Root cause analysis of medication errors at a multi-specialty hospital in Western India

Background: Medication use is a complex process in a medical setting, it starts with physician prescribing, followed by nurse transcribing, pharmacist dispensing, medication administration, and patient monitoring. There is a definite role of clinical pharmacists in reduction of Medication errors by examining and evaluating its causes and communicate the results to physicians and caregivers. The aim of the present study was study of medication errors for the safety & the health benefit of the patient visiting multi specialty hospital. Methods: The Observational study was carried out at in-patient appointments at multi specialty hospital during the period of June 2012 to April 2013 at Baroda. Results: Total of 300 patients were observed out of which medication error has occurred in 117 (39%) cases considering 62% were males & 38% female patients. Out of 117 cases 28% of transcription errors, 62% of prescription errors, 11% of dispensing errors & 16 % Administration errors. 51% of medication errors were occurring in the age group of 40-60. Root cause analysis showed that prescription error was due to Illegible handwriting, No dosage form prescribed, the Wrong Brand name prescribed; transcription error due to Wrong drug is transcribed; administrative error due to Wrong dose is administered, Drug administered through wrong route, Wrong drug is administered while dispensing error due to Urgent dispensation not done within 10 to 15 minutes, Wrong dose dispensed.Conclusion: Most common medication errors were Prescription error & Transcription error which accounts for almost 77% of the total error, which is according to Pareto 80:20 Principle

Detection of Pecan Weevil Larvae in Pecan Nutmeat Using Multispectral Imaging System

This project utilizes multispectral imaging techniques to detect and identify pecan weevil larvae in pecan nutmeat. Diffuse reflectance measurements were obtained for weevil larvae and pecan nutmeat using a VIS/NIR spectrometer. PCA and derivative analysis were performed to identify the spectral wavelengths that best differentiated pecan nutmeat from larvae. The four potential wavelengths in the spectral range of silicon CCD were identified as 855nm, 902nm, 940nm and 981 nm. The images were acquired with a NIR enhanced camera. The images acquired at 980nm showed significant gray scale contrast between pecan nutmeat and larvae. These images were then processed using masking and morphological processing. This method was compared to a novel active contour based image segmentation algorithm. The contour based algorithm produced much better segmentation results and should be used instead of simple masking operation. Classification accuracy of 84% was obtained for the training images and 74% for the testing images.Biosystems and Agricultural Engineerin