Using Drug Databases to Assess Prescribing Practices and Continuity of Care

使用药物数据库评估处方实践和护理连续性

基本信息

批准号：
8558112
负责人：
Clement McDonald
金额：
$ 11.15万
依托单位：
NATIONAL LIBRARY OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
资助国家：
美国
起止时间：
至
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/8558112
关键词：
Accident and Emergency department Algorithms Area Asses Behavior Caring Clinical Code Coma Continuity of Patient Care Data Data Analyses Databases Date of birth Disasters District of Columbia Drug Interactions Drug usage Electronics Emergency Care Emergency Situation Frequencies Funding Gender Goals Hospitals Insurance Interruption Intervention Learning Manuals Maps Measures Minor Names Narcotics Nurses Paper Patients Pattern Persons Pharmaceutical Preparations Phase Physicians Process Provider Publications Readiness Recording of previous events Records Reference Standards Reporting Research Secure Source Spottings Terminology Text Time Triage Variant Visit Writing base experience metropolitan older patient routine care suburb

Accident and Emergency department Algorithms Area Asses Behavior Caring Clinical Code Coma Continuity of Patient Care Data Data Analyses Databases Date of birth Disasters District of Columbia Drug Interactions Drug usage Electronics Emergency Care Emergency Situation Frequencies Funding Gender Goals Hospitals Insurance Interruption Intervention Learning Manuals Maps Measures Minor Names Narcotics Nurses Paper Patients Pattern Persons Pharmaceutical Preparations Phase Physicians Process Provider Publications Readiness Recording of previous events Records Reference Standards Reporting Research Secure Source Spottings Terminology Text Time Triage Variant Visit Writing base experience metropolitan older patient routine care suburb

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项目摘要

An accurate medication history is an essential part of patient assessment and can have vital impact on the person's care. However, manually-acquired histories are prone to inaccuracies. The problem is especially serious in emergency care and in disaster situations due to the lack of time, overloaded staff and special patient conditions (e.g. comatose or confused patients, unaccompanied minors or elderly patients). This study is partially funded by the Bethesda Hospitals Emergency Preparedness Partnership. It focuses on patients attended by the Emergency Department (ED) of a regional hospital (Suburban Hospital, Bethesda, MD) and evaluates the potential added value of electronic prescription history information from Surescripts. We established a secure electronic connection between the hospital and Surescripts so that prescription-filling reports could be retrieved from Surescripts in real-time, based on four pieces of patient identifying information (name, date of birth, gender and zip code) obtained from the registration process. For three months we collected the Surescripts information in parallel with the medication history manually acquired by the ED nurse. We also retrieved demographic, administrative (e.g. class of insurance, mode of arrival) and clinical (e.g. vital signs, Glasgow coma score) information from the hospitals database as predictors. All the information was de-identified before being sent to NLM for analysis. This research only involved de-identified data collected for routine care purposes. We conducted the data analysis retrospectively; there was no intervention or patient contact. The ED-collected records of prescriptions were manually typed in by triage nurses, so the drug names were subject to variation and typos. Surescripts data provided standardized names. To make the two sources comparable, we mapped all drugs to their standard names in RxNorm, the U.S. standard reference drug terminology. Mapping was done largely by automatic text matching algorithms followed by manual review of the unmapped items. About two-thirds of all ED patients were registered in the Surescripts database, and for about half of all patients, Surescripts returned some medication history information. We have completed the analysis of this data, and in short, Surescripts provides more complete medication history than the manual history when the Surescripts database has any information about the patient. However, it has no information for about a third of the patients who have medications. The Surescripts information contains drugs that the patient is currently taking but also the full history of prescriptions being filled in the past year. ED providers found the summaries very useful in spotting problematic behaviors (e.g. narcotic drugs abuse, poor drug compliance). We have submitted a paper for publication. With the Surescripts prescription data we obtained in the first phase, we performed preliminary analyses of the number of different prescribers per patient as a measure of care continuity, and it seemed quite high. We have also examined the number of interruptions that physicians would experience due to drug interaction messages under different levels of interaction importance. While doing this analysis, we learned about, and will acquire, a much larger de-identified database of prescriptions covering the entire metropolitan area where the first phase study was done. With this database we will seek to answer many questions about prescribing patterns, including, but not limited to: the degree to which drug interacting pairs written by different providers from different offices would not be seen as an interaction by the provider in either office; the drugs most frequently responsible for drug interactions; the frequency of provider reminder interruptions due to drug interactions under different thresholds for interaction importance, and; providers patterns of prescribing comparing patients who have visited EDs and those who have not.

准确的药物病史是患者评估的重要组成部分，可能对人的护理产生至关重要的影响。但是，手动获得的历史容易出现不准确。由于缺乏时间，员工超负荷和特殊患者状况（例如昏迷或困惑的患者，无人陪伴的未成年人或老年患者），问题在急诊护理和灾难情况下尤为严重。这项研究部分由贝塞斯达医院的紧急准备伙伴关系资助。它重点介绍了一家地区医院（马里兰州贝塞斯达郊区医院）急诊科（ED）出席的患者，并评估了来自监视的电子处方历史信息的潜在附加值。我们建立了医院和监测之间的安全电子连接，以便根据从注册过程中获得的四个患者识别信息（姓名，出生日期，性别和性别代码），可以实时从监视中检索处方报告。在三个月的时间里，我们根据ED护士手动获得的药物病史并行收集了调查信息。我们还从医院数据库中检索了人口统计学，行政（例如，保险类，到达方式）和临床（例如生命体征，格拉斯哥昏迷）信息。所有信息在发送到NLM进行分析之前已被取消识别。这项研究仅涉及用于常规护理目的收集的取消识别数据。我们追溯进行了数据分析。没有干预或患者接触。通过Triage护士手动键入了ED收集的处方记录，因此药物名称会发生差异和错别字。监视数据提供了标准化的名称。为了使这两个来源可比，我们将所有药物映射到其标准名称中，以美国标准参考药物术语为rxnorm。映射很大程度上是通过自动匹配算法进行的，然后是对未覆盖项目的手动审查。所有ED患者中约有三分之二在Surescripts数据库中注册，并且在所有患者中，监测返回了一些药物病史信息。我们已经完成了对这些数据的分析，简而言之，与手动记录相比，当Surescripts数据库具有有关患者的任何信息时，提供了更完整的药物病史。但是，它没有大约三分之一的药物患者的信息。调查信息包含患者目前正在服用的药物，但在过去一年中填写处方的完整历史。 ED提供者发现这些摘要在发现有问题的行为方面非常有用（例如麻醉药物滥用，药物合规性差）。我们提交了一篇论文供出版。通过我们在第一阶段获得的监测处方数据，我们对每位患者不同处方者的数量进行了初步分析，以衡量护理连续性，而且似乎很高。我们还检查了医生在不同级别的相互作用重要性下，医生会遇到的中断数量。在进行此分析的同时，我们了解并将获得一个更大的处方数据库，涵盖了整个大都市地区进行了第一阶段研究。在此数据库中，我们将寻求回答有关开处方模式的许多问题，包括但不限于：由不同办公室的不同提供者编写的药物相互作用对的程度不会被任何办公室的提供者视为互动；这些药物最常见的药物相互作用；提供者提醒提醒中断的频率是由于在不同阈值下的药物相互作用而导致的相互作用重要性的频率，并且；提供者规定比较访问ED的患者和没有的患者的情况。