Best Practices for Interoperable Data Exchange Using LOINC

Report
Best Practices for Interoperable
Data Exchange Using LOINC
Ming-Chin (Mark) Lin, MD
Stanley M. Huff, MD
Introduction
• Two primary use cases
– Sharing data between and among different
institutions for patient care
– Aggregating data between and among different
institutions for clinical research, quality
improvement, public health surveillance, etc.
(secondary use)
• Use LOINC codes as the lingua franca for the
data sharing
Introduction (continued)
• Mark’s work comparing LOINC usage across ARUP,
Regenstrief, and Intermountain
• What is truth?
– If local codes from different sites are mapped to the same LOINC
code, how do we know they are really the same test?
– If local codes from different sites are mapped to different LOINC
codes, how do we know they are really different tests?
• Extensional definitions
– Comparison of names (substance, timing, property, specimen),
units of measure, mean value, standard deviation, coded values,
co-occurring tests, etc.
• Results: We found about a 4% error rate in mapping
– And that is us! What is it like for “regular” facilities?
Introduction (continued)
• Analyzing the errors lead to additional
questions
– Can we classify the errors?
– What is the ultimate goal of mapping?
– Can we define “best practices” for mapping so
that everyone doing mapping can achieve greater
accuracy?
“Fit for Purpose” or “Good Enough”
mapping
• Example: Tests with a method specified at site
A are mapped to methodless tests at site B
• Works for the known use case
– Either estimated weights or scale weights may be
good enough for a particular study
• This represents a loss of information when
data moves from A to B
Proposed Best Strategy
• Always map to the LOINC code or combination of
codes that capture all known information about
the test
– Always capture the method in the data if it is known
• Rationale: All uses of the data (especially
secondary uses) are not known at the time of
initial mapping or data collection
• “Fit for Purpose” mappings will preclude
secondary use of the data in some situations
– What if you want to study whether two different test
methods are truly equivalent?
Degrees of Interoperability
• Degree I: Exact equivalence without translation
– Same code, unit of measure, and value set
– Data are mutually substitutable in all contexts of use
• Degree II: Exact equivalence after translation
– Unit of measure conversion (need UCUM)
– Mass concentration to substance concentration conversion
(need the molecular weight)
– Pre and post coordination translation
• Method as part of LOINC code versus method sent somewhere else in
the message
• Peak or trough as part of LOINC code versus peak and trough sent
somewhere else in the message
– Data are mutually substitutable in all contexts of use after
translation
Degrees of Interoperability (cont)
• Degree III: Context specific subsumption
– A parent-child relationship exists between tests at
the different institutions
• Method specific tests roll up to methodless tests
• IgM or IgG antibodies roll up to generic antibody
– Data are mutually substitutable only in a specific
context of use even after translation
• Degree IV: No interoperability
– No comparable data or information exists
between or among institutions
Examples
Proposal
• Create specific best practice mapping guidelines
for difficult situations and common errors
• Examples
– How to deal with variable granularity in methods
– How to deal with pre and post coordinated specimen
type
– How to deal with pre and post coordinated challenge
conditions
– Use of Acnc and Titr
Example Guideline for Method
• If possible, and the method is known, map to the
methodless LOINC code and always send the
method in some other part of the message
– Related policy: the LOINC committee will make all
needed methodless LOINC codes
• If the method is known but it is not possible to
post coordinate the method, map to the method
specific pre coordinated LOINC code
• If the method is not known, map to the
methodless LOINC code
Example Guideline for Interpretations
• Always map to the quantitative LOINC code
– Related policy: The LOINC Committee will discourage
or deprecate the use of nominal or ordinal LOINC
codes for concentrations
• Send numbers when they exist as the value of
OBX 5
• Send interpretations when they exist as the value
of OBX 8
• One or the other or both of the numeric value
and the interpretation can exist in a data instance
Discussion

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