Prescription Errors Research Articles

Barriers to opioid use in the Arab world.

The Arab world consists of 22 countries, representing 5.5% of the world's population. Morphine consumption accounts for less than 1% of the world's consumption. This is the first study to identify barriers to opioid use in the Arab world. This study aimed to investigate the barriers to opioid use in pain management in the Arab world. Online survey was developed to investigate barriers to governance, prescribing, distributing, dispensing and administering, as well as educational barriers in the Arab world. The questionnaire was sent via email and a mobile app to one expert physician in pain management and one licensed pharmacist from each Arab country. With the exception of Tunisia, Djibouti and Comoros, 34(77%) participants from 19 Arab countries answered the survey. Most countries lack local opioid production, necessitate special licenses for physicians, and restrict opioid prescribing to medical specialists. Special prescription forms are mandated, and pharmacists lack the authority to correct prescription errors or accept refill or verbal orders on opioids. Storage requirements for empty ampoules and prescriptions are enforced. Nurses are not allowed to carry opioids during home visits, and only first degree relatives can collect opioids for patients. Furthermore, the integration of palliative care and pain management curricula into pharmacies and medical schools is lacking. There is a wide range of regulatory and other barriers to opioid use in the Arab world. There is a substantial need for regulatory review and reform, as well as for educational initiatives, in most Arab countries.

INTERVENÇÃO FARMACÊUTICA NA INCIDÊNCIA DE ERROS DE PRESCRIÇÃO RELACIONADA A MEDICAMENTOS

The pharmacist plays a crucial role in healthcare by helping to reduce prescription and medication errors, as well as issues related to pharmacotherapy that could harm hospitalized patients. The aim of this study was to analyze, based on the literature, the contribution of the clinical pharmacist in the hospital setting, focusing on intervention and reducing the incidence of medication-related prescription errors. By working in collaboration with the multidisciplinary team, the clinical pharmacist provides guidance to professionals on the safe and rational use of medications, which enhances the quality of patient therapy. The impact of the clinical pharmacist is significant, as they are capable of reducing the occurrence of avoidable adverse effects by 66%, which can be controlled not only through the discontinuation of medication combinations but also through dose adjustment. It is important to highlight the central role of the pharmacist in medication dispensing, emphasizing the importance of technical and clinical analysis of prescriptions and medication releases in hospital settings, thereby promoting the rational use of medications.

Assessment of Errors in Handwritten Prescriptions in Zliten City- Libya

Errors in handwritten prescriptions are a major factor in medical errors and are the main cause of harm to patients due to the lack of clarity of the prescription or the lack of correct data, which leads to the prescription of the wrong medication, causing adverse events. The present study aimed to identify the common errors in handwriting prescriptions in Zliten City. To collect information about errors in handwritten prescriptions, we used two models: first, we distributed fifty-one questionnaires to fifty-one pharmacies distributed in all areas of Zliten city, and second, we collected one hundred and fifty prescriptions from different health facilities distributed in different areas within Zliten city. The questionnaires and prescriptions then analysed to identify medical errors. In the first model of the questionnaire, the results are as follows: the patient's name and age are often present, while the gender, doctor's name, and stamp are often absent. The main issue lies in the clarity of the font for the drug's name, dose, and dosage form. In the second model of the prescriptions, the results are as follows: the patient's name is mostly present, while gender and diagnosis are absent in about 40% of the prescriptions, the doctor's name is mostly absent, and only 2% of the prescriptions have the doctor's stamp and number in the syndicate, and the main issue lies in the clarity of the font for the drug's name, dose, and dosage form., as it is unclear in between 20-30% of the prescriptions. We found that the patient's information is present in most prescriptions the opposite of the questionnaire in which it is less. Also in the prescriber's information, the analysis in our result for prescription contradicted the questionnaires, as most prescribers in the questionnaire are present, we also found that during the analysis of drug information in prescription not clear more than in the questionnaire. From this research, we concluded that there are many errors in prescriptions, possibly because of the large number of cases that need to be seen by the doctor and the speed of writing, and perhaps because doctors forget the vocabulary of the names of medicines. Because of the many errors in handwritten prescriptions, we must immediately switch to computerized prescription writing.

Audit project on the appropriateness of teicoplanin prescribing in Milton Keynes University Hospital (MKUH)

Abstract Introduction Teicoplanin is the Trust’s preferred glycopeptide antibiotic compared to vancomycin due to the once-daily dosing, less toxic side effects and monitoring requirements1. Teicoplanin dosing regimen is weight-dependent, including loading and maintenance doses adjusted according to creatinine clearance (CrCl) from Day 52. As antimicrobial resistance emergence continues to be a public health concern, appropriate teicoplanin use is vital to avoid treatment failure in line with antimicrobial stewardship3. Aim and Standards To assess teicoplanin prescribing compliance with the Trust guideline. 100% compliance was expected for the following standards: 1. Teicoplanin is prescribed for an approved indication according to Trust guideline or by a Consultant Microbiologist. 2. Loading dose of teicoplanin is prescribed for treatment initiation. 3. Appropriate teicoplanin loading dose is prescribed based on actual body weight (ABW) and indication. 4. Appropriate teicoplanin maintenance dose is prescribed until Day 4 based on ABW and indication. 5. Appropriate teicoplanin maintenance dose is prescribed from Day 5 onwards based on CrCl, ABW and indication. Method This study did not require ethics approval. To assess audit feasibility, a pilot was done looking at teicoplanin prescriptions and clinical notes against the audit standards. CrCl was calculated where appropriate. Retrospective data of 18 teicoplanin prescriptions between 08/11/2022-14/11/2022 were extracted from the Electronic Prescribing and Medicines Administration (EPMA) system onto an Excel data collection spreadsheet. No changes were made to the data collection tool. One month’s data between 11/10/2022-07/11/2022 were further extracted and process was repeated. Paediatric patients and indications for surgical prophylaxis and Clostridioides difficile infection were excluded. Results 88 patients were included in the study. 90% (n=79) of teicoplanin prescriptions were prescribed for an indication approved on the Trust’s antimicrobial guideline or by a Consultant Microbiologist. Teicoplanin loading dose was prescribed for 82% (n=71) of patients. 1 patient was excluded as loading dose was administered in another hospital. 46% (n=40) of patients were prescribed the appropriate teicoplanin loading dose. 60% (n=34) of the 57 patients who continued teicoplanin up until Day 4 were prescribed the appropriate teicoplanin maintenance dose. 56% (n=22) of the 39 patients treated with teicoplanin past Day 4 were prescribed the appropriate teicoplanin maintenance dose. None of the 5 standards were met. Conclusion The results indicate inappropriate teicoplanin prescribing against the current Trust guideline which need improvement. Training with prescribers on utilising the EPMA’s pre-populated teicoplanin dose prescription function alongside encouraging pledges to be an Antibiotic Guardian are recommended during their induction. This would help avoid prescription errors and reduce antimicrobial resistance development. The data collected did not subdivide patients under specific specialities, which could highlight areas where training should be focused on. This limitation should be addressed when the re-audit due in 1 years’ time is carried out, to evaluate the changes implemented.

System-Wide, Electronic Health Record-Based Medication Alerts for Appropriate Prescribing of Direct Oral Anticoagulants: Pilot Randomized Controlled Trial.

While direct oral anticoagulants (DOACs) have improved oral anticoagulation management, inappropriate prescribing remains prevalent and leads to adverse drug events. Antithrombotic stewardship programs seek to enhance DOAC prescribing but require scalable and sustainable strategies. We present a pilot, prescriber-level randomized controlled trial to assess the effectiveness of electronic health record (EHR)-based medication alerts in a large health system. The pilot assessed prescriber responses to alerts for initial DOAC prescription errors (apixaban and rivaroxaban). A user-centered, multistage design process informed alert development, emphasizing clear indication, appropriate dosing based on renal function, and drug-drug interactions. Alerts appeared whenever a DOAC was being prescribed in a way that did not follow package label instructions. Clinician responses measured acceptability, accuracy, feasibility, and utilization of the alerts. The study ran from August 1, 2022, through April 30, 2023. Only 1 prescriber requested trial exclusion, demonstrating acceptability. The error rate for false alerts due to incomplete data was 6.6% (16/243). Two scenarios with alert design and/or execution errors occurred but were quickly identified and resolved, underlining the importance of a responsive quality assurance process in EHR-based interventions. Trial feasibility issues related to alert-data capture were identified and resolved. Trial feasibility was also assessed with balanced randomization of prescribers and the inclusion of various alerts across both medications. Assessing utilization, 34.2% (83/243) of the encounters (with 134 prescribers) led to a prescription change. The pilot implementation study demonstrated the acceptability, accuracy, feasibility, and estimates of the utilization of EHR-based medication alerts for DOAC prescriptions and successfully established just-in-time randomization of prescribing clinicians. This pilot study sets the stage for large-scale, randomized implementation evaluations of EHR-based alerts to improve medication safety. ClinicalTrials.gov NCT05351749; https://clinicaltrials.gov/study/NCT05351749.

Understanding prescribing errors for system optimisation: the technology-related error mechanism classification.

Technology-related prescribing errors curtail the positive impacts of computerised provider order entry (CPOE) on medication safety. Understanding how technology-related errors (TREs) occur can inform CPOE optimisation. Previously, we developed a classification of the underlying mechanisms of TREs using prescribing error data from two adult hospitals. Our objective was to update the classification using paediatric prescribing error data and to assess the reliability with which reviewers could independently apply the classification. Using data on 1696 prescribing errors identified by chart review in 2016 and 2017 at a tertiary paediatric hospital, we identified errors that were technology-related. These errors were investigated to classify their underlying mechanisms using our previously developed classification, and new categories were added based on the data. A two-step process was used to identify and classify TREs involving a review of the error in the CPOE and simulating the error in the CPOE testing environment. The technology-related error mechanism (TREM) classification comprises six mechanism categories, one contributing factor and 19 subcategories. The categories are as follows: (1) incorrect system configuration or system malfunction, (2) opening or using the wrong patient record, (3) selection errors, (4) construction errors, (5) editing errors, (6) errors that occur when using workflows that differ from a paper-based system (7) contributing factor: use of hybrid systems. TREs remain a critical issue for CPOE. The updated TREM classification provides a systematic means of assessing and monitoring TREs to inform and prioritise system improvements and has now been updated for the paediatric setting.

Improving prescribing learning in problem-based learning.

Prescribing errors are known to occur in clinical practice. To ensure prescribing competence, foundation doctors in the United Kingdom now need to pass a national Prescribing Safety Assessment (PSA). Medical students are requesting more prescribing learning. We propose that early year's problem-based learning (PBL) sessions in medical curricula may be a place where more prescribing-related material could be added to ensure preparedness to prescribe. We modified existing PBL material by adding prescribing-related tasks within the patient cases. To ensure relevancy, the prescribing tasks were blueprinted to the assessment structure of the PSA. An example task would be to tailor prescribing, advise on required monitoring and provide information about medication to the (fictional) patients. Free text questionnaires were sent to second-year medical students at two points in the academic year. Thirty-eight of 244 participants responded. Students expressed perceived deficits in their prescribing education both within PBL and in other curriculum areas. Students desired more faculty-led approaches to learning, yet acknowledged that the tasks introduced in PBL sessions, especially those that promoted use of clinical guidelines and national prescribing resources were useful. Although students expressed a desire for increased faculty-led learning on prescribing, the introduction of prescribing tasks into early-year's PBL cases has a place. For example, tasks that promote students' use of prescribing and evidence-based resources may build their confidence in using them throughout their medical degree and within the PSA assessment (where the formularies can be used by candidates).

Voluntary Neonatal Medication Incident Reporting-A Single Centre Retrospective Analysis.

Background: Medication errors in neonatal intensive care units (NICUs) are prevalent, with dosage and prescription errors being the most common. Aims: To identify the common medication errors reported over twelve years using a voluntary, nonanonymous incident reporting system (RiskMan clinical incident reporting information system) at an Australian tertiary NICU. Methods: This was a single-centre cohort study conducted at a tertiary NICU. All medication-related incidents (errors) reported prospectively through the RiskMan online voluntary reporting database from January 2010 to December 2021 were included. The medication incidents were grouped into administration, prescription, pharmacy-related, and others, which included the remaining uncommon incidents. Results: Over the study period, 583 medication errors were reported, including administration-related (41.3%), prescription-related (24.5%), pharmacy-related (10.1%), and other errors (24%). Most incidents were reported by nursing and midwifery staff (77%) and pharmacists (17.5%). Most outcomes were minor or insignificant (98%), with only a few resulting in major or significant harm. There was one extreme incident that may have contributed to the death of a neonate and nine moderate incidents. Conclusions: Our results demonstrate that medication errors are common and highlight the need to support improvement initiatives and implement existing evidence-based interventions in routine practice to minimise medication errors in the NICU.

Improving Collaborative Interactions Between Humans and Artificial Intelligence to Achieve Optimal Patient Outcomes in the Healthcare Industry

The introduction of Artificial Intelligence (AI) into the healthcare industry holds immense promise for improving patient outcomes. However, the interaction between healthcare professionals and AI systems is critical to fully realize the potential benefits. Artificial intelligence (AI) applications have transformed healthcare. This study is based on a general literature review uncovering the role of Al in healthcare and focuses on the following key aspects: medical imaging and diagnostics, virtual patient care, medical research and drug discovery, patient engagement and compliance, rehabilitation and other administrative applications. The impact of AI is observed in detecting clinical conditions in medical imaging and diagnostic services, controlling the outbreak of coronavirus disease 2019 (COVID-19) with early diagnosis, providing virtual patient care using Ai-powered tools, managing electronic health records, augmenting patient engagement and compliance with the treatment plan, reducing the administrative workload of healthcare professionals (HCPs), discovering new drugs and vaccines, spotting medical prescription errors, extensive data storage and analysis, and technology-assisted rehabilitation. Nevertheless, this science pitch meets several technical, ethical, and social challenges, including privacy, safety, the right to decide and try, costs, information and consent, access, and efficacy, while integrating AI into healthcare. The governance of AI applications is crucial for patient safety and accountability and for raising HCPs’ belief in enhancing acceptance and boosting significant health precisely address regulatory, ethical, and trust issues while advancing the acceptance and implementation of AI. Since COVID-19 hit the global health system, the concept of AI has created a revolution in healthcare, and such an uprising could be another step forward to meet future healthcare needs.

GLP-1 RA Prescribing Errors in a Multidisciplinary Digital Weight-Loss Service: A Retrospective Quantitative Analysis.

Digital weight loss services (DWLSs) that use Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have demonstrated potential in contributing to a shift in global obesity rates. However, reasonable concerns have been raised about the prescribing safety of these services. Prior to this study, electronic prescribing safety had only been investigated in hospital settings and community clinics. This study retrospectively analyzed prescribing errors committed over a 6-month period in 2023 at Australia's largest GLP-1 RA-supported DWLS. The analysis found that 1654 (4.4%) of the 37323 audited GLP-1 RA prescriptions contained an error. Most errors pertained to insufficient safety counselling (49.15%) and inadequate investigations of potential contraindications (30.29%). Although a large portion of prescribing errors were detected via the automated query method (64.9%), the other three auditing methods all detected a significant number of true errors (>100). Patients from the highest body mass index category (40+ kg/m2) were overrepresented in the service's prescribing error data. These findings lay a vital foundation in the emerging literature on GLP-1 RA-supported DWLSs.

"Doctor, would it surprise you if there were prescribing errors in this patient's medication?" Identifying eligible patients for in-hospital pharmacotherapeutic stewardship: A matched case-control study.

Evaluating a patient's medication list is critical to reduce prescribing errors (PEs), but is a labour- and time-intensive process. Identification of patients at risk of PEs could improve the allocation of scarce time and resources, but currently available prediction tools are not effective. To investigate whether ward doctors can identify patients at risk of PEs. This prospective matched case-control study was conducted on three clinical wards in an academic hospital. Otolaryngology and oncology ward doctors used clinical intuition to select patients requiring a clinical medication review (CMR) (cases). These patients were then matched 1:1 on age (±10years) and number (±1) of prescriptions with patients not selected for CMRs on the internal medicine and upper gastrointestinal surgery ward (controls). A multidisciplinary in-hospital pharmacotherapeutic stewardship team assessed the prevalence of PEs. A total of 387 patients with 5191 prescriptions were included. Overall, 799 PEs affecting 279 patients (72.1%) were identified. Most PEs (58.8%) occurred during hospitalization. There were no significant differences in age, number of prescriptions, sex, renal function or documented allergies or intolerances between the cases and controls or between controls and other patients who did not receive a CMR. The incidence of PEs was higher in cases than in controls (97.5% vs 72.5%, odds ratio= 14.8, 95% confidence interval [CI] 1.8-121.1, P= .002)). The rate of PEs was three times higher in cases than in controls (incidence rate ratio=3.0, 95% CI 2.3-4.0, P< .001). Ward doctors can effectively identify patients with PEs, and thus at risk of medication-related harm, using clinical intuition.

Pharmacists at the Forefront: Identifying and Addressing Prescription Errors in Outpatient Settings of Tertiary Care Hospitals in Pakistan

Objective: The study sought to quantify the frequency and categorize the types of prescribing errors occurring in outpatient settings while evaluating the efficacy of pharmacist interventions in mitigating such errors. Methodology: This study was a cross-sectional, retrospective interventional study conducted over a one-year period from September 1, 2017, to August 31, 2018, at the outpatient departments of one government and one private tertiary care hospital in Hyderabad, Pakistan. A total of 2,552 outpatient prescriptions were randomly collected and evaluated by the researchers to identify prescribing errors, using the British National Formulary (BNF) as a reference guide. The study rigorously adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines, ensuring comprehensive reporting, transparency in methodology, analysis, and interpretation of the observational research findings Results: The collected data were analyzed using chi-square tests in SPSS version 25 to assess statistical significance. Among the 2,552 outpatient prescriptions examined, 12,501 (40.4%) prescribing errors were identified. The error rate was higher in the government hospital (6,672; 42.8%) compared to the private hospital (5,829; 38.0%). The most prevalent errors occurred during the subscription stage (2,302; 45.1%), with 1,245 (48.1%) and 1,057 (42.0%) errors in the government and private hospitals, respectively. This was followed by errors in the inscription (3,447; 45.0%), superscription (5,156; 40.4%), and transcription (1,596; 31.3%) stages. Common interventions during the subscription stage addressed incomplete patient information (age, weight, etc.), missing consultant signatures, and stamps. For the inscription stage, frequent interventions involved incorrect drug doses and strengths.Typical interventions for the subscription and inscription stages included adding missing therapy durations and usage instructions, respectively. Pharmacist interventions were accepted at a higher rate in private hospitals (3,669; 62.9%) compared to government hospitals (3,675; 55.1%), with a total of 7,344 (58.7%) interventions accepted. Conclusion: The study revealed a high prevalence of prescribing errors across all stages of the outpatient prescription process, with the subscription stage being the most error-prone. The findings highlight the critical role of pharmacist-led prescription interventions in mitigating prescribing errors, thereby enhancing prescribing practices, optimizing therapeutic outcomes, and safeguarding patient safety.

Pharmacists' interventions on prescribing errors in Malaysia.

Prescribing errors (PEs) cause significant avoidable harm globally. In Malaysia, despite the prevalence of PEs in government healthcare facilities, there is limited research on how pharmacist staffing levels influence intervention frequency and effectiveness. This study aims to address this gap by analysing intervention trends and assessing their association with staffing levels, highlighting the correlation between increased pharmacist presence and the frequency of interventions. This retrospective cross-sectional study analysed data from the Ministry of Health's Pharmacy Management Form and the Pharmacy Board Registry from 2017 to 2019. Multivariate regression and two-way ANOVA assessed the association between the number of pharmacists, total prescriptions, and interventions on PEs in Health Clinic Outpatient Pharmacy, Hospital Outpatient Pharmacy, and Hospital Inpatient Pharmacy settings. Annually, pharmacists intervened in approximately 1.8% of total prescriptions, with the most common errors being wrong dose, wrong medication, and wrong dosing frequency. These interventions were consistent across all settings, highlighting the uniformity in pharmacists' approach to managing PEs. The regression analysis revealed a significant positive correlation between the number of pharmacists, total prescriptions, and interventions on PEs, with an adjusted R-squared value of 0.899. Both the number of pharmacists and total prescriptions received were positively significant (p < 0.05), indicating that increased pharmacist presence strongly correlates with intervention frequency. No statistically significant differences were observed in intervention rates across different settings and severity levels, suggesting that pharmacists consistently provide effective interventions irrespective of the clinical context. In conclusion, this study confirms that increasing the number of pharmacists and total prescriptions received are critical predictors of interventions on PEs in Malaysia. It underscores the vital role of pharmacists in enhancing patient safety and healthcare quality, demonstrating their effectiveness in diverse settings and their adaptability to various patient needs and challenges.

Enhancing antibiotic prescribing practices at the main military training hospital of Tunis: A study of pharmaceutical interventions

Bacterial infections have historically posed significant challenges until the discovery of antibiotics, which revolutionized infectious disease treatment. However, bacterial adaptation mechanisms over time have led to increased antimicrobial resistance, necessitating judicious antibiotic use. This study aims to comprehensively analyze pharmaceutical interventions related to antibiotic prescriptions governed by antibiotic order forms to identify and rectify medication errors, optimizing antibiotic prescribing practices. Approval for this research was obtained from the institutional review board of the Main Military Training Hospital of Tunis, Tunisia. A retrospective study was conducted at the main military training hospital of Tunis over 4 months. Pharmaceutical validation of antibiotic prescriptions through antibiotic order forms was conducted by a pharmacy resident. Pharmaceutical interventions were initiated upon detection of errors, and patient records were accessed through institutional software. Out of 1100 prescription forms analyzed, 41 pharmaceutical interventions were conducted for 7 antibiotics. Twenty-four percent of all interventions were related to antibiotic order forms, with the intensive care unit accounting for the highest number of errors. Under-dosage and prescription errors were common. Our pharmaceutical interventions related to antibiotic order forms are crucial for optimizing antibiotic therapy. Feedback mechanisms to healthcare teams are essential for enhancing prescription quality and patient care outcomes. Ongoing surveillance and improvement efforts are necessary to address medication errors and enhance antimicrobial stewardship.

Recognizing and preventing unacknowledged prescribing errors associated with polypharmacy

BackgroundPrescribing errors put an enormous burden on health and the economy, claiming implementation of effective methods to prevent/reduce them. Polypharmacy regimens (five or more drugs) are highly prone to unacknowledged prescribing errors, since the complex network of drug-drug interactions, guidelines and contraindications is challenging to be adequately evaluated in the prescription phase, especially if different doctors are involved. Clinical decision support systems aimed at polypharmacy evaluation may be crucial to recognize and correct prescribing errors.MethodsA commercial clinical decision support system (Drug-PIN®) was applied to estimate the frequency of unrecognized prescribing errors in a group of 307 consecutive patients accessing the hospital pre-admission service of the Sant’Andrea Hospital of Rome, Italy, in the period April-June 2023. Drug-PIN® is a two-step system, first scoring the risk (low, moderate or high) associated with a certain therapy-patient pair, then allowing therapy optimization by medications exchanges. We defined prescribing errors as cases where therapy optimization could achieve consistent reduction of the Drug-PIN® calculated risk.ResultsPolypharmacy was present in 205 patients, and moderate to high risk for medication harm was predicted by Drug-PIN® in 91 patients (29.6%). In 58 of them (63.7%), Drug-PIN® guided optimization of the therapy could be achieved, with a statistically significant reduction of the calculated therapy-associated risk score. Patients whose therapy cannot be improved have a statistically significant higher number of used drugs. Considering the overall study population, the rate of avoidable prescribing errors was 18.89%.ConclusionsResults suggest that computer-aided evaluation of medication-associated harm could be a valuable and actionable tool to identify and prevent prescribing errors in polypharmacy. We conducted the study in a Hospital pre-admission setting, which is not representative of the general population but represents a hotspot to intercept fragile population, where a consistent fraction of potentially harmful polypharmacy regimens could be promptly identified and corrected by systematic use of adequate clinical decision support tools.

Prescribing Errors in an Ambulatory Care Setting: Mitigating Risks in Outpatient Medication Orders, Cross-Sectional Review.

Prescribing errors (PEs) are the most common type of medication error, which may occur by prescribing the wrong medication, improper dose, dosage, and/or even prescribing a drug to the wrong patient. The present study aims to compile PEs that were generated in an ambulatory care setting at a tertiary-care hospital in Saudi Arabia. A retrospective cross-sectional review was conducted for all reported PEs in ambulatory care clinics for 3 years. The potential hazardous outcomes of these PEs were classified according to the medication error index. A total of 897 records containing 1199 PEs were retrieved. More than a third of prescribers had frequently committed PEs-ranging from 2 to 39 times. The most encountered errors were prescribing incorrect doses, medication duplication, incorrect dosing frequency, and inappropriate duration (34.5%, 14.1%, 11.6%, and 9.8%, respectively). The most frequent mistakes were when prescribing antibiotics (22.9%) and drugs for cardiovascular conditions (18.5%). Most errors were of mild to moderate severity, mostly type-B near-miss errors and did not reach patients. Only two prescription events (0.17%) had severe consequences that required intervention to avoid any subsequent harm or damage. The current investigation has revealed a substantial percentage of PEs, mostly in internal medicine and cardiology departments. Although PEs are undoubtedly not easy to avoid, monitoring and recognizing these inaccuracies is pivotal to preventing potential harm and promoting patient safety.

Assessing the Effectiveness of Telepharmacy Services in Rural and Underserved Areas

This study evaluates the effectiveness of telepharmacy services in improving healthcare delivery in rural and underserved areas. Utilizing a mixed-methods design, both quantitative and qualitative data were collected over a 12-month period. The study involved 200 patients who used telepharmacy services, providing remote access to pharmacists for medication dispensing, consultations, and patient education. Quantitative data included patient surveys on medication adherence and satisfaction, along with medication records to assess dispensing errors. Qualitative data were obtained through interviews with patients and pharmacists to explore their experiences. Results indicated a significant increase in medication adherence rates from 60.0% to 85.0% post-telepharmacy implementation. Patient satisfaction scores across various domains improved notably, with mean scores for access to pharmacists, quality of consultations, and overall satisfaction showing significant enhancements (p &lt; 0.001). Additionally, there was a substantial reduction in medication errors, with dispensing errors decreasing from 15.0% to 5.0% (p &lt; 0.01) and prescription errors from 10.0% to 4.0% (p &lt; 0.05). Economic analysis revealed a decrease in healthcare costs per patient from $2000 to $1500, along with a reduction in hospitalizations per 1000 patients from 50 to 30 (p &lt; 0.01). These findings are consistent with previous studies and underscore the potential of telepharmacy as a cost-effective and efficient solution to healthcare disparities in rural and underserved regions. Despite technological and regulatory challenges, telepharmacy represents a promising approach to enhancing healthcare access, improving clinical outcomes, and achieving significant cost savings in rural healthcare systems.

Pharmacists Impact on Promoting the Public Health

Because they can guarantee that patients receive safe and effective medications, pharmacists are essential members of the healthcare team. In an effort to maximize patient results, they work in tandem with other medical specialists to evaluate pharmacological therapy, dispense medication, counsel patients on drug interactions and side effects, and monitor medication schedules. Pharmacists also give patients advice on managing illnesses, changing lifestyles, and adhering to medication regimens. The range of work that pharmacists do has expanded with the emergence of numerous global health issues. Safe and efficient drug usage by community and clinical pharmacists is necessary to provide the best possible patient outcomes. The public is still ignorant about the pharmacist's contribution to national and international health, nevertheless. They also perform drug use assessments, act as drug information specialists, and offer advice on the proper choice and dosage of medications. Pharmacists play a critical role in healthcare organizations as they strive to reduce prescription errors, enhance patient safety, and manage costs. The pharmacist can improve public health in a beneficial way. Thus far, the rise in the importance of pharmacists has been more influenced by the expansion of patient services than by a population-based approach to health. Pharmacists may find that integrating the five public health core competencies—social and behavioral science, health policy and administration, epidemiology, biostatistics, and environmental health sciences—into their pharmacy practice increases their efficacy and influence.

Enhancing Medication Safety with ML-Enhanced Decision Support Systems: A Comparative Analysis of Prescription Error Detection

Background: Medication prescription errors are a global issue, leading to significant morbidity and mortality. Traditional rule-based Medical Decision Support Systems (MDSS) are often ineffective, generating numerous false alerts and failing to detect all potential errors. This study assesses a new anomaly detection system integrated with Electronic Health Records (EHR) to improve the accuracy and utility of medication error warnings. Methods: Anomalous prescription detection was implemented alongside an existing MDSS in a real-world inpatient setting over 18 months. The new system utilized Machine Learning (ML) combined with a rule-based MDSS to analyze historical EHR data. It aimed to identify and flag high-risk prescriptions through real-time anomaly detection. The performance of this hybrid system was compared against traditional MDSS and multicriteria query (MQ) methods. A clinical pharmacist reviewed 415 patients (3401 prescriptions) to validate the effectiveness of the system, assessing notifications for accuracy, clinical relevance, and practicality. Results: The ML-enhanced MDSS demonstrated superior performance compared to traditional systems. It achieved a 76% interception rate for prescriptions needing pharmacist review and a precision rate of 75%. The hybrid system outperformed traditional MDSS and MQ methods, with areas under the ROC and PRC curves of 0.84 and 0.79, respectively, compared to 0.66 and 0.57 for MDSS and 0.7 and 0.58 for MQ approaches. Conclusion: Integrating ML with rule-based MDSS significantly improves the detection of high-risk medication prescriptions, reducing false alerts and enhancing accuracy. This hybrid approach offers a more effective tool for identifying potential medication errors and improving patient safety in inpatient settings.

A Smart Diagnostic, e-Prescription and Cryptocurrency Billing System

This study focuses on the development of a smart e-prescription and billing system that integrates blockchain, artificial intelligence (AI), and analytics to enhance healthcare services. The system's core features include an AI-driven symptom checker, appointment scheduling, and cryptocurrency-based billing. A systematic review of secondary data from academic studies and industry-related articles was conducted to assess current practices in drug prescription, dispensation, and existing software solutions. The symptom-checker model was trained using a dataset of 4,963 entries, with an 80/20 split between training and testing sets. A Decision Tree Classifier was employed, showing promising performance. The findings suggest that the e-prescription (eRx) application can reduce healthcare costs, minimize prescription errors, and improve the overall quality and efficiency of care. The system was built using frontend web technologies, with Python supporting backend functionalities. Cryptocurrency was implemented as the primary payment method, while machine learning was used to support appointment scheduling. The study recommends reliable internet access and adequate hardware for optimal system performance.