MINNESOTA
COUNCIL of
H E A L TH
P L A N S
COURT INTERNATIONAL BUILDING
2550 UNIVERSITY AVENUE WEST
SUITE 255 SOUTH
ST. PAUL, MINNESOTA 55114
651-645-0099 FAX 651-645-0098
May 5, 2015
VIA EMAIL: [email protected]
Ms. Anne Krohmer, Project Coordinator
Minnesota Department of Health
RE: State-Based Risk Adjustment RFI
Dear Ms. Krohmer:
Thank you for the opportunity to comment on your plans to assess a state-based risk adjustment model. This
letter reflects individual health plan comments and serves as a group response to your request for information.
In general, we have concerns with introducing a state-based risk adjustment model at this time. The federal
government has had more time, better standardized data and greater analytical resources to support its model.
Additionally, the economy of scale achieved through the federal risk adjustment program makes it very costeffective. It will be difficult to accomplish greater cost-effectiveness with a state-based model.
Also keep in mind that comparing a state-based risk-adjustment methodology to a static 2014 federal riskadjustment approach ignores the reality that the federal program is evolving and will continue to evolve over
time. For example, CMS recognizes the partial month issue and will likely address it in an upcoming iteration of
its model along with other continuous improvements. As a result, a state-based model that is “better than” 2014
federal risk adjustment may not be any improvement over 2016 or 2017 federal risk adjustment.
Before commenting on your request for information, we outline specific concerns on the draft data request.
These concerns are in three areas: data integrity, legislative scope and granularity of data.
Data Integrity
The Department seeks not only post-ACA 2014 data, but also pre-ACA 2013 data, altered for the current
marketplace. Asking health plans to manipulate 2013 data to estimate what it could be under the ACA is
unnecessary and risky. Because the 2013 and 2014 (and beyond) markets are fundamentally different, the
manipulation of 2013 data could call into question the validity of any modeling. Specifically,
 It is highly unlikely that 2013 data includes a population with rare diseases as the 2013 market was
underwritten.
 In 2013 individuals could purchase products excluding benefits such as mental health, chemical health,
maternity and/or brand drug coverage. These benefits were required in 2014.
 Many of the 2013 products do not reach bronze level criteria.
We understand the need for data to identify disease prevalence levels and strongly recommend a sound approach
be developed to meet this need. As proposed, the lack of claims for rare diseases and excluded benefits could
distort any analysis.
Blue Cross and Blue Shield/Blue Plus of Minnesota  HealthPartners  Medica
Metropolitan Health Plan  PreferredOne  Sanford Health Plan of Minnesota  UCare
Anne Krohmer
May 5, 2015
Page 2
Beyond Legislated Scope
The data sought are beyond the study’s legislated scope. Study parameters stated in legislation are:
 Evaluate the extent to which Minnesota’s All Payer Claims Database (APCD) could be used for
conducting state-based risk adjustment.
 Collect data needed for the study.
 Conduct modeling to determine if a Minnesota-based risk adjustment model can perform better and be
more cost-effective than the federal risk adjustment model.
It appears that data to support other policy-related work have been added to the study design. The following
details are not necessary to answer the clear, technical question of how to do risk-adjustment:
 A MinnesotaCare subsidy indicator. This study’s focus is on the risk adjustment program in the
commercial, non-grandfathered individual and small group markets. If the purpose for this request is to
address the Basic Health Program and its funding, it should be addressed separately in order to allow for
thorough consideration of all issues around this important topic.
 A self-funded vs. fully insured indicator. The risk adjustment program applies only to the fully insured,
non-grandfathered individual and small group markets.
 Market category code indicator. Risk adjustment applies at the individual member level, making it
unclear why it is necessary to distinguish among groups of different sizes.
 Zip code data. Zip codes cross over counties and uniform geographic rating areas established by the
state. If geographic areas are part of the study, MDH should just ask for the rating area. As requested this
detail could confuse the data.
 HIOS plan IDs. HIOS plan IDs are unnecessary for the study and they are not constant year to year.
These ID numbers change within the same plan and are sometimes reused for different plans the next
year.
 Data on groups sized 51-100. In addition to being unnecessary for this study, system limitation prevent
data from being broken out as requested.
Granularity of Data
The draft request gathers data at an unnecessarily granular level, exceeding the current full-fledged federal risk
adjustment program. That added detail will make data gathering, analysis and modeling more difficult, and press
on resource constraints of the State contractors and health plans. A hurried exercise is more likely to raise
technical and process questions than to provide information for you to effectively identify the pros and cons of a
state-based risk adjustment process.
Below we provide health plan comments on the RFI and responses to specific questions.

Our understanding of the federal risk adjustment model is not consistent with information presented by
the Department in the RFI. The federal risk adjustment program transfers funds from plans with lowerrisk enrollees to plans with higher-risk enrollees. This process mitigates the impacts of adverse selection
and is a tool for maintaining a stable health insurance market. Congress created this program as a
permanent check against adverse selection resulting from guaranteed issuance of coverage. The
program’s sole purpose is to mitigate adverse selection in each state’s health insurance market. As a
Anne Krohmer
May 5, 2015
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result, carriers are essentially “bidding” on the average cost of members, eliminating a carrier’s incentive
for avoiding risk. The federal model then redistributes funds based on the risk factors of each carrier’s
enrolled population. (Question 1.)
The RFI seeks feedback on the potential areas for improvement relative to the current federal risk
adjustment methodology. We question the ability of commenters to offer feedback because results for
the first year have not been calculated or released. A study of the federal risk adjustment methodology’s
effectiveness and outcomes is necessary to draw an objective conclusion. Such analysis would require
years of experience with the federal model and must consider improvements made to the system over
time.
The federal risk adjustment model uses a hierarchical condition category based on federal averages.
Minnesota does not have data that is specific enough to allow accurate calculations for risk adjustment.
(Question 2.a.)
As mentioned above, using 2013 pre-ACA data to gain prevalence information is a flawed approach and
needs to be reconsidered. (Question 2.a.)
The risk adjustment system should not account for network design because it is already accounted for in
rate setting. (Question 2.a.)
As mentioned above, interaction of risk adjustment with Basic Health Program funding is outside of the
scope of this study.
A state-based reinsurance program is out of scope for this study. Reinsurance is not risk adjustment and
should remain separate. (Question 2.c.)
Administrative simplification across government programs and commercial markets is unlikely given the
products and populations are significantly different. The only way to accomplish this would be to
compromise the effectiveness of the risk adjustment methodology. Such compromise is contrary to the
purposes of the study and to the ACA’s risk adjustment program. The program’s purpose is to mitigate
the impacts of adverse selection in the commercial non-grandfathered individual and small group
markets. (Question 2.d.)
A risk adjustment process requiring new data not already in the public domain would add additional
costs and ongoing maintenance. This path not only opens questions of taking private data, but also
creates unique management issues for a state model. This approach would not be easier and cheaper than
a federal approach that relies on data in the public domain. (Question 2.e.)
The federal risk adjustment model already accounts for geographic rating areas. (Question 3.d.)
There is concern that historically there have been quality issues with the data in Minnesota’s APCD.
Final reports on the quality of the APCD data are still pending. Until issues with data quality in
Minnesota’s APCD are resolved, using that data set may result in faulty study conclusions.
A key consideration to highlight in the RFI recommendation is the cost of a state-based risk adjustment program
to the state’s insurance market and ultimately, to consumers. The cost of the federal program is a nominal
portion of the premium (it equals $1.75 per member per year for 2016, and for 2014 it was $1 per member per
year). Economies of scale make it an extremely cost-efficient program with the opportunities to improve upon it
very limited. For instance:
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All of the health plans in Minnesota have already invested significant financial and staff resources into
building the EDGE server system used by the federal risk adjustment and other “3-Rs” programs. Even
with a state-based program, health plans must use the EDGE sever for other 3-R programs.
Anne Krohmer
May 5, 2015
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CMS has a team of at least 200 individuals working on risk adjustment and they have already produced
hundreds of program guidelines and instruction manuals.
Using the APCD as the data source for state-based risk adjustment would require an extensive and costly
data validation process. Data validation requirements for the EDGE server system are more rigorous
than those used for the APCD, and have been tested and refined for more than a year. Performing the
same data validation exercise with OnPoint would take years and cost the state and the health plans
millions of dollars. This exercise would be wasteful since data validation work has already been
performed for the EDGE servers and the servers provide the data necessary to execute the risk
adjustment program.
Because the federal model continues to evolve, a state-based model will need evolve as well. This means
that there are both one-time and ongoing costs for developing a state based risk-adjustment
methodology.
In closing, the risk adjustment study as planned is more aggressive than the time and resources devoted to
accomplish it. We encourage the Department to take any steps possible to simplify this study and narrow its
design. We are only beginning the second year into ACA implementation and relying on just one full-year of
data, or worse, manufactured pre-ACA data, is not likely to clearly answer the question of whether the state
should pursue a state-based risk adjustment program.
Thank you for the opportunity to comment on the Request for Information. We recognize the difficulty of the
mandated study and hope that our comments help to clarify potential issues. We look forward to continued
collaboration on this project as you assess the best path forward for the State.
Sincerely,
James D. Schowalter
President/CEO
Minnesota Council of Health Plans