Medication Delivery Process Research Articles

A Comprehensive Review on Redundancy usage of Animal models in Novel Drug testing

Millions of animals are used for laboratory research and development purposes each year; these living creatures endure suffering before being killed. Animal testing has other drawbacks in addition to bioethical concerns, such as high costs, the need for specialized labor, permission, and time commitment. As a result, Researchers have worked to make several substitute techniques that may replace using animals in tests. These techniques potentially save millions of animals' lives every year, in addition to providing precise findings. In- silico pharmacology methods are used in conjunction with computer and robotics research methodologies to develop alternative techniques for animal experimentation. In this context, several approaches are listed. Certain techniques are just as trustworthy as in-vivo animal models when it comes to precisely predicting the actions of drugs. These substitute techniques also have a number of benefits over using animals in experiments. Given that up to 90% of clinical trials fail, there is rising ethical concern over the use of excessive animals in drug research and development. The non-animal models described in this article have the potential to accelerate the medication delivery process at a faster pace. This review provides researchers and readers who are not aware of about predictive in- silico techniques a basic knowledge of the underlying theory. New advancements, software, acceptability hurdles, integrated techniques, and current applications are all covered, with links to more resources provided for each area. Furthermore, these alternative methods offer a variety of advantages over experimental animals.

Pentetic acid derived dual purpose fluorescent carbon dots for pH responsive drug delivery and antioxidant proficiency

Heteroatom-doped surface-engineered carbon dots provide substantial potential, not only in their fluorescence sensing capabilities but also as nanocarriers for medicinal compounds and in exhibiting antioxidant behaviour. Here we describe a way to make naturally occurring carbon dots (PACDs) utilizing pentetic acid and gelatin in a one-step thermal coupling procedure. Antioxidant activity, biocompatibility, and colloidal stability were all highlighted by the PACDs. In order to assess the PACDs' drug transport capabilities, anticancer model drug molecules were also attached to their surface. Prolonged release patterns were seen in the drug-containing PACDs, indicating that they could be used for controlled drug delivery. Cumulative release data has been fitted into the Higuchi and Weibull models to understand the medication delivery process. The PACDs showed release characteristics that were sensitive to changes in pH; at acidic pH, the release profile could be more precisely controlled (∼28 %) than at alkaline pH (∼59 %). At PACDs concentrations <1 mg/mL, the radical activity is >80 % active; however this activity is greatly affected by the concentration. Because of their low toxicity to living human cell lines, PACDs are an attractive and versatile nano-vector for use in biomedical studies.

Response to COVID-19 Pandemic: Managing Inpatient Pharmacy Services at King Abdulaziz Medical City - Jeddah.

Since early December 2019, the coronavirus disease 2019 (COVID-19) has been relentlessly spread worldwide and has hit the healthcare systems with terrible force. Pharmacists play a vital role in the healthcare system in providing medicines, therapeutics, vaccines, clinical services, and other pharmaceutical care services to patients. Therefore, to ensure all these services continued at King Abdulaziz Medical City - Jeddah during the COVID-19 pandemic, the Department of Pharmaceutical Care initiated a departmental crisis preparedness plan, as a part of general hospital preparedness plan. It started with adjusting medication dosing time, instituting a daily medication refill process, working remotely, expanding the use of automation, and modifying employee schedules. Other actions included the following: handling drug shortages, placing restrictions on some medications, using personal protective equipment, changing routine practices of pharmacy aides, revising the medication delivery process, starting a contingency training program, and restricting pneumatic tube operation. We took guidance from the Ministry of Health, our own institute's experience, World Health Organization recommendations, updated scientific research, and the American Society of Health-System Pharmacists regulatory updates. This article aims to describe how health services, policies, and systems were applied and adapted to address a specific problem while maintaining all pharmacy employees' safety. This article reviews the inpatient pharmacy's particular needs and responses to these needs to meet the COVID-19 pandemic challenges.

Process Risks in Perioperative Medication Delivery

One anesthesia provider is often responsible for prescribing, formulating, dispensing, administering, and documenting medications in the operating room. Unlike other hospital units, there are few safety interventions. Systems engineering approaches can provide important insights into improving patient safety during medication delivery processes (Kaplan et al., 2013; Reid et al., 2005). This study observed anesthesia medication delivery during 20 anesthetic cases in the OR and interviewed 10 anesthesia providers in a large midatlantic academic hospital using a Systems Engineering Initiative for Patient Safety (SEIPS) framework to identify process risk in perioperative medication delivery (Holden et al., 2013). Anesthesia attendings, fellows, residents, and certified resident nurse anesthetists (CRNAs) were sampled based on who was in the OR during observations and who volunteered for interviews. Interviews were transcribed and coded through a consensus procedure. The medication delivery process was described using a SEIPS-based process map. Tasks were separated based on the anesthesia phase, though the tasks and phases are not linear; e.g: a provider may prepare for the next case during the maintenance phase.

PP88 Intravenous Medication Delivery System Cost-Effectiveness Analysis

Introduction:Medication delivery is one of the most common interventions in clinical practice. It requires the direct involvement of nurses and high precision infusion pumps in order to increase the infusion accuracy. Any mistake in the medication delivery process can lead to a medication error, resulting in adverse events with considerable increases in hospital length of stay and cost. Research studies should analyze this area more in emerging countries, as their realities differ from the realities of developed countries, where most of the literature of this area has been developed. This research study analyses this area in Brazil, a leading emerging country. The incorporation of these technologies in health services have caused two major problems: uncertainty around its effectiveness in reducing adverse drug event rates related to infusion dose errors, and the high cost of their inputs. The objective of this study was to analyze the cost-effectiveness of intelligent drug library infusion pumps to reduce adverse drug events during intravenous medication delivery in pediatric and neonatal patients.Methods:Cost-effectiveness was evaluated using a decision-tree framework, considering two scenarios as the base case: the reference one, which uses conventional infusion pumps for intravenous medication delivery with a volume greater than 60 mL, and an alternative one, which uses the drug library infusion pumps. The analysis is with the Unified Health System (Brazil's publicly funded health care system) perspective. The Monte Carlo simulations addressed the uncertainties of the framework. The effectiveness measure was avoidance of adverse drug events.Results:The probabilistic analysis showed the drug library infusion pumps to be more cost-effective than conventional pumps. This ratified what had already been revealed by acceptance curve, which demonstrated that the drug library infusion pumps are more likely to be cost-effective compared to the conventional infusion pumps (with a minimum of the incremental cost-effectiveness of USD 1,501.28).Conclusions:The study demonstrated that the use of the drug library infusion pumps in the pediatric and the neonatal intensive care unit can improve the results of the adverse drug event reduction strategy.

Case Article—A Prescription for Budget Woes at Gracious University Hospital

This case study focuses on pharmacy operations from the standpoint of the chief financial officer for Gracious University Hospital. Her charge was to reduce operational expenses on top of pre-established budget cuts. Her first order of business was to handle inventory of the automated dispensing cabinets (ADCs) located on each floor of the hospital which contains a limited supply of medication supplied by the central pharmacy. In order to develop an effective inventory plan, a tiger team was developed consisting of physicians, patients, nurses, and pharmacists who developed a physical simulation competition between hospital unit floors which focused on the medication delivery process from prescription entry to medication administration. While observing the process, data would be captured and teams would attempt to derive better inventory policies for the medications kept in the ADCs. This case introduces students to healthcare operations by providing background on pharmacy medication delivery systems. The learning objectives of the case and accompanying simulation activity are to (1) explore the challenges of inventory management in healthcare (2) develop and analyze inventory policies based on data collection and observation (3) understand the impact of variability and perishability on inventory management. An electronic companion is available at https://doi.org/10.1287/ited.2016.0159ca .

Entscheidungsunterstützung beim Medikamentenprozess: Wie umfangreich sind die hospINDEX - Stammdaten?

Decision-making support for the drug-order process: How comprehensive is the hospINDEX database? Systems for computerized physician order entry (CPOE) are increasingly enhanced by clinical decision support (CDS) functions in order to reduce errors in the medication delivery process. Therefore, up-to-date and quality-approved drug knowledge databases must be available, including data that is semantically structured and coded in machine-readable form. We analyzed the coverage of the CDS data from a commercially available database (hospINDEX) relative to the drugs administered to inpatients at the University Hospital in Zurich (USZ). The most comprehensive data retrieved was related to allergies and incompatibilities, pregnancy and lactation, as well as maximal doses and alerts in the context of renal and hepatic insufficiency, resulting in a coverage of 31.3% for drug orders and 45.3% for drug administrations. Lower coverage was observed for nutrition interactions, dosage adaption for renal insufficiency, and links to doping lists. Data provided on drug-drug-interactions was quite comprehensive; yet owing to its limited specificity, this functionality was primarily used by consulting pharmacologists, but only infrequently by prescribing physicians. The availability of comprehensive, machine-readable CDS data is gaining increasing relevance in advanced and quality-controlled health care services. There is thus room for improvement in Swiss drug knowledge databases, with data for selected functions only available for approximately half of the administered drugs.

Community Pharmacists in Malaysia: Are They Ready for the Next Leap Forward?

Results: Ninety two patients were included in the study. 7353 drug doses were reviewed. 1563 (21.3%) medication errors were identified. The majority of medication errors identified were documentation errors during administration process (59%). These were followed by errors detected during transcription (15%), dispensing (14%), and prescribing (7%). Five percent of errors were associated with errors in drug distribution and health insurance systems. Pharmacist identified eight incomplete medication histories during medication reconciliation, intercepted 24 dispensing errors and prevented eight administration errors. Conclusions: Pharmacist’s clinical review activities can detect and intercept medication errors during medication delivery process. The success of such activities however requires the collaboration of other healthcare professionals, as well as patients.

Nature and frequency of medication errors in a geriatric ward: an Indonesian experience.

PurposeTo determine the nature and frequency of medication errors during medication delivery processes in a public teaching hospital geriatric ward in Bali, Indonesia.MethodsA 20-week prospective study on medication errors occurring during the medication delivery process was conducted in a geriatric ward in a public teaching hospital in Bali, Indonesia. Participants selected were inpatients aged more than 60 years. Patients were excluded if they had a malignancy, were undergoing surgery, or receiving chemotherapy treatment. The occurrence of medication errors in prescribing, transcribing, dispensing, and administration were detected by the investigator providing in-hospital clinical pharmacy services.ResultsSeven hundred and seventy drug orders and 7,662 drug doses were reviewed as part of the study. There were 1,563 medication errors detected among the 7,662 drug doses reviewed, representing an error rate of 20.4%. Administration errors were the most frequent medication errors identified (59%), followed by transcription errors (15%), dispensing errors (14%), and prescribing errors (7%). Errors in documentation were the most common form of administration errors. Of these errors, 2.4% were classified as potentially serious and 10.3% as potentially significant.ConclusionMedication errors occurred in every stage of the medication delivery process, with administration errors being the most frequent. The majority of errors identified in the administration stage were related to documentation. Provision of in-hospital clinical pharmacy services could potentially play a significant role in detecting and preventing medication errors.

Human Factors Perspectives on a Systemic Approach to Ensuring a Safer Medication Delivery Process

The current, prevailing approach to addressing medication delivery safety issues has been to apply solutions at the point of failure with direct, local remediation. These include computerized physician order entry to address transcription and prescribing problems, tall man lettering for label clarity and smart pump systems to address programming use errors. We discuss the lack of a systemic, holistic approach to addressing medication delivery issues that has led to fragmented solutions that do not address the problem as intended and introduce new, unintended patient safety issues. We use recent case studies in addition to our own experimental data from human factors investigations to show how a comprehensive human factors approach can be applied to address systemic error in medication delivery. Only by identifying how (1) subsystems interconnect, (2) information flows, (3) care providers communicate and (4) users are impacted will healthcare organizations and system vendors be able to fully address error in medication delivery. Much of what is required from organizations is to transcend the organizational boundaries of medicine, pharmacy and nursing to produce a delivery system that ensures an integrated approach that addresses all stakeholders' needs.

Probabilistic Risk Analysis of Medication Error

Over the years, the United States has spent billions of dollars in its quest to improve the quality and safety of health care through the development of new drugs and technologies. Using the probabilistic risk analysis of medication error process, we demonstrate the application of Bayesian Causal Network Model to assess the probabilities of occurrence of rare events related to medication errors. This article summarizes the methodology involved in the process. A convenience sample of annual incident reports from a Northeast acute care community hospital was used for the study. Importance sampling was used to improve the accuracy of estimates of the rare events so that we can better understand the relationship of causes within the reported events. The Bayesian Causal Network Model provided contextual maps of the behaviors and errors that lead to medication delivery process failures, including unanticipated risks associated with actual errors as well as near misses and common deviations from standard procedures and policies. Health care administrators, clinicians, regulators, and educators can prospectively identify and prioritize risk reduction interventions using the Bayesian Causal Network Model. The Bayesian Causal Network Model can identify behavioral and systemic factors that can enhance or reduce the risk of wrong drug, wrong frequency, wrong dose, omitted dose, drug interactions, and wrong patient medication errors in hospitals.

Understanding and reducing the medication delivery waste via systems mapping and analysis

The enormous gaps in the knowledge required to understand medication errors and their related costs (or wastes) in all hospital settings have become a growing national concern. Such gaps are often the major reasons causing risk for patient safety and creating waste to the hospital. However, medication delivery system cannot be successfully improved and implemented without a clear understanding of various process flows running around the entire hospital system. This paper presents a systems mapping and analysis method to help understand and reduce the medication delivery waste. The effectiveness of our method is illustrated by a case study that we conducted for the medication delivery process at Bozeman Deaconess Hospital, MT.

Systems Analysis of Adverse Drug Events

To the Editor. —Groundbreaking though their work is, Dr Bates and colleagues1and Dr Leape and colleagues2may have collectively oversimplified the management tasks for reducing adverse drug events (ADEs). By launching into computerized systems changes without a deeper understanding of medication delivery process stability, they also encourage management decision making that appears contrary to knowledge-based approaches to such matters. Deming's3knowledge-based management theory is grounded in the predictability of organizational systems. Prediction requires stable processes. Neither Bates et al nor Leape et al demonstrated that what was observed was in a Upper Control Limit Average per Week 1989 Weekly Control Chart 1990 Weekly Control Chart Actual weekly process control charts of a corporation's Occupational Safety and Health Administration—reportable injuries for 1989 and 1990. The left side of the Figure shows an unstable system in which nonrandom, assignable causes of variation produced a spike of injuries after