Best Practices for Interoperable Data Exchange Using LOINC

1. Best Practices for Interoperable Data Exchange Using LOINC Ming-Chin (Mark) Lin, MD Stanley M. Huff, MD

2. 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 linguafranca for the data sharing

3. 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?

4. 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?

5. “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

6. 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?

7. 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

8. 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

9. Examples

10. 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

11. 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

12. 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

13. Discussion