A Drug Information System Constructed on a Computerized Drug Cart to Help Medication Administrating

• Main Authors: Sung, Hao-Chen Lawrence, 宋浩辰
• Other Authors: 邱泓文
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/15879060797443882117

碩士 === 臺北醫學大學 === 醫學資訊研究所 === 97 === INTRUDUCTION In Taiwan, clinical pharmacy has become more and more important these years, and the pharmacy law had revised that medication care should be pharmacists’ obligation in 2007. However, pharmacists could barely practice medication care for patients, especially inpatients in the present system. Therefore, many hospitals use information technology to fix the situation, so as this thesis. In this study, we designed a system constructed on the computerized drug deliver cart to prevent medication errors in many ways, expecting to reach not only “zero omission”, but also play the clinical pharmacists’ role, and raise patient safety. METHODS Two databases were created to complete the system. The first data source is called “The Integrated Pharmacy Care Database” which was released by the Department of Health (DOH) of Taiwan. The second data source is an “Intravenous Drug Compatibility Database”, the compatibility information were mainly sorted from a textbook called “Handbook on Injectable Drugs” published by American Society of Health-System Pharmacists (ASHP). This database stored information for incompatible drug-drug or drug-solution results. In this study, we constructed three drug-safety information modules, they are drug information module, drug interaction module, and intravenous drug incompatibility module. Delphi language was applied to code the programs of this system. RESULTS We completely constructed three drug-safety information modules including drug information module, drug interaction module, and intravenous drug incompatibility module. We completed a drug information database including 4,408 drug information, and a intravenous drug compatibility database including 1,452 incompatible drug combinations. After the system is completed, we used real patients’ drug data to analyze drug interaction rates, and found that 16.3% of inpatients had drug-drug interaction issues. DISSCUSIONS AND CONCLUSIONS According to the results, we found that it’s necessary to apply decision support functions in different stage of medication therapy to improve patient safety. In this case, a decision support function could play its role on computerized drug deliver cart, as well as administrating stage. However, the drug alert content should be different from stages to fit the present workflow, and the incompatible drug alert function would be more useful if it could also suggest a proper route or dispensing method. These are issues that could be continuously focused in the future.