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