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COMPUTER ASSISTED PATIENT INTERVIEWING IN CLINICAL PHARMACY

COMPUTER ASSISTED PATIENT INTERVIEWING IN CLINICAL PHARMACY
临床药学中计算机辅助患者会诊
批准号:
3838530
负责人:
J M DELEO
金额:
$0.0万
依托单位国家:
美国
项目类别:
财政年份:
--
资助国家:
美国
项目状态:
未结题
起止时间:

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英文摘要
As clinical pharmacists become more involved in direct patient care by dispensing medication information and helping to identify potential drug interaction-induced health hazards, they must keep abreast of new drug information, allocate more one-on-one time for patients, and maintain effective interviewing skills. In support of these activities, CSL began a collaboration in 1990 with the NIH Clinical Center Pharmacy Department. The objective was to develop a computer interviewing system that collects medication histories, dispenses medication information to patients, and detects possible untoward events related to medication regimens, thereby making more pharmacist time available for patients who are not candidates for computer interviewing. Warnings generated by this system could aid in focusing the pharmacist-patient interaction. The initial version of the medication history system developed, tested, and reported in FY91, included system interview scripts for patient demographics, health history, and drug usage. A concise summary report is produced after the interview. In FY92 the interview scripts and adverse drug reaction (ADR) thesaurus were refined and a comprehensive report describing ADR's sorted by body systems was prepared and submitted to USP to assist in standardizing future ADR terminology. Database modules were designed to support adverse drug reaction and drug-drug interaction detection and programs were created for patient drug information and physician drug monitoring information retrieval. Also, a neural network module for adverse drug reaction detection was developed that demonstrated improvement over a previous multi-level system evaluation scheme. Completion and integration of all program modules and database components, and initiation of formal testing and evaluation of the completed system are planned for FY93.
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BREAST CANCER PATIENT SURVIVAL PREDICTION--A NEURAL NETWORK APPROACH
AUDITORY BRAINSTEM RESPONSE (ABR) ANALYSIS AND INTERPRETATION EXPERT SYSTEM
BREAST CANCER PATIENT SURVIVAL PREDICTION--A NEURAL NETWORK APPROACH
COMPUTER ASSISTED PATIENT INTERVIEWING IN CLINICAL PHARMACY