172 research outputs found

    Extemporaneous indomethacin oral suspension prepared from injectable ampoules for therapy in premature infants and paediatric patients

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    Indomethacin (IND) is used for off-label prescription for the treatment of patent ductus arteriosus (PDA) in premature infants. In Argentina, IND is only available as a suppository, dermic cream, injectable ampoules, and delayed-release capsules. Aiming to improve paediatric treatment and minimise the risk associated with improper dosage, this work focused on the development of an extemporaneous 0.2% IND oral suspension, starting from the commercially injectable formulation. Two 150mL batches of suspension were prepared using GRAS excipients. The suspensions were stored for 17 days at room temperature. Physical stability, morphological analysis of suspended particles, sedimentation volume, easy re-suspension, and dynamic viscosity were studied. The IND content, dissolution studies and microbiological attributes of non-sterile pharmaceutical products were also evaluated. After 17 days of storage, the suspension was easily re-dispersed after 15 s of simple hand-shaking. There were no detectable changes in colour, odour, and/or flavour. The suspension showed minimal changes in pH, viscosity, shape, and mean size of the suspended IND particles. The content uniformity and drug dissolution remained within the acceptable range during storage. This oral liquid suspension is an interesting alternative to be prepared by hospital pharmacy services for optimising the paediatric treatment of PDA.Fil: de Lafuente, Yanina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica; ArgentinaFil: García, Mónica Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica; ArgentinaFil: Jimenez Kairuz, Alvaro Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Unidad de Investigación y Desarrollo en Tecnología Farmacéutica; Argentin

    Future Supply of Medical Radioisotopes for the UK Report 2014

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    The UK has no research nuclear reactors and relies on the importation of 99Mo and other medical radioisotopes (e.g. Iodine-131) from overseas (excluding PET radioisotopes). The UK is therefore vulnerable not only to global shortages, but to problems with shipping and importation of the products. In this context Professor Erika Denton UK national Clinical Director for Diagnostics requested that the British Nuclear Medicine Society lead a working group with stakeholders including representatives from the Science & Technology Facilities Council (STFC) to prepare a report. The group had a first meeting on 10 April 2013 followed by a working group meeting with presentations on 9th September 2013 where the scope of the work required to produce a report was agreed. The objectives of the report are: to describe the status of the use of medical radioisotopes in the UK; to anticipate the potential impact of shortages for the UK; to assess potential alternative avenues of medical radioisotope production for the UK market; and to explore ways of mitigating the impact of medical radioisotopes on patient care pathways. The report incorporates details of a visit to the Cyclotron Facilities at Edmonton, Alberta and at TRIUMF, Vancouver BC in Canada by members of the report team.Comment: 121 page

    Operations Research Frameworks for Improving Make-Ahead Drug Policies at Outpatient Chemotherapy Infusion Centers

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    Outpatient chemotherapy infusion is one of the most common forms of treatment used to cure, control, and ease symptoms of cancer. Patients who require outpatient chemotherapy infusion undergo lengthy and physically demanding infusion sessions over the course of their treatment. While the frequency and duration of visits vary by patient, drug, and cancer type, most patients will require several treatments over the course of months or years to complete their regimen/treat their disease. Receiving infusion is just one part of the complex treatment process. Patients may have their blood work done, wait for the results to process, visit their oncologist, wait on their order to be placed by their oncologist and prepared by the pharmacy, and then have the infusion administered by infusion clinic staff. Each step introduces randomness which can lead to propagated delays. These delays negatively affect patients as well as clinical operation cost and staff workload. We focus on optimizing drug preparation at the pharmacy to reduce patient delays. Drugs can be prepared the morning before patients arrive to prevent the patient from waiting the additional time needed to prepare their prescribed drugs in addition to any other wait time incurred during peak pharmacy hours. However, patients scheduled for outpatient chemotherapy infusion sometimes may need to cancel at the last minute even after arriving for their appointment (i.e. patient may be deemed too ill to receive treatment). This results in the health system incurring waste cost if the drug was made ahead since the drugs are patient specific and have a short shelf life. Infusion centers must implement policies to balance this potential waste cost with the time savings for their patients and staff. In support of this effort, this dissertation focuses on methods and strategies to improve the process flow of chemotherapy infusion outpatients by optimizing pharmacy make-ahead policies. We propose using three different methods which build upon each other. First we develop a predictive model which utilizes patient-specific data to estimate the probability that a patient will defer or not show for treatment on a given day. Generally, the ability to generate high-quality predictions of patient deferrals can be highly valuable in managing clinical operations, such as scheduling patients, determining which drugs to make before patients arrive, and establishing the proper staffing for a given day. We also introduce how the patient-specific probability of deferral can help determine a ``general rule of thumb" policy for what should be made ahead on a given day. Next we utilize these probabilities in two integer programming models. These multi-criteria optimization models prioritize which and how many drugs to make ahead given a fixed window of time. This is done with the dual objectives of reducing the expected waste cost as well as the expected value of reduced patient waiting time. Lastly, we utilize simulation to better quantify the impact of our proposed policies. We show that making chemotherapy drugs ahead of an infusion appointment not only benefit the patient they are prescribed for but also subsequent patients due to the decrease load (i.e., reduced blocking) on the pharmacy system as a whole. Each method utilizes electronic medical record data from the University of Michigan Rogel Cancer Center (UMRCC) but may be generalized to any cancer center infusion clinic.PHDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/151706/1/donalric_1.pdfDescription of donalric_1.pdf : Restricted to UM users only

    Multiobjective and Robust Optimization in Pharmacy Delivery and Emergency Department Nurse Staffing

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    Over the past 20 years, hospitals have seen a drastic improvement in patient service with improved patient recovery times, faster delivery of care, and an increased focus on patient safety. In addition, healthcare has also began to focus on its staffing, making efforts to improve staff satisfaction. Despite these advancements, healthcare spending has continued increasing. The objectives of cost, staff satisfaction, and patient safety do not always align. In addition, in the healthcare sector demand is frequently unknown, compounding the difficulty in solving these problems. This dissertation provides deterministic and robust optimization models to solve the pharmacy distribution problem and the emergency department nurse staffing problem. Pharmacy distribution is one area of the healthcare system which has seen an increase in technology to improve patient safety and help facilitate distributing medication from the central pharmacy to the patient. Pharmacy robots are used to pick medication cost effectively in the central pharmacy while automated dispensing cabinets (ADCs) are point-of-use storage maintained on the inpatient units. These technologies have provided the ability to deliver medication more cost effectively and improve patient safety. However, the two technologies are often implemented independently of each other and therefore may not work cohesively within the distribution process. This dissertation presents a model which focuses on the trade-off between cost and patient safety. The model is solved to minimize the total distribution system cost, including purchasing and maintenance of technology, as well as minimizing the total distribution workload cost. A robust model is formulated and solved to account for the variation in medication demand and determine the effect variation has on planning decisions. Emergency departments treat patients with various illnesses which results in a wide range of complexities in determining staffing. Patient demand varies by the day of the week and the hour of the day. This results in difficulty determining the daily staffing levels necessary to treat patients efficiently while also considering available staffing resources. This dissertation provides a basic model which determines the daily staffing levels for an emergency department based on predetermined staffing levels. This model is expanded by determining staffing levels in the presence of understaffing by assessing nurse to patient ratios. Several additional models are introduced which consider the variation in patient demand that occurs daily. The performance of these models is considered across a calendar year by comparing the results with current patient safety standards and in comparison with each other to determine the best method to determine nurse staffing levels in the presence of variable demand and understaffing

    Improving Healthcare Logistics Processes

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    Continuing professional development - challenge for professional organization

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    Professions, as one of key sectors of social systems, bear a leading role in the existing social work organization. Free professions take up a special place and significance, all the way from Roman artes liberales to our times. Pharmaceutical profession, as one of the oldest, led by ethical principles, is regulated by postulates accepted by the profession members, and in modern times established through legislations. Typical determinants of the regulated professions, which also refer to pharmacists, as chamber members, are as follows: following ethical principles, specific skills and knowledge, professional development, autonomy at work, continuing improvement, competencies development, professional associations, licensing

    Radiopharmaceuticals

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    Radiopharmaceuticals - Current Research for Better Diagnosis and Therapy discusses the importance of radiopharmaceuticals and their environmental, pharmaceutical, diagnostic, therapeutic, and research applications. Chapters address such topics as the fundamentals of radiopharmaceutical chemistry and preparation, fabrication, materials manipulation, and characterization of radiopharmaceuticals, applications of radiopharmaceuticals in preclinical studies, radiopharmaceuticals in modern cancer therapy, and new trends in preparation, biodistribution, and pharmacokinetics of radiopharmaceuticals in diagnosis and research
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