Medicare Payment
CMS Methodology Adequate to Estimate National Error Rate Gao ID: GAO-06-300 March 24, 2006The Centers for Medicare & Medicaid Services (CMS) estimated that the Medicare program paid approximately $20 billion (net) in error for fee-for-service (FFS) claims in fiscal year 2004. CMS established two programs--the Comprehensive Error Rate Testing (CERT) Program and the Hospital Payment Monitoring Program (HPMP)--to measure the accuracy of claims paid. The Medicare Prescription Drug, Improvement, and Modernization Act of 2003 directed GAO to study the adequacy of the methodology that CMS used to estimate the Medicare FFS claims paid in error. GAO reviewed the extent to which CMS's methodology for estimating the fiscal year 2004 error rates was adequate by contractor type for (1) the CERT Program, (2) the HPMP, and (3) the combined national error rate (including both the CERT Program and the HPMP). GAO reviewed relevant CMS documents and reports related to the CERT Program and the HPMP. In addition, GAO reviewed work performed by the Department of Health and Human Services (HHS) Office of Inspector General (OIG) and its contractor that evaluated CMS's fiscal year 2004 statistical methods and other aspects of the error rate estimation process. GAO also conducted interviews with officials from CMS, HHS's OIG, and their contractors.
The methodology used by CMS for the CERT Program was adequate to estimate the fiscal year 2004 error rates by contractor type--carrier, durable medical equipment regional carrier (DMERC), and fiscal intermediary (FI). Carriers pay claims submitted by physicians, diagnostic laboratories and facilities, and ambulance service providers. DMERCs pay claims submitted by durable medical equipment suppliers. FIs pay claims submitted by hospitals, home health agencies, hospital outpatient departments, skilled nursing facilities, and hospices. The methodology was adequate because CMS used a large sample--about 120,000 claims--and an appropriate sample selection strategy. For these fiscal year 2004 error rate estimates, CMS made improvements in the collection of medical records that supported the sampled claims. These medical records were appropriately reviewed to determine whether there were errors in payment. CMS used valid statistical methods to estimate the fiscal year 2004 error rates for the carrier, DMERC, and FI contractor types. The methodology used by CMS for the HPMP was adequate to estimate the fiscal year 2004 error rate by quality improvement organizations (QIO), which are responsible for ascertaining the accuracy of coding and payment of Medicare FFS paid claims for acute care inpatient hospital stays. CMS's sampling methods were adequate because the agency used a large sample, approximately 40,000 claims, that was representative of the population from which it was drawn in terms of average dollar amount per claim. Also, the HPMP had adequate processes in place to ensure appropriate determinations of error. CMS used valid statistical methods to estimate the fiscal year 2004 error rate for the QIO contractor type. The fiscal year 2004 contractor-type error rate estimates for the CERT Program and the HPMP were appropriately combined to determine the national Medicare error rate through the use of a valid statistical method. CMS estimated the national Medicare error rate by averaging the carrier, DMERC, and FI contractor-type error rates in the CERT Program and the QIO contractor-type error rate in the HPMP, weighted by each contractor type's share of total Medicare FFS payments. In written comments, HHS noted that GAO found CMS's methodology adequate for estimating the fiscal year 2004 national Medicare FFS error rate. HHS also noted that CMS is continually committed to refining the processes to estimate, as well as lower, the level of improper payments in the Medicare FFS program.
GAO-06-300, Medicare Payment: CMS Methodology Adequate to Estimate National Error Rate
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Report to Congressional Committees:
United States Government Accountability Office:
GAO:
March 2006:
Medicare Payment:
CMS Methodology Adequate to Estimate National Error Rate:
GAO-06-300:
GAO Highlights:
Highlights of GAO-06-300, a report to congressional committees:
Why GAO Did This Study:
The Centers for Medicare & Medicaid Services (CMS) estimated that the
Medicare program paid approximately $20 billion (net) in error for fee-
for-service (FFS) claims in fiscal year 2004. CMS established two
programs”the Comprehensive Error Rate Testing (CERT) Program and the
Hospital Payment Monitoring Program (HPMP)”to measure the accuracy of
claims paid.
The Medicare Prescription Drug, Improvement, and Modernization Act of
2003 directed GAO to study the adequacy of the methodology that CMS
used to estimate the Medicare FFS claims paid in error. GAO reviewed
the extent to which CMS‘s methodology for estimating the fiscal year
2004 error rates was adequate by contractor type for (1) the CERT
Program, (2) the HPMP, and (3) the combined national error rate
(including both the CERT Program and the HPMP).
GAO reviewed relevant CMS documents and reports related to the CERT
Program and the HPMP. In addition, GAO reviewed work performed by the
Department of Health and Human Services (HHS) Office of Inspector
General (OIG) and its contractor that evaluated CMS‘s fiscal year 2004
statistical methods and other aspects of the error rate estimation
process. GAO also conducted interviews with officials from CMS, HHS‘s
OIG, and their contractors.
What GAO Found:
The methodology used by CMS for the CERT Program was adequate to
estimate the fiscal year 2004 error rates by contractor type”carrier,
durable medical equipment regional carrier (DMERC), and fiscal
intermediary (FI). Carriers pay claims submitted by physicians,
diagnostic laboratories and facilities, and ambulance service
providers. DMERCs pay claims submitted by durable medical equipment
suppliers. FIs pay claims submitted by hospitals, home health agencies,
hospital outpatient departments, skilled nursing facilities, and
hospices. The methodology was adequate because CMS used a large
sample”about 120,000 claims”and an appropriate sample selection
strategy. For these fiscal year 2004 error rate estimates, CMS made
improvements in the collection of medical records that supported the
sampled claims. These medical records were appropriately reviewed to
determine whether there were errors in payment. CMS used valid
statistical methods to estimate the fiscal year 2004 error rates for
the carrier, DMERC, and FI contractor types.
The methodology used by CMS for the HPMP was adequate to estimate the
fiscal year 2004 error rate by quality improvement organizations (QIO),
which are responsible for ascertaining the accuracy of coding and
payment of Medicare FFS paid claims for acute care inpatient hospital
stays. CMS‘s sampling methods were adequate because the agency used a
large sample, approximately 40,000 claims, that was representative of
the population from which it was drawn in terms of average dollar
amount per claim. Also, the HPMP had adequate processes in place to
ensure appropriate determinations of error. CMS used valid statistical
methods to estimate the fiscal year 2004 error rate for the QIO
contractor type.
The fiscal year 2004 contractor-type error rate estimates for the CERT
Program and the HPMP were appropriately combined to determine the
national Medicare error rate through the use of a valid statistical
method. CMS estimated the national Medicare error rate by averaging the
carrier, DMERC, and FI contractor-type error rates in the CERT Program
and the QIO contractor-type error rate in the HPMP, weighted by each
contractor type‘s share of total Medicare FFS payments.
In written comments, HHS noted that GAO found CMS‘s methodology
adequate for estimating the fiscal year 2004 national Medicare FFS
error rate. HHS also noted that CMS is continually committed to
refining the processes to estimate, as well as lower, the level of
improper payments in the Medicare FFS program.
Medicare Net FFS Error Rates and Dollars of Claims Paid in Error,
Fiscal Year 2004:
[See Table 1]
www.gao.gov/cgi-bin/getrpt?GAO-06-300.
To view the full product, including the scope and methodology, click on
the link above. For more information, contact A. Bruce Steinwald at
(202) 512-7101 or steinwalda@gao.gov.
[End of section]
Contents:
Letter:
Results in Brief:
Background:
CMS Methodology Adequate for Estimating the Error Rates in the CERT
Program:
CMS Methodology Adequate for Estimating the Error Rate in the HPMP:
CMS Methodology Adequate for Estimating the National Error Rate:
Concluding Observations:
Agency Comments:
Appendix I: Scope and Methodology:
Appendix II: Fiscal Year 2004 Error Rate Information by Contractor Type-
-Carriers, DMERCs, FIs, and QIOs:
Appendix III: Comments from the Department of Health and Human
Services:
Appendix IV: GAO Contact and Staff Acknowledgments:
Tables:
Table 1: Medicare FFS Error Rates and Dollars of Claims Paid in Error,
Fiscal Year 2004:
Table 2: National Medicare FFS Error Rate by Category of Error, Fiscal
Year 2004:
Figures:
Figure 1: Medicare FFS Error Rates Estimated through the CERT Program:
Figure 2: Medicare FFS Error Rates Estimated through the HPMP:
Figure 3: Medicare FFS Error Rates That Produce the National Error
Rate:
Abbreviations:
CDAC: Clinical Data Abstraction Center:
CERT: Comprehensive Error Rate Testing:
CMS: Centers for Medicare & Medicaid Services:
DMERC: durable medical equipment regional carrier:
DRG: diagnosis-related group:
FFS: fee-for-service:
FI: fiscal intermediary:
GPRA: Government Performance and Results Act of 1993:
HHS: Department of Health and Human Services:
HPMP: Hospital Payment Monitoring Program:
IPIA: Improper Payments Information Act:
MAC: Medicare administrative contractor:
OIG: Office of Inspector General:
OMB: Office of Management and Budget:
PPS: prospective payment system:
QIO: quality improvement organization:
United States Government Accountability Office:
Washington, DC 20548:
March 24, 2006:
The Honorable Charles E. Grassley:
Chairman:
The Honorable Max Baucus:
Ranking Minority Member:
Committee on Finance:
United States Senate:
The Honorable Joe L. Barton:
Chairman:
The Honorable John D. Dingell:
Ranking Minority Member:
Committee on Energy and Commerce:
House of Representatives:
The Honorable William M. Thomas:
Chairman:
The Honorable Charles B. Rangel:
Ranking Minority Member:
Committee on Ways and Means:
House of Representatives:
The Centers for Medicare & Medicaid Services (CMS), the agency that
administers the Medicare program, monitors the accuracy of claims paid
for services provided to Medicare beneficiaries. Each fiscal year, CMS
reports an estimate of the claims paid in error based on a sample of
claims from previous years. In fiscal year 2004, CMS reported an error
rate of 9.3 percent, which represented approximately $20 billion in
error out of the approximately $214 billion in fee-for-service (FFS)
payments.[Footnote 1] The fiscal year 2004 error rate estimated the
percentage of FFS payments that did not comply with Medicare's payment
rules for a sample of claims that included inpatient discharges that
occurred from July 1, 2002, through June 30, 2003, as well other
services that were paid in 2003. The fiscal year 2004 Medicare FFS
error rate was significantly higher than the goal of 4.8 percent for
that fiscal year, which CMS set under the Government Performance and
Results Act of 1993 (GPRA).[Footnote 2]
CMS uses several types of contractors to ensure the payment accuracy of
Medicare claims,[Footnote 3] including carriers,[Footnote 4] durable
medical equipment regional carriers (DMERC),[Footnote 5] fiscal
intermediaries (FI),[Footnote 6] and quality improvement organizations
(QIO).[Footnote 7] Using contractor-specific error rate information,
CMS estimates an error rate for each type of contractor; the agency
produces a national Medicare error rate by aggregating the four
contractor-type error rates. In its fiscal year 2004 Medicare error
rate report, CMS stated that it planned to use error rate information
to help determine the underlying reasons for claim errors, such as
incorrect coding, and implement corrective actions.[Footnote 8] In a
congressional testimony in July 2005, the Director of CMS's Office of
Financial Management stated that CMS plans to create performance
incentives for contractors.[Footnote 9] CMS is also implementing a
multiyear contractor reform initiative, which will reduce the number of
contractors responsible for paying claims.
To monitor the accuracy of Medicare FFS claims paid by contractors, CMS
established two programs--the Comprehensive Error Rate Testing (CERT)
Program and the Hospital Payment Monitoring Program (HPMP).[Footnote
10] Through the CERT Program, CMS monitors payment decisions made by
three types of contractors--carriers, DMERCs, and FIs. It does this
through a review of the claims and submitted medical record
documentation to ensure that there is support for the payment based on
the information reviewed for a sample of paid claims. CMS uses a
similar process for the HPMP for a sample of claims that are reviewed
by QIOs for accuracy of payment.
The Department of Health and Human Services (HHS) Office of Inspector
General (OIG)[Footnote 11] estimated the error rate for each fiscal
year from 1996 through 2002. CMS made significant changes to the
methodology, including substantially increasing the size of the sample
used to estimate the error rate, when it assumed responsibility for
estimating the Medicare error rate in fiscal year 2003. CMS has
continued to make changes to the methodology in subsequent years.
The Medicare Prescription Drug, Improvement, and Modernization Act of
2003 requires that we study the adequacy of the methodology that CMS
used to estimate Medicare error rates and to make recommendations as
deemed appropriate.[Footnote 12] Specifically, we report on the extent
to which the methodology used by CMS to estimate the fiscal year 2004
Medicare error rates was adequate (1) by contractor type (carrier,
DMERC, and FI) for the CERT Program, (2) by contractor type (QIO) for
the HPMP, and (3) for the combined national error rate (including the
CERT Program and the HPMP).
To conduct our analysis of the adequacy of the methodology that CMS
used to estimate fiscal year 2004 Medicare error rates, we reviewed
relevant documents, including CMS's Medicare error rate reports for
fiscal years 2003 and 2004, CERT and HPMP program documentation, and
HHS OIG reports evaluating the fiscal year 2004 CERT Program and
HPMP.[Footnote 13] In addition, we reviewed work performed by an OIG
contractor that evaluated CMS's statistical sampling and estimation
methodology for the fiscal year 2004 Medicare error rate, including the
contractor's report and supporting workpapers. We interviewed OIG
officials; OIG contractor staff; CMS officials; and staff of the CERT
subcontractor responsible for calculating the error rates for carriers,
DMERCs, and FIs and the national error rate for fiscal year 2004.
Commenting on the adequacy of the methodology used in any other years
was beyond the scope of our work. However, it is important to note that
changes in the methodology may affect the estimation of the error rates
and thus the comparability of these rates over time.
As part of our assessment of the adequacy of the methodology that CMS
used to estimate the Medicare error rates for fiscal year 2004, we
reviewed the reliability of these estimates by examining the precision
of the contractor-specific error rates, the contractor-type error
rates, and the national error rate. Precision is the amount of
variation between an estimate (such as the error rate for a sample of
Medicare FFS paid claims) and the result that would be obtained from
measuring the entire population (such as the error rate for all
Medicare FFS paid claims). We examined precision of the error rate
estimates by assessing relative precision, which is the standard
error[Footnote 14] of the error rate estimate divided by the estimate
itself. Estimates with lower relative precision are more reliable. For
the purposes of this report, we established that a relative precision
of no greater than 15 percent was within the acceptable statistical
standard for precision.[Footnote 15] We chose relative precision
because it allows for better comparison of the reliability of the range
of error rates across contractors.[Footnote 16]
During the course of our work, CMS published a report in November 2005
that included its fiscal year 2005 error rates.[Footnote 17] While an
evaluation of the methodology used to estimate the fiscal year 2005
error rates was outside the scope of our work, we reviewed the report
and included references in this report where appropriate.
For more information on our scope and methodology, see appendix I. We
performed our work from April 2005 through March 2006 in accordance
with generally accepted government auditing standards.
Results in Brief:
We found that the methodology used by CMS for the CERT Program was
adequate to estimate the fiscal year 2004 error rates by contractor
type (carrier, DMERC, and FI). CMS's sample of 120,000 claims was
sufficiently large to reliably estimate the error rate and was
appropriately selected. Further, CMS used systematic sampling with a
random start, a method that is designed to ensure that the sample is
representative of the population. CMS also had appropriate procedures
in place to collect medical records from providers, such as physicians,
durable medical equipment suppliers, and hospital outpatient
departments, which supported the paid claims. Additionally, the
processes used by CMS to identify and categorize payment errors were
adequate because they ensured that the reviews conducted of the medical
records supporting the paid claims were performed according to the
established procedures for the CERT Program. This included adequate
qualifications and training of those individuals conducting the medical
record reviews. Further, CMS used valid statistical methods to estimate
the fiscal year 2004 carrier, DMERC, and FI contractor-type error rates
and standard errors.
We found also that the methodology used by CMS for the HPMP to
calculate the fiscal year 2004 contractor-type error rate for QIOs was
adequate to reliably measure claims paid in error. We found the
sampling methods to be adequate because CMS's sample of approximately
40,000 claims was sufficiently large to estimate the QIO contractor-
type error rate. It was also representative of the population from
which it was drawn in terms of average dollar amount per claim. Based
on our review of oversight work of the HPMP conducted by OIG, we also
found that the process used in the HPMP to collect the medical records
that support the claims selected for review was adequate. Additionally,
the processes CMS used to identify and categorize payment errors were
adequate because they ensured that the reviews conducted of the medical
records supporting the paid claims were performed according to
established procedures for the HPMP. This included adequate
qualifications and training of those individuals conducting the medical
record reviews. CMS also used valid statistical methods to estimate the
QIO contractor-type error rate and standard error.
The fiscal year 2004 error rates by contractor type (carrier, DMERC,
FI, and QIO) were appropriately aggregated to determine the national
Medicare error rate through the use of a valid statistical method. CMS
estimated the national Medicare error rate by averaging the error rates
of the four contractor types (carrier, DMERC, FI, and QIO), weighted by
each contractor type's proportion of total Medicare FFS payments.
In written comments on a draft of this report, HHS noted that we found
the CMS methodology adequate for estimating the fiscal year 2004
national Medicare FFS error rate. HHS also noted that CMS is
continually committed to refining the processes to estimate, as well as
lower, the level of improper payments in the Medicare FFS program.
Background:
In fiscal year 2003, CMS assumed responsibility for estimating the
national Medicare error rate, a responsibility that had previously been
held by HHS OIG. OIG began estimating the national Medicare error rate
in fiscal year 1996,[Footnote 18] and continued doing so for each
subsequent fiscal year through 2002. The transfer of responsibilities
for estimating the national Medicare error rate to CMS coincided with
the implementation of the Improper Payments Information Act of 2002
(IPIA). The IPIA requires federal agencies to estimate and report
annually on the extent of erroneous payments in their programs and
activities.[Footnote 19] The IPIA defines an improper payment as any
payment that should not have been made or that was made in an incorrect
amount, including both under-and overpayments. All agencies that
identify a program as susceptible to significant improper payments,
defined by guidance from the Office of Management and Budget (OMB) in
2003 as exceeding both 2.5 percent of total program payments and $10
million,[Footnote 20] are required to annually report to Congress and
the President an estimate of improper payments and report on corrective
actions.
In addition to estimating the national Medicare error rate for purposes
of compliance with the IPIA, CMS also began producing contractor-
specific error rate estimates beginning in fiscal year 2003 to identify
the underlying causes of errors and to adjust action plans for
carriers, DMERCs, FIs, and QIOs. To produce these contractor-specific
error rate estimates for fiscal year 2004, CMS sampled approximately
160,000 claims. The contractor-specific error rate information was then
aggregated by the four contractor types (carrier, DMERC, FI, and QIO),
which were ultimately combined to estimate the national Medicare error
rate. Under the methodology previously used by OIG to estimate the
national Medicare error rate, 6,000 claims were sampled. While the
sample size used by OIG was sufficient to estimate the national
Medicare error rate, it was not sufficient to reliably estimate the
contractor-specific error rates. Additionally, the increased sample
size improved precision of the national Medicare error rate estimate.
CMS Programs to Monitor the Payment Accuracy of Medicare FFS Claims:
The objective of the CERT Program and the HPMP is to measure the degree
to which CMS, through its contractors, is accurately paying claims.
Through the CERT Program, CMS monitors the accuracy of Medicare FFS
claims that are paid by carriers, DMERCs, and FIs. In fiscal year 2004,
the Medicare error rates by contractor type as estimated through the
CERT Program were 10.7 percent for the carrier contractor type, 11.1
percent for the DMERC contractor type, and 15.8 percent for the FI
contractor type. (See table 1.)
Table 1: Medicare FFS Error Rates and Dollars of Claims Paid in Error,
Fiscal Year 2004:
CMS program: CERT Program;
Contractor type: Carrier;
Error rate (percentage): 10.7;
Dollars paid in error (in billions): $6.5.
Contractor type: DMERC;
Error rate (percentage): 11.1;
Dollars paid in error (in billions): $1.0.
Contractor type: FI;
Error rate (percentage): 15.8;
Dollars paid in error (in billions): $9.3.
CMS program: HPMP;
Contractor type: QIO;
Error rate (percentage): 3.6;
Dollars paid in error (in billions): $3.1.
CMS program: National Medicare FFS error rate;
Contractor type: All contractor types;
Error rate (percentage): 9.3;
Dollars paid in error (in billions): $19.9.
Source: CMS.
Notes: This table reflects net Medicare FFS error rates and dollars of
claims paid in error. Based on data provided in CMS's fiscal year 2005
error rate report, we calculated the net Medicare FFS error rates and
net dollars paid in error for fiscal year 2005 by contractor type as
follows: carriers--6.0 percent and $4.1 billion; DMERCs--8.6 percent
and $0.8 billion; FIs--3.2 percent and $2.0 billion; and QIOs-
-3.8 percent and $3.5 billion. The national Medicare FFS error rate and
dollars paid in error were 4.4 percent and $10.3 billion. See
Department of Health and Human Services, Centers for Medicare &
Medicaid Services, Improper Medicare FFS Payments Long Report (Web
Version) for November 2005. 2005.
https://www.cms.hhs.gov/apps/er_report/preview_er_report.asp?from=public
&which=long&reportID=3(downloaded Jan. 26, 2006).
[End of table]
Through the HPMP, CMS monitors the accuracy of paid Medicare FFS claims
for acute care inpatient hospital stays--generally those that are
covered under the prospective payment system (PPS). For fiscal year
2004, the Medicare error rate for the QIO contractor type, as estimated
through the HPMP, was 3.6 percent. (See table 1.)
CERT Program:
To estimate contractor-specific Medicare FFS error rates for the CERT
Program, CMS reviews a sample of claims from each of the applicable
contractors, which included 25 carriers, 4 DMERCs, and 31 FIs for the
fiscal year 2004 error rates. These error rates are then aggregated by
contractor type. (See fig. 1.) For fiscal year 2004, CMS contracted
with AdvanceMed to administer the CERT Program. AdvanceMed sampled
approximately 120,000 claims submitted from January 1, 2003, through
December 31, 2003, to estimate the fiscal year 2004 contractor-specific
and contractor-type error rates for the CERT Program.
Figure 1: Medicare FFS Error Rates Estimated through the CERT Program:
[See PDF for image]
[End of figure]
For each of the approximately 120,000 sampled claims, AdvanceMed
requested the medical records from the provider that rendered the
service or from the contractor that processed the related claim, if the
contractor previously performed a medical review on the claim. If a
provider did not respond to the initial request for medical records
after 19 days, AdvanceMed initiated a series of follow-up procedures in
an attempt to obtain the information. The follow-up procedures with
nonresponding providers for fiscal year 2004 included three written
letters and three contacts by telephone. Additionally, in fiscal year
2004, OIG followed up directly with nonresponders on claims over a
certain dollar amount. If medical records were not received within 55
days of the initial request, the entire amount of the claim was
classified by AdvanceMed as an overpayment error.
When medical records were received from the provider or from the
contractor, CERT medical review staff reviewed the claim (which billed
for the services provided) and the supporting medical records (which
detailed the diagnosis and services provided) to assess whether the
claim followed Medicare's payment rules and national and local coverage
decisions.[Footnote 21] Claims that did not follow these rules were
classified by AdvanceMed as being in error. Providers whose claims were
reviewed were allowed to appeal these claims, and if the error
determination for a claim was overturned through the appeals process,
AdvanceMed adjusted the error rate accordingly. For the fiscal year
2004 error rate, AdvanceMed notified individual carriers, DMERCs, and
FIs of their respective payment errors.[Footnote 22]
HPMP:
For the HPMP, CMS analyzes a sample of claims across QIOs to estimate
Medicare error rates by state, because QIOs are organizations with
state-based service areas. CMS estimated the QIO contractor-type error
rate by aggregating the QIO error rate estimates for each of the 50
states, the District of Columbia, and Puerto Rico. (See fig. 2.)
Through the HPMP, CMS sampled approximately 40,000 claims for acute
care inpatient hospital discharges that occurred from July 1, 2002,
through June 30, 2003, to estimate the fiscal year 2004 state-specific
and contractor-type error rates for QIOs.
Figure 2: Medicare FFS Error Rates Estimated through the HPMP:
[See PDF for image]
[End of figure]
For fiscal year 2004, CMS contracted with two organizations known as
Clinical Data Abstraction Centers (CDAC)--AdvanceMed and DynKePRO--
that were responsible for requesting medical records from providers for
each of the approximately 40,000 sampled claims. Each CDAC was
responsible for reviewing the sampled claims, which were assigned on
the basis of the geographic location where the discharge occurred. Upon
receipt of the medical records, CDAC admission necessity reviewers
screened the related claims for the appropriateness of the
hospitalization and, with the exception of claims from Maryland, coding
specialists independently recoded diagnosis-related groups (DRG) based
on the records submitted.[Footnote 23] Because Maryland does not use
DRG coding, nonphysician reviewers screened claims from Maryland to
determine whether the length of the acute care inpatient hospital stay
was appropriate.[Footnote 24],[Footnote 25] Claims that failed the
screening process, including those where the admission was determined
to be unnecessary or where an inappropriate DRG code was used, were
forwarded to the QIO responsible for the state where the discharge
occurred for further review. Records not received by the CDACs within
30 days of the request for information were "canceled" and referred to
the QIO to be processed as overpayment errors caused by nonresponse.
The QIO referred these claims to the FI responsible for paying the
claim for the necessary payment adjustments.
At the QIO, claims forwarded from the CDACs underwent further review,
primarily medical necessity admission reviews and DRG validations.
Determinations of error were made by QIO physician reviewers. Providers
whose claims were reviewed were given the opportunity to provide
comments or discuss the case and pursue additional review, which could
result in an appeal to an administrative law judge. After the matter
was resolved, resulting in a determination that a provider was either
underpaid or overpaid, the QIO forwarded the claim to the FI for
payment adjustment.
Estimation of the National Medicare FFS Error Rate:
CMS estimated the national Medicare FFS error rate by combining the
three contractor-type error rates (carrier, DMERC, and FI) from the
CERT Program and the one contractor-type error rate (QIO) from the
HPMP. (See fig. 3.)
Figure 3: Medicare FFS Error Rates That Produce the National Error
Rate:
[See PDF for image]
[End of figure]
Medicare FFS claims that were paid in error as identified by the CERT
Program and the HPMP for the fiscal year 2004 error rates were sorted
into one of five categories of error:
* Insufficient documentation: Provider did not submit sufficient
documentation to support that the services billed were actually
provided.
* Nonresponse: Provider did not submit any documentation to support
that the services billed were actually provided.
* Medically unnecessary services: Provider submitted sufficient
documentation, but the services that were billed were deemed not
medically necessary or the setting or level of care was deemed
inappropriate.
* Incorrect coding: Provider submitted documentation that supported a
different billing code that was associated with a lower or higher
payment than that submitted for the services billed.
* Other: Provider submitted documentation, but the services billed did
not comply with Medicare's benefit or other billing requirements.
See table 2 for the national Medicare FFS error rate by category of
error for fiscal year 2004.
Table 4: National Medicare FFS Error Rate by Category of Error, Fiscal
Year 2004:
Category of error: Insufficient documentation;
Net errors as a percentage of total dollar amount sampled (fiscal year
2004): 4.1.
Category of error: Nonresponse;
Net errors as a percentage of total dollar amount sampled (fiscal year
2004): 2.8.
Category of error: Medically unnecessary;
Net errors as a percentage of total dollar amount sampled (fiscal year
2004): 1.6.
Category of error: Incorrect coding;
Net errors as a percentage of total dollar amount sampled (fiscal year
2004): 0.7.
Category of error: Other;
Net errors as a percentage of total dollar amount sampled (fiscal year
2004): 0.2.
Category of error: National Medicare FFS error rate;
Net errors as a percentage of total dollar amount sampled (fiscal year
2004): 9.3.
Source: CMS.
Notes: This table reflects net Medicare FFS error rates generated by
both the CERT Program and the HPMP. Numbers do not sum to total because
of rounding.
[End of table]
As reported in CMS's fiscal year 2004 Medicare error rate report, the
agency planned to use the error rates to help determine the underlying
reasons for claim errors, such as incorrect coding or nonresponse, and
implement corrective action plans for carriers, DMERCs, FIs, and
QIOs.[Footnote 26] Draft statements of work, dated February and April
2005, for carriers, DMERCs, and FIs set goals for contractors to
achieve a paid claims error rate of less than a certain percentage, to
be determined by CMS. According to the standards for minimum
performance on QIO statements of work that ended in 2005 for some QIOs
and 2006 for other QIOs,[Footnote 27] QIOs are evaluated on 12 tasks,
one of which is the HPMP. QIOs have to meet the performance criteria
standards on 10 tasks set forth by CMS to be eligible for a
noncompetitive contract renewal.
CMS's use of the error rates is being done in the context of the
agency's current effort to significantly reform its contracting efforts
for the payment of Medicare claims.[Footnote 28] By July 2009, CMS
plans to reduce the total number of contractors responsible for paying
Medicare claims to 23 total contractors, which the agency refers to as
Medicare administrative contractors (MAC). CMS also plans to institute
performance incentives in the new contracts, which will be based on a
number of different factors, including the Medicare error rates.
According to CMS's report to Congress on Medicare contracting reform,
CMS believes that the consolidation of Medicare contractors and the
integration of processing for Medicare claims[Footnote 29] will lead to
a reduced Medicare error rate.[Footnote 30]
CMS Methodology Adequate for Estimating the Error Rates in the CERT
Program:
The methodology used by CMS in the CERT Program to estimate error rates
by contractor type (carrier, DMERC, and FI) in fiscal year 2004 was
adequate. We found that the sample size and the use of systematic
sampling with a random start were adequate to reliably estimate the
Medicare error rates by contractor type. The CERT Program also had
adequate processes in place to collect medical records and to
accurately identify and categorize payment errors. The statistical
methods that CMS used to estimate the contractor-type error rates were
valid.
Sampling Methods:
The sample size that CMS used in the CERT Program, approximately
120,000 claims, was sufficiently large to produce reliable estimates of
the fiscal year 2004 Medicare error rates by contractor type (carrier,
DMERC, and FI). CMS selected 167 claims each month on a daily basis
from each of the 60 contractors, including 25 carriers, 4 DMERCs, and
31 FIs.[Footnote 31] This sample generated error rate estimates by
contractor type within acceptable statistical standards, such as
relative precision of no greater than 15 percent.[Footnote 32]
Specifically, the error rate for the carrier contractor type was 10.7
percent with a relative precision of 3.7 percent, the error rate for
the DMERC contractor type was 11.1 percent with a relative precision of
13.5 percent, and the error rate for the FI contractor type was 15.7
percent with a relative precision of 4.5 percent.
Further, we found that the sampling methods were adequate because CMS
used a systematic sample with a random start.[Footnote 33] Sampling
methods that employ a random start are designed to ensure that the
sample selected is representative of the population from which it is
drawn. We reviewed CERT Program documentation, which described the use
of a systematic sample with a random start. The OIG contractor reviewed
the computer program used for the CERT Program sample selection and
verified that the claims were selected according to the documentation.
CMS officials told us that the CERT Program conducts tests to compare
the sampled claims to the population of claims. For example, CMS
compared the percentage of claims sampled in each category of Medicare-
covered service to the percentage of claims in the population by
category of Medicare-covered service. CMS provided us with an example
of this test for one contractor's claims from January 2003 through June
2003.
While the relative precision of the fiscal year 2004 error rate
estimates by contractor type for the CERT Program was within acceptable
statistical standards of no greater than 15 percent, the relative
precision of half of the contractor-specific error rate estimates was
not. (See app. II for contractor-specific error rate information,
including the estimates and corresponding relative precision, for
carriers, DMERCs, and FIs.)
Thirty of the 60 contractor-specific error rates had relative precision
that were not within acceptable statistical standards.[Footnote 34]
Additionally, the relative precision of the contractor-specific error
rates showed wide variation within each contractor type. Relative
precision among carriers ranged from 8.9 percent to 17.0 percent; among
DMERCs, relative precision ranged from 12.3 percent to 20.7 percent;
and among FIs, relative precision ranged from 10.3 percent to 42.5
percent. As demonstrated by the range in relative precision among FIs,
for example, the error rate estimate for one FI was nearly four times
more reliable than the error rate estimate for another.
The variation in relative precision among the contractor-specific error
rate estimates was due, in part, to the sampling method CMS used for
the CERT Program. CMS took an equal sample size from each contractor
despite the fact that individual contractors accounted for varied
amounts of Medicare claim volumes and total payments. For example, the
claim volume for carriers in 2003 ranged from a minimum of 5.3 million
claims to a maximum of 206 million claims; total payments for carriers
in 2003 ranged from a minimum of $168 million to about $6.7 billion.
CMS officials told us that they plan to reallocate the CERT Program
sample at the contractor level by increasing the sample size for those
contractors that are not reaching CMS's targeted precision and by
decreasing the sample size for those contractors that are reaching
targeted precision and achieving low error rates. In September 2005,
CMS officials reported that this change to the methodology is expected
to be implemented for the fiscal year 2007 error rate estimation, which
will be based on claims processed in parts of 2006 and 2007. We support
CMS's planned changes to its sampling methodology. We believe that
reallocation of the sample as planned by CMS will improve the relative
precision of these estimates. If future samples were based on the
volume of claims or total payments of each contractor and the relative
precision of the contractor-specific error rate rather than on the
current basis of an equal allocation across contractors, relative
precision would likely be improved for the contractor-specific error
rates of those targeted contractors that were allocated a larger
sample. This is because relative precision improves with increased
sample size. There would also likely be decreased variation in relative
precision across all contractor-specific error rates.[Footnote 35]
These results could be achieved without increasing the overall sample
size for the CERT Program.
Medical Record Collection Process:
Based on our review of oversight work conducted by OIG, we found that
the process CMS used to collect medical records from providers for the
CERT Program was adequate. Staff of AdvanceMed, the CMS contractor
responsible for administering the CERT Program, were responsible for
requesting medical records for each of the approximately 120,000
sampled claims used to estimate the fiscal year 2004 error rates.
According to an OIG review of CMS's corrective actions to improve
nonresponse in the CERT Program for fiscal year 2004, AdvanceMed
conducted a timely and systematic follow-up with providers that did not
respond to initial requests for medical records.[Footnote 36] For the
medical records collection process for the fiscal year 2004 error
rates, CMS implemented corrective actions in the CERT Program to
address the factors associated with the high rate of nonresponse
experienced during the medical records collection process for the prior
fiscal year. According to the CMS fiscal year 2003 error rate report,
for example, the agency found that some nonresponse in fiscal year 2003
was due to providers' lack of familiarity with AdvanceMed.[Footnote 37]
In previous years when OIG had responsibility for estimating the
Medicare error rate, OIG requested medical records directly from
providers; providers were familiar with OIG and understood the
importance of complying with the requests. However, when the
responsibility for estimating the Medicare error rate was transferred
to CMS, many providers were unfamiliar with AdvanceMed and may have
been reluctant to submit medical records to an unknown company. Another
factor that caused provider nonresponse in fiscal year 2003, according
to the CMS report, was providers' confusion about the submission of
medical records within the constraints of the privacy regulations
issued by HHS under the Health Insurance Portability and Accountability
Act of 1996,[Footnote 38] which limit the use and release of
individually identifiable health information. According to the CMS
report, CMS found that providers were sometimes unaware that sending
medical records to the CERT Program contractor was permissible under
the regulations. As reported in the OIG review cited previously, CMS
implemented corrective actions that increased provider compliance with
medical record requests in fiscal year 2004. According to the OIG
report, CMS conducted educational efforts to clarify the role of
AdvanceMed. Additionally, OIG further reported that CMS took action to
address providers' concerns about compliance with the privacy
regulations by revising its request letters to providers to highlight
AdvanceMed's authorization, acting on CMS's behalf, to obtain medical
records as requested. OIG told us that CMS instructed carriers, DMERCs,
and FIs to refer certain claims for nonresponding providers to OIG for
follow-up.[Footnote 39]
These improvements in the process used to collect medical records in
the CERT Program helped reduce nonresponse. According to information
provided to us by CMS, the percentage of error caused by nonresponse in
the CERT Program decreased from 61 percent for fiscal year 2003 to 34
percent in fiscal year 2004.[Footnote 40] According to CMS's fiscal
year 2005 error rate report, the agency continued several corrective
actions to address nonresponse for sampled claims for the fiscal year
2005 error rates.[Footnote 41] Further, beginning with claims sampled
to estimate the fiscal year 2006 Medicare error rates, CMS transferred
the medical record collection duties to a second contractor, Lifecare
Management Partners, which the agency refers to as the CERT Program
documentation contractor. CMS officials told us that the CERT Program
documentation contractor is automating the medical record collection
process and eliminating paper copies of documentation.
Identification and Categorization of Payment Errors:
Based on our review of OIG's fiscal year 2004 CERT Program evaluation,
we concluded that the processes used in the CERT Program to identify
and categorize payment errors for fiscal year 2004 were adequate
because the medical record reviews were performed appropriately and the
CERT Program staff conducting the reviews were adequately trained and
qualified.[Footnote 42] Staff of the CERT Program contractor,
AdvanceMed, reviewed the medical records to verify that claims were
processed according to Medicare payment rules; if not, a claim was
found to be in error and assigned to one of five categories of error
(insufficient documentation, nonresponse, medically unnecessary,
incorrect coding, or other). We reviewed work conducted by OIG that
found AdvanceMed, the CMS contractor responsible for administering the
CERT Program, had appropriate controls in place to ensure that the
medical record reviews were performed in accordance with established
CERT Program procedures. We also reviewed work by OIG, which examined
the educational and training requirements for medical record reviewers
as established in the CERT Program and assessed selected training files
for selected medical record reviewers. OIG officials told us that they
found these selected CERT Program medical record reviewers to be
adequately trained and qualified.
OIG found that AdvanceMed did not complete all required quality
assurance reviews within the designated time frame. CMS told OIG that
it planned to reduce AdvanceMed's workload. AdvanceMed conducts quality
assurance reviews on a sample of medically reviewed claims to validate
the initial reviewer's decision on whether a claim was paid in error.
OIG found that for the fiscal year 2004 CERT Program, AdvanceMed
completed 984 of the required 2,587 quality assurance reviews by the
required date. To determine whether these quality assurance reviews
ensured the reliability of the CERT Program claims review process, OIG
randomly sampled 45 of the 2,587 claims selected for quality assurance
reviews. Of these 45 claims, AdvanceMed had completed a quality
assurance review on 5 claims. OIG reported that the results of the 5
quality assurance reviews confirmed the results of the initial medical
record reviews. Further, OIG reported that AdvanceMed stated that a
backlog of medical reviews prevented the completion of the required
quality assurance reviews within the prescribed time frame. In response
to the OIG report on the fiscal year 2004 CERT Program evaluation, CMS
commented that with Lifecare Management Partners assuming
responsibilities for medical record collection for the fiscal year 2006
Medicare error rate estimation, AdvanceMed's workload would be reduced.
As a result, CMS commented that this will free up the necessary
resources for AdvanceMed to comply with the quality assurance
requirements. Further, in its response to the OIG report, CMS commented
that both AdvanceMed and Lifecare Management Partners are required to
report to the agency on the results of the quality assurance activities
conducted. According to OIG's evaluation of the fiscal year 2005 CERT
Program, OIG found that AdvanceMed completed all of the required
quality assurance reviews.[Footnote 43]
Statistical Methods:
We found that the statistical methods used to estimate the error rates
and standard errors by contractor type (carrier, DMERC, and FI) for the
CERT Program were adequate. Based on our review of the computer
programming code that generated the error rate estimates and standard
errors by the CERT Program subcontractor responsible for calculating
the contractor-type error rates, The Lewin Group, we found that the
statistical methods were based on standard statistical principles and
were used appropriately. For each contractor type, the stratified
combined ratio estimation method was used to calculate the error rate
by taking the difference between the overpaid dollars and the underpaid
dollars divided by the total dollars paid by Medicare for FFS claims of
each contractor type.[Footnote 44] The payment errors from the sample
were then extrapolated to the population for each contractor type to
estimate total payment errors. Further, The Lewin Group used a standard
statistical method to calculate the standard errors of each of the
contractor-type error rates.[Footnote 45] This method is appropriate
for obtaining the standard error of an estimate when the stratified
combined ratio estimation method is used and is valid for large sample
sizes, such as that used for the CERT Program.
CMS Methodology Adequate for Estimating the Error Rate in the HPMP:
We found that the methodology used by CMS was adequate to produce a
reliable estimate of the fiscal year 2004 Medicare error rate for the
one contractor type (QIO) in the HPMP. We found the methodology
adequate because the sample size was large enough to produce a reliable
error rate estimate. Additionally, the sample was representative of the
population. We found also that the methodology was adequate because the
HPMP contractors responsible for collecting the medical records for the
sampled claims, as well as for identifying and determining errors, had
appropriate controls in place to ensure that established procedures
were followed. Further, the statistical method that CMS used to
calculate the contractor-type error rate was valid.
Sampling Methods:
The sample size that CMS used for the HPMP, about 40,000 claims, was
sufficiently large to produce a reliable estimate of the fiscal year
2004 error rate for the QIO contractor type. Using a systematic sample,
CMS selected 62 discharge claims per month for the District of
Columbia, Puerto Rico, and each state except Alaska. CMS selected 42
claims per month for Alaska. The QIO contractor-type error rate was 3.6
percent with a relative precision of 5.6 percent. The relative
precision for the QIO contractor-type error rate estimate is within
acceptable statistical standards (a relative precision of no greater
than 15 percent).
For the QIO contractor-type error rate to be a reliable estimate, it
was necessary that the sample of discharge claims from which the error
rate was estimated be representative of the population from which it
was drawn. CMS's documentation stated that the HPMP used a systematic
sample selection process with a random start, which is a generally
accepted method of sampling that is designed to ensure that the sample
drawn is representative of the population. Our review of the computer
programming code that selected the sample, however, found that a random
start was not used.[Footnote 46] To determine whether the HPMP sample
was compromised by the lack of a random start and whether it
represented the population from which it was drawn, we examined the OIG
contractor's comparison of the June 2003 sample to a re-created version
of the June 2003 population file from which the sample was
drawn.[Footnote 47] Based on our review, we found that the HPMP sample
was representative of the population from which it was drawn in terms
of average dollar amount per claim.
While relative precision of the fiscal year 2004 QIO contractor-type
error rate estimate was within acceptable statistical standards,
relative precision of most of the state-specific QIO error rate
estimates was not. (See app. II for state-specific QIO error rate
information, including the error rate estimates and corresponding
relative precision.) Only three states' error rate estimates--Kentucky,
Massachusetts, and New Mexico--had relative precision of less than 15
percent. Additionally, there was wide variation in relative precision
of the state-specific QIO error rate estimates. Relative precision of
the state-specific QIO error rates ranged from 10.5 percent in
Massachusetts to 83.3 percent in Mississippi. The differences in
relative precision of these state-specific QIO error rate estimates
indicate that the error rate estimate for the QIO that served
Massachusetts was eight times more reliable than the error rate
estimate for the QIO that served Mississippi. The variation in relative
precision was due, in part, to the sampling methods used by CMS for the
HPMP. CMS took an equal sample size for each state except Alaska,
despite the fact that there was significant variation between states in
the overall volume of discharge claims and total payments. The number
of discharges per state varied from a low of 15,166 in Wyoming to a
high of 825,845 in Florida.[Footnote 48] Similarly, total dollars paid
for acute-care inpatient hospital stays varied from less than $100
million in Wyoming to a high of $7.5 billion in California.
Although in February 2006 a CMS official told us the agency has no
plans to reallocate the HPMP sample, CMS could adopt a similar sampling
strategy as it plans to do for the CERT Program. If future state
samples were based on the volume of discharge claims or total payments
per state and the relative precision of the state-specific QIO error
rates, rather than on the current basis of an equal allocation per
state, relative precision would likely be improved for the state-
specific QIO error rates in those states that were allocated a larger
sample since relative precision improves as sample size increases.
There would also likely be decreased variation in relative precision
across all state-specific QIO error rates.[Footnote 49] These results
could be achieved without increasing the overall sample size for the
HPMP.
In addition to issues with the wide variation of relative precision of
the state-specific QIO error rate estimates, we also found large
differences in the average dollar amount per claim between the state-
specific samples for some states and the respective state populations.
These differences suggest that the samples drawn for more than half of
the states were not representative of each state's population. Based on
our examination of the OIG contractor's comparison of the state samples
and the state populations for June 2003, we found that the ratio of the
average dollar amount per claim in a state's sample to the average
dollar amount per claim in a state's population varied from 62 percent
in Maryland to 143 percent in Kentucky. Twelve states had a ratio above
110 percent, and 16 states had a ratio below 90 percent.[Footnote 50]
It is still possible for the national HPMP sample to be representative
of the national HPMP population even if all of the state-specific
samples are not representative of their state populations. The larger
size of the HPMP sample overall mitigates the problems identified in
the smaller state-specific samples.
Medical Record Collection Process:
Based on our review of oversight work of the HPMP conducted by
OIG,[Footnote 51] we found that the process CMS used for collecting
medical records from providers was adequate. OIG selected 46 discharge
claims that were sampled for the HPMP to determine if the CDACs,
AdvanceMed and DynKePRO, followed established HPMP procedures for
obtaining and reviewing medical records to identify payment errors. OIG
found that the CDACs generally had appropriate controls in place to
ensure that the medical records were obtained and reviewed according to
established HPMP procedures. Of the 46 discharge claims reviewed, OIG
found that in two instances a required follow-up letter to the provider
was not sent due to an error by a substitute CDAC employee. However,
the medical records for these two discharge claims were obtained within
30 days of the original request, which resulted in no adverse effect on
the error rate estimates. Overall, nonresponse for fiscal year 2004
represented approximately 5.1 percent of the total QIO contractor-type
error rate of 3.6 percent, or 0.2 percent of all discharge claims
reviewed through the HPMP.
The issue with providers not responding to requests for medical records
was not as significant an issue for the HPMP as it was for the CERT
Program. According to the CMS report on the fiscal year 2005 error
rate, nonresponse was less problematic in the HPMP because of several
factors, including the following: (1) providers were more likely to
respond to requests from the HPMP since the average claim value was
higher than the average claim value in the CERT Program;[Footnote 52]
(2) providers were more familiar with the HPMP than with the CERT
Program; and (3) providers were paid the cost of providing medical
records by the HPMP, but not by the CERT Program.[Footnote 53]
Identification and Categorization of Payment Errors:
Based on our review of OIG's fiscal year 2004 HPMP evaluation,[Footnote
54] we concluded that the CDACs (AdvanceMed and DynKePRO) generally had
processes in place to adequately identify and categorize claims paid in
error in the HPMP for fiscal year 2004. OIG officials told us that they
found the medical record reviewers, both admission necessity reviewers
and DRG coding specialists, at the two CDACs met CMS's qualifications
for these positions.[Footnote 55] As part of its review of the fiscal
year 2004 HPMP, OIG reviewed 46 discharge claims that were part of the
sample for estimating the QIO contractor-type error rate. Based on that
review, OIG reported that the CDACs generally had appropriate controls
in place to ensure that admission necessity and DRG validation reviews
were performed in accordance with CMS established procedures and that
the results of those reviews were adequately maintained, updated, and
reported.
As part of the internal HPMP quality control process, two activities
were conducted regularly to ensure the reliability and accuracy of CDAC
reviews both within each CDAC and across the two CDACs. Each CDAC
randomly chose 30 claims per month to be reviewed by two of its medical
record reviewers for intra-CDAC tests. Each CDAC compared the results
of the two medical record reviews to determine the reliability of
reviews within the CDACs and reported the results of the comparisons to
CMS. The CDACs performed inter-CDAC tests to assess the reliability of
the reviews between the two CDACs. For these tests, an additional 30
claims were chosen at random per quarter by each of the CDACs for
review by a medical records reviewer at the other CDAC. As part of its
evaluation of the fiscal year 2004 HPMP, OIG selected 45 claims that
went through the intra-CDAC process and 42 claims that went through the
inter-CDAC process to determine if these quality control activities
ensured the reliability of the CDAC review process. OIG reported that
the quality control reviews were generally operating effectively to
ensure the reliability of the review process and the consistency of the
error rate determination decisions.[Footnote 56]
From the same evaluation of the fiscal year 2004 HPMP, OIG found that
the CMS contractor tasked with calculating the dollar amounts paid in
error, Texas Medical Foundation, used a method that produced an amount
of dollars in error that in some cases differed from what OIG found to
be the amount of dollars in error. For claims identified by a QIO as
having errors caused by changes in DRG codes, Texas Medical Foundation
used a method that produced different dollar amounts in error than
would have been produced if it had used the software that FIs used to
pay the original discharge claims.[Footnote 57] The Texas Medical
Foundation calculated a different amount in error for about 76 percent
of 200 incorrectly coded claims that OIG reviewed. However, OIG
reported that the differences did not have a significant effect on the
QIO contractor-type error rate estimate. A CMS official told us that
the agency has not invested in modifying the software for use by the
Texas Medical Foundation for technical and financial reasons. For
example, the software requires modifications using a specific
programming language for which CMS has limited personnel with the
needed expertise.
Statistical Methods:
We verified the statistical methods CMS used to estimate the QIO
contractor-type error rate and standard error in the HPMP by reviewing
the computer programming code that produced this information. We found
that the methods CMS used were adequate because they were based on
standard statistical methods and were applied appropriately. To
estimate the QIO contractor-type error rate, CMS weighted[Footnote 58]
each state-specific QIO error rate according to that state's share of
the total Medicare FFS payments for acute-care inpatient hospital
claims nationwide. This method is referred to as a stratified mean per
unit estimation.[Footnote 59] Like the CERT Program, CMS used a
standard statistical method to calculate the standard error of the
estimate.[Footnote 60] In our review of the computer programming code
that generated the QIO contractor-type error rate estimate, we found
that CMS used annual instead of monthly weights in its estimate of the
annual total dollars paid in error.[Footnote 61] It would have been
more appropriate for CMS to have used monthly weights because the HPMP
sample was drawn on a monthly, not an annual, basis. However, when we
reviewed the OIG contractor's comparison of the estimate of annual
dollars paid in error using annual weights to what the estimate would
have been had CMS used monthly weights, we concluded that the use of
annual weights did not significantly affect the QIO contractor-type
error rate estimate. A CMS official told us and provided us with
documentation that beginning with the HPMP's fiscal year 2005 error
rate estimation process, monthly weights are being used.
CMS Methodology Adequate for Estimating the National Error Rate:
CMS appropriately combined the error rates under the CERT Program and
the HPMP to estimate the fiscal year 2004 national Medicare error rate.
CMS estimated the national Medicare error rate by averaging the error
rates of the four contractor types (carrier, DMERC, FI, and QIO),
weighted by each contractor type's share of total Medicare FFS
payments. Likewise, CMS calculated the standard error, or precision, of
the national error rate based on the standard error of each of the four
types of contractors' error rate estimates, weighted by each contractor
type's proportion of total Medicare FFS payments. The methods CMS used
to calculate the national error rate and the standard error were
statistically valid, since the units of measurement, which in this case
were Medicare claims, of the four error rates that were combined were
mutually exclusive (independent) among contractor types.[Footnote 62]
Each contractor type consisted of multiple individual contractors.
These contractors were independent in that one contractor's estimated
error rate or standard error did not affect the estimates of other
contractors, since the claims in the population and in the sample were
not overlapping among contractors.
Concluding Observations:
Since assuming responsibility for estimating the national Medicare
error rate in fiscal year 2003, CMS has made changes to the
methodology, which have provided CMS with more detailed information
about the error, thereby allowing the agency to better identify the
underlying causes of error and implement corrective action plans to
address them. For example, CMS significantly increased the size of the
sample used to estimate the Medicare FFS claims paid in error. The
increased sample size allowed the agency to estimate not only the error
rate at the national level, but also more detailed error rates at the
contractor-type and contractor-specific levels. Further, CMS has made
changes in the way it collects medical records from providers in an
effort to reduce the rate of error caused by nonresponse and
insufficient documentation. These changes may affect the error rate
estimates and thus the comparability of the estimates over time.
Consequently, users of the error rate information should exercise
caution when making year-to-year comparisons.
Our work focused on the methodology CMS used to estimate the national
Medicare error rate and contractor-type error rates for fiscal year
2004. For these error rates, we found the methodology adequate for that
year. Under CMS's contracting reform initiative, there will be fewer
individual contractors (carriers, DMERCs, and FIs). If CMS maintains
the same overall sample size, the sample sizes of the remaining
individual contractors would be increased. Reliability of the
contractor-specific error rate estimates is likely to improve with the
larger sample sizes. Until then, the wide variation in reliability of
the contractor-specific error rate estimates may preclude meaningful
comparisons across individual contractors.
Agency Comments:
We received written comments from HHS (see app. III.) In responding to
our draft report, HHS noted that we found the CMS methodology adequate
for estimating the fiscal year 2004 national Medicare FFS error rate.
HHS also noted that CMS is continually committed to refining the
processes to estimate, as well as lower, the level of improper payments
in the Medicare FFS program.
In its comments, HHS noted improvement in the national Medicare error
rate from fiscal years 2004 to 2005. The department attributed the
decline in the error rate to marked improvement in the nonresponse
(which CMS now calls "no documentation") and the insufficient
documentation error rates. Commenting on the adequacy of the fiscal
year 2005 methodology was beyond the scope of our work; however, as we
noted in the draft report, changes in the methodology may affect the
estimation of the error rates and thus the comparability of these error
rates over time. For example, we discussed in the draft report that CMS
has made changes in the way it collects medical records from providers
in an effort to reduce the rate of error caused by nonresponse and
insufficient documentation. These changes primarily affected HHS's
processes for calculating an annual error rate estimate for the
Medicare FFS program. This may represent a refinement in the program's
estimation methodology rather than improved accountability over program
dollars.
The national Medicare error rates for fiscal years 2004 and 2005
provided by HHS in its comments are not comparable to the error rates
cited in this report for fiscal years 2004 and 2005. HHS provided gross
error rates, which were calculated using gross dollars paid in error.
Gross dollars paid in error were calculated by adding dollars paid in
error that were due to underpayments to those that were due to
overpayments. As noted in the draft report, we reported net error
rates. Net error rates were calculated using net dollars paid in error.
Net dollars paid in error were calculated by subtracting dollars paid
in error that were due to underpayments from those that were due to
overpayments.
HHS also provided technical comments, which we have addressed as
appropriate.
We are sending copies of this report to the Secretary of Health and
Human Services, the HHS Inspector General, the Administrator of CMS,
and appropriate congressional committees. We will also provide copies
to others upon request. In addition, the report is available at no
charge on the GAO Web site at http://www.gao.gov.
If you or your staff have any questions about this report, please
contact me at (202) 512-7101 or steinwalda@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 IV.
Signed by:
A. Bruce Steinwald:
Director, Health Care:
[End of section]
Appendix I: Scope and Methodology:
We reviewed the following components of the Centers for Medicare &
Medicaid Services's (CMS) methodology for estimating the fiscal year
2004 error rate:
* Sampling methods, including sample size, sample selection, sample
representation, and precision of the estimates.
* The medical records collection process.
* Identification and categorization of claims payment error, including
the medical record review process and quality assurance reviews.
* Statistical methods used to estimate the error rates and precision.
To conduct our analysis of CMS's sampling methods, we reviewed work
performed by the Department of Health and Human Services (HHS) Office
of Inspector General (OIG) contractor that assessed these methods and
CMS documentation for the fiscal year 2004 Medicare error rate. For the
Comprehensive Error Rate Testing (CERT) Program, we reviewed the
program manual, which described the CERT Program sampling methods as
well as CMS's Medicare error rate reports for fiscal years 2003 and
2004.[Footnote 63] For the Hospital Payment Monitoring Program (HPMP),
we reviewed the program manual and the HPMP computer programming code
that generated the sample to verify that the sample was taken in
accordance with the procedures outlined in the manual. Additionally, we
reviewed the OIG contractor's comparison of the June 2003 sample and a
re-created version of the June 2003 sampling frame, or population, for
the HPMP. It was not possible for the OIG contractor to obtain the
exact June 2003 population file because the file is continuously
updated and previous versions are not retained. We did not believe it
was necessary to compare every month's sample to the population from
which it was drawn because of the large size of the sample
(approximately 40,000 discharge claims) and population (approximately
11.5 million discharge claims), and the fact that the sample was drawn
in the same manner each month.
To conduct our analysis of CMS's medical record collection and review
processes and identification and categorization of payment errors, we
relied primarily on reports published by OIG. Since 2003, OIG has
conducted annual reviews of the CERT Program and the HPMP as part of
its review of work performed for HHS by contractors. These annual
reviews examine whether the CERT Program and HPMP contractors have
appropriate controls in place to ensure that the medical record reviews
and quality assurance reviews were performed in accordance with
established procedures. We reviewed OIG's annual reviews of the CERT
Program and the HPMP for fiscal year 2004.[Footnote 64] Our analysis of
provider nonresponse within the CERT Program relied on two OIG studies
of CMS's actions to reduce nonresponse implemented for the CERT Program
for fiscal year 2004.[Footnote 65] For the HPMP, we also reviewed four
intra-Clinical Data Abstraction Center (CDAC) reports and two inter-
CDAC reports, which were quality assurance reviews intended to assess
the consistency of review decisions both within and across CDACs.
To conduct our analysis of CMS's statistical methods, we reviewed the
OIG contractor's computer programming code, which replicated CMS's
estimation of the error rates for carriers, durable medical equipment
regional carriers (DMERC), and fiscal intermediaries (FI), as
calculated by the CERT Program subcontractor responsible for
statistical analysis of the error rates for fiscal year 2004. We
reviewed CMS's computer programming code, which calculated the HPMP
error rate for quality improvement organizations (QIO). In conducting
these reviews of the computer programming codes for both the CERT
Program and the HPMP, we verified that each code appropriately
implemented a methodology that employed standard statistical principles
and was used appropriately.
To inform all aspects of our study, we interviewed OIG officials with
oversight responsibility for the error rate estimation, OIG contractor
staff who conducted the evaluation of the statistical methodology, CMS
officials with programmatic responsibilities for the CERT Program and
the HPMP, and staff of the CERT Program subcontractor for statistical
analysis.
We performed our work from April 2005 through March 2006 in accordance
with generally accepted government auditing standards.
[End of section]
Appendix II: Fiscal Year 2004 Error Rate Information by Contractor Type-
-Carriers, DMERCs, FIs, and QIOs:
Contractor:
Contractor: Triple S, Inc. PR/VI;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $689,224,693;
CMS estimated paid claims error rate (percentage): 17.9%;
CMS estimated standard error[C] (percentage): 1.6%;
Relative precision[D](percentage): 8.9%.
Contractor: BCBS AR NM/OK/LA;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,293,083,008;
CMS estimated paid claims error rate (percentage): 12.7%;
CMS estimated standard error[C] (percentage): 1.2%;
Relative precision[D](percentage): 9.4%.
Contractor: NHIC CA;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $6,837,462,204;
CMS estimated paid claims error rate (percentage): 10.8%;
CMS estimated standard error[C] (percentage): 1.1%;
Relative precision[D](percentage): 10.2%.
Contractor: NHIC MA/ME/NH/VT;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $3,323,197,031;
CMS estimated paid claims error rate (percentage): 9.6%;
CMS estimated standard error[C] (percentage): 1.0%;
Relative precision[D](percentage): 10.4%.
Contractor: TrailBlazer TX;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $5,169,066,589;
CMS estimated paid claims error rate (percentage): 14.1%;
CMS estimated standard error[C] (percentage): 1.5%;
Relative precision[D](percentage): 10.6%.
Contractor: BCBS RI;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $232,458,933;
CMS estimated paid claims error rate (percentage): 13.5%;
CMS estimated standard error[C] (percentage): 1.5%;
Relative precision[D](percentage): 11.1%.
Contractor: GHI NY;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $372,383,958;
CMS estimated paid claims error rate (percentage): 14.3%;
CMS estimated standard error[C] (percentage): 1.6%;
Relative precision[D](percentage): 11.2%.
Contractor: Palmetto GBA OH/WV;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $4,226,979,481;
CMS estimated paid claims error rate (percentage): 10.6%;
CMS estimated standard error[C] (percentage): 1.2%;
Relative precision[D](percentage): 11.3%.
Contractor: First Coast Service Options FL;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $7,367,509,907;
CMS estimated paid claims error rate (percentage): 9.7%;
CMS estimated standard error[C] (percentage): 1.1%;
Relative precision[D](percentage): 11.3%.
Contractor: BCBS UT;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $287,713,078;
CMS estimated paid claims error rate (percentage): 10.2%;
CMS estimated standard error[C] (percentage): 1.2%;
Relative precision[D](percentage): 11.8%.
Contractor: First Coast Service Options CT;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,106,082,763;
CMS estimated paid claims error rate (percentage): 7.6%;
CMS estimated standard error[C] (percentage): 0.9%;
Relative precision[D](percentage): 11.8%.
Contractor: TrailBlazer MD/DC/DE/VA;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $4,158,091,772;
CMS estimated paid claims error rate (percentage): 9.2%;
CMS estimated standard error[C] (percentage): 1.1%;
Relative precision[D](percentage): 12.0%.
Contractor: BCBS AR AR/MO;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,292,786,396;
CMS estimated paid claims error rate (percentage): 10.6%;
CMS estimated standard error[C] (percentage): 1.4%;
Relative precision[D](percentage): 13.2%.
Contractor: HGSA PA;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $3,606,318,041;
CMS estimated paid claims error rate (percentage): 9.7%;
CMS estimated standard error[C] (percentage): 1.3%;
Relative precision[D](percentage): 13.4%.
Contractor: WPS WI/IL/MI/MN;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $8,126,245,486;
CMS estimated paid claims error rate (percentage): 11.1%;
CMS estimated standard error[C] (percentage): 1.6%;
Relative precision[D](percentage): 14.4%.
Contractor: Cahaba GBA AL/GA/MS;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $3,868,072,306;
CMS estimated paid claims error rate (percentage): 11.1%;
CMS estimated standard error[C] (percentage): 1.6%;
Relative precision[D](percentage): 14.4%.
Contractor: BCBS KS KS/NE/Kansas City;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,581,255,014;
CMS estimated paid claims error rate (percentage): 6.9%;
CMS estimated standard error[C] (percentage): 1.0%;
Relative precision[D](percentage): 14.5%.
Contractor: Palmetto SC;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,189,260,267;
CMS estimated paid claims error rate (percentage): 13.1%;
CMS estimated standard error[C] (percentage): 1.9%;
Relative precision[D](percentage): 14.5%.
Contractor: Noridian CO/ND/SD/WY/IA;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,865,892,800;
CMS estimated paid claims error rate (percentage): 9.5%;
CMS estimated standard error[C] (percentage): 1.4%;
Relative precision[D](percentage): 14.7%.
Contractor: Empire NY/NJ;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $7,268,107,083;
CMS estimated paid claims error rate (percentage): 10.8%;
CMS estimated standard error[C] (percentage): 1.6%;
Relative precision[D](percentage): 14.8%.
Contractor: Noridian AZ/HI/NV/AK/OR/WA;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $4,981,083,701;
CMS estimated paid claims error rate (percentage): 10.7%;
CMS estimated standard error[C] (percentage): 1.6%;
Relative precision[D](percentage): 15.0%.
Contractor: AdminaStar IN/KY;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,708,331,380;
CMS estimated paid claims error rate (percentage): 10.0%;
CMS estimated standard error[C] (percentage): 1.5%;
Relative precision[D](percentage): 15.0%.
Contractor: HealthNow NY;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,358,023,183;
CMS estimated paid claims error rate (percentage): 8.2%;
CMS estimated standard error[C] (percentage): 1.3%;
Relative precision[D](percentage): 15.9%.
Contractor: CIGNA ID/TN/NC;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $4,830,134,495;
CMS estimated paid claims error rate (percentage): 10.9%;
CMS estimated standard error[C] (percentage): 1.8%;
Relative precision[D](percentage): 16.5%.
Contractor: BCBS MT;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $193,432,019;
CMS estimated paid claims error rate (percentage): 5.3%;
CMS estimated standard error[C] (percentage): 0.9%;
Relative precision[D](percentage): 17.0%.
Contractor: All carriers;
CMS targeted sample size[A]: 50,100;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $79,932,195,591;
CMS estimated paid claims error rate (percentage): 10.7%;
CMS estimated standard error[C] (percentage): 0.4%;
Relative precision[D](percentage): 3.7%.
DMERC[F]:
DMERC[F]: TriCenturion Region A[G];
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,364,899,356;
CMS estimated paid claims error rate (percentage): 7.3%;
CMS estimated standard error[C] (percentage): 0.9%;
Relative precision[D](percentage): 12.3%.
DMERC[F]: AdminaStar Federal-Region B;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,241,150,409;
CMS estimated paid claims error rate (percentage): 6.6%;
CMS estimated standard error[C] (percentage): 0.9%;
Relative precision[D](percentage): 13.6%.
DMERC[F]: CIGNA-Region D;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,800,134,845;
CMS estimated paid claims error rate (percentage): 11.6%;
CMS estimated standard error[C] (percentage): 2.1%;
Relative precision[D](percentage): 18.1%.
DMERC[F]: Palmetto GBA Region C;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $4,928,003,571;
CMS estimated paid claims error rate (percentage): 14.0%;
CMS estimated standard error[C] (percentage): 2.9%;
Relative precision[D](percentage): 20.7%.
DMERC[F]: All DMERCs;
CMS targeted sample size[A]: 8,016;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $10,334,188,182;
CMS estimated paid claims error rate (percentage): 11.1%;
CMS estimated standard error[C] (percentage): 1.5%;
Relative precision[D](percentage): 13.5%.
FI[H]: UGS CA/HI/AS/GU/NMI;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $6,003,110,480;
CMS estimated paid claims error rate (percentage): 20.4%;
CMS estimated standard error[C] (percentage): 2.1%;
Relative precision[D](percentage): 10.3%.
FI[H]: Palmetto GBA SC;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $6,194,956,951;
CMS estimated paid claims error rate (percentage): 10.3%;
CMS estimated standard error[C] (percentage): 1.1%;
Relative precision[D](percentage): 10.7%.
FI[H]: Mutual of Omaha;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $11,797,457,474;
CMS estimated paid claims error rate (percentage): 26.8%;
CMS estimated standard error[C] (percentage): 3.2%;
Relative precision[D](percentage): 11.9%.
FI[H]: First Coast Service Options FL;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,472,517,626;
CMS estimated paid claims error rate (percentage): 23.0%;
CMS estimated standard error[C] (percentage): 2.9%;
Relative precision[D](percentage): 12.6%.
FI[H]: TrailBlazer TX/CO/NM;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $4,556,783,468;
CMS estimated paid claims error rate (percentage): 14.1%;
CMS estimated standard error[C] (percentage): 2.0%;
Relative precision[D](percentage): 14.2%.
FI[H]: Cahaba GBA AL;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $705,028,658;
CMS estimated paid claims error rate (percentage): 15.5%;
CMS estimated standard error[C] (percentage): 2.2%;
Relative precision[D](percentage): 14.2%.
FI[H]: Trispan MS/LA/MO;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,675,273,646;
CMS estimated paid claims error rate (percentage): 15.8%;
CMS estimated standard error[C] (percentage): 2.6%;
Relative precision[D](percentage): 16.5%.
FI[H]: BCBS RI;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $781,806,244;
CMS estimated paid claims error rate (percentage): 19.3%;
CMS estimated standard error[C] (percentage): 3.2%;
Relative precision[D](percentage): 16.6%.
FI[H]: Empire NY/CT/DE;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $5,811,286,709;
CMS estimated paid claims error rate (percentage): 17.2%;
CMS estimated standard error[C] (percentage): 2.9%;
Relative precision[D](percentage): 16.9%.
FI[H]: UGS VA/WV;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,449,840,434;
CMS estimated paid claims error rate (percentage): 16.6%;
CMS estimated standard error[C] (percentage): 2.8%;
Relative precision[D](percentage): 16.9%.
FI[H]: COSVI PR/VI;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $158,822,429;
CMS estimated paid claims error rate (percentage): 11.9%;
CMS estimated standard error[C] (percentage): 2.1%;
Relative precision[D](percentage): 17.6%.
FI[H]: Medicare Northwest OR/ID/UT;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $711,126,486;
CMS estimated paid claims error rate (percentage): 14.6%;
CMS estimated standard error[C] (percentage): 2.6%;
Relative precision[D](percentage): 17.8%.
FI[H]: Palmetto GBA NC;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $3,190,067,317;
CMS estimated paid claims error rate (percentage): 16.7%;
CMS estimated standard error[C] (percentage): 3.0%;
Relative precision[D](percentage): 18.0%.
FI[H]: Veritus PA;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,079,132,007;
CMS estimated paid claims error rate (percentage): 14.7%;
CMS estimated standard error[C] (percentage): 2.7%;
Relative precision[D](percentage): 18.4%.
FI[H]: UGS MI/WI;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $4,952,538,415;
CMS estimated paid claims error rate (percentage): 13.5%;
CMS estimated standard error[C] (percentage): 2.5%;
Relative precision[D](percentage): 18.5%.
FI[H]: Anthem NH/VT;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $641,811,111;
CMS estimated paid claims error rate (percentage): 9.0%;
CMS estimated standard error[C] (percentage): 1.7%;
Relative precision[D](percentage): 18.9%.
FI[H]: BCBS WY;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $83,003,027;
CMS estimated paid claims error rate (percentage): 14.7%;
CMS estimated standard error[C] (percentage): 2.8%;
Relative precision[D](percentage): 19.0%.
FI[H]: BCBS AZ;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $325,070,959;
CMS estimated paid claims error rate (percentage): 7.3%;
CMS estimated standard error[C] (percentage): 1.4%;
Relative precision[D](percentage): 19.2%.
FI[H]: CareFirst MD/DC;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,159,553,514;
CMS estimated paid claims error rate (percentage): 25.3%;
CMS estimated standard error[C] (percentage): 4.9%;
Relative precision[D](percentage): 19.4%.
FI[H]: Cahaba GBA IA;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $4,273,518,964;
CMS estimated paid claims error rate (percentage): 5.6%;
CMS estimated standard error[C] (percentage): 1.1%;
Relative precision[D](percentage): 19.6%.
FI[H]: Noridian MN/ND;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,309,949,370;
CMS estimated paid claims error rate (percentage): 16.2%;
CMS estimated standard error[C] (percentage): 3.3%;
Relative precision[D](percentage): 20.4%.
FI[H]: BCBS AR;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $481,442,284;
CMS estimated paid claims error rate (percentage): 26.1%;
CMS estimated standard error[C] (percentage): 5.5%;
Relative precision[D](percentage): 21.1%.
FI[H]: BCBS NE;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $299,081,984;
CMS estimated paid claims error rate (percentage): 12.8%;
CMS estimated standard error[C] (percentage): 2.7%;
Relative precision[D](percentage): 21.1%.
FI[H]: Anthem MA/ME;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,852,313,346;
CMS estimated paid claims error rate (percentage): 10.4%;
CMS estimated standard error[C] (percentage): 2.2%;
Relative precision[D](percentage): 21.2%.
FI[H]: BCBS GA;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,105,558,870;
CMS estimated paid claims error rate (percentage): 6.9%;
CMS estimated standard error[C] (percentage): 1.5%;
Relative precision[D](percentage): 21.7%.
FI[H]: BCBS KS;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $512,584,700;
CMS estimated paid claims error rate (percentage): 10.0%;
CMS estimated standard error[C] (percentage): 2.2%;
Relative precision[D](percentage): 22.0%.
FI[H]: AdminaStar IN/IL/KY/OH;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $9,610,571,631;
CMS estimated paid claims error rate (percentage): 12.2%;
CMS estimated standard error[C] (percentage): 2.7%;
Relative precision[D](percentage): 22.1%.
FI[H]: BCBS MT;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $229,695,544;
CMS estimated paid claims error rate (percentage): 6.8%;
CMS estimated standard error[C] (percentage): 1.7%;
Relative precision[D](percentage): 25.0%.
FI[H]: BCBS OK;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,109,256,221;
CMS estimated paid claims error rate (percentage): 8.6%;
CMS estimated standard error[C] (percentage): 2.2%;
Relative precision[D](percentage): 25.6%.
FI[H]: Riverbend TN/NJ;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $3,622,031,691;
CMS estimated paid claims error rate (percentage): 9.7%;
CMS estimated standard error[C] (percentage): 3.0%;
Relative precision[D](percentage): 30.9%.
FI[H]: Premera WA/AK;
CMS targeted sample size[A]: 2,004;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,004,968,329;
CMS estimated paid claims error rate (percentage): 7.3%;
CMS estimated standard error[C] (percentage): 3.1%;
Relative precision[D](percentage): 42.5%.
FI[H]: All FIs;
CMS targeted sample size[A]: 62,124;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $83,160,159,889;
CMS estimated paid claims error rate (percentage): 15.7%;
CMS estimated standard error[C] (percentage): 0.7%;
Relative precision[D](percentage): 4.5%.
QIO by state[I]: Massachusetts;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,135,744,081;
CMS estimated paid claims error rate (percentage): 8.6%;
CMS estimated standard error[C] (percentage): 0.90%;
Relative precision[D](percentage): 10.5%.
QIO by state[I]: Kentucky;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,482,350,516;
CMS estimated paid claims error rate (percentage): 9.3%;
CMS estimated standard error[C] (percentage): 1.10%;
Relative precision[D](percentage): 11.8%.
QIO by state[I]: New Mexico;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $324,592,033;
CMS estimated paid claims error rate (percentage): 6.1%;
CMS estimated standard error[C] (percentage): 0.90%;
Relative precision[D](percentage): 14.8%.
QIO by state[I]: Maine;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $417,801,848;
CMS estimated paid claims error rate (percentage): 4.6%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 15.2%.
QIO by state[I]: Louisiana;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,388,303,707;
CMS estimated paid claims error rate (percentage): 5.8%;
CMS estimated standard error[C] (percentage): 0.90%;
Relative precision[D](percentage): 15.5%.
QIO by state[I]: Arkansas;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $851,144,822;
CMS estimated paid claims error rate (percentage): 4.5%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 15.6%.
QIO by state[I]: Illinois;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $3,864,432,432;
CMS estimated paid claims error rate (percentage): 4.4%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 15.9%.
QIO by state[I]: Delaware;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $271,799,810;
CMS estimated paid claims error rate (percentage): 4.2%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 16.7%.
QIO by state[I]: Maryland;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,067,187,033;
CMS estimated paid claims error rate (percentage): 3.0%;
CMS estimated standard error[C] (percentage): 0.50%;
Relative precision[D](percentage): 16.7%.
QIO by state[I]: Iowa;
CMS targeted sample size[A]: 744; Total Medicare fee- for-service
payments in fiscal year 2004[B[(IN DOLLARS)] rs): 812,196,278;
CMS estimated paid claims error rate (percentage): 3.6%;
CMS estimated standard error[C] (percentage): 0.60%;
Relative precision[D](percentage): 16.7%.
QIO by state[I]: Indiana;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,784,654,000;
CMS estimated paid claims error rate (percentage): 4.1%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 17.1%.
QIO by state[I]: Nevada;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $402,837,978;
CMS estimated paid claims error rate (percentage): 4.6%;
CMS estimated standard error[C] (percentage): 0.80%;
Relative precision[D](percentage): 17.4%.
QIO by state[I]: New Hampshire;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $328,223,324;
CMS estimated paid claims error rate (percentage): 3.4%;
CMS estimated standard error[C] (percentage): 0.60%;
Relative precision[D](percentage): 17.6%.
QIO by state[I]: Florida;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $5,696,783,961;
CMS estimated paid claims error rate (percentage): 5.1%;
CMS estimated standard error[C] (percentage): 0.90%;
Relative precision[D](percentage): 17.6%.
QIO by state[I]: Michigan;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $3,467,564,282;
CMS estimated paid claims error rate (percentage): 3.9%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 17.9%.
QIO by state[I]: West Virginia;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $729,042,409;
CMS estimated paid claims error rate (percentage): 4.4%;
CMS estimated standard error[C] (percentage): 0.80%;
Relative precision[D](percentage): 18.2%.
QIO by state[I]: Vermont;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $164,700,697;
CMS estimated paid claims error rate (percentage): 3.3%;
CMS estimated standard error[C] (percentage): 0.60%;
Relative precision[D](percentage): 18.2%.
QIO by state[I]: South Dakota;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $232,787,316;
CMS estimated paid claims error rate (percentage): 3.8%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 18.4%.
QIO by state[I]: Ohio;
CMS targeted sample size[A]: 744; Total Medicare fee- for-service
payments in fiscal year 2004[B[(IN DOLLARS)] rs): 3,469,584,344;
CMS estimated paid claims error rate (percentage): 3.2%;
CMS estimated standard error[C] (percentage): 0.60%;
Relative precision[D](percentage): 18.8%.
QIO by state[I]: Alabama;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,603,881,531;
CMS estimated paid claims error rate (percentage): 3.2%;
CMS estimated standard error[C] (percentage): 0.60%;
Relative precision[D](percentage): 18.8%.
QIO by state[I]: Rhode Island;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $269,904,786;
CMS estimated paid claims error rate (percentage): 4.2%;
CMS estimated standard error[C] (percentage): 0.80%;
Relative precision[D](percentage): 19.0%.
QIO by state[I]: Virginia;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,933,408,829;
CMS estimated paid claims error rate (percentage): 3.5%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 20.0%.
QIO by state[I]: Oklahoma;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $964,748,057;
CMS estimated paid claims error rate (percentage): 3.5%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 20.0%.
QIO by state[I]: Alaska;
CMS targeted sample size[A]: 504;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $100,985,029;
CMS estimated paid claims error rate (percentage): 3.5%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 20.0%.
QIO by state[I]: North Dakota;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $216,246,500;
CMS estimated paid claims error rate (percentage): 2.0%;
CMS estimated standard error[C] (percentage): 0.40%;
Relative precision[D](percentage): 20.0%.
QIO by state[I]: South Carolina;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,408,487,704;
CMS estimated paid claims error rate (percentage): 5.4%;
CMS estimated standard error[C] (percentage): 1.10%;
Relative precision[D](percentage): 20.4%.
QIO by state[I]: New Jersey;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $3,595,399,138;
CMS estimated paid claims error rate (percentage): 2.9%;
CMS estimated standard error[C] (percentage): 0.60%;
Relative precision[D](percentage): 20.7%.
QIO by state[I]: Puerto Rico;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $376,450,167;
CMS estimated paid claims error rate (percentage): 4.8%;
CMS estimated standard error[C] (percentage): 1.00%;
Relative precision[D](percentage): 20.8%.
QIO by state[I]: Utah;
CMS targeted sample size[A]: 744; Total Medicare fee- for-service
payments in fiscal year 2004[B[(IN DOLLARS)] rs): 389,527,711;
CMS estimated paid claims error rate (percentage): 3.8%;
CMS estimated standard error[C] (percentage): 0.80%;
Relative precision[D](percentage): 21.1%.
QIO by state[I]: Connecticut;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,295,269,906;
CMS estimated paid claims error rate (percentage): 3.2%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 21.9%.
QIO by state[I]: New York;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $6,522,717,692;
CMS estimated paid claims error rate (percentage): 2.6%;
CMS estimated standard error[C] (percentage): 0.60%;
Relative precision[D](percentage): 23.1%.
QIO by state[I]: Idaho;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $237,198,385;
CMS estimated paid claims error rate (percentage): 2.6%;
CMS estimated standard error[C] (percentage): 0.60%;
Relative precision[D](percentage): 23.1%.
QIO by state[I]: Texas;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $5,573,613,357;
CMS estimated paid claims error rate (percentage): 4.2%;
CMS estimated standard error[C] (percentage): 1.00%;
Relative precision[D](percentage): 23.8%.
QIO by state[I]: North Carolina;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,720,223,476;
CMS estimated paid claims error rate (percentage): 2.1%;
CMS estimated standard error[C] (percentage): 0.50%;
Relative precision[D](percentage): 23.8%.
QIO by state[I]: Washington;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,253,681,476;
CMS estimated paid claims error rate (percentage): 2.1%;
CMS estimated standard error[C] (percentage): 0.50%;
Relative precision[D](percentage): 23.8%.
QIO by state[I]: Oregon;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $689,865,040;
CMS estimated paid claims error rate (percentage): 2.5%;
CMS estimated standard error[C] (percentage): 0.60%;
Relative precision[D](percentage): 24.0%.
QIO by state[I]: Pennsylvania;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $4,290,842,680;
CMS estimated paid claims error rate (percentage): 2.5%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 28.0%.
QIO by state[I]: Nebraska;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $500,351,357;
CMS estimated paid claims error rate (percentage): 1.4%;
CMS estimated standard error[C] (percentage): 0.40%;
Relative precision[D](percentage): 28.6%.
QIO by state[I]: District of Columbia;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $393,305,231;
CMS estimated paid claims error rate (percentage): 1.3%;
CMS estimated standard error[C] (percentage): 0.40%;
Relative precision[D](percentage): 30.8%.
QIO by state[I]: Kansas;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $762,382,857;
CMS estimated paid claims error rate (percentage): 2.8%;
CMS estimated standard error[C] (percentage): 0.90%;
Relative precision[D](percentage): 32.1%.
QIO by state[I]: Georgia;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,215,263,714;
CMS estimated paid claims error rate (percentage): 2.1%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 33.3%.
QIO by state[I]: Arizona;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,081,388,500;
CMS estimated paid claims error rate (percentage): 2.4%;
CMS estimated standard error[C] (percentage): 0.80%;
Relative precision[D](percentage): 33.3%.
QIO by state[I]: Tennessee;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $2,093,513,706;
CMS estimated paid claims error rate (percentage): 1.7%;
CMS estimated standard error[C] (percentage): 0.60%;
Relative precision[D](percentage): 35.3%.
QIO by state[I]: Missouri;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,935,671,182;
CMS estimated paid claims error rate (percentage): 1.1%;
CMS estimated standard error[C] (percentage): 0.40%;
Relative precision[D](percentage): 36.4%.
QIO by state[I]: Wyoming;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $99,863,364;
CMS estimated paid claims error rate (percentage): 1.1%;
CMS estimated standard error[C] (percentage): 0.40%;
Relative precision[D](percentage): 36.4%.
QIO by state[I]: California;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $7,517,783,935;
CMS estimated paid claims error rate (percentage): 4.6%;
CMS estimated standard error[C] (percentage): 1.70%;
Relative precision[D](percentage): 37.0%.
QIO by state[I]: Wisconsin;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,575,519,000;
CMS estimated paid claims error rate (percentage): 1.0%;
CMS estimated standard error[C] (percentage): 0.40%;
Relative precision[D](percentage): 40.0%.
QIO by state[I]: Minnesota;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $1,412,860,400;
CMS estimated paid claims error rate (percentage): 1.0%;
CMS estimated standard error[C] (percentage): 0.50%;
Relative precision[D](percentage): 50.0%.
QIO by state[I]: Colorado;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $703,166,846;
CMS estimated paid claims error rate (percentage): 1.3%;
CMS estimated standard error[C] (percentage): 0.70%;
Relative precision[D](percentage): 53.8%.
QIO by state[I]: Hawaii;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $203,010,800;
CMS estimated paid claims error rate (percentage): 0.5%;
CMS estimated standard error[C] (percentage): 0.30%;
Relative precision[D](percentage): 60.0%.
QIO by state[I]: Montana;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $226,885,429;
CMS estimated paid claims error rate (percentage): 0.7%;
CMS estimated standard error[C] (percentage): 0.50%;
Relative precision[D](percentage): 71.4%.
QIO by state[I]: Mississippi;
CMS targeted sample size[A]: 744;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $884,792,083;
CMS estimated paid claims error rate (percentage): 1.2%;
CMS estimated standard error[C] (percentage): 1.00%;
Relative precision[D](percentage): 83.3%.
QIO by state[I]: All QIOs;
CMS targeted sample size[A]: 38,448;
Total Medicare fee-for-service payments in fiscal year 2004[B] (in
dollars): $84,939,940,736;
CMS estimated paid claims error rate (percentage): 3.6%;
CMS estimated standard error[C] (percentage): 0.20%;
Relative precision[D](percentage): 5.6%.
Source: GAO analysis of CMS data.
Note: This table reflects net paid claims error rates.
[A] For carriers, DMERCs, and FIs, sample size was the targeted number
of claims drawn for the fiscal year 2004 error rate estimates for each
contractor. While CMS selected an equal sample from each of these
contractors, the final sample sizes varied among contractors. Some
selected claims were excluded from the final sample because the claims
were missing information, such as dates of service and provider or
patient information. For QIOs, the targeted sample size was the actual
sample size.
[B] We calculated total Medicare fee-for-service payments by dividing
the projected improper payment by the paid claims error rate. According
to the CMS fiscal year 2004 error rate report, CMS did not adjust
projected improper payments data to exclude beneficiary co- payments,
deductibles, and reductions to recover previous overpayments. This
means that the improper payment amounts appear larger than they would
otherwise. However, error rates are unaffected.
[C] Standard error is a measure of variation around the estimate, in
this case the error rate.
[D] Relative precision equals the contractor's standard error divided
by the contractor's paid claims error rate.
[E] Carriers are health insurers and pay claims submitted by
physicians, diagnostic laboratories and facilities, and ambulance
service providers.
[F] DMERCs are health insurers and pay claims submitted by durable
medical equipment suppliers.
[G] For the fiscal year 2004 error rate,TriCenturion, a program
safeguard contractor, was responsible for medical review in one of the
four DMERC regions. Program safeguard contractors are Medicare
contractors that conduct activities to address or prevent improper
payments. As such, it was TriCenturion, not the DMERC, which was
responsible for lowering the error rates in its region.
[H] FIs are almost exclusively health insurers and pay claims submitted
by home health agencies, non-prospective payment system (PPS)
hospitals, hospital outpatient departments, skilled nursing facilities,
and hospices. PPS is a reimbursement method used by Medicare where the
payment is made based on a predetermined rate and is unaffected by the
provider's actual costs.
[I] QIOs (formally known as peer review organizations) are responsible
for ascertaining the accuracy of coding and payment of paid Medicare
FFS claims for acute care inpatient hospital stays--generally those
that are covered by PPS--for Medicare beneficiaries in all 50 states,
the District of Columbia, and Puerto Rico. Unlike carriers, DMERCs, and
FIs, however, QIOs do not process and pay claims. These activities are
conducted by FIs.
[End of table]
[End of section]
Appendix III: Comments from the Department of Health and Human
Services:
DEPARTMENT OF HEALTH & HUMAN SERVICES:
Office of Inspector General:
Washington, D.C. 20201:
MAR 8 2006:
Mr. A. Bruce Steinwald:
Director, Health Care:
U.S. Government Accountability Office:
Washington, DC 20548:
Dear Mr. Steinwald:
Enclosed are the Department's comments on the U.S. Government
Accountability Office's (GAO) draft report entitled, "MEDICARE PAYMENT:
CMS Methodology Adequate To Estimate National Error Rate" (GAO-06-300).
These comments represent the tentative position of the Department and
are subject to reevaluation when the final version of this report is
received.
The Department provided several technical comments directly to your
staff.
The Department appreciates the opportunity to comment on this draft
report before its publication.
Sincerely,
Signed for:
Daniel R. Levinson:
Inspector General:
Enclosure:
The Office of Inspector General (OIG) is transmitting the Department's
response to this draft report in our capacity as the Department's
designated focal point and coordinator for U.S. Government
Accountability Office reports. OIG has not conducted an independent
assessment of these comments and therefore expresses no opinion on
them.
COMMENTS OF THE DEPARTMENT OF HEALTH AND HUMAN SERVICES ON THE U.S.
GOVERNMENT ACCOUNTABILITY OFFICE'S DRAFT REPORT ENTITLED, "MEDICARE
PAYMENT: CMS METHODOLOGY ADEQUATE TO ESTIMATE NATIONAL ERROR RATE" (GAO-
06-300):
The Department of Health and Human Services (HHS) appreciates the
opportunity to comment on the draft report. HHS appreciates the time
and resources GAO invested in researching and reporting the methodology
for estimating a national Medicare Fee-for-Service (FFS) error rate.
GAO found the Centers for Medicare & Medicaid Services (CMS)
methodology adequate for estimating the fiscal year 2004 national
Medicare FFS error rate. CMS is continually committed to refining the
processes to estimate, as well as to lower, the level of improper
payments in the Medicare FFS program.
The Medicare FFS error rate has significantly improved, from 10.1
percent in 2004 to 5.2 percent in 2005. CMS reviewed approximately
160,000 FFS Medicare claims in 2005 as part of its Medicare
comprehensive error rate-testing (CERT) program. The detailed review of
a sample of Medicare FFS claims provides an accurate statistical error
rate estimate on individual contractors, types of service, and provider
types. CMS is now able to identify specific problem areas and target
improvement efforts. The CERT program reflects the agency's increased
commitment to use detailed data and analysis in managing the Medicare
program through identifying and reducing improper payments.
The significant reduction in the Medicare FFS error rate from 2004 to
2005 is largely attributed to marked improvement in the no-
documentation and the insufficient documentation error rates. Since the
CERT program began, CMS and Medicare contractors have focused a large
part of their efforts on educating providers about CERT and the
importance of responding to CERT requests for medical records. This has
dramatically reduced the number of no-documentation errors. Provider
education also helped reduce the insufficient documentation error rate
to just over one percent.
[End of section]
Appendix IV: GAO Contact and Staff Acknowledgments:
GAO Contact:
A. Bruce Steinwald, (202) 512-7101 or steinwalda@gao.gov:
Acknowledgments:
In addition to the contact named above, Debra Draper, Assistant
Director; Lori Achman; Jennie Apter; Dae Park; and Ann Tynan made key
contributions to this report.
FOOTNOTES
[1] Unless otherwise specified, dollars paid in error and error rates
discussed in this report are net amounts. Net dollars paid in error
were calculated by subtracting dollars paid in error that were due to
underpayments from those that were due to overpayments. The net dollars
paid in error were then used to estimate the error rate. CMS also
reported gross dollars paid in error and error rates in fiscal year
2004. Gross dollars paid in error were calculated by adding dollars
paid in error that were due to underpayments to those that were due to
overpayments.
[2] GPRA requires agencies to develop multiyear strategic plans, annual
performance goals, and annual performance reports. See Pub. L. No. 103-
62, 107 Stat. 285.
[3] In a few cases, program safeguard contractors are responsible for
ensuring the payment accuracy of Medicare claims. Program safeguard
contractors are Medicare contractors that conduct activities to address
or prevent improper payments.
[4] Carriers are health insurers and pay claims submitted by
physicians, diagnostic laboratories and facilities, and ambulance
service providers.
[5] DMERCs are health insurers and pay claims submitted by durable
medical equipment suppliers. In fiscal year 2004, a program safeguard
contractor, TriCenturion, was responsible for medical review and for
lowering the error rates in its region.
[6] FIs are almost exclusively health insurers and pay claims submitted
by home health agencies, non-prospective payment system (PPS)
hospitals, hospital outpatient departments, skilled nursing facilities,
and hospices. PPS is a reimbursement method used by Medicare where the
payment is made based on a predetermined rate and is unaffected by the
provider's actual costs.
[7] QIOs (formerly known as peer review organizations) are responsible
for ascertaining the accuracy of coding and payment of paid Medicare
FFS claims for acute care inpatient hospital stays--generally those
that are covered by PPS--for Medicare beneficiaries in all 50 states,
the District of Columbia, and Puerto Rico. Unlike carriers, DMERCs, and
FIs, however, QIOs do not process and pay claims. These activities are
conducted by FIs.
[8] See Department of Health and Human Services, Centers for Medicare &
Medicaid Services, Improper Medicare Fee-for-Service Payments Report
Fiscal Year 2004 (Baltimore, Md.: December 2004).
[9] See Senate Homeland Security and Governmental Affairs Subcommittee
on Federal Financial Management, Government Information and
International Security, Hearing on Medicare and Medicaid Improper
Payments, Statement of the Director of Office of Financial Management,
Centers for Medicare & Medicaid Services, 109th Congress, July 12,
2005.
[10] Each program monitors the accuracy of paid claims that constitute
approximately 50 percent of Medicare's FFS payments annually.
[11] OIG regularly conducts audits, evaluations, and investigations
pertaining to HHS programs.
[12] Pub. L. No. 108-173, § 921(b)(3), 117 Stat. 2066, 2388-89.
[13] Since the creation of the CERT Program and the HPMP in 2003, OIG
has conducted annual reviews of the programs as part of its oversight
of work performed for HHS by contractors.
[14] The standard error is a measure of variation around the estimate,
in this case, the error rate.
[15] See, for example, M.H. Hansen, W.N. Hurwitz, and W.G. Madow,
Sample Survey Methods and Theory, vol. I (New York, N.Y.: John Wiley &
Sons, Inc., 1953), 130.
[16] To provide illustration, consider that one contractor has an error
rate of 11.9 percent with a standard error of 2.1 percent and a second
contractor has an error rate of 20.4 percent also with a standard error
of 2.1 percent. The standard errors are the same, but relative
precision, which is calculated by dividing the standard error by the
error rate estimate, illustrates that the reliability of the estimates
is different. Relative precision of the error rate estimate for the
first contractor is 17.6 percent, while the relative precision of the
error rate estimate for the second contractor is 10.3 percent. This
indicates that the second contractor's error rate estimate is more
reliable.
[17] See Department of Health and Human Services, Centers for Medicare
& Medicaid Services, Improper Medicare FFS Payments Long Report (Web
Version) for November 2005. 2005.
https://www.cms.hhs.gov/apps/er_report/preview_er_report.asp?from=public
&which=long&reportID=3 (downloaded Jan. 26, 2006).
[18] According to OIG testimony in February 2000, OIG began estimating
the national Medicare error rates in fiscal year 1996 as part of its
audit of CMS's financial statements. See House Committee on the Budget,
Statement of Inspector General, Department of Health and Human
Services, Hearing on Medicare and Medicaid: HHS High-Risk Programs,
106th Congress, February 17, 2000.
[19] Pub. L. No. 107-300, 116 Stat. 2350 (codified at 31 U.S.C. § 3321
note).
[20] OMB Mem. M-03-13 (2003).
[21] In Medicare, decisions about whether and under what circumstances
new procedures or devices are covered are made nationally by CMS or
locally by Medicare contractors for beneficiaries in their service
areas.
[22] In the fiscal year 2005 error rate report, CMS reported that
carriers, DMERCs, and FIs collected overpayments identified during the
November 2005 error rate reporting period. Further, CMS reported that
the agency will instruct carriers, DMERCs, and FIs to make payments to
providers in underpayment cases identified for the November 2006 and
later reports. See Department of Health and Human Services, Centers for
Medicare & Medicaid Services, Improper Medicare FFS Payments Long
Report (Web Version) for November 2005.
[23] DRG coding is the classification system used by Medicare to group
patients according to diagnosis, type of treatment, age, and other
criteria. Under PPS, hospitals are paid a predetermined rate for
treating patients based on the specific DRG category, regardless of the
actual cost of care for the individual.
[24] Maryland is the only state that does not use the PPS system for
acute care inpatient hospitals. Maryland instead has an alternative
payment system, known as an all-payer system, in which the state
decides each hospital's level of reimbursement and requires that all
payers be charged the same rate for the same service. Medicare and
Medicaid pay the state-approved rates.
[25] Claims from Maryland with length of stay errors are considered
medically unnecessary services. Length of stay reviews identified cases
of potential delayed discharge. For example, the patient was medically
stable, and continued hospitalization was unnecessary.
[26] See Department of Health and Human Services, Centers for Medicare
& Medicaid Services, Improper Medicare Fee-for-Service Payments Report
Fiscal Year 2004.
[27] CMS entered into multiyear contracts with QIOs divided into three
groups. Each of the three groups had different contract end dates.
[28] See GAO, Medicare Contracting Reform: CMS's Plan Has Gaps and Its
Anticipated Savings Are Uncertain, GAO-05-873 (Washington, D.C.: Aug.
17, 2005).
[29] Under the current contracting structure, Medicare Part A and Part
B claims are paid by different types of contractors. Part A covers
inpatient hospital care, skilled nursing facility care, some home
health care services, and hospice care, which are paid by FIs. Part B
services include physician and outpatient hospital services, diagnostic
tests, mental health services, outpatient physical and occupational
therapy, ambulance services, some home health services, and medical
equipment and supplies, which are paid by carriers and DMERCs. Under
the reformed structure, MACs will be responsible for both Part A and B
claims.
[30] See Department of Health and Human Services, Medicare Contracting
Reform: A Blueprint for a Better Medicare (Washington, D.C.: Feb. 7,
2005).
[31] While CMS selected an equal sample from each contractor, the final
sample sizes among contractors varied. Some selected claims were
excluded from the final sample because the claims were missing
information, such as dates of service and provider or patient
information.
[32] Relative precision of no greater than 15 percent is considered to
be within acceptable statistical standards. See, for example, Hansen,
Hurwitz, and Madow, 130.
[33] Systematic sampling is a selection procedure by which the sample
is selected from the population (Medicare claims) on the basis of a
uniform interval, such as every fifth claim, between sampling units
(claims), after a random starting point has been determined. The
uniform interval is determined by dividing the given sample size into
the population size and dropping decimals in the result. The random
start is determined by using an acceptable method of selecting random
numbers and is a number between 1 and the uniform interval.
[34] Of the 30 contractor-specific error rates with relative precision
above acceptable statistical standards, 25 were FIs.
[35] See, for example, W.G. Cochran, Sampling Techniques, 3rd Ed. (New
York, N.Y.: John Wiley & Sons, 1977), 96-99.
[36] See Department of Health and Human Services, Office of Inspector
General, Review of Corrective Actions to Improve the Comprehensive
Error Rate Testing Process for Obtaining Medical Records, A-03-04-00005
(Washington, D.C.: June 2004). See also Department of Health and Human
Services, Office of Inspector General, Review of Providers'
Responsiveness to Requests for Medical Records Under the Comprehensive
Error Rate Testing Program, A-01-04-00517 (Washington, D.C.: September
2004).
[37] See Department of Health and Human Services, Centers for Medicare
& Medicaid Services, Improper Medicare Fee-for-Service Payments Fiscal
Year 2003 (Baltimore, Md.: December 2003).
[38] 45 C.F.R. Parts 160 and 164 (2005).
[39] Claims greater than $40 were referred to OIG for follow-up.
[40] In fiscal year 2003, 54.7 percent of the national Medicare error
rate was due to nonresponse. In fiscal year 2004, nonresponse decreased
to 29.7 percent of the national Medicare error rate.
[41] According to CMS's fiscal year 2005 error rate report, the CERT
Program reduced error caused by nonresponse in fiscal year 2005 through
several corrective actions, including educating providers about the
CERT Program and encouraging providers to submit medical records by
fax. Unlike fiscal year 2004, for which CMS reported net error rates,
in fiscal year 2005, CMS reported only gross error rates and gross
dollars paid in error; therefore we can only compare gross figures for
nonresponse for fiscal years 2004 and 2005. As a percentage of the
total gross Medicare error rate, nonresponse decreased from 30.7
percent in fiscal year 2004 to 13.5 percent in fiscal year 2005. See
Department of Health and Human Services, Centers for Medicare &
Medicaid Services, Improper Medicare FFS Payments Long Report (Web
Version) for November 2005.
[42] See Department of Health and Human Services, Office of Inspector
General, Oversight and Evaluation of the Fiscal Year 2004 Comprehensive
Error Rate Testing Program, A-03-04-00007 (Washington, D.C.: November
2004).
[43] See Department of Health and Human Services, Office of Inspector
General, Oversight and Evaluation of the Fiscal Year 2005 Comprehensive
Error Rate Testing Program, A-03-05-00006 (Washington, D.C.: November
2005).
[44] See, for example, Cochran, 164-166.
[45] The Lewin Group used the Taylor series approximation method to
calculate the standard errors. See, for example, Cochran, 319.
[46] A CMS official told us and provided documentation that beginning
with the fiscal year 2006 error rate estimation, the HPMP will move to
a simple random sample in which all records are chosen at random within
each state, thus eliminating the need for systematic sampling. Simple
random sampling is also an accepted method of sampling to achieve a
sample that is representative of the population from which it was
drawn.
[47] It was not possible for the OIG contractor to obtain the exact
June 2003 population file because the file is continuously updated and
previous versions are not retained. We did not believe it was necessary
to compare every month's sample to the population from which it was
drawn because the large size of the annual sample (approximately 40,000
claims) and population (approximately 11.5 million claims) would make
the task too burdensome, and the fact that the sample was drawn in the
same manner each month meant the results from one month should not
differ significantly from the results from any other month.
[48] The range reported here does not reflect the claims or total
payment volume in Alaska since CMS takes a smaller sample from Alaska
than from all other states, the District of Columbia, and Puerto Rico.
[49] See, for example, Cochran, 96-99.
[50] A ratio of 100 percent would mean that the average claim amount in
the sample was equal to the average claim amount in the population.
[51] See Department of Health and Human Services, Office of Inspector
General, Oversight and Evaluation of the Fiscal Year 2004 Hospital
Payment Monitoring Program, A-03-04-00008 (Washington, D.C.: November
2004).
[52] For example, according to our analysis of data provided by the
HPMP, the average claim value for claims reviewed for the fiscal year
2004 error rate for QIOs was approximately $7,500. According to our
analysis of Medicare claims data from the Part B Extract Summary System
Carrier Data File, the average claim value for carriers in 2003 was
$32.
[53] See Department of Health and Human Services, Centers for Medicare
& Medicaid Services, Improper Medicare FFS Payments Long Report (Web
Version) for November 2005.
[54] See Department of Health and Human Services, Office of Inspector
General, Oversight and Evaluation of the Fiscal Year 2004 Hospital
Payment Monitoring Program.
[55] According to OIG, CMS requires that CDACs employ admission
necessity reviewers who are licensed practical nurses with utilization
review experience. CMS requires that coding specialists be registered
health information administrators, registered health information
technicians, or certified coding specialists.
[56] See Department of Health and Human Services, Office of the
Inspector General, Oversight and Evaluation of the Fiscal Year 2004
Hospital Payment Monitoring Program.
[57] FIs, which are responsible for paying acute-care inpatient
hospital claims, use a software program available on the CMS Web site,
PRICER, to calculate the Medicare payment amount. The program
calculates the Medicare payment amount using information supplied on
the provider claim and current national and hospital-specific factors
related to the payment amount. CMS stated that the PRICER program does
not consider all of the factors used by FIs when pricing acute-care
inpatient hospital claims.
[58] To better ensure that data from a sample represent data from the
population from which they are drawn, the sample data are often
adjusted to reflect the probability of a specific data point, in this
case an acute-care inpatient hospital discharge claim, being chosen.
This process is called weighting. Sample weights reflect the different
probabilities that each claim has of being chosen as part of the
sample. The less likely a claim is to be selected, the larger its
sample weight.
[59] See, for example, Hansen, Hurwitz, and Madow, 172-173.
[60] CMS used a Taylor series linear approximation method.
[61] To estimate the total annual dollars paid in error for QIOs, CMS
projects the dollar amounts found in error in the sample to the broad
population.
[62] Statistical theory demonstrates that combining the estimates based
on independent samples is a valid estimate of the aggregate of the
samples. See, for example, Hansen, Hurwitz, and Madow, 190.
[63] See Department of Health and Human Services, Centers for Medicare
& Medicaid Services, Improper Medicare Fee-for-Service Payments Fiscal
Year 2003 (Baltimore, Md.: December 2003). See also Department of
Health and Human Services, Centers for Medicare & Medicaid Services,
Improper Medicare Fee-for-Service Payments Report Fiscal Year 2004
(Baltimore, Md.: December 2004).
[64] See Department of Health and Human Services, Office of Inspector
General, Oversight and Evaluation of the Fiscal Year 2004 Comprehensive
Error Rate Testing Program, A-03-04-00007 (Washington, D.C.: November
2004). See also Department of Health and Human Services, Office of
Inspector General, Oversight and Evaluation of the Fiscal Year 2004
Hospital Payment Monitoring Program, A-03-04-00008 (Washington, D.C.:
November 2004).
[65] See Department of Health and Human Services, Office of Inspector
General, Review of Corrective Actions to Improve the Comprehensive
Error Rate Testing Process for Obtaining Medical Records, A-03-04-00005
(Washington, D.C.: June 2004). See also Department of Health and Human
Services, Office of Inspector General, Review of Providers'
Responsiveness to Requests for Medical Records Under Comprehensive
Error Rate Testing Program, A-01-04-00517 (Washington, D.C.: September
2004).
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