Quest Diagnostics -- Ask at Order Entry Insight 20140707

Quality Lab-EHR Interoperability
Enabling Effective Patient Data Collection
Ask at Order Entry
Insight into Ask at Order Entry (AOE) functionality using
international standards as directed by the U.S. Dept. of HHS
July 2014
By Ken McCaslin, FHL7
Freida Hall, FHL7
Virginia Sturmfels, MT (ASCP)
Keith C. Drake, Ph.D.

Table of Contents
About the Authors 3
Overview 4
Organization/Target Audience 5
History of Events 5
The Goal of the AOE Standardization 6
AOE Concepts 6
AOE Structure 7
Ask at Order Entry – Why this is Necessary 9
Benefits from Standardized AOEs 10
Next Steps for Success 11
Information Technology/Electronic Health Record (EHR) 12
The Future Direction of AOEs 18
Appendix A - AOE 19
Appendix B - Acronyms 23

About the Authors
Virginia Sturmfels
Virginia is the Manager of Medical Regulatory Affairs at Quest Diagnostics
and Co-Chair of S&I Framework’s Vocabulary Work Group. Virginia has been
an active participant on the LRI and LOI Work Groups. She also participated
in the ACLA HIT Committee’s work effort that produced the “HL7 Version 2
Implementation Guide: Laboratory Test Compendium Framework, Release 1 also
known as the eDOS IG.1
”
Freida Hall
Freida is the Manager of Healthcare Standards at Quest Diagnostics, Co-
Chair of HL7’s Technical and Support Services Steering Division, Co-Chair of
HL7’s Project Services Work Group, is a member of HL7’s Technical Steering
Committee and past HL7 Board Secretary. She also is Co-Chair of S&I
Framework’s eDOS IG Work Group. Freida is in the inaugural class (2010) of
HL7 Fellows and has held several other roles in healthcare.
Ken McCaslin
Ken is the Director of Healthcare Standards at Quest Diagnostics, Co-Chair
of HL7’s Electronic Services Work Group, Co-Chair of American Clinical
Laboratory Association’s (ACLA) Health Information Technology (HIT)
Committee and Chair HL7’s Technical Steering Committee and HL7 Board
Member. He is Co-Chair of S&I Framework’s LRI and LOI IG Work Groups. Ken
also is in the inaugural class (2010) of HL7 Fellows and has held several other
roles in healthcare standards development. He participated in the ACLA HIT
Committees work effort that produced the “HL7 Version 2 Implementation Guide:
Laboratory Test Compendium Framework, Release 1” also known as the eDOS IG.
Keith C. Drake, Ph.D.
Keith is the managing Executive of the Quest Diagnostics Health IT Quality
Solutions™ Program. The Program’s objective is to promote quality Lab-EHR
interoperability by identifying and recognizing commercial electronic health
record (EHR) systems meeting Quest Diagnostics high standard for result
and order transactions, interface implementation and maintenance, and B2B
business processes.
1
This guide can be found at http://www.hl7.org/implement/standards/product_brief.cfm?product_id=151 at Health Level Seven International (HL7). It is an American National Standards Institute (ANSI)
Informative standard.

Overview
Upon receipt of a laboratory test, the laboratory may request additional
information to accompany the order and collected sample. In some cases, no
additional information is required; the test request is simply accompanied by
the appropriate specimen. In other instances, additional information beyond
patient name, age, and gender provide supplementary content necessary to
fully report the ordered test. This supplemental information often is produced
by additional test-specific questioning of the ordering provider. The result of
these questions often is designated as Ask at Order Entry (AOE) information.
AOE information should be provided as results attached to the Order Code that
they impact. This additional data is used by the laboratory in conjunction with
the test result to provide the physician with a patient-specific result.
This paper addresses AOEs based on the assumption of electronic ordering
of laboratory tests. Therefore, its discussion is based on Health Level Seven
International’s® (HL7®)2
Order Message structure, specifically version 2.5.1 to
be consistent with the federal initiatives on Meaningful Use3
(MU). Laboratory
Orders are specifically addressed in MU Stage 34
(MU3) and have a specific
Implementation Guide (IG) called the Laboratory Order Interface IG (LOI IG5
).
There is a companion IG called the electronic Directory of Services IG
(eDOS IG6
) that provides the laboratory’s full test compendium to the
Electronic Health Record (EHR) system using HL7’s Master File Updates.7
AOEs
are provided in the eDOS IG including the laboratory’s local code, description
(the question), and when available, the Logical Observation Identifiers Names
and Codes (LOINC).
Work is under way in the health IT industry to create AOE standards to define
how the AOE is identified, the data type the AOE values should support, and
a potential list of ordinals that will be used to respond to the AOE request. In
some cases, the data type directs the use of an HL7 table as identified in the
underlying standard. In other cases, the data type is designed to have multiple
inputs, and without an identified terminology, the test result may not be
structured to provide seamless processing and reporting. These are the issues
this paper addresses.
2
Health Level Seven International ® (HL7®) is a healthcare standards body focused on the clinical and administrative data standards. This body has two message standards Version 2.x and Version 3.0.
Additional HL7 information can be found at http://www.hl7.org .
3
Meaningful Use (MU) is an initiative from the Health and Human Services (HHS) under the auspices of the Office of the National Coordinator of Health Information Technology (ONC). The initiatives
have been released in stages beginning with Stage 1 in 2010, Stage 2 in 2012 and Stage 3 is anticipated to be released in January 2014. The initiatives for each stage of MU are driven by participating
members of the community. That work is posted and maintained on the Standards and Interoperability Framework Initiative (S&I Framework) wiki for all to view. That wiki can be found at http://wiki.
siframework.org/ .
4
Meaningful Use Stage 3 Laboratory Orders can be referenced on the S&I Framework wiki at: http://wiki.siframework.org/Laboratory+Orders+Interface+Initiative
5
The LOI IG can be found at: http://wiki.siframework.org/Laboratory+Orders+Interface+Initiative
6
The eDOS IG is defined as “HL7 Version 2 Implementation Guide: Laboratory Test Compendium Framework, Release 1”can be found at: http://www.hl7.org/implement/standards/product_brief.
cfm?product_id=151
7
HL7 Master File Updates can be found in chapter 8 of version 2.x. In this case, eDOS IG is based on chapter 8 of HL7 version 2.5.1.
Work is under way in
the health IT industry to
create AOE standards.

Organization/Target Audience
The majority of this paper is assumed to be of interest to all audiences; however,
information more technical in nature is included in the Information Technology/
Electronic Health Record (EHR) section. The technical information is written for
the EHR community and information technology (IT) professionals. It assumes
a working knowledge of HL78
(specifically version 2.5.1 through 2.8.1), how the
HL7 message is constructed, ANSI documentation processes, LOINC®9
, and
RELMA®. In most instances discussions about HL7 messages, segments, and
fields will be limited.
History of Events
Several years ago, a group of healthcare standards pioneers in the laboratory
industry gathered in Washington D.C., home of the American Clinical
Laboratory Association (ACLA), to develop the first electronic delivery of a
laboratory’s Directory of Services (DOS) using an existing standard, in this
case HL7 version 2.6 known as eDOS IG. That first IG used HL7 Chapter 8 –
Master Files to develop the messages necessary to send the DOS using existing
connectivity already employed to support the delivery of laboratory orders
and results. This breakthrough IG can be found at HL7 as an ANSI Standard
titled “HL7 Version 2 Implementation Guide: Laboratory Test Compendium
Framework, Release 1“ (http://www.hl7.org/implement/standards/product_
brief.cfm?product_id=151)
In 2012, this guide was adopted by the Standards and Interoperability
Framework Initiative (S&I Framework) to be part of the next stage of
Meaningful Use under the eDOS IG Work Group.10
This Work Group, in
collaboration with the Vocabulary Work Group11
has been standardizing the
AOE process and broadening the eDOS IG to support the expanded standards
being developed for the AOEs. Quest Diagnostics employees Freida Hall and
Virginia Sturmfels are among the leadership of these two groups. The outcome
of their work is an updated eDOS IG that will be known as “HL7 Version 2
Implementation Guide: Laboratory Test Compendium Framework, Release 2.“
Appendix A of this Implementation Guide is the initial work done by these two
groups on the development of guidance for standard AOEs. This new document
has been released as a Draft Standard for Trial Use (DSTU) with anticipation
that further updates may be necessary after an initial pilot period. “Release
3” likely will start development in 2014 and should result in the Normative
standard. In addition, the Release 2 document was aligned with its companion
guides: the Laboratory Results Interface Implementation Guide (LRI IG) and the
Laboratory Orders Interface IG (LOI IG).
8
For more information about HL7 messages, segments and fields see the HL7 version 2.5.1 standard. It can be found at: http://www.hl7.org/implement/standards/product_brief.cfm?product_id=185
9
LOINC® is a registered trademark of the Regenstrief Institute and can be found at http://www.regenstrief.org/ and the LOINC standard can be found at http://www.loinc.org/. It will require accepting the
copyright notice and license agreement before entering the LOINC database.
10
The eDOS Work Group can be found at: http://wiki.siframework.org/LOI+-+eDOS
11
The Vocabulary Work Group can be found at: http://wiki.siframework.org/LOI+-+Vocabulary+WG

The Goal of AOE Standardization
The goal of AOE standardization is a seamless gathering of AOE information
from the ordering provider by the EHR, electronically transmitting the
information in the HL7 Order Message, and uploading it into the patient record
at the laboratory. The benefits of this process are: 1) the laboratory does not
manually enter the AOE information into the LIS thereby saving costs and
reducing errors, and 2) the test report sent back to the ordering provider
automatically echoes the AOE information used to construct a patient-specific
test value. These goals can only be reached if there is a reliable process
that involves both the EHR and Laboratory Information Systems (LIS) using
the same formats. Additionally, the ordering provider must use the same
terminology as the laboratory, enabled by agreement on standards that can be
supported.
AOE Concepts
AOEconceptscanbecategorizedintotwogeneralcategories:1)AdditionalInformation,
and 2) State of other results. State of other results is very different from previous
results. An example is an AOE that asks “Was the previous result abnormal?” This
AOE question is not asking for the previous results, it is asking the clinician to define
if the previous results were normal or abnormal. In this case, a normal answer
for this question would be “No” and an abnormal answer would be “Yes”.
In the LOI IG, the user will find the HL7 message structure to support previous
results. This message structure should be used when sending previous results.
However, State of Other Results is an AOE often asked as a Yes/No response or
in a similar fashion. Therefore, this remains as an AOE.
The other AOE type is the Additional Information. In this area we have two
categories of: 1) Information about the specimen, and 2) Information necessary
in providing laboratory results. Information about the specimen can define how
it was collected, type of specimen, quantity of specimen, or timing of collection
of specimen. This information may modify how the specimen is processed at
the laboratory or alter a procedure.
With the information necessary in providing laboratory results, the AOEs may
require the ordering provider to provide clinically significant information, such as
patient race or ethnicity. The AOE may ask for clinical information such as Last
Menstrual Period (LMP) in a date format or other required data in a structured
format so that the information can be used for calculations and risk assessment.
AOE benefits:
1) the laboratory does
not manually enter the
AOE information into
the LIS thereby saving
costs and reducing
errors, and 2) the test
report automatically
echoes the AOE
information used to
construct a patient-
specific test value.

AOE Structure
There are several components to the AOE: The identifier, the description (also
the question being asked), the format of the data (using data types12
), and in
some instances the accepted values for a given AOE as illustrated in the table
below. Additional information on Data Type is provided in the Information
Technology/Electronic Health Record (EHR) section.
Figure 1-1 – Example of AOE requirements table from S&I Framework13
Example LOINC AOE Questions
LOINC
Code
LOINC
Long Name
Alias Name Data
Type
Usage Note
11778-8 Delivery date
estimated
Estimated
due date
DT
11884-4 Gestational age
Estimated
NM Be sure to populate
the units in OBX-6.
in weeks
Gestational
age (weeks)
the units in OBX-6.
In some cases, there are answers to AOE questions provided by LOINC as
outlined in this paper and illustrated in Figure 1-2 below.
LOINC
Code
LOINC
Long Name
Alias
Name
Suggested
HL7 Data
Type OBX
response
Usage Note
Usage Note
32624-9 Race CWE PID-10 (Race) value is provided for
demographic, not clinical use. An
AOE must be provided for those tests
where Race drives the interpretation of
results. The value must be determined
by the ordering provider and must be
sent as an AOE OBX. Refer to LOINC
for suggested answer list. More specific
race values are available, but not
limited to, those found in the CDCREC
document if needed for AOE. (http://
www.cdc.gov/nchs/data/dvs/Race_
Ethnicity_CodeSet.pdf)
12
For a discussion on data types; primitive and complex see: http://help.adobe.com/en_US/AS2LCR/Flash_10.0/help.html?content=00000029.html Also see chapter 2 of the HL7 Version 2.5.1.
13
Is called HL7 Version 2.5.1 Implementation Guide: S&I Framework Laboratory Test Compendium Framework, Release 2 US Realm and can be found at: http://www.hl7.org/implement/standards/prod-
uct_brief.cfm?product_id=151
14

Figure 1-2 depicts the Ask on Order question “Race,” which may have an impact on the
laboratory result value or reference range for certain laboratory tests. As explained in the
S&I IG Usage Notes, if the patient’s race is not pertinent for the clinical test, it is reported
along with other demographic data (date of birth, address, etc.) in the HL7 Message,
and an AOE is not required. To view the LOINC suggested answer list for “Race,” one first
needs to visit the LOINC.org® website.15
By entering 32624-9 to search for the LOINC
code, its description and several other properties of the code are displayed. The LOINC
suggested answer list can be viewed by clicking the hyperlinked code, which will display
a second screen showing other attributes of the code and suggested answers as shown
in Figure 1-3 below. In this example, the five values displayed in the LOINC answer list are
the same as those developed by the Office of Management and Budget (OMB)16
and used
in Meaningful Use to report demographics. They also are used by the Census Bureau and
other federal agencies.
The Centers for Disease Control developed a list of more granular race codes, which
may be used when a more specific value can be obtained or is required for electronic
public health reporting purposes.17
The list of Race codes is hierarchal in nature, meaning
granular codes can “roll up” to the five OMB values. The sequence number and answer
ID ‘LL’ number shown in Figure 1-4 LOINC Race – expanded display are not the values
messaged for Meaningful Use AOEs; instead use the top hierarchy of the CDC code list
(R1, R2, etc.) or if necessary, a more granular value from the CDCREC table.
Figure 1-3 – LOINC Race
LOINC Code LOINC Long Name
1002-5 AMERICAN INDIAN OR ALASKA NATIVE
2028-9 ASIAN
2054-5 BLACK OR AFRICAN AMERICAN
2076-8 NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER
2106-3 WHITE
15
LOINC® is a registered trademark of the Regenstrief Institute and can be found at http://www.regenstrief.org/ and the LOINC standard can be found at http://www.loinc.org/. It will require accepting the
copyright notice and license agreement before entering the LOINC database.
16
http://www.whitehouse.gov/omb/inforeg_statpolicy/#dr Data on Race and Ethnicity.
17
http://www.cdc.gov/nchs/data/dvs/Race_Ethnicity_CodeSet.pdf

Figure 1-4 LOINC Race – expanded display
Some of the AOEs will suggest LOINC values or other values suggested by the
IG authors. Those values will reference the best place to find more information
about the AOEs. The ultimate goal is to develop a precise process for defining
AOEs, determine the appropriate data type based on HL7 Table 125, and (if
possible) suggest consistent responses. These consistent responses provide for
a reliable structured data process that is easily understood and, if necessary,
capture additional information from the source for the standard data input.
A standard data input eliminates the concerns of mistyping information and
of multiple concepts for the same responses. It is recommended that (when
possible) the available options be presented to the ordering provider so that
they can easily select the appropriate response.
Ask at Order Entry – Why this is Necessary
Laboratory tests by themselves provide valuable diagnostic insight to a patient’s
illness/wellness status. In some cases, the additional information provided
by AOEs allows the laboratory to present the ordering provider with greater
insight. Some computations based on AOE information can easily be found
on the Internet, with the outcome determined by a simple calculator. The
laboratory regularly provides calculated values based on AOEs, for thousands of
patients daily, thereby reducing the opportunity for error and programmatically
determining if the resulting calculation is within appropriate normal ranges. This
automated approach also makes better use of the ordering provider’s valuable time.
In some cases, the AOEs provide the laboratory with valuable information about
the specimen collection site and the source and process used to collect the
patient’s specimen. The laboratory therefore is able to properly prepare the
specimen for testing, using appropriate media or reagents. The additional AOE
information may also assist the pathologist in providing an accurate assessment
of the specimen.
AOEs provide the
laboratory with valuable
information about the
specimen collection
site and the source and
process used to collect
the patient’s specimen.

18
Health Information Exchange among U.S. Non-federal Acute Care Hospitals: 2008-2013; Matthew Swain, MPH; Dustin Charles, MPH; Michael F. Furukawa, PhD; ONC Data Brief, No. 17, May 2014.
19
Use and Characteristics of Electronic Health Record Systems Among Office-based Physician Practices: United States, 2001–2013; Chun-Ju Hsiao, Ph.D., and Esther Hing, M.P.H.; NCHS Data Brief, No. 143, January 2014.
20
http://www.healthit.gov/sites/default/files/acceleratinghieprinciples_strategy.pdf
21
Institute of Medicine report: Health IT and Patient Safety, Building Safer Systems for Better Care, http://www.iom.edu/Reports/2011/Health-IT-and-Patient-Safety-Building-Safer-Systems-for-Better-Care.aspx
22
45 CFR §170.314(b)(5) Incorporate Laboratory Tests and Values/Results
The inclusion of
patient specific
information obtained
from AOEs will provide
patients with customized
data regarding their
health status
Benefits from Standardized AOEs
The Department of Health and Human Services (HHS) has stated that the
exchange of health information should be both interoperable and transmitted
electronically across a myriad of information systems. These objectives enable
the nation to realize a patient-centered, value-driven health care system.
However, gaps and challenges remain for the widespread use of interoperable
systems and Health Information Exchanges (HIEs) across providers, settings
of care, consumers and patients, and payers. Health care providers and their
vendors lack a business imperative to electronically share person-level health
information across providers. In 2013, only 42% of hospital exchanged clinical
care summaries electronically with providers outside the hospital and only 37%
used electronic exchange to share medication histories with those providers.18
Moreover, in 2013, only 48% of office-based physician were using a basic
EHR system.19
Similarly, consumers and patients are not actively engaged in
accessing and using their personal health information and requesting that their
providers do the same.20
However, the April 2014 U.S. Department of Health
and Human Services rule requiring labs to directly provide patient direct access
to their test reports, is expected to result in increased engagement
To accelerate health information exchange and interoperability, laboratories and
EHR Vendors are under pressure from multiple federal agencies to standardize
data and their exchange, due to findings by the Institute of Medicine (IOM).
These findings indicate that appropriately implemented health information
technology systems improves provider’s performance, improves communication
with patients, and enhances patient safety.21
Specifically for laboratory results,
the Meaningful Use Stage 2 incentive program administered by CMS and ONC
requires EHR technology designed for an ambulatory setting to be capable of
electronically receiving, incorporating, and displaying clinical laboratory tests
and values/results in accordance with the HL7 Version 2.5.1 Implementation Guide:
S&I Framework Lab Results Interface (LRI) and with laboratory tests represented in
LOINC®.22
Using LOINC codes and other structured data enables decision support
and provider alerts in EHR systems, as well as meeting Meaningful Use requirements.
As the healthcare community moves toward more personalized medicine,
the inclusion of patient specific information obtained from AOEs will provide
patients with customized data regarding their health status.
In The Quality of Health Care Delivered to Adults in the United States, the authors note:
“As a nation, we are transforming health care delivery into a system that
is patient-centered and value-based. Existing Medicare and Medicaid
programs and initiatives, as well as new programs authorized by the
Patient Protection and Affordable Care Act (Affordable Care Act),
focus on new service delivery and payment models that encourage and

facilitate greater coordination of care and improved quality. These new
initiatives include Accountable Care Organizations (ACOs), bundled
payments, health and medical homes, and reductions in payment for
hospital readmissions. Critical to the success of these programs and
the ultimate goal of a transformed health care system is real-time
interoperable HIE among a variety of health care stakeholders (clinicians,
laboratories, hospital, pharmacy, health plans, payers and patients)
regardless of the application or application vendor. Greater access to
person-level health information is integral to improving the quality,
efficiency, and safety of health care delivery.”23
Next Steps for Success
CMS and ONC reported in their Principles and Strategy for Accelerating Health
Information Exchange (HIE) published August 7, 201324
, that stakeholders
should advocate expansion of LOINC usage to accelerate health information
exchange (excerpt below):
Laboratory Tests/Results Exchange
Commenters raised concern about barriers to using standardized
electronic laboratory results including the cost of interfaces and the
current trend towards creating preferred laboratories. Commenters
suggested finalizing the Proposed Rule entitled “Clinical Laboratory
Improvement Amendments (CLIA) Program and HIPAA Privacy
Rule; Patients’ Access to Test Reports”25
to expand patients’ rights
to access health records directly from laboratories, which has since
been finalized. Commenters also advocated for further integration of
Logical Observation Identifiers Names and Codes (LOINC®)26
into every
possible program as the best method to increase interoperability and
the electronic exchange of laboratory test results. To make progress in
this area, commenters identified mapping other standards to LOINC®
as a critical step in facilitating the adoption of LOINC® and suggested
that HHS could provide such mapping as it has done in other areas. A
few commenters recommended that CLIA regulations be revised to
require laboratories to send results using LOINC®. Commenters also
suggested that ONC ensure that laboratory-related certification criteria
under the ONC HIT Certification Program (e.g., 45 CFR § 170.314(b)(5)
and (6)), including the Laboratory Results Interface (LRI) specification,
are consistent with 42 CFR 493.1291 and CLIA guidance. Once these
certification criteria are consistent, some commenters suggested that
23
McGlynn, E.A., S.M. Asch, J. Adams, J. Keesey, J. Hicks, A. DeCristofaro, and E.A. Kerr, “The Quality of Health Care Delivered to Adults in the United States.” New England Journal of Medicine 2003 348:
2635-45. See also, Rosenbaum, R., “Data Governance and Stewardship: Designing Data Stewardship Entities and Advancing Data Access,” Health Services Research 2010 45:5, Part II.
24
http://www.healthit.gov/sites/default/files/acceleratinghieprinciples_strategy.pdf
25
76 Fed. Reg. 56712 (Sept. 14, 2011)
26
LOINC® is a database of universal standards for identifying medical laboratory observations.

HHS consider offering a “safe harbor” or allow anyone who appropriately
uses a laboratory system certified to the laboratory-related certification
criteria to be deemed in compliance with CLIA regulations.
Information Technology/Electronic Health Record (EHR)
AOE Format
The format of the HL7 message requires that the owner of the identifier be
included. This requirement is forced through the data type of the HL7 field, which
in this case is the OBX segment position 3 (OBX-3). OBX-3 is known as the
Observation Identifier which uses the CWE (Coded With Exceptions) data type.
The CWE data type is a complex data type because it has multiple components.
Depending on its version, the CWE data type it can have 11 or more components.27
For this discussion, we are interested only in the first six components, which
are broken down as twin triplets. Essentially, the two components in each of the
three sets are equivalent to one another: components 1 and 4 (the identifier) are
the same; as are components 2 and 5 (description or question) and components
3 and 6 (source of identifier). Note that components 4 through 6 are noted in the
data type as the alternative to components 1 through 3. This designation provides
the ability to message local laboratory codes with a standard code specification
such as LOINC.
Maternal Serum Screening – Hardcopy Requisition
The Maternal Serum Screening Profile has many complexities based on the
trimester of the mother upon sample collection. The following example is based
on a 2nd
Trimester Screening Test named Quad Screen (Quest Diagnostics Order
Code 30294).
To share a test that has more AOEs, the example also will share the additional
AOEs needed for the 1st Trimester Screen HyperGly-hCG (Quest Diagnostics
Order Code 16020) as noted on the example Quest Diagnostics hardcopy
Requisition.28
27
See HL7 version 2.5.1 chapter 2 for details about the components of CWE
28
This information was taken from the Quest Diagnostics hardcopy requisition for Maternal Serum Screening (MSAFP) revision date 3/2013. It should be noted that this revision breaks out questions
that need to be responded to by the ordering provider at Order time. For more information, the requisition can be found at: https://login6.smartworks.com/Assets/MET_32CE0969-7EFF-4CD9-A0D1-
A80870D1DC05/QD20330-NW_Proof.pdf

Also provided on the requisition are the AOE questions:
Because maternal serum screening test results are influenced by certain patient
characteristics, the following data must be provided with the specimen, in order to
permitaccurateinterpretationoftheresults.Thequestionsthatarealwaysaskedare:29
Date of Birth
Collection Date
Maternal Weight
Estimated Date of Delivery (EDD)
How was the EDD determined:
Ultrasound,LastMenstrualPeriod(LMP)orPhysicalExam
Mother’s Ethnic Origin: African American, Asian, Caucasian, Hispanic,
and Other
Number of Fetuses: One, two, or more
When more how many:
Yes/No questions:
Patient is an insulin-dependent diabetic prior to pregnancy
This is a repeat specimen for this pregnancy
Previous Pregnancy with Down Syndrome
Yes/No Questions requiring more information if Yes
History of Neural tube defect – If yes explain
Pregnancyisfromadonoregg–Ageofdonorattimeofeggretrieval:
Request for other relevant clinical information
29
Refer to Appendix A for additional information on AOE/LOINC mapping

Through an initiative
within the S&I
Framework, there is an
effort to standardize the
LOINC codes for AOEs.
Additional questions for the first trimester are:
Ultrasound Date
Ultrasonographer’s name:
NTQR or FMF
Ultrasonographer’s ID#
Location ID#
Reading Physician ID#
Crown Rump Length (CRL)
Nuchal translucency (NT)
Nasal Bone: Present, Absent, Not Assessed
If twin gestation, are the twins: Dichorionic, Monochorionic
Twin B Crown Rump Length (CRL)
Twin B Nuchal Translucency (NT)
Twin B Nasal Bone: Present, Absent, Not Assessed
Construction of the Electronic Ask at Order Entry components
This construction takes on a slightly different process; instead of clicking boxes
or filling in data above a blank line, the EHR must guide the ordering provider
through the process. The EHR system provides navigation tools; i.e., answer
drop-down choices, system auto population of the answers, etc.
The collection date should be captured in the designated HL7 fields. The
SPM segment field 17 is the Specimen Collection Date. Patient Date of Birth
is messaged in the PID segment in field 7 Date/Time of Birth. These fields
are critical because without the DOB and the collection date a test cannot
be reported with the appropriate reference range. The remaining data on the
hardcopy requisition are Ask at Order Entry questions. The best method for
the data to be interchanged between an EHR and the performing laboratory are
OBX segments trailing the OBR of the test in question.
The OBX segment contains the result field where the response to the AOE
question will be placed. This is OBX-5, called Result Value. The structure of
this field is derived from OBX-2, Value Type. Value Type is pulled from HL7
table 0125, which effectively defines the data types. This approach allows
the response to be structured in a very deliberate way based on the selected
data type. Historically, the Value Types used were typically Text Data (TX) or
String Data (ST). This definition was used for cases including information that
should have been formatted as date, timestamps, address, person, or other
information.
Through an initiative within the S&I Framework, there is an effort to standardize
the LOINC codes for AOEs. In addition, this effort is attempting to structure
further the AOEs by specifying the most appropriate data type for a given
LOINC code in order for the content to be sent to the laboratory. As an
example, Last Menstrual Period (LMP) would have a date data type to ensure a
consistent structure for information transmission.

Example LOINC AOE Questions
LOINC
Code
LOINC
Long Name
Alias Name Data
Type
Usage Note
11778-8 Delivery date
estimated
Estimated
due date
DT
Estimated
the units in OBX-6.
in weeks
Gestational
age (weeks)
the units in OBX-6.
Delivery Date Estimated above in Figure 1-5, LOINC code 11778-8, must be
sent as data type DT for Date. Data Types can be found prior to HL7 version
2.4 in chapter 2 and beginning in version 2.5 in chapter 2A. The DT data type
is constructed in a unique fashion. The EHR will need to prompt for input of the
data and then reformat it from what the user will be comfortable inputting to
how electronically it will be sent. Refer to Figure 1-6 below.
Figure 1-6 – HL7 Component Table
SEQ LEN DT OPT TBL# COMPONENT NAME COMMENTS
8 Date
• Definition: Specifies the century and year with optional precision
to month and day.
• Maximum Length: 8
• As of v 2.3, the number of digits populated specifies the precision
using the format specification YYYY[MM[DD]]. Thus:
-- onlythefirstfourdigitsareusedtospecifyaprecisionof“year”
-- the first six are used to specify a precision of “month”
-- the first eight are used to specify a precision of “day”
• Examples:
-- |19880704|
-- |199503|
• Prior to v 2.3, this data type was specified in the format
YYYYMMDD. As of v 2.3 month and days are no longer required.
By site-specific agreement, YYYYMMDD may be used where
backward compatibility must be maintained.
Taken from HL7 Version 2.5.1 Chapter 2A section 2.A.2131
30
31
HL7 Version 2.5.1 is copyrighted. Quest Diagnostics is a Benefactor Member of HL7.

32
The HL7 V3 Publishing Facilitators Guide is available only to HL7 members. It is embedded in ballot documents. In this case in the V3 September 2013 Ballot was used and can be found at: http://www.
hl7.org/v3ballotarchive/v3ballot/html/welcome/environment/index.html and then the Guide is provided as a component of the ballot. The table of actors is found in Section D. Storybook Names as part
of the Publishing Facilitators Guide near the end of the V3 ballot document, sub-section D.2 - D.5.
33
Quest Diagnostics Maternal Serum Quad Screen order code 30294 http://www.questdiagnostics.com/testcenter/TestDetail.action?ntc=30294
While the underlying standard suggests that Month and Day are optional, for this
LOINC code it is required. Note that the format is Year, Month, and Day. In the
United States, most users expect to enter dates in this format: Month/Day/Year.
For this paper, names and organizations are drawn from the HL7 V3 Publishing
Facilitators guide.32
This guide provides a message that includes Ask at Order
Entry (AOE) Observations, values that were created from lab testing and
calculations based on input as AOEs, and the values from lab testing.
Continuing the example of Maternal Serum Screening, Dr. Flem F. Flora ordered
the Maternal Serum Alpha Feta-Protein Quad Screen for Eve E. Everywoman
who is in her 2nd trimester of pregnancy. Eve E. Everywoman is an African-
American with a calculated due date of March 20, 2015, is in her 16th week of
pregnancy, and her current weight is 175 lbs. All of these data are observations
by Dr. Flora, which she provided to her staff to add as AOEs to the lab order
to be forwarded to Quest Diagnostics, the preferred lab for Eve’s medical
insurance company. These different pieces of information, when inserted into
the HL7 message, have several unique data types. However, this factor does not
cause an issue of concern for Dr. Flora’s staff; the EHR prompts the user for the
information and ensures the data is properly collected and reformatted in the
HL7 message.
In the Directory of Service provided by Quest Diagnostics for the Quad Screen
test 30294 there are several AOEs included as necessary when ordering this
test. The EHR prompts for this information are shown in Figure 1-6, including
how the information must be structured to meet the HL7 format. As noted
previously, the Data Type(s) that determine the required format of the result
is provided in the result record, which is the OBX-2. The value in this field
determines the format for OBX-5, the component where the result is placed as
outlined below in the table.
The Maternal Serum Quad Screen will be used as an example, Quest
Diagnostics Order Code 30294.33
The complexity of the data being captured as
results for the Ask at Order Entry questions creates the necessity of a variety of
data types for the result.

Figure 1-6 – Maternal Serum Quad Screen
Result Entered by
the staff
Sent in the HL7
message as an
observation in
OBX-5
OBX-2 Data
Type
(HL7 Data
Type34
)
LMP – Last
Menstrual
Period
10/4/2013 20131004 DT
EDD -
Estimated
delivery
date
3/20/2013 20140320 DT
How
EDD was
calculated
LMP LMP ST
Number of
fetuses
1 1 NM
First
Pregnancy
Yes Y ID
Estimated
Gestational
Age
16 16 NM
Race* African/
American
2058-6^ African/
American^ CDCREC
CWE
Note: * The code for African/American 2058-6 is from the Vocabulary data set as noted in the footnote below.35
34
HL7 Data types can be found in chapter 2a of the Version 2.x standards. In this case it is best to reference version 2.5.1 since this is the standard referenced by Meaningful
Use. A copy of the standard can be found at: http://www.hl7.org/documentcenter/private/standards/V251/HL7-xml_v2.5.1_annotated.zip
35
The data set can be found at: http://www.cdc.gov/nchs/data/dvs/Race_Ethnicity_CodeSet.pdf

An example EHR screen for the Quad Screen might look like the following:
Figure 1-7 – EHR Screen Example
In many cases the EHR could provide drop down screens to allow the selection
of the appropriate value.
The Future Direction of AOEs
Standardized AOEs, along with several other initiatives to standardize
laboratory test ordering and resulting, will allow ordering providers to meet the
federal initiatives of Meaningful Use. The standardization and consistent use
of AOEs is being introduced in the eDOS IG release. There will continue to be
discussion about the selection of standardized AOEs and the application of an
applicable LOINC code.
Laboratory Community of Practice (LabCoP) has agreed to sponsor the
standardization of AOEs in the future. Currently, the industry is anticipating
decisions to be made by the LOINC Committee in 2014 to determine the
process for LabCoP to interact with the Regenstrief Institute for the assignment
of LOINC codes.

Appendix A — AOE
Because maternal serum screening test results are influenced by certain patient characteristics, the following data must
be provided with the specimen in order to permit accurate interpretation of the results. The list of questions below
includes appropriate LOINC codes used by Quest Diagnostics or other mapping instruction from the ONC S&I Framework
eDOS AOE document.
• Date of Birth – send in PID-7 Patient Date of Birth
• Collection Information
33882-2 Collection Time
49049-0 Collection time of Unspecified
Specimen
SPM-17 (Specimen Collection Date/Time)
(DR_1.1 [Range Start Date/Time])
19151-0 Specimen drawn [Date and
time] of Serum or Plasma
SPM-17 (Specimen Collection Date/Time)
(DR_1.1 [Range Start Date/Time])
• Maternal Weight – not specifically maternal
29463-7 Body weight NM Methodless
Be sure to populate the units in OBX-6.
3141-9 Body weight (measured) Patient weight
(measured)
NM Be sure to populate the units in OBX-6.
3142-7 Body weight (stated) Patient weight
(stated)
NM Be sure to populate the units in OBX-6.
• Estimated Date of Delivery (EDD)
-- How was the EDD determined:
ƒƒ Ultrasound, Last Menstrual Period (LMP) or Physical Exam
11778-8 Delivery date Estimated Estimated
due date
DT
34970-4 Ultrasound Date DT
8665-2 Date last menstrual period DT

• Mother’s Ethnic Origin: African American, Asian, Caucasian, Hispanic, Other
42784-9 Ethnic background Stated CWE PID-22 (Ethnic Group) value is provided for
demographic, not clinical use. An AOE must
be provided for those tests where Ethnic
Group drives the interpretation of results. The
value must be determined by the ordering
provider and must be sent as an AOE OBX.
More specific ethnicity values are available,
but not limited to, those found in the
CDCREC document if needed for AOE.
(http://www.cdc.gov/nchs/data/dvs/Race_
Ethnicity_CodeSet.pdf)
32624-9 Race CWE PID-10 (Race) value is provided for
demographic, not clinical use. An AOE must
be provided for those tests where Race drives
the interpretation of results. The value must
be determined by the ordering provider and
must be sent as an AOE OBX.
More specific race values are available, but
not limited to, those found in the CDCREC
document if needed for AOE. (http://www.
cdc.gov/nchs/data/dvs/Race_Ethnicity_
CodeSet.pdf).
69490-1 Ethnicity OMB 1997 Ethnicity CWE Refer to LOINC for suggested answer list.
• Number of Fetuses: One, two, or more
-- When more how many:
11878-6 Number of Fetuses by US Number of
Fetuses
NM ‘US’ is Ultrasound
42479-6 Fetal Narrative Study
observation general,
multiple fetuses US
ST

• Yes/No questions:
-- Patient is an insulin-dependent diabetic prior to pregnancy (**not pre-pregnancy)
44877-9 Insulin dependent diabetes
mellitus [Presence]
Insulin
dependent
DM
CWE Y/N (HL7 Table 0136)
-- This is a repeat specimen for this pregnancy
-- Previous Pregnancy with Down Syndrome
• Yes/No Questions requiring more information if Yes
-- History of Neural tube defect – If yes explain
-- Narrative of History of neural tube defect
53827-2 History of neural tube
defect Qualitative
History of
ONTD
CNE Y/N (HL7 Table 0136)
49053-2 History of neural tube
defect Narrative
TX
• Pregnancy is from a donor egg – Age of donor at time of egg retrieval:
53948-6 Donated egg [Presence] Donor egg CWE Y/N (HL7 Table 0136)

Request for other relevant clinical information
Additional questions for the first trimester are:
• Ultrasound Date
34970-4 Ultrasound Date DT
• Ultrasonographer’s name:
49088-8 Sonographer name XPN
• NTQR or FMF
• Ultrasonographer’s ID#
• Location ID#
• Reading Physician ID#
• Crown Rump Length (CRL)
11957-8 Fetal Crown Rump length
US
Fetal Crown
Rump length
• Nuchal translucency (NT)
12146-7 Fetal Nuchal fold thickness
US
Nuchal
translucency
• Nasal Bone: Present, Absent, Not Assessed
• If twin gestation, are the twins: Dichorionic, Monochorionic
• Twin B Crown Rump Length (CRL)
• Twin B Nuchal Translucency (NT)
• Twin B Nasal Bone: Present, Absent, Not Assessed

ACA Affordable Care Act
ACLA American Clinical Laboratory Association
ACO Accountable Care Organizations
ANSI American National Standards Institute
AOE Ask at Order Entry
CLIA Clinical Laboratory Improvement Amendments
CMS Centers for Medicare and Medicaid Services
CNE HL7 Data Type - Coded with no Exceptions
CRL Crown Rump Length
CWE HL7 Data Type – Coded with Exceptions
DOB Date of Birth
DOS Directory of Service
DR HL7 Data Type – Date/Time Range
DT HL7 Data Type -Date
EDD Estimated Date of Delivery
eDOS Electronic Directory of Service
EHR Electronic Health Record
FHL7 Fellow, Health Level Seven
FMF Fetal Medicine Foundation
HHS US Department of Health and Human Services
HIE Health Information Exchange
HIT Health Information Technology
HL7® Health Level Seven
IG Implementation Guide
IOM Institute of Medicine
LabCoP Lab Community of Practice
LMP Last Menstrual Period
LOI Laboratory Order Interface
LOINC® Logical Observation Identifiers Names and Codes
LRI Lab Result Interface
MT(ASCP) Medical Technologist (American Society for Clinical Pathology)
MU Meaningful Use
NT Nuchal translucency
NTQR Nuchal Translucency Quality Review
OBR HL7 Observation Request Segment
OBX HL7 Observation/Result Segment
OMB Office of Management and Budget
ONC Office of the National Coordinator (preferred abbreviation for ONCHIT - Office of
the National Coordinator of Health Information Technology )
RELMA Regenstrief LOINC Mapping Assistant
S&I Standards and Interoperability (sponsored by the Office of National Coordinator)
SN HL7 Data Type – Structured Numeric
SPM HL7 Specimen Segment
US United States
Appendix B - Acronyms

Quest Diagnostics -- Ask at Order Entry Insight 20140707

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