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Objectives: The number of electronic prescriptions (ePrescriptions) grows steadily in Belgium as in other European countries. In the future, Belgium wants to dematerialize the ePrescription flow, removing all paper trails. A quality check of the digital content and implementation of national ePrescription guidelines in the field was conducted, comparing the content at both prescription and pharmacy side. Methods: An explanatory mixed-methods design was applied. In a first phase, potential problems (warning flags) were identified by consulting stakeholders. Secondly, the warning flags were validated to problems (errors) in a random set of ePrescriptions collected in April 2019. In a third phase, explanatory interviews were held with various stakeholders in order to find explanations and to identify the initiators of these errors. Results: In the first phase, 15 warning flags were identified to evaluate the quality of an ePrescription. In the second phase, a random selection of 11,798 ePrescriptions was validated. The most prevalent errors found, were the digital construction of the messages (18.88%), combined with lots of necessarily deemed substitutions by the pharmacist (3.39%) not following what was prescribed originally. In the third phase, stakeholders indicated that software of the prescriber and the use of inconsistent databases between prescriber and pharmacy can often be seen as the cause and initiator of these problems. Conclusions: Use of authentic medication databases and well-designed software systems have the potential to solve ePrescription problems. Focus should go to prevention instead of detection.

BackgroundFree-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.MethodsA 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.ResultsPharmacy 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, pConclusionPharmacy 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.

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 open-ended 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. © 2019 The Author(s). 2-s2.0-85058557719 PubMed: 30709101

Background Pharmacists in community and hospital pharmacies assess prescriptions to prevent prescription errors and adverse drug events. There are, however, few reports on prevalence of clinical important pharmaceutical interventions for patients located within primary care. Objective To study documented pharmaceutical interventions on prescriptions in Norwegian pharmacies for patients located in primary care. Setting Data were collected in 11 community pharmacies during a 3 months period in 2016, and the outpatient department of four hospital pharmacies in Norway during a 6 months period of 2018. Method Retrospective analysis of electronically documented pharmaceutical interventions on prescriptions for patients located in primary care. Main outcome measure The number and classification of pharmaceutical interventions in relation to the total number of prescriptions. Results An intervention was documented in 124,178 (45.1%) of the 275,339 prescriptions dispensed during the study period. Interventions of potential clinical importance were performed and documented in 0.8% (2262) of the prescriptions. Conclusion A substantial number of pharmaceutical interventions are performed on prescriptions in Norwegian pharmacies after introduction of electronic prescriptions. A potentially clinical important intervention is performed in one of every 125 prescriptions (0.8%). This result indicates that pharmacists at Norwegian pharmacies prevent more than 400,000 prescription errors of potential clinical importance each year.

Objectives To investigate (1) what Finnish pharmacy customers have learned about the implemented electronic prescriptions (e-prescriptions), (2) from whom or where have they learned about them, (3) whether they are satisfied with the information received and if not, (4) what more information they would like. Methods We surveyed 1288 (44%) pharmacy customers aged ≥18 years collecting medicines for themselves with e-prescriptions in 18 pharmacies across Finland in 2015. Descriptive analysis, chi-square and Fisher's exact tests were used in the analysis. Key findings Nearly all respondents had received information about e-prescriptions (97%). A physician (67%) and a pharmacy (53%) were the most common information sources. The vast majority of the respondents had learned about how to purchase medicines with an e-prescription (86%). Most of them had also received information about the benefits of e-prescriptions (59%) and how they can view their e-prescriptions on a computer (58%). The majority of pharmacy customers felt they had received sufficient information on e-prescriptions (83%). Those dissatisfied with the information received asked for more information about how e-prescriptions are protected against misuse (47%) and who can view their e-prescriptions (44%). Conclusions Most Finnish pharmacy customers have learned how to use e-prescriptions, what their benefits are and how to view e-prescriptions on a computer. The information is generally obtained from physicians and pharmacies. Information needs concern data protection and data security. Customers are mainly satisfied with the information received. However, their knowledge only partly meets the national requirements on the information they should be provided with.

SummaryAfter implementation of a system-wide EMR within our university system, e-prescribing is now commonplace.The authors conducted a study to assess whether optimization of computerized provider order entry (CPOE) can reduce errors in these electronically transmitted prescriptions and would require less frequent interventions from pharmacists, in particular the need for them to “call to clarify” (CTC) details of particular prescriptions. Secondary analysis based on cost assumptions was preformed to presume cost differences before and after optimization changes.In order to generate complete, error-free prescriptions, optimization changes were implemented in the form of in line validation messages. These messages were generated if (1) an order did not specify a provider or pharmacy; (2) the DEA requirements were not met; (3) character limits were exceeded in patient sig or demographics or (4) administration instructions had breaks or had both discrete and free text elements. Retrospectively, prescriptions were randomly selected from a nine month period before and after implementing changes. These prescriptions were analyzed by a pharmacist and a nurse to identify types of errors that would require a CTC to a prescribing provider. Errors were compared statistically to determine effectiveness of changes pre and post optimization.A total of 602 prescriptions were analyzed; 301 before changes and 301 after changes. Of these prescriptions, 20.27% had errors before changes and 12.96% had errors after changes. The decline in the error rate was considered statistically significant for pImplementing optimization changes to the CPOE resulted in a reduction in error rate requiring pharmacist CTC. This study identifies effective optimization changes for electronic prescribing that can reduce prescribing errors and may result in cost saving.

The National Diabetes Inpatient Audit is a yearly audit aimed at providing a snapshot view on various aspects of diabetes care across hospitals in England. Results are provided for each hospital and are shown in comparison to other hospitals. Since 2011, our 450-bedded hospital has been in the first quartile with regards to medication errors, prescription errors, medicine management errors and insulin errors. In the 2016 audit, we had 11.6% medication errors whereas across England, there were 44.6% medication errors. Our service is exemplary on many fronts. Foundation year doctors get formal training in diabetes care. Information Technology is key in providing the fail-proof electronic prescribing software, access to General Practitioner’s Health records, safe insulin prescribing e-module, and up-to-date online clinical guidelines. We have Pharmacists and Pharmacist Technicians who check electronic prescriptions on a daily basis. We also benefit from the service of a Diabetes Specialist Pharmacist. We provide a twice-weekly specialist diabetes ward round across the whole hospital and patients are usually identified from the Electronic Patients Record software. The Diabetes Specialist Nurses are additionally available for one-to-one education Monday to Friday 0900 to 1700. Finally, we run a comprehensive diabetes education day for nurses and other allied health care professionals twice a year. Disclosure M. Parsad: None. K.D. Lambert: None. D. Ardern: None. A.C. Mezzullo: None.

Lääkemääräys on laadittava sähköisesti 1.1.2017 alkaen. Laissa määriteltyjen poikkeustapausten perusteella laaditussa kirjallisessa ja puhelinlääkemääräyksessä on perusteltava, miksi sitä ei ole annettu sähköisesti. Valtakunnallisen toiminnallisen muutoksen myötä on mahdollista selvittää ensimmäisen kerran lääkemääräysten kokonaismäärä Suomessa. Tutkimusaineistona ovat reseptikeskukseen tallennetut potilastietojärjestelmissä ja Kelaimessa laaditut sähköiset lääkemääräykset sekä apteekeissa tallennetut (sähköistetyt) kirjalliset, puhelin- ja erityislupavalmisteiden lääkemääräykset tutkimusjaksolla 1.1.–30.11.2017. Reseptikeskukseen tallennettiin tutkimusjaksolla 29,477 (100 %) milj. sähköistä lääkemääräystä, joista 96,6 % oli laadittu potilastietojärjestelmissä ja 1,0 % Kelaimella. Apteekeissa sähköistettiin 0,375 (1,3 %) milj. lääkemääräystä, joista 0,246 (0,8 %) milj. oli kirjallisia ja 0,122 (0,4 %) milj. puhelinlääkemääräyksiä. Apteekeissa sähköistetyistä lääkemääräyksistä yli puolet oli kirjallisia lääkemääräyksiä, jotka oli laadittu teknisen häiriön perusteella. Tutkimuksessa selvitettiin ensimmäisen kerran Suomessa lääkemääräysten kokonaismäärää vuoden 2017 yhdentoista kuukauden tietojen perusteella. Valtakunnallisessa seurannassa ilmeni päivittäin teknisiä häiriöitä, joiden perusteella laadittiin kirjallisia ja puhelinlääkemääräyksiä., Electronic prescription is mandatory in Finland since 1 January, 2017. A physician or a dentist can issue a written or a telephone prescription under exceptional circumstances, and the reason for issuing must be given. Because of the administrative nationwide change it was the first time possible to find out prescription volume in Finland. Written and telephone prescriptions were typed in to the national Prescription Centre at the 815 pharmacies. Electronic prescriptions were sent to the Prescription Centre (ePrescription Service) from electronic patient data systems, or Kelain web prescription service. Data from the Prescription Centre were extracted from 1 January till 30 November, 2017. There were 29.477 Million (100%) new electronic prescriptions, of which 96.6% were from electronic patient data systems and 1.0% from Kelain web service. Altogether 0.375 Million (1.3%) prescriptions were typed in at the pharmacies, of which 0.246 Million (0.8%) were written and 0.122 Million (0.4%) telephone prescriptions. Approximately half of the prescriptions typed in at the pharmacies were written prescriptions that were issued because of a technical failure. In this study we report the first time prescription volume in Finland. All the prescriptions in the national Prescription Centre are electronic, and only 1.3% of the prescriptions were typed in at the pharmacies in the first eleven months since the electronic prescription became mandatory 1 January, 2017. Written prescriptions were issued because a technical failure occurred in local or areal data or software systems.

Importance Electronic prescribing promises to improve the safety and clarity of prescriptions. However, it also can introduce miscommunication between prescribers and pharmacists. There are situations where information that is meant to be sent to pharmacists is not sent to them, which has the potential for dangerous errors. Objective To examine how frequently prescribers or administrative personnel put information intended for pharmacists in a field not sent to pharmacists, classify the type of information included, and assess the potential harm associated with these missed messages. Design, Setting, Participants Medication record data from our legacy electronic health record were requested for ambulatory care patients seen at an academic medical center from January 1, 2000, to May 31, 2015 (20 123 881 records). From this database, 6 060 272 medication orders met our inclusion criteria. We analyzed a random sample of 10 000 medication orders with internal comments. Main Outcomes and Measures Reviewers classified internal comments for intent. Comments intended for pharmacists were also sorted into descriptive categories and analyzed for the potential for patient harm. Results We found that 11.7% of the prescriptions in our sample contained comments that were intended to be sent to pharmacists. Many comments contained information about the dose, route, or duration of the prescription (38.0%). Approximately a third of the comments intended for pharmacists contained information that had the potential for significant or severe harm if not communicated. Conclusion We found undelivered comments that were clearly intended for pharmacists and contained important information for either pharmacists or patients. This poses a legitimate safety concern, as a portion of comments contained information that could have prevented severe or significant harm.

Objective To validate electronic prescriptions (e-prescriptions) as a method for measuring treatment adherence in patients with hypertension. Methods This prospective study initially included 120 patients treated for hypertension in primary care centers. Adherence was measured using the gold standard, the medication event monitoring system (MEMS), versus the index test, the e-prescription program, at baseline and at 6, 12, 18 and 24 months. We calculated the adherence rate using the MEMS and the medication possession ratio (MPR) for the e-prescriptions. We considered patients adherent if they had an adherence rate of 80% to 100%. To validate the e-prescription, we obtained measures of diagnostic accuracy, the Kappa concordance index, and the area under the ROC curve (AUC). Results We included 102 patients. Overall adherence was 77.4% by MEMS (95%CI: 66.8-88) and 80.4% (95%CI: 70.3-90.5) by MPR. At 24 months, sensitivity was 87% and specificity, 93.7%. The AUC was 0.903 (95%CI: 0.817-0.989). Conclusion Measures of treatment adherence were not significantly different between e-prescription and gold standard at most visits, and the e-prescription showed good discriminatory diagnostic capacity. Practice implications If patients are included in an e-prescription program for at least 2 years, e-prescription is an inexpensive method to measure adherence in hypertension.

Background In July 2015, the electronic software CATO was introduced for chemotherapy prescribing. Before CATO implementation, chemotherapy prescriptions were handwritten on a designated form. Purpose To determine the impact of electronic prescribing by comparing the rate of prescribing errors and omissions using handwritten versus electronic prescriptions, and to compare the clinical significance of errors and omissions for both prescribing methods. Material and methods A data collection form was designed based on chemotherapy prescription requirements detailed by the National Cancer Control Programme (NCCP) in Ireland. Omissions and errors were defined as the absence or incorrect recording of these requirements. Data collection was completed by 4 pharmacists. Pharmacists categorised prescription errors/omissions as potentially clinically significant or not. This was not graded for this analysis. A pilot (n=30) was completed by all data collectors to ensure consistent data collection. Only parenteral oncology/haematology prescriptions were included. Data were collected in two phases. Phase 1 was a retrospective review of handwritten chemotherapy prescriptions identified by random systematic sampling. Phase 2 was a prospective analysis of electronic prescriptions. A sample size with 60% population proportion was chosen. Results 153 handwritten prescriptions and 153 electronic prescriptions were analysed. 53% reduction in prescribing errors was found (p Conclusion Introduction of CATO prescribing has significantly reduced prescribing errors. Potentially clinically significant errors and omissions have also greatly reduced. These data, although subjective, suggest that the quality and safety of chemotherapy prescribing has greatly improved. Continued auditing of prescribing errors and omissions is imperative to further improve these results. No conflict of interest

Background Medicines prescription is the centrepiece in the triad of care (patient–prescriber–pharmacy). The electronic prescription has long been considered an effective means to reduce transcription errors as well as securing the flow of drugs at the hospital level. However, the experience of the Massachusetts General Hospital of Boston team found an error rate comparable between manual and electronic prescriptions (11.7%)1 What about the time saving that electronic prescribing can provide compared with manual prescribing? Purpose The objective of this work was to evaluate the impact of electronic prescription of medicine on time saving of the pharmaceutical team compared with manual prescription in our hospital. Material and methods We analysed the prescriptions received and processed in our hospital pharmacy over a period of 1 month according to good dispensing practices. We calculated the time between receipt of prescriptions and dispensation of medicines by the pharmaceutical team for both prescription modalities (electronic and manual). Results 384 (58%) manual prescriptions and 276 (42%) electronic prescriptions were analysed, prepared and dispensed by the pharmacy team in our hospital. The average length of preparation of manual prescriptions was 25±10 min and the average length of preparation of electronic prescriptions was 15 min±5. The difference was statistically significant (p Conclusion Our team found a considerable gain in time (10 min by prescription or 170 min per day) between prescription of medicines by physicians and their dispensation by the hospital pharmacy despite the high number of drugs dispensed in the case of electronic prescriptions. This time saved would allow the pharmaceutical team to focus on other activities, more precisely the pharmacological analysis of prescriptions and hospital preparations. References and/or acknowledgements 1. Nanji KC, Rothschild JM, Salzberg C, et al. Errors associated with outpatient computerised prescribing systems. J Am Med Inform Assoc2011;18:767–73. No conflict of interest

A pediatric compounded non-sterile products repository (pCNP) to optimize the effectiveness and safety of “off-label” use of compounded pharmacotherapy through complete transmission of electronic prescriptions across the continuum of care is described. The advent of electronic prescribing has the potential to refocus and resolve long-standing issues of prescription therapy for pediatric patients related to formulation, indication, dosing, and outcomes follow-up, among others. This white paper describes the architecture and function of the pCNP repository. Further, it calls on professional societies, health information technology (HIT) and pharmaceutical industries, universities, and government to create a safer pediatric pharmacotherapy system across the continuum of care. This system would include pCNPs within the existing federal and corporate database structures for medical language, and integrates advanced system safety features as requirements for prescribing, compounding, and dispensing non-mass produced prescription therapies for children.

Objective The objectives of this cross-sectional study were to estimate the prevalence of unintended discrepancies between three sources of prescription information and to describe the types of electronic prescribing system vulnerabilities identified. Methods Staff from community pharmacies identified approximately 200 new prescriptions written at three participating ambulatory care clinics (2 adult, 1 paediatric). Unintended discrepancies were identified by comparing three sources of prescription information: (1) the prescriber's note as documented in the patient's chart; (2) the electronic prescription (e-prescription) entered into the clinic's electronic prescribing software; (3) the medication that was ultimately dispensed by the pharmacy as indicated on the prescription label. The discrepancy rate was calculated by dividing the number of discrepancies identified by the number of prescriptions evaluated. Results A total of 602 prescriptions written by 33 prescribers were evaluated from the 3 ambulatory care clinics. The discrepancy rate between the prescriber's note and the e-prescription was 1.7%, 0.6% and 3.9% for the three clinics. The discrepancy rate between the e-prescription (clinic) and the prescription label (pharmacy) was 4.2%, 0.9% and 1.5%. Differences between directions for administration was the most common type of discrepancy identified. Conclusions Discrepancy rates between the prescriber's note and the e-prescription were similar to the discrepancy rates between the e-prescription and pharmacy label. To reduce outpatient medication errors, a better understanding is needed of the sources of discrepancies that occur within the prescriber's clinic, and those that occur between the clinic and pharmacy.

Handwritten recycled paper prescription for parenteral nutrition (PN) may become a concentrated source of viable contaminants, including pathogens. This study examined the effect of using fresh printouts of electronic prescriptions on these contaminants.Cellulose sponge stick swabs with neutralizing buffer were used to sample the surfaces of PN prescriptions (n = 32 handwritten recycled; n = 32 printed electronic) on arrival to the pharmacy or following printing and PN prescriptions and bags packaged together during delivery (n = 38 handwritten recycled; n = 34 printed electronic) on arrival to hospital wards. Different media plates and standard microbiological procedures identified the type and number of contaminants.Staphylococcus aureus, fungi, and mold were infrequent contaminants. nonspecific aerobes more frequently contaminated handwritten recycled than printed electronic prescriptions (into pharmacy, 94% vs 44%, fisher exact test P .001; onto wards, 76% vs 50%, p = .028), with greater numbers of colony-forming units (CFU) (into pharmacy, median 130 [interquartile range (IQR), 65260] VS 0 [075], Mann-Whitney U test, P .001; onto wards, median 120 [15320] vs 10 [040], P = .001). packaging with handwritten recycled prescriptions led to more frequent nonspecific aerobic bag surface contamination (63% vs 41%, fisher exact test P = .097), with greater numbers of CFU (median 40 [IQR, 080] VS 0 [040], Mann-Whitney U test, P = .036).The use of printed electronic PN prescriptions can reduce microbial loads for contamination of surfaces that compromises aseptic techniques.

Objectives The purpose was to explore pharmacists’ opinions regarding the impacts of electronic prescriptions (ePrescriptions) on medication safety in Finnish community pharmacies. Further objectives were to explore how often and what kinds of ambiguities or errors pharmacists have perceived in ePrescriptions. Method A survey of randomly selected dispensers (n = 1004) and pharmacists (n = 228) was conducted in 2014. Results Altogether 778 questionnaires were returned, yielding response rates of 64% (n = 635) for dispensers and 65% (n = 143) for pharmacists. The respondents felt that ePrescriptions improve medication safety in many areas: they lower the number of prescription forgeries, reduce the risk of dispensing errors, promote better management of the patient’s overall medication, facilitate monitoring of duplicative therapy and drug interactions, and lessen the risk of incorrect interpretation of prescriptions. Many respondents (32%) reported that they had weekly found ambiguities or errors in ePrescriptions that required clarification during the dispensing process. Of the respondents, 18.6% had found such ambiguities or errors daily or almost daily. The three most common ambiguities or errors in ePrescriptions were incorrect total amount of medication (79.0%), missing notation of exceptional dosage instructions or exceptional purpose of use (SIC!) (69.0%), and unclear or incorrect dosage instructions (65.4%). Incorrect strength (14.9%) and incorrect pharmaceutical form (14.2%) were also commonly experienced problems. Conclusions According to Finnish community pharmacists, the introduction of ePrescriptions has promoted medication safety in many areas. However, ambiguities and errors are common in ePrescriptions. Some of these can delay dispensing of the medicine, whereas others can cause serious risks to medication safety., final draft, peerReviewed

Background Clinical decision support systems (CDSS) reduce prescription errors, but their effectiveness is reduced by high alert rates, “alert fatigue”, and indiscriminate rejection. Objectives To compare acceptance rates of alerts generated by the SafeRx ® prescription CDSS among different alert types and departments in a tertiary care hospital, identify factors associated with alert acceptance, and determine whether alert overrides were justified. Methods In a retrospective study, we compared acceptance rates of all prescription alerts generated in 2013 in 18 departments of Israel’s largest tertiary care center. In a prospective study in 2 internal medicine departments, we collected data on factors potentially associated with alert override, and an expert panel evaluated the justification for each overridden alert. We used multivariate analyses to examine the association between patient and physician-related factors and alert acceptance. Results In the retrospective study, of 390,841 prescriptions, 37.1% triggered at least one alert, 5.3% of which were accepted. Acceptance rates ranged from 7.9% for excessive dose alerts to 4.0% for duplicate drug and major drug-drug interactions alerts (p Conclusions The vast majority of SafeRx ® alerts are overridden, and overriding is justified in most cases. Minimizing the number of alerts is essential to reduce the likelihood of developing “alert fatigue”. Our findings may inform a rational, department-specific approach for alert silencing.

Background Increased electronic prescribing (eRx) rates have the potential to prevent errors, increase patient safety, and curtail fraud. US Federal meaningful use guidelines require at least a 40% electronic prescribing rate. Objective We evaluated eRx rates among primary care providers in New York City in order to determine trends as well as identify any obstacles to increased eRx rates required by meaningful use guidelines. Methods The datawe analysed included automatic electronic data transmissions from providers enrolled in the Primary Care Information Project (PCIP) from 1 January 2009 to 1 July 2010 and follow-up telephone calls to a subset of these providers to identify potential barriers to increased eRx usage. Results Over the course of the study, these providers increased the eRx rate from 12.9 to 27.5%, with an average rate of 24.1%. Conversations with providers identified their perceived barriers to increased eRx use as primarily patient preference for paper prescriptions and a belief that many pharmacies do not accept eRx. Conclusions The data gathered from our providers indicate that there is an increasing trend in the eRx rate to 27.5% by July 2010, but still short of the 40% meaningful use level. However, obstacles to increased rates remain primarily providers' belief that many patients prefer paper prescriptions and many pharmacies are not yet prepared to accept electronic prescriptions.

This study investigated whether the adoption of electronic prescriptions (e-prescriptions) had increased in the 27 member countries of the European Union (EU) in the beginning of this decade. Our previous study in 2002 concerning the old union with 15 countries had discovered that e-prescriptions were rare in daily practice and that there was only slight interest for their future use. Since the internal market with free movement of people, goods, services, and capital is a central issue in the Union, we took a cross-border view of the use of the e-prescriptions.A semiopen questionnaire on the use of e-prescriptions, chosen systems, the process itself, investments, and the acceptance of non-national European prescriptions was e-mailed to community pharmacy associations of the 27 EU member countries that were members of or otherwise identified by the Pharmaceutical Group of the EU.Five countries were using e-prescriptions as a part of their daily practice, but only Denmark and Sweden reported nationwide use. These countries were the same that used e-prescriptions nationally already in 2002. Pilots presented in 2002 had not yet advanced into daily practice. Some new pilots/projects were prepared in the old and new member countries. E-prescription models and systems used were divergent between the countries and sometimes even within a country.Nationwide use of e-prescriptions was not more common than in 2002. Several countries had piloted or were piloting projects on e-prescriptions. Interoperability of different systems is a challenge to which EU-funded projects might offer a solution.

Many e-prescribing systems allow for both structured and free-text fields in prescriptions, making possible internal discrepancies. This study reviewed 2914 electronic prescriptions that contained free-text fields. Internal discrepancies were found in 16.1% of the prescriptions. Most (83.8%) of the discrepancies could potentially lead to adverse events and many (16.8%) to severe adverse events, involving a hospital admission or death. Discrepancies in doses, routes or complex regimens were most likely to have a potential for a severe event (p=0.0001). Discrepancies between structured and free-text fields in electronic prescriptions are common and can cause patient harm. Improvements in electronic medical record design are necessary to minimize the risk of discrepancies and resulting adverse events.

e-Prescribing systems with decision support do not routinely communicate an adequate amount of information regarding the prescribers' decision to pharmacists. To address this communication gap in the e-prescribing process, we implemented a system called Show Your Work (SYW) that appends alerts and override comments to e-prescriptions generated by an e-prescribing system. To assess the quantitative impact of this system, we conducted a randomized, double-blinded, controlled study to assess pharmacy callback rates and types, and to uncover any unintended consequences of the annotations. Each day, SYW output across the enterprise was turned ''on'' or ''off'' randomly for all e-prescriptions. A convenience sample of three pharmacies, blinded to SYW status, submitted callback logs each day. These logs were used to calculate the rate of and reason for callbacks. At the conclusion of the study, we surveyed the 50 most frequently used pharmacies in our area to assess the impact of SYW on satisfaction and communication. A total of 202 callbacks had occurred yielding a callback rate of 45 callbacks/1000 prescriptions for SYW ''on'' days and 40 callbacks/1000 prescriptions for ''off'' days (p=0.4). We received 38 surveys (76% response rate) with 33 respondents commenting about SYW. Most respondents agreed (69%) that SYW favorably impacted callbacks-especially with pediatric prescriptions (82%). Comments suggested that SYW increased callbacks where necessary and decreased them in other situations, but did not contribute to unnecessary callbacks. These findings support the continued and potentially expanded use of SYW by e-prescribing systems to enhance communication with pharmacists.

Electronically transmitted prescriptions (ETPs) became common after 1995 in Sweden; however, it is accompanied by a substantial increase in the number of prescriptions not picked up at pharmacies.To investigate the "no pick-up" rates of ETPs at pharmacies across type of drug and patient age and gender and the reasons patients' report for no pick-up.A cross-sectional study examining no pick-up of ETPs transmitted during 3 months in 2002, and a mail survey of patients to determine the reasons for failure to pick-up in the county of Sörmland, Sweden, with a population of 261,000, and 21 pharmacies. Chi-square tests were used for calculations of frequency differences among groups.The overall no pick-up rate of ETPs was 2.5%; men had consistently higher rates than women. The highest rates were seen for adolescents and young adults. Rates were higher than average for antibiotics. About 60% of the answers indicated that prescriptions not picked up were duplicate prescriptions or not needed. "Unintentional nonadherence" was reported by one-fifth of patients.No pick-up rate in general was low (2.5%), but there were differences across patient age and gender, the rates being higher among adolescents and young adults. Duplicate prescriptions may explain a significant share of the abandoned prescriptions.

The Institute of Medicine revealed that about 7,000 Americans are killed each year due to medication errors. This alarming number is prompting many physicians and practitioners to change their old habits of prescribing. Now we have e-prescribing! Electronic prescribing or e-prescribing, as it is very well known now, is the use of an automated data-entry system to generate electronic prescriptions. From cell phones to huge systems, physicians are always waking up to this new reality. This method of prescribing would eventually replace the current practice in writing the prescription on a paper. Electronic or computerized prescribing systems in the practice of medicine are a change that is belated. About 90% of prescriptions in the United States are still handwritten. Instead, medications should be ordered on an electronic platform such as a handheld device that is ultimately interacting with three databases: patient drug history, scientific drug information and guideline reference, and patient-spe...

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.

The adoption of electronic prescribing is on the rise, as it reduces medication errors compared to handwritten orders. The inadvertent dispensing of discontinued medications is a type of medication error that is less well described, but one that can lead to adverse events. Software for electronic prescriptions transmits orders for refills or new prescriptions, but not discontinuations, to the pharmacy. Medications that have been stopped are displayed only at the prescribing facility's electronic medical record (EMR). This report describes five cases in which the pharmacy dispensed electronically discontinued medications, two of which contributed to adverse outcomes.

Objectives The increasing rate of e-prescribing is associated with a significant number of unclaimed prescriptions. The costs of unclaimed e-prescriptions could create an unwanted burden on community pharmacy practices. The objective of this study was to calculate the rate and costs of filled but unclaimed e-prescriptions at an independent pharmacy. Methods This study was performed at a rural independent pharmacy in a Midwestern state. The rate and costs of the unclaimed e-prescriptions were determined by collecting information about all unclaimed e-prescriptions for a 6-month period from August 2013 to January 2014. The costs of unclaimed prescriptions included those expenses incurred to prepare the prescription, contact the patient, and return the unclaimed prescription to inventory. Two sensitivity analyses were conducted. Results The total cost of 147 unclaimed e-prescriptions equaled $3,677.70 for the study period. Thus, the monthly cost of unclaimed e-prescriptions was $612.92 and the average cost of each unclaimed prescription was $25.02. The sensitivity analyses showed that using a technician to perform prescription return tasks reduced average costs to $19.33 and that using a state Medicaid cost of dispensing resulted in average costs of $18.54 per prescription. The rate of unclaimed e-prescriptions was 0.82%. Conclusion The percentage of unclaimed e-prescriptions in this pharmacy was less than 1%. In addition to increased cost, unclaimed e-prescriptions add inefficiency to the work flow of the pharmacy staff, which can limit the time that they are available for performing revenue-generating activities. Adjustments to work flow and insurer policies could help to reduce the burden of unclaimed e-prescriptions.

SummaryObjective: To determine whether specific design interventions (changes in the user interface (UI)) of an electronic health record (EHR) medication module are associated with an increase or decrease in the incidence of contradictions between the structured and narrative components of electronic prescriptions (internal prescription discrepancies).Materials and Methods: We performed a retrospective analysis of 960,000 randomly selected electronic prescriptions generated in a single EHR between 01/2004 and 12/2011. Internal prescription discrepancies were identified using a validated natural language processing tool with recall of 76% and precision of 84%. A multivariable autoregressive integrated moving average (ARIMA) model was used to evaluate the effect of five UI changes in the EHR medication module on incidence of internal prescription discrepancies.Results: Over the study period 175,725 (18.4%) prescriptions were found to have internal discrepancies. The highest rate of prescription discrepancies was observed in March 2006 (22.5%) and the lowest in March 2009 (15.0%).Addition of „as directed“ option to the dropdown decreased prescription discrepancies by 195 / month (p = 0.0004). An non-interruptive alert that reminded providers to ensure that structured and narrative components did not contradict each other decreased prescription discrepancies by 145 / month (p = 0.03). Addition of a „Renew / Sign“ button to the Medication module (a negative control) did not have an effect in prescription discrepancies.Conclusions: Several UI changes in the electronic medication module were effective in reducing the incidence of internal prescription discrepancies. Further research is needed to identify interventions that can completely eliminate this type of prescription error and their effects on patient outcomes.Citation: Turchin A, Sawarkar A, Dementieva YA, Breydo E, Ramelson H. Effect of EHR user interface changes on internal prescription discrepancies. Appl Clin Inf 2014; 5: 708–720http://dx.doi.org/10.4338/ACI-2014-03-RA-0023

Background Electronic prescribing (e-prescribing) may prevent medication errors caused by prescription illegibility; however, information technologies also may introduce different kinds of medication errors. Objective To identify and quantify e-prescribing problems reported through an electronic prescribing incident reporting tool in the United States. Methods Voluntary and anonymous reports to a web-based, e-prescribing incident reporting tool were collected during 18 months using convenience sampling. Questions in the reporting tool were designed to elicit information on pharmacists' experiences with e-prescribing. Data were analyzed to characterize the different types of e-prescribing concerns. Results A total of 484 reports were collected through the incident reporting tool. Out of 484 reports, 75% corresponded to electronic prescriptions received directly into pharmacies' computers and 23% were computer-generated prescriptions faxed to pharmacies. Most of reports corresponded to comments, complaints or identified unsafe conditions regarding electronic prescriptions (49%), followed by incidents that did not reach the patient (44%) and those that reached patients (6%). The majority of problems reported involved directions (24%) and quantity selection (12%). Conclusion The use of an incident reporting tool revealed a variety of issues regarding e-prescribing. The majority of the issues reported in this study were related to directions and quantity selection. The findings in this study indicate that software system changes and appropriate prescriber training are required to decrease or eliminate some of these issues.

BACKGROUND Non-adherence to essential medications represents an important public health problem. Little is known about the frequency with which patients fail to fill prescriptions when new medications are started (“primary non-adherence”) or predictors of failure to fill.

The legal framework in South Africa (SA) provides for strict requirements regarding prescriptions. However, pharmacists are still confronted daily with illegible handwritten scripts, increasing the risk of medication errors. E-prescribing is being implemented in SA to overcome these disadvantages. The general regulations made in terms of the Medicines and Related Substances Act as well as the Electronic Communications and Transactions Act must be read conjointly for the purposes of understanding the legal framework of electronic prescriptions in SA.

Introduction A paediatric pharmacist orders paediatric parenteral nutrition (PN), following discussion with the gastroenterology Registrar or Consultant. The PN is then prescribed on the electronic drug chart by a rotational gastroenterology SHO. Nursing staff administer the PN as per electronic prescription. Last year, there were nine reported PN prescribing or administration incidents which affected patient care at this Trust. Aim To establish whether paediatric PN regimens were correctly documented in medical notes, prescribed on electronic drug chart, endorsed on insert for notes (a written confirmation of the bag9s constituents) and administered as per electronic prescription. Standards 1. 100% of PN regimens (amount to be administered and number of hours of infusion) are documented daily in the patient9s notes, as discussed at ward round. 2. 100% of PN regimens are clinically appropriate for the patient each day. 3. 100% of electronic PN prescriptions have the correct date, infusion volume, infusion rate and number of hours of infusion. 4. 100% of PN insert for notes are endorsed with amount to be administered, number of hours of infusion and signed by prescriber. 5. 100% of infusion pumps are set to run at the correct rate as per electronic prescription. Method Data was collected prospectively for 5 weeks. All paediatric in-patients on PN were included. On weekdays, patient medical notes were checked for documentation of regimens. Each weekday morning, PN infusion pump rates were checked. Each weekday afternoon, electronic prescriptions were screened, prior to administration. PN for the weekend was prescribed and screened in advance on Friday. PN insert for notes were checked for endorsement and prescriber9s signature. Results There were 10 patients in total, with 3–7 paediatric in-patients on PN at any one time. There were 159 electronic prescriptions and 154 inserts for notes. Patient medical notes were checked for documentation 125 times. Infusion pumps were checked 108 times. All prescribed PN regimens were clinically appropriate for the patients each day (standard 2). All infusion pumps were set to run at the correct rate by nursing staff (standard 5). PN regimens were fully documented in patient notes only 42% (53/125) of the time (standard 1). Only 68% (105/154) of insert for notes were endorsed and signed by the prescribing doctor (standard 4). 18% (29/159) of electronic prescriptions were prescribed incorrectly (standard 3). 28 incorrect prescriptions were picked up by the pharmacist and amended prior to administration. Conclusions The audit demonstrated that documentation of PN regimens in medical notes and endorsement of PN insert for notes by prescribers was poor and needs to be improved. There were 29 electronic prescribing errors, of which 97% (28/29) were corrected by the pharmacist prior to administration. This audit highlighted that formal training for doctors new to electronic PN prescribing is required. A re-audit could be carried out after implementation of this. An electronic prescribing guideline is now available. The results have been presented at the paediatric clinical governance and gastroenterology educational meetings.

Background Ours is a 110-bed regional hospital with electronic prescribing throughout. The electronic prescription programme offers allergy alert systems and the need for dosage adjustment in renal and hepatic impairment. However, no warning of potential drug interactions is included. Purpose To establish a drug interaction screening system to complement the electronic prescribing programme. Materials and Methods Prospective one-year study (Sept 2011–Sept 2012). Computerized drug interaction alerts can improve the safety, quality and efficiency of care processes and reduce the rate of medicines errors, but sending mass alerts can generate what is known as ‘alert fatigue’. For this reason we selected those drugs categorised in Micromedex® 2.0 as contraindicated for simultaneous and significant interactions (the interaction can cause death and/or require medical intervention to minimise or avoid serious side effects); drugs classified as D in Lexi-Comp OnlineTM (consider modifying the treatment and X (avoid combination); those classified as clinically important by the Arizona CERT. The interaction was detected by crossing data in Access 2003 with the pharmacotherapeutic profile of patients obtained in the electronic prescribing programme (eOsabide) and a proprietary database which contains a total of 3,133 pairs of interactions. The report was written in the patient’s medical history (Osabide-Global) and acceptance was verified in 24–48 hours. Results We detected a total of 1996 interactions and 25% of them were reported, 27% of which led to changes in medical treatment. The main cause of non-notification (36%) was that one drug was prescribed if needed. Conclusions The project was very well accepted among medical professionals and has improved the quality of prescribing. The biggest drawback is the delay in detecting the interaction; it would be helpful if the system generated the warning at the time of prescription. No conflict of interest.

Background Electronic prescribing (EP) systems have been recognised as successful in reducing chemotherapy prescribing errors. However, electronic prescriptions are unlikely to prevent all errors, and new types of errors may emerge. Purpose To assess prescribing error rates and identify new error types and their causes with the implementation of a electronic prescribing system for ambulatory cancer patients at a London Cancer Centre. Materials and Methods A service evaluation was conducted in two parts, covering two different strategies for interception of prescribing errors – prospectively by pharmacists during a 2-week period, and retrospectively using data from the pharmacy EP telephone helpline service, over 41 weeks. Results The overall rate of error-containing prescriptions was estimated to be 6%. In the prospective part, 32 errors were identified from 571 electronic chemotherapy prescriptions. Most commonly committed errors were chemotherapy drug dose adjustments (13; 41%) and weight omissions (11; 34%). In the retrospective analysis, 95 of 141 errors (67%) were ‘e-selection errors’, classified mainly as ‘work-arounds’ (26; 18%), ‘wrong commands’ (35; 25%), or ‘wrong fields’ (27; 19%). 63 errors (45%) were related to scheduling a chemotherapy or supportive drug or regimen. Electronic system-related causes of prescribing errors were recognised in 4 of 32 cases (13%) in the prospective part, and in 89 of 141 cases (63%) in the retrospective part. It was estimated that with implementation of technical solutions and additional prescriber training, 85% of these errors could be prevented in the future. Conclusions The estimated rate of chemotherapy prescribing errors was 6%. A number of different errors, specific for electronic prescribing, were identified, with a thorough explanation of how various errors may have occurred. Future larger scale studies are needed to confirm prescribing error rates, and to possibly identify other, previously unrecognised, types of chemotherapy prescribing errors. No conflict of interest.

[Figure][1] FIGURE. Proponents believe e-prescribing will reduce paperwork and health care system costs. Photos.com The United States government is telling doctors it’s time to set aside their legendarily lousy handwriting and convert to electronic prescriptions. To drive home the