April 22, 2008

The Honorable Michael O. Leavitt

Chairman

American Health Information Community

200 Independence Avenue, S.W.

Washington, D.C. 20201

Dear Mr. Chairman:

The American Health Information Community Quality Workgroup (QWG) was
formed in 2006 and given the following broad and specific charges:

> **Broad Charge for the Workgroup:** Make recommendations to the
> American Health Information Community so that breakthroughs in health
> information technology (health IT) can provide the data needed for the
> development of quality measures that are useful to patients and others
> in the health care industry, automate the measurement and reporting of
> a comprehensive current and future set of quality measures, and
> accelerate the use of clinical decision support that can improve
> performance on those quality measures. Also, make recommendations for
> how performance measures should align with the capabilities and
> limitations of health IT.
>
> **Specific Charge for the Workgroup:** Make recommendations to the
> American Health Information Community that specify how certified
> health information technology should support the capture, aggregation,
> and reporting of data for a core set of ambulatory and inpatient
> quality measures.

This letter puts forth recommendations that advance the broad charge of
the workgroup; a recommendations letter presented to the Community in
March 2007 addressed the specific charge. In addition to the
recommendations for the broad charge, this letter describes the QWG's
approach to developing the recommendations, key themes that shaped the
recommendations, and important activities occurring today that impact
the recommendations. Appendix A contains a glossary of terms used in
this recommendations letter and Appendix B contains a diagram that gives
an overview of the roadmap of the QWG's vision for the future.

**The Quality Workgroup's Approach to Date for the Broad Charge**

In January 2007, the Quality Workgroup presented a vision for an ideal
future state for quality measurement and improvement to the American
Health Information Community (AHIC). The Quality Workgroup envisioned a
future where transparent reporting of quality performance and quality
improvement is used to inform decisions about patient care in a system
that is both information-driven and patient-focused. Thus, the vision
incorporates an expectation that quality measurement and improvement
activities will evolve from a site-centric focus to a patient-centric
focus. This evolution will require new policies and technical
advancements to collect, aggregate and analyze longitudinal data to
evaluate and improve the quality of patient care over defined time
periods and across care settings, at both the individual and population
levels. Moreover, the future state is strongly informed by the
perspective that the use of health IT can improve quality by both
reducing reporting burden and driving improvements in care at the point
of delivery.

After gathering testimony and conducting research, the Quality Workgroup
undertook a requirements analysis in August 2007 to define the
capabilities and policies needed to achieve the vision. The requirements
analysis identifies enablers and barriers in today's environment and
summarizes the policy, technical, and business requirements throughout
the health IT and quality communities needed for successful operation in
the future environment.

Based on the requirements analysis, the Quality Workgroup developed a
vision roadmap during Fall 2007 that articulates a path forward for
developing the health IT capabilities needed to achieve the future state
by 2014. The vision roadmap is predicated on several themes from the
vision and articulates key changes that must occur over the next six
years. However, these key changes will require the identification of
sources of funding and business models over this period of time to
support the creation of the infrastructure that will enable data sharing
and aggregation.

**Key Themes from the Vision Roadmap**

The roadmap is made up of twelve components that can be further divided
into policy-related components and technical data-oriented components as
shown in the exhibit below. Please see Appendix B for the detailed
vision roadmap.

+---------------------------------+------------------------------------+
| **Vision Roadmap Policy         | **Vision Roadmap Technical         |
| Components**                    | Data-Oriented Components**         |
+---------------------------------+------------------------------------+
| -   Business Case / Incentives  | -   Quality Data Set               |
|                                 |                                    |
| -   Measure Set Evolution       | -   Expanded Data Element          |
|                                 |     Standardization                |
| -   Legal Framework for Data    |                                    |
|     Sharing                     | -   Coding Improvements            |
|                                 |                                    |
| -   Data Stewardship            | -   Patient and Provider-Oriented  |
|                                 |     Clinical Decision Support      |
| -   Patient and Provider Record |                                    |
|     Matching                    |                                    |
|                                 |                                    |
| -   Patient Record              |                                    |
|     De-Identification           |                                    |
|                                 |                                    |
| -   Data Exchange and           |                                    |
|     Aggregation                 |                                    |
+---------------------------------+------------------------------------+

The following key themes emerged from the vision and inform the vision
roadmap:

-   **Patient-centric quality measurement:** The patient-centric
    emphasis in the broad charge indicates a need for longitudinal
    quality measurement and improvement, where data is collected and
    used to inform quality improvement across care settings and over
    time, thereby putting the patient at the focal point of any
    improvement efforts.

-   **Payment reform as an accelerator:** Payment reform is required to
    create incentives for both better-coordinated, high-quality health
    care and the development of a health IT infrastructure to enable the
    exchange of health information across care settings.  

-   **Importance of data exchange and aggregation:** Patient-centric
    care requires data exchange between providers and across care
    settings. Data aggregation is needed to create population-level
    metrics for the purpose of longitudinal quality measurement and
    improvement. Policy decisions and industry consensus must be
    established in order to further develop existing strategies and
    technological solutions, which include, but are not limited to:
    interoperable IT systems; protocols for physician and provider
    matching; and rules related to privacy and security.

-   **Alignment around national priorities for quality measurement:** A
    national priority setting process will focus the development of
    measures, the needed enhancements to medical coding, and the
    development of IT specifications and standards related to
    interoperability, data export and storage that are necessary to
    allow efficient assessment of the nation's progress towards quality
    goals.

-   **Proactive consideration of health IT needs to support quality:**
    The links between quality measurement and improvement and health IT
    need to be addressed proactively to achieve the future state of the
    vision. In the current system, quality measures are developed in
    silos within care settings, necessitating measure data harmonization
    in the testing and maintenance phases of measure development across
    care settings and across measure sets, and expending significant
    resources. A common set of data types or elements, i.e., a quality
    data set (QDS), can be used across quality measure development,
    health IT standards development and harmonization, guideline
    development, and clinical decision support during the design of
    measure sets to increase efficiency, lower net costs, and ultimately
    facilitate better care coordination.

-   **Support for a multi-source data strategy:** Much of the work
    toward the future state vision can begin now; there is no need to
    wait for full electronic health record (EHR) adoption. A
    multi-source data strategy can make use of existing sources of data
    (paper-based and electronic, administrative and clinical) for
    quality measurement while also integrating increasing amounts of
    clinical data from EHRs as it becomes available. An advantage of a
    multi-source data strategy would be the availability of cost of care
    data at the point of care so that providers are better able to make
    cost-effective decisions as appropriate.

The vision roadmap provides guidance for the efforts of current and
future quality improvement efforts for groups such as the AHIC and its
successor. The Quality Workgroup recognizes that the scope of the vision
roadmap is quite broad. Therefore, the workgroup has chosen a few
components about which to make formal recommendations, areas where
substantive progress could be made within the next year and which have
the potential to create a cycle of progress towards the eventual
realization of the future state vision. The recommendations are focused
on improving the quality of data used for quality measurement and
reporting through:

1)  Facilitating the alignment of initiatives to develop and implement
    measures for quality improvement.

2)  Developing and implementing a quality data set to support quality
    measurement and reporting.

3)  Prioritizing the creation of standards for structuring selected
    clinical data.

**Relevant Organizations and Projects**

Several key activities are occurring in parallel with the work of the
Quality Workgroup. These activities offer opportunities for alignment
with the vision roadmap and within the quality community's measure
development process, and offer potential inputs to a quality data set.

The *National Committee on Vital and Health Statistics* (*NCVHS) Quality
Workgroup* submitted a report to the Secretary of the Department of
Health and Human Services (HHS) on January 28, 2008, titled "Quality
Measurement and Public Reporting in the Current Health Care
Environment." The report focuses on the emerging use of a multi-source
data model to measure and report quality, and offers ten recommendations
in the areas of public reporting, data quality, performance measurement
reporting infrastructure, and the evolving landscape of performance
measures and EHRs.

At the direction of the Agency for Healthcare Research and Quality
(AHRQ), and in fulfillment of a prior Quality Workgroup recommendation,
the *National Quality Forum's Health Information Technology Expert Panel
(HITEP)* has completed an initial effort to prioritize and define types
of data elements for inclusion in EHRs to facilitate standardized
measurement and reporting for a core set of HQA and AQA measures. Some
of the recommendations from the HITEP have gone forth to the Healthcare
Information Technology Standards Panel (HITSP) as inputs to the
interoperability specifications to support the Quality Use Case. HITSP's
harmonized interoperability standards, which have been accepted by the
AHIC and will in time be endorsed by the Secretary of the Department of
Health and Human Services, will become requirements for EHR
certification by the Certification Commission for Healthcare Information
Technology (CCHIT). These data types could be considered as foundational
inputs to a quality data set.

The *National Quality Forum* has begun working in partnership with other
leadership organizations to establish national priorities and goals for
performance measurement and public reporting through its *Priorities
Partners* committee. The Priorities Partners committee anticipates
releasing their first set of national priorities for conditions as well
as certain cross-cutting areas in the summer of 2008.

The *Centers for Medicare and Medicaid (CMS)* is currently developing
its Continuity Assessment Record and Evaluation (CARE) instrument which
will contain key data items to support care transitions. In the Deficit
Reduction Act of 2005, Congress required CMS to develop a uniform
assessment instrument to measure and compare Medicare beneficiaries'
health and functional status across provider settings, at intervals, and
over time, upon hospital discharge. CMS is also required to test the
instrument's usefulness in a 3-year demonstration that would start in
early 2008. With this instrument, CMS is taking advantage of an
opportunity to move from the paper-based tools of the past to an
internet-based application for data collection.

The Better Quality Information to Improve Care for Medicare
Beneficiaries (BQI) Project is a CMS-funded quality improvement
organization (QIO) special project in which the Delmarva Foundation for
Medical Care has subcontracted with six communities, or pilot sites.
These pilot sites are testing methods to aggregate Medicare claims data
with data from commercial health plans and, in some cases, Medicaid, in
order to calculate and report quality measures for physician groups and,
in some cases, individual physicians.  The results from this project
will be used to guide future efforts for aggregating Medicare claims
data with data from other payers to produce quality measure results that
provide a more comprehensive picture of the quality of services being
provided by physicians to Medicare beneficiaries. 

The *Joint Commission* has developed a proposed list of data items that
should be transferred with a patient from a hospital to another provider
setting, whether by a paper or electronic system. The items were chosen
because they represent areas that have high impacts on safety and
quality of care but were not being addressed by other health IT
organizations. This data set was originally intended for use within the
Joint Commission's activities yet could become part of a data set across
organizations.

The *Quality Alliance Steering Committee (QASC)* is a collaborative
effort among existing quality alliances, government, physicians, nurses,
hospitals, health insurers, consumers, accrediting agencies and
foundations to dramatically improve the quality of health care across
the U.S. The vision of QASC is to advance high-quality, cost-effective,
patient-centered health care through the coordination of the various
groups that are working to promote public reporting of health care
provider information. QASC is currently testing approaches to combining
summary provider information from Medicare and private health plan data
at the national level, as well as developing a roadmap for integration
of administrative data and other data streams (e.g., clinical
registries, laboratory and imaging results reporting) to support quality
measurement and reporting.

*AHRQ* recently convened a meeting of medical specialty societies and
other selected experts to discuss strategies to obtain and use data
needed for quality improvement and to move measurement from an
environment of "data convenience" to an environment where clinical
guidelines drive development of clinical decision support and quality
measures. During this meeting, participants discussed the need for a
data strategy that would involve the coordination and alignment of
standards for structured clinical data to support effective use of
clinical guidelines, clinical decision support and quality measurement.
The outcomes of this meeting, and any follow-up meetings, will be useful
input for the activities recommended below.

The *Nationwide Health Information Network (NHIN)* is intended to
provide a secure, nationwide, interoperable health information
infrastructure that will connect providers, consumers, and others
involved in supporting health and healthcare. Often referred to as a
"network of networks," the NHIN will enable health information to follow
the consumer, be available for clinical decision making, and support
appropriate use of healthcare information beyond direct patient care to
improve health. Now in its second year of development, the NHIN has
awarded several grants for trial implementations through state and
regional health information exchanges. Participants will implement and
test the NHIN specifications, including the 2007 Quality Use Case, and
demonstrate their connectivity to other networks.

Plans are now underway to establish a successor to the AHIC as a
public-private partnership based in the private sector by fall 2008. The
*AHIC successor* will be independent and sustainable and will bring
together the best attributes and resources of public and private
entities. This new public-private partnership will develop a unified
approach to realize an effective, interoperable nationwide health
information system that supports the health and well-being of the people
of this country.

***Recommendations***

The Workgroup has identified the following actionable recommendations to
meet the broad charge.

**1. Facilitate the alignment of initiatives to develop and implement
measures for quality improvement.**

In its vision, the QWG states, "To realize the future vision, a unified
national agenda for quality measurement must be developed and must be
aligned with the common framework for measurement and use standard
definitions of terms to the extent possible. Measure developers will
have to collaborate to facilitate measure harmonization and vendors will
have to collaborate with the National Quality Forum (NQF) and quality
measurement organizations to encourage development and implementation of
common conventions and guidelines for measure development."

The QWG believes that quality improvement efforts and health IT efforts
could become better aligned to achieve this vision, creating synergies
among currently siloed efforts in order to streamline and automate the
quality measurement that would lead to improvement in the quality of
care. More specifically, HHS and the Quality Workgroup have recognized
an ongoing need to help coordinate the alignment of initiatives to
develop and implement measures for quality improvement across multiple
public and private organizations. In response to that need, staff from
the Office of the National Coordinator for Health IT (ONC) and members
of the Quality Workgroup organized two meetings of representatives of
relevant organizations in Fall 2007, resulting in the documentation of
the existing and future measure development process with a set of
diagrams. The organizations represented at these meetings included ONC,
AHRQ, CMS, National Quality Forum, HITSP, CCHIT, Integrating the
Healthcare Enterprise (IHE), and the AMA-NCQA Collaborative. The
participants at these meetings have expressed a common desire to
continue meeting regularly and more formally to further align the
various initiatives. The intent would be to identify areas of overlap or
areas where gaps exist with the goal of enhancing efficiency in the
measure development process, while avoiding the creation of extra burden
for participating organizations.

> **Recommendation 1.1: HHS, including the Office of the National
> Coordinator for Health IT and the Agency for Healthcare Research and
> Quality, in coordination with the Quality Alliance Steering Committee
> and the AHIC successor, should convene forums at regular intervals
> through December 2008 in order to facilitate the alignment of quality
> improvement and health information technology initiatives; in
> particular, those initiatives supporting quality measure development
> and implementation. Representatives of specific organizations should
> be included in the forums, such as the Centers for Medicare and
> Medicaid Services, the Federal Health Architecture, NIH/National
> Library of Medicine, the National Quality Forum, HITSP, CCHIT,
> Integrating the Healthcare Enterprise (IHE) and the AMA-NCQA
> Collaborative. Additionally, representatives of organizations such as
> guideline developers, AQA, HQA, the Joint Commission, and standards
> development organizations (SDOs) may be invited. As an outcome of the
> forums, HHS, in collaboration with the represented organizations,
> should develop a plan by October 28, 2008, for continued
> public-private cooperation to align the initiatives.**

**2. Develop and implement a quality data set to support quality
measurement and reporting.**

The Quality Workgroup recognizes opportunities to advance
standardization of the data elements that are inputs into quality
measures and care coordination efforts by supporting the development and
implementation of a quality data set. The QDS refers to a minimum set of
data elements or types of data elements that can be used as the basis
for developing harmonized and machine-computable quality measures. More
specifically, the QDS will serve as the basis for prioritizing data
elements for inclusion in EHRs and other health IT systems and for
prioritizing the development of standards for interoperability, data
export, and data storage and for prioritizing related certification
criteria.

It is anticipated that the development of the QDS will be dynamic and
iterative. The efforts to define the QDS will need to be anchored in the
clinician's view of data that is important for exchange across
caregivers and sites of care to support high quality, coordinated care.
At the same time, the QDS must enable evaluation of that care and
support the evolving quality measurement landscape, which is being
articulated, in part, by the National Quality Forum's Priorities
Partners initiative. The QDS will facilitate the exchange of information
across providers, institutions, and care settings to support care
coordination and transitions across care settings, thereby promoting a
more patient-centric approach to care delivery and a longitudinal
approach to quality improvement. The QDS will also serve as a means to
communicate clearly to providers and EHR vendors about which data
elements need to be reliably and accurately captured. The improved
availability of certain data elements will support the implementation of
clinical decision support systems that enhance patient care.

The value proposition for the establishment of the QDS is the savings
for several stakeholder groups that could be realized by increasing the
efficiency of the measure design and data definition process. Currently,
significant resources are expended by measure endorsers to reconcile
measure definitions across settings and to reconcile data definitions
across measure sets. IT vendors often must respond to these multiple
data definitions, hampering efforts to streamline product implementation
and provider workflow. If measure sets and data definitions were
harmonized during the design of measure sets, rather than downstream
during the testing and maintenance phases of measure development, much
of this retro-fitting work could be avoided and efficiencies could be
realized.

> **Recommendation 2.1: HHS, including the Agency for Healthcare
> Research and Quality and the Centers for Medicare and Medicaid
> Services, should collaborate with** **key private sector stakeholders,
> including measure developers, health IT vendors, clinicians,
> providers, and quality organizations, to define a quality data set
> that would support quality measurement that is automated,
> patient-centric, and longitudinal with the goal of improving care
> delivery and outcomes. The quality data set should include, at a
> minimum, relevant data captured during inpatient and physician office
> visits, and data required to support transitions of care among other
> provider settings.**
>
> **Recommendation 2.1.1: By December 31, 2008, the collaborative effort
> named in recommendation 2.1 should review existing data sets used for
> quality measurement, including those developed by the Centers for
> Medicare and Medicaid Services for its CARE tool, by the HITEP in its
> initial work, by the Joint Commission for transfers of care, and by
> others as appropriate, as the basis of a harmonized minimum set of
> data types or elements that can be used for automating quality
> measures. The effort should also incorporate into the harmonized
> quality data set those data types or elements needed to support
> measure sets and national priority areas. The effort should assign a
> priority level to each data type or element within the quality data
> set as an aid to implementation.**
>
> **Recommendation 2.1.2:  The Centers for Medicare and Medicaid
> Services, in expanding its set of quality measures, should work with
> the HHS Indian Health Service, [the Department of Veterans Affairs,
> and the Department of Defense]{.underline} to test the effectiveness
> of the harmonized minimum set of data types or elements, as developed
> in Recommendation 2.1.1, to capture and aggregate data from electronic
> health records.**
>
> **Recommendation 2.1.3: HHS, in coordination with the Quality Alliance
> Steering Committee and the AHIC successor, should maintain the minimum
> quality data set over time, modifying the quality data set as needed
> to address new measures and national priorities for quality
> measurement, and obtaining feedback on the quality data set from
> measure developers, health IT vendors, clinicians, providers, and
> quality organizations.**
>
> **Recommendation 2.2: Within three years following the identification
> of a quality data set, the Centers for Medicare and Medicaid Services
> should promote the use of the quality data set in its requirements for
> quality measurement and reporting across care settings.**
>
> **Recommendation 2.3: To accomplish some quality objectives,
> electronic health records must not only exchange data but also use and
> store certain data types or elements within electronic health records.
> Therefore, the Healthcare Information Technology Standards Panel
> (HITSP) should identify the data standards needed to fill identified
> gaps for inclusion of the identified quality data set for use in both
> ambulatory and inpatient electronic health records.**
>
> **Recommendation 2.4: The Certification Commission for Healthcare
> Information Technology (CCHIT) should consider developing the
> appropriate criteria necessary to support the inclusion of the
> identified quality data set in both ambulatory and inpatient
> electronic health records. This requirement should be submitted for
> inclusion on the CCHIT Roadmap in sufficient time for implementation
> in 2010.**
>
> []{.mark}

**3. Prioritize the creation of standards for structuring** **selected
clinical data.**

Currently, most quality measures are based on data abstracted from paper
records or from administrative data. Administrative data is easily
accessible, structured, and standardized, but lacks clinically rich
information. Clinical data, on the other hand, is not easily accessible
or useable. However, the common consensus among the quality improvement
and health information technology communities is that structured
clinical data could help drive significant improvements in the quality
of health care delivery. Progress to create this structure has been slow
and could benefit from increased coordination across standards
development organizations (SDOs).

Greater standardization of clinical data would facilitate consistent and
complete capture of clinical information in EHRs and support the use of
clinical decision support tools. Additionally, clinical data could be
used to help providers and quality improvement professionals better
understand outcomes and other aspects of patient care. Greater
standardization of clinical data would also support near-term efforts to
develop "clinically-enriched" data sources to support quality
measurement and reporting. The QASC is currently developing a roadmap
for aggregating administrative data and clinical data (e.g., registries,
laboratory results reporting, medications) to produce
clinically-enriched data sources capable of supporting a broader range
of quality measurement and reporting requirements.

> **Recommendation 3.1: The Agency for Healthcare Research and Quality,
> in collaboration with the Office of the National Coordinator for
> Health IT and in consultation with NIH/National Library of Medicine,
> should conduct an environmental scan of current initiatives where
> electronic clinical data is being used to inform quality improvement
> initiatives in order to identify areas where data standards for
> structured clinical data are needed. Initiatives for review include,
> but are not limited to, the** **Better Quality Information to Improve
> Care for Medicare Beneficiaries (BQI) pilots and the Nationwide Health
> Information Network (NHIN) Trial Implementation sites. In preparing
> the environmental scan, which should be completed by November 30,
> 2008, experts could be convened from the BQI and NHIN sites that have
> experience in combining clinical and administrative data from multiple
> sources.**
>
> **Recommendation 3.2: The Agency for Healthcare Research and Quality,
> in collaboration with Office of the National Coordinator for Health IT
> and in consultation with NIH/National Library of Medicine, should use
> the results of the environmental scan from Recommendation 3.1 as well
> as the work of the National Quality Forum's Health Information
> Technology Expert Panel (HITEP) to develop recommendations to the
> Healthcare Information Technology Standards Panel (HITSP) for the
> identification of standards for structuring clinical data. These
> recommendations should be submitted to HITSP by January 31, 2009.**
>
> **Recommendation 3.3: Through its convening function, the Agency for
> Healthcare Research and Quality, in collaboration with the Office of
> the National Coordinator for Health IT and in consultation with
> NIH/National Library of Medicine, should produce an action agenda by
> March 31, 2009. The action agenda should prioritize areas for
> structuring selected clinical data used across care settings, and
> identify opportunities to align efforts that are already underway to
> create standards related to clinical data. This work should be guided
> by an expert panel comprised of members of the EHR vendor community,
> clinicians, providers, specialty societies, standard development
> organizations, the National Quality Forum, guideline developers,
> measure developers, health plans, the Quality Alliance Steering
> Committee, the AHIC successor and others as appropriate, to ensure
> that standardization of documentation is aligned with care delivery
> and the development of executable guidelines and automatable quality
> measures**.

These recommendations are supported by information obtained through
research and testimony to the Quality Workgroup, which is contained in
the supporting documents available at <http://www.hhs.gov/healthit/>.

Thank you for giving us the opportunity to submit these recommendations.
We look forward to discussing these recommendations with you and the
members of the American Health Information Community.

Sincerely yours,

/Carolyn Clancy/ /Richard Stephens/

Carolyn Clancy Richard Stephens

Co-chair, Quality Workgroup Co-chair, Quality Workgroup

**Appendix A:  Glossary of Terms Relevant to the Quality Data Set**

**Data Element:**  A discrete unit of data (such as patient birth date
or principal diagnosis) of interest to an organization. It is a unit of
data for which the definition, identification, representation, and
permissible values are specified by means of a set of attributes.

**Data Format:** A description of the allowed format for the values of a
data element.

**Data Standard:**  A standard that will enable information systems to
exchange clinical systems in a private and secure manner both within and
between institutions.

**Data Strategy:**  A well-defined approach to collecting and using data
to support a business process that:

-   has been agreed upon by a group of experts

-   has been publicly vetted

-   provides rules, guidelines, or characteristics

-   helps to ensure that materials, products, processes, and services
    satisfy the needs that result from the intended use of the data

-   is available in an accessible format

-   is subject to an ongoing review and revision process

**Data Type:** A group or category of data elements.

**Data Value:** One of the allowable values of a data element.

**Measure Specification:**  Detailed instructions necessary to convert
health care data into a quality measure

**Quality Data Set:**  A minimum set of data types or elements that can
be used as the basis for developing harmonized and machine-computable
quality measures.  The QDS will serve as the basis for prioritizing data
elements for inclusion in EHRs and other health IT systems and for
prioritizing the development of standards for interoperability, data
export, and data storage and for prioritizing related certification
criteria.

*Sources:  HITSP Glossary v.1.0; Quality Use Case; The Joint Commission
Specifications Manual for National Hospital Quality Measures, Version
2.3b; Connecting for Health; wikipedia.org; National Quality Forum's
Health Information Technology Expert Panel report*

**Example:**

> Data Type: Diagnosis
>
> Data Elements: Principal Diagnosis, Secondary Diagnoses
>
> Data Value: Principal Diagnosis = 428 Heart Failure
>
> Data Standard: ICD9-CM
>
> Data Format: alphanumeric

In this example, the data element is included in both the numerator and
denominator statements of many measure specifications.  To produce a
measure, data elements are connected through algorithms which specify
sequences of retrieval, aggregation and required values for data
elements.

**Appendix B: A Roadmap for Developing Health IT Capabilities to Achieve
the Quality Workgroup Vision**