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Background: Medication errors are a prime concern for all in healthcare. As such the use of information technologies in drug prescribing and administration has received considerable attention in recent years, with the hope of improving patient safety. Because of the complexity of drug regimens in renal transplant patients, occurrence of medication errors is inevitable even with a well adopted computerized physician order entering (CPOE) system. Our objective was to quantify medication error type and frequency in an inpatient renal transplant unit. Methods: Systemic evaluation of all medication errors during an initial 10-day audit and a 28-day follow-up audit in an inpatient renal transplant unit. Each error was concurrently evaluated for potential to result in adverse patient consequences (category), error type and associated medication class. Results: A total of 103 clinically significant medication errors were detected during the 10-day (43 errors) and 28-day audit (60 errors) time periods. The most common errors were wrong medication dose ordered and wrong time of drug administration. Thirty-six out of 66 prescribing/ ordering errors reached the patient. Conclusions: Even with utilization of computerized physician order entry system in an inpatient renal transplant unit, post-kidney transplant patients are at risk for adverse outcomes due to medication errors. The risk factors may be multifactorial and will require both organizational and technical approaches to resolve.

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Purpose To assess the quality of the performance of the medication reconciliation process during hospital admission. Methods Subjects were randomized by facility over a 30-day period. Standardized questionnaires were utilized to obtain demographic information, drug allergies, and medication histories. This information was compared with medication reconciliation forms completed upon hospital admission. The primary outcome was the percent of accurate forms completed by the admitting clinician. Secondary outcomes were the accuracy of individual components of the medication order and the time required to accurately reconcile medications. Results One hundred fourteen medication reconciliation forms were audited; over half the subjects were white males with a mean age of 51 years and a median of 7 home medications. Accurate medication reconciliation was documented on 13% of forms. Allergies were consistent among providers in 59% of patients. Of 742 medication orders, the number of inaccuracies was as follows: wrong dose (108, 14.6%), wrong frequency (108, 14.6%), wrong route (54, 7.3%), and wrong medication (25, 3.4%). Omissions (204) and commissions (98) occurred at a rate of 1.79 and 0.86, respectively (114 forms evaluated). The majority of patient/caregiver, outpatient provider, and retail pharmacy interviews required 15 minutes or less to complete. Conclusions Though a national benchmark does not exist for the quality of medication reconciliation performed on hospital admission, there are opportunities to increase the accuracy of medication information obtained during hospital admission.

Quality monitoring of paperboard depends on the measurement of several properties. Part of these properties have online devices to do measurements while another part can only be measured in the laboratory, an activity that sometimes require more time than a production of one entire jumbo roll or generate waste until fix the production. The advantage to use mathematical modeling as the neural networks is the ability to 'predict' online the product final properties through the machine's information such as speed, flow of pulp, coating weight and the quality of fiber as degree of refining and whiteness. One of the properties used for assessing the quality of paperboard is the mottling that describes a marbled appearance on the paperboard surface. Mottling is determined using the method STFI™ Mottling who is characterized by a coefficient of variation of reflectance or standard deviation -defined by the methodology of the equipment. This property when out of parameters affects the quality of the final printed package, giving unsightly appearance. The focus of this study is to determine parameters by mathematical modeling that influence the mottling in order to provide conditions for machine's operators to perform the process, reducing the variation of this property and keep the values inside the specified limits. The model was developed from historical data of 6 months of paperboard machine operation. The results indicated that mottling is mainly influenced by the temperature of the dryer after coating process. Application-Statement: A further understanding of the mechanisms that cause mottling would help to optimize the paperboard quality.