Current Issue : April - June Volume : 2013 Issue Number : 2 Articles : 7 Articles
Background: Limited evidence exists on the effectiveness of external diabetes support provided by diabetes\r\nspecialists and community retail pharmacists to facilitate insulin-prescribing in family practice.\r\nMethods: A stratified, parallel group, randomized control study was conducted in 15 sites across Canada. Family\r\nphysicians received insulin initiation/titration education, a physician-specific ââ?¬Ë?report cardââ?¬â?¢ on the characteristics of\r\ntheir type 2 diabetes (T2DM) population, and a registry of insulin-eligible patients at a workshop. Intervention\r\nphysicians in addition received: (1) diabetes specialist/educator consultation support (active diabetes specialist/\r\neducator consultation support for 2 months [the educator initiated contact every 2 weeks] and passive consultation\r\nsupport for 10 months [family physician initiated as needed]); and (2) community retail pharmacist support (option\r\nto refer patients to the pharmacist(s) for a 1-hour insulin-initiation session). The primary outcome was the insulin\r\nprescribing rate (IPR) per physician defined as the number of insulin starts of insulin-eligible patients during the\r\n12-month strategy.\r\nResults: Consenting, eligible physicians (n = 151) participated with 15 specialist sites and 107 community\r\npharmacists providing the intervention. Most physicians were male (74%), and had an average of 81 patients with\r\nT2DM. Few (9%) routinely initiated patients on insulin. Physicians were randomly allocated to usual care (n = 78) or\r\nthe intervention (n = 73). Intervention physicians had a mean (SE) IPR of 2.28 (0.27) compared to 2.29 (0.25) for\r\ncontrol physicians, with an estimated adjusted RR (95% CI) of 0.99 (0.80 to 1.24), p = 0.96.\r\nConclusions: An insulin support program utilizing diabetes experts and community retail pharmacists to enhance\r\ninsulin prescribing in family practice was not successful. Too few physicians are appropriately intensifying diabetes\r\nmanagement through insulin initiation, and aggressive therapeutic treatment is lacking....
Background: An accurate medication list at hospital admission is essential for the evaluation and further treatment\r\nof patients. The objective of this study was to describe the frequency, type and predictors of errors in medication\r\nhistory, and to evaluate the extent to which standard care corrects these errors.\r\nMethods: A descriptive study was carried out in two medical wards in a Swedish hospital using Lund Integrated\r\nMedicines Management (LIMM)-based medication reconciliation. A clinical pharmacist identified each patient�s\r\nmost accurate pre-admission medication list by conducting a medication reconciliation process shortly after\r\nadmission. This list was then compared with the patient�s medication list in the hospital medical records. Addition\r\nor withdrawal of a drug or changes to the dose or dosage form in the hospital medication list were considered\r\nmedication discrepancies. Medication discrepancies for which no clinical reason could be identified (unintentional\r\nchanges) were considered medication history errors.\r\nResults: The final study population comprised 670 of 818 eligible patients. At least one medication history error\r\nwas identified by pharmacists conducting medication reconciliations for 313 of these patients (47%; 95% CI 43-\r\n51%). The most common medication error was an omitted drug, followed by a wrong dose. Multivariate logistic\r\nregression analysis showed that a higher number of drugs at admission (odds ratio [OR] per 1 drug increase =\r\n1.10; 95% CI 1.06-1.14; p < 0.0001) and the patient living in their own home without any care services (OR = 1.58;\r\n95% CI 1.02-2.45; p = 0.042) were predictors for medication history errors at admission. The results further indicated\r\nthat standard care by non-pharmacist ward staff had partly corrected the errors in affected patients by four days\r\nafter admission, but a considerable proportion of the errors made in the initial medication history at admission\r\nremained undetected by standard care (OR for medication errors detected by pharmacists� medication\r\nreconciliation carried out on days 4-11 compared to days 0-1 = 0.52; 95% CI 0.30-0.91; p=0.021).\r\nConclusions: Clinical pharmacists conducting LIMM-based medication reconciliations have a high potential for\r\ncorrecting errors in medication history for all patients. In an older Swedish population, those prescribed many\r\ndrugs seem to benefit most from admission medication reconciliation....
Background: The potential for unsafe acts to result in harm to patients is constant risks to be managed in any\r\nhealth care delivery system including pharmacies. The number of reported errors is influenced by a various\r\nelements including safety culture. The aim of this study is to investigate a possible relationship between reported\r\ndispensing errors and safety culture, taking into account demographic and pharmacy variables, in Swedish\r\ncommunity pharmacies.\r\nMethods: A cross-sectional study was performed, encompassing 546 (62.8%) of the 870 Swedish community\r\npharmacies. All staff in the pharmacies on December 1st, 2007 were included in the study. To assess safety culture\r\ndomains in the pharmacies, the Safety Attitudes Questionnaire (SAQ) was used. Numbers of dispensed prescription\r\nitems as well as dispensing errors for each pharmacy across the first half year of 2008 were summarised.\r\nIntercorrelations among a number of variables including SAQ survey domains, general properties of the pharmacy,\r\ndemographic characteristics, and dispensing errors were calculated. A negative binomial regression model was used\r\nto further examine the relationship between the variables and dispensing errors.\r\nResults: The first analysis demonstrated a number of significant correlations between reported dispensing errors\r\nand the variables examined. Negative correlations were found with SAQ domains Teamwork Climate, Safety\r\nClimate, Job Satisfaction as well as mean age and response rates. Positive relationships were demonstrated with\r\nStress Recognition (SAQ), number of employees, educational diversity, birth country diversity, education country\r\ndiversity and number of dispensed prescription items. Variables displaying a significant relationship to errors in this\r\nanalysis were included in the regression analysis. When controlling for demographic variables, only Stress\r\nRecognition, mean age, educational diversity and number of dispensed prescription items and employees, were still\r\nassociated with dispensing errors.\r\nConclusion: This study replicated previous work linking safety to errors, but went one step further and controlled\r\nfor a variety of variables. Controlling rendered the relationship between Safety Climate and dispensing insignificant,\r\nwhile the relationship to Stress Recognition remained significant. Variables such as age and education country\r\ndiversity were found also to correlate with reporting behaviour. Further studies on the demographic variables\r\nmight generate interesting results....
Background: As a result of the previous part of this trial, many patients with cardiovascular disease were expected\r\nto receive a statin for the first time. In order to provide these patients with comprehensive information on statins,\r\nas recommended by professional guidance, education at first and second dispensing of statins had to be\r\nimplemented. This study was designed to assess the effectiveness of an intensive implementation program\r\ntargeted at pharmacy project assistants on the frequency of providing education at first dispensing (EAFD) and\r\neducation at second dispensing (EASD) of statins in community pharmacies.\r\nMethods: The participating community pharmacies were clustered on the basis of local collaboration, were\r\nnumbered by a research assistant and subsequently an independent statistician performed a block randomization,\r\nin which the cluster size (number of pharmacies in each cluster) was balanced. The pharmacies in the control\r\ngroup received a written manual on the implementation of EAFD and EASD; the pharmacies in the intervention\r\ngroup received intensive support for the implementation. The impact of the intensive implementation program on\r\nthe implementation process and on the primary outcomes was examined in a random coefficient logistic\r\nregression model, which took into account that patients were grouped within pharmacy clusters.\r\nResults: Of the 37 pharmacies in the intervention group, 17 pharmacies (50%) provided EAFD and 12 pharmacies\r\n(35.3%) provided EASD compared to 14 pharmacies (45.2%, P = 0.715) and 12 pharmacies (38.7%, P = 0.899),\r\nrespectively, of the 34 pharmacies in the control group. In the intervention group a total of 72 of 469 new statin\r\nusers (15.4%) received education and 49 of 393 patients with a second statin prescription (12.5%) compared to 78\r\nof 402 new users (19.4%, P = 0.944) and 35 of 342 patients with a second prescription (10.2%, P = 0.579) in the\r\ncontrol group.\r\nConclusion: The intensive implementation program did not increase the frequency of providing EAFD and EASD\r\nof statins in community pharmacies....
Background: Public pressure has increasingly emphasized the need to ensure the continuing quality of care\r\nprovided by health professionals over their careers. Health profession�s regulatory authorities, mandated to be\r\npublicly accountable for safe and effective care, are revising their quality assurance programs to focus on regular\r\nevaluations of practitioner performance. New methods for routine screening of performance are required and the\r\nuse of administrative data for measuring performance on quality of care indicators has been suggested as one\r\nattractive option. Preliminary studies have shown that community pharmacy claims databases contain the\r\ninformation required to operationalize quality of care indicators. The purpose of this project was to determine the\r\nfeasibility of routine use of information from these databases by regulatory authorities to screen the quality of care\r\nprovided at community pharmacies.\r\nMethods: Information from the Canadian province of Quebec�s medication insurance program provided data on\r\nprescriptions dispensed in 2002 by more than 5000 pharmacists in 1799 community pharmacies. Pharmacy-specific\r\nperformance rates were calculated on four quality of care indicators: two safety indicators (dispensing of contraindicated\r\nbenzodiazepines to seniors and dispensing of nonselective beta-blockers to patients with respiratory\r\ndisease) and two effectiveness indicators (dispensing asthma or hypertension medications to non-compliant\r\npatients). Descriptive statistics were used to summarize performance.\r\nResults: Reliable estimates of performance could be obtained for more than 90% of pharmacies. The average rate\r\nof dispensing was 4.3% (range 0 - 42.5%) for contra-indicated benzodiazepines, 15.2% (range 0 - 100%) for\r\nnonselective beta-blockers to respiratory patients, 10.7% (range 0 - 70%) for hypertension medications to\r\nnoncompliant patients, and 43.3% (0 - 91.6%) for short-acting beta-agonists in over-use situations. There were\r\nmodest correlations in performance across the four indicators. Nine pharmacies (0.5%) performed in the lowest\r\nquartile in all four of the indicators, and 5.3% (n = 95) performed in the lowest quartile on three of four indicators.\r\nConclusions: Routinely collected pharmacy claims data can be used to monitor indicators of the quality of care\r\nprovided in community pharmacies, and may be useful in future to identify underperforming pharmacists, measure\r\nthe impact of policy changes and determine predictors of best practices....
An increase in the health consciousness and to improve quality of life in recent years with some early drug recalls from marketed raising issues by regulatory authorities. The need of an hour insists to establish a grating of legal and humane aspects based Pharmacovigilance (PV) system. Adverse Drug Reactions (ADR) to be the 4th-6th largest cause of death in the USA and are estimated to cause 3-7% of all hospital admissions. PV is a continuous and ongoing process which allows assessing the safety of medicinal product through its life cycle. PV collects, records, codes Adverse Drug Events (ADEs)/ADRs analyses and assesses the reports, promotes the safe use of drugs, creates appropriate structures, and means of communication needed to perform its tasks. The PV in India is a need of an hour because, of increasing trend of outsourced clinical trials and new researches going on in clinical field. India joined the World Health Organization (WHO) Adverse Drug Reaction Monitoring Program based in Uppsala, Sweden. The National Pharmacovigilance Program established in January 2005, was to be overseen by the National Pharmacovigilance Advisory Committee (NPAC) based in the Central Drugs Standard Control Organization (CDSCO), New Delhi was to collate information from all over the country and send it to the Uppsala Monitoring centre in Sweden....
The present study was therefore, undertaken to estimate prevalence of asthma in school going children in Ahmedabad. A total of 1561 children were surveyed comprising of urban (992) and rural population (569) using questionnaire and Pulmonary Function Test. Data of demographic profile, information on allergy, passive smoking exposure, and family history of asthma were collected by questionnaire. Pulmonary Function Test was carried out for assessment of lung function by spirometer. Prevalence of asthma among school going children of Ahmedabad, aged 12 to 17 years is, 4.48%. Gender difference and residential area (rural and urban) are not significantly associated with the prevalence of asthma. Prevalence rates of asthma among school going children with family history of asthma (35.71%), allergy (60%) and passive smoking exposure (41.42%) were significantly higher. (p<0.005) In Ahmedabad population, the prevalence of asthma among school going children of 12 to 17 years is 4.46%. Prevalence of asthma is associated with passive smoking exposure, family history of asthma and allergy. Presence of allergy is the most prominent risk factor for development of asthma....
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