MEDICARE 

ADVANTAGE

Substantial Excess 

Payments Underscore 

Need for CMS to 

Improve Accuracy of 

Risk Score 

Adjustments

Report to Congressional Requesters

January 2013

GAO-13-206

United States Government Accountability Office

GAO
United States Government Accountability Office

Highlights of GAO-13-206, a report to 

congressional requesters

January 2013

MEDICARE ADVANTAGE

Substantial Excess Payments Underscore Need for 

CMS to Improve Accuracy of Risk Score 

Adjustments

Why GAO Did This Study

CMS pays plans in MA—the private 

plan alternative to FFS—a 

predetermined amount per beneficiary 

adjusted for health status. To make 

this adjustment, CMS calculates a risk 

score, a relative measure of expected 

health care for each beneficiary. Risk 

scores should be the same among all 

beneficiaries with the same health 

conditions and demographic 

characteristics. Differences in 

diagnostic coding between MA plans 

and Medicare FFS led to 

inappropriately high MA risk scores 

and payments to MA plans, and CMS 

adjusted for coding differences in 

2010. In January 2012, GAO reported 

that CMS’s adjustments to risk scores 

did not sufficiently correct for coding 

differences, resulting in excess 

payments to MA plans. Since 

completing the analysis for the January 

2012 report, risk score data for two 

additional years have become 

available. GAO (1) determined the 

extent to which differences, if any, in 

diagnostic coding between MA plans 

and Medicare FFS affected MA risk 

scores and payments to MA plans in 

2010, 2011, and 2012; and 

(2) identified what changes, if any, 

CMS made to its risk score adjustment 

methodology for 2013 and intends to 

make for future years. To do this, GAO 

compared risk score growth for MA 

beneficiaries with an estimate of what 

risk score growth would have been for 

those beneficiaries if they were in 

Medicare FFS for 2010 and projected 

the growth to 2011 and 2012, and 

determined if there were changes to 

CMS’s methodology by reviewing 

agency documentation and 

interviewing agency officials. 

What GAO Found

GAO found that the cumulative impact of coding differences on risk scores 

increased from 2010 through 2012 and was greater than the Centers for 

Medicare & Medicaid Services’ (CMS) risk score adjustment of 3.4 percent for 

each of the 3 years. In updating the analysis from its January 2012 report, GAO 

estimated that cumulative Medicare Advantage (MA) risk scores in 2010 were 

4.2 percent higher than they likely would have been if the same beneficiaries had 

been enrolled continuously in Medicare fee-for-service (FFS). For 2011, GAO 

estimated that differences in diagnostic coding resulted in risk scores that were 

4.6 to 5.3 percent higher than they likely would have been if the same 

beneficiaries had been continuously enrolled in FFS. This upward trend 

continued for 2012, with estimated risk scores 4.9 to 6.4 percent higher.

CMS’s adjustment to risk scores for 2010 through 2012 to account for diagnostic 

coding differences was too low, resulting in estimated excess payments to MA 

plans of at least $3.2 billion. CMS’s annual 3.4 percent reduction in risk scores is 

equivalent to $2.8 billion in 2010, $3.0 billion in 2011 and $3.2 billion in 2012. 

According to GAO’s estimates, the amount of the excess payments to MA plans 

after accounting for CMS’s adjustments was $0.6 billion in 2010, between 

$1.1 billion and $1.6 billion in 2011, and between $1.5 billion and $2.9 billion in 

2012. Cumulatively across the 3 years, this equals excess payments of between 

$3.2 billion and $5.1 billion.

For 2013, CMS continues to use the risk score adjustment of 3.4 percent it used 

in 2010, 2011, and 2012. To conduct its data-based analysis, CMS officials 

reported that they used the same methodology used in 2010, but they 

incorporated more recent data. CMS officials told us that, in addition to the 

results of the data analysis, they incorporated additional factors such as recent 

payment changes made to the MA program under the Patient Protection and 

Affordable Care Act and the maintenance of benefits for seniors. The Social 

Security Act does not prescribe CMS’s methodology for adjusting for differences 

in diagnostic coding. However, the express purpose of the requirements to 

conduct and incorporate into the risk scores a data-based analysis of coding 

differences is to ensure payment accuracy. The act does not provide for factors 

other than the results of the analysis to be incorporated into the adjustment, 

suggesting that accuracy would be ensured solely through the incorporation of 

analytical results. CMS officials stated that they believed there was policy 

discretion with respect to the most appropriate adjustment factor but did not 

identify the specific source of their authority to consider factors other than the 

required data analysis when determining the adjustment amount. While CMS did

not change its risk score adjustment methodology for 2013, agency officials said 

they may revisit their methodology for future years.

GAO’s findings underscore the importance for CMS to implement the 

recommendation from GAO’s January 2012 report that the agency improve the 

accuracy of its MA risk score adjustments by taking steps such as using the most 

current data available and incorporating adjustments for additional beneficiary 

characteristics.

CMS reviewed a draft of this report and stated that it had no comments.

View GAO-13-206. For more information, 

contact James Cosgrove at (202) 512-7114 or 

cosgrovej@gao.gov.
Page i GAO-13-206 Medicare Advantage Diagnostic Coding

Letter 1 

Background 5

CMS’s Adjustment for Coding Differences for 2010 through 2012 

Was Too Low, Resulting in Estimated Excess Payments to MA 

Plans of at Least $3.2 Billion 8

CMS Did Not Change Its Risk Score Adjustment Methodology for 

2013, but May Revisit It in Future Years 11

Concluding Observations 12

Agency Comments 13

Appendix I Scope and Methodology 14

Appendix II GAO Contact and Staff Acknowledgments 21

Table

Table 1: Impact of Adjustments for Coding Differences on Total 

Payments to MA Plans in 2010, 2011, and 2012 19

Figures

Figure 1: CMS and GAO Adjustments of Risk Scores to Account for 

Diagnostic Coding Differences, 2010 to 2012 9

Figure 2: Estimated Excess Payments to MA Plans after 

Accounting for CMS’s Risk Score Adjustments for 

Diagnostic Coding Differences, 2010-2012 10

Contents 
Page ii GAO-13-206 Medicare Advantage Diagnostic Coding

Abbreviations

CMS Centers for Medicare & Medicaid Services

FFS fee-for-service 

HCC hierarchical condition category

MA Medicare Advantage

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Page 1 GAO-13-206 Medicare Advantage Diagnostic Coding

United States Government Accountability Office

Washington, DC 20548

January 31, 2013

The Honorable Henry A. Waxman

Ranking Member

Committee on Energy and Commerce

House of Representatives

The Honorable Sander M. Levin

Ranking Member

Committee on Ways and Means

House of Representatives

In 2012, the federal government will spend an estimated $134.7 billion on 

the Medicare Advantage (MA) program, an alternative to the original 

Medicare fee-for-service (FFS) program, in which private health plans 

offer health care coverage to Medicare beneficiaries. The Centers for 

Medicare & Medicaid Services (CMS), the agency that administers 

Medicare, pays private plans a monthly amount per beneficiary to provide 

health care services for each beneficiary enrolled in these plans. CMS 

adjusts this payment to account for a beneficiary’s health status, a 

process known as risk adjustment, and assigns to each MA beneficiary a 

risk score—a relative measure of expected health care costs.1

Risk scores for beneficiaries with the same diagnoses and characteristics 

should be identical, regardless of whether the beneficiaries are in an MA 

plan or Medicare FFS. However, MA plans have a greater incentive than 

FFS providers to make sure that all medical diagnoses are 

comprehensively coded, as this can increase beneficiaries’ risk scores 

and ultimately the payments plans receive. This is not the case for FFS 

providers, who are generally paid for the services they provided and 

whose payments do not vary based on the diagnoses of the beneficiaries 

 

1

Information on a beneficiary’s age, sex, Medicaid enrollment status, original reason for 

Medicare entitlement (i.e., age or disability), and major medical conditions all generally 

factor into the calculation of the risk score. To gather information on medical diagnoses for 

beneficiaries in Medicare FFS, CMS analyzes the claims that FFS providers submit for 

payment. For beneficiaries enrolled in MA plans, instead of submitting claims, CMS 

requires plans to submit certain diagnosis codes for each beneficiary. Medical diagnoses 

are not used to calculate risk scores for beneficiaries who were not enrolled in Medicare 

for all of the previous year.

 
 

Page 2 GAO-13-206 Medicare Advantage Diagnostic Coding

who received the services.2

In January 2012, we reported that CMS’s adjustments to account for 

differences in diagnostic coding were inadequate and resulted in excess 

payments to MA plans.

Consequently, risk scores for beneficiaries in 

MA plans may tend to be higher relative to the risk scores of beneficiaries 

in FFS who are in similar health and have identical characteristics. To 

ensure that MA plans are not overpaid as a result of these differences in 

diagnostic coding patterns, CMS makes a separate adjustment to MA 

plan payments.

3

We also found that the impact of coding differences increased over time 

and noted that this trend suggested that the cumulative impact of coding 

differences in 2011 and 2012 could be larger than in 2010. However, 

CMS applied the same 3.4 percent adjustment to risk scores it used in 

2010 to risk scores in 2011 and 2012. To help ensure appropriate 

payments to MA plans, we recommended that CMS take steps to improve 

the accuracy of the adjustment made for differences in diagnostic coding 

practices between MA plans and Medicare FFS.

In 2010, CMS estimated that 3.4 percent of MA 

beneficiary risk scores were attributable to diagnostic coding differences 

between MA plans and Medicare FFS providers. CMS reduced MA 

beneficiaries’ 2010 risk scores by 3.4 percent, which resulted in the 

agency saving $2.7 billion in excess payments to MA plans. However, on 

the basis of the information available when we did our study, we 

estimated that the difference in diagnostic coding between MA plans and 

Medicare FFS providers was greater—4.8 percent to 7.1 percent—

depending on the assumptions made about trends in risk score growth. 

Our estimate differed from CMS’s because we used more recent data, 

incorporated the trend of coding differences over time, and accounted for 

additional beneficiary characteristics.

Since we completed the analysis for our January 2012 report, risk score 

data for 2 additional years have become available. You asked us to 

update and extend our work on differences in diagnostic coding practices 

 

2

One important exception is hospital acute inpatient services, for which Medicare payment 

is based on Medicare severity diagnosis–related groups rather than services.

3

See GAO, Medicare Advantage: CMS Should Improve the Accuracy of Risk Score 

Adjustments for Diagnostic Coding Practices, GAO-12-51 (Washington, D.C.: Jan. 12, 

2012).
 

Page 3 GAO-13-206 Medicare Advantage Diagnostic Coding

between MA and Medicare FFS and their impact on MA payments. This 

report (1) determines the extent to which differences, if any, in diagnostic 

coding between MA plans and Medicare FFS affected MA risk scores and 

payments to MA plans in 2010, 2011, and 2012; and (2) identifies what 

changes, if any, CMS made to its risk score adjustment methodology for 

2013 and intends to make for future years.

To determine the extent to which differences in diagnostic coding 

between MA plans and Medicare FFS affected MA risk scores for 2010, 

2011, and 2012, we used a similar approach as for our January 2012 

report. We first compared actual risk score growth for beneficiaries in MA 

plans with the estimated risk score growth MA beneficiaries would have 

had if they were enrolled in Medicare FFS. To do this, we calculated 

changes in disease scores—the portion of the risk score that is based on 

a beneficiary’s coded diagnoses—for MA beneficiaries and used 

regression analysis to estimate what changes in disease scores would 

have been if those beneficiaries were enrolled in Medicare FFS.4 We 

attributed differences between actual and estimated disease score growth 

to differences in coding practices between MA plans and Medicare FFS. 

We estimated the extent to which differences in diagnostic coding 

between MA plans and Medicare FFS affected 2010, 2011, and 2012 risk 

scores by estimating the cumulative impact of coding differences starting 

with 2007 risk scores.5

 

4

In our regression analysis, we accounted for the following beneficiary characteristics: 

age, sex, diagnoses as a proxy for health status, Medicaid enrollment status, beneficiary 

residential location, and whether the original reason for Medicare entitlement was 

disability. These characteristics may affect the frequency with which beneficiaries interact 

with health care providers, thereby affecting the amount of information contained within 

beneficiaries’ medical records and the completeness with which providers code 

diagnoses.

5

Our use of 2007 risk scores, based on prior-year diagnoses, as the first risk score to 

contribute to our cumulative coding estimate assumes that MA plans and Medicare FFS 

had similar coding patterns at that time. CMS believes that MA coding patterns may have 

been less comprehensive than FFS when the CMS-Hierarchical Condition Categories 

(CMS-HCC) model was first implemented, and that coding pattern differences caused MA 

risk scores to grow faster than FFS; therefore, there may have been a period of “catch-up” 

before MA coding patterns became more comprehensive than FFS. For our previous 

report, we evaluated how sensitive our analysis results were to our assumption that 

coding patterns for MA and FFS were similar in 2006—the year of coding on which 2007 

risk scores were based—by evaluating how our results would change if we assumed the 

“catch-up” period was shorter and that MA and FFS coding patterns were similar in 

2004—the first year the CMS-HCC model was implemented. Altering the year by which 

MA coding patterns had “caught up” to FFS coding patterns had little effect on our results.
 

Page 4 GAO-13-206 Medicare Advantage Diagnostic Coding

Because 2010 risk scores were the most recent available at the time of 

our analysis for this report, we projected the estimated impact of coding 

differences to 2012 using different assumptions of trends: the lower 

projection assumed that the impact of coding differences on risk score 

growth for 2010 to 2012 was the same as it was for 2009 to 2010, while 

the higher projection assumed that the trend in the impacts of diagnostic 

coding differences on risk score growth from 2005 through 2010 

continued through 2012.6

We made two enhancements to the methodology used for our January 

2012 report. First, we altered our assumption about which beneficiaries 

had risk score growth that could be affected by differences in coding 

practices between MA plans and Medicare FFS. Specifically, for our 

January 2012 report, we assumed that beneficiaries who were recently 

enrolled in MA without any prior Medicare FFS enrollment experienced 

the same risk score growth due to diagnostic coding differences as 

beneficiaries who were enrolled in Medicare FFS or MA the previous 

year. However, enrollees who are new to the Medicare program tend to 

be healthier than other beneficiaries and may have less contact with their 

health plan physicians and less information in their medical records that 

plans could use to adjust risk scores. Therefore, for this report, we 

instead made the more conservative assumption that beneficiaries new to 

Medicare and enrolled in MA did not have risk score growth that could be 

affected by differences in coding practices between MA plans and 

Medicare FFS. Second, we adjusted both our lower and higher 

cumulative estimates to account for the effect of beneficiaries who died 

after June 30, 2010, or otherwise left MA since 2010. For our January 

2012 report, we did not make this adjustment. We determined this 

adjustment was needed for the current report after observing that the 

beneficiaries who left MA or died had, on average, a greater difference 

between their actual and estimated disease scores than those 

beneficiaries who remained in MA.

To calculate the cumulative impact of coding 

differences on 2010, 2011, and 2012 MA risk scores, we summed the 

impacts over the previous periods, weighted by the proportion of the MA 

population that could have experienced risk score growth due to coding 

differences during that period.

 

6

We included the impact of diagnostic coding differences for 2005-2006 and 2006-2007 

on risk score growth in our trend line.
 

Page 5 GAO-13-206 Medicare Advantage Diagnostic Coding

To quantify the cumulative impact of both our and CMS’s estimates of 

coding differences on payments to MA plans, we estimated the risk score 

growth attributable to coding differences, as described above. We then 

used data on MA plan bids—plans’ proposed reimbursement rates for the 

average beneficiary—to calculate total risk-adjusted payments for each 

MA plan before and after applying a coding adjustment. Finally, we 

calculated the difference between the two payment amounts.

We analyzed data from CMS on Medicare beneficiaries, including data 

collected from Medicare providers and MA plans. We assessed the 

reliability of the CMS data we used by interviewing officials responsible 

for using these data to determine MA payments, reviewing relevant 

documentation, and examining the data for obvious errors. We 

determined that the data were sufficiently reliable for the purposes of our 

study. See appendix I for more details on our scope and methodology.

To describe changes, if any, CMS made to its coding adjustment 

methodology for 2013 and intends to make for future years, we reviewed 

CMS documents and interviewed CMS staff. In particular, we indentified 

the extent to which CMS planned to update its methodology to 

incorporate recent data, additional beneficiary characteristics, and 

account for trends in practice pattern disparities.

We conducted this performance audit from March 2012 through January

2013 in accordance with generally accepted government auditing 

standards. Those standards require that we plan and perform the audit to 

obtain sufficient, appropriate evidence to provide a reasonable basis for 

our findings and conclusions based on our audit objectives. We believe 

that the evidence obtained provides a reasonable basis for our findings 

and conclusions based on our audit objectives.

The Social Security Act requires that payments to MA plans be adjusted 

for variation in the cost of providing health care to beneficiaries on the 

basis of various risk factors, including health status.7

 

7

42 U.S.C. § 1395w-23(a)(1)(C)(i). 

For most MA 

beneficiaries, CMS uses its CMS-Hierarchical Condition Categories 

Background 
 

Page 6 GAO-13-206 Medicare Advantage Diagnostic Coding

(CMS-HCC) model to risk-adjust payments to MA plans.8 HCCs, which 

represent major medical conditions, are groups of medical diagnoses 

where related groups of diagnoses are ranked on the basis of disease 

severity and cost. The CMS-HCC risk adjustment model uses enrollment 

and claims data from Medicare FFS. The model uses beneficiary 

characteristic and diagnostic data from a base year to calculate the 

expected health care expenditures under Medicare FFS for the following 

year.9

The Social Security Act further directs CMS to ensure that adjustments to 

payments for health status reflect changes in treatment and coding 

practices in Medicare FFS and differences in coding patterns between 

MA plans and providers under Medicare Parts A and B to the extent 

differences are identified.

For example, CMS used MA beneficiary diagnostic and 

demographic data for 2009 to determine the risk scores used to adjust 

payments to MA plans in 2010.

10

 

8

We use the term CMS-HCC model to refer specifically to CMS’s community model. CMS 

published the details of its CMS-HCC risk adjustment model on March 28, 2003, and 

May 12, 2003. CMS-HCC model adjustments to MA payments were phased in from 2004 

to 2010. CMS uses the CMS-HCC model to risk-adjust payments for most MA 

beneficiaries; however, separate models are used for beneficiaries that were not enrolled 

in Medicare for all of the previous year, have end-stage renal disease, or resided in an 

institutional facility for at least 90 consecutive days. 

To ensure payment accuracy, the act requires 

CMS to conduct an annual analysis of these coding differences in time to 

incorporate the results into the risk scores for each year. In conducting 

such an analysis, CMS is required to use data submitted with respect to 

2004 and subsequent years as such data are available. CMS is required 

to continue adjusting risk scores for coding differences until the time it is 

able to implement risk adjustment using MA diagnostic, cost, and use 

data. Beginning with 2014, the diagnostic coding adjustments are subject 

to a statutory minimum, which was recently amended by the American 

9

The CMS-HCC model uses 1 calendar year of data to estimate each beneficiary’s 

expected Medicare expenditures for the following year. Expected Medicare expenditures 

for each beneficiary are divided by the average Medicare expenditures for all Medicare 

FFS beneficiaries to generate a risk score.

1042 U.S.C. § 1395w-23(a)(1)(C)(ii).The requirement to adjust risk scores for differences 

in diagnostic coding originated in the Deficit Reduction Act of 2005, which required 

adjustments in 2008, 2009, and 2010. Pub. L. No. 109-171, § 5301(b), 120 Stat. 4, 51 

(2006). The Health Care and Education Reconciliation Act of 2010 extended the 

requirement beyond 2010 and made other changes. Pub. L. No. 111-152, § 1102(e), 

124 Stat. 1029, 1046.
 

Page 7 GAO-13-206 Medicare Advantage Diagnostic Coding

Taxpayer Relief Act of 2012.

11 Specifically, the Social Security Act, as 

amended, requires CMS to reduce MA risk scores by at least 

1.5 percentage points more than the 2010 adjustment (a total of 

4.9 percent) for 2014 and increases the annual minimum percentage 

reduction to not less than 5.9 percent for 2019 and subsequent years.12

CMS did not adjust MA risk scores in 2008 or 2009, the first years for 

which a diagnostic coding adjustment was required under the Deficit 

Reduction Act of 2005.13 However, for 2010 CMS estimated that 

3.4 percent of MA beneficiary risk scores were attributable to differences 

in diagnostic coding over the previous 3 years and reduced MA 

beneficiaries’ 2010 risk scores by 3.4 percent. To calculate this 

percentage, CMS estimated the annual difference in disease score 

growth between MA and Medicare FFS beneficiaries for three different 

groups of beneficiaries who were either enrolled in the same MA plan or 

in Medicare FFS from 2004 to 2005, 2005 to 2006, and 2006 to 2007. 

CMS accounted for differences in age and mortality when estimating the 

difference in disease score growth between MA and Medicare FFS 

beneficiaries for each period. Then, CMS calculated the average of the 

three estimates.14

• CMS multiplied the average annual difference in risk score growth by 

its estimate of the average length of time that 2010 MA beneficiaries 

had been continuously enrolled in the same MA plans over the 

previous 3 years,

To apply this average estimate to 2010 MA 

beneficiaries,

15

 

11Pub. L. No. 112-240, § 639, 126 Stat. 2313 (2013).

and

1242 U.S.C. § 1395w-23(a)(1)(C)(ii)(III). 

13The Deficit Reduction Act required CMS to adjust risk scores for MA beneficiaries to 

take into account differences in treatment and diagnostic coding between MA plans and 

Medicare FFS to the extent that the impact of differences could be identified. For 2008 

and 2009, CMS stated that it was unable to definitively attribute differences in MA and 

FFS risk scores to underlying diagnostic coding differences and therefore did not adjust 

risk scores.

14The average was weighted by the number of beneficiaries enrolled in the same MA plan 

during each period.

15CMS used MA enrollment data for MA beneficiaries in 2009 and the previous 3 years to 

estimate the average length of time that 2010 MA beneficiaries had been continuously in 

their MA plan during the previous 3 years.
 

Page 8 GAO-13-206 Medicare Advantage Diagnostic Coding

• CMS multiplied this result by 81.8 percent, its estimate of the 

percentage of 2010 MA beneficiaries who were enrolled in an MA plan 

in 2009 and therefore were previously exposed to MA coding 

practices.16

CMS applied the same 3.4 percent adjustment to risk scores it used in 

2010 to risk scores in 2011 and 2012.

CMS’s risk score adjustment for diagnostic coding differences for 2010 

through 2012 was too low. Specifically, we estimated that the cumulative 

impact of coding differences on risk scores increased from 2010 through 

2012 and was greater than CMS’s risk score adjustment of 3.4 percent for 

each of the 3 years. In updating our analysis from the January 2012 

report, we estimated that cumulative risk scores in 2010 were 4.2 percent 

higher than they likely would have been if the same beneficiaries had 

been enrolled continuously in FFS.17 Using the methodology described 

earlier, we estimated that differences in diagnostic coding resulted in 

2011 risk scores that were 4.6 to 5.3 percent higher than they likely would 

have been if the same beneficiaries had been continuously enrolled in 

FFS. This upward trend continued for 2012, with estimated risk scores 

4.9 to 6.4 percent higher (see fig. 1).18

 

16CMS’s estimate of the percentage of 2010 MA beneficiaries whose risk scores reflected 

MA diagnostic coding was based on the percentage of 2009 MA beneficiaries who were 

also in MA plans in 2008.

17This estimate, based on more complete data, is less than our January 2012 estimate 

that the cumulative impact of coding differences on risk scores in 2010 would be between 

4.8 percent and 7.1 percent.

18As described in our methods section detailed in app. I, we made two enhancements to 

our methodology for projecting the cumulative impact of coding differences on risk scores 

that resulted in more conservative estimates for 2011 and 2012 than what our estimates 

would have been if we used the methodology from our January 2012 report. 

CMS’s Adjustment for 

Coding Differences 

for 2010 through 2012 

Was Too Low, 

Resulting in 

Estimated Excess 

Payments to MA Plans 

of at Least $3.2 Billion
 

Page 9 GAO-13-206 Medicare Advantage Diagnostic Coding

Figure 1: CMS and GAO Adjustments of Risk Scores to Account for Diagnostic 

Coding Differences, 2010 to 2012

Note: We estimated risk score adjustments for differences in diagnostic coding between MA plans 

and Medicare FFS for 2010, 2011, and 2012 by estimating the cumulative impact of coding 

differences starting with 2007 risk scores. We used two different assumptions of the effect of coding 

differences on risk score growth from 2010 to 2012. Our low estimate assumes that the percentage of 

risk score growth attributable to coding differences for 2010 to 2011 and 2011 to 2012 remains the 

same as it was from 2009 to 2010. Our high estimate assumes that the percentage of risk score 

growth attributable to coding differences for 2010 to 2011 and 2011 to 2012 continues the trend for 

our study population from 2005 to 2010. We adjusted our lower and higher cumulative estimates for 

2011 and 2012 to account for the effect of beneficiaries who died after June 30, 2010, or otherwise 

left MA since 2010. 

Because CMS’s adjustment to risk scores for 2010 through 2012 to 

account for diagnostic coding differences was too low, we estimated that 

MA plans received excess payments of between $3.2 billion and 

$5.1 billion over the 3-year period. CMS’s annual 3.4 percent reduction in 

risk scores is equivalent to reducing total payments to MA plans by an 

estimated $2.8 billion in 2010, $3.0 billion in 2011 and $3.2 billion in 2012. 

According to our estimates, the amount of the excess payments to MA 

plans after accounting for CMS’s adjustments was $0.6 billion in 2010, 
 

Page 10 GAO-13-206 Medicare Advantage Diagnostic Coding

$1.1 billion to $1.6 billion in 2011, and $1.5 billion to $2.9 billion in 2012. 

(See fig. 2.)19

Figure 2: Estimated Excess Payments to MA Plans after Accounting for CMS’s Risk 

Score Adjustments for Diagnostic Coding Differences, 2010-2012

Note: To quantify the impact of both our and CMS’s estimates of coding differences on payments to 

MA plans, we used data MA plans submitted to CMS to determine payments to MA plans. We 

calculated total risk-adjusted payments for each MA plan before and after applying a coding 

adjustment and calculated the difference between the two amounts. For our 2011 and 2012 coding 

adjustment estimates, we used two different assumptions of the effect of coding differences on risk 

scores from 2010 to 2012. Our low estimate assumes that the percentage of risk score growth 

attributable to coding differences for 2010 to 2011 and 2011 to 2012 remained the same as it was 

from 2009 to 2010. Our high estimate assumes that the percentage of risk score growth attributable 

to coding differences for 2010 to 2011 and 2011 to 2012 continues the trend for our study population 

from 2005 to 2010. We adjusted our lower and higher cumulative estimates for 2011 and 2012 to 

 

19Our estimate of $0.6 billion in excess payments to MA plans in 2010, after accounting 

for CMS’s reduction, was less than what we projected in our January 2012 report. In that 

report, we estimated the dollar impact for 2010, after accounting for CMS’s reduction, 

would be between $1.2 billion and $3.1 billion.
 

Page 11 GAO-13-206 Medicare Advantage Diagnostic Coding

account for the effect of beneficiaries who died after June 30, 2010, or otherwise left MA since 2010. 

CMS’s annual 3.4 percent reduction in risk scores is equivalent to $2.8 billion in 2010, $3.0 billion in 

2011, and $3.2 billion in 2012. Our updated estimate of the dollar impact in 2010 risk score growth 

due to coding differences over the previous 3 years was equivalent to $3.4 billion in payments to MA. 

For 2011, we estimated that risk score growth over the previous 4 years was equivalent to at least 

$4.1 billion and up to $4.6 billion in payments to MA plans. For 2012, we estimated that risk growth 

over the previous 5 years was equivalent to at least $4.7 billion and up to $6.1 billion in payments to 

MA plans.

According to CMS officials, the agency used the same methodology to 

determine the 2013 risk score adjustment as it used in 2011 and 2012, 

resulting in a risk score adjustment of 3.4 percent for 2013. CMS 

conducted a data-based analysis of coding differences for 2013 and 

considered the results, along with other factors, in determining the 

adjustment provided for in the Social Security Act. To conduct its databased analysis, CMS officials reported that they used the same 

methodology they used to calculate the 3.4 percent adjustment for 2010, 

but incorporated more recent data.20 In addition to the results of their 

data-based analysis, CMS officials told us that they took into account 

other factors when determining the 2013 risk score adjustment, such as 

payment changes made to the MA program under the Patient Protection 

and Affordable Care Act, the stability of the MA program, and the 

maintenance of benefits for seniors.21

The Social Security Act does not prescribe the methodology that CMS is 

to use in adjusting for differences in diagnostic coding and, in this regard, 

it provides the agency with discretion in designing and conducting its 

analysis of coding differences. However, the express purpose of the 

requirements to conduct and incorporate a data-based analysis of coding 

CMS’s risk score adjustment of 

3.4 percent for 2013 is the same that it used in 2010, 2011, and 2012.

 

20CMS used data through 2009 to calculate risk score growth due to coding differences for 

2013. In January 2012, we reported that CMS found the impact of coding differences 

increased from 2004 through 2008. The data-based analysis, as published in the 2010 

advance notice and 2010 rate announcement, produced a single-estimate of the 

adjustment needed to correct for coding differences. See CMS, “Advance Notice of 

Methodological Changes for Calendar Year 2010 for Medicare Advantage Capitation 

Rates and Part C and Part D Payment Policies” (Feb. 20, 2009), pp. 9-11, and CMS, 

“Announcement of Calendar Year 2010 Medicare Advantage Capitation Rates and 

Medicare Advantage and Part D Payment Policies” (Apr. 6, 2009), p.19.

21The Patient Protection and Affordable Care Act, as amended by the Health Care and 

Education Reconciliation Act of 2010, included provisions that affected MA plan payments, 

such as a transition to a payment system based on national county benchmarks and a 

requirement that at least 85 percent of revenues must go towards benefits.

CMS Did Not Change 

Its Risk Score 

Adjustment 

Methodology for 2013, 

but May Revisit It in 

Future Years
 

Page 12 GAO-13-206 Medicare Advantage Diagnostic Coding

differences into the risk scores is to ensure payment accuracy. The 

statute does not provide for factors other than the results of the analysis 

to be incorporated into the adjustment, suggesting that accuracy would be 

achieved through the incorporation of these analytical results by 

themselves. In response to our inquiries, CMS officials told us that they 

reviewed a range of options when determining an adjustment for 2013, 

but did not explain whether these options were derived from the agency’s 

data-based analysis. CMS officials did not identify the specific source of 

their authority to consider factors other than the required data-based 

analysis when determining the adjustment amount, but stated that they 

believed that there was policy discretion with respect to the most 

appropriate adjustment factor for the payment year. While CMS did not 

change its risk score adjustment methodology for 2013, agency officials 

said they may revisit their methodology for future years. While diagnostic 

coding adjustments are subject to a statutory minimum beginning in 2014, 

CMS may implement a diagnostic coding adjustment that is greater than 

the statutory minimum if they determine the minimum is too low.

Risk adjustment is important to ensure that payments to MA plans 

adequately account for differences in beneficiaries’ health status and to 

maintain plans’ financial incentive to enroll and care for beneficiaries 

regardless of their health status. Our work confirms that differences in 

diagnostic coding caused risk scores for MA beneficiaries to be higher 

than those for comparable beneficiaries in Medicare FFS in 2010, 2011, 

and 2012. CMS’s decision to use a 3.4 percent adjustment to risk scores 

for 2010 through 2012 instead of the higher adjustments called for by our 

analysis resulted in excess payments to MA plans. The existence of such 

excess payments indicates that CMS’s adjustment does not accurately 

account for differences in treatment and diagnostic coding between MA 

plans and Medicare FFS—the stated goal of the statute that required 

CMS to develop a diagnostic coding adjustment. In our January 2012 

report, we recommended that CMS take steps to improve the accuracy of 

the adjustment to account for excess payments due to differences in 

diagnostic coding. We noted that CMS could, for example, account for 

additional beneficiary characteristics, include the most recent data 

available, identify and account for all the years of coding differences that 

could affect the payment year for which an adjustment is made, and 

incorporate the trend of the impact of coding differences on risk scores. 

CMS’s adjustment for 2013 is the same as it used in 2010, 2011, and 

2012. However, given our finding that this adjustment was too low and 

resulted in estimated excess payments to MA plans of at least 

$3.2 billion, we continue to believe that it is important for CMS to 

Concluding 

Observations 
 

Page 13 GAO-13-206 Medicare Advantage Diagnostic Coding

implement our recommendation that it update its methodology to more 

accurately account for differences in diagnostic coding.

We provided a draft of this report to CMS for comment. CMS did not have 

any general comments. The agency provided one technical comment, 

which we incorporated.

As agreed with your offices, unless you publicly announce the contents of 

this report earlier, we plan no further distribution until 30 days from the 

report date. At that time, we will send copies to the Secretary of Health 

and Human Services, interested congressional committees, and others. 

In addition, the report is available at no charge on the GAO website at 

http://www.gao.gov. 

If you or your staff has any questions about this report, please contact me 

at (202) 512-7114 or cosgrovej@gao.gov. Contact points for our Offices 

of Congressional Relations and Public Affairs may be found on the last 

page of this report. GAO staff who made major contributions to this report 

are listed in appendix II.

James Cosgrove

Director, Health Care

Agency Comments
Appendix I: Scope and Methodology

Page 14 GAO-13-206 Medicare Advantage Diagnostic Coding

This appendix describes the scope and methodology that we used to 

address our objective to determine the extent to which differences, if any, 

in diagnostic coding between Medicare Advantage (MA) plans and 

Medicare fee-for-service (FFS) affected risk scores and payments to MA 

plans in 2010, 2011, and 2012. This methodology includes enhancements 

from the methodology we used in our January 2012 report.

To determine the extent to which differences, if any, in diagnostic coding 

between MA plans and Medicare FFS affected MA risk scores in 2010, 

2011, and 2012, we compared actual risk score growth for beneficiaries in 

our MA study population with the estimated risk score growth these 

beneficiaries would have had if they had been enrolled in Medicare FFS. 

For our estimates, we assumed MA plans and Medicare FFS had 

equivalent coding patterns in 2006—the year of coding upon which 2007 

risk scores were based—and therefore calculated the cumulative effect of 

coding differences starting with risk score data from 2007. Because 2010 

risk score data were the most current data available at the time of our 

analysis, we projected the extent of coding differences in 2011 and 2012 

on the basis of trends from 2005 through 2010.1 To do these analyses, 

we used Centers for Medicare & Medicaid Services (CMS) enrollment 

and risk score data from 2004 through 2011. Risk scores for a given 

calendar year are generally based on beneficiaries’ diagnoses in the 

previous year, so we identified our study population on the basis of 

enrollment data for 2004 through 2009 and analyzed risk scores for that 

population for 2005 through 2010.2

Our MA study population consisted of a retrospective cohort of 2010 MA 

beneficiaries who were enrolled in MA for all of 2009 and either MA or 

FFS in 2008, and we followed them back for the length of their continuous 

enrollment to 2004.3

 

1

While our estimate of the cumulative impact of coding differences for 2010 is based on 

3 years of coding differences, we included an additional 2 years of coding differences, 

going back to 2005, to identify a trend used to project estimates to 2011 and 2012.

Beneficiaries remained in our cohort for as many 

2

Medical diagnoses are not used to calculate risk scores for beneficiaries who were not 

enrolled in Medicare for all of the previous year.

3

We included MA beneficiaries who were enrolled in health maintenance organization, 

preferred provider organization, and private fee-for-service plans as well as plans offered 

by provider-sponsored organizations.

Appendix I: Scope and Methodology

Estimating the Impact 

of Coding Differences 

on MA Risk Scores
Appendix I: Scope and Methodology

Page 15 GAO-13-206 Medicare Advantage Diagnostic Coding

years as they were continuously enrolled in MA, plus (if applicable) the 

year of Medicare FFS enrollment immediately preceding their MA 

enrollment.4

To estimate the risk score growth MA beneficiaries would have 

experienced in prior periods if they had been enrolled in Medicare FFS, 

we developed regression models based on a control population of FFS 

beneficiaries. Specifically, we followed the same method as described 

above to develop a retrospective cohort of 2010 FFS beneficiaries. For 

each of 5 prior periods (2005 to 2006, 2006 to 2007, 2007 to 2008, 2008 

to 2009, and 2009 to 2010), we used this FFS retrospective cohort to 

estimate a regression model that described the relationship in Medicare 

FFS between a beneficiary’s characteristics and growth in the 

beneficiary’s disease score—the portion of a beneficiary’s risk score that 

is based on a beneficiary’s coded diagnoses. In the regression model we 

used change in disease score (year 2 - year 1) as our dependent variable 

and included age, sex, hierarchical condition categories (HCC), HCC 

interaction variables, Medicaid status, and whether the original reason for 

Medicare entitlement was disability as independent variables because 

they are specified in the CMS-HCC model.5 We also included one urban 

and one rural variable for each of the 50 United States; Washington, D.C.; 

and Puerto Rico as independent variables to identify beneficiary 

residential location.6

 

4

By including 1 year of baseline FFS data in our study period for MA beneficiaries who 

had been enrolled in FFS prior to joining an MA plan, we were able to analyze the impact 

of coding differences for MA beneficiaries during their first year in an MA plan. We 

excluded data for years during which a beneficiary (1) was diagnosed with end-stage renal 

disease; (2) resided in a long-term care facility for more than 90 consecutive days; (3) died 

prior to July 1, 2010; or (4) moved to a new state or changed urban/rural status.

Then we used these regression models and data on 

beneficiary characteristics for our MA study population to estimate the 

5

We calculated disease scores using the 2010 version of the CMS-HCC risk adjustment 

community model (used for payment in 2010), and summed the appropriate coefficients 

for each of the HCC variables. We normalized disease scores for each year to 2005 by 

using the FFS normalization factor that CMS used to normalize risk scores in 2010. 

Normalization keeps the average Medicare FFS risk score constant at 1.0 over time and is 

necessary to compare disease scores across years.

6

Beneficiary residential location is a proxy for other factors that vary with geography and 

that may affect the frequency with which beneficiaries interact with health care providers 

and therefore the completeness with which providers code diagnoses, such as physician 

practice patterns. We did not include rural variables for Washington, D.C.; New Jersey; 

and Rhode Island because these locations are entirely urban.
Appendix I: Scope and Methodology

Page 16 GAO-13-206 Medicare Advantage Diagnostic Coding

change in disease scores that would have occurred if those MA 

beneficiaries had been continuously enrolled in FFS.7

We then compared these estimates of disease score growth under FFS to 

the MA beneficiaries’ actual disease score growth and, because the 

regression model accounted for other relevant factors affecting disease 

score growth, we identified the difference as attributable to coding 

differences between MA and FFS. To calculate the cumulative impact of 

coding differences on 2010 MA risk scores, we summed the 2007 to 

2008, 2008 to 2009, and 2009 to 2010 impact estimates for our 

retrospective MA cohort, weighting each impact estimate by the 

percentage of 2010 MA beneficiaries that could have experienced risk 

score growth due to coding differences during that period. To convert the 

cumulative impact of coding differences on 2010 MA risk scores into a 

percentage, we divided by the average MA risk score in 2010. To 

calculate the cumulative impact of coding differences on 2011 and 2012 

MA risk scores, we used a similar methodology, except that we had to 

estimate the risk score growth due to coding differences for 2010 to 2011 

and 2011 to 2012.8

To estimate the risk score growth due to coding differences for 2010 to 

2011 and 2011 to 2012, we used the estimates based on our 2010 

retrospective cohorts for five time periods—2005 to 2006, 2006 to 2007, 

2007 to 2008, 2008 to 2009, and 2009 to 2010—and made two different 

projection assumptions. One projection, which we used to calculate our 

high cumulative impact estimate, assumed that the trend over 2005 to 

2010 continued through 2012.9

 

7

Our analysis also accounted for mortality by requiring all beneficiaries in our study 

populations to be alive through June 30, 2010.

 We also provided a more conservative 

estimate that assumed the annual growth trend in coding differences from 

8

In addition, because CMS would not have enrollment data after January 2010 when 

publishing its 2011 adjustment and after January 2011 when publishing its 2012 

adjustment, we used data from prior years to estimate the percentage of 2011 and 2012 

MA beneficiaries that could have experienced risk score growth due to coding differences 

during each period. 

9

For this projection, we fit a logarithmic trend line to 2005-2006, 2006-2007, 2007-2008, 

2008-2009, and 2009-2010 impact estimates and used the resulting expression to 

extrapolate impact estimates to 2010-2011 and 2011-2012. We used the following 

coordinates (annual impact, period) for all MA beneficiaries to estimate the model: 

(-0.0091, 1), (0.0177, 2), (0.0203, 3), (0.0227, 4), and (0.0229, 5).
Appendix I: Scope and Methodology

Page 17 GAO-13-206 Medicare Advantage Diagnostic Coding

2010 to 2012 stabilized at the same level as 2009-2010. We provided this 

lower estimate to account for the possibility that the growth rate will flatten 

as MA plans improve their systems for comprehensively coding 

diagnoses.

Our updated methodology includes two major enhancements to the 

methodology used for our January 2012 report. First, we altered our 

methodology to make a more conservative assumption of the risk score 

growth due to coding differences for beneficiaries that recently enrolled in 

MA without any prior Medicare FFS enrollment. These beneficiaries are 

new to the Medicare program and tend to be healthier than other 

beneficiaries. Therefore, they may have less contact with their health plan 

physicians and less information in their medical records that plans could 

use to adjust risk scores. As a result, for MA beneficiaries that had a risk 

score based on MA coding for the second year of the period but did not 

have a risk score based on either MA or FFS coding for the first year of 

the period, we altered our methodology to assume that these 

beneficiaries had zero risk score growth due to coding differences during 

the period.10

Second, we adjusted our cumulative impact estimates for 2011 and 2012 

to account for the effect of beneficiaries who died after June 30, 2010, or 

otherwise left MA since 2010. We determined an adjustment was needed 

after observing that the impacts of coding differences for the time periods 

2005-2006, 2006-2007, and 2007-2008 were smaller for the 2010 

retrospective cohort used for this study than for the 2008 retrospective 

cohort used for our January 2012 report. We attributed these differences 

to beneficiaries who were in our 2008 cohort but not our 2010 cohort as 

having, on average, greater differences between their actual and 

estimated disease scores than those beneficiaries who remained in MA. It 

is possible this is due to sicker beneficiaries with greater coding 

differences relative to Medicare FFS leaving the study cohort as they 

aged, either because of death or to rejoin Medicare FFS. We expect that 

For the January 2012 report, we had assumed that these 

beneficiaries experienced the same risk score growth due to coding 

differences, on average, as did those beneficiaries for which we could 

measure risk score growth due to coding differences.

 

10For both our January 2012 report and this report, we excluded new enrollees from our 

analysis as they had only one risk score and it was not based on their diagnoses. Thus, 

new enrollees did not have the opportunity to experience risk score growth due to coding 

differences.
Appendix I: Scope and Methodology

Page 18 GAO-13-206 Medicare Advantage Diagnostic Coding

beneficiaries who leave MA or die after 2010 would have a similar effect 

on our 2011 and 2012 projections. To address this, we adjusted our 

estimates of the impact of coding differences on the basis of the 

magnitude of differences in the impact of coding differences for our 2008 

and 2010 retrospective cohorts during each period.11 We applied these 

adjustments relative to the projection year (i.e., half of the differences 

between the 2008 and 2010 cohorts for periods 2005-2010 were applied 

to 2006-2011 for our 2011 projection and the full difference between the 

cohorts was applied to 2007-2012 for our 2012 projection).

To quantify the impact of both our and CMS’s estimates of coding 

differences on payments to MA plans in 2010, 2011, and 2012, we used 

data on MA plan bids—plans’ proposed reimbursement rates for the 

average beneficiary—which are used to determine payments to MA plans 

and information on MA plan enrollment. We analyzed monthly MA 

enrollment for 2010 and 2011, and because enrollment data for 2012 was 

incomplete, we used the annual trend for these 2 years in conjunction 

with actual enrollment for the first 9 months of 2012 to estimate total 2012 

MA enrollment. We used these data to calculate total risk-adjusted 

payments for each MA plan before and after applying a coding 

adjustment, and then used the differences between these payment levels 

to estimate the percentage reduction in total projected payments to MA 

plans resulting from adjustments for coding differences in 2010, 2011, 

and 2012.12

 

11We calculated the difference in annual impacts between the 2008 and 2010 cohorts for 

2005-2006, 2006-2007, and 2007-2008 and then projected the linear trend of those 

differences forward to 2008-2009 and 2009-2010.

Then we applied the percentage reduction in payments 

associated with each adjustment to the estimated total payments to MA 

plans—$114.8 billion in 2010, $122.9 billion in 2011, and $133.5 billion in 

2012—and accounted for reduced Medicare Part B premium payments 

12We assumed that MA plans did not adjust their bids in 2010, 2011, and 2012 as a result 

of the adjustment for coding differences.

Estimating the Impact 

on Payments to MA 

Plans in 2010, 2011, 

and 2012
Appendix I: Scope and Methodology

Page 19 GAO-13-206 Medicare Advantage Diagnostic Coding

received by CMS, which offset the reduction in MA payments (see 

table 1).13

Table 1: Impact of Adjustments for Coding Differences on Total Payments to MA 

Plans in 2010, 2011, and 2012

Reduction in MA payments

Adjustment applied to reduce 

MA risk scores (source) Percentage Dollars (in billions)

2010

3.4 percent (CMS) 2.4% $2.8

4.2 percent (GAO) 3.0 3.4

2011

3.4 percent (CMS) 2.4 3.0

4.6 percent (GAO) 3.3 a 4.1

5.3 percent (GAO) 3.8 b 4.6

2012

3.4 percent (CMS) 2.4 3.2

4.9 percent (GAO) 3.5 a 4.7

6.4 percent (GAO) 4.6 b 6.1

Source: GAO analysis of Medicare data.

Notes: We analyzed a retrospective cohort of beneficiaries from 2005 to 2010 to estimate the impact 

of coding differences on MA risk scores and used two different assumptions of the effect of coding 

differences on risk scores from 2010 to 2012. The percentage reduction in 2010, 2011, and 2012 MA 

payments is less than the adjustment applied to 2010, 2011, and 2012 MA risk scores because the 

impact of the adjustment to risk scores is reduced by additional payments some MA plans are eligible 

to receive.

a

GAO low estimate assumes the annual impacts from 2010 to 2012 are the same as the impact from 

2009 to 2010, after adjusting our estimate to account for beneficiaries who left MA or died between 

July 1, 2010, and 2011 for our 2011 estimate or between July 1, 2010, and 2012 for our 2012 

estimate.

b

 

13We estimated $114.8 billion to be the total payments to MA plans without adjustments 

CMS made in 2010 for budget neutrality and for coding differences. Each estimate in 

table 1 does not incorporate the impact of CMS’s 2010, 2011, or 2012 adjustment. All 

estimates of the dollar impact of the adjustment for coding differences account for offset 

due to reduced Medicare Part B premiums received by Medicare—11.92 percent in 2010, 

11.91 percent in 2011 and 11.93 percent in 2012. Additionally, estimates do not include 

Medicare savings for a small number of beneficiaries with end-stage renal disease whose 

risk scores were adjusted for coding differences.

GAO high estimate assumes the annual impacts from 2010 to 2012 continue the trend of increasing 

annual impacts from 2005 to 2010 after adjusting our estimate to account for beneficiaries who left 

MA or died between July 1, 2010 and 2011 for our 2011 estimate or between July 1, 2010 and 2012 

for our 2012 estimate.
Appendix I: Scope and Methodology

Page 20 GAO-13-206 Medicare Advantage Diagnostic Coding

We analyzed data from CMS on Medicare beneficiaries, including data 

collected from Medicare providers and MA plans. We assessed the 

reliability of the CMS data we used by interviewing officials responsible 

for using these data to determine MA payments, reviewing relevant 

documentation, and examining the data for obvious errors. We 

determined that the data were sufficiently reliable for the purposes of our 

study.
Appendix II: GAO Contact and Staff 

Acknowledgments

Page 21 GAO-13-206 Medicare Advantage Diagnostic Coding

James Cosgrove, (202) 512-7114 or cosgrovej@gao.gov

In addition to the contact named above, Christine Brudevold, Assistant 

Director; Alison Binkowski; William A. Crafton; Gregory Giusto; 

Andrew Johnson; Richard Lipinski; Elizabeth Morrison; and 

Jennifer Whitworth made key contributions to this report.

Appendix II: GAO Contact and Staff 

Acknowledgments 

GAO Contact

Staff 

Acknowledgments 

(291027)
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