4 resultados para prescribing patterns

em Aston University Research Archive


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Objective of the study To determine the extent and nature of unlicensed/off-label prescribing patterns in hospitalised children in Palestine. Setting Four paediatric wards in two public health system hospitals in Palestine [Caritas children’s hospital (Medical and neonatal intensive care units) and Rafidia general hospital (Medical and surgical units)]. Method A prospective survey of drugs administered to infants and children <18 years old was carried out over a five-week period in the four paediatric wards. Main outcome measure Drug-licensing status of all prescriptions was determined according to the Palestinian Registered Product List and the Physician’s Desk Reference. Results Overall, 917 drug prescriptions were administered to 387children. Of all drug prescriptions, 528 (57.5%) were licensed for use in children; 65 (7.1%) were unlicensed; and 324 (35.3%) were used off-label. Of all children, 49.6% received off-label prescriptions, 10.1% received unlicensed medications and 8.2% received both. Seventy-two percent of off-label drugs and 66% of unlicensed drugs were prescribed for children <2 years. Multivariate analysis showed that patients who were admitted to the neonatal intensive care unit and infants aged 0–1 years were most likely to receive a greater number of off-label or unlicensed medications (OR 1.80; 95% CI 1.03–3.59 and OR 1.99; 95% CI 0.88–3.73, respectively). Conclusion The present findings confirmed the elevated prevalence of unlicensed and off-label paediatric drugs use in Palestine and strongly support the need to perform well designed clinical studies in children.

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BACKGROUND: Since 1972, the Australian College of Optometry has worked in partnership with Vision Australia to provide multidisciplinary low-vision care at the Kooyong Low Vision Clinic. In 1999, Wolffsohn and Cochrane reported on the demographic characteristics of patients attending Kooyong. Sixteen years on, the aim of this study is to review the demographics of the Kooyong patient cohort and prescribing patterns. METHODS: Records of all new patients (n = 155) attending the Kooyong Low Vision Clinic for optometry services between April and September 2012 were retrospectively reviewed. RESULTS: Median age was 84.3 years (range 7.7 to 98.1 years) with 59 per cent female. The majority of patients presented with late-onset degenerative pathology, 49 per cent with a primary diagnosis of age-related macular degeneration. Many (47.1 per cent) lived with their families. Mean distance visual acuity was 0.57 ± 0.47 logMAR or approximately 6/24. The median spectacle-corrected near visual acuity was N8 (range N3 to worse than N80). Fifty patients (32.3 per cent) were prescribed new spectacles, 51 (32.9 per cent) low vision aids and five (8.3 per cent) were prescribed electronic magnification devices. Almost two-thirds (63.9 per cent) were referred for occupational therapy management and 12.3 per cent for orientation and mobility services. CONCLUSIONS: The profile of patients presenting for low-vision services at Kooyong is broadly similar to that identified in 1999. Outcomes appear to be similar, aside from an expected increase in electronic devices and technological solutions; however, the nature of services is changing, as treatments for ocular diseases advance and assistive technology develops and becomes more accessible. Alongside the aging population and age-related ocular disease being the predominant cause of low vision in Australia, the health-funding landscape is becoming more restrictive. The challenge for the future will be to provide timely, high-quality care in an economically efficient model.

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Using prescription analyses and questionnaires, the way drug information was used by general medical practitioners during the drug adoption process was studied. Three new drugs were considered; an innovation and two 'me-too' products. The innovation was accepted by general practitioners via a contagion process, information passing among doctors. The 'me-too' preparations were accepted more slowly and by a process which did not include the contagion effect. 'Industrial' information such as direct mail was used more at the 'awareness' stage of the adoption process while 'professional' sources of information such as articles in medical journals were used more to evaluate a new product. It was shown that 'industrial' information was preferred by older single practice doctors who did not specialise, had a first degree only and who did not dispense their own prescriptions. Doctors were divided into early and late-prescribers by using the date they first prescribed the innovatory drug. Their approach to drug information sources was further studied and it was shown that the early-prescriber issued slightly more prescriptions per month, had a larger list size, read fewer journals and generally rated industrial sources of information more highly than late-prescribers. The prescribing habits of three consultant rheumatologists were analysed and compared with those of the general practitioners in the community which they served. Very little association was noted and the influence of the consultant on the prescribing habits of general practitioners was concluded to be low. The consultants influence was suggested to be of two components, active and passive; the active component being the most influential. Journal advertising and advertisement placement were studied for one of the 'me-too' drugs. It was concluded that advertisement placement should be based on the reading patterns of general practitioners and not on ad-hoc data gathered by representatives as was the present practice. A model was proposed relating the 'time to prescribe' a new drug to the variables suggested throughout this work. Four of these variables were shown to be significant. These were, the list size, the medical age of the prescriber, the number of new preparations prescribed in a given time and the number of partners in the practice.

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Background: The Aston Medication Adherence Study was designed to examine non-adherence to prescribed medicines within an inner-city population using general practice (GP) prescribing data. Objective: To examine non-adherence patterns to prescribed oralmedications within three chronic disease states and to compare differences in adherence levels between various patient groups to assist the routine identification of low adherence amongst patients within the Heart of Birmingham teaching Primary Care Trust (HoBtPCT). Setting: Patients within the area covered by HoBtPCT (England) prescribed medication for dyslipidaemia, type-2 diabetes and hypothyroidism, between 2000 and 2010 inclusively. HoBtPCT's population was disproportionately young,with seventy per cent of residents fromBlack and Minority Ethnic groups. Method: Systematic computational analysis of all medication issue data from 76 GP surgeries dichotomised patients into two groups (adherent and non-adherent) for each pharmacotherapeutic agent within the treatment groups. Dichotomised groupings were further analysed by recorded patient demographics to identify predictors of lower adherence levels. Results were compared to an analysis of a self-reportmeasure of adherence [using the Modified Morisky Scale© (MMAS-8)] and clinical value data (cholesterol values) from GP surgery records. Main outcome: Adherence levels for different patient demographics, for patients within specific longterm treatment groups. Results: Analysis within all three groups showed that for patients with the following characteristics, adherence levels were statistically lower than for others; patients: younger than 60 years of age; whose religion is coded as "Islam"; whose ethnicity is coded as one of the Asian groupings or as "Caribbean", "Other Black" and "African"; whose primary language is coded as "Urdu" or "Bengali"; and whose postcodes indicate that they live within the most socioeconomically deprived areas of HoBtPCT. Statistically significant correlations between adherence status and results from the selfreport measure of adherence and of clinical value data analysis were found. Conclusion: Using data fromGP prescribing systems, a computerised tool to calculate individual adherence levels for oral pharmacotherapy for the treatment of diabetes, dyslipidaemia and hypothyroidism has been developed.The tool has been used to establish nonadherence levels within the three treatment groups and the demographic characteristics indicative of lower adherence levels, which in turn will enable the targeting of interventional support within HoBtPCT. © Koninklijke Nederlandse Maatschappij ter bevordering der Pharmacie 2013.