GS1 to Sunset Application Identifier AI(22) Data Structure for Secondary Attributes
Introduced more than 15 years ago to provide a convenient migration path for companies converting from the Health Industry Bar Code (HIBC) Supplier Labeling Standard to the global GS1 System of product identification and bar code marking standards, Application Identifier AI(22), “Secondary Data for Specific Health Industry Products,” is now slated for withdrawal effective January 1, 2013.
According to the newly revised GS1 General Specifications (Version 10, Issue 1) published by the GS1 Global Office in Brussels and applicable worldwide, “GS1 has established 01 Jan 2013 as the global Sunset date for AI (22) as no continuing business rationale for it exists. After this date, GS1 will return AI (22) to the numbers available for assignment to new Application Identifier requirements.”
The withdrawal of AI(22) is expected to reduce confusion and improve efficiency in the global healthcare supply chain. Other application identifiers for QTY, EXP DATE, and BATCH/LOT (all of which can be represented in AI(22)) were already in general use when AI(22) was adopted and these other application identifiers—AI(30) for COUNT (aka QTY), AI(17) for EXP DATE, and AI(10) for BATCH/LOT—have also been widely used in healthcare for decades. (One has to acknowledge, though, that how certain segments of the U.S. healthcare supply chain have historically used AI(30), “Count of Items for Variable Measure Trade Item,” is not in strict accordance with GS1 specifications.)
For those who are not intimately familiar with the GS1 System, an application identifier (AI) is a two-, three-, or four-digit code preceding a GS1 System data element that uniquely defines the format and meaning of the data that follows. In other words, an application identifier is metadata or “data about the data” with which it is associated.
There are over 100 application identifiers in the GS1 system covering product, asset, and location identification; production, packaging, best before, and expiration date (all formatted exclusively as YYMMDD); serial number; purchase order; weight and dimension of most every kind; ship-to postal code; and many, many more. The character (numeric or alphanumeric, including many special characters), length (fixed or variable, including maximum length), and other attributes (e.g., number of implied decimal places) of the data are all defined in the application identifier look-up table.
From the simplest GS1-128 linear bar code encoding AI(01)+AI(21)—that is, Global Trade Item Number (i.e., product identification) plus unique serial number—to a more complex 2-D Data Matrix symbol encoding AI(01)+AI(21) +AI(17)+AI(10)—that is, GTIN, serial number, expiration date, and batch/lot code—it is only by means of the application identifiers and the AI look-up table that application software can properly interpret the data.
For healthcare manufacturers that use the AI(22) coding structure to represent “secondary” or product attribute data (in this case, QTY, EXP DATE, and BATCH/LOT) in bar codes on their product packaging, the withdrawal of AI(22) means revising artwork and/or label templates. AI(22) is used by some med/surg manufacturers on individual stock-keeping units and perhaps most widely on a significant number of pharmaceutical product identification labels at the case level. AI(17) and AI(10) are also widely used in both applications.
The decision to withdraw AI(22) was not taken hurriedly or lightly; it came as a result of a four-year effort to develop a global AIDC Application Standard for Healthcare. The work groups involved in developing this standard included “more than 100 experts from every region of the world and representing every segment of the healthcare supply chain,” according to Grant Hodgkins, Alcon Laboratories Inc., Co-Chair of the AIDC Application Standards work group and Tri-Chair of the GS1 Healthcare Global Leadership Team.
Equally important, says Tom Heist, Director Global Standards, GS1 GSMP, “The work groups followed the GS1 Global Standards Management Process methodology of gathering and analyzing global business requirements and then devised an appropriate solution for each requirement. There was an extended public review period and a formal eBallot.”
|GS1 System Application Identifiers used worldwide on products throughout the healthcare supply chain.|
Whether one uses AI(22) or a combination of AI(17), AI(10), and AI(30), there is very little difference between the two in terms of the GS1-128 linear bar code space requirements, although AI(22) is sometimes slightly shorter. If one is using 2-D Data Matrix, there is usually no difference at all in symbol size. While AI(22) does have one superior characteristic, namely, the inclusion of a “link character” to tie it back to the associated GTIN, this was not considered sufficient to outweigh its disadvantages.
According to many bar code systems experts, with 23 different permutations for encoding QTY, EXP DATE, and BATCH/LOT within AI(22), healthcare manufacturers have always found it a complex and confusing data structure to encode. The proof of this is the significant number of incorrectly formatted AI(22) bar codes on packages of every kind. One industry pundit claims that there are probably more “bad” or incorrectly encoded AI(22) bar codes in the supply chain than there are correct ones. Of course, badly encoded data usually yields scanned data that cannot be properly interpreted, whether at the receiving dock, central supply, the operating room, or the patient bedside. Elimination of AI(22) should therefore provide improved data integrity.
In addition, having multiple ways to represent critical product identification and attribute data elements adds to system complexity and is confusing to the person trying to determine what to scan, whether the bar code is correctly encoded or not. The global evolution toward the GS1 System as the dominant product identification standard—and a consistent, uniform syntax for healthcare secondary data within that standard—will reduce supply-chain complexity, improve efficiency, and simplify training at every level of the supply chain.
As just one example, consider that there are an estimated 13 million nurses worldwide. Many of those nurses and other caregivers who have experience in a bar code scanning environment have made it clear that multiple bar codes on a package and the lack of a single standard is an impediment to implementation, not just to efficient implementation but to any implementation. Although we are still some years away from achieving it, the GS1 Healthcare vision underscores that reality. Over the long term, it envisions that every healthcare item will have one data carrier (as one example, a 2-D Data Matrix bar code) with all key information scanned by anyone who needs it at every key process.
Another significant influence in the decision to sunset AI(22) is the fact that current and expected national government regulations (for example, Turkey’s healthcare “Regulation on Packaging and Labelling” [sic] to name just one of many) call specifically for the use of AI(17) and AI(10)—and in Data Matrix symbology, not a linear bar code. For now, however, in the U.S. FDA regulations still require a linear bar code encoding the National Drug Code on prescription and certain other pharmaceuticals.
Over the next several months, at least one key U.S. pharmaceutical industry bar code implementation guideline is set to be updated to reflect this change in AI use and other changes, such as the just-announced Final Guidance from FDA outlining its recommendations for a Standardized Numerical Identifier (SNI) on pharmaceuticals. A number of pharmaceutical and medical/
surgical manufacturers—especially those who actively participate in standards development and who therefore have been aware of this GS1 AI(22) application identifier withdrawal for many months—are already working to revise their packaging and labeling. The package and/or label design of potentially thousands of products worldwide is affected and while January 1, 2013, may seem like a long way away and plenty of time to accomplish the task, a thousand days can wind up being a very short time indeed.
George Wright IV is a certified GS1 US Bar Code Consultant and regular contributor to Pharmaceutical and Medical Packaging News. Questions, comments, or requests for application assistance should be emailed to the author at email@example.com.