Parvaneh Afshar1, Benyamin Mohseni Saravi2, Ebrahim Nehmati3, Ebrahim Bagherian Farahabbadi4, Azadeh Yazdanian5, Hasan Siamian6, Mohammad Vahedi7. 1. Reference laboratory, Mazandaran University of Medical Sciences, Sari, Mazandaran, Iran. 2. Health information Management Office, Mazandaran University of Medical Sciences, Sari, Mazandaran, Iran. 3. Microbiology laboratory of Boo Ali Sina Hospital, Mazandaran University of Medical Sciences, Sari, Mazandaran, Iran. 4. Statistics & mathematics Department, Islamic Azad University, Sari Branch, Sari, Mazandaran, Iran. 5. Health information Technology Department, Mazandaran University of Medical Sciences, Sari, Mazandaran, Iran. 6. Health information Management, Mazandaran University of Medical Sciences, Sari, Mazandaran, Iran. 7. Microbiology Department, Mazandaran University of Medical Sciences, Mazandaran, Sari, Iran.
Abstract
INTRODUCTION: One of the issues in health care delivery system is resistance to antibiotics. Many researches were done to show the causes and antibiotics which was resistance. In most researches the methods of classifying and reporting this resistance were made by researcher, so in this research we examined the International Classification of Diseases 10 the edition (ICD-10). METHODS AND MATERIALS: This is a descriptive cross section study; data was collected from laboratory of Boo Ali Sina hospital, during 2011-2012. The check list was designed according the aim of study. Variables were age, bacterial agent, specimen, and antibiotics. The bacteria and resistance were classified with ICD-10. The data were analyzed with SPSS (16) soft ware and the descriptive statistics. RESULTS: Results showed that of the 10198 request for culture and antibiogram, there were 1020(10%) resistance. The specimen were 648 (63.5%) urine, blood 127(12.5%), other secretion 125 (12/3%), sputum 102 (10%), lumbar puncture 8 (0/8%), stool 6 (6/0%) and bone marrow 4 (0.4%). The E coli was the most 413 (40.5%) resistance cause to antibiotics which was coded with B96.2 and the most resistance was to multiple antibiotics 885(86.8%) with the U88 code. CONCLUSION: The results showed that by using the ICD-10 codes, the study of multiple causes and resistance is possible. The routine usage of coding of the ICD-10 would result to an up to date bank of resistance to antibiotics in every hospitals and useful for physicians, other health care, and health administrations.
INTRODUCTION: One of the issues in health care delivery system is resistance to antibiotics. Many researches were done to show the causes and antibiotics which was resistance. In most researches the methods of classifying and reporting this resistance were made by researcher, so in this research we examined the International Classification of Diseases 10 the edition (ICD-10). METHODS AND MATERIALS: This is a descriptive cross section study; data was collected from laboratory of Boo Ali Sina hospital, during 2011-2012. The check list was designed according the aim of study. Variables were age, bacterial agent, specimen, and antibiotics. The bacteria and resistance were classified with ICD-10. The data were analyzed with SPSS (16) soft ware and the descriptive statistics. RESULTS: Results showed that of the 10198 request for culture and antibiogram, there were 1020(10%) resistance. The specimen were 648 (63.5%) urine, blood 127(12.5%), other secretion 125 (12/3%), sputum 102 (10%), lumbar puncture 8 (0/8%), stool 6 (6/0%) and bone marrow 4 (0.4%). The E coli was the most 413 (40.5%) resistance cause to antibiotics which was coded with B96.2 and the most resistance was to multiple antibiotics 885(86.8%) with the U88 code. CONCLUSION: The results showed that by using the ICD-10 codes, the study of multiple causes and resistance is possible. The routine usage of coding of the ICD-10 would result to an up to date bank of resistance to antibiotics in every hospitals and useful for physicians, other health care, and health administrations.
Authors: M Opatowski; P Tuppin; K Cosker; M Touat; G De Lagasnerie; D Guillemot; J Salomon; C Brun-Buisson; L Watier Journal: Epidemiol Infect Date: 2019-01 Impact factor: 2.451