Medication Name Research Articles

CЕМАНТИКО-КОННОТАЦИОННОЕ ПОЛЕ НАЗВАНИЙ МЕДИЦИНСКИХ ПРОФЕССИЙ ЧЕРЕЗ ПРИЗМУ ЭКЗИСТЕНЦИАЛЬНЫХ МОДУСОВ В РАССКАЗАХ А.П. ЧЕХОВА

CЕМАНТИКО-КОННОТАЦИОННОЕ ПОЛЕ НАЗВАНИЙ МЕДИЦИНСКИХ ПРОФЕССИЙ ЧЕРЕЗ ПРИЗМУ ЭКЗИСТЕНЦИАЛЬНЫХ МОДУСОВ В РАССКАЗАХ А.П. ЧЕХОВА

Location-based expert system for diabetes diagnosis and medication recommendation

Using expert systems in the medical field has been practiced continuously for the past decades. There are attempts of using expert systems for a diabetes diagnosis. In this paper, we go further by proposing an expert system that not only diagnoses diabetes but also recommends the right medication depending on the location where the patient lives and on the symptoms of the patient and other effective factors. This system can be very helpful to many diabetic patients, especially to those who are not aware of their disease type or how to control it. The system outputs a list of names of locally available brand names of medications that suit the diabetes type of the patient and that do not pose any danger to the health of the patients according to their symptoms, effective factors, and results of the patients’ medical tests. Our expert system is capable of reasoning using either forward chaining or backward chaining. The rules in the knowledge base are collected from several medical textbooks and articles published in scientific journals, periodicals, and international conferences. To verify the content of the knowledge base, a medical expert and a pharmacist working in Kuwait were consulted.

A systematic literature review of LASA error interventions.

AimsThe aim of this systematic review was to explore and evaluate the efficacy of interventions to reduce the prevalence of look‐alike, sound‐alike (LASA) medication name errors.MethodsWe conducted a systematic review of the literature, searching PubMed, EMBASE, Scopus and Web of Science up to December 2016, and re‐ran the search in February 2020 for later results. We included studies of interventions to reduce LASA errors and included randomized controlled trials, controlled before‐and‐after studies, and interrupted time series. Details were registered in Prospero (ID: CRD42016048198).ResultsWe identified six studies that fulfilled our inclusion criteria. All were conducted in laboratories. Given the diversity in the included studies, we did not conduct a meta‐analysis and instead report the findings narratively. The only intervention explored in RCTs was capitalization of selected letters (“Tall Man”), for which we found limited efficacy and no consensus.ConclusionsTall Man lettering is a marginally effective intervention to reduce LASA errors, with a number of caveats. We suggest that Tall Man gives rise to a “quasi‐placebo effect”, whereby a user derives more benefit from Tall Man lettering if they are aware of its purpose. Keywords: (on scholar one).

Latin and Lithuanian Anatomical Terms in “Medicinos terminų žodynas”: Two-Word Anatomical Terms

Based on the collected material, the article reviews the aspects of the appearance of Lithuanian anatomical terms. Anatomical terms, like terms in general, must be short and informative. The scientific-technical term must be accurate, short, and easy to use so that it can be used as a constituent of a new term. Traditional Latin terminology, in some cases, of course, is more precise than Lithuanian: the same thing in Lithuanian dialects has several or even dozens of names. However, the majority of medical terms are composite terms. Composite terms are most productive. Lithuanian terminology has been developed since the last decades of the 19th century. The latest Lithuanian-Latin Dictionary of Medical Terms by Vytautas Astrauskas, Stasys Biziulevičius, Salezijus Pavilonis, Adomas Vaitilavičius, and Antanas Vileišis was issued in 1980. The terms of anatomy are given according to the Paris Anatomical Nomenclature with the amendments of New York (1960) and Wiesbaden (1965). Non-relevant terms were rejected. The terms created from scientists’ surnames as well as the names of proprietary and branded medications, were also not included. The terms of histology and embryology are presented in accordance with the international nomenclature approved at the International Congress on Anatomy held in Leningrad in 1970. The dictionary has contributed to the process of purification, standardization, and different development of written Lithuanian language.

Extracting medication information from unstructured public health data: a demonstration on data from population-based and tertiary-based samples

BackgroundUnstructured data from clinical epidemiological studies can be valuable and easy to obtain. However, it requires further extraction and processing for data analysis. Doing this manually is labor-intensive, slow and subject to error. In this study, we propose an automation framework for extracting and processing unstructured data.MethodsThe proposed automation framework consisted of two natural language processing (NLP) based tools for unstructured text data for medications and reasons for medication use. We first checked spelling using a spell-check program trained on publicly available knowledge sources and then applied NLP techniques. We mapped medication names into generic names using vocabulary from publicly available knowledge sources. We used WHO’s Anatomical Therapeutic Chemical (ATC) classification system to map generic medication names to medication classes. We processed the reasons for medication with the Lancaster stemmer method and then grouped and mapped to disease classes based on organ systems. Finally, we demonstrated this automation framework on two data sources for Mylagic Encephalomyelitis/ Chronic Fatigue Syndrome (ME/CFS): tertiary-based (n = 378) and population-based (n = 664) samples.ResultsA total of 8681 raw medication records were used for this demonstration. The 1266 distinct medication names (omitting supplements) were condensed to 89 ATC classification system categories. The 1432 distinct raw reasons for medication use were condensed to 65 categories via NLP. Compared to completion of the entire process manually, our automation process reduced the number of the terms requiring manual labor for mapping by 84.4% for medications and 59.4% for reasons for medication use. Additionally, this process improved the precision of the mapped results.ConclusionsOur automation framework demonstrates the usefulness of NLP strategies even when there is no established mapping database. For a less established database (e.g., reasons for medication use), the method is easily modifiable as new knowledge sources for mapping are introduced. The capability to condense large features into interpretable ones will be valuable for subsequent analytical studies involving techniques such as machine learning and data mining.

Features of translation of some rarely used anthropometric terms from Ukrainian into English

Nowadays, anthropometric researches have confidently taken its place in medicine. They are useful not only for health assessment, but also are used in many fields: forensic medicine (to estimate the age of the subject), forensic dentistry (it is an interdiscipline of forensic medicine and dentistry) for the identification of individual and age estimation, dentistry (anthropometric diagnostic methods of dentognathic anomalies and deformations, and there is a potential correlation among number of teeth, chewing ability and anthropometric profile), pediatrics, obstetrics and gynecology, as well as for the diagnosis of overweight (important indicators of nutritional status in the children and adults), for sports control and for the standardization purpose. The symptoms of many diseases are expressed in anthropometric changes. Unfortunately, in Ukraine there is still no generally accepted translation of anthropometric terms from Ukrainian into English. Often for the same medical anthropological term, different names and definitions are used in foreign scientific works. Therefore, the aim of the work was to unify and standardize the translation of rarely used anthropometric terms from Ukrainian into English, as well as determination of the place of the anthropometric point measurement and its schematic representation. We have used the standardized techniques proposed by Shaparenko P.P. and Burikh M.P. (2000), set out in the “Anthropometric data analysis sets manual” (1994), in the works of Hobbs P.C. (1975) and Brinkley J.F with co-authors (2016), where some anthropometric terms were described that are used when measuring the head, determining the height above the floor of some points of the trunk and upper limb of a person, and anthropometric parameters of the hand. The conclusion is made about the correctness of the proposed translation from Ukrainian into English, considering the specialized terminology. We hope that in the future this list will be supplemented with the new terms related to measurements of the auricle, upper and lower extremities.

Assessment of a pharmacy technician medication history program.

To determine the percentage of unintentional prior-to-admission (PTA) medication list discrepancies captured by second-source verification. A prospective, randomized, controlled intervention was conducted on all patients admitted to a large academic medical center with a PTA medication list completed by a pharmacy technician from December 2018 through January 2019. Excluded patients included those admitted as observation status or discharged prior to the time of second-source verification. The following data was collected: patient's medical record number, age, admission date and time, service admitted to, date and time of completed PTA medication list, date and time of second-source verification, type of second-source verification, medication name, dose, route, frequency, formulation, and confidence level of pharmacy technician completing the initial PTA medication list. Second-source verification was conducted on all medications from a patient's PTA medication list after completion by a pharmacy technician. There were a total of 992 medications from the 200 randomly assigned patients with a completed PTA medication list by a pharmacy technician during the study time frame. Of these medications, 116 (11.7%) contained a discrepancy identified by second-source verification. The most common type of discrepancy was omission (67%) followed by dosing, frequency, and formulation. The median time to complete second-source verification was 9 minutes (interquartile range, 5-17 minutes). Second-source verification at the time of hospital admission helps identify medication discrepancies and may improve medication use safety and prescribing pattern and, accordingly, may contribute to reducing medication errors.

Pediatric ingestions with gummy formulated medications: a retrospective study

Context Gummy formulations are widely available with estimated 65% marketed for children. Currently, there are few studies describing children ingesting gummy formulated medications. The aim of this study was to quantify and identify the type of ingestions due to gummy formulated medications, evaluate their clinical significance as defined by adverse outcomes: associated symptoms, emergency department (ED) visits, and hospitalizations. Methods Retrospective study in children aged 0–19 exposed to gummy formulated medications from 2015 to 2017 as identified by calls made to the Regional Poison Control Center (RPCC). A list of potentially toxic gummy formulated medications was compiled and reviewed by medical and clinical toxicologists. We categorized medications into vitamins, minerals and supplements, melatonin, and other. Data collected included: medication name, number of units, age, sex, symptoms described, ED visit, hospitalization, and unintentional or intentional ingestion. Discussion Of the 66,059 pediatric exposures received by RPCC, 1143 (1.7%) involved gummy formulated medications of which 1098 were analyzed. Median age was 3 years, 57.7% were males and 7% were symptomatic. Seventy-four percent exposures involved vitamins and 24% melatonin. In comparison to other gummy exposures, those who ingested melatonin had 8.4 times higher odds of being symptomatic (OR: 8.4, 95% CI: 5.1, 14) and 4.8 times higher odds of visiting ED (OR: 4.8, 95% CI: 2.5, 9). The predominant symptoms reported were drowsiness, gastrointestinal upset, and hyperactivity. Two patients were hospitalized who ingested multiple medications, one was unintentional, and one was intentional as a suicide attempt thus admitted for psychiatric stabilization. Conclusions Gummy formulated medications comprised <2% of the total pediatric calls to the RPCC. Although, the occurrence of symptoms is rare, these medications especially those containing melatonin should be safely stored.

Integrating and Evaluating the Data Quality and Utility of Smart Pump Information in Detecting Medication Administration Errors: Evaluation Study.

BackgroundAt present, electronic health records (EHRs) are the central focus of clinical informatics given their role as the primary source of clinical data. Despite their granularity, the EHR data heavily rely on manual input and are prone to human errors. Many other sources of data exist in the clinical setting, including digital medical devices such as smart infusion pumps. When incorporated with prescribing data from EHRs, smart pump records (SPRs) are capable of shedding light on actions that take place during the medication use process. However, harmoniz-ing the 2 sources is hindered by multiple technical challenges, and the data quality and utility of SPRs have not been fully realized.ObjectiveThis study aims to evaluate the quality and utility of SPRs incorporated with EHR data in detecting medication administration errors. Our overarching hypothesis is that SPRs would contribute unique information in the med-ication use process, enabling more comprehensive detection of discrepancies and potential errors in medication administration.MethodsWe evaluated the medication use process of 9 high-risk medications for patients admitted to the neonatal inten-sive care unit during a 1-year period. An automated algorithm was developed to align SPRs with their medica-tion orders in the EHRs using patient ID, medication name, and timestamp. The aligned data were manually re-viewed by a clinical research coordinator and 2 pediatric physicians to identify discrepancies in medication ad-ministration. The data quality of SPRs was assessed with the proportion of information that was linked to valid EHR orders. To evaluate their utility, we compared the frequency and severity of discrepancies captured by the SPR and EHR data, respectively. A novel concordance assessment was also developed to understand the detec-tion power and capabilities of SPR and EHR data.ResultsApproximately 70% of the SPRs contained valid patient IDs and medication names, making them feasible for data integration. After combining the 2 sources, the investigative team reviewed 2307 medication orders with 10,575 medication administration records (MARs) and 23,397 SPRs. A total of 321 MAR and 682 SPR dis-crepancies were identified, with vasopressors showing the highest discrepancy rates, followed by narcotics and total parenteral nutrition. Compared with EHR MARs, substantial dosing discrepancies were more commonly detectable using the SPRs. The concordance analysis showed little overlap between MAR and SPR discrepan-cies, with most discrepancies captured by the SPR data.ConclusionsWe integrated smart infusion pump information with EHR data to analyze the most error-prone phases of the medication lifecycle. The findings suggested that SPRs could be a more reliable data source for medication error detection. Ultimately, it is imperative to integrate SPR information with EHR data to fully detect and mitigate medication administration errors in the clinical setting.

Blockchain Based Security Solution for Medical Data

Existing health organizations maintain their patients and medical data using centralised management approach. This system is more vulnerable to data breaches which leads to security threats and patients don’t have control over their data. According to German cybersecurity company Greenbone Networks, the patient records, 121 millions of medical images and scans from India has been leaked which includes details such as the name of the patient, their date of birth, the national ID, name of the medical institution, their medical history, physician names and other details. According to poneman cost of data breach study, the cost of the data breach for healthcare organizations approximated to be $380 per record. According to 2016 Breach Barometer Report, 27,314,647 patient records were affected. The patient don’t have control over their data and data can be misused. Hyperledger fabric framework based Blockchain technology is most desirable solution to prevent data manipulation and data theft .It also facilitates patient to have control over their data. Hyperledger fabric is a permissioned distributed ledger framework and provide high degrees of confidentiality, flexibility, and scalability.

Assessment of parents’ understanding of pediatric medical prescriptions

Objective: To assess the accuracy of the parent understanding of pediatric prescription and prescribed medications and examine factors associated. Methods: Cross-sectional, observational questionnaire-based study involving 354 eligible parents was carried out in the pediatric department of a tertiary care teaching hospital. Parent's sociodemographic details and their understanding of prescription including medication name, indication, dose, frequency, and duration were assessed by a self-administered questionnaire and their association analyzed statistically. Results: Mean age of parents was 33 ± 1.2 with the majority of females 57.06%. Out of 354 parents, 22.32% had low literacy and 37.74% were working as farmers. Overall understanding of prescription was present in only 25.14% of parents. The majority of parents were having a better understanding of the frequency of drug administration (79.09), while poor understanding was observed with respect to dosage calculation of medication (45.76%) and adverse drug reactions (25.14%) and the difference in the understanding was statistically significant (P<0.05). Factors like the age of parents, Child’s age, parent occupation, education of parent, experience in administering medicine, number of medicines prescribed, and type of dosage form were significantly impacting parent’s understanding regarding medication (P<0.05). Conclusion: Unperceived medication instruction understanding gaps exist at all literacy levels for pediatric patients among all parents. Communication and care delivery practices need further evaluation. Practice implications: Clinicians should be aware of the frequency of parent medication misunderstanding and give more attention to parents’ counseling.

Twelve-Month Review of Infusion Pump Near-Miss Medication and Dose Selection Errors and User-Initiated "Good Save" Corrections: Retrospective Study.

BackgroundThere is a paucity of quantitative evidence in the current literature on the incidence of wrong medication and wrong dose administration of intravenous medications by clinicians. The difficulties of obtaining reliable data are related to the fact that at this stage of the medication administration chain, detection of errors is extremely difficult. Smart pump medication library logs and their reporting software record medication and dose selections made by users, as well as cancellations of selections and the time between these actions. Analysis of these data adds quantitative data to the detection of these kinds of errors.ObjectiveWe aimed to establish, in a reproducible and reliable study, baseline data to show how metrics in the set-up and programming phase of intravenous medication administration can be produced from medication library near-miss error reports from infusion pumps.MethodsWe performed a 12-month retrospective review of medication library reports from infusion pumps from across a facility to obtain metrics on the set-up phase of intravenous medication administration. Cancelled infusions and resolutions of all infusion alerts by users were analyzed. Decision times of clinicians were calculated from the time-date stamps of the pumps’ logs.ResultsIncorrect medication selections represented 3.45% (10,017/290,807) of all medication library alerts and 22.40% (10,017/44,721) of all cancelled infusions. Of these cancelled medications, all high-risk medications, oncology medications, and all intravenous medications delivered to pediatric patients and neonates required a two-nurse check according to the local policy. Wrong dose selection was responsible for 2.93% (8533/290,807) of all alarms and 19.08% (8533/44,721) of infusion cancellations. Average error recognition to cancellation and correction times were 27.00 s (SD 22.25) for medication error correction and 26.52 s (SD 24.71) for dose correction. The mean character count of medications corrected from initial lookalike-soundalike selection errors was 13.04, with a heavier distribution toward higher character counts. The position of the word/phrase error was spread among name beginning (6991/10,017, 69.79%), middle (2144/10,017, 21.40%), and end (882/10,017, 8.80%).ConclusionsThe study identified a high number of lookalike-soundalike near miss errors, with cancellation of one medication being rapidly followed by the programming of a second. This phenomenon was largely centered on initial misreadings of the beginning of the medication name, with some incidences of misreading in the middle and end portions of medication nomenclature. The value of an infusion pump showing the entire medication name complete with TALLman lettering on the interface matching that of medication labeling is supported by these findings. The study provides a quantitative appraisal of an area that has been resistant to study and measurement, which is the number of intravenous medication administration errors of wrong medication and wrong dose that occur in clinical settings.

Medication use and driving patterns in older drivers: preliminary findings from the LongROAD study

BackgroundThe potential for impaired driving due to medication use can occur at any age, though older adults are more likely to take multiple prescribed medications and experience side effects that may affect driving ability. The purpose of this study was to characterize the relationship between medications and driving safety behaviors.MethodsData for this study came from the five-site Longitudinal Research on Aging Drivers (LongROAD) project. Participants were active drivers, age 65–79 years at enrollment, and patients at one of the 5 participating sites. Medication names and doses were obtained at baseline based on the “brown-bag review” method. Medications were coded using the American Hospital Formulary Service system. Driving data were collected by a GPS accelerometer installed in the study participants’ main vehicles.ResultsMedication data were available for 2949 (98.6%) of the 2990 participants, and 2898 (96.9% of all participants) had both medication data and at least 30 recorded days of driving. The median number of medications taken per study participant was seven, with a range of 0–51. Total number of medications was significantly associated with a higher rapid deceleration rate. Certain medication classes were significantly associated with other driving outcomes, including central nervous system agents (more speeding events), hormones and gastrointestinal medications (more rapid decelerations), electrolytes (fewer rapid decelerations), and antihistamines (greater right to left turn ratio).ConclusionsOlder adult drivers are taking large quantities of prescription and non-prescription medications that may affect their driving safety. Certain medication classes are associated with potentially adverse driving patterns, such as speeding and rapid decelerations, while others are associated with potentially protective maneuvers, such as right hand turning. Further research is warranted to identify and mitigate potential adverse effects of such medications on driving safety in older adults.

Estimate General Practitioners Active Supply in Iran: Capture-Recapture Method for Three Data Sources

Accurate estimation of active general practitioners (GPs) is a concern for health authorities to estimate requirements. This study aimed to accurately estimate GPs active supply in Iran using three sources capture-recapture (CRC) method. This cross-sectional study collected data during 2015-2016, targeting all GPs registered in three independent data sources; a national survey from all hospitals, database of human resource management office at health ministry and physicians' offices databank. Variables including medical council codes, GP names, surnames and national ID codes were used for data linkage among the three sources. Three sources CRC method was applied using log-linear models to estimate the total number of active GPs in STATA software. Overall, 27,048 GPs were identified after removing the duplicate records. Based on CRC three sources data, the total number of GPs were 53,630 in 2015-2016. Distribution of GPs per 1,000 population among the provinces indicates that provinces of Kohgiluyeh & Boyer Ahmad, Mazandaran, Golestan and Yazd with ratios of 1.28, 1.28, 1.21 and 1.17 physicians rank the highest proportion of GPs and the provinces of Sistan & Baluchestan, Ilam, Zanjan, Alborz, North Khorasan with corresponding ratios of 0.24, 0.40, 0.40, 0.43 and 0.45 GPs ranked the lowest. CRC method is known to be the best and rapidest method to estimate active GP due to its compatibility for the current situation of databanks in Iran. Therefore, this method is a good application in human resource distribution and planning.

Cultural Aspects of Malaysian English and Russian Medical Profession Names

The translation of medical profession names may challenge even the most experienced translator. Selecting the appropriate equivalents is not always evident: the English term dentist for instance may correspond to either стоматолог [ stəmɐtˈolək ] (“mouth expert”) or зубной врач [ zʊbnˈoj vrˈatɕ ] (“tooth doctor”) or дантист [dɐntˈist] (“dental hygienist”) in the Russian language. A physiotherapist can be translated as физиотерапевт [fɪzɪɐtɪrɐpˈevt] ; however a physiotherapist in Russia must necessarily hold a medical doctor degree, in contrast with the practice of most Anglo-Saxon countries. Although the compared terms are often considered as equivalents by bilingual dictionaries (e.g.: surgeon and хирург [xɪrˈurk]) (Buvalin and Lenart 2017); however, their denotations and connotations may significantly differ, thus their improper translation may lead to intercultural misunderstandings. In this paper, 17 pairs of English-Russian medical profession names were investigated – the English lexemes coming from the Malaysian variety of the English language – with two competing linguistic methods: the association experiment and a corpus linguistic approach. The authors aimed at identifying semantic dissimilarities between the Malaysian English and the Russian lexemes in a cross-cultural context, from the perspective of both the association experiment and corpus linguistic methods. Firstly, a questionnaire-based association experiment was conducted with 300 Russian and 50 Malaysian medical university students, followed by a contrastive corpus linguistic analysis relying on the Russian National Corpus and the NOW (News on the Web) corpus. Results of the cross-cultural investigation revealed substantial semantic differences between the English and Russian profession names, as well as confirmed the complementary character of the association experiment and the corpus linguistic methods. Keywords: medical profession names; association experiment; corpus linguistics; verbal consciousness; cross-cultural investigation

Adherence to prescription-writing guidelines for outpatients in Southern Gauteng district hospitals.

BackgroundMedical prescription writing is legally and professionally regulated in order to prevent errors that can result in patients being harmed. This study assesses prescriber adherence to such regulations in primary care settings.MethodsA cross-sectional study of 412 prescriptions from four district hospital outpatient departments (OPDs) was conducted in March 2015. Primary outcome data were obtained by scoring prescriptions for accuracy across four categories: completion of essential elements, use of generic names of medications, use of recommended abbreviations and decimals and legibility. Secondary outcome data sought associations between accuracy scores and characteristics of the OPDs that might influence prescriber adherence.ResultsCompletion of the essential elements, including patient identifiers, prescriber identifiers, treatment regimen and date scored 44%, 77%, 99% and 99% respectively. Legibility, the use of generic names of medications and the use of recommended abbreviations and decimals scored 90%, 39% and 35%, respectively. Only 38% of prescriptions achieved a global accuracy score (GAS) of between 80% and 100%. A significant association was found between lower GAS and the number of prescriptions written per day (p = 0.001) as well as with the number of prescribers working on that day (p = 0.005), suggesting a negative impact on prescribers’ performance because of workload pressures.ConclusionLow GAS values indicate poor adherence to prescription-writing regulations. Elements requiring substantial improvement include completion of patient and prescriber identifiers, use of generic medication names and the use of recommended abbreviations and decimals. This study provides baseline data for future initiatives for improvement in prescription-writing quality.

Cross-sectional study of drug utilisation in a Chinese neonatal unit.

ObjectiveThis study aimed to describe drug utilisation in a large Chinese neonatal unit and to compare the findings with those from other countries.MethodsData were collected from electronic medical records. Prescription drugs were defined as the number of unique medication names for each patient. Medicine doses were defined as the total number of doses of all medicines administered. Information was collected regarding drugs prescribed to inpatients between March 1 and April 1 2018 in the neonatal intensive care unit and the general neonatal ward of West China Second University Hospital.ResultsThe 319 neonates received 1276 prescription drugs and 11,410 medicine doses involving 81 drugs. Vitamin K1, hepatitis B vaccine, and cefoperazone-sulbactam were the three most frequently prescribed drugs. Antimicrobials were the most frequently used group of medicines, with cefoperazone-sulbactam and piperacillin-tazobactam the most frequently used in an off-label manner. Domperidone and simethicone were both widely used.ConclusionsThe most commonly prescribed antimicrobials differed greatly from those reported for other countries. The evidence base for the use of some medicines is poor, and is indicative of irrational prescribing.

Development of a 3D-printed Medication Label for the Blind and Visually Impaired.

This study explored the potential of three-dimensional printing (3DP) technology in producing a three-dimensional (3D) medication label for blind and visually impaired (BVI) patients to ease their drug administration. Different variations of label wordings, dosing instructions, and medication identifiers were designed with reference to guidelines by the American Foundation for the Blind. Shapes and symbols were used as dosing instructions and medication identifiers to the patient’s medical conditions. Prototype designs were created with common graphics computer-assisted drafting software and 3D-printed using acrylonitrile butadiene styrene as the polymer filament. Feedback was then obtained from five people with normal vision and four BVI persons. The initial prototype comprised four components, namely, medication name and strength, patient’s name, dosing instruction, and medication identifier. A revised label comprising the latter two components was developed after feedback by BVI persons. Words were in all uppercase and regular font type, with a 5-mm center-to-center letter spacing. Elevation heights of the letters alternated between 1 mm and 1.5 mm. A half sphere represented the medication dose unit, while vertical lines and a horizontal center line with alternating elevation of arrowheads represented the frequency of administration and the medication’s consumption in relation to food, respectively. Symbols based on target organs were used as medication identifiers. With rapid advancements in 3DP technologies, there is tremendous potential for producing 3D labels in patients’ medication management.

The problem of look-alike, sound-alike name errors: Drivers and solutions.

Look-alike or sound-alike (LASA) medication names may be mistaken for each other, e.g. mercaptamine and mercaptopurine. If an error of this sort is not intercepted, it can reach the patient and may result in harm. LASA errors occur because of shared linguistic properties between names (phonetic or orthographic), and potential for error is compounded by similar packaging, tablet appearance, tablet strength, route of administration or therapeutic indication. Estimates of prevalence range from 0.00003 to 0.0022% of all prescriptions, 7% of near misses, and between 6.2 and 14.7% of all medication error events. Solutions to LASA errors can target people or systems, and include reducing interruptions or distractions during medication administration, typographic tweaks, such as selective capitalization (Tall Man letters) or boldface, barcoding, and computerized physician order entry.

Evaluation of Medication Error Incident Reports at a Tertiary Care Hospital.

Background: Medications errors (MEs) have been a major concern of healthcare systems worldwide. Voluntary-based incident reporting is the mainstay system to detect such events in many institutions. However, the number of reports can be highly variable across institutions depending on their adoption of the safety culture. This study aimed to evaluate and analyze medication error incidents that were submitted through the hospital safety reporting system in 2015 at a tertiary care center in the western region of Saudi Arabia, and to explore the most common types of harmful MEs in addition to the risk factors that led to such harmful incidents. Methods: This is a descriptive study that was conducted utilizing 624 medication error reports extracted from the hospital safety reporting system. Reports were analyzed based on the medication name, event type, event description, nodes of the medication use process, harm score (adapted from the National Coordinating Council for Medication Error Reporting and Prevention harm index), patients’ age/gender, incident setting, and time of occurrence as documented in the Safety Reporting System (SRS). Furthermore, all errors that resulted in injury or harm to patients had a deeper review by two senior pharmacists to find contributing factors that led to these harmful incidents and recommend system-based preventive strategies. Results: This study showed that most reported incidents were near misses (69.3%). The pediatric population was involved in 28.4% of the incident reports. Most of the reported incidents were categorized as occurring in the inpatient setting (57.4%). Medication error incidents were more likely to be reported in the morning shift versus evening and night shift (77.4% vs. 22.6%). Most reported incidents involved the dispensing stage (36.7%). High-alert medications were reported in 281 out of 624 events (45%). Conclusions: The hospital medication safety reporting program is a great tool to identify system-based issues in the medication management system. This study identified many opportunities for improvement in the medication use system, especially in management of chemotherapy and anticoagulant agents.