Reliability of data in VBA's claims processing workload reporting system can be enhanced and opportunities exist to use beneficiary demographic data to estimate future workload requirements.
Report No.: 7D2-B01-020
Date: February 27, 1997
Office of Inspector General
Washington DC 20420
1. This project was initiated at the request of the
Veterans Benefits Administration's (VBA) Chief Financial Officer
because of concerns that the workload reporting system, especially
for Compensation and Pension (C&P) benefits, was not sufficiently
accurate to assure appropriate workload reporting and performance
measurement of VBA operations. Shortly after we initiated this
project, VBA management suspended a planned C&P organizational
restructuring due to management's concerns regarding the accuracy
of workload data.
2. VBA needs to maintain accurate and reliable workload
reporting so that it can effectively track and measure organizational
performance and assure effective use of staff resources. In carrying
out its responsibility for administering monetary benefits to
support the nation's statutory obligation to its veterans, VBA's
C&P program operations encompass substantial field staffing
resources with 4,320 Full-Time Equivalent Employees assigned to
Adjudication Divisions in the 50 states, the District of Columbia,
Puerto Rico, and the Philippines. These field sites are responsible
for managing and completing a substantial claims workload that
included 2.7 million C&P claims and about $18 billion in veterans
benefits paid during Fiscal Year 1996.
3. The audit found that VBA's data reliability of
its Work-in-Progress (WIPP) system needs to be improved. Our
analysis of the WIPP data file disclosed:
4. The audit focused on VBA workload reporting and
distribution. Our primary objective was to test data validity
and demonstrate how VBA systems could be used to better assure
the accuracy and reliability of reported accomplishment of benefit
claims processing. The audit reviewed workload reporting associated
with processing original compensation claims, since this has been
a specific concern of VBA management. Our review results identified
opportunities for VBA to enhance the accuracy and reliability
of workload reporting and performance measurement of claims processing
operations with improved tracking of the delivery of benefits
to beneficiaries. In addition, there are opportunities to use
beneficiary demographic data derived from the C&P automated
files as a tool to enhance predictions of future workload.
5. Our review of WIPP data files showed that over
reporting occurred because duplicate completed compensation cases
were included and incomplete claims processing actions were incorrectly
reported as completed. This resulted in more completed compensation
case counts and shorter case completion times than should have
been reported. These types of reporting errors may be controlled
by establishing system edits and by increasing management oversight
and review. The audit has shown that the temporary nature of
WIPP data files leaves VBA vulnerable to workload reporting errors
and system manipulation because WIPP data is not available for
management oversight and review. VBA should routinely collect
and analyze this data to help assure more accurate and reliable
workload reporting and performance measurement.
6. In addition to under reporting claims processing
timeliness, the audit found that the current workload management
system does not provide VBA with information on how long it actually
takes to process a veteran's claim when claims work is transferred
between ROs. VBA data reporting systems are designed to measure
organizational unit productivity and can only tell how long it
takes to process a claim if only one RO is involved in the case
processing. When claims work is transferred between ROs, individual
timelines can only be reported for case work completed by each
RO. While this provides a measure of each RO's timeliness, it
does not provide a true measure of the total length of time that
was required to complete claims processing actions and provide
veterans with a decision on their benefit requests. VBA needs
to modify existing system productivity reporting so that it can
adequately measure and track the timeliness of claims work that
is transferred between ROs.
7. Our audit also found that there are opportunities
for VBA to use demographic data on beneficiaries, derived from
the C&P automated files, as a tool for enhancing the estimate
of future workload. Since veteran population is a key factor
considered by VBA as part of planning for organizational restructuring,
our analysis provides VBA with a useful profile of each RO and
the actual client base served. This type of information can be
used by VBA (with other factors currently in use) in estimating
future demand for claims, shifting workload, and completing reasonableness
tests of work performed. The beneficiary distribution information
can provide greater insight into future workload issues since
the use of only veteran population data does not include the significant
number of non-veteran beneficiaries (20 percent of all beneficiaries
are survivors).
8. Given the importance of VBA's claims processing
operations and the opportunities we identified to enhance workload
reporting and performance measurement, we provided program officials
with interim briefings and survey results packages during the
course of the audit so appropriate corrective actions could be
considered as soon as possible. Our discussions with key VBA
officials indicated that automated systems could be better used
as a tool in assessing data reliability and how demographic distribution
information on VA beneficiaries could be useful in understanding
workload generation.
9. The report includes recommendations to address
the issues which are discussed above. These recommendations can
provide for a strengthened management information system with
enhanced workload reporting and performance measurement, and use
of demographic data on beneficiaries as a tool in addressing workload
generation issues. The Acting Under Secretary for Benefits agreed
with the report recommendations and provided acceptable implementation
actions. We consider the report issues resolved and will follow
up on planned actions until they are completed.
[Signed]
MICHAEL G. SULLIVAN
Assistant Inspector General
for Auditing
Memorandum to the Acting Under Secretary for
Benefits (20) i
RESULTS AND RECOMMENDATIONS
1. VBA Can Enhance the
Accuracy and Reliability of its Workload Reporting System 1
Conclusion 4
Recommendation 1 5
2. Beneficiary Demographic Data Should be Used in
Estimating Future Workload 7
Conclusion 8
Recommendation 2 8
APPENDIXES
I OBJECTIVES, SCOPE, AND
METHODOLOGY 10
II BACKGROUND 12
III RESULTS OF AUDIT OF
DATA VALIDATION IN THE WORK-IN-PROGRESS (WIPP) SYSTEM 13
IV DISTRIBUTION OF VETERANS AND BENEFICIARIES
BY STATE 16
V COMPARISON OF REGIONAL OFFICE OF JURISDICTION
WITH BENEFICIARY RESIDENCE 20
VI ACTING UNDER SECRETARY
FOR BENEFITS COMMENTS 24
VII FINAL REPORT DISTRIBUTION 26
1. VBA Can Enhance the Accuracy and Reliability
of its Workload Reporting System
Our analysis of claims processing workload reporting
found over reporting in the quantity of work performed (analysis
of original compensation claims showed over reporting of work
completed by about 5.3 percent) and the timeliness of processing
claims took longer than reported (analysis of original compensation
claims showed claims processing took an average of 10 days longer
than reported). Our review of the Veterans Benefits Administration's
(VBA) Work-in-Progress (WIPP) system data files showed that these
reporting errors occurred because duplicate completed compensation
cases were included and incomplete case processing actions were
incorrectly reported as completed. This resulted in more completed
case counts and shorter case completion timelines than should
have been reported. (Results of audit of data validation in
the WIPP system are in Appendix III on pages 13-15.) These
types of reporting errors can be controlled by establishing appropriate
system edits and by increasing management oversight and review.
Our audit has shown that the temporary nature of
WIPP data files leaves VBA vulnerable to workload reporting errors
and system manipulation because the WIPP data is not available
for management oversight and review. VBA should routinely collect
and analyze this data to help assure more accurate and reliable
workload reporting and performance measurement. In addition,
the current workload reporting system does not allow VBA to know
how long it actually takes to process a veteran's claim when claims
processing work is transferred between Regional Offices (RO).
VBA's reporting systems are designed to measure organizational
unit productivity and can tell how long it takes to process a
claim if only one RO is involved in the case processing. VBA
needs to modify existing system productivity reporting so that
it can adequately measure and track the timeliness of claims work
that is transferred between ROs.
VBA Organizational Restructuring Decisions Involving
Claims Processing Activities Need to be Based on Reliable Work
Measurement Data
Our review efforts were performed at the request
of the VBA Chief Financial Officer to assist VBA in a data validation
effort that would help assure that future organizational restructuring
decisions are made with the best work measurement data available.
Claims processing restructuring decisions are being considered
on how to improve the effectiveness and efficiency of VBA's operations
based upon existing management information from systems that have
not always been highly regarded. As VBA's plans to restructure
the organization become more essential to meet the Agency's challenges,
and have a greater impact on staff and clients, the Agency has
come under increasing challenges to the validity of the data used
to make these decisions.
VBA's efforts to meet the challenges in restructuring
operations is focused on field operations that do not require
direct personal contact with clients. Also, the most significant
and contentious restructuring must be done in the processing of
C&P benefits, VBA's largest program. In carrying out its responsibility
for administering monetary benefits to support the nation's statutory
obligation to its veterans, VBA's C&P program operations involve
substantial field staffing resources with 4,320 Full-Time Equivalent
Employees assigned to Adjudication Divisions in the 50 states,
the District of Columbia, Puerto Rico, and the Philippines. These
field sites are also responsible for managing and completing a
substantial claims workload that included 2.7 million C&P
claims and about $18 billion in benefits paid in Fiscal Year 1996.
The audit focused on workload reporting associated
with original compensation claims. The processing of original
compensation claim has been an area of specific concern for VBA
management and one in which they have been working to improve
their quality and timeliness. Our data validation testing involving
original compensation claims showed that VBA systems had workload
reporting errors which have resulted in over reporting of the
quantity of work performed and under reporting of the elapsed
timeliness of claims processing. VBA can effectively eliminate
these errors and establish more accurate and reliable workload
reporting with appropriate system edits and expanded oversight
and review of WIPP data.
VBA Systems Can be Used to Better Assure the Accuracy
and Reliability of Reported Claims Processing Work
Based upon prior audit work in VBA program areas,
we determined that VBA's automated data processing systems could
be used as a validation tool to perform internal data consistency
checks and to recalculate some of VBA's work measurement data.
Available VBA management information can be used to provide nationwide
oversight of claims processing to provide better assurance of
the accuracy and reliability of reported work and improved tracking
of the delivery of benefits to beneficiaries. This is particularly
important since VBA no longer conducts field station surveys that
would show erroneous workload reporting patterns and facilitate
the identification of errors that should be reviewed and corrected.
Workload Reporting Errors Can be Better Controlled
Our analysis of workload reporting found over reporting
of the quantity of work performed (analysis of original compensation
claims showed over reporting of work completed by about 5.3 percent)
and the timeliness of claims processing took longer than reported
(analysis of original compensation claims showed claims processing
took an average 10 days longer than reported). (Results of
audit of data validation in the WIPP system are in Appendix III
on pages 13-15.) WIPP data was collected for a 6-month period
(January-June 1996) from the Regional Data Processing Centers.
This data reflects details of work processed on individual veteran
claims by each RO and provides key information such as: which
employee accomplished the reported work, type of adjudication
work activities reported (end product codes), and dates of completed
actions. Our analysis of WIPP system information involving work
completed on original compensation awards showed over reporting
of end product work accomplished because duplicate completed cases
were included. For the 6-month period included in our review,
we identified 4,079 duplicate case work counts out of 76,568 reported.
This type of reporting error can be controlled by establishing
appropriate system edits that would prevent duplicate credit for
end product work completed on original compensation claims.
Based upon our analysis of data on original claims
that were reestablished and authorized during the period of our
review, we also found under reporting of the elapsed time associated
with claims processing. Our analysis of the detailed WIPP data
files showed that original compensation claims took an average
of 10 days longer to process than reported by VBA (161 days versus
151 reported in original WIPP data). The lower reported elapsed
time resulted from the 4,079 duplicate completed cases that were
included in the work counts and from another 6,754 cases where
incomplete case processing actions were incorrectly reported as
completed. Typically, these actions occur when RO staff cancel
a pending claim in the WIPP system and then reestablish the claim,
showing a new date of claim as the date on which it is reestablished.
The new claim is completed in a few days and the WIPP data system
reflects a lower average number of days per case than should have
been reported. (Results of audit of data validation in the
WIPP system are in Appendix III on pages 13-15.) Timeliness
of claims processing is a key VBA productivity measurement that
should accurately reflect the efforts of RO staff in delivering
benefits to beneficiaries. Our review results show that the temporary
nature of the WIPP data files leaves VBA vulnerable to not identifying
workload reporting errors and system manipulation because the
data is no longer available for management oversight and review.
VBA should routinely collect and analyze this data to help assure
more accurate and reliable workload reporting.
During the course of the audit, we provided C&P staff with case examples involving multiple WIPP records in which they agreed that the data we provided indicated that there was excessive work performed or claimed. While our review did not include reviews of individual veteran claims folders maintained at the ROs, the nature of the reported work counts identified showed and VBA management agreed that reporting errors are occurring.
Tracking of Claims Work Transferred Between Regional
Offices Needs to be Improved
The current workload reporting system does not allow
VBA to know how long it actually takes to process a veteran's
claim when work on the claim is transferred between ROs. VBA
data reporting systems are designed to measure organizational
unit productivity and can only tell how long it takes to process
a claim if only one RO is involved in the case processing. When
claims work is transferred between ROs, individual timeliness
can be reported for case work completed by each RO, but not cumulatively
for the claim.
Our review identified cases where multiple timelines
had been reported for case work completed by each RO, which did
not reflect the actual time that the veteran was waiting for a
benefit decision. While the current workload reporting system
provides a measure of an RO's timeliness, it does not provide
a true measure of the total length of time that was required to
complete veteran claims processing actions and provide veterans
with a decision on their benefit requests. At the time of our
review, over 27,000 cases were reportedly transferred from one
RO to another for claims processing through June of Fiscal Year
(FY) 1996. VBA needs to modify the existing work measurement
system and productivity reporting so that they focus on accurately
measuring and tracking how well VA is meeting veterans' claims
processing needs involving claims work transferred between ROs.
Conclusion
Our review identified opportunities for VBA to enhance
the accuracy and reliability of workload reporting and performance
measurement of claims processing operations with improved tracking
of the delivery of benefits to beneficiaries. Maintaining accurate
and reliable workload measurement is particularly important at
this time since VBA is considering significant organizational
restructuring that will be based, in part, on this information.
For More Information
Recommendation 1
We recommend that the Acting Under Secretary for
Benefits take the following actions to improve reporting, oversight,
and tracking of work associated with benefit claims processing:
a. Establish appropriate system edits to help prevent
duplicate reporting of work on benefit claims.
b. Routinely collect and analyze WIPP data to help
assure accurate and reliable workload reporting and performance
measurement.
c. Modify existing system productivity reporting
to assure appropriate tracking of the timeliness of claims processing
involving work transferred between Regional Offices.
Acting Under Secretary for Benefits Comments
We concur with Recommendation 1. In fact, we are
taking action to address the processing timeliness measurement
concerns associated with brokered work referred to in sub-element
c. We are amending the instructions on brokered work to require
that stations sending cases must maintain a pending issue control
on each case temporarily transferred to another station to be
worked. Upon return of the case, the station of original jurisdiction
will complete a review of the brokered cases then finalize the
pending end product. This change allows us to capture the total
processing time for each brokered case and eliminates potential
distortion to the average processing time of all original compensation
claims.
We support the concept of system edits expressed
in sub-element a to prevent duplication of work credit. We also
agree with sub-element b that management at the local, area, and
national levels should have the ability to routinely collect claims
completion data to monitor the accuracy of and ensure the reliability
of workload reports and associated performance measures. In addition,
I am establishing a Performance Measures Task Group to identify
ways to prevent errors in the systems, improve the integrity of
the systems, and address all of the concerns raised by your report.
A draft of their charter was included with the Acting Under Secretary's
comments and is on page 25.
(See Appendix VI on pages 24-25 for the full text
of the Acting Under Secretary's comments.)
Office of Inspector General Comments
The Acting Under Secretary's comments and implementation actions are acceptable and responsive to the recommendation. We consider the issues resolved and will follow up on planned actions until they are completed.
2. Beneficiary Demographic Data Should
be Used in Estimating Future Workload
VBA can improve its ability to estimate future workload
requirements through the use of beneficiary demographic data (those
veterans and survivors receiving benefits) derived from the C&P
automated files. We identified three possible demographic distributions
of VA beneficiaries that could be useful in understanding workload
generation: veteran population, beneficiary file assignment, and
beneficiary residence. Since veteran population is a key factor
being considered by VBA as part of its planning for organizational
restructuring, our analysis provides a useful profile of each
RO and the actual client base served. This information could
be used by VBA in predicting future demand for claims, shifting
workload, and completing reasonableness tests of work performed.
An analysis of the C&P master record files as
of March 1996, found a number of variances between reported veteran
population and beneficiaries as a proportion of their respective
populations. We compared the percentage of total veteran population
with the percentage of total VA beneficiary population in each
state and the District of Columbia. This analysis identified
variances between these percentages which VBA needs to consider
in estimating future demand for claims work. For example, in
California, with the largest number of both veterans (about 2.8
million) and beneficiaries (about 267,000), the percentage of
veterans residing in the State (10.81 percent) exceeds the percentage
of beneficiaries (8.05 percent) by a variance 2.76. An estimate
of future workload in California based on veteran population alone
could overstate the amount of claims work that the smaller percentage
of beneficiaries in the state actually would generate. Conversely,
in the District of Columbia the variance between the percentage
of veterans (0.19 percent) and the percentage of beneficiaries
(1.63 percent) is -1.44, indicating a greater amount of claims
work than would be expected if only veteran population data was
considered. (Details of the distribution of veterans and beneficiaries
by state are in Appendix IV on pages 16-19.)
Our analysis also showed that 16.2 percent of beneficiaries
live within the jurisdictional boundaries of a RO other than the
one that services their claim. This is not totally unexpected
as case transfers between ROs are not required when a beneficiary
moves, only when the beneficiary requests it or there is a claim
to change benefits. However, this variance, between veterans
who live within a RO jurisdiction and those who do not, should
be identified when determining the RO workload. (Details of
the comparison of Regional Office of Jurisdiction with beneficiary
residence are in Appendix V on pages 20-23.) Our analysis
shows that beneficiary distribution can provide a useful insight
into workload generation issues (in addition to using overall
veteran population information), because the use of only veteran
population data does not include the significant number of non-veteran
beneficiaries (20 percent of all beneficiaries are survivors).
The number of non-veteran beneficiaries represent workload requirements
that need to be addressed when considering future demand for services.
The use of beneficiary data also takes into account only those
who are using the system, not all who may be eligible and not
making demands upon it.
We believe that VBA could benefit from using the
two beneficiary distributions we have discussed. The beneficiary
distribution by residence could be useful in estimating future
demand for claims. Variances from current jurisdictional assignment
would indicate shifting workload demands. The jurisdictional
assignment distributions would be most useful for conducting reasonableness
tests when compared to work performed. Variance from current
jurisdictional assignment could indicate workload churning or
greater efficiency. For example, states that have significantly
lower proportions of resident beneficiaries than case assignments,
such as New York, would be expected to have lessening workload
demands, and states that have significantly higher proportions
of resident beneficiaries than case assignments, such as Florida,
would be expected to have increasing workload demands. Estimates
of future workload could take these shifts into account when allocating
resources. (Details of the comparison of Regional Office of
Jurisdiction with beneficiary residence are in Appendix V on pages
20-23.) Our comparison of RO workload distribution and beneficiary
distribution provides a demonstration of the types of demographic
distributions of beneficiaries that we believe can be useful to
VBA in understanding and predicting workload generation.
Conclusion
There are opportunities for VBA to use demographic
data on beneficiaries derived from C&P automated files as
a tool in estimating future workload in addition to using veteran
population data. Since veteran population is a key factor being
considered by VBA as part of its planning for organizational restructuring,
we believe our analysis provides a useful profile of each RO and
the actual client base served.
For More Information
Recommendation 2
We recommend that the Acting Under Secretary for Benefits consider using the types of demographic distributions of beneficiaries identified in the audit as additional tools in estimating future demand for benefit claims work.
Acting Under Secretary for Benefits Comments
We concur with Recommendations 2. The additional
demographic data regarding beneficiaries might well fit into our
larger Business Process Re-engineering effort to fundamentally
redesign the claims adjudication process.
(See Appendix VI on pages 24-25 for the full text
of the Acting Under Secretary's comments.)
Office of Inspector General Comments
The Acting Under Secretary's comments indicate agreement
with our recommendation that they consider using the types of
demographic distributions of beneficiaries identified in the audit.
We consider the issue resolved and will follow up on VBA's future
actions to use demographic data on beneficiaries as a part of
the Business Process Re-engineering effort.
Objectives
The project was initiated at the request of the Veterans
Benefits Administration's (VBA) Chief Financial Officer because
of concerns that VBA's workload reporting system, especially for
Compensation and Pension (C&P) benefits, was not sufficiently
accurate to assure appropriate workload reporting and performance
measurement of VBA operations. We focused our audit efforts in
two areas: workload reporting and distribution. Our primary objective
was to test the validity of workload data and demonstrate how
VBA management systems could be used to better assure the accuracy
and reliability of reported work on processing veteran benefit
claims.
Scope and Methodology
The audit focused on validating those data items
that are the most significant in terms of their impact on work/staff
distribution and those most likely to be challenged as subject
to error or manipulation. Based upon prior audit work in VBA
program areas, we determined that VBA's automated data processing
systems could be used as a validation tool to perform internal
data consistency checks and to recalculate some of VBA's work
measurement data. We recalculated samples of the work accomplished,
who did it, and how long it took to do; to validate the productivity
relationships reported in the existing automated workload reporting
system. Our review focused on original compensation claims as
a means to test data validity and demonstrate how the system could
be used to enhance the accuracy and reliability of workload reporting
and performance measurement. The audit included the following
key elements:
The audit was performed in accordance with generally
accepted government auditing standards.BACKGROUND
Currently, VBA is involved in initiatives to reengineer
benefit delivery programs in concert with the Government Performance
and Results Act of 1993. Organizational modeling is an important
component in all of VBA's reengineering activities that is being
undertaken at each RO. VBA is redesigning the basic benefits
delivery organization that embodies its Adjudication and Veterans
Services Division operations. As a part of this process, VBA
proposed an initiative to consolidate C&P program activities.
In evaluating ROs for the proposed consolidation effort, VBA
considered work measurement data in the evaluation process. However,
because of concerns regarding the accuracy and reliability of
reported work measurement data, VBA suspended its organizational
restructuring initiative involving C&P program activities.
VBA is continuing to focus on using business process reengineering
methods to develop methods to restructure RO operations.
VBA's workload reporting system evolved in the mid-1950's
in response to the need for an organized and systematic work measurement
system that could be used to identify and allocate resources needed
to accomplish necessary work. In 1985, VBA changed from a predominately
manual work measurement system to an automated productivity measurement
system. In 1991, the current work measurement system became operational
and includes performance measurement information on C&P claims
processing work that was the subject of our data validation focus
on this project.
Based upon prior audit work in VBA program areas,
we determined that VBA's automated work measurement system data
could be used as a validation tool to perform internal consistency
checks and to recalculate some of the work measurement data.
Our automated data analysis focused on workload reporting and
distribution, to test data validity and demonstrate how VBA systems
could be used to better assure the accuracy and reliability of
reported work on veteran benefit claims.
Workload and Timeliness Measurement for Compensation
and Pension Actions
Regional Offices (RO) process C&P claims using
a computer system known as "Target." Target also generates
management reports of the number and type of C&P actions completed
by each RO and the average length of time taken to complete each
action. These reports are based on information input and actions
taken by RO Adjudication Division staff at various times during
the processing of each claim.
The two most critical pieces of information for these
reports are the end product code (EPC) and the date of claim.
When Adjudication Division staff receive an application, letter,
document, or other correspondence, they must determine the claim
or issue involved. This issue is identified in Target by an EPC.
Each EPC has an assigned work rate standard measured in decimal
hours. The standard represents the amount of labor, as determined
by periodic studies, required to complete a particular EPC. "Assignment
of the correct EPC is of prime importance, because it properly
accounts for time required to complete similar issues and it affects
the projection of future workloads."
Two EPCs are used to identify original compensations
claims. EPC 110 identifies claims involving one to seven issues.
Each disability claimed or identified is considered a separate
issue. EPC 010 identifies claims with eight or more issues.
A pending EPC 110 or 010 should not be cleared (reported as completed)
until all issues raised by the claim have been resolved.
The date of claim is defined as the date of receipt
in the RO of the material requiring a determination. The date
entered is the basis for determining actual processing time required
to complete action on a specific claim and the average processing
time for all claims of this type.
The input of the information needed to establish
a claim in the Target system creates a Pending Issue File (PIF).
The Work-in-Progress (WIPP) subsystem of Target uses PIF information
to track pending workload and to measure how long VA takes to
complete each claim.
The accuracy of the information in the PIF determines
WIPP's effectiveness as a management tool and the validity of
workload and processing time reports generated from this information.
Our analysis of WIPP transactions for a 6month period (January 5
through July 5, 1996) found that ROs had actually adjudicated
4,079 fewer original compensation claims-5.3 percent-than the
total reported for this period. We also found that the average
time needed to process original compensation claims during this
period was 10 days greater-6 percent-than the reported processing
time. (Our analysis of WIPP data is summarized on page 15.)
WIPP System Lacks Controls to Prevent Incorrect
Actions That Can Overstate the Amount of Work Completed and Understate
Processing Time
The Target system lacks controls that would prevent
RO staff from taking actions which would give them credit for
work they have not actually completed or under report the length
of time actually taken to complete action on a claim. Two commands
used in Target processing of claims-CAUT (Claims Authorization)
and PCLR (Pending Issue Clear)-will clear pending WIPP controls
and give the RO credit for completing action on a claim. Another
command-PCAN (Pending Issue Canceled)-will cancel an existing
PIF with no end product credit. The Target system does not keep
a record of these transactions after they are processed, and VBA
does not capture them for further analysis or quality control
purposes.
Our review of WIPP transactions for original compensation
claims found two methods by which RO staff used PCLR, CAUT, and
PCAN actions to get credit for work that was not completed and
to under report the time it took to complete action on a claim.
An RO can receive credit for completing two or more EPC 010/110
actions on the same claim by "PCLRing" (and receiving
credit for completing) a claim that has been pending for some
time. The RO then immediately establishes a new claim for disability
compensation, using the date of claim for the new claim as the
date on which it is reestablished. The RO then clears the new
claim within a few days by a CAUT action. These types of cases
are identified on page 15 in the summary of our analysis of WIPP
data as "duplicates." We identified 4,079 of
these duplicate cases and calculated the additional processing
days associated with the "PCLRd" pending claims. Duplicate
cases over report the true number of original compensation claims
completed by the number of times the duplicate actions are taken.
They also distort the reported average processing time of these
claims.
For example, a pending EPC 110 with a date of claim
of September 25, 1995 was "PCLRd" by the RO on
January 18, 1996. The processing time was 115 days. A second
EPC 110, with a date of claim of January 18, 1996, was established
on January 19, 1996. The second claim was cleared by a CAUT
action on January 24, 1996 with a processing time of only
6 days. In this example, the RO received credit for completing
two original compensation claims with an average processing time
of 60 days ([115+6]÷2). However, the RO actually took 121
days to complete only one claim.
ROs can also distort the reported average processing
time of original compensation claims by canceling a pending claim
with a PCAN command and then immediately reestablishing the claim,
showing the date of claim for the new claim as the date on which
it is reestablished. The RO then clears the new claim within
a few days by a CAUT action. These cases are identified below
in the summary of our analysis of WIPP data as "extra day
cases." We identified 6,754 such cases and calculated the
additional processing days associated with the "PCANd"
pending claims.
Although ROs do not receive credit for completing
the "PCANd" claim in extra day cases, these cases distort
the reported average processing time of original compensation
claims. Only the processing time of the reestablished claim is
considered when calculating average processing time. The time
associated with the "PCANd" claim is disregarded. For
example, a pending EPC 110 with a date of claim of January 26,
1996 was "PCANd" by the RO on May 22, 1996 after
it had been pending for 117 days. The RO reestablished the claim
on May 29, 1996 with the same date of claim, and cleared
it with a CAUT action on June 5, 1996. Although the reported
processing time for this case was only 7 days, it actually took
131 days to complete.
| Number of cases/Elapsed days | 76,568 | 11,595,818 | ||||||
| Average Processing Time- | ||||||||
| CAUT | 59,760 | 9,077,619 | All CAUTs/PCLRs | 151 | ||||
| PCAN | 2,256 | 297,638 | ||||||
| PCLR | 5,975 | 816,075 | ||||||
| Totals | 68,157 | 10,233,325 | Number of cases/Elapsed days | 4,079 | 559,708 | |||
| Percentage of total | ||||||||
| CAUTs/PCLRs | 5.3% | |||||||
| CAUT | 5,133 | 901,587 | Average Processing Time-Duplicates | 137 | ||||
| PCAN | 537 | 59,222 | ||||||
| PCLR | 5,700 | 800,537 | ||||||
| Totals | 11,370 | 1,761,346 | Number of cases/Elapsed days | 6,754 | 753,694 | |||
| Percentage of total | ||||||||
| CAUTs/PCLRs | 8.8% | |||||||
| CAUT | 64,893 | 9,979,206 | Average Processing Time-Extra Day Cases | 112 | ||||
| PCAN | 2,793 | 356,860 | ||||||
| PCLR | 11,675 | 1,616,612 | Total Elapsed Days-CAUTs/PCLRS | |||||
| Totals | 79,361 | 11,952,678 | and Extra Day Cases | 12,349,512 | ||||
| Average Processing Time- | ||||||||
| CAUTs/PCLRs and Extra Day Cases | 161 | |||||||
| Extra Days Added to Average | ||||||||
| Processing Time | 10 | |||||||
| Percentage Increase in Average | ||||||||
| Processing Time | 6% | |||||||
Use of Demographic Data by VBA for Planning Purposes
VBA has established a Field Restructuring Task Group
"charged with developing recommendations by which the benefits
delivery function can be restructured to maintain or improve accessibility
and service, while minimizing adverse impact on affected employees
and achieving resource savings." One of the assumptions
guiding the Task Group in its work is: "Consideration will
be given to customer service data, which indicates that veterans
and their families desire improved access to services."
In recommending sites for realignment or expansion, one of the
selection criteria to be used by the Task Group is: "Demographics
of the veteran population (to support decisions on locations of
additional access points to improve and expand service)."
The supporting data package prepared by the Task
Group included a listing of the number of veterans per state and
the total number in the United States (excluding Puerto Rico).
We found no indication that the Task Group has received any other
demographic data to aid in its decisionmaking. However,
consideration of only veteran population distribution by the Task
Group would neglect several important considerations:
We believe that data showing the place of residence
of all C&P beneficiaries, both veterans and survivors, taken
from the C&P master record would be a useful tool in predicting
future workload patterns. This data considers those who are currently
using the system, not those who may not be eligible or who do
not intend to apply for C&P benefits. The statebystate
distribution of all C&P beneficiaries shows the pattern of
cases currently serviced by VBA and would be useful in estimating
service demands in the near future. Continued analysis of beneficiary
distribution over a period of time would identify any shifting
workload patterns.
| Total veteran population (6/1/95 estimate) | 26,067,000 | |||
| Veteran pension cases | 432,895 | |||
| Veteran compensation cases | 2,235,675 | |||
| Total veteran cases | 2,668,570 | |||
| Death compensation cases | 307,097 | |||
| Death pension cases | 354,582 | |||
| Total death cases | 661,679 | |||
| Total active cases (as of 9/30/95) | 3,330,249 | |||
StatebyState Distribution of All Veterans
and VA Beneficiaries
The Annual Report
of the Secretary of Veterans Affairs-Fiscal Year 1995
contains a table, based on U. S. Department of Commerce, Bureau
of Census data, listing the estimated number of veterans living
in each state and the District of Columbia
as of July 1, 1995. We used this information to calculate
the percentage of all veterans in each jurisdiction.
We also extracted the addresses of all beneficiaries-veterans
and surviving spouses-from the March 1996 C&P master record.
Using this information and a ZIP Code directory, we determined
the number of beneficiaries with mailing addresses in each state,
the District of Columbia, Puerto Rico, and the Philippines. We
also calculated the percentage of all beneficiaries in each jurisdiction.
We then computed a variance for each state by subtracting
the state's percentage of VA beneficiaries from its percentage
of veterans. (Details of our comparison of veteran and beneficiary
population, by state are on page 19.) The following variances
in states with large veteran and beneficiary populations are of
interest:
We recognize the following limitations in our variance
calculations:
Our comparison of veteran and beneficiary populations is not intended to be used as an actual planning document. Rather, it is intended to be a prototype of the kind of analysis we believe would be a useful tool along with veteran population data in estimating workload for each RO.
| |||||||||
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| TOTALS | 26,067,000 | 100% | 3,322,025 | 100% | |||||
| California | 2,818,000 | 10.81% | 267,277 | 8.05% | |||||
| Illinois | 1,074,000 | 4.12% | 81,107 | 2.44% | |||||
| Pennsylvania | 1,363,000 | 5.23% | 142,880 | 4.30% | |||||
| Michigan | 949,000 | 3.64% | 90,849 | 2.73% | |||||
| New York | 1,538,000 | 5.90% | 172,405 | 5.19% | |||||
| New Jersey | 741,000 | 2.84% | 73,965 | 2.23% | |||||
| Ohio | 1,188,000 | 4.56% | 131,052 | 3.94% | |||||
| Iowa | 291,000 | 1.12% | 17,119 | 0.52% | |||||
| Maryland | 530,000 | 2.03% | 49,147 | 1.48% | |||||
| Indiana | 593,000 | 2.27% | 57,942 | 1.74% | |||||
| Connecticut | 339,000 | 1.30% | 28,819 | 0.87% | |||||
| Wisconsin | 507,000 | 1.94% | 52,690 | 1.59% | |||||
| Virginia | 705,000 | 2.70% | 79,205 | 2.38% | |||||
| Minnesota | 462,000 | 1.77% | 51,806 | 1.56% | |||||
| Kansas | 263,000 | 1.01% | 31,042 | 0.93% | |||||
| New Hampshire | 135,000 | 0.52% | 14,852 | 0.45% | |||||
| Washington | 631,000 | 2.42% | 78,396 | 2.36% | |||||
| Idaho | 112,000 | 0.43% | 12,504 | 0.38% | |||||
| Utah | 138,000 | 0.53% | 16,011 | 0.48% | |||||
| Delaware | 78,000 | 0.30% | 8,694 | 0.26% | |||||
| Missouri | 586,000 | 2.25% | 73,732 | 2.22% | |||||
| Oregon | 371,000 | 1.42% | 46,922 | 1.41% | |||||
| Hawaii | 116,000 | 0.45% | 14,595 | 0.44% | |||||
| North Dakota | 59,000 | 0.23% | 8,162 | 0.25% | |||||
| Alaska | 65,000 | 0.25% | 8,945 | 0.27% | |||||
| Nevada | 186,000 | 0.71% | 24,381 | 0.73% | |||||
| Vermont | 62,000 | 0.24% | 9,057 | 0.27% | |||||
| Arizona | 459,000 | 1.76% | 59,740 | 1.80% | |||||
| Montana | 95,000 | 0.36% | 13,680 | 0.41% | |||||
| South Carolina | 380,000 | 1.46% | 50,580 | 1.52% | |||||
| Kentucky | 367,000 | 1.41% | 49,032 | 1.48% | |||||
| South Dakota | 74,000 | 0.28% | 11,718 | 0.35% | |||||
| Massachusetts | 594,000 | 2.28% | 79,352 | 2.39% | |||||
| Maine | 153,000 | 0.59% | 23,486 | 0.71% | |||||
| New Mexico | 172,000 | 0.66% | 28,879 | 0.87% | |||||
| West Virginia | 199,000 | 0.76% | 32,385 | 0.97% | |||||
| Colorado | 385,000 | 1.48% | 56,355 | 1.70% | |||||
| Rhode Island | 109,000 | 0.42% | 21,607 | 0.65% | |||||
| Nebraska | 168,000 | 0.64% | 30,650 | 0.92% | |||||
| Mississippi | 233,000 | 0.89% | 43,739 | 1.32% | |||||
| Louisiana | 378,000 | 1.45% | 62,867 | 1.89% | |||||
| Arkansas | 258,000 | 0.99% | 49,976 | 1.50% | |||||
| Georgia | 685,000 | 2.63% | 106,927 | 3.22% | |||||
| Oklahoma | 350,000 | 1.34% | 65,786 | 1.98% | |||||
| Florida | 1,709,000 | 6.56% | 240,207 | 7.23% | |||||
| North Carolina | 711,000 | 2.73% | 113,543 | 3.42% | |||||
| Tennessee | 516,000 | 1.98% | 88,898 | 2.68% | |||||
| Alabama | 427,000 | 1.64% | 78,293 | 2.36% | |||||
| Texas | 1,647,000 | 6.32% | 248,041 | 7.47% | |||||
| District of Columbia | 50,000 | 0.19% | 54,104 | 1.63% | |||||
| Wyoming | 48,000 | 0.18% | Included in Colorado total | ||||||
| Puerto Rico | - - | - - | 48,228 | 1.45% | |||||
| Philippines | - - | - - | 20,086 | 0.60% | |||||
| No address in C&P Master Record | 310 | ||||||||
Jurisdiction Over Claims Folders
In general, a beneficiary's claims folder is under
the jurisdiction of the RO assigned the geographical area where
the beneficiary maintains a permanent residence. However, VBA
procedures do not require that claims folders be transferred from
one RO to another solely because beneficiaries have changed addresses.
As a result, many beneficiaries who have relocated since having
a claim processed by VA are residing in the jurisdiction of ROs
other than those where their claims folders are located. In March
1996, over 537,000 C&P beneficiaries-16.2 percent-were in
this situation. The following table shows the number and percentage
of various categories of beneficiaries
living in the jurisdiction of ROs other than those holding their
claims folders:
| ||||||
| Compensation | 2,239,557 | 392,525 | ||||
| Pension: | Live | 423,347 | 43,627 | |||
| Death | 343,451 | 42,963 | ||||
| All Pension | 766,798 | |||||
| SC Survivors* | 315,670 | 58,313 | ||||
| Totals | 3,322,025 | 537,428 | ||||
*
Dependency and Indemnity Compensation and Death Compensation
Comparison of
the Number of Claims Folders Located at Each RO With the Number
of Beneficiaries Residing in RO's Area of Jurisdiction
We compared the number of C&P beneficiaries residing in each RO's jurisdiction with the number of claims folders at each RO. We did this comparison by first extracting information showing beneficiary addresses and claims folder locations from the March 1996 C&P master record. Using a list of the ZIP codes within each RO's area of jurisdiction and the master beneficiary record information, we determined the number of claims folders and the number of beneficiaries residing within each RO's jurisdiction. We then computed the difference between the number of claims folders at each RO and the number of beneficiaries residing in that RO's jurisdiction. We also calculated a ratio for each RO by dividing the number of claims folders at the RO by the number of beneficiaries residing in that RO's jurisdiction. The ratio is shown as a percentage. (Details of our comparison for each RO are on pages 22-23.)
We believe that the pattern of beneficiary residences
and the ratios for each RO may be more reliable predictors of
nearterm future workload patterns than claims folder location
alone. Although claims folders are not transferred between ROs
solely because a beneficiary has relocated, they are transferred
when a claim is received from a beneficiary residing in another
RO's jurisdiction.
The following examples support our recommendation
that analysis of the patterns of beneficiary residence should
be used as an additional tool for planning purposes:
Continued analysis of the ratios at each RO between
beneficiary residence and claims folder location would be useful
in identifying changing workload patterns. Ratios significantly
greater or lesser than 100 percent at a particular RO may indicate
that the RO will have an increasing or decreasing share of the
total workload.
The following ratios as of March 1996 are of interest:
We recognize the following limitations in our comparison
of the number of claims folders at each RO with the number of
beneficiaries residing in its jurisdiction:
Our comparison is not intended to be used as an actual planning document. Rather, we offer it as the prototype of an additional analytical tool that could be useful for VBA in understanding and predicting workload generation and aid in its planning for restructuring.
|
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| |
| TOTALS | 3,322,025 | 3,322,025 | 537,428 | |||
| Des Moines | Iowa | 17,119 | 30,752 | 13,633 | 179.6% | |
| Fargo | North Dakota | 8,162 | 13,533 | 5,371 | 165.8% | |
| Washington | District of Columbia | 54,104 | 68,054 | 13,950 | 125.8% | |
| New York | New York | 114,518 | 139,374 | 24,856 | 121.7% | |
| Los Angeles | California | 92,739 | 110,352 | 17,613 | 119.0% | |
| Providence | Rhode Island | 21,607 | 25,453 | 3,846 | 117.8% | |
| Louisville | Kentucky | 49,032 | 57,216 | 8,184 | 116.7% | |
| Chicago | Illinois | 81,107 | 92,531 | 11,424 | 114.1% | |
| Philadelphia | Pennsylvania | 89,303 | 96,527 | 7,224 | 108.1% | |
| Columbia | South Carolina | 50,580 | 54,510 | 3,930 | 107.8% | |
| Boise | Idaho | 12,504 | 13,472 | 968 | 107.7% | |
| Pittsburgh | Pennsylvania | 53,577 | 56,860 | 3,283 | 106.1% | |
| Boston | Massachusetts | 79,352 | 84,119 | 4,767 | 106.0% | |
| Manchester | New Hampshire | 14,852 | 15,658 | 806 | 105.4% | |
| Milwaukee | Wisconsin | 52,690 | 55,441 | 2,751 | 105.2% | |
| Jackson | Mississippi | 43,739 | 45,911 | 2,172 | 105.0% | |
| Oakland | California | 112,023 | 117,213 | 5,190 | 104.6% | |
| Hartford | Connecticut | 28,819 | 30,057 | 1,238 | 104.3% | |
| Detroit | Michigan | 90,849 | 94,541 | 3,692 | 104.1% | |
| Houston | Texas | 93,070 | 96,542 | 3,472 | 103.7% | |
| Wichita | Kansas | 31,042 | 32,183 | 1,141 | 103.7% | |
| Seattle | Washington | 78,396 | 81,214 | 2,818 | 103.6% | |
| Roanoke | Virginia | 79,205 | 81,760 | 2,555 | 103.2% | |
| Newark | New Jersey | 73,965 | 75,775 | 1,810 | 102.4% | |
| Buffalo | New York | 57,887 | 59,065 | 1,178 | 102.0% | |
| Honolulu | Hawaii | 14,595 | 14,892 | 297 | 102.0% | |
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| |
| Denver | Colorado | 56,355 | 57,475 | 1,120 | 102.0% | |
| Anchorage | Alaska | 8,945 | 9,116 | 171 | 101.9% | |
| Muskogee | Oklahoma | 65,786 | 66,796 | 1,010 | 101.5% | |
| New Orleans | Louisiana | 62,867 | 63,631 | 764 | 101.2% | |
| Sioux Falls | South Dakota | 11,718 | 11,800 | 82 | 100.7% | |
| Little Rock | Arkansas | 49,976 | 49,991 | 15 | 100.0% | |
| Montgomery | Alabama | 78,293 | 78,260 | (33) | 100.0% | |
| Wilmington | Delaware | 8,694 | 8,683 | (11) | 99.9% | |
| Salt Lake City | Utah | 16,011 | 15,952 | (59) | 99.6% | |
| Cleveland | Ohio | 131,052 | 128,962 | (2,090) | 98.4% | |
| San Juan | Puerto Rico | 48,228 | 47,311 | (917) | 98.1% | |
| White River Jct | Vermont | 9,057 | 8,812 | (245) | 97.3% | |
| Togus | Maine | 23,486 | 22,750 | (736) | 96.9% | |
| Albuquerque | New Mexico | 28,879 | 27,820 | (1,059) | 96.3% | |
| Ft Harrison | Montana | 13,680 | 13,014 | (666) | 95.1% | |
| Waco | Texas | 154,971 | 147,302 | (7,669) | 95.1% | |
| Huntington | West Virginia | 32,385 | 30,661 | (1,724) | 94.7% | |
| Atlanta | Georgia | 106,927 | 100,980 | (5,947) | 94.4% | |
| Winston-Salem | North Carolina | 113,543 | 106,316 | (7,227) | 93.6% | |
| Indianapolis | Indiana | 57,942 | 53,939 | (4,003) | 93.1% | |
| St. Paul | Minnesota | 51,806 | 47,513 | (4,293) | 91.7% | |
| St. Louis | Missouri | 73,732 | 66,020 | (7,712) | 89.5% | |
| Nashville | Tennessee | 88,898 | 77,190 | (11,708) | 86.8% | |
| Portland | Oregon | 46,922 | 40,130 | (6,792) | 85.5% | |
| Phoenix | Arizona | 59,740 | 50,191 | (9,549) | 84.0% | |
| St. Petersburg | Florida | 240,207 | 199,150 | (41,057) | 82.9% | |
| San Diego | California | 62,515 | 50,031 | (12,484) | 80.0% | |
| Baltimore | Maryland | 49,147 | 36,970 | (12,177) | 75.2% | |
| Lincoln | Nebraska | 30,650 | 22,497 | (8,153) | 73.4% | |
| Reno | Nevada | 24,381 | 17,322 | (7,059) | 71.0% | |
| Cheyenne | Wyoming | Included in Denver total | ||||
| Manila | Philippines | 20,086 | 22,525 | 2,439 | 112.1% | |
| No address in C&P Master Record | 310 | |||||
| Department of
Veterans Affairs | Memorandum |
Date: February 3, 1997
From: Acting Under Secretary for Benefits (20) Subj: Draft Report of Audit of VBA's Data Reliability in the Claims Processing
Workload Reporting System
To: Planning and Policy Staff Members
1. We concur with Recommendation 1. In fact, we are taking action to address the processing timeliness measurement concerns associated with brokered work referred to in sub-element c. We are amending the instructions on brokered work to require that stations sending cases must maintain a pending issue control on each case temporarily transferred to another station to be worked. Upon return of the case, the station of original jurisdiction will complete a review of the brokered cases then finalize the pending end product. This change allows us to capture the total processing time for each brokered case and eliminates potential distortion to the average processing time of all original compensation claims.
2. We support the concept of system edits expressed in sub-element a to prevent duplication of work credit. We also agree with sub-element b that management at the local, area, and national levels should all have the ability to routinely collect claims completion data to monitor the accuracy of and ensure the reliability of workload reports and associated performance measures.
3. In addition, I am establishing a Performance Measures Task Group to identify ways to prevent errors in the systems, improve the integrity of the systems and address all the concerns raised by your report. A draft of their charter is attached.
4. We concur with Recommendation 2. The additional demographic data regarding beneficiaries might well fit into our larger Business Process Re-engineering effort to fundamentally redesign the claims adjudication process. [Signed] Stephen L. Lemons | |
| VA Form 2105
Mar 1989 | |
1. Identify Data Sets necessary to support the comprehensive Performance Measures of the Business Lines.
2. Recommend an approach to achieving a fully automated data collection system in support of the comprehensive Performance Measures.
3. Look at how the comprehensive Performance Measures can be used in resource allocation. 4. Other potential tasks or relationships: a. Executive Information System b. Doors c. Work Measurement
d. Process Control TASK FORCE COMPOSITION: CHAIR 1. 2. 3. 4. 5.
6. |
Secretary of Veterans Affairs (00)
Acting Under Secretary for Benefits (20A11)
General Counsel (02)
Assistant Secretary for Policy and Planning (008)
Assistant Secretary for Congressional Affairs (009)
Deputy Assistant Secretary for Public Affairs (80)
Deputy Assistant Secretary for Congressional Affairs
(60)
NonVA Distribution
Office of Management and Budget
US General Accounting Office
Congressional Committees:
Chairman, Senate Committee on Governmental Affairs
Ranking Member, Senate Committee on Governmental Affairs
Chairman, Senate Committee on Veterans' Affairs
Ranking Member, Senate Committee on Veterans' Affairs
Chairman, House Committee on Government Reform and Oversight
Ranking Member, House Committee on Government Reform and Oversight
Chairman, House Committee on Veterans' Affairs
Ranking Democratic Member, House Committee on Veterans' Affairs
Chairman, Senate Subcommittee on VA, HUD, and Independent Agencies,
Committee on Appropriations
Ranking Member, Senate Subcommittee on VA, HUD, and Independent Agencies,
Committee on Appropriations
Chairman, House Subcommittee on VA, HUD, and Independent Agencies,
Committee on Appropriations
Ranking Member, House Subcommittee on VA, HUD, and Independent Agencies,
Committee on Appropriations