Dosing Errors Research Articles

In-Hospital Prescription Checking System for Hospitalized Patients with Decreased Glomerular Filtration Rate.

Clinical decision support systems (CDSS) are reported to be useful in preventing dosage errors in renally excreted drugs by alerting hospital pharmacists to inadequate dosages for hospitalized patients with decreased GFR. However, it is unclear whether CDSS can reduce dosage errors in renally excreted drugs in hospitalized patients. To prevent dosage errors in renally excreted drugs, we introduced a prescription checking system (PCS) for in-hospital prescriptions. This retrospective study aimed to evaluate whether a prescription audit by hospital pharmacists using the PCS reduced the rate of dosage errors in renally excreted drugs. The target drugs were allopurinol, cibenzoline, famotidine, and pilsicainide. Interrupted time series analysis was used to evaluate trends in the 4-weekly dosage error rates over 52 weeks before PCS implementation and 52 weeks after PCS implementation. Before and after PCS implementation, 474 and 331 prescriptions containing one of the targeted drugs, respectively, were generated. The estimated baseline level of the 4-weekly dosage error rates was 34%. The trend before the PCS implementation was stable with no observable trend. The estimated level change from the last point in the pre-PCS implementation to the first point in the PCS implementation was -20% (P<0.001). There was no change in the trend after PCS implementation. We demonstrated that a prescription audit by hospital pharmacists using the PCS reduced the rate of dosage errors in the target renally excreted drugs in hospitalized patients. Although further studies are needed to confirm whether our results can be generalized to other health facilities, our findings highlight the need for a PCS to prevent the overdose of renally excreted drugs.

Geometric Analysis and Dosimetric Evaluation of Various Deformable Image Registration (DIR) Algorithms for Abdominal Images with 3D Biomechanically Modelled Deformation

<h3>Purpose/Objective(s)</h3> The accuracy of DIR algorithms available on commercial radiotherapy planning platforms were examined and their clinical applicability geometrically and dosimetrically for abdominal sites were evaluated using biomechanically modelled deformation. <h3>Materials/Methods</h3> 5 pancreatic patients' planning CT were used in this study. Following the guideline of AAPM TG-132, a patient-specific QA workflow was developed and implemented to evaluate DIR for abdomen using digital phantoms, created with a commercial virtual phantom software (VPS). First, the planning CT images were deformed in superior-inferior direction to simulation respiratory motion in lung and abdomen, using the biomechanical model embedded in VPS. In addition, 5 mm motion in both anterior-posterior and lateral directions were added to region of interest (ROI), including stomach and duodenum, and small bowel. The added ROI deformations are consistent with the abdomen data observed in daily CBCT. The resulting 3D deformation vector field (DVF) and the corresponding deformed CT was then obtained, serving as ground truth. Second, the original planning CT and the deformed CT were imported to two commercial DIR systems (DS1 and DS2), to perform DIR with intensity-based algorithms, and derive DVFs. Quantitative differences between ground truth DVF and DS1 or DS2's DVFs, such as mean, max, and the distribution of DIR errors were tabulated. Then the original plan was re-calculated on the deformed CT, which was generated based on DS1 or DS2's DVF. The dose errors were then calculated on a pixel-to-pixel basis. The relationship between the DIR errors and the dose error ranges (25%-75% on the dose error distribution histogram) were investigated. As a pilot study, comprehensive reports were generated to show the DIR performances as patient specific QA records. <h3>Results</h3> The displacements on the ground truth DVF range from 0 to 37 mm. Geometric analysis showed DIR errors as tabulated below. Dosimetrically, as the DIR error increases, the dose error range also increase, for both DS1 and DS2. Dosimetric evaluation of the dose errors for ROIs were tabulated as below. <h3>Conclusion</h3> Preliminary evaluation of geometric and dosimetric accuracy of DIR on DS1 and DS2 were performed, with a realistic biomechanical model derived DVF serving as ground truth. A patient specific DIR QA workflow was developed for a pancreatic patient cohort, and it has potential to be implemented as a clinical workflow.

Dosimetry Validation Study for Automated Head and Neck Cancer Organs at Risk Segmentation Using Stratified Learning and Neural Architecture Search

<h3>Purpose/Objective(s)</h3> Organs at risk (OARs) segmentation is an essential process in head and neck (H&N) cancer radiotherapy. We have reported high automated segmentation geometric accuracy of Stratified Learning and Neural Architecture Search method in terms of Dice Score (DSC) from our previous study. In this study, we would evaluate the dosimetric influence of our automated approach before integrating this method into the clinical workflow. <h3>Materials/Methods</h3> To measure the dosimetric effects brought by the OARs' variance, the intensity-modulated radiotherapy (IMRT) dose plans of 10 head and neck cancer patients were replanned using the original tumor target volumes and three substitute OAR contours permutations (deep learning generated stratified organs at risk segmentation (SOARS), SOARS revised by physician (SOARS-revised), and OAR delineated from scratch by physician (human reader)). We further examined the clinical dosimetric accuracy and the clinical reference OAR contours were overlaid on top of each replanned dose grid to evaluate the dosimetric differences. <h3>Results</h3> After replanning, SOARS and SOARS-revised contours have slightly smaller Diff (max dose) as compared to human reader contours (3.4%, 3.5% vs. 4.1%). For the Diff (mean dose), human reader, SOARS, SOARS-revised achieves similar results, i.e., 5.3%, 5.0%, and 5.0%, respectively. However, more OARs from the human reader have dose variations larger than 10% or 20% as compared to SOARS and SOARS-revised. Overall, our results indicate that using OAR contours from human reader, SOARS, and SOARS-revised lead to generally comparable dose accuracy in clinical practice. SOAR-related OAR contours have fewer OARs with dose error larger than 10% or 20%. <h3>Conclusion</h3> This study further validates the clinical applicability of a deep learning based automated H&N OAR segmentation method by comparing dosimetry of plans using OAR contours generated automatically and by a human reader to the gold standard contours. The dose variations calculated after planning on automated segmentation contours are less than 5%. Our proposed automated H&N OAR segmentation method not only achieves high geometric accuracy but also helps deliver treatment beams with little variances.

Patient-Specific Quality Assurance of Deformable Image Registrations Using Atlas for Adaptive Radiotherapy of Lung Cancer

<h3>Purpose/Objective(s)</h3> Evaluating the uncertainty of deformable image registration (DIR) is challenging because the ground truth is often unavailable. We developed an automated method to create realistic deformations via an atlas and assess DIR algorithms on a patient-specific level for adaptive radiotherapy. <h3>Materials/Methods</h3> A library of deformations was created by extracting the longitudinal anatomical changes observed from an atlas of 60 locally advanced non-small cell lung cancer patients treated with IMRT (60Gy, 30 fx). The deformation vector field (DVF) between the planning CT (pCT) and last weekly CBCT of an atlas patient was derived via a free-form DIR algorithm and served as a ground truth pattern. An inquiry patient was first matched to an atlas patient on gross tumor volume (GTV) location and volume. The pCT of an inquiry patient was then deformably registered to that of an atlas patient to establish a voxel-based correspondence. Then, the deformation pattern of the atlas patient was transferred to the inquiry patient pCT by applying the known DVF to the corresponding voxels, resulting in a digital CT phantom. Subsequently, this CT phantom was appended with CBCT artifacts using a physics-based augmentation (Alam, PMB 2021) to imitate a weekly CBCT. To evaluate DIRs, a large deformation diffeomorphic metric mapping (LDDMM) algorithm, and two commercial systems (C1 C2) were used between the phantom (both simulated CT and CBCT) and actual pCT of the inquiry patient. Derived DVFs were compared to the ground truth. The voxel-level geometric and dosimetric uncertainties of DIRs were calculated using the DVF95% errors, fraction of volume with ≤1.5mm errors (V1.5mm) and mean dose errors (D_mean) for GTV and esophagus. <h3>Results</h3> In a retrospective evaluation of 10 paired inquiry and atlas patients, the actual deformations observed between the pCT and weekly CBCTs of inquiry patients were well-contained by the combined patterns from the matched atlas, validating the feasibility of an atlas. LDDMM performed consistently well, especially for the CT-CBCT registration (p<0.01, two-tailed t-test). GTV mean dose is less sensitive to DIR errors than esophagus mean dose. <h3>Conclusion</h3> It is feasible to augment anatomical changes for a particular inquiry patient using deformation patterns from matched patients in an atlas and evaluate the uncertainty of DIR algorithms in realistic simulations. Integration of such an automated program facilitates the clinical implementation of adaptive radiotherapy that involves longitudinal imaging studies.

Efficient dose-volume histogram-based pretreatment patient-specific quality assurance methodology with combined deep learning and machine learning models for volumetric modulated arc radiotherapy.

Weak correlation between gamma passing rates and dose differences in target volumes and organs at risk (OARs) has been reported in several studies. Evaluation on the differences between planned dose-volume histogram (DVH) and reconstructed DVH from measurement was adopted and incorporated into patient-specific quality assurance (PSQA). However, it is difficult to develop a methodology allowing the evaluation of errors on DVHs accurately and quickly. To develop a DVH-based pretreatment PSQA for volumetric modulated arc therapy (VMAT) with combined deep learning (DL) and machine learning models to overcome the limitation of conventional gamma index (GI) and improve the efficiency of DVH-based PSQA. A DL model with a three-dimensional squeeze-and-excitation residual blocks incorporated into a modified U-net was developed to predict the measured PSQA DVHs of 208 head-and-neck (H&N) cancer patients underwent VMAT between 2018 and 2021 from two hospitals, in which 162 cases was randomly selected for training, 18 for validation, and 28 for testing. After evaluating the differences between treatment planning system (TPS) and PSQA DVHs predicted by DL model with multiple metrics, a pass or fail (PoF) classification model was developed using XGBoost algorithm. Evaluation of domain experts on dose errors between TPS and reconstructed PSQA DVHs was taken as ground truth for PoF classification model training. The prediction model was able to achieve a good agreement between predicted, measured, and TPS doses. Quantitative evaluation demonstrated no significant difference between predicted PSQA dose and measured dose for target and OARs, except for Dmean of PTV6900 (p=0.001), D50 of PTV6000 (p=0.014), D2 of PTV5400 (p=0.009), D50 of left parotid (p=0.015), and Dmax of left inner ear (p=0.007). The XGBoost model achieved an area under curves, accuracy, sensitivity, and specificity of 0.89 versus 0.88, 0.89 versus 0.86, 0. 71 versus 0.71, and 0.95 versus 0.91 with measured and predicted PSQA doses, respectively. The agreement between domain experts and the classification model was 86% for 28 test cases. The successful prediction of PSQA doses and classification of PoF for H&N VMAT PSQA indicating that this DVH-based PSQA method is promising to overcome the limitations of GI and to improve the efficiency and accuracy of VMAT delivery.

Quality assurance for MRI-only radiation therapy: A voxel-wise population-based methodology for image and dose assessment of synthetic CT generation methods.

The quality assurance of synthetic CT (sCT) is crucial for safe clinical transfer to an MRI-only radiotherapy planning workflow. The aim of this work is to propose a population-based process assessing local errors in the generation of sCTs and their impact on dose distribution. For the analysis to be anatomically meaningful, a customized interpatient registration method brought the population data to the same coordinate system. Then, the voxel-based process was applied on two sCT generation methods: a bulk-density method and a generative adversarial network. The CT and MRI pairs of 39 patients treated by radiotherapy for prostate cancer were used for sCT generation, and 26 of them with delineated structures were selected for analysis. Voxel-wise errors in sCT compared to CT were assessed for image intensities and dose calculation, and a population-based statistical test was applied to identify the regions where discrepancies were significant. The cumulative histograms of the mean absolute dose error per volume of tissue were computed to give a quantitative indication of the error for each generation method. Accurate interpatient registration was achieved, with mean Dice scores higher than 0.91 for all organs. The proposed method produces three-dimensional maps that precisely show the location of the major discrepancies for both sCT generation methods, highlighting the heterogeneity of image and dose errors for sCT generation methods from MRI across the pelvic anatomy. Hence, this method provides additional information that will assist with both sCT development and quality control for MRI-based planning radiotherapy.

SARU: A self-attention ResUNet to generate synthetic CT images for MR-only BNCT treatment planning.

Despite the significant physical differences between magnetic resonance imaging (MRI) and computed tomography (CT), the high entropy of MRI data indicates the existence of a surjective transformation from MRI to CT image. However, there is no specific optimization of the network itself in previous MRI/CT translation works, resulting in mistakes in details such as the skull margin and cavity edge. These errors might have moderate effect on conventional radiotherapy, but for boron neutron capture therapy (BNCT), the skin dose will be a critical part of the dose composition. Thus, the purpose of this work is to create a self-attention network that could directly transfer MRI to synthetical computerized tomography (sCT) images with lower inaccuracy at the skin edge and examine the viability of magnetic resonance (MR)-guided BNCT. A retrospective analysis was undertaken on 104 patients with brain malignancies who had both CT and MRI as part of their radiation treatment plan. The CT images were deformably registered to the MRI. In the U-shaped generation network, we introduced spatial and channel attention modules, as well as a versatile "Attentional ResBlock," which reduce the parameters while maintaining high performance. We employed five-fold cross-validation to test all patients, compared the proposed network to those used in earlier studies, and used Monte Carlo software to simulate the BNCT process for dosimetric evaluation in test set. Compared with UNet, Pix2Pix, and ResNet, the mean absolute error (MAE) of self-attention ResUNet (SARU) is reduced by 12.91, 17.48, and 9.50HU, respectively. The "two one-sided tests" show no significant difference in dose-volume histogram (DVH) results. And for all tested cases, the average 2%/2mm gamma index of UNet, ResNet, Pix2Pix, and SARU were 0.96±0.03, 0.96±0.03, 0.95±0.03, and 0.98±0.01, respectively. The error of skin dose from SARU is much less than the results from other methods. We have developed a residual U-shape network with an attention mechanism to generate sCT images from MRI for BNCT treatment planning with lower MAE in six organs. There is no significant difference between the dose distribution calculated by sCT and real CT. This solution may greatly simplify the BNCT treatment planning process, lower the BNCT treatment dose, and minimize image feature mismatch.

ACUTE PERICARDITIS CAUSED BY COVID-19 INFECTION AND ITS MANAGEMENT

ACUTE PERICARDITIS CAUSED BY COVID-19 INFECTION AND ITS MANAGEMENT

Effects of dose error and sample size on sonic boom dose-response curves

NASA will soon be collecting noise-annoyance community survey data as the X-59 aircraft flies supersonically over several communities in the USA. Sparse measurements of the X-59 sonic thumps will be used together with physics-based simulations to estimate noise doses at survey participant locations. These dose estimates have associated error that affects the accuracy of modeled dose-response curves, which can result in misestimation of annoyance. The precision in dose-response curves is also a consideration in selecting the number of survey participants. To enable pretest studies of dose error and precision, simulated dose-response data were generated based on NASA’s Quiet Supersonic Flights 2018 test. The data included various degrees of dose error and sample size. Frequentist multilevel logistic regression models were fit to the true and perturbed dose-response data. Simple proportional relationships were identified between the model parameters and the perturbation standard deviation. The summary dose-response curves illustrate the impact on accuracy if dose error is not accounted for in the model. The precision in the dose-response curves is also shown as the number of participants and degree of participation is varied. Finally, sampling variability is illustrated by showing the dose-response curves for several replicates with random draws of participants and errors.

Medication administration errors made among undergraduate nursing students: A need for change in teaching methods.

Systems factors, such as interruptions, contribute to nursing errors. Gaining an understanding of what contributes to nursing student errors can inform educational strategies aimed to improve patient safety. The aims of this study were to investigate: (a) within-subjects differences in error rates among nursing students during interrupted compared to uninterrupted simulated medication administration, (b) types of medication administration errors made by nursing students, and (c) nursing students' perceptions of their ability to independently administer medication. A descriptive comparative within-subjects design was utilized in this two-site study. Data on errors were collected via direct observation. Senior baccalaureate nursing student participants discussed their experience of interrupted and uninterrupted simulated medication administration during individual debriefing sessions. Nearly one-third of participants made errors. Error rates were similar in interrupted (19.4%) and uninterrupted (16.7%) conditions. Near-misses, which were not included in the error rates, were reported by 8% of participants. The most common error types were documentation and dose errors. Students attributed the interruption and lack of independent medication administration practice as causes for errors. Educational programs must adequately prepare nursing students for independent safe medication administration in complex work environments. The inclusion of systems factors in educational modalities is critical.

882TiP Subcutaneous vs intravenous nivolumab in patients with melanoma following complete resection

Nivolumab (NIVO), a programmed death-1 immune checkpoint inhibitor, is approved globally as an effective treatment across multiple cancer types. Several studies are investigating subcutaneous (SC) NIVO, co-formulated with recombinant human hyaluronidase PH20 (rHuPH20), as it may benefit patients, clinicians, and the healthcare system. Patients with cancer often prefer SC over IV administration. SC dosing may alleviate the need for IV vein ports, lower the risk of dosing errors, allow more patient flexibility, and reduce dose preparation and administration times, thereby optimizing occupancy in infusion centres. In CheckMate 8KX, SC NIVO + rHuPH20 was well tolerated in patients with different solid tumours and exposures were comparable to IV NIVO 3 mg/kg Q2W (from historical data). Investigations of SC NIVO vs IV NIVO in patients with clear cell renal cell carcinoma (phase 3 CheckMate 67T study) or melanoma following complete resection are ongoing. CheckMate 6GE is a multicentre, randomized, open-label, phase 3 study evaluating the pharmacokinetic (PK) noninferiority of SC NIVO + rHuPH20 vs IV NIVO in patients with melanoma following complete resection. Inclusion criteria are stage IIIA/B/C/D or stage IV melanoma, complete resection ≤ 12 weeks before randomization or treatment assignment, and ECOG performance status ≤ 1. Key exclusion criteria include a history of uveal/mucosal melanoma, untreated/unresected CNS metastases, concurrent malignancy or history of prior malignancy active ≤ 2 years before randomization or treatment assignment, known or suspected autoimmune disease, serious/uncontrolled medical disorder 4 weeks before screening, and prior immunotherapy. Patients (N ≈ 286) are randomized (1:1) to receive SC NIVO or IV NIVO in part 1 (stratified by stage [IIIA/B vs IIIC/D/IV] and weight [< 80 kg vs ≥ 80 kg]) or enrolled in the part 2 PK cohort. PK, safety, efficacy, immunogenicity, and cancer treatment satisfaction will be evaluated (Table).Table: 882TiPPrimary endpointsTime-averaged NIVO serum concentration over the first 28 daysCmin at steady stateSecondary endpointsSafety and tolerability, eg, AEs, serious AEs, immune-mediated AEs, death, administration-related reactions, laboratory abnormalitiesRecurrence-free survivalOverall survivalAdditional PK parameters: Cmin on Day 28, Cmax after the first dose, time to Cmax after the first dose, Cmax at steady state, time-averaged NIVO serum concentration at steady stateImmunogenicity (anti-NIVO and neutralizing antibodies)Cancer Treatment Satisfaction QuestionnaireAE, adverse event; Cmax, maximum NIVO serum concentration; Cmin, minimum NIVO serum concentration. Open table in a new tab AE, adverse event; Cmax, maximum NIVO serum concentration; Cmin, minimum NIVO serum concentration. NCT05297565. Professional medical writing and editorial assistance was provided by George Hsu, PhD, and Matthew Weddig, BA, of Spark Medica Inc., funded by Bristol Myers Squibb. Bristol Myers Squibb.

Interventions and Impact of Pharmacist-Delivered Services for People Infected with COVID-19: A Systematic Review.

Pharmacists are essential members of the healthcare team. The emergence of the novel coronavirus disease 2019 (COVID-19) pandemic has led pharmacists to undertake additional clinical roles. We aim to conduct a systematic review on the interventions and impact of pharmacist-delivered services in managing COVID-19 patients. We searched PubMed, Embase, Scopus, CINAHL plus, International Pharmaceutical s, and Web of Science from 1 December 2019 (the first case of COVID-19 emerged) to 13 January 2022 to retrieve the articles. Cochrane handbook and PRISMA guidelines were followed respectively to perform and report the review. The pharmacist-led interventions were reported following the Descriptive Elements of Pharmacist Intervention Characterization Tool (DEPICT) version 2. The protocol of systematic review was registered on PROSPERO (CRD42021277128). Studies quality was assessed with the modified NOS scale. In total, 7 observational studies were identified from 10,838 studies. Identification of dosage errors (n = 6 studies), regimen modifications (n = 5), removal of obsolete/duplicate medications (n = 5), identification and management of adverse drug reactions (n = 4), drug interactions prevention (n = 2), and physicians acceptance rate (n = 3) of therapy-related services delivered in-person or via tele-pharmacy were among the pharmacist-delivered services. Common interventions delivered by pharmacists also included optimizing the use of antibacterial, antivirals, and anticoagulants in COVID-19 infected patients. The acceptance of pharmacist-delivered services by physicians was high (88.5–95.5%). Included studies have described pharmacists’ beneficial role in managing patients with COVID-19 including detection, resolution, and prevention of medication-related problems, with physicians demonstrating high trust in pharmacists’ advice. Future research should assess the feasibility and scalability of such roles in real-world settings.

Therapeutic Error: Types and Prevention Strategies and Focus about "Look Alike/Sound Alike" and "High Risk" Drugs

Introduction: Therapeutic errors are among the main causes of drug-related problems, in terms of enhanced toxicological or reduced therapeutic effect, and concern all stages of the drug chain, from manufacturing to prescription, dispensing and administration. Everyone, pharmacists and doctors in all settings, should be aware of how to prevent and manage them and which drugs are at greatest risk. In this article we will focus on LASA (look alike/sound alike), on FAR (high-risk drugs) and on the guidelines especially for prevention.&#x0D; Methods: The article is a minireview that was written by research in paper and online on PubMed and Embase. We performed a search of any publications available in these databases between the years 1990 and 2022, using the key words: therapeutic errors, misuse / diversion of drugs, drug poisoning. After a review of the titles and abstracts, the articles chosen were considered relevant in providing evidence of the problem. We also added personal knowledge about the topic of the article and used some paper documents.&#x0D; Discussion and Conclusions: Most of the errors in therapy occur during administration, due to errors in doses, posology or interactions or incorrect manipulations of pharmaceutical forms, and in dispensing, due to incorrect interpretation of the prescription or confusion on the packaging in the case of LASAs. Pharmacists and doctors but also patients themselves should pay attention to the time of prescription and doctors to the drug history not only for interactions but also to avoid making mistakes in patients who take drugs with names or packages similar to the one described above. Moreover, attention must be paid in writing the prescription, in dosage, and pharmaceutical forms. Particular attention should be paid to handling by children and to avoiding any misuse of the medicines themselves.

Observational study on medication administration errors at a University Hospital in Brazil: incidence, nature and associated factors

BackgroundMedication administration errors are frequent and cause significant harm globally. However, only a few data are available on their prevalence, nature, and severity in developing countries, particularly in Brazil. This study attempts to determine the incidence, nature, and factors associated with medication administration errors observed in a university hospital.MethodsThis was a prospective observational study, conducted in a clinical and surgical unit of a University Hospital in Brazil. Two previously trained professionals directly observed medication preparation and administration for 15 days, 24 h a day, in February 2020. The type of error, the category of the medication involved, according to the anatomical therapeutic chemical classification system, and associated risk factors were analyzed. Multivariate logistic regression was adopted to identify factors associated with errors.ResultsThe administration of 561 drug doses was observed. The mean total medication administration error rate was 36.2% (95% confidence interval 32.3–40.2). The main factors associated with time errors were interruptions. Regarding technique errors, the primary factors observed were the route of administration, interruptions, and workload.ConclusionsHere, we identified a high total medication administration error rate, the most frequent being technique, wrong time, dose, and omission errors. The factors associated with errors were interruptions, route of administration and workload, which agrees well with the results of other national and international studies.

Detection of novel benzodiazepines in post-mortem cases

The global prevalence of novel benzodiazepines (BZDs) has increased significantly in recent years with the predominant BZDs constantly changing to evade bans pertaining to specific chemical structures. As of 2020 the European Union Early Warning System (EWS) was monitoring 30 novel BZDs, 16 of which have been reported since 2016. Evidence of novel BZD-associated harms is growing and there is concern regarding their prevalence in drug-related deaths. We therefore analysed deaths in England, Wales, and Northern Ireland where novel BZDs, i.e., those that are not available on prescription via the National Health Service (NHS) in the United Kingdom, were detected at post-mortem in order to determine the circumstances surrounding novel BZD-associated fatalities. The National Programme on Substance Abuse Deaths (NPSAD) receives voluntary reports on drug-related deaths from coroners across England, Wales, and Northern Ireland that covers approximately 80% of all coronial jurisdictions. Deaths that occurred between 1999-2020 and were reported to NPSAD by the 1st of November 2021 where a novel BZD was detected at post-mortem were extracted for analysis. Qualifying cases contained toxicological evidence of novel BZDs and/or their metabolites in post-mortem tissue(s). Analysis and statistical tests were performed using the IBM® SPSS software (Version 26). 971 deaths were extracted from NPSAD where a novel BZD was detected at post-mortem, with the first post-mortem detection occurring in 1999 with flunitrazepam. A sharp increase in deaths has been reported since 2016 and a total of 16 different novel BZDs detected in submitted toxicology reports. Five of these novel BZDs were detected for the first time in 2019 and 2020 (flualprazolam, delorazepam, flubroalprazolam, cinolazepam, meclonazepam), but nevertheless represent 20% of total novel BZD detections ( n = 211/1,064 [note: in some cases multiple novel BZDs were detected]). The most commonly detected novel BZDs were alprazolam and phenazepam until 2018, after which etizolam, flubromazolam and flualprazolam detections prevail. The cause of death in 95% of cases ( n = 926/971) was due to drug toxicity in which novel BZDs were directly implicated in causing death in 34% ( n = 319/926). Polydrug use was evident in 99% of cases ( n = 964/971) and the majority involved the co-administration of at least one additional central nervous system (CNS) depressant (98%, n = 943/964), namely opioids (84%, n = 812/964). Most deaths were deemed to be accidental in nature (92%, n = 894/971), with small proportions due to suicide (4%, n = 42/971), natural causes (1%, n = 12/971), and those where intent could not be determined (2%, n = 23/971). Decedents were mainly male (83% of cases, n = 801/971), had a known history of illicit substance use (71%, n = 687/971) and lived in the most deprived areas of the country (deciles 1-3, 59% of cases; n = 541/971). The results of this study document a startling increase in novel BZD detections in post-mortem toxicology, with a shift in the predominant novel BZDs over time. As novel BZDs are sold on the Internet as ‘research chemicals’ or the illicit market at a low cost, there is greater access and less oversight which can lead to dosing errors and unintended adverse effects. The concomitant use with other CNS depressants furthers the likelihood of a fatal outcome through increased sedation and respiratory depression, as shown here with the majority of fatalities resulting from mixed drug toxicity. To our knowledge this is the largest dataset on novel BZD-related fatalities to date. Reporting of novel BZD deaths has increased considerably in England, Wales, and Northern Ireland with specific concerns relating to polydrug use. The wide availability of novel BZDs combined with the lack of complete understanding regarding their pharmacology is likely contributing to the exponential rise in novel BZD-associated fatalities.

Online searches of children's oseltamivir in public primary and specialized care: Detecting influenza outbreaks in Finland using dedicated databases for health care professionals.

Health care professionals working in primary and specialized care typically search for medical information from Internet sources. In Finland, Physician's Databases are online portals aimed at professionals seeking medical information. As dosage errors may occur when prescribing medication to children, professionals' need for reliable medical information has increased in public health care centers and hospitals. Influenza continues to be a public health threat, with young children at risk of developing severe illness and easily transmitting the virus. Oseltamivir is used to treat children with influenza. The objective of this study was to compare searches for children's oseltamivir and influenza diagnoses in primary and specialized care, and to determine if the searches could aid detection of influenza outbreaks. We compared searches in Physician's Databases for children's oral suspension of oseltamivir (6 mg/mL) for influenza diagnoses of children under 7 years and laboratory findings of influenza A and B from the National Infectious Disease Register. Searches and diagnoses were assessed in primary and specialized care across Finland by season from 2012-2016. The Moving Epidemic Method (MEM) calculated seasonal starts and ends, and paired differences in the mean compared two indicators. Correlation was tested to compare seasons. We found that searches and diagnoses in primary and specialized care showed visually similar patterns annually. The MEM-calculated starting weeks in searches appeared mainly in the same week. Oseltamivir searches in primary care preceded diagnoses by -1.0 weeks (95% CI: -3.0, -0.3; p = 0.132) with very high correlation (τ = 0.913). Specialized care oseltamivir searches and diagnoses correlated moderately (τ = 0.667). Health care professionals' searches for children's oseltamivir in online databases linked with the registers of children's influenza diagnoses in primary and specialized care. Therefore, database searches should be considered as supplementary information in disease surveillance when detecting influenza epidemics.

EVALUATING THE IMPACT OF ELECTRONIC HEALTH RECORD SYSTEMS ON REDUCING MEDICATION ERRORS: A STUDY AT LADY READING HOSPITAL, PESHAWAR

Medication mistakes significantly threaten hospitals, leading to adverse events and increased healthcare costs. Electronic health records (EHRs) have been introduced to reduce the frequency of errors and mitigate these issues. This study aimed to determine if the EHR system reduced medical errors at Lady Reading Hospital (LRH) in Peshawar, Pakistan, thereby enhancing patient safety. A retrospective study was conducted from January 3, 2021, to July 3, 2021. The assessment involved a detailed analysis of medication error incidents at LRH, recorded during this period, involving 200 patients. Data from the Department of Pharmacy were collected and analyzed concerning the occurrence, types, and possible contributing causes of medication errors. The results showed a significant reduction in medication error rates following the implementation of the EHR system. The number of medication errors decreased from 80 incidents to 30 occurrences. Specifically, overall mistakes dropped from 25 to 5, omissions from 15 to 10, and wrong medication reports from 20 to 8. The most common types of errors included dosage errors (accounting for 50 incidents), followed by wrong medication (30 incidents), and omissions (25 incidents). Factors contributing to these errors included communication gaps (20 incidents), transcribing errors (15 incidents), and inadequate training (10 incidents). An evaluation of the severity of these errors revealed 15 minor, 25 moderate, and 10 severe problems. Implementing the EHR system significantly enhanced patient safety by improving communication and providing continuous access to accurate patient information. The findings indicate that EHRs are a crucial component of hospital drug safety, significantly reducing medication errors. Integrating electronic record-keeping facilitates medication management processes, provides real-time information access, and improves communication among healthcare professionals. However, addressing other aspects of system malfunctions and ensuring effective system distribution is essential for successful EHR implementation in healthcare facilities. Future research should focus on designing longitudinal studies to evaluate the long-term safety of medications, the use of EHR systems, and strategies to further improve patient care quality.

Liquid Medication Dosing Error amongst Parents Caregivers at Outpatient Clinic

Abstract: Objectives: To evaluate the effectiveness of Patient Information Leaflet (PIL) based educational intervention to improve liquid medication measuring ability of parents/ caregivers. Simultaneously, to assess parents’ measuring ability by dosing instrument type, and identify the association of various factors with dosing errors. Materials and Methods: A multi-centric, randomized controlled interventional study conducted at 2 pediatric clinics in Gandhinagar, Gujarat. Primary caregivers who would be giving medication to the patient (1 year to 12 years) were randomized in an alternative manner into control (without education) and intervention group (education with PILs), and asked to measure a dose of 5 mL using 3 measuring devices: dosing cup, oral dropper and calibrated spoon. Measured doses were categorized as an accurate dose (<10% deviation), acceptable dose (10%-20% deviation) and inaccurate dose (>20% deviation). Results: Total 164 parents/caregivers were enrolled and randomized; 82 in each group. Overall, 65.8% and 79.2% measured doses were accurate in the control and intervention group, respectively (p=0.0018). The range of measured doses (mL) of control group was higher than that of intervention group. About the instruments, the maximum number of participants measured an inaccurate dose with the calibrated spoon (10.9%), and the range of doses of oral dropper and calibrated spoon were higher than that of the dosing cup. Additionally, the likelihood of making dosing errors was not associated with the instruments used, gender, age and education level of the participants. Conclusion: The education provided to the participants helped to improve their measuring ability. Participants’ measuring ability was better while using the dosing cup as compared with the use of oral dropper and calibrated spoon. Keywords: Pediatric, Oral liquid medication, Parent’s dosing error, Medication error, Patient education.

Development of a device that remotely removes a mask in the head and neck immobilization system: a prototype and demonstration experiment.

In this study, a prototype device was developed to quickly remove the mask used to immobilize the head and neck by remotely releasing the quick fasteners. As a first step in investigating the usefulness of this prototype, we performed repeated removal tests and examined the accuracy of dose calculation. The results showed that the quick-release fasteners of a Type-S system (CIVCO Medical Solutions, Iowa, USA) could be removed remotely and accurately (success rate: 100%). Additionally, the dose errors in treatment planning were negligible (< 1.0%), and the gamma pass rate was equivalent (99.9%). Therefore, this prototype device with a remote system would help manage patient safety in emergencies, such as a disaster or a sudden change in the patient's condition. However, age-related deterioration with long-term clinical use or its ability to link with beam-off still requires further exploration.

Improving Caregiver Understanding of Liquid Acetaminophen Administration at Primary Care Visits

Liquid medication dosing errors are common in pediatrics. Our outpatient clinic identified gaps in caregiver education based on a 2015 American Academy of Pediatrics policy statement on prescribing liquid medications. This quality improvement (QI) initiative sought to improve caregiver's understanding of liquid acetaminophen administration at the 2-month well-child visit from 30% to 70% over a 32-month period. A resident-led interdisciplinary QI team performed sequential interventions to improve our outcome measure: the percentage of caregivers with an adequate understanding of 4 essential components of liquid acetaminophen administration (name, indication, dose, and frequency). Outcome data were collected via a 4-item verbal assessment of caregiver's understanding by nursing staff, with correct answers to all items considered adequate understanding. Process measures (medications prescribed and education provided), and balancing measures (anticipatory guidance items discussed) were gathered via electronic health record review. Shewhart "P" charts and established rules for detecting special cause variation were used to analyze data. Scatter plots assessed the association between the provision of syringes and caregiver understanding of medication administration. In 636 caregivers, overall understanding of medication use improved from 39.8% to 74%. Knowledge of accurate dosage improved from 50.9% to 76.8%. Correlation between syringe provision and caregiver understanding was strong (R = .84). Resident-led QI improved caregiver's understanding of liquid acetaminophen administration in infants. The most impactful interventions were implementation of English and Spanish pictograms and provision of dose-demarcated oral syringes, coupled with teach-back. Future interventions will examine generalizability to other medications and expansion to other services.