The 2023 American Geriatrics Society Updated Beers Criteria® Application in Low- and Middle-Income Countries: A Walk-through.

The 2023 update of the American Geriatrics Society Beers Criteria® provides a comprehensive set of guidelines for optimizing medication use in older people. While this update is based on a rigorous review of evidence from clinical trials and research studies published between 2017 and 2022, its application in low- and middle-income countries (LMICs) may present unique challenges and considerations. LMICs often face different health care realities compared with high-income countries, such as limited access to medications, varying prescribing practices, and resource constraints. As a result, the Beers Criteria® 2023 update, which includes the addition, deletion, and revision of medicines based on new evidence, may not be entirely applicable or feasible in these settings. This commentary aims to explore the implications of the 2023 Beers Criteria® update for LMICs, highlighting the need for context-specific adaptations and strategies to optimize medication use and improve health outcomes for older people in resource-limited settings.

Assessment of drug therapy satisfaction amongst the elderly: A patient reported outcomes measures approach.

BACKGROUND: Understanding elderly experiences enhance healthcare outcomes and patient satisfaction. Recognizing caregivers' role and implementing supportive measures enhance care. OBJECTIVES: Quantify drug satisfaction using patient-reported outcomes measures approach. Assess caregiver burden using short version of Burden Scale for Family Caregivers. METHODS: Six-month cross-sectional study in Department of Geriatrics. Elderly (≥60), minimum one comorbidity, admitted for >48 h, and consenting to participate were enrolled. Patient satisfaction assessed using Treatment Satisfaction with Medicines Questionnaire (SATMED-Q). SPSS version 27 used to calculate odds ratio. RESULTS: 282 participants enrolled. SATMED-Q score 47.41 ± 10.34, indicating overall satisfaction. Treatment satisfaction range 47.07 % to 100 %. Age [OR 0.964, 95 % CI 0.932-0.996 (p = 0.029)] and education [OR 1.500, 95 % CI 1.129-1.992 (p = 0.005)] influenced satisfaction. 268 [95.03 %] had caregivers, 14 [4.96 %] did not. Caregiver burden score 9.25 ± 9.11. CONCLUSION: Insights obtained from assessing satisfaction and caregiver burden enables physicians to improve welfare of elderly and caregivers.

Idiopathic Hypertension with Multiple Cranial Nerve Palsies: A Case Report and Literature Review.

We report a rare case of idiopathic intracranial hypertension (IIH) with multiple cranial nerve palsies involving cranial nerves VI, VII, IX, and X in a 32-year-old female who had no prior comorbidities. Her condition improved rapidly on a ten-day regimen of acetazolamide and tablet topiramate. IIH should be considered in every patient presenting with persistent headache and multiple cranial nerve abnormalities. This paper also includes a literature review of similar cases.

Dose 4 You: Dose Division Calculator-A Tool to Reduce Calculation Errors.

Background: Medication dosing calculation errors can cause significant harm to patients, especially in the pediatric population. Crushing tablets for dose division purposes may increase the risk of calculation errors, which can lead to incorrect dosing and compromised patient safety. This study aimed to develop a calculator to eliminate calculation errors associated with dose division. Methods: Using the Wix platform, a group of pharmacists created a user-friendly webpage "Dose 4 You." To enable accurate dose division calculations, the advanced language model Chat GPT and Visual Studio were used. The tool assists healthcare professionals through a step-by-step process, allowing them to enter the necessary dose and medication requirements. The Dose 4 You web page's reliability and feasibility were assessed using retrospective data and validated questionnaires, including the System Usability Scale (SUS), respectively and a Likert scale-based acceptance questionnaire. Results: The Dose 4 You website calculated the required amount of powdered tablet to achieve the desired dose with 100% accuracy. The obtained SUS score was 88.38, indicating excellent usability. The average score of all questions for acceptance was found to be 4.7 ± 0.15 indicating a strong agreement on the tool's usefulness and effectiveness. Conclusion: Dose 4 You is a reliable tool that improves patient safety by streamlining dose calculations and lowering calculation errors. The tool's ease of use, practicality in daily clinical practice, and potential to reduce medication errors are highlighted by the positive perception among healthcare professionals. Dose 4 You's successful implementation demonstrates the power of technology and collaboration in transforming medication administration and improving patient outcomes. Similar innovative solutions to optimize healthcare practices can be explored in future health informatics endeavors.

Development of the EldenCare application: Empowering physicians and clinical pharmacists towards enhancing elderly care.

The growing healthcare burden on the elderly population, combined with an increase in prescription drug use, necessitates the development of novel solutions for improving elderly care. EldenCare connects doctors, clinical pharmacists, and elderly patients. EldenCare was developed by a multidisciplinary team comprising geriatricians, clinical pharmacists, and software engineers. The software offers various features tailored to the needs of each user group, revolutionizing medication management and patient care. For geriatricians, EldenCare provides efficient means of recording patient information, scheduling appointments, and documenting follow-up. Clinical pharmacists can take advantage of the software's advanced features, including identifying medication risks, facilitating dose adjustments, identifying potentially inappropriate medications, and tracking adverse drug reactions. Elderly patients benefit from features such as medication alerts, appointment management, medication lists and an adverse drug reaction diary. The study is divided into five distinct phases: requirements phase, design phase, coding & unit testing phase-frontend, coding & unit testing phase-database/cloud, testing phase. The expected benefits of the EldenCare software include increased medication safety, improved communication between healthcare providers and patients, and improved healthcare outcomes for older adults. EldenCare aims to revolutionise medication management and promote a patient-centered healthcare system by empowering clinical pharmacists and engaging older adults in their care-using technology.

Assessment of Medication Safety Incidents Associated with High-alert Medication Use in Intensive Care Setting: A Clinical Pharmacist Approach.

Background: High-alert medications (HAMs) potentiate heightened risk of causing patient harm ranging from 0.24 to 89.6 errors per 100 prescriptions. High-alert medications are crucially utilized in the intensive care settings (ICUs) due to their excellent potential in delivering therapeutic efficacy, yet these medications could cause severe harm if used inappropriately. Despite the cautious use of these medications, medication safety issues persist, which compromises patient safety. Methods: A prospective interventional study was conducted in ICUs for a period of 6 months. The HAMs were adopted from the Institute for Safe Medication Practices (ISMP) list of HAMs that were used. A suitably designed medication error assessment form was used to capture the necessary data, including demographics, medications, medication error, and the contributing factors. The National Coordinating Council for Medication Error Reporting and Prevention (NCCMERP) index was used to categorize the medication errors (MEs). The error rate was calculated using error rate formula. Continuous variables were expressed as mean ± standard deviation, whereas categorical variables were presented in frequencies and percentages. Results: A total of 165 patients were enrolled during the study period, with 98 (59.4%) being male and 67 (40.6%) female. The majority [54 (32.73%)] of the study participants belonged to the 61-70 age range. A total of 204 MEs were reported, of which [92 (41.5%)] errors were prescribing errors, followed by documentation errors [69 (33.82%)] and administration errors [43 (21.08%)]. The baseline medication error rate was noted to be 160.12/1,000 patient days. Potassium chloride, tramadol, propranolol, aspirin, insulin, and metoprolol were identified as the most common HAMs to cause errors. According to NCC MERP classification, 41.18% were categorized as category B, followed by category C (35.78%). An overall of 666 contributing factors (CFs) were identified for 204 errors. Stress (24.32%) was the most common factor that contributed to the MEs, followed by workload (21.47%). Conclusion: While great strides have been adopted in error prevention, yet the goal of making HAM errors "never" event has not been achieved. Thus, an active surveillance by a clinical pharmacist could support the healthcare team in promoting patient care. How to cite this article: Aradhya PJ, Ravi R, Subhash Chandra BJ, Ramesh M, Chalasani SH. Assessment of Medication Safety Incidents Associated with High-alert Medications Use in Intensive Care Setting: A Clinical Pharmacist Approach. Indian J Crit Care Med 2023;27(12):917-922.

Artificial intelligence in the field of pharmacy practice: A literature review.

Artificial intelligence (AI) is a transformative technology used in various industrial sectors including healthcare. In pharmacy practice, AI has the potential to significantly improve medication management and patient care. This review explores various AI applications in the field of pharmacy practice. The incorporation of AI technologies provides pharmacists with tools and systems that help them make accurate and evidence-based clinical decisions. By using AI algorithms and Machine Learning, pharmacists can analyze a large volume of patient data, including medical records, laboratory results, and medication profiles, aiding them in identifying potential drug-drug interactions, assessing the safety and efficacy of medicines, and making informed recommendations tailored to individual patient requirements. Various AI models have been developed to predict and detect adverse drug events, assist clinical decision support systems with medication-related decisions, automate dispensing processes in community pharmacies, optimize medication dosages, detect drug-drug interactions, improve adherence through smart technologies, detect and prevent medication errors, provide medication therapy management services, and support telemedicine initiatives. By incorporating AI into clinical practice, health care professionals can augment their decision-making processes and provide patients with personalized care. AI allows for greater collaboration between different healthcare services provided to a single patient. For patients, AI may be a useful tool for providing guidance on how and when to take a medication, aiding in patient education, and promoting medication adherence and AI may be used to know how and where to obtain the most cost-effective healthcare and how best to communicate with healthcare professionals, optimize the health monitoring using wearables devices, provide everyday lifestyle and health guidance, and integrate diet and exercise.

Materiovigilance in Intensive Care Units: An Active Surveillance.

Background: Medical devices are the vital part of healthcare system. The use of medical devices is higher in the intensive care units leading to increased exposure rendering the exponential rise in incidence of medical device associated adverse events (MDAEs). Timely detection and reporting of MDAEs can help reduce the disease and associated liabilities. Objective: To determine the rate, patterns, and predictors of MDAEs. Methods: An active surveillance was carried out in the intensive care units (ICUs) of a tertiary care teaching hospital located in southern India. The patients were monitored for MDAEs which were reported based on MvPI guidance document 1.2. The predictors were calculated using an odds ratio at 95% confidence interval. Results: A total of 185 MDAEs were reported amongst 116 patients, of which the majority [74 (63.7%)] were males. Most of the MDAEs were attributed to urethral-catheters [42 (22.7%)] among which a high majority of 34 were associated with urinary tract infections (UTI), followed by ventilators [35 (18.9%)] with all events causing pneumonia. Urethral catheters and ventilators are both classified as categories B and C respectively based on device risk classification provided by the Indian Pharmacopoeia Commission (IPC). Over 58% of MDAEs were reported among the elderly. The causality assessment was possible for 90 (48.6%) MDAEs whereas 86 (46.4%) were probable. The majority of the MDAEs reported were serious [165 (89.2%)] and only [20 (10.8%)] were found to be non-serious on the severity scale. Most [104 (56.2%)] of the devices attributed to MDAEs were single-use devices, of which [103 (55.6%)] were destroyed and only [81 (43.7%)] were retained in healthcare facilities. Conclusions: Despite the best possible care in the intensive care units (ICUs), MDAEs are inevitable, adding to the burden of patients in terms of suffering, disease, extended hospital stay, and increased costs. MDAEs require rigorous monitoring of patients, especially in the elderly population and patients with increased exposure to multiple devices.

Dextromethorphan Induced Dystonia: A Rare Case Report.

Dextromethorphan is a distant derivative of morphine, used as an antitussive agent indicated in standard care for various infections and respiratory conditions ranging from the common cold (rhinoviruses) to severe acute respiratory illness (SARI). Being a derivative of morphine, a natural central nervous system (CNS) depressant, dextromethorphan produces little to no action on CNS when ingested in the prescription dosage. We present a case of a 64-year-old female patient, a known case of ischemic heart disease post angioplasty and stenting to the left anterior descending artery (LAD), with heart failure with reduced ejection fraction (HFrEF), diabetes, hypertension, chronic kidney disease, and hypothyroidism who developed extrapyramidal symptoms post dextromethorphan administration. The incidence of dextromethorphan-induced dystonia is unknown, and the literature review suggests 4 case reports indicating dextromethorphan-induced dystonia, and each of those reports is a case of either accidental overdose or overdose in substance abuse disorder. No cases of these CNS side effects are described among adults with a therapeutic dose of dextromethorphan. This case report serves to sensitize the clinician about this rare occurrence.

Amiodarone-Induced Hyponatremia in An Elderly Patient: A Rare Case Report.

Amiodarone is an antiarrhythmic drug belonging to Vaughan-Williams Class III with additional Class IV effects, which is known to cause many adverse drug reactions (ADRs) necessitating close monitoring. In about 20% of patients, their therapy is discontinued due to adverse effects such as hepatic impairment, thyroid dysfunction, and several pulmonary complications. Although dyselectrolytemia is a common adverse reaction reported with many cardiac medications, the incidence of hyponatremia associated with amiodarone intake is not reported widely in the literature. We are reporting a case of a 73-year-old female patient, with hypertension and ischemic heart disease (IHD) receiving oral amiodarone, presenting with severe hyponatremia, requiring recurrent hospitalization. Amiodarone was found to be responsible after evaluating for the possible causes of hyponatremia. As the incidence of amiodarone-associated hyponatremia is unknown, and not many cases are reported, this case report serves to sensitize the clinician to consider amiodarone-induced hyponatremia as one of the differential diagnoses in cases of unexplained hyponatremia.

Pharmacist-Initiated Medication Error-Reporting and Monitoring Programme in a Developing Country Scenario.

Medication errors (MEs) often prelude guilt and fear in health care professionals (HCPs), thereby resulting in under-reporting and further compromising patient safety. To improve patient safety, we conducted a study on the implementation of a voluntary medication error-reporting and monitoring programme. The ME reporting system was established using the principles based on prospective, voluntary, open, anonymous, and stand-alone surveillance in a tertiary care teaching hospital located in South India. A prospective observational study was carried out for three years and a voluntary Medication Error-reporting Form was developed to report medication errors MEs that had occurred in patients of either sex were included in the study, and the reporters were given the choice to remain anonymous. The analysis was carried out and discussed with HCPs to minimise the recurrence. A total of 1310 medication errors were reported among 20,256 hospitalised patients and the incidence was 6.4%. Common aetiologies were administration errors [501 (38.2%)], followed by prescribing and transcribing errors [363 (28%)]. Root-cause of these MEs were distractions, workload, and communications. Analgesics/antipyretics (19.4%) and antibiotics (15.7%) were the most commonly implicated classes of medications. A clinical pharmacist initiated non-punitive anonymous ME reporting system could improve patient safety.

Towards patient safety: assessment of medication errors in the intensive care unit in a developing country's tertiary care teaching hospital.

OBJECTIVES: To determine the incidence, causes, patterns and outcomes of medication errors (MEs) in the intensive care unit. METHODS: The ME reporting system was established using the principles based on prospective, voluntary, open, anonymous and stand-alone surveillance in a tertiary care teaching hospital located in southern India. MEs involving patients of either sex were included in the study, and the reporters were given the choice to remain anonymous. The analysis was carried out to determine the patterns, causes and outcomes of the reported errors and was discussed with healthcare professionals (HCPs) to minimise the recurrence of MEs. RESULTS: A total of 292 MEs were reported voluntarily among 5137 admitted patients and the incidence of MEs was 5.6%. Administration errors (n=143, 49%) were the most common type of MEs reported followed by prescription errors (n=56, 19%) and dispensing errors (n=43, 15%). Factors responsible for MEs were related to performance deficit of HCPs due to excessive workload, fatigue, unclear interpersonnel communications and patient-related factors, which accounted for 37.6%, 13.1%, 9.6% and 7.7%, respectively. The majority of the reported MEs had an outcome of category C and A, based on the National Coordinating Council for ME Reporting and Prevention (NCC MERP) outcome category scale, amounting to 42.2% and 41.7%, respectively. CONCLUSIONS: Although the majority of MEs that reached the patients did not cause any harm, providing continuous education and awareness of MEs to HCPs and patients may minimise the scope of the factors that may contribute to MEs and improve overall patient safety.