (also called Health Insurance Marketplaces, or “Marketplaces”). 1 Individuals who enroll in qualified health plans (QHPs) through individual market Exchanges may receive premium tax credits to make health insurance more affordable and financial assistance to reduce cost sharing for health care services. In 2014, HHS will also operationalize the premium stabilization programs established by the Affordable Care Act—the risk adjustment, reinsurance, and risk corridors programs—which are intended to mitigate the impact of possible adverse selection and stabilize the price of health insurance in the individual and small group markets. We believe that these programs, together with other reforms of the Affordable Care Act, will make high-quality health insurance affordable and accessible to millions of Americans. 1 The word “Exchanges” refers to both State Exchanges, also called State-based Exchanges, and Federally-facilitated Exchanges (FFEs). In this proposed rule, we use the terms “State Exchange” or “FFE” when we are referring to a particular type of Exchange. When we refer to “FFEs,” we are also referring to State Partnership Exchanges, which are a form of FFE. HHS has previously outlined the major provisions and parameters related to the advance payments of the premium tax credit, cost-sharing reductions, and premium stabilization programs. This proposed rule proposes additional provisions related to the implementation of these programs. Specifically, we propose certain oversight provisions for the premium stabilization programs, as well as key payment parameters for the 2015 benefit year. The Patient Protection and Affordable Care Act; HHS Notice of Benefit and Payment Parameters for 2014 final rule (78 FR 15410) (2014 Payment Notice) finalized the risk adjustment methodology that HHS will use when it operates risk adjustment on behalf of a State. This proposed rule proposes minor updates to this risk adjustment methodology for 2014 to account for certain private market Medicaid expansion plans, and seeks comment on how to adjust the geographic cost factor in the payment transfer formula to account for less populous rating areas in future benefit years. In this proposed rule, we also propose to clarify the counting methods for determining small group size for participation in the risk adjustment and risk corridors programs. Using the methodology set forth in the 2014 Payment Notice for determining the uniform reinsurance contribution rate and uniform reinsurance payment parameters, we propose in this rule a 2015 uniform reinsurance contribution rate of $44 annually per capita, and the 2015 uniform reinsurance payment parameters—a $70,000 attachment point, a $250,000 reinsurance cap, and a 50 percent coinsurance rate. We also propose to decrease the attachment point for 2014 from $60,000 to $45,000. Additionally, in order to maximize the financial effect of the transitional reinsurance program, we propose that if reinsurance contributions collected for a benefit year exceed the requests for reinsurance payments for the benefit year, we would increase the coinsurance rate on our reinsurance payments, ensuring that all of the contributions collected for a benefit year are expended for claims for that benefit year. We also propose several provisions related to cost sharing. First, we propose a methodology for estimating average per capita premium and for calculating the premium adjustment percentage for 2015 which is used to set the rate of increase for several parameters detailed in the Affordable Care Act, including the maximum annual limitation on cost sharing and the maximum annual limitation on deductibles for health plans in the small group market for 2015. We also propose to set the same reduced maximum annual limitations on cost sharing for the 2015 benefit year as we established for the 2014 benefit year for cost-sharing reduction plan variations. Additionally, we are proposing certain modifications to the methodology for calculating advance payments for cost-sharing reductions for the 2015 benefit year. We also propose standards for updating the actuarial value (AV) calculator. This proposed rule provides for a 2015 Federally-facilitated Exchange (FFE) user fee rate of 3.5 percent of premium. Additionally, we propose a user fee adjustment allowance for administrative costs in the 2015 benefit year to reimburse third party administrators that provide payment for contraceptive services for enrollees in certain self-insured group health plans that receive an accommodation from the obligation to cover these services in 2014. On November 14, 2013, the Federal government announced a policy under which it will not consider certain non-grandfathered health insurance coverage in the individual or small group market renewed between January 1, 2014, and October 1, 2014, under certain conditions to be out of compliance with specified 2014 market rules, and requested that States adopt a similar non-enforcement policy. 2 2 Letter to Insurance Commissioners, Center for Consumer Information and Insurance Oversight, November 14, 2013. See http://www.cms.gov/CCIIO/Resources/Letters/Downloads/commissioner-letter-11-14-2013.PDF . Issuers have set their 2014 premiums for individual and small group market plans by estimating the health risk of enrollees across all of their plans in the respective markets, in accordance with the single risk pool requirement at 45 CFR 156.80. These estimates assumed that individuals currently enrolled in the transitional plans described above would participate in the single risk pools applicable to all non-grandfathered individual and small group plans, respectively (or a merged risk pool, if required by the State). Individuals who elect to continue coverage in a transitional plan (forgoing premium tax credits and cost-sharing reductions that might be available through an Exchange plan, and the essential health benefits package offered by plans compliant with the 2014 market rules, and perhaps taking advantage of the underwritten premiums offered by the transitional plan) may have lower health risk, on average, than enrollees in individual and small group plans subject to the 2014 market rules. If lower health risk individuals remain in a separate risk pool, the transitional policy could increase an issuer's average expected claims cost for plans that comply with the 2014 market rules. Because issuers would have set premiums for QHPs in accordance with 45 CFR 156.80 based on a risk pool assumed to include the potentially lower health risk individuals that enroll in the transitional plans, an increase in expected claims costs could lead to unexpected losses. To help address the effects of this transitional policy on the risk pool, we are exploring modifications to a number of programs. We have outlined various options under consideration throughout this proposed rule, including adjustments to the reinsurance and risk corridors programs. We are seeking comment on these proposals, as well as soliciting suggestions for alternate proposals. As the impact of the transitional policy becomes clearer, we will determine what, if any, adjustments are appropriate. The success of the premium stabilization programs depends on a robust oversight program. This proposed rule expands on provisions of the Premium Stabilization Rule (77 FR 17220), the 2014 Payment Notice (78 FR 15410), and the first and second final Program Integrity Rules (78 FR 54070 and 78 FR 65046). In this proposed rule, we propose that HHS may audit State-operated reinsurance programs, contributing entities, and issuers of risk adjustment covered plans and reinsurance eligible-plans. We also clarify participation standards for the risk corridors program, and outline a proposed process for validating risk corridors data submissions and enforcing compliance with the provisions of the risk corridors program. We also propose several provisions regarding the HHS-operated risk adjustment data validation process. On June 22, 2013, we issued “The Affordable Care Act HHS-operated Risk Adjustment Data Validation Process White Paper” 3 and on June 25, 2013, we held a public meeting to discuss how to best ensure the accuracy and consistency of the data we will use when operating the risk adjustment program on behalf of a State. In this proposed rule, we propose standards for risk adjustment data validation, including a sampling methodology for the initial validation audit and detailed audit standards. These proposed standards would be tested for 2 years before they are used as a basis for payment adjustments. This proposed rule also includes a proposal to implement, over time, the requirements related to patient safety standards that QHP issuers must meet, and proposes reducing the time period for which a State electing to operate an Exchange after 2014 must have in effect an approved, or conditionally approved, Exchange Blueprint and operational readiness assessment from at least 12 months to 6.5 months prior to the Exchange's first effective date of coverage. We also propose provisions related to the privacy and security of personally identifiable information (PII), the annual open enrollment period for 2015, the annual limitation on cost sharing for stand-alone dental plans, and the meaningful difference standards for QHPs offered through an FFE. We also propose certain standards for the Small Business Health Options Program (SHOP) and for composite rating in the small group market. 3 Available at: https://www.regtap.info/uploads/library/ACA_HHS_OperatedRADVWhitePaper_062213_5CR_062213.pdf II. Background A. Legislative and Regulatory Overview The Patient Protection and Affordable Care Act (Pub. L. 111-148) was enacted on March 23, 2010. The Health Care and Education Reconciliation Act of 2010 (Pub. L. 111-152), which amended and revised several provisions of the Patient Protection and Affordable Care Act, was enacted on March 30, 2010. In this proposed rule, we refer to the two statutes collectively as the “Affordable Care Act.” Section 1302 of the Affordable Care Act directs the Secretary of Health and Human Services (referred to throughout this rule as the Secretary) to define EHBs and provides for cost-sharing limits and AV requirements. Sections 1302(d)(1) and (d)(2) of the Affordable Care Act describe the determination of the levels of coverage based on AV. Consistent with section 1302(d)(2)(A) of the Affordable Care Act, AV is calculated based on the provision of EHB to a standard population. Section 1302(d)(3) of the Affordable Care Act directs the Secretary to develop guidelines that allow for de minimis variation in AV calculations. Section 1311(b)(1)(B) of the Affordable Care Act directs that the SHOP assist qualified small employers in facilitating the enrollment of their employees in QHPs offered in the small group market. Under section 1312(f)(2)(B) of the Affordable Care Act, beginning in 2017, States will have the option to allow issuers to offer QHPs in the large group market through the SHOP. Section 1311(c)(6)(B) of the Affordable Care Act states that the Secretary is to require an Exchange to provide for annual open enrollment periods for calendar years after the initial enrollment period. Section 1311(h)(1) of the Affordable Care Act specifies that a QHP may contract with health care providers and hospitals with more than 50 beds only if they meet certain patient safety standards, including use of a patient safety evaluation system, a comprehensive hospital discharge program, and implementation of health care quality improvement activities. Section 1311(h)(2) of the Affordable Care Act also provides the Secretary flexibility to establish reasonable exceptions to these patient safety requirements and section 1311(h)(3) of the Affordable Care Act allows the Secretary flexibility to issue regulations to modify the number of beds described in section 1311(h)(1)(A) of the Affordable Care Act. Section 1313 of the Affordable Care Act, combined with section 1321 of the Affordable Care Act, provides the Secretary with the authority to oversee the financial integrity of State Exchanges, their compliance with HHS standards, and the efficient and non-discriminatory administration of State Exchange activities. Section 1321(a) of the Affordable Care Act provides general authority for the Secretary to establish standards and regulations to implement the statutory requirements related to Exchanges, QHPs, and other components of Title I of the Affordable Care Act. When operating an FFE under section 1321(c)(1) of the Affordable Care Act, HHS has the authority under sections 1321(c)(1) and 1311(d)(5)(A) of the Affordable Care Act to collect and spend user fees. In addition, 31 U.S.C. 9701 permits a Federal agency to establish a charge for a service provided by the agency. Office of Management and Budget (OMB) Circular A-25 Revised establishes Federal policy regarding user fees and specifies that a user charge will be assessed against each identifiable recipient for special benefits derived from Federal activities beyond those received by the general public. Section 1341 of the Affordable Care Act requires the establishment of a transitional reinsurance program in each State to help pay the cost of treating high-cost enrollees in the individual market from 2014 through 2016. Section 1342 of the Affordable Care Act directs the Secretary to establish a temporary risk corridors program that provides for the sharing in gains or losses resulting from inaccurate rate setting from 2014 through 2016 between the Federal government and certain participating plans. Section 1343 of the Affordable Care Act establishes a permanent risk adjustment program that is intended to provide increased payments to health insurance issuers that attract higher-risk populations, such as those with chronic conditions, and thereby reduce incentives for issuers to avoid higher-risk enrollees. Sections 1402 and 1412 of the Affordable Care Act establish a program for reducing cost sharing for individuals with lower household income and Indians. Section 1411(g) of the Affordable Care Act provides that any person who receives information specified in section 1411(b) provided by an applicant or information specified in section 1411(c), (d), or (e) from a Federal agency must use the information only for the purpose of and to the extent necessary to ensure the efficient operation of the Exchange, and may not disclose the information to any other person except as provided in that section. Section 6103(l)(21)(C) of the Code additionally provides that return information disclosed under section 6103(l)(21)(A) or (B) may be used only for the purpose of and to the extent necessary in establishing eligibility for participation in the Exchange, verifying the appropriate amount of any premium tax credit or cost-sharing reduction, or determining eligibility for participation in a health insurance affordability program as described in that section. 1. Premium Stabilization Programs In the July 15, 2011 Federal Register (76 FR 41930), we published a proposed rule outlining the premium stabilization programs. We implemented the premium stabilization programs in a final rule, published in the March 23, 2012 Federal Register (77 FR 17220) (Premium Stabilization Rule). In the December 7, 2012 Federal Register (77 FR 73118), we published a proposed rule outlining the benefit and payment parameters for 2014 to expand the provisions related to the premium stabilization programs and set forth payment parameters in those programs (proposed 2014 Payment Notice). We published the 2014 Payment Notice in the March 11, 2013 Federal Register (78 FR 153410). As discussed above, we published a white paper on risk adjustment data validation on June 22, 2013, and hosted a public meeting on June 25, 2013, to discuss the white paper. 2. Program Integrity In the June 19, 2013 Federal Register (78 FR 37032), we published a proposed rule that proposed certain program integrity standards related to Exchanges and the premium stabilization programs (proposed Program Integrity Rule). The provisions of that proposed rule were finalized in two rules, the “first final Program Integrity Rule” published in the August 30, 2013 Federal Register (78 FR 54070) and the “second final Program Integrity Rule” published in the October 30, 2013 Federal Register (78 FR 65046). 3. Exchanges, Essential Health Benefits, Actuarial Value A proposed rule relating to EHBs and AV was published in the November 26, 2012 Federal Register (77 FR 70644). We proposed standards related to the premium adjustment percentage in the Standards Related to Essential Health Benefits, Actuarial Value, and Accreditation Final Rule, published in the February 25, 2013 Federal Register (78 FR 12834) (EHB Rule). We established standards for the administration and payment of cost-sharing reductions and the SHOP in the 2014 Payment Notice and in the Amendments to the HHS Notice of Benefit and Payment Parameters for 2014 interim final rule, published in the March 11, 2013 Federal Register (78 FR 15541). The provisions established in the interim final rule were finalized in the second final Program Integrity Rule. We set forth standards related to Exchange user fees in the 2014 Payment Notice. We also established an adjustment to the FFE user fee in the Coverage of Certain Preventive Services Under the Affordable Care Act final rule, published in the July 2, 2013 Federal Register (78 FR 39870) (Preventive Services Rule). A Request for Comment relating to Exchanges was published in the August 3, 2010 Federal Register (75 FR 45584). An Initial Guidance to States on Exchanges was issued on November 18, 2010. A proposed rule was published in the July 15, 2011 Federal Register (76 FR 41866) to implement components of the Exchange. A proposed rule regarding Exchange functions in the individual market, eligibility determinations, and Exchange standards for employers was published in the August 17, 2011 Federal Register (76 FR 51202). A final rule implementing components of the Exchanges and setting forth standards for eligibility for Exchanges was published in the March 27, 2012 Federal Register (77 FR 18310) (Exchange Establishment Rule). 4. Market Rules Provisions relating to the 2014 market reforms and rate review were published in Patient Protection and Affordable Care Act; Health Insurance Market Rules; Rate Review proposed rule in the November 26, 2012 Federal Register (77 FR 70584). A final rule implementing these provisions was published in the February 27, 2013 Federal Register (78 FR 13406) (Market Reform Rule). 5. Medical Loss Ratio We published a request for comment on PHS Act section 2718 in the April 14, 2010 Federal Register (75 FR 19297), and published an interim final rule with a 60-day comment period relating to the medical loss ratio (MLR) program on December 1, 2010 (75 FR 74864). A final rule with a 30-day comment period was published in the December 7, 2011 Federal Register (76 FR 76574). B. Stakeholder Consultation and Input In addition to seeking advice from the public on risk adjustment data validation, HHS has consulted with stakeholders on policies related to the operation of Exchanges, including the SHOP and the premium stabilization programs. HHS has held a number of listening sessions with consumers, providers, employers, health plans, the actuarial community, and State representatives to gather public input. HHS consulted with stakeholders through regular meetings with the National Association of Insurance Commissioners (NAIC), regular contact with States through the Exchange Establishment grant and Exchange Blueprint approval processes, and meetings with Tribal leaders and representatives, health insurance issuers, trade groups, consumer advocates, employers, and other interested parties. We considered all of the public input as we developed the policies in this proposed rule. C. Structure of Proposed Rule The regulations outlined in this proposed rule would be codified in 45 CFR parts 144, 147, 153, 155 and 156. The proposed regulations in parts 144 and 147 propose amendments relating to student health insurance coverage. The proposed regulations in part 147 also outline market-wide provisions regarding composite rating. The proposed regulations in part 153 outline the 2015 uniform contribution rate and uniform reinsurance payment parameters for the 2015 benefit year and oversight provisions related to the premium stabilization programs, such as provisions related to risk adjustment data validation, risk corridors data validation, and HHS's authority to audit entities participating in these programs. The proposed regulations in part 153 propose that excess reinsurance contributions collected for a benefit year be used for claims for that benefit year. The proposed regulations in part 155 propose to reduce the time that States that elect to establish and operate an Exchange after 2014 must have in effect an approved or conditionally approved Exchange Blueprint and readiness assessment from 12 months to 6.5 months prior to the Exchange's first effective date of coverage. The proposed regulations also include a change to the annual open enrollment period for the 2015 benefit year and certain proposals related to the SHOP Exchanges, which we discuss in greater detail below. We also propose in part 155 to amend § 155.260 to allow the Secretary to determine that additional uses or disclosures of PII not specifically permitted by § 155.260 ensure the efficient operation of the Exchange. In addition, we propose to establish a process under which Exchanges may seek the Secretary's approval for other uses of applicant PII not specifically permitted by § 155.260. We also propose to amend § 155.260 to more specifically define the term “non-Exchange entity” and to provide a baseline for the privacy and security standards to which Exchanges must bind non-Exchange entities through written contracts or agreements. The proposed regulations in part 156 set forth provisions related to cost sharing, including the premium adjustment percentage, the maximum annual limitation on cost sharing, the maximum annual limitation on deductibles for health plans in the small group market, the reductions in the maximum annual limitation for cost sharing plan variations, and the methodology to calculate advance payments of cost-sharing reductions for 2015. They also outline the 2015 FFE user fee rate and propose a user fee adjustment to reimburse third party administrators that pay for contraceptive services for enrollees in certain self-insured group health plans that receive an accommodation from the obligation to cover these services. They also include provisions related to parameters for making updates to the AV calculator in future plan years. The proposed 2015 AV Calculator and a proposed 2015 AV Calculator methodology, which would supersede the 2014 versions of these documents incorporated by reference in the EHB Rule, are being incorporated by reference in this proposed rule. In part 156 we also propose a meaningful difference standard for QHPs offered through an FFE and patient safety standards for issuers of QHPs. Finally, we propose an administrative appeals process applicable to the premium stabilization, cost-sharing reduction, advance payments of the premium tax credit, and FFE user fee programs. In parts 155 and 156, we also propose the following provisions related to the SHOP: • We propose to permit all SHOPs performing premium aggregation to establish one or more standard processes for premium calculation, payment, and collection. • We propose that in the FF-SHOPs, for plan years when premium aggregation is available, employers be required to make premium payments to the FF-SHOP according to a timeline and process established by HHS. We further propose that for plan years beginning on or after January 1, 2015, unless the QHP issuer receives a cancellation notice from the FF-SHOP, the issuer would be required to effectuate coverage. • We propose a standard premium pro-rating methodology for the FF-SHOPs, for plan years when premium aggregation is available, providing that groups will be charged for the portion of the month for which an enrollee is enrolled. • We propose to make explicit our interpretation of current regulations that no SHOPs would be permitted to collect information on a SHOP application unless that information is necessary to determine SHOP eligibility or effectuate enrollment through the SHOP. • We propose that no SHOPs would be permitted to perform individual market Exchange eligibility determinations or verifications. • We propose that a qualified employer that becomes a large employer but continues to purchase coverage through a SHOP would continue to be rated as a small employer. • We propose to limit the employer and employee eligibility adjustment periods to circumstances when the SHOP has an optional verification process, and collects information through that verification process that is inconsistent with the information provided by an employer or employee on a SHOP application. • We propose for plan years beginning on or after January 1, 2015 to give SHOPs in States that permit this activity under State law, the option of permitting enrollment in a SHOP through the Internet Web site of an agent or broker. • We propose to limit the availability of composite premiums in the FF-SHOPs after employee choice and premium aggregation become available. • We propose methods for employers in the FF-SHOPs to offer stand-alone dental coverage after employee choice becomes available in those SHOPs. • We propose for plan years beginning on or after January 1, 2015 to permit FF-SHOPs to give employers the flexibility to define different premium percentage contributions for full-time employees and non-full-time employees. We note that nothing in these proposed regulations would limit the authority of the Office of the Inspector General (OIG) as set forth by the Inspector General Act of 1978 or other applicable law. III. Provisions of the Proposed HHS Notice of Benefit and Payment Parameters for 2015 A. Part 144—Requirements Relating to Health Insurance Coverage In § 144.103, the term “policy year,” as amended by the second final Program Integrity Rule, is defined as: (1) With respect to a grandfathered health plan offered in the individual health insurance market, the 12-month period that is designated as the policy year in the policy documents of the individual health insurance coverage. If there is no designation of a policy year in the policy document (or no such policy document is available), then the policy year is the deductible or limit year used under the coverage. If deductibles or other limits are not imposed on a yearly basis, the policy year is the calendar year; and (2) with respect to a non-grandfathered health plan offered in the individual health insurance market, or in a market in which the State has merged the individual and small group risk pools (merged market), for coverage issued or renewed beginning January 1, 2014, a calendar year for which health insurance coverage provides coverage for health benefits. Further, § 147.104, as amended by the second final Program Integrity Rule, establishes individual market open enrollment periods based on a calendar policy year and provides that non-grandfathered coverage in the individual or merged markets must be offered on a calendar year basis, with a policy year beginning on January 1 and ending on December 31 of each year. Under regulations at § 147.145(a), student health insurance coverage is defined as individual health insurance coverage. Section 147.145(b), however, exempts student health insurance coverage from certain PHS Act and Affordable Care Act requirements that apply to individual health insurance coverage, including certain guaranteed availability provisions of section 2702 of the PHS Act, implemented at § 147.104. As discussed below, because student health insurance coverage is traditionally offered on a school year basis (for example, a policy year beginning on September 1 of each year and ending on August 30 of the following year), we are proposing to modify § 147.145 to exempt student health insurance coverage from the requirement under section 2702 to establish open enrollment periods and coverage effective dates that are based on a calendar policy year, including the requirement that non-grandfathered coverage in the individual and merged markets be offered on a calendar year basis. We are also proposing conforming amendments to the definition of “policy year” to reflect that student health insurance coverage would not be required to be offered on a calendar year basis. We seek comment on this proposal. B. Part 147—Health Insurance Reform Requirements for the Group and Individual Health Insurance Markets 1. Composite Rating Section 2701 of the PHS Act, as added by section 1201 of the Affordable Care Act, establishes permissible rating factors that may be used to vary the premium rate charged by a health insurance issuer for non-grandfathered health insurance coverage (including QHPs) in the individual and small group markets beginning in 2014. 4 The factors are: family size, rating area, age, and tobacco use (within limits). Section 2701(a)(4) of the PHS Act provides that with respect to family coverage under a group health plan or health insurance coverage, any rating variation for age or tobacco use must be applied based on the proportion of the premium attributable to each family member covered under the plan or coverage. 4 Beginning in 2017, States will have the option to allow issuers to offer QHPs in the large group market through the SHOP. If a State elects this option, the rating rules in section 2701 and its implementing regulations will apply to all coverage offered in such State's large group market (except for self-insured group health plans) under to section 2701(a)(5) of the PHS Act. In the Market Reform Rule, we applied the per-member rating requirement of PHS Act section 2701(a)(4) in both the individual and small group markets. Thus, at § 147.102(c), we generally directed that issuers calculate a separate premium for each individual covered under the plan or coverage based on allowable rating factors including age and tobacco use, and sum the individual rates to determine the total premium charged by the issuer to a family or to a group health plan. 5 5 States that do not permit rating for age or tobacco use may require health insurance issuers in the individual and small group markets to use uniform family tiers and corresponding multipliers established by the State. § 147.102(c)(2). We recognized that in the small group market it is common industry billing practice to charge an employer a uniform premium for a given family composition by adding the per-member rates and dividing by the total number of employees covered under the employer's health insurance plan. We indicated that nothing prevents an issuer from converting per-member rates into average enrollee premium amounts (calculated composite premiums), provided that the total group premium is the same total amount derived in accordance with the process established by the regulations. Because calculated composite premiums are average rates for a particular group, changes in employee census would typically cause a change in the average rate. For example, a new average rate per enrollee would typically result from employees adding or dropping coverage during the course of the plan year, causing employer and employee contributions to change as well. We have been asked about such mid-year changes in group composition and how issuers should address the resulting changes in the calculated composite premium for the group. In this proposed rule, we propose to add a provision at § 147.102(c)(3) clarifying that if an issuer offers a composite premium calculated when the employer obtains or renews coverage, the issuer must ensure that such amount does not vary for any plan participant or beneficiary during the plan year with respect to the particular plan involved. Under this approach, an issuer would be required to accept the group's composite premium, calculated based on applicable employee enrollment at the beginning of the plan year, as the applicable premium rate for any new individual who enrolls in the plan during the plan year. 6 Terminations of coverage during the plan year also would not change the composite premium. At the time of renewal, the issuer would recalculate a group's composite premium based on plan enrollment at that time for subsequent coverage. This will allow calculated composite premiums, and thus employer and employee contributions to coverage, to remain stable during the plan year, regardless of changes in the group's composition. 6 In cases where the composite premium does not incorporate the age or tobacco use rating factor, an issuer would be required to accept the group's composite premium, calculated based on applicable employee enrollment at the beginning of the plan year, multiplied by any applicable age or tobacco rating factor, as the applicable premium for any new individual who enrolls in the plan during the plan year. Under § 147.102(a)(1)(iv), rating for tobacco use is subject to the nondiscrimination and wellness provisions under section 2705 of the PHS Act and its implementing regulations, regardless of whether the composite premium incorporates the tobacco use rating factor. This proposed policy would generally apply to health insurance issuers offering non-grandfathered health insurance coverage in the small group market, through a SHOP or outside of a SHOP, for plan years beginning on or after January 1, 2015. However, we encourage issuers to voluntarily adopt this approach for plan years beginning in 2014. As discussed in more detail below, we propose a limited exception to this policy in § 155.705(b)(11)(ii)(D) and § 156.285(a)(4)(ii) of this proposed rule, under which composite rating would not be available when an employer participating in a Federally-facilitated SHOP elects to offer its employees all QHPs within a single level of coverage under § 155.705(b)(3)(iv)(A). We are considering establishing a uniform tiered-composite rating structure that would apply market wide unless a State requires and HHS approves an alternate tiered-composite rating methodology. Under the approach we are considering, a small group market issuer offering composite rating would calculate the composite premium for different tiers of enrollees covered under the employer's plan. For example, in a two-tier structure, one composite premium would be calculated for covered adults (employees and adult dependents) and another composite premium would be calculated for covered children. Alternatively, in a three-tier structure, there would be one composite premium for covered employees, a second composite premium for covered adult dependents, and a third composite premium for covered children. The premium for a given family composition would simply be determined by summing the applicable tiered-composite rates. We believe a tiered-composite approach would promote simplicity for issuers and employers, and ensure that premiums for family coverage appropriately reflect the lower rates for children. We seek comments on all aspects of this approach to composite rating. We also seek comments on whether to establish a default uniform tiered-composite rating structure, including the appropriate number and types of enrollee tiers (for example, an employee-only tier, an adult dependent tier, and a child dependent tier). 2. Student Health Insurance Coverage As discussed above, under § 147.145(a), student health insurance coverage is defined as a type of individual health insurance coverage. However, § 147.145(b) provides that for purposes of the guaranteed availability requirements of section 2702 of the PHS Act, a health insurance issuer that offers student health insurance coverage is not required to accept individuals who are not students or dependents of student in such coverage. Because student health insurance coverage is traditionally offered on a school year basis that does not align with the calendar year, we do not believe student health insurance should be required to establish open enrollment periods and coverage effective dates under § 147.104(b)(1) and (2) that are based on a calendar policy year, including the requirement that non-grandfathered coverage in the individual and merged markets be offered on a calendar year basis. Accordingly, we are proposing to amend § 147.145(b)(1)(ii) to exempt student health insurance coverage from these guaranteed availability requirements. We seek comments on this proposal and whether other modifications are necessary for student health insurance coverage. C. Part 153—Standards Related to Reinsurance, Risk Corridors, and Risk Adjustment under the Affordable Care Act 1. Provisions and Parameters for the Permanent Risk Adjustment Program The risk adjustment program is a permanent program created by section 1343 of the Affordable Care Act that transfers funds from lower risk, non-grandfathered plans to higher risk, non-grandfathered plans in the individual and small group markets, inside and outside the Exchanges. In subparts D and G of the Premium Stabilization Rule, we established standards for the administration of the risk adjustment program. A State that is approved or conditionally approved by the Secretary to operate an Exchange may establish a risk adjustment program, or have HHS do so on its behalf. a. Risk Adjustment User Fees If a State is not approved to operate or chooses to forgo operating its own risk adjustment program, HHS will operate risk adjustment on the State's behalf. As described in the 2014 Payment Notice, HHS's operation of risk adjustment on behalf of States is funded through a risk adjustment user fee. Section 153.610(f)(2) provides that an issuer of a risk adjustment covered plan must remit a user fee to HHS for each month equal to the product of its monthly enrollment in the plan and the per-enrollee-per-month risk adjustment user fee specified in the annual HHS notice of benefit and payment parameters for the applicable benefit year. OMB Circular No. A-25R establishes Federal policy regarding user fees, and specifies that a user charge will be assessed against each identifiable recipient for special benefits derived from Federal activities beyond those received by the general public. The risk adjustment program will provide special benefits as defined in section 6(a)(1)(b) of Circular No. A-25R to an issuer of a risk adjustment covered plan because it will mitigate the financial instability associated with risk selection as other market reforms go into effect. The risk adjustment program also will contribute to consumer confidence in the health insurance industry by helping to stabilize premiums across the individual and small group health insurance markets. In the 2014 Payment Notice, we estimated Federal administrative expenses of operating the risk adjustment program to be $0.96 per enrollee per year, based on our estimated contract costs for risk adjustment operations. For the 2015 benefit year, we propose to use the same methodology to estimate our administrative expenses to operate the program. These contracts cover development of the model and methodology, collections, payments, account management, data collection, data validation, program integrity and audit functions, operational and fraud analytics, stakeholder training, and operational support. We do not propose to set the user fee to cover costs associated with Federal personnel. To calculate the user fee, we would divide HHS's projected total costs for administering the risk adjustment programs on behalf of States by the expected number of enrollees in risk adjustment covered plans (other than plans not subject to market reforms and student health plans, which are not subject to payments and charges under the risk adjustment methodology HHS uses when it operates risk adjustment on behalf of a State) in HHS-operated risk adjustment programs for the benefit year. We estimate that the total cost for HHS to operate the risk adjustment program on behalf of States for 2015 will be approximately $27.3 million, and that the per capita risk adjustment user fee would be no more than $1.00 per enrollee per year. We seek comment on this proposed assessment of user fees to support HHS-operated risk adjustment programs. b. HHS Risk Adjustment Methodology Considerations In the 2014 Payment Notice, we finalized the methodology that HHS will use when operating a risk adjustment program on behalf of a State in 2014. We propose to use the same methodology in 2015. In this proposed rule, we propose to clarify the treatment of premium assistance Medicaid alternative plans in this risk adjustment methodology, and seek comment on potential adjustments to the geographic cost factor in the HHS risk adjustment model for future years. (i) Incorporation of Premium Assistance Medicaid Alternative Plans in the HHS Risk Adjustment Methodology Section 1343(c) of the Affordable Care Act provides that risk adjustment applies to non-grandfathered health insurance coverage offered in the individual and small group markets. In some States, expansion of Medicaid benefits under section 2001(a) of the Affordable Care Act may take the form of enrolling newly Medicaid-eligible enrollees into individual market plans. For example, these enrollees could be placed into silver plan variations—either the 94 percent silver plan variation or the zero cost sharing plan variation—with a portion of the premiums and cost sharing paid for by Medicaid on their behalf. Because individuals in these types of Medicaid expansion plans receive significant cost-sharing assistance, they may utilize medical services at a higher rate. To address this induced utilization in the context of cost-sharing reduction plan variations in the HHS risk adjustment methodology, we increase the risk score for individuals in plan variations by a certain factor. We propose to use the same factor for individuals enrolled in the corresponding Medicaid expansion plan variations. Table 1 shows the cost-sharing adjustments for both 94 percent silver plan variation enrollees and zero cost-sharing plan variation enrollees for silver QHPs as finalized in the 2014 Payment Notice. We propose to implement these adjustments for 2014. We plan to evaluate these adjustments in the future, after data from the initial years of risk adjustment is available. We seek comment on this approach. Table 1—Cost-Sharing Reduction Adjustments Plan variation Induced utilization factor 94 percent Plan Variation 1.12 Zero Cost-Sharing Plan Variation of Silver QHP 1.12 (ii) Adjustment to the Geographic Cost Factor As finalized in the 2014 Payment Notice, the geographic cost factor is an adjustment in the payment transfer formula to account for plan costs such as input prices that vary geographically and are likely to affect plan premiums. For the metal-level risk pool, it is calculated based on the observed average silver plan premium in a geographic area relative to the statewide average silver plan premium. It is separately calculated for catastrophic plans in a geographic area relative to the statewide catastrophic pool. However, several States have defined a large number of rating areas. Less populous rating areas raise concerns about the accuracy and stability of the calculation of the geographic cost factor because in less populous rating areas the geographic cost factor might be calculated based on a small number of plans. Inaccurate or unstable geographic cost factors could distort premiums and the stability of the risk adjustment model. We seek comment on how to best adjust the geographic cost factors or geographic rating areas in future years to address these potential premium distortions. We also seek comments on how this adjustment should be implemented for a separately risk adjusted pool of catastrophic plans. We do not intend to make this adjustment for 2014. c. Small Group Determination for Risk Adjustment For a plan to be subject to risk adjustment, according to section 1343(c) of the Affordable Care Act and the definition of a “risk adjustment covered plan” in § 153.20, a plan must be offered in the “individual or small group market.” The definition of small group market in § 153.20 references the definition at section 1304(a)(3) of the Affordable Care Act. Section 1304(a)(3) of the Affordable Care Act, in defining “small group market,” references the definition of a “small employer” in section 1304(b)(2) of the Affordable Care Act. That definition provides that an employer with an average of at least 1 but not more than 100 employees on business days during the preceding calendar year and who employs at least 1 employee on the first day of the plan year will be considered a “small employer.” However, section 1304(b)(3) of the Affordable Care Act provides that, for plan years beginning before January 1, 2016, a State may elect to limit “small employer” to mean an employer with at least 1 but not more than 50 employees. In the 2014 Payment Notice, we stated that we believe that the Affordable Care Act requires the use of a counting method that accounts for part-time employees, and that the full-time equivalent method described in section 4980H(c)(2)(E) of the Code is a reasonable method to apply. Thus, we believe that the risk adjustment program must also use a counting method that takes employees that are not full-time into account when determining whether a group health plan must participate in that program. However, we also recognize that, because risk adjustment is intended to stabilize premiums by mitigating the effects of the rating rules, it is important that the program be available to plans that are subject to the rating rules, to the extent permissible under the Affordable Care Act. We recognize that a number of States, which have primary enforcement jurisdiction over the market rules, may use counting methods that do not take non-full-time employees into account. Thus, we propose to clarify that in determining which group health plans participate as small group plans in the risk adjustment program, we would apply the applicable State counting method, unless the State counting method does not take into account employees that are not full-time. In that circumstance, we would apply the full-time equivalent method described in section 4980H(c)(2)(E) of the Code. 7 We believe that this approach defers to State counting methods and aligns with State enforcement of rating rules, within the bounds of what is permissible under the Affordable Care Act. We seek comment on our interpretation of the permissible counting rules for purposes of risk adjustment, the approach described above, and on alternate counting methods that may be preferable. We also seek comment on whether we should codify these risk adjustment counting rules in regulation text. 7 We note that the IRS has published a proposed regulation that contains further details that would apply to this calculation (54.4980H-2(c)). d. Risk Adjustment Data Validation The 2014 Payment Notice established a risk adjustment data validation program that HHS will use when operating risk adjustment on behalf of a State. In the 2014 Payment Notice, we specified a framework for this program that includes six stages: (1) Sample selection; (2) initial validation audit; (3) second validation audit; (4) error estimation; (5) appeals; and (6) payment adjustments. To develop the details of the program, we sought the input of issuers, consumer advocates, providers, and other stakeholders. We issued the “Affordable Care Act HHS-Operated Risk Adjustment Data Validation Process White Paper” on June 22, 2013. That white paper discussed and sought comments on a number of potential considerations for the development of the risk adjustment data validation methodology. On June 25, 2013, we held a public meeting to discuss the topics considered in the white paper. We received submissions from 53 commenters, including issuers, issuer trade groups, advocacy groups, and consultants. As we noted in the white paper, our overall goals are to promote consistency and a level playing field by establishing uniform audit requirements, and to protect private information by limiting data transfers during the data validation process. In this proposed rule, we propose provisions for the risk adjustment data validation process and methodology that reflect our analysis of the white paper comments and our discussions with stakeholders. We note that a State operating a risk adjustment program is not required to adopt these standards. These proposed rules are consistent with the white paper and lessons drawn from our experience with Medicare Advantage risk adjustment data validation and thus should be familiar to issuers. (i) Sample Selection The first stage in the HHS-operated risk adjustment data validation process is the selection of a sample of an issuer's enrollees whose risk adjustment data will be validated. In the proposed 2014 Payment Notice, we stated that HHS would choose a sample size of enrollees such that the estimated risk score errors would be statistically sound and the enrollee-level risk score distributions would reflect enrollee characteristics for each issuer. We stated that in determining the appropriate sample size for data validation, we recognized the importance of striking a balance between ensuring statistical soundness of the sample and minimizing the operational burden on issuers, providers, and HHS. Additionally, we stated that we would ensure that the sample would cover critical subpopulations of enrollees for each risk adjustment covered plan, such as enrollees with and without hierarchical condition categories (HCCs). To develop a proposed sample size for the first year of the HHS risk adjustment data validation program, we propose to use the methodology outlined in the white paper. Our goal in determining the enrollee sample size for the initial 2 years of risk adjustment data validation is to propose a statistically valid sample large enough to inform us to the dynamics of the risk adjustment data validation process in operation and estimation of risk score accuracy. As we established in the 2014 Payment Notice, for HHS to observe and optimize the risk adjustment data validation process, no payment adjustments will be made based on the risk adjustment data validation process for the initial 2 years of HHS-operated risk adjustment. In general, we propose to select the initial validation audit sample for a given benefit year by dividing the relevant population into a number of “strata,” representing different demographic and risk score bands. We are proposing that, for the initial 2 years of the risk adjustment data validation program, the initial validation audit sample will consist of 200 enrollees from each issuer. We stated in the 2014 Payment Notice that the overall sample will reflect a disproportionate selection of enrollees with HCCs. Here, we discuss in detail our proposed sampling methodology, including our proposal to group enrollees to account for age characteristics and health status. Some commenters on the white paper suggested that we also consider sampling based on plan types and other characteristics. We will consider other sampling strategies in the future, but believe that we do not yet have enough experience with the risk adjustment process to determine the most appropriate sampling groups at this time. Therefore, we are proposing a simple age and risk score stratification for at least the initial 2 years of the program. Following the division of the relevant population into strata, we propose to use the following formulas to calculate a proposed sample size for the initial validation audit each year. In general, the proposed formula for the overall sample size for an issuer ( n ) is: ep02de13.008 Where: H is the number of strata; N h is the population size of the hth stratum; Y is the average risk score of the population, adjusted based upon the estimated risk score error; S h represents the standard deviation of risk score error for the hth stratum; Prec represents the desired precision level (for example, 10 percent, meaning a 10 percent margin of error in the estimated risk score); and z-value is the z-value associated with the desired confidence level (for example, 1.96 for a two-sided 95 percent confidence level). As noted above, we propose a sample size of 200 enrollees from each issuer for the initial 2 years of the program. The formula above would be used after this initial 2-year period to calculate a more precise, issuer-specific sample size for each issuer. The proposed formula for calculating the sample size for each stratum is: ep02de13.009 Where: N h is the population size of the h th stratum; n is the overall sample size; and S h represents the standard deviation of risk score error for the h th stratum. For the 2014 benefit year, the parameters listed above were developed using data from two principal sources: Medicare Advantage risk adjustment data validation net error rates and variances; and expenditures data from the Truven Health Analytics 2010 MarketScan® Commercial Claims and Encounters database (MarketScan®). We chose to use Medicare Advantage error rates because Medicare Advantage utilizes an HCC-based methodology similar to the one used for HHS risk adjustment, and because it uses a similar risk adjustment data validation process to determine payment error rates. We also chose to use the MarketScan® expenditure database because of the comprehensiveness of the database, which was the primary source for calibration for the HHS risk adjustment models. The database contains enrollee-specific claims utilization, expenditures, and enrollment across inpatient, outpatient, and prescription drug services from a selection of large employers and health plans. The database includes de-identified data from approximately 100 payers, and contains more than 500 million claims from insured employees, spouses, and dependents. We used enrollee predicted expenditure results from our risk adjustment model calibration, which was based on the MarketScan® data, to stratify the population (by age group for enrollees with HCCs, and within a single group for enrollees with no HCCs), then calculated risk scores for the predicted expenditures to relate them to the average expenditures. To estimate a sample size for each issuer, an average issuer size was estimated based on the total expected insured population and the total expected number of issuers. The average issuer population containing enrollees with and without HCCs was assumed to be split 20 percent with HCCs and 80 percent without HCCs, consistent with the MarketScan® data. We propose to group each issuer's enrollee population into 10 strata based on age group, risk level, and presence of HCCs, as follows: • Strata 1-3 would include low, medium, and high risk adults with the presence of at least one HCC. • Strata 4-6 would include low, medium, and high risk children with the presence of at least one HCC. • Strata 7-9 would include low, medium, and high risk infants with the presence of at least one HCC. • Stratum 10 will include the No-HCC population, which will not be further stratified by age or risk level, because we assume this stratum has a uniformly low error rate. We calculated a predicted risk score for each individual in each stratum by dividing the predicted expenditures for that individual by the average predicted expenditures for the entire population. Using these individual predicted risk scores, we calculated the overall average risk score for all individuals in each risk-based stratum. This calculation was performed nine times for the HCC population—once for each of the three risk-based strata within each of the three age groups. We set the minimum risk score for enrollees without HCCs in the tenth stratum. This method of stratification is similar to that used in the Medicare Advantage risk adjustment data validation program. That program divides enrollees into three strata, representing low, medium, and high risk expenditures. Error rates and variances are calculated for each of these strata. In the initial year, before error rate and standard deviation data for the population subject to the HHS-operated risk adjustment program are available, we propose to use the Medicare Advantage error rates and variances to calculate sample sizes. After the initial year, we will evaluate whether sufficient HHS-operated risk adjustment error rate and standard deviation data are available to calculate sample sizes. We propose to use the lowest error rate across all HCC strata as the error rate for the stratum of enrollees without HCCs, and we propose to use the variance associated with that error rate to calculate the standard deviation of the error for the stratum of enrollees without HCCs. If error rates and variances are smaller than assumed for this stratum, the resulting sampling precision may increase. Because the Medicare Advantage error rates and variances are not calculated for different age bands, and therefore are available only for three risk-score differentiated subgroups, we used the same risk score error rates and standard deviation for the age bands for a risk category. Thus, we used the same risk score error rate and standard deviation assumptions for the adult, child, and infant strata associated with each risk score band. We do not anticipate the expected risk score error rate and variance to be uniform for all age groups; however, in the absence of data, we made this simplifying assumption. In general, we believe the Medicare Advantage error rates and variances likely overstate the corresponding error rates and assumptions for the HHS risk adjusted population, and therefore, the estimated precision of our error estimates may be understated. The formulas identified above require data on error rates and standard deviations for the strata, and also a target confidence interval and sampling precision level (or margin of error). For the initial year, we propose to use a 10 percent relative sampling precision at a two-sided 95 percent confidence level. That is, we wish to obtain a sample size such that 1.96 8 multiplied by the standard error, divided by the estimated adjusted risk score, equals 10 percent or less. After actual data are collected from the initial year, we will test and evaluate the data for use in determining the sample size in future years. 8 Critical value for the two-sided 95 percent confidence level. Once the proposed overall sample size is calculated, the enrollee count will be distributed among the population based on the second formula above for calculating the sample size of each stratum. Because strata with enrollees with HCCs have a higher standard deviation of risk score error, the overall sample will be disproportionately allocated to enrollees with HCCs (Strata 1-9), helping to ensure adequate coverage of the higher risk portion of the enrollee population. In the proposed rule for the 2014 Payment Notice, we suggested that an issuer's initial validation audit sample for risk adjustment data validation would consist of approximately 300 enrollees. After conducting the calculations described above, we believe that we can achieve acceptable sampling precision with a sample size of 200 enrollees for the initial years of HHS-operated risk adjustment data validation. Therefore, we are proposing a sample size of 200 enrollees in the initial 2 years of the program. As noted above, we may provide for different, or issuer-specific, sample sizes in future years. When data becomes available from the program's first year, we expect to examine our sampling assumptions using actual enrollee data. We anticipate that at least in the initial years of the risk adjustment data validation program, the stratification design will remain consistent with the design outlined above—nine HCC strata and one No-HCC stratum. However, the specific size and allocation of the sample to each stratum may be refined based on average issuer enrollee risk score distributions. For example, in future years, we are considering using larger sample sizes for larger issuers or issuers with higher variability in their enrollee risk scores, and smaller sample sizes for smaller issuers or issuers with lower variability in their enrollee risk scores. The sampling design may also consist of a minimum and maximum sample size per stratum for each average issuer (large, medium, small) to follow when selecting the sample. We seek comments on this approach, including our proposed sample size of 200 enrollees for the initial 2 years of HHS-operated risk adjustment data validation. (ii) Initial Validation Audit The second stage of the HHS-operated risk adjustment data validation process is the initial validation audit. In § 153.630(b)(1), we require an issuer of a risk adjustment covered plan to engage one or more independent auditors to perform an initial validation audit of a sample of its risk adjustment data selected by HHS, which will include individually identifiable health information subject to HIPAA. 9 In this section of this proposed rule, we discuss proposed standards and guidelines regarding the qualifications of the initial validation auditor, including conflict of interest standards, standards for the initial validation audit, rater consistency and reliability, and confirmation of risk adjustment errors. As discussed in the white paper, we considered existing best practices and standards for independent auditors, such as those of Medicare Quality Improvement Organizations and the National Committee for Quality Assurance, when establishing our standards for initial validation auditors. 9 Whether any given organization is a HIPAA business associate is a fact-specific inquiry. We expect that most independent auditors operating on behalf of an issuer of a health plan would be performing activities that would render them a business associate of the covered plan, and would be required to enter into and maintain a business associate agreement with the health plan. (1) Initial Validation Auditor The 2014 Payment Notice established certain standards for the initial validation auditor. In § 153.630(b)(2) and (b)(3), we direct the issuer to ensure that the initial validation auditor is reasonably capable of performing an initial validation audit, and is reasonably free of conflicts of interest, such that it is able to conduct the initial validation audit in an impartial manner with its impartiality not reasonably open to question. In the white paper, we elaborated on options for ensuring that an initial validation auditor meets these criteria, including standardized auditor certification processes and promulgation of best practices. Many commenters sought additional information and guidance regarding initial validation auditor selection and requested that HHS define conflicts of interest between an issuer and the initial validation auditor. We propose certain guidance on these topics here. We are considering the following criteria for assessing conflicts of interest between the issuer and the initial validation auditor: • Neither the issuer nor any member of its management team (or any member of the immediate family of such a member) may have any material financial or ownership interest in the initial validation auditor, such that the financial success of the initial validation auditor could be seen as materially affecting the financial success of the issuer or management team member (or immediate family member) and the impartiality of the initial validation audit process could reasonably be called into question, or such that the issuer or management team member (or immediate family member) could be reasonably seen as having the ability to influence the decision-making of the initial validation auditor; • Neither the initial validation auditor nor any member of its management team or data validation audit team (or any member of the immediate family of such a member) may have any material financial or ownership interest in the issuer, such that the financial success of the issuer could be reasonably seen as materially affecting the financial success of the initial validation auditor or management team or audit team member (or immediate family member) and the impartiality of the initial validation audit process could reasonably be called into question, or such that the initial validation auditor or management or audit team member (or immediate family member) could be seen as having the ability to influence the decision-making of the issuer; • Owners, directors and officers of the issuer may not be owners, directors or officers of the initial validation auditor, and vice versa; • Members of the data validation audit team of the initial validation auditor may not be married to, in a domestic partnership with, or otherwise be in the same immediate family as an owner, director, officer, or employee of the issuer; and • The initial validation auditor may not have had a role in establishing any relevant internal controls of the issuer related to the risk adjustment data validation process when HHS is operating risk adjustment on behalf of a State, or serve in any capacity as an advisor to the issuer regarding the initial validation audit. In addition, we are considering standards under which issuers would verify that no key individuals involved in supervising or performing the initial validation audit have been excluded from working with either the Medicare or Medicaid program, are on the Office of the Inspector General exclusion list, or are under investigation with respect to any HHS programs. We note that we intend to review the initial validation auditor's qualifications and relationship to the issuer to verify that the initial validation auditor is qualified to perform the audit, and that the issuer and initial validation auditor are free of actual or apparent conflicts of interest, including those stated above. We note that HHS could gather information through external reporting to support that review. Although we are confident that most issuers will exercise diligence in selecting an initial validation auditor that will be able to comply with HHS audit standards, we intend to monitor the performance of initial validation auditors to determine whether certification or additional safeguards are necessary. We propose to amend § 153.630(b)(1) to specify that the issuer of a risk adjustment covered plan must provide HHS with the identity of the initial validation auditor, and must attest to the absence of conflicts of interest between the initial validation auditor (or the members of its audit team, owners, directors, officers, or employees) and the issuer (or its owners, directors, officers, or employees). We propose to consider any individual with a significant ownership stake in an entity such that the individual could reasonably be seen to have the ability to influence the decision making of the entity to be an “owner,” and propose to consider any individual that serves on the governing board of an entity to be a director of the entity. We are contemplating beginning the initial validation process at the end of the first quarter of the year following the benefit year, with the issuer's submission of the initial validation auditor's identity. We expect to identify the enrollee sample for the initial validation audit in the summer of the year following the benefit year. We are contemplating requiring delivery of the initial validation audit findings to HHS in the fourth quarter of that year. We include a proposed schedule of the risk adjustment data validation process at the end of this section. Once the audit sample is selected by HHS, we expect issuers would ensure that the initial validation audit is conducted in the following manner: • The issuer would provide the initial validation auditor with source enrollment and source medical record documentation to validate issuer-submitted risk adjustment data for each sampled enrollee; • The issuer and initial validation auditor would determine a timeline and information-transfer methodology that satisfies data security and privacy requirements, including the applicable provisions of HIPAA, and enables the initial validation auditor to meet HHS established timelines; • The initial validation auditor would analyze the enrollment and medical record data to validate the demographic information, plan or plan variation enrollment, and health status of each enrollee in the sample in accordance with the standards established by HHS; and • The initial validation auditor would provide HHS with the final results from the initial validation audit and all requested information for the second validation audit. We note that § 153.630(f)(2) is not changed by this proposal, and that the issuer would be required to ensure that its initial validation auditor comply with the security standards described at 45 CFR 164.308, 164.310, and 164.312 in connection with the initial validation audit. We seek comments on these proposals. (2) Standards for the Initial Validation Audit We propose to add a new paragraph (b)(5) to § 153.630, in which we propose that an initial validation audit review of enrollee health status be conducted by medical coders certified after examination by a nationally recognized accrediting agency for medical coding, such as the American Health Information Management Association (AHIMA) or the American Academy of Professional Coders (AAPC). We seek comment on other nationally recognized accrediting agencies that may be appropriate to certify medical coders who are performing the initial validation audit review of enrollee health status. (3) Validation of Enrollees' Risk Scores An enrollee's risk score is derived from demographic and health status factors, which requires the use of enrollee identifiable information. Thus, we propose to add paragraph (b)(6) to § 153.630, to require an issuer to provide the initial validation auditor and the second validation auditor with all relevant information on each sampled enrollee, including source enrollment documentation, claims and encounter data, and medical record documentation (defined below) from providers of services to enrollees in the applicable sample without unreasonable delay and in a manner that reasonably assures confidentiality and security of data in transmission (“data in transit”). We note that existing privacy and security standards, such as standards under HIPAA and those detailed at § 153.630(f)(2), would apply. This information will be used to validate the enrollment, demographic, and health status data of each enrollee. Only source documentation for encounters with dates of services within the applicable benefit year would be considered relevant. This would require issuers to collect the appropriate enrollment and claims information from their own systems, as well as from all relevant providers (particularly with respect to medical record documentation). We note that only a very small percentage of an issuer's records containing personally identifiable information would be made available to auditors as part of the risk adjustment data validation process, and that similar transmissions are required today for data validation for the Medicare Advantage program. As we describe in this section at (viii), regarding data security standards, we are seeking comment on the applicability and effectiveness of current standards, as well as what other standards HHS should promulgate to ensure data security and privacy protections. We also propose to add paragraph (b)(7) to § 153.630 to describe the standards for validating each factor of an enrollee's risk score. In paragraph (b)(7)(i), we propose that the initial validation auditor must validate demographic data and enrollment information by reviewing plan source enrollment documentation, such as the 834 transaction, 10 which is the HIPAA-standard form used for plan benefit enrollment and maintenance transactions. These enrollment transactions reflect the data the issuer captured for an enrollee's age, name, sex, plan of enrollment, and enrollment periods in the plan. We note that certain identifying information from these enrollment transactions, such as the enrollee's name, would be used to ensure that the appropriate medical documentation has been provided. 10 Issuers and State Exchanges use the ASC X12 Standards for Electronic Data Interchange Technical Report Type 3—Benefit Enrollment and Maintenance (834), August 2006, ASC X12N/005010X220, as referenced in § 162.1502, or “834 form” to transmit and update enrollment and eligibility to HHS as often as daily but at least monthly. In Federal operations, HHS and the issuer exchange and update data via this same form. The sample audit pool will consist of enrollees with and without risk adjustment-eligible diagnoses within eligible dates of service. For each enrollee in the sample with risk adjustment HCC scores, the initial validation auditor would validate diagnoses through a review of the relevant risk adjustment-eligible medical records. We consider medical record documentation generated with respect to dates of service that occurred during the benefit year at issue to be relevant for these purposes. For enrollees without risk adjustment HCCs for whom the issuer has submitted a risk adjustment-eligible claim or encounter, we would require the initial validation auditor to review all medical record documentation for those risk adjustment-eligible claims or encounters, as provided by the issuer, to determine if HCC diagnoses should be assigned for risk score calculation, provided that the documentation meets the requirements for the risk adjustment data validation audits. Documents used to validate all components of the risk score must reflect dates of service during the applicable benefit year. In the initial years of the data validation program, we plan to accept certain supplemental documentation, such as health assessments, to support the risk adjustment diagnosis. We expect to provide additional details on acceptable supplemental documentation in future guidance. 11 11 See “HHS-Operated Data Collection Policy FAQ” for a discussion of chart review as an acceptable source of supplemental diagnosis codes. Additional detail will be provided in future guidance. https://www.regtap.info/uploads/library/HHS_OperatedDataCollectionPolicyFAQs_062613 . Therefore, in § 153.630(b)(7)(ii), we propose that the validation of enrollee health status (that is, the medical diagnoses) occur through medical record review, that the validation of medical records include a check that the records originate from the provider of the medical services, that they align with the dates of service for the medical diagnosis, and that they reflect permitted providers and services. In this paragraph, we also propose, for purposes of § 153.630, that “medical record documentation” mean: “clinical documentation of hospital inpatient or outpatient treatment or professional medical treatment from which enrollee health status is documented and related to accepted risk adjustment services that occurred during a specified period of time.” Medical record documentation must be generated in the course of a face-to-face or telehealth visit documented and authenticated by a permitted provider. We expect to provide additional guidance on telehealth services in future guidance. In § 153.630(b)(7)(iii), we propose that medical record review and abstraction be performed in accordance with industry standards for coding and reporting. Current industry standards are set forth in the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), or the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, 4th Edition (ICD-10-CM) guidelines for coding and reporting. (4) Confirmation of Risk Adjustment Errors We note that the data validation audit processes may identify various discrepancies, many of which will have no impact on an enrollee's risk score. For example, if a medical diagnosis underlying an enrollee's HCC was present on a claim but was not supported by medical record documentation, but the same HCC was supported by the medical record for a different diagnosis, we propose that no risk adjustment error be assessed for the enrollee's HCC. However, if none of the medical record documentation supports a particular HCC diagnosis for an enrollee, we propose that a risk adjustment error be assessed. We consider a risk adjustment error to occur when a discrepancy uncovered in the data validation audit process results in a change to the enrollee's risk score. A risk adjustment error may result from incorrect demographic data, an unsupported HCC diagnosis, or a new HCC diagnosis identified during the medical record review. An unsupported HCC diagnosis could be the result of missing medical record documentation, medical record documentation that does not reflect the diagnosis, or invalid medical record documentation (such as an unauthenticated record or a record that does not meet risk adjustment data collection standards for the applicable benefit year). We propose in § 153.630(b)(7)(iv) that a senior reviewer must confirm any finding of a risk adjustment error. We believe that a senior reviewer is a reviewer with substantial expertise in medical record coding such that the initial validation auditor would consider the senior reviewer to be the standard against which to measure inter-rater reliability and coding consistency. As such, we propose to define a senior reviewer as a medical coder certified by a nationally recognized accrediting agency who possesses at least 5 years of experience in medical coding. We seek comment on the credentials and expertise that should be required of a senior reviewer. (5) Review Consistency and Reliability Validation audits typically include methods of evaluating review consistency and reliability. We believe such processes help to ensure the integrity of the data validation process and strengthen the validity of audit results. In § 153.630(b)(8), we propose that the initial validation auditor measure and report to the issuer and HHS its inter-rater reliability rates among its reviewers. Such processes measure the degree of agreement among reviewers. We propose to set the threshold for the acceptable level of consistency among reviewers at 95 percent for both demographic and enrollment data review, and health status data review outcome. Reviews should be performed using rater-to-standard procedures whereby reviews conducted by reviewers with extensive qualifications and credentials are used to establish testing thresholds or standards for consistency. (iii) Second Validation Audit The initial validation audit will be followed by a second validation audit, which will be conducted by an auditor retained by HHS to verify the accuracy of the findings of the initial validation audit. We propose to select a subsample of the initial validation audit sample enrollees for review by the second validation auditor. The second validation auditor would perform the data validation audit of the enrollee subsample, adhering to the same audit standards applicable to the initial validation audit described above, but would only review enrollee information that was originally presented during the initial validation audit. In § 153.630(c), we established standards for issuers of risk adjustment covered plans related to HHS's second validation audit. In § 153.630(b)(4), we established that issuers must submit (or ensure that their initial validation auditor submits) data validation information, as specified by HHS, from their initial validation audit for each enrollee included in the initial validation sample. Issuers must transmit all information to HHS or its second validation auditor in a timeframe and manner to be determined by HHS. The second validation auditor would inform the issuer of error findings based on its review of enrollees in the second validation audit subsample. We will provide additional guidance on the manner and timeframe of these submissions in the future. As discussed in the white paper, we are considering selecting the second validation audit subsample using a sampling methodology that will allow for pair-wise means testing to establish statistical difference between the initial and second validation audit results. If the pair-wise means test results suggest that the difference in enrollee results between the initial validation audit and second validation audit is not statistically significant, the initial validation audit error results would be used for error estimation and calculation of adjustments for plan average risk score. If the test results suggest a statistical difference, the second validation auditor would perform another validation audit on a larger subsample of the enrollees previously subject to the initial validation audit. The results from the second validation audit of the larger subsample would again be compared to the results of the initial validation audit using the pair-wise means test. Again, if no statistical difference is found between the initial validation audit and the second validation audit conducted on the larger subsample, HHS would apply the initial validation audit error results for error estimation using all enrollees selected for the initial validation audit sample. However, if a statistical difference is found based on the second validation audit on the larger subsample, HHS would apply the second validation audit error results to modify the risk scores of the issuer's enrollees, as discussed below. We are considering using a 95 percent confidence interval, but seek comment on the appropriate confidence interval to use with respect to these pair-wise means tests. As discussed in the white paper, we are considering a number of ways to expedite the second validation audit and the subsequent appeals processes. One possibility would be to begin the second validation audit on those enrollees for which the initial validation audit is complete, even if the entire initial validation audit has not been completed. For example, an issuer could allow its initial validation auditor to submit data validation documentation and results a number of months in advance of the HHS established deadline for submission of initial validation audit results. The second validation auditor would thus be able to begin its review earlier, permitting more time to provide feedback to the issuer on the results of that review and allowing for more opportunity for discussion prior to finalizing the second validation audit findings. Prior to finalizing the risk score adjustment based on the second validation audit findings, the second validation auditor may request discussions with the initial validation auditor to identify the source of the differences, or may review the initial validation auditor's processes. If the initial validation audits are substantiated, the second validation auditor may adjust its risk scores accordingly. This process would not allow for any additional documentation to be submitted on those enrollees for which the second validation audit began early. The appeals decision from the expedited, concurrent process would be final and binding, but would provide issuers the opportunity to begin the process earlier. If HHS establishes a concurrent second validation audit and appeals process, we would need to develop intermediate timelines for initial validation auditor submission of audit documentation and data to the second validation auditor. We seek comments on this approach for establishing a concurrent second validation audit and appeals process. (iv) Error Estimation The fourth stage in the HHS risk adjustment data validation process is error estimation. Upon completion of the initial and second validation audits, HHS will derive an issuer-level risk score adjustment and confidence interval. This adjustment would be used to adjust the average risk score for each risk adjustment eligible plan offered by the issuer. HHS intends to provide each issuer with enrollee-level audit results and the error estimates. We are proposing a two-phase procedure to accept or correct the results of the initial validation audit based on the results of the second validation audit. In phase one, as described above, we conduct a pair-wise statistical test for consistency between the initial validation and second validation audit results (as described above for second validation audits). In phase two, if we determine that the results of the two audits are inconsistent, we would adjust the initial validation audit results based on the second validation audit results. For phase two, we describe two options for using second validation audit results to derive an estimate of an overall corrected risk score for each issuer. Phase One: Consistency Test between Initial and Second Validation Audit In phase one, a pair-wise statistical test would be performed to determine if the initial validation audit sample results should be adjusted using the results of the second validation audit. To illustrate the underlying statistical test, consider the following notations: x i is the i th initial validation audit risk score observation in the second validation audit sample of n observations; y i is the i th second validation audit risk score observation in the second validation audit sample of n observations; d i is the difference between y i and x i within the second validation audit sample; d is the mean of all d i observations within the second validation audit sample; and S x is standard deviation of all d i observations within the second validation audit sample. Assume an issuer submits enrollment and claims data to its dedicated distributed data environment that are used to compute a set of “original” risk scores. As required by the risk adjustment data validation process, the issuer engages an independent validation auditor, who reviews N enrollee records, as sampled by HHS, and validates the original enrollee risk scores. From the N enrollees in the initial validation audit sample, HHS selects a smaller second validation audit subsample of n enrollees. For each second validation audit selected record, HHS calculates the difference, d i = y i − x i . HHS then conducts a pair-wise means test to determine whether the mean difference, d , is statistically significant (that is, unlikely to be zero). Specifically, HHS would conduct a statistical test to determine if zero (0) is contained within the range, EP02DE13.010 If so, HHS would conclude that there is no statistically significant difference between risk scores determined by the initial and second validation audit processes, and would accept the results of the initial validation audit. However, if zero (0) is not contained within this range (that is, the difference between d and zero is statistically significant), HHS would expand the second validation audit subsample to select a larger subset of N , have the second validation auditor review the enrollee files, and again conduct a pair-wise means test using this larger subsample. If the statistical test shows no statistically significant difference, HHS would accept the results of the initial validation audit. If the statistical test shows a statistically significant difference between the initial and larger subsample second validation audit findings, HHS would conduct phase two to adjust the full initial validation audit sample based on the larger subsample second validation audit findings. Phase Two: Adjustment to the Initial Validation Audit Sample In phase two, we propose that if the difference between the initial and second validation audits is found to be statistically significant, then HHS would utilize the risk score error rate calculated from the larger second validation audit subsample to adjust the full initial validation audit sample, which could in turn be used to adjust the average risk scores for each plan. This approach would adjust the entire initial validation audit sample using a one-for-one replacement for the enrollees reviewed by the second validation audit, and a uniform adjustment for the enrollees that were not. We also considered another option, as discussed in the white paper and below. Under this alternate approach, we would use the error rate from the larger second validation audit subsample directly in our determination of whether and by how much to adjust the risk scores of all enrollees in the issuer's risk adjustment covered plans. This approach would disregard all enrollees in the initial validation audit sample that were not reviewed as part of the larger second validation audit subsample. To illustrate these two options under the phase two adjustment process, consider the following notations: M is the total number of enrollees in the risk adjustment covered plan; N is the initial validation audit sample size; n is the size of the larger second validation audit subsample; y N is the mean of the initial validation audit-adjusted risk scores in the initial validation audit sample N; y n is the mean of the second validation audit-adjusted risk scores in the second validation audit sample n; x N is the mean of the original risk scores in the initial validation audit sample N; x n is the mean of the original risk scores in the second validation audit sample n; X M is the original risk score total across all M records; Y N is the projected correct risk score across all M records using the initial validation error rate; and EP02DE13.011 y n is the projected correct risk score across all M records using the error rate from the larger second validation audit subsample. EP02DE13.012 Under this proposed approach, we would undertake the following steps to adjust the risk scores in the initial validation audit samples: (1) Replace the initial validation audit-adjusted risk scores with the second validation audit-adjusted risk scores in the n records that were sampled from N (one-for-one risk score adjustment). (2) Apply a uniform adjustment factor, EP02DE13.013 to the initial validation audit-adjusted risk scores in the ( N - n ) records not reviewed by the second validation audit. Under the alternate approach, the second validation audit-adjusted risk scores in the n records in the larger second validation audit subsample would be used as the basis for adjustment of plan-level average risk scores. Considering the comments in response to the white paper, and in order to estimate error using a narrower confidence interval, we are proposing to use the larger second validation audit subsample to adjust the initial validation audit sample (by direct replacement for enrollees reviewed by the second validation audit, and by proportional adjustment for the other enrollees), whose adjusted error rate could be used as a basis to adjust plan average risk scores for all risk adjustment covered plans of the issuer. We seek comment on our proposed approach. Adjusted Risk Score Projections Based on the proposals described above, the results of the initial or second validation audits could be used as the basis for projecting a corrected risk score for each issuer's population. The projections described above would be performed on a stratum-by-stratum level and weighted accordingly to achieve an estimate of the corrected risk score for each issuer. As described in the white paper, a stratified separate ratio estimator 12 would be used to estimate the corrected average risk score for each issuer. To compute the stratified separate ratio estimator, HHS would first extrapolate the total correct risk score within each stratum, then sum the stratum-specific projected correct risk scores for all strata, with the total sum divided by the total enrollee count to arrive at the corrected average risk score. The projected risk score error could then be calculated as the difference between the recorded average risk score across the entire population and the point estimate. 12 For a discussion of stratified separate ratio estimators, see Cochran, William G., Sampling Techniques, third edition, John Wiley & Sons, 1977, at 164. The stratified separate ratio estimator of the total correct risk score is calculated using the following equation: EP02DE13.014 Where: Y R is used to estimate the correct risk score; y h is the sample mean of the correct risk score in stratum h; x h is the sample mean of the original risk score in stratum h; X h is the total sum of the original risk score in stratum h; and H is the total number of strata. Y R would then be normalized by the enrollment count to derive a corrected average risk score for the issuer. To estimate the variance of the point estimate, HHS will first estimate the variance within each stratum and then sum the stratum-specific variances for all strata. The estimated variance of the stratified separate ratio estimate for the correct risk score is calculated as follows: EP02DE13.015 Where: n h is the number of enrollees sampled in stratum h; N h is the population frequency in stratum h; y ih is the corrected risk score for the i th sampled enrollee in stratum h; x ih is the original risk score for the i th sampled enrollee in stratum h; and EP02DE13.016 The square root of the estimated variance is the standard error (SE). We are proposing to use the issuer's corrected average risk score to compute an adjustment factor, based on the ratio between the corrected average risk score and the original average risk score that could be applied to adjust plan average risk for all risk adjustment eligible plans within the issuer. We are considering two options for applying the adjustment factor. Under the first option, we are considering directly applying an adjustment factor to all of the issuer's risk adjustment covered plans. Under the second option, we are considering applying this adjustment only if the corrected average risk score and the recorded average risk score are statistically different. Were we to implement the second option, a critical parameter of the statistical test would be the target confidence interval, which would determine the stringency of the test. For example, we could perform the statistical test at the 90, 95, or 99 percent confidence interval. We note that the HHS Office of the Inspector General performs certain similar data validation tests using a 90 percent confidence interval, while the Medicare Advantage risk adjustment data validation program uses a 99 percent confidence interval. We also note that even if the statistical test finds the two risk scores to be statistically different, we could apply the adjustment factor to adjust plan average risk scores based upon using the point estimate of the adjusted average risk score, or some other value within an interval around the point estimate, such as the upper or lower bound of a 95 percent confidence interval around the point estimate. The choice among these options poses a tradeoff between reducing issuers' incentives to aggressively report or code diagnoses, and increasing the variability of issuers' risk adjustment payments. Under the first option, an issuer that reports data that systematically overstates its risk score would, on average, assuming the corrected risk scores are unbiased estimates of the true risk scores, receive a downward adjustment to its reported risk score equal in magnitude to the degree of overstatement. As a result, this option could eliminate an issuer's incentive to overstate its risk score. On the other hand, due to sampling variation, the first option would routinely introduce significant variability in issuers' risk scores (both up and down), even if the issuer was making no attempt to manipulate its risk scores. While these adjustments would make such an issuer's risk adjustment payments less predictable in any given year, they would not introduce systematic bias in risk scores (assuming the corrected risk scores are unbiased estimates of the true risk scores). The second option, in contrast, would only adjust an issuer's risk scores when it is very likely that the reported risk scores deviated from the true values, so issuers' risk adjustment payments would be more predictable. However, particularly if the confidence level of the statistical test were set at a high threshold, this approach would often fail to make adjustments when an issuer does in fact overstate its risk score. Based on commenters' feedback on the white paper, we are proposing to use the second approach described above—we would adjust the plan average risk scores of an issuer based upon the ratio between the correct average risk score estimate and recorded average risk score only if the difference between the estimated and recorded average risk scores were determined to be statistically significant. We are proposing to use a 95 percent confidence interval to determine if the adjusted average risk score and the recorded average risk score are statistically different. Nevertheless, we welcome comments on both options discussed above and on the appropriate tradeoff between reducing issuers' incentive to aggressively report or code diagnoses and increasing the variability of issuers' risk adjustment payments. In addition, regarding the proposed approach in particular, we seek comments on the appropriate confidence interval to apply when determining whether an adjustment to an issuer's plan average risk score is necessary. Error Estimation Example To illustrate the corrected average risk score and error estimation process described above, assume that a sample of 200 enrollees is selected for initial validation audit review for a particular issuer. From this sample, assume that a subsample of 20 enrollees is selected for second validation audit review. Assume the issuer's average recorded population risk score is 1.60 and the projected correct population risk score from the sample of 200 is 1.40, with a two-sided 95 percent confidence interval of 1.30 to 1.50. The first step in the error estimation process will determine if the initial validation audit results should be corrected based on the second validation audit review or accepted without adjustment. We would perform a pair-wise means test to compare the projected risk scores for the sample of 200 enrollees and the subsample of 20 enrollees. For this example, assume that the statistical test fails (that is, there is a statistically significant difference between the projected risk scores in the sample of 200 and the subsample of 20). 13 We would then select an expanded subsample from the original sample of 200 enrollees. Assume that the larger sample is a sample of 100 enrollees. Following completion of the larger second validation audit, we would perform the pair-wise means test again. Assume the test fails again (that is, there is a statistically significant difference in the projected risk scores between the sample of 200 and the larger subsample of 100). We would conclude that the risk scores in the sample of 200 enrollees need to be adjusted. 13 If the test passes, then no adjustments would be made to the sample of 200 and the projected results from this sample would be used to adjust average plan liability risk scores. In the second step of error estimation, HHS would adjust the risk scores in the sample of 200 using a one-for-one replacement for the risk scores of the enrollees reviewed by the second validation auditor, and a uniform adjustment for the other enrollees in the initial validation audit sample. The one-for-one replacement will replace the risk scores calculated based on initial validation audit findings, with the risk scores calculated based on the second validation audit findings for the larger subsample of 100. The remaining 100 enrollees that were not included in the second validation audit subsample would be adjusted based on the ratio of two projections: (1) the projected correct population risk score using the second validation audit findings in the subsample of 100 (assume this projected risk score is 1.50, with a two-sided 95 percent confidence interval of 1.30 to 1.70); divided by (2) the projected correct population risk score using the initial validation audit findings in the sample of 200 (equal to 1.40 based on the assumption noted above). The adjustment ratio is equal to 1.07 = 1.50/1.40. Therefore, the risk scores of the remaining 100 enrollees not included in the second validation audit subsample would be increased by 7 percent. The projected correct population risk score from the revised sample of 200 would therefore be 1.45, with a two-sided 95 percent confidence interval of 1.35 to 1.55. (v) Appeals We anticipate that the risk adjustment data validation appeals process would occur annually, beginning in the spring of the year in which the error rate will be applied to adjust risk scores and affect risk adjustment payments and charges. Because we are not applying error rates to adjust payments and charges for the initial 2 years of the risk adjustment program, the first year for which payments and charges would apply would be 2016. Risk scores and initial payments and charges would be calculated in the spring of 2017 for that payment cycle. We anticipate the appeals process will begin in the spring of 2018, prior to the 2017 payment transfers. We will provide additional guidance on the appeals process and schedule in future rulemaking. (vi) Payment Transfer Adjustments Risk adjustment payment transfer amounts will be based on adjusted plan average risk scores. The data validation audits would be used to develop a risk score error adjustment for each issuer, as described above. Each issuer's risk score adjustment would be applied to adjust the plan average risk score for each of the issuer's risk adjustment covered plans. This adjustment would be applied on a prospective basis beginning with the risk adjustment data for benefit year 2016 (that is, the adjustments would take effect in 2018, during payment transfers for 2017). Because an issuer's adjusted plan average risk score is normalized as part of the risk adjustment payment calculation, the effect of an issuer's risk score error adjustment will depend upon its magnitude and direction compared to the average risk score error adjustment and direction for the entire market. We are considering reporting the following summary findings to issuers for the initial 2 years of the program: • State- or market-wide error rates. • Issuer error rates. • Initial validation audit or error rates. • Projected financial impact of the proposed risk adjustments, as determined by the initial and second validation auditors. • The 2-year interval before risk adjustment data validation adjustments are applied to risk scores and affect payments and charges will provide initial validation auditors and issuers the opportunity to reform existing processes prior to the implementation of HHS payment transfer adjustments for the 2016 benefit year. We believe that the reports described above will help issuers and initial validation auditors better understand the likely effects of the risk adjustment data validation program in States where HHS operates risk adjustment. We seek comment on considerations for reporting error rates and any additional information that could improve transparency in the markets. (vii) Oversight The second final Program Integrity Rule outlined selected oversight provisions related to the premium stabilization programs, such as maintenance of records, sanctions for failing to establish a dedicated distributed data environment, and the application of a default risk adjustment charge to issuers in the individual and small group market that fail to provide data necessary for risk adjustment. We are proposing to expand on these provisions to include oversight related to risk adjustment data validation when HHS operates risk adjustment on behalf of a State. Section 153.620 provides that an issuer that offers risk adjustment covered plans must comply with any data validation requests by the State or HHS on behalf of the State, and that an issuer that offers risk adjustment covered plans must also maintain documents and records, whether paper, electronic, or in other media, sufficient to enable the evaluation of the issuer's compliance with applicable risk adjustment standards, and must make that evidence available upon request to HHS, OIG, the Comptroller General, or their designee, or in a State where the State is operating risk adjustment, the State or its designee to any such entity. Based on our authority under section 1321(c)(2) of the Affordable Care Act, we are proposing in § 153.630(b)(9) that, when HHS operates risk adjustment on behalf of a State, an issuer of a risk adjustment covered plan that does not engage an initial validation auditor within the timeframe specified by HHS of the year following the benefit year, or that otherwise does not arrange for a risk adjustment initial validation audit that complies with applicable regulations, may be subject to civil money penalties. We note that we intend to apply the proposed sanction so that the level of the enforcement action would be proportional to the level of the violation. While we would reserve the right to impose penalties up to the maximum amounts proposed in § 156.805(c), as a general principle, we intend to work collaboratively with issuers to address problems in conducting the risk adjustment data validation process. In our application of the proposed sanction, we would take into account the totality of the issuer's circumstances, including such factors as an issuer's previous record (if any), the frequency and level of the violation, and any aggravating or mitigating circumstances. Our intent is to encourage issuers to address non-compliance and not to severely affect their business, especially where the issuer demonstrates good faith in monitoring compliance with applicable standards, identifies any suspected occurrences of non-compliance, and attempts to remedy any non-compliance. We also note that HHS will not perform the initial validation audit for an issuer that does not hire an initial validation auditor or otherwise does not submit initial validation audit results that comply with the regulations in subpart G and subpart H of part 153. For these issuers, we propose in § 153.630(b)(10) to assign a default risk adjustment charge. We are considering whether this charge should be the same charge as contemplated in § 153.740(b), should be based on a default error rate, or should be calculated based on some other methodology. We will propose a methodology for computing the default error rate or default charge in future rulemaking. Issuers may request technical assistance from HHS at any stage of the risk adjustment data validation process. HHS may also offer such assistance directly if we become aware of technical issues arising at any time during the risk adjustment data validation process. We plan to provide further assistance and clarification around the risk adjustment data validation process through a range of vehicles, including additional guidance, training materials, webinars, and user group calls. We welcome comment on these proposals. (viii) Data Security We recognize that the risk adjustment data validation process outlined here will require the transmission of sensitive data and documents between the issuer and the initial and second validation auditors. HHS takes seriously the importance of safeguarding protected health information and personally identifiab [Text truncated at 120,000 characters. The full text is on the page linked above.] --- Source: Frix Law Library, https://www.frixlaw.com/law-library/documents/fr%3A2013-28610. Public record. Not legal advice.