Ming-Chin (Mark) Lin, MD
Stanley M. Huff, MD
• 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
• 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?
• 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?
• 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
• 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?
• 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
• 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
• 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
• 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
• 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