Analysis of Prescribers' Notes in Electronic Prescriptions in Ambulatory Practice.

IMPORTANCE: The optional free-text Notes field in ambulatory electronic prescriptions (e-prescriptions) allows prescribers to communicate additional prescription-related information to dispensing pharmacists. However, populating this field with irrelevant or inappropriate information can create confusion, workflow disruptions, and potential patient harm. OBJECTIVES: To analyze the content of free-text prescriber notes in new ambulatory e-prescriptions and to develop recommendations to improve e-prescribing practices. DESIGN, SETTING, AND PARTICIPANTS: We performed a qualitative analysis of e-prescriptions containing free-text prescriber notes for conformance to the intended purpose of the free-text field as established in the national e-prescribing standard. The study sample contained 26 341 new e-prescriptions randomly selected from 3 024 737 e-prescriptions containing notes transmitted to community pharmacies across the United States during a 1-week period (November 10-16, 2013). The study e-prescriptions were issued by 22 549 community-based prescribers using 492 different electronic health record (EHR) or e-prescribing software application systems. Data analysis was conducted from February 23, 2014, to November 4, 2015. MAIN OUTCOMES AND MEASURES: Reviewers classified free-text prescriber notes as appropriate, inappropriate (content for which a standard, structured data-entry field is available in the widely implemented national e-prescribing standard), or unnecessary (irrelevant to dispensing pharmacists). We developed and applied a classification scheme to further characterize and quantify types of appropriate and inappropriate content. RESULTS: Of the 26 341 free-text notes, 17 421 (66.1%) contained inappropriate content, 7522 (28.6%) contained appropriate content, and 1398 (5.3%) contained information considered to be unnecessary. Further characterization of inappropriate content resulted in 20 192 classification codes, of which 3841 codes (19.0%) were assigned because of patient directions that conflicted with directions included in the designated standard field intended for this purpose. Characterization of appropriate content resulted in 7785 classification codes, of which 3685 (47.3%) contained information that could be communicated using structured fields already approved in a yet-to-be implemented version of the e-prescribing standard. An additional 745 (9.6%) were prescription cancellation requests for which a separate e-prescribing message currently exists but is not widely supported by software vendors or used by prescribers. CONCLUSIONS AND RELEVANCE: The free-text Notes field in e-prescriptions is frequently used inappropriately, suggesting the need for better prerelease usability testing, consistent end user training and feedback, and rigorous postmarketing evaluation and surveillance of EHR or e-prescribing software applications. Accelerated implementation of new e-prescribing standards and rapid adoption of existing ones could also reduce prescribers' reliance on free-text use in ambulatory e-prescriptions.

Evaluating the implementation of RxNorm in ambulatory electronic prescriptions.

OBJECTIVE: RxNorm is a standardized drug nomenclature maintained by the National Library of Medicine that has been recommended as an alternative to the National Drug Code (NDC) terminology for use in electronic prescribing. The objective of this study was to evaluate the implementation of RxNorm in ambulatory care electronic prescriptions (e-prescriptions). METHODS: We analyzed a random sample of 49 997 e-prescriptions that were received by 7391 locations of a national retail pharmacy chain during a single day in April 2014. The e-prescriptions in the sample were generated by 37 801 ambulatory care prescribers using 519 different e-prescribing software applications. RESULTS: We found that 97.9% of e-prescriptions in the study sample could be accurately represented by an RxNorm identifier. However, RxNorm identifiers were actually used as drug identifiers in only 16 433 (33.0%) e-prescriptions. Another 431 (2.5%) e-prescriptions that used RxNorm identifiers had a discrepancy in the corresponding Drug Database Code qualifier field or did not have a qualifier (Term Type) at all. In 10 e-prescriptions (0.06%), the free-text drug description and the RxNorm concept unique identifier pointed to completely different drug concepts, and in 7 e-prescriptions (0.04%), the NDC and RxNorm drug identifiers pointed to completely different drug concepts. DISCUSSION: The National Library of Medicine continues to enhance the RxNorm terminology and expand its scope. This study illustrates the need for technology vendors to improve their implementation of RxNorm; doing so will accelerate the adoption of RxNorm as the preferred alternative to using the NDC terminology in e-prescribing.

Analysis of National Drug Code Identifiers in Ambulatory E-Prescribing.

BACKGROUND: Communication of an accurate and interpretable drug identifier between prescriber and pharmacist is critically important for realizing the potential benefits of electronic prescribing (e-prescribing) while minimizing its risk. The National Drug Code (NDC) is the most commonly used codified drug identifier in ambulatory care e-prescribing, but concerns have been raised regarding its use for this purpose.  OBJECTIVES: To (a) assess the frequency of NDC identifier transmission in ambulatory e-prescribing; (b) characterize the type of NDC identifier transmitted (representative, repackaged, obsolete, private label, and unit dose); and (c) assess the level of agreement between drug descriptions corresponding to NDC identifiers in electronic prescriptions (e-prescriptions) and the free-text drug descriptions that were entered by prescribers.  METHODS: We analyzed a sample of 49,997 e-prescriptions that were transmitted by ambulatory care prescribers to outlets of a national retail drugstore chain during a single day in April 2014. The First Databank MedKnowledge drug database was used as the primary reference data base to assess the frequency and types of NDC numbers in the e-prescription messages. The FDA's Comprehensive NDC Standard Product Labeling Data Elements File and the National Library of Medicine's RxNorm data file were used as secondary and tertiary references, respectively, to identify NDC numbers that could not be located in the primary reference file. Three experienced reviewers compared the free-text drug description that had been entered by the prescriber with the drug description corresponding to the NDC number from 1 of the 3 reference database files to identify discrepancies. Two licensed pharmacists with residency training and ambulatory care experience served as final adjudicators. RESULTS: A total of 42,602 e-prescriptions contained a value in the NDC field, of which 42,335 (84.71%) were found in 1 of the 3 study reference databases and were thus considered to be valid NDC numbers. A total of 28,172 (67.70%) e-prescriptions in the sample were found to contain a representative NDC number, according to the definition used by the National Council for Prescription Drug Programs (NCPDP). The remaining e-prescriptions consisted of 4 subtypes of unrepresentative NDC numbers. In 41,298 (97.55%) e-prescriptions that contained an NDC number, the drug description associated with the number from 1 of the 3 data source files pointed to the identical semantic drug concept as the free-text drug description that had been entered by the prescriber. However, in 87 (0.21%) e-prescriptions, the free-text drug descriptions and the drug description associated with the NDC number pointed to completely different semantic drug concepts. CONCLUSIONS: We found the use of NDC identifiers in our sample of e-prescriptions to be relatively high. However, approximately one-third consisted of unrepresentative NDC numbers (obsolete, repackaged, unit dose, or private label) that have the potential to create workflow disruptions at the dispensing pharmacy. Most disturbing was our finding that more than 2 out of every 1,000 e-prescriptions in our sample contained a free-text drug description that pointed to a completely different drug concept than that associated with its NDC value. Our study suggests the need for e-prescribing technology vendors to maintain accurate and up-to-date drug database files within their systems and to conduct regular validation checks to ensure that the drug descriptions associated with the NDC identifier and the free-text drug description that is sent in the e-prescription message point to the same drug concept. The FDA may need to consider a more active role in ensuring the accuracy of NDC assignment by drug manufacturers.