A Prescription For Enhancing Electronic Prescribing Safety.

While electronic prescribing has been shown to reduce medication errors and improve prescribing safety, it is vulnerable to error-prone processes. We review six intersecting areas in which changes to electronic prescribing systems, particularly in the outpatient setting, could transform medication ordering quality and safety. We recommend incorporating medication indications into electronic prescribing, establishing a single shared online medication list, implementing the transmission of electronic cancellation orders to pharmacies (CancelRx) to ensure that drugs are safely and reliably discontinued, implementing standardized structured and codified prescription instructions, reengineering clinical decision support, and redesigning electronic prescribing to facilitate the ordering of nondrug alternatives.

Quality and Variability of Patient Directions in Electronic Prescriptions in the Ambulatory Care Setting.

BACKGROUND: The prescriber's directions to the patient (Sig) are one of the most quality-sensitive components of a prescription order. Owing to their free-text format, the Sig data that are transmitted in electronic prescriptions (e-prescriptions) have the potential to produce interpretation challenges at receiving pharmacies that may threaten patient safety and also negatively affect medication labeling and patient counseling. Ensuring that all data transmitted in the e-prescription are complete and unambiguous is essential for minimizing disruptions in workflow at prescribers' offices and receiving pharmacies and optimizing the safety and effectiveness of patient care. OBJECTIVES: To (a) assess the quality and variability of free-text Sig strings in ambulatory e-prescriptions and (b) propose best-practice recommendations to improve the use of this quality-sensitive field. METHODS: A retrospective qualitative analysis was performed on a nationally representative sample of 25,000 e-prescriptions issued by 22,152 community-based prescribers across the United States using 501 electronic health records (EHRs) or e-prescribing software applications. The content of Sig text strings in e-prescriptions was classified according to a Sig classification scheme developed with guidance from an expert advisory panel. The Sig text strings were also analyzed for quality-related events (QREs). For purposes of this analysis, QREs were defined as Sig text content that could impair accurate and unambiguous interpretation by staff at receiving pharmacies. RESULTS: A total of 3,797 unique Sig concepts were identified in the 25,000 Sig text strings analyzed; more than 50% of all Sigs could be categorized into 25 unique Sig concepts. Even Sig strings that expressed apparently simple and straightforward concepts displayed substantial variability; for example, the sample contained 832 permutations of words and phrases used to convey the Sig concept of "Take 1 tablet by mouth once daily." Approximately 10% of Sigs contained QREs that could pose patient safety risks or workflow disruptions that could necessitate pharmacist callbacks to prescribers for clarification or other manual interventions. CONCLUSIONS: The quality of free-text patient directions in e-prescriptions can vary dramatically. However, more than half of all patient directions sent in the ambulatory setting can be categorized into only 25 Sig concepts. This suggests an immediate, practical opportunity to improve patient safety and workflow efficiency for both prescribers and pharmacies. Recommendations include implementing enhancements to Sig creation tools in e-prescribing and EHR software applications, adoption of the Structured and Codified Sig format supported by the current national e-prescribing standard, and improved usability testing and end-user training for generating complete and unambiguous patient directions. Such quality improvements are essential for optimizing the safety and effectiveness of patient care as well as for minimizing workflow disruptions to both prescribers and pharmacies. DISCLOSURES: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Yang, Ward-Charlerie, Dhavle, and Green are employed by Surescripts. Rupp reported receiving consulting fees from Surescripts during the conduct of this study. No other disclosures were reported. The content in this article is solely the responsibility of the authors and does not necessarily represent the official views of Surescripts and Midwestern University or any of the affiliated institutions of the authors. Study concept and design were contributed by all the authors. Yang and Ward-Charlerie collected the data, and data interpretion was performed by Yang, Ward-Charlerie and Dhavle. The manuscript was primarily written by Yang, along with Dhavle and Green, and revised by Yang, Dhavle, Rupp, and Green.

A better way: leveraging a proven and utilized system for improving current medication reconciliation processes.

In this reply to the commentary, "A Call for a Statewide Medication Reconciliation Program," published in the October 2016 issue of The American Journal of Managed Care®, authors note that although they agree with the authors' assessment of the problem, they believe there is a proven and scalable solution to improve medication reconciliation that is already available to, and used by, clinicians.

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.

Towards creating the perfect electronic prescription.

Significant strides have been made in electronic (e)-prescribing standards and software applications that have further fueled the adoption and use of e-prescribing. However, for e-prescribing to realize its full potential for improving the safety, effectiveness, and efficiency of prescription drug delivery, important work remains to be carried out. This perspective describes the ultimate goal of all e-prescribing stakeholders including prescribers and dispensing pharmacists: a clear, complete, and unambiguous e-prescription order that can be seamlessly received, processed, and fulfilled at the dispensing pharmacy without the need for additional clarification from the prescriber. We discuss the challenges to creating the perfect e-prescription by focusing on selected data segments and data fields that are available in the new e-prescription transaction as defined in the NCPDP SCRIPT Standard and suggest steps that could be taken to move the industry closer to achieving this vision.

Perioperative nesiritide versus milrinone in high-risk coronary artery bypass graft patients.

BACKGROUND: Patients with left-ventricular dysfunction have an increased risk of developing heart failure after coronary artery bypass graft (CABG) surgery. Therapies to maintain cardiac output in such patients warrant investigation. Nesiritide is unique among intravenous medications used to manage heart failure. It mediates natriuresis and vasodilation and suppresses the reninangiotensin-aldosterone axis. Nesiritide may attenuate the body's neurohormonal response to myocardial stretch after CABG and provide clinical benefit in the immediate postoperative period. OBJECTIVE: To determine whether perioperative infusion of nesiritide improves clinical outcomes compared with milrinone therapy. METHODS: A prospective, open-label, randomized controlled trial was conducted in 40 consecutive hemodynamically stable patients with ejection fractions 35% or less undergoing CABG surgery. Patients were randomized to receive either an intraoperative bolus of nesiritide or milrinone followed by a 24 hour infusion of each agent. Length of postoperative intensive care unit stay was the primary outcome variable evaluated. Incidence of postoperative heart failure, 30 day readmission rates, mortality, and other clinical parameters were also compared. RESULTS: Patients receiving nesiritide had a mean +/- SD postoperative intensive care unit stay of 50.6 +/- 46.8 hours compared with 44.1 +/- 23.5 hours in those receiving milrinone (p = 0.578). Incidence of postoperative heart failure was also not significantly different between the drugs (p = 0.259). Thirty day follow-up confirmed no difference in hospital readmission rates between nesiritide and milrinone (p = 0.661). No differences in mortality were observed during hospitalization or 30 days of follow-up. CONCLUSIONS: Nesiritide does not decrease postoperative intensive care unit stay or other clinical parameters compared with milrinone in high-risk patients with hemodynamically stable left-ventricular function undergoing CABG surgery.