Towards creating the perfect electronic prescription

Physicians' Perspectives with the E-prescribing System in Five Teaching Hospitals

OBJECTIVES

 Despite the evidence suggesting the potential of electronic prescribing (e-prescribing), this system also faces challenges that can lead to inefficiency and even failure. This study aimed to evaluate physicians' perspectives on the efficiency, effectiveness, opportunities, and challenges associated with the e-prescribing system.

METHODS

 In 2023, a descriptive analytics cross-sectional study was carried out. Due to the finite population size, all the physicians from five studied hospitals who agreed to participate in the study were included through the census method (n = 195). Data collection was conducted using a validated questionnaire. Data were analyzed using descriptive (mean, standard deviation, and frequency) and analytical (Pearson's correlation coefficient, two-sample t-test, one-way analysis of variance (ANOVA), and linear multiple regression model) statistics.

RESULTS

 The mean scores of efficiency and effectiveness were 47.47 ± 14.46 and 36.09 ± 10.67 out of 95 and 65, respectively. Removing the illegibility of the prescriptions (n = 22) was the most frequent opportunity and internet connectivity problem (n = 37) was the most frequent challenge associated with the e-prescribing system. There was a strong positive significant correlation between efficiency and effectiveness (r = 0.850, p < 0.01). Moreover, age was found to have a significant negative correlation with efficiency (B =  -7.261, p = 0.004) and effectiveness (B = - 5.784, p = 0.002).

CONCLUSION

 Physicians believe that e-prescribing enhances the efficiency and effectiveness of their work. There are many opportunity and challenges to the use of e-prescription. Assessing the needs of physicians, actively participating and training them in the stages of design and implementation, and conducting regular evaluations of the e-prescribing system are crucial to overcome the challenges. Our finding offers insightful information about how doctors see the e-prescribing system at teaching hospitals and provide a basis for managers and policy makers at the local and national levels to support the implementation of this system and plan for improvement of its shortcomings.

Implementation outcomes of the Structured and Codified SIG format in electronic prescription directions

OBJECTIVE

To determine the extent of implementation, completeness, and accuracy of Structured and Codified SIG (S&C SIG) directions on electronic prescriptions (e-prescriptions).

MATERIALS AND METHODS

A retrospective analysis of a random sample of 3.8 million e-prescriptions sent from electronic prescribing (e-prescribing) software to outpatient pharmacies in the United States between 2019 and 2021. Natural language processing was used to identify direction components, including action verb, dose, frequency, route, duration, and indication from free-text directions and were compared to the S&C SIG format. Inductive qualitative analysis of S&C direction identified error types and frequencies for each component.

RESULTS

Implementation of the S&C SIG format in e-prescribing software resulted in 32.4% of e-prescriptions transmitted with these standardized directions. Directions using the S&C SIG format contained a greater percentage of each direction component compared to free-text directions, except for the indication component. Structured and codified directions contained quality issues in 10.3% of cases.

DISCUSSION

Expanding adoption of more diverse direction terminology for the S&C SIG formats can improve the coverage of directions using the S&C SIG format. Building out e-prescribing software interfaces to include more direction components can improve patient medication use and safety. Quality improvement efforts, such as improving the design of e-prescribing software and auditing for discrepancies, are needed to identify and eliminate implementation-related issues with direction information from the S&C SIG format so that e-prescription directions are always accurately represented.

CONCLUSION

Although directions using the S&C SIG format may result in more complete directions, greater adoption of the format and best practices for preventing its incorrect use are necessary.

Comparing the variability of ingredient, strength, and dose form information from electronic prescriptions with RxNorm drug product descriptions

OBJECTIVE

To determine the variability of ingredient, strength, and dose form information from drug product descriptions in real-world electronic prescription (e-prescription) data.

MATERIALS AND METHODS

A sample of 10 399 324 e-prescriptions from 2019 to 2021 were obtained. Drug product descriptions were analyzed with a named entity extraction model and National Drug Codes (NDCs) were used to get RxNorm Concept Unique Identifiers (RxCUI) via RxNorm. The number of drug product description variants for each RxCUI was determined. Variants identified were compared to RxNorm to determine the extent of matching terminology used.

RESULTS

A total of 353 002 unique pairs of drug product descriptions and NDCs were analyzed. The median (1st-3rd quartile) number of variants extracted for each standardized expression in RxNorm, was 3 (2-7) for ingredients, 4 (2-8) for strength, and 41 (11-122) for dosage forms. Of the pairs, 42.35% of ingredients (n = 328 032), 51.23% of strengths (n = 321 706), and 10.60% of dose forms (n = 326 653) used matching terminology, while 16.31%, 24.85%, and 13.05% contained nonmatching terminology, respectively.

DISCUSSION

A wide variety of drug product descriptions makes it difficult to determine whether 2 drug product descriptions describe the same drug product (eg, using abbreviations to describe an active ingredient or using different units to represent a concentration). This results in patient safety risks that lead to incorrect drug products being ordered, dispensed, and used by patients. Implementation and use of standardized terminology may reduce these risks.

CONCLUSION

Drug product descriptions on real-world e-prescriptions exhibit large variation resulting in unnecessary ambiguity and potential patient safety risks.

High alert drugs screening using gradient boosting classifier

Prescription errors in high alert drugs (HAD), a group of drugs that have a high risk of complications and potential negative consequences, are a major and serious problem in medicine. Standardized hospital interventions, protocols, or guidelines were implemented to reduce the errors but were not found to be highly effective. Machine learning driven clinical decision support systems (CDSS) show a potential solution to address this problem. We developed a HAD screening protocol with a machine learning model using Gradient Boosting Classifier and screening parameters to identify the events of HAD prescription errors from the drug prescriptions of out and inpatients at Maharaj Nakhon Chiang Mai hospital in 2018. The machine learning algorithm was able to screen drug prescription events with a risk of HAD inappropriate use and identify over 98% of actual HAD mismatches in the test set and 99% in the evaluation set. This study demonstrates that machine learning plays an important role and has potential benefit to screen and reduce errors in HAD prescriptions.

Evaluating physicians' perspectives on the efficiency and effectiveness of the electronic prescribing system

BACKGROUND

The implementation of the electronic prescribing system follows certain objectives, and users' perspectives can contribute to understanding the efficiency and effectiveness of this system. This study aimed to evaluate physicians' perspectives on the efficiency and effectiveness of the electronic prescribing system.

METHODS

This study was conducted on all physicians using the electronic prescribing system in clinics and hospitals affiliated with the treatment deputy of the Social Security Organization (SSO) in Sistan and Baluchistan Province in Iran. Data were collected using a self-administered questionnaire containing three sections: (i) Six items related to demographic data and clinical experience, (ii) Specific questions based on a five-point Likert scale-related physicians' perspectives about efficiency (19 questions) and effectiveness (13 questions), and (iii) Open-ended questions about the positive and negative aspects of using the electronic prescribing system.

RESULTS

The mean and standard deviation of the efficiency and effectiveness of the electronic prescribing system were 3.68 ± 0.67 and 3.84 ± 0.65, respectively. Patient safety had the highest mean score among all dimensions (4.0 ± 0.64). Most participants (n = 55, 79%) considered the efficiency and effectiveness of this system high. More than 90 percent of the physicians (n = 63) believed that the electronic prescribing system enables a better medication prescription by providing alerts and access to patients' medication history.

CONCLUSION

The findings showed that most physicians believed that the electronic prescribing system of Iran's SSO has high efficiency and effectiveness. In particular, physicians believed that using this system improves patient safety and reduces costs.

Assessing automated product selection success rates in transmissions between electronic prescribing and community pharmacy platforms

OBJECTIVE

Wrong drug product errors occurring in community pharmacies often originate at the transcription stage. Electronic prescribing and automated product selection are strategies to reduce product selection errors. However, it is unclear how often automated product selection succeeds in outpatient pharmacy platforms.

MATERIALS AND METHODS

The intake of over 800 e-prescriptions was observed at baseline and after intervention to assess the rate of automated product selection success. A dispensing accuracy audit was performed at baseline and postintervention to determine whether enhanced automated product selection would result in greater accuracy; data for both analyses were compared by 2x2 Chi square tests. In addition, an anonymous survey was sent to a convenience sample of 60 area community pharmacy managers.

RESULTS

At baseline, 79.8% of 888 e-prescriptions achieved automated product selection. After the intervention period, 84.5% of 903 e-prescriptions achieved automated product selection (P = .008). Analysis of dispensing accuracy audits detected a slight but not statistically significant improvement in accuracy rate (99.3% versus 98.9%, P = .359). Fourteen surveys were returned, revealing that other community pharmacies experience similar automated product selection failure rates.

DISCUSSION

Our results suggest that manual product selection by pharmacy personnel is required for a higher than anticipated proportion of e-prescriptions received and filled by community pharmacies, which may pose risks to both medication safety and efficiency.

CONCLUSION

The question of how to increase automated product selection rates and enhance interoperability between prescriber and community pharmacy platforms warrants further investigation.

Medication adherence for atrial fibrillation patients: triangulating measures from a smart pill bottle, e-prescribing software, and patient communication through the electronic health record

OBJECTIVE

Our primary objectives were to examine adherence rates across two technologies (e-prescribing software and smart pill bottle) with cross-validation from alert-triggered messaging within the patient electronic health record (EHR) portal and to explore the benefits and challenges faced by atrial fibrillation (AF) patients in using a smart pill bottle.

MATERIALS AND METHODS

We triangulated the rate of oral anticoagulant medication adherence among 160 AF patients over 6 months using an EHR in combination with data from the AdhereTech© Wireless Smart Pill Bottle and Surescripts©. In addition, we collected qualitative feedback on patients' Smart Pill Bottle usage through structured interviews with 153 participants.

RESULTS

Patients maintained an average adherence rate of 90.0% according to the smart pill bottle; however, when dose misses were calibrated based on patient or provider feedback, the adjusted adherence was 93.6%. Surescripts adherence rates for refills were 92.2%. Participants generally found the bottle easy to operate but suggested that its size and functionality did not fit seamlessly into their existing routine, as many used weekly pill organizers to manage multiple medications.

DISCUSSION

Though each method of tracking adherence has positive and negative attributes, combining them and seeking patient feedback may help capture a more accurate adherence rate than any single technological intervention. Technologies may have different design considerations for research and consumer use.

CONCLUSION

Overall, these technologies provide useful but imperfect adherence data for research purposes, and smart pill bottles could be improved with patient-centered design.

LAY SUMMARY

Medication adherence is very important for those with chronic health issues. For those with heart disease, medication adherence not only offers opportunities for improving quality of life, but it also can be life-saving. Nonetheless, many patients with heart disease, including those with atrial fibrillation (the target group for this study) do not take their medications regularly. As technologies advance, there is unprecedented opportunity to track patients' medication adherence through various methods, which might provide motivation and information to patients as they make daily choices about medication use. In this study, we cross-referenced the results of two of these measures over 6 months-a smart pill bottle, which we used to track pill bottle openings, and e-prescribing software, which we used to track medication refills. We also supplemented these measures with nurse-patient communication via the EHR messaging portal to record exceptions (eg, travel and medication changes) and interviewed patients about their medication use during the 6-month trial. Overall, the tracking technologies worked relatively well to track patient (n = 160) medication behavior; however, they did not capture exceptions. Hence, triangulating data from different sources, with a patient feedback loop, appears critical for gathering accurate data on medication adherence.

Work effort, readability and quality of pharmacy transcription of patient directions from electronic prescriptions: a retrospective observational cohort analysis

Background

Free-text directions generated by prescribers in electronic prescriptions can be difficult for patients to understand due to their variability, complexity and ambiguity. Pharmacy staff are responsible for transcribing these directions so that patients can take their medication as prescribed. However, little is known about the quality of these transcribed directions received by patients.

Methods

A retrospective observational analysis of 529 990 e-prescription directions processed at a mail-order pharmacy in the USA. We measured pharmacy staff editing of directions using string edit distance and execution time using the Keystroke-Level Model. Using the New Dale-Chall (NDC) readability formula, we calculated NDC cloze scores of the patient directions before and after transcription. We also evaluated the quality of directions (eg, included a dose, dose unit, frequency of administration) before and after transcription with a random sample of 966 patient directions.

Results

Pharmacy staff edited 83.8% of all e-prescription directions received with a median edit distance of 18 per e-prescription. We estimated a median of 6.64 s of transcribing each e-prescription. The median NDC score increased by 68.6% after transcription (26.12 vs 44.03, p<0.001), which indicated a significant readability improvement. In our sample, 51.4% of patient directions on e-prescriptions contained at least one pre-defined direction quality issue. Pharmacy staff corrected 79.5% of the quality issues.

Conclusion

Pharmacy staff put significant effort into transcribing e-prescription directions. Manual transcription removed the majority of quality issues; however, pharmacy staff still miss or introduce following their manual transcription processes. The development of tools and techniques such as a comprehensive set of structured direction components or machine learning–based natural language processing techniques may help produce clear directions.

10 ways to improve medication safety in community pharmacies

DATA SOURCES

Not applicable.

SUMMARY

Since at least the time of Hippocrates, health care providers have recognized their responsibility to protect patients from potential harm resulting from the care they provide. In pharmacy, such harm typically results from a violation of any of the "5 rights" of safe medication use. However, a memorable adage stops short of providing operational guidance to improve medication safety. Specific actionable recommendations are needed to identify changes that, if implemented, would significantly improve the safety of medication delivery and use.

CONCLUSION

Most threats to medication safety result from weaknesses or failures in one or more of the key system elements identified by the Institute for Safe Medication Practices. Pharmacists should be advocates for implementing targeted recommendations to strengthen their practice systems and improve medication safety.

The past and current state of the Czech outpatient electronic prescription (eRecept)

INTRODUCTION

Outpatient Electronic Prescription Systems (OEPSs) are widely used in some European states, such as Denmark, Sweden and the Netherlands. The Czech OEPS (known as eRecept) was introduced in 2011, but with limited functions and voluntary usage it was not much accepted until 2018, when its usage was made compulsory not only for pharmacies, but for physicians as well.

METHODS

Using data from the Czech State Institute for Drug Control (Státní ústav pro kontrolu léčiv or SÚKL in Czech) and from other sources, the system was described and data about its performance since 2013 have been obtained.

RESULTS

The usage of the system was very low between 2013 and 2016, whilst moderate growth was seen in 2017. By 2018, the system has been widely adopted, although some twenty per cent of Czech physicians still do not use the system at all.

DISCUSSION

A sudden rise in usage can be explained as the result of making the system compulsory starting in January 2018. Still, new features of the system are eagerly awaited and should be introduced to expand its benefits.

CONCLUSION

The Czech Republic has joined the EU countries widely using the OEPS.

Evaluation of Transition to Electronic Prescriptions in Turkey: Perspective of Family Physicians

Background: One of the most important steps of the health transformation program involves the application of electronic prescriptions (e-prescriptions) in health services. Information technologies are highly important in generating e-prescriptions, which can be described as a document produced by authorized personnel electronically, containing written information and instructions regarding a patient’s medication and its usage. E-prescribing has become increasingly applied in recent years as a contributing application to prescribers and patients. The aim of this study was to determine the level of satisfaction of family physicians providing primary care in Turkey regarding the application of e-prescriptions, and reveal the related positive effects and problems encountered in the first months of implementation of e-prescribing.

Methods: A questionnaire with eight questions was sent to e-mails of all family physicians working in Turkey in May 2013. A total of 1564 family physicians filled in the questionnaire form and sent it back by e-mail. The responses to openended questions were evaluated by content analysis.

Results: It was observed that the most frequently indicated advantages of the application of e-prescriptions were speeding up the prescription process and saving time (36.6%). The most commonly reported problems regarding the application of e-prescriptions were found to be system-induced problems (26.5%) and internet problems (19.9%). In addition, the mean score of satisfaction of the family physicians who did not report problems with the application of e-prescriptions was higher than that of those who reported having problems with it. In the study, 77.8% of the family physicians were satisfied with the application of e-prescriptions.

Conclusion: Although some problems were reported regarding the application of e-prescriptions in the first months of the application, family physicians participated in the study were found to be satisfied with the application of e-prescriptions, and identified positive effects on their work and processes.

Systematic review and meta-analysis of community pharmacy error rates in the USA: 1993-2015

Importance

While much is known about hospital pharmacy error rates in the USA, comparatively little is known about community pharmacy dispensing error rates.

Objective

The aim of this study was to determine the rate of community pharmacy dispensing errors in the USA.

Methods

English language, peer-reviewed observational and interventional studies that reported community pharmacy dispensing error rates in the USA from January 1993 to December 2015 were identified in 10 bibliographic databases and topic-relevant grey literature. Studies with a denominator reflecting the total number of prescriptions in the sample were necessary for inclusion in the meta-analysis. A random effects meta-analysis was conducted to estimate an aggregate community pharmacy dispensing error rate. Heterogeneity was assessed using the I² statistic prior to analysis.

Results

The search yielded a total of 8490 records, of which 11 articles were included in the systematic review. Two articles did not have adequate data components to be included in the meta-analysis. Dispensing error rates ranged from 0.00003% (43/1 420 091) to 55% (55/100). The meta-analysis included 1 461 128 prescriptions. The overall community pharmacy dispensing error rate was estimated to be 0.015 (95% CI 0.014 to 0.018); however, significant heterogeneity was observed across studies (I²=99.6). Stratification by study error identification methodology was found to have a significant impact on dispensing error rate (p<0.001).

Conclusion and relevance

There are few published articles that describe community pharmacy dispensing error rates in the USA. Thus, there is limited information about the current rate of community pharmacy dispensing errors. A robust investigation is needed to assess dispensing error rates in the USA to assess the nature and magnitude of the problem and establish prevention strategies.

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.

Improving Clinical Decision Support in Pharmacy: Toward the Perfect DUR Alert

The cornerstone of every health care profession is decision making. Historically, the decisions made by pharmacists have focused on ensuring the accuracy and physical integrity of the pharmaceutical product delivered to the patient in strict compliance with the prescriber's order. As the role of the pharmacist evolved over the past half century, the focus of decision making progressively shifted from a product-centric orientation to optimizing the interaction that occurs between the pharmaceutical product and the patient. Toward that end, prospective drug utilization review (pro-DUR) represents, perhaps, the quintessential expression of the pharmacist's contemporary clinical role. Fueled by evolving practice standards, innovations in information technology, and legal mandates such as The Omnibus Budget Reconciliation Act of 1990, computer-assisted pro-DUR systems have become a ubiquitous component of pharmacy practice. While these data-driven clinical decision support systems have clearly demonstrated their ability to improve the quality and safety of medication delivery and use, they have yet to fully achieve their promised potential. Doing so will require recognition of continuing shortcomings and a shared commitment by all stakeholders to develop and adhere to best practice guidelines that will better ensure that alerts received by practitioners are valid, interpretable, clinically significant, and actionable.

DISCLOSURES

The authors received no funding for this article. Rupp discloses consultancy fees from Surescripts unrelated to this manuscript. Both authors contributed equally to concept, analysis, and manuscript preparation.

The good pharmacy practice on Einstein Program at Paraisópolis Community

Objectives:

To describe indicators and processes developed and implemented for pharmaceutical assistance at the Einstein Program at Paraisópolis Community pharmacy.

Methods:

This was a descriptive study of retrospective data from January 2012 to December 2015. Data were obtained from spreadsheets developed for monitoring the productivity and care quality provided at the pharmacy. The evaluated variables were pharmaceutical assistance to prescription, pharmaceutical intervention, orientation (standard and pharmaceutical) and pharmaceutical orientation rate.

Results:

The pharmacy assisted, on average, 2,308 prescriptions monthly, dispensing 4,871 items, including medications, materials and food supplements. Since March 2015, virtually, the pharmacist analyzed all prescriptions, prior to dispensing. In the analyzed period, there was an increase in monthly pharmaceutical interventions from 7 to 32 on average, and, although there was a decrease in the number of standard orientation, the pharmaceutical orientation had an increase, causing a rise of pharmaceutical orientation rate from 4 to 11%.

Conclusion:

The processes developed and implemented at the program pharmacy sought to follow the good pharmacy practice, and help patients to make the best use of their medications.

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.

Positioning a Paediatric Compounded Non-Sterile Product Electronic Repository (pCNPeRx) within the Health Information Technology Infrastructure

Numerous gaps in the current medication use system impede complete transmission of electronically identifiable and standardized extemporaneous formulations as well as a uniform approach to medication therapy management (MTM) for paediatric patients. The Pharmacy Health Information Technology Collaborative (Pharmacy HIT) identified six components that may have direct importance for pharmacy related to medication use in children. This paper will discuss key positions within the information technology infrastructure (HIT) where an electronic repository for the medication management of paediatric patients' compounded non-sterile products (pCNP) and care provision could be housed optimally to facilitate and maintain transmission of e-prescriptions (eRx) from initiation to fulfillment. Further, the paper will propose key placement requirements to provide for maximal interoperability of electronic medication management systems to minimize disruptions across the continuum of care.

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.

Challenges to the implementation of a nationwide electronic prescribing network in primary care: a qualitative study of users' perceptions

BACKGROUND AND OBJECTIVE

The objective of this study was to identify physicians' and pharmacists' perceptions of the challenges and benefits to implementing a nationwide electronic prescribing network linking medical clinics and community pharmacies in Quebec, Canada.

METHODS

Forty-nine people (12 general practitioners, 2 managers, 33 community pharmacists, and 2 pharmacy staff members) from 40 points of care (10 primary care clinics (42% of all the connected sites) and 30 community pharmacies (44%)) were interviewed in 2013. Verbatim transcripts were analyzed using thematic analysis.

RESULTS

A low level of network use was observed. Most pharmacists processed e-prescriptions by manual entry instead of importing electronically. They reported concerns about potential errors generated by importing e-prescriptions, mainly due to the instruction field. Paper prescriptions were still perceived as the best means for safe and effective processing of prescriptions in pharmacies. Speed issues when validating e-prescription messages were seen as an irritant by physicians, and resulted in several of them abandoning transmission. Displaying the medications based on the dispensing data was identified as the main obstacle to meaningful use of medication histories.

CONCLUSIONS

Numerous challenges impeded realization of the benefits of this network. Standards for e-prescription messages, as well as rules for message validation, need to be improved to increase the potential benefits of e-prescriptions. Standard drug terminology including the concept of clinical medication should be developed, and the implementation of rules in local applications to allow for the classification and reconciliation of medication lists from dispensing data should be made a priority.