Hospital Quality Data
Issues and Challenges Related to How Hospitals Submit Data and How CMS Ensures Data Reliability
Gao ID: GAO-08-555T March 6, 2008
Hospitals submit data on a series of quality measures to the Centers for Medicare & Medicaid Services (CMS) and receive scores on their performance. CMS instituted the Reporting Hospital Quality Data for Annual Payment Update Program (APU program) to collect the quality data from hospitals and report their rates on the measures on its Hospital Compare Web site. For hospital quality data to be useful to patients and other users, they need to be reliable, that is, accurate and complete. The Deficit Reduction Act of 2005 directed CMS to implement a value-based purchasing program for Medicare that beginning in fiscal year 2009 would adjust payments to hospitals based on factors related to the quality of care they provide. This statement provides information on (1) how hospitals collect and submit quality data to CMS and (2) how CMS works to ensure the reliability of the quality data submitted. This statement is based primarily on Hospital Quality Data: HHS Should Specify Steps and Time Frame for Using Information Technology to Collect and Submit Data (GAO-07-320, Apr. 25, 2007) and Hospital Quality Data: CMS Needs More Rigorous Methods to Ensure Reliability of Publicly Released Data (GAO-06-54, Jan. 31, 2006). In preparing these reports, GAO conducted case studies of eight hospitals, and reviewed documents of, and interviewed officials at CMS.
GAO reported in April 2007 that the eight case study hospitals visited used six steps to collect and submit quality data, two of which (steps 2 and 3) involved complex abstraction--the process of reviewing and assessing all relevant pieces of information in a patient's medical record to determine the appropriate value for each data element. The six steps were (1) identify patients for whom the quality data should be submitted, (2) locate needed information in the medical records, (3) determine the appropriate value for each data element, (4) transmit the data to CMS, (5) review reports to ensure acceptance of the data by CMS, and (6) supply copies of selected medical records to CMS for data validation. Several factors account for the complexity of the abstraction process (steps 2 and 3), including the content and organization of the medical record, the scope of information and clinical judgment required for certain data elements, and frequent changes by CMS in its data specifications. GAO's case studies also showed that existing information technology (IT) systems help hospitals gather some quality data but are far from enabling hospitals to automate the abstraction process. GAO reported in January 2006 that CMS had processes for ensuring the accuracy of the quality data submitted by hospitals but had no ongoing process for ensuring completeness of these data. To check accuracy, one CMS contractor electronically checks the data as they are submitted to the clinical warehouse. Another contractor conducts an independent audit by comparing the quality data submitted by a hospital from the medical records for a sample of five patients per quarter for each hospital to the quality data that the contractor reabstracts from the same medical records. The data are deemed to be accurate if there is 80 percent or greater agreement between these two sets of results. However, GAO also reported that CMS's determination as to whether hospitals met the accuracy standard was statistically uncertain for some hospitals because of the small number of records examined--five cases per quarter per hospital regardless of the hospital's size. In 2006 GAO also reported that CMS did not have an ongoing process for assessing the completeness of quality data submitted by hospitals and recommended that CMS take steps to improve its processes for ensuring the accuracy and completeness of the hospital quality data. CMS agreed the process needed improvement. For fiscal year 2008 and subsequent years, CMS required that hospitals attest each quarter to the completeness and accuracy of their data. Further, in a 2007 report to Congress that lays out a plan to implement a value-based purchasing program, CMS recognized the need to redesign the data infrastructure and validation process to support a value-based purchasing program by, for example, increasing the number of patient medical records sampled from selected hospitals.
GAO-08-555T, Hospital Quality Data: Issues and Challenges Related to How Hospitals Submit Data and How CMS Ensures Data Reliability
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Testimony:
Before the Committee on Finance, U.S. Senate:
United States Government Accountability Office:
GAO:
For Release on Delivery:
Expected at 2:00 p.m. EST:
Thursday, March 6, 2008:
Hospital Quality Data:
Issues and Challenges Related to How Hospitals Submit Data and How CMS
Ensures Data Reliability:
Statement for the Record:
Linda T. Kohn, Acting Director:
Health Care:
GAO-08-555T:
GAO Highlights:
Highlights of GAO-08-555T, a statement for the record for the Committee
on Finance, U.S. Senate.
Why GAO Did This Study:
Hospitals submit data on a series of quality measures to the Centers
for Medicare & Medicaid Services (CMS) and receive scores on their
performance. CMS instituted the Reporting Hospital Quality Data for
Annual Payment Update Program (APU program) to collect the quality data
from hospitals and report their rates on the measures on its Hospital
Compare Web site. For hospital quality data to be useful to patients
and other users, they need to be reliable, that is, accurate and
complete.
The Deficit Reduction Act of 2005 directed CMS to implement a value-
based purchasing program for Medicare that beginning in fiscal year
2009 would adjust payments to hospitals based on factors related to the
quality of care they provide.
This statement provides information on (1) how hospitals collect and
submit quality data to CMS and (2) how CMS works to ensure the
reliability of the quality data submitted. This statement is based
primarily on Hospital Quality Data: HHS Should Specify Steps and Time
Frame for Using Information Technology to Collect and Submit Data (GAO-
07-320, Apr. 25, 2007) and Hospital Quality Data: CMS Needs More
Rigorous Methods to Ensure Reliability of Publicly Released Data (GAO-
06-54, Jan. 31, 2006). In preparing these reports, GAO conducted case
studies of eight hospitals, and reviewed documents of, and interviewed
officials at CMS.
What GAO Found:
GAO reported in April 2007 that the eight case study hospitals visited
used six steps to collect and submit quality data, two of which (steps
2 and 3) involved complex abstraction”the process of reviewing and
assessing all relevant pieces of information in a patient‘s medical
record to determine the appropriate value for each data element. The
six steps were (1) identify patients for whom the quality data should
be submitted, (2) locate needed information in the medical records, (3)
determine the appropriate value for each data element, (4) transmit the
data to CMS, (5) review reports to ensure acceptance of the data by
CMS, and (6) supply copies of selected medical records to CMS for data
validation. Several factors account for the complexity of the
abstraction process (steps 2 and 3), including the content and
organization of the medical record, the scope of information and
clinical judgment required for certain data elements, and frequent
changes by CMS in its data specifications. GAO‘s case studies also
showed that existing information technology (IT) systems help hospitals
gather some quality data but are far from enabling hospitals to
automate the abstraction process.
GAO reported in January 2006 that CMS had processes for ensuring the
accuracy of the quality data submitted by hospitals but had no ongoing
process for ensuring completeness of these data. To check accuracy, one
CMS contractor electronically checks the data as they are submitted to
the clinical warehouse. Another contractor conducts an independent
audit by comparing the quality data submitted by a hospital from the
medical records for a sample of five patients per quarter for each
hospital to the quality data that the contractor reabstracts from the
same medical records. The data are deemed to be accurate if there is 80
percent or greater agreement between these two sets of results.
However, GAO also reported that CMS‘s determination as to whether
hospitals met the accuracy standard was statistically uncertain for
some hospitals because of the small number of records examined”five
cases per quarter per hospital regardless of the hospital‘s size. In
2006 GAO also reported that CMS did not have an ongoing process for
assessing the completeness of quality data submitted by hospitals and
recommended that CMS take steps to improve its processes for ensuring
the accuracy and completeness of the hospital quality data. CMS agreed
the process needed improvement. For fiscal year 2008 and subsequent
years, CMS required that hospitals attest each quarter to the
completeness and accuracy of their data. Further, in a 2007 report to
Congress that lays out a plan to implement a value-based purchasing
program, CMS recognized the need to redesign the data infrastructure
and validation process to support a value-based purchasing program by,
for example, increasing the number of patient medical records sampled
from selected hospitals.
To view the full product, including the scope and methodology, click on
[Hyperlink, http://www.GAO-08-555T]. For more information, contact
Linda T. Kohn at (202) 512-7114 or kohnl@gao.gov.
[End of section]
Mr. Chairman and Members of the Committee:
I am pleased to have the opportunity to comment as requested on topics
related to the Centers for Medicare & Medicaid Services's (CMS) Value-
based Purchasing Program Implementation Plan. On November 21, 2007, CMS
issued a report to Congress that lays out its plan to implement this
program. The plan builds on the foundation of CMS's Annual Payment
Update (APU) program that requires participating hospitals to submit
data--referred to here as quality data--that are used to calculate
hospital performance on measures of the quality of care provided in
order to avoid a reduction in their full Medicare payment update each
fiscal year.[Footnote 1] The vast majority of acute care hospitals
treating Medicare patients choose to submit quality data each quarter
to CMS, rather than accept a reduced annual payment update.
In the APU program, each quality measure consists of a set of
standardized data elements, which define the specific data that
hospitals need to submit to CMS. Hospitals determine a value for each
data element of a measure for patients--Medicare and non-Medicare--who
have a medical condition covered by the APU program, that is, heart
attack, heart failure, pneumonia, or surgery. The values for the data
elements consist of numerical data and other administrative and
clinical information that are obtained from the medical records of the
patients. Hospitals submit their quality data electronically, over the
Internet, to a clinical data warehouse operated by a CMS contractor.
In order to inform the public about hospital quality, CMS posts on a
public Web site--Hospital Compare--the performance scores that
hospitals receive on the quality measures derived from the data they
submit. For hospital quality data to be useful to patients and other
users, the data need to be reliable--that is, both accurate and
complete. If a hospital submits complete data, that is, data on all the
cases that meet the specific inclusion criteria for eligible patients,
but the data are not collected, or abstracted, from the patients'
medical records accurately, the data will not be reliable. Similarly,
if a hospital submits accurate data, but those data are incomplete
because the hospital leaves out eligible cases, the data will not be
reliable.
Although the APU program was originally set to expire in 2007, the
Deficit Reduction Act of 2005[Footnote 2] (DRA) made the APU program
permanent. The act also raised the Medicare payment reduction[Footnote
3] and required the Secretary of Health and Human Services (HHS) to
increase the number of measures for which hospitals participating in
the APU program would have to provide data in order to receive their
full Medicare payment update. Furthermore, DRA directed the Secretary
to develop a plan to implement a value-based purchasing program for
Medicare that beginning in fiscal year 2009 would adjust payments to
hospitals based on factors related to the quality of care they provide.
My statement today provides information on (1) how hospitals collect
and submit quality data to CMS and (2) how CMS works to ensure the
reliability of the quality data submitted by hospitals.
My statement is based primarily on findings from our two reports on
hospital quality data.[Footnote 4] In April 2007, we reported on case
studies that we conducted at eight individual acute care hospitals,
which were participating in the APU program, in order to obtain
information about the processes they used to collect and submit quality
data to CMS. As we noted in our report, because our evidence was
limited to the eight case studies, we cannot generalize to acute care
hospitals across the country. In January 2006, we reported on the
reliability of publicly reported information on hospital quality
obtained through the APU program that included a review of CMS
documents and interviews with CMS officials. We also reviewed CMS's
November 21, 2007, report to Congress which discusses options to
implement a value-based purchasing program.[Footnote 5] All the work
for our two reports on hospital quality data was done in accordance
with generally accepted government auditing standards. We conducted
this performance audit from February to March 2008, in accordance with
generally accepted government auditing standards. Those standards
require that we plan and perform the audit to obtain sufficient,
appropriate evidence to provide a reasonable basis for our findings
based on our audit objectives. We believe that the evidence obtained
provides a reasonable basis for our findings based on our audit
objectives.
In summary, in April 2007, we reported that the eight case study
hospitals we visited used six steps to collect and submit quality data,
two of which involved complex abstraction--the process of reviewing and
assessing all relevant pieces of information in a patient's medical
record to determine the appropriate value for each data element.
Several factors account for the complexity of the abstraction process,
including the content and organization of the medical record, the scope
of information and clinical judgment required for certain data
elements, and frequent changes by CMS in its data specifications. Our
case studies also showed that existing IT systems can help hospitals
gather some quality data but are far from enabling hospitals to
automate the abstraction process. In January 2006 we reported that CMS
had a process in place to assess the accuracy of the APU program data
submitted by hospitals, but had no ongoing process to assess the
completeness of those data.
Hospitals Use Six Steps to Collect and Submit Quality Data and IT
Systems Can Help:
In our April 2007 report,[Footnote 6] we found that whether patient
information was recorded electronically, on paper, or as a mix of both,
all eight of the case study hospitals collected and submitted their
quality data by carrying out six sequential steps: (1) identify
patients for whom the quality data should be submitted, (2) locate
needed information in the medical records, (3) determine the
appropriate value for each data element, (4) transmit the data to CMS,
(5) review reports to ensure acceptance of the data by CMS, and (6)
supply copies of selected medical records to CMS for data validation.
The description by hospital officials of the processes they used to
collect and submit quality data indicated that steps 2 and 3 (locating
the relevant clinical information and determining appropriate values
for the data elements), which involve the process of abstraction, were
the most complex steps of the six identified, due to several factors.
The first complicating factor was that the information abstractors
[Footnote 7] needed to determine the correct data element values for a
given patient was generally located in many different sections of the
patient's medical record. Much of the clinical information needed was
found in the sections of the medical record prepared by clinicians.
Often the information in question, such as contraindications for
aspirin or beta blockers, could be found in any of a number of places
in the medical record where clinicians made entries. As a result,
abstractors frequently had to read through multiple parts of the
record--sometimes the entire record--to find the information needed to
determine the correct value for just one data element.
The second factor was related to the scope of the information required
for certain data elements. Some of the data elements that the
abstractors had to fill in represented a composite of related data and
clinical judgment applied by the abstractor, not just a single discrete
piece of information. Such composite data elements typically were
governed by complicated rules for determining the clinical
appropriateness of a specific treatment for a given patient.
The third factor was the necessity abstractors at the case study
hospitals faced to adjust to frequent changes in the data
specifications set by CMS. For example, from fall 2004 through summer
2006, roughly every 3 months hospital abstractors had to stop and take
note of what had changed in the data specifications and revamp their
quality data collection procedures accordingly. Some of these changes
reflected modifications in the quality measures themselves. CMS changed
its schedule for issuing revisions to its data specifications from
every 3 months to every 6 months.
All the case study hospitals found that, over time, they had to
increase the amount of staff resources devoted to abstracting quality
data for the CMS quality measures, most notably as the number of
measures on which they were submitting data expanded. Officials at the
case study hospitals generally reported that the amount of staff time
required for abstraction increased proportionately with the number of
conditions for which they reported quality data. For example, as the
hospitals began to report on the surgical quality measures, they found
that the staff hours needed for this new set of quality measures were
directly related to the number of patient medical records to be
abstracted and the number of data elements collected. In other words,
they found no "economies of scale" as they expanded the scope of
quality data abstraction. Officials at the case study hospitals
estimated that the amount of staff resources devoted to abstracting
data for the CMS quality measures ranged from 0.7 to 2.5 full-time
equivalents (FTE),[Footnote 8] typically registered nurses. On the
other hand, officials at the case study hospitals reported that the
demands that quality data collection and submission placed on their
clinical staff resources were offset by the benefits that they derived
from the resulting information on their clinical performance. Each one
had a process for tracking changes in their performance over time and
providing feedback to individual clinicians and reports to hospital
administrators and trustees.
We found that the existing IT systems in the case study hospitals could
facilitate the collection of quality data, but that there were limits
on the advantages that the systems could provide. IT systems, and the
electronic records they support, offered hospitals two key benefits:
(1) improving accessibility to and legibility of the medical record,
and (2) facilitating the incorporation of CMS's required data elements
into the medical record. On the other hand, the limitations that
hospital officials reported in using existing IT systems to collect
quality data stemmed from having a mix of paper and electronic systems;
the prevalence of data recorded in IT systems as unstructured
paragraphs of narrative or text, as opposed to discrete data fields
reserved for specific pieces of information; and the inability of some
IT systems to access related data stored on another IT system in the
same hospital. All the case study hospitals were working to expand the
scope and functionality of their IT systems, but most officials at the
case study hospitals viewed full-scale automation of quality data
collection and submission through implementation of IT systems as, at
best, a long-term prospect.
CMS Has Processes for Ensuring Accuracy but Has No Ongoing Process for
Ensuring Completeness of Quality Data:
We reported in January 2006[Footnote 9] that CMS had processes for
assessing the accuracy of the quality data submitted by hospitals for
the APU program, but had no ongoing process in place to assess the
completeness of those data. To check accuracy, one CMS contractor
electronically checks the data as they are submitted to the clinical
warehouse. Another contractor conducts an independent audit by
comparing the quality data submitted by a hospital from the medical
records for a sample of five patients per quarter for each hospital to
the quality data that the contractor reabstracts from the same medical
records. The data are deemed to be accurate if there is 80 percent or
greater agreement between these two sets of results, which allows the
hospital to receive the full payment update from Medicare. However, we
also reported that CMS's determination as to whether hospitals met the
accuracy standard was statistically uncertain for some hospitals
because of the small number of records examined--five per quarter per
hospital, regardless of the hospital's size. Further, CMS did not have
an ongoing process for assessing the completeness of quality data
submitted by hospitals. Because of the purposes for which these data
may be used, there could be an incentive for hospitals to selectively
report data on cases that score well on the quality measures.
In our 2006 report we recommended that CMS take steps to improve its
processes for ensuring the accuracy and completeness of the hospital
quality data and CMS agreed the process needed to be improved. For
fiscal year 2008 and subsequent years it required that hospitals attest
each quarter to the completeness and accuracy of their data, including
the volume of data, submitted to the clinical warehouse.[Footnote 10]
Further, in its 2007 report to Congress that lays out a plan to
implement a value-based purchasing program, CMS recognized the need to
redesign the data infrastructure and validation process to support a
value-based purchasing program, by, for example, increasing the number
of patient medical records sampled from selected hospitals.
For more information regarding this statement, please contact Linda T.
Kohn at (202) 512-7114 or kohnl@gao.gov. Contact points for our Offices
of Congressional Relations and Public Affairs may be found on the last
page of this statement. Krister Friday, Shannon Slawter Legeer, and
Eric Peterson made key contributions to this statement.
[End of section]
Footnotes:
[1] The Medicare Prescription Drug, Improvement, and Modernization Act
of 2003 created a financial incentive for hospitals, and CMS
established the Reporting Hospital Quality Data for Annual Payment
Update (RHQDAPU) Program (the "APU program") to implement that
incentive. See Pub. L. No. 108-173, § 501(b), 117 Stat. 2066, 2289-90.
Most acute care hospitals (i.e., those paid under the Medicare
inpatient prospective payment system) receive an annual payment update
that increases the standardized payment amount that Medicare pays them
per patient, based on projected increases in hospital operating
expenses.
[2] See Pub. L. No. 109-171, § 5001(a), 120 Stat. 4, 28-29.
[3] The magnitude of the reduction in the annual payment update for
hospitals not submitting the quality data rose from 0.4 percentage
points to 2 percentage points, starting in fiscal year 2007.
[4] See GAO, Hospital Quality Data: HHS Should Specify Steps and Time
Frame for Using Information Technology to Collect and Submit Data,
GAO-07-320 (Washington, D.C.: Apr. 25, 2007) and Hospital Quality Data:
CMS Needs More Rigorous Methods to Ensure Reliability of Publicly
Released Data, GAO-06-54 (Washington, D.C.: Jan. 31, 2006).
[5] Centers for Medicare & Medicaid Services, Report to Congress: Plan
to Implement a Medicare Hospital Value-Based Purchasing Program (Nov.
21, 2007).
[6] See GAO-07-320.
[7] Throughout this statement, we use the term "abstractor" to indicate
hospital staff who are trained to follow a detailed protocol in order
to extract specified information in a consistent fashion from the
medical records of multiple patients.
[8] These represent the FTEs devoted specifically to quality data
collection and submission. Hospital officials noted that additional
FTEs were involved in analyzing the hospital's performance on the
quality measures and achieving improvements through changes in clinical
process and educational efforts with the hospital's clinicians.
[9] See GAO-06-54.
[10] See 72 Fed. Reg. 47130, 47364 (Aug. 22, 2007).
[End of section]
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