A Cognitive Approach to Refine and Enhance Use of a Dental Diagnostic Terminology

改进和增强牙科诊断术语使用的认知方法

• 批准号: 8511361
• 负责人: Elsbeth Kalenderian
• 金额: $ 68.07万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-15 至 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8511361
• 关键词: Adopted; Adoption; Clinical; Clinical Data; Clinical Research; Cognitive; Collaborations; Communication; Communities; Data; Databases; Dental; Dental Schools; Dentistry; Dentists; Deposition; Development; Diagnosis; Diagnostic; Electronic Health Record; Evaluation; Funding; Goals; Head; Health; Health Status; Informatics; Knowledge; Medical History; Medicine; Methods; Oral health; Outcome; Patients; Positioning Attribute; Procedures; Process; Provider; Quality of Care; Recording of previous events; Registries; Reporting; Research; Schools; Scientific Advances and Accomplishments; Site; System; Terminology; Testing; United States National Library of Medicine; Universities; Visit; base; computer human interaction; data integration; diagnostic accuracy; empowered; health care quality; improved; public health relevance; response; satisfaction; software systems; task analysis

DESCRIPTION (provided by applicant): The advent of the electronic health record (EHR) affords unprecedented clinical research opportunities to improve the nation's health. Dentistry is uniquely positioned to leverage the EHR's power because nearly all U.S. dental schools use the same EHR, axiUm. Twenty dental schools that use axiUm have formed the Consortium for Oral-Health- Related Informatics (COHRI) and have agreed to deposit their data in a common registry. This registry will become the largest ever oral health research database. An important impediment to the consistent integration of these data is the lack of uniformly accepted dental diagnosis terms. COHRI schools have agreed upon a standardized diagnosis terminology, EZcodes, which encompass and expand upon existing diagnosis terminologies. However, to be useful, these terms must be consistently and correctly entered into the EHR. Our preliminary studies show that this is not currently the case and that the diagnostic term entry process in axiUm is inefficient and error-conducive. OBJECTIVE: The goals of this proposal are to increase utilization of diagnosis terms, decrease error rates of term entry, increase provider satisfaction with the entry process, and increase the number of COHRI schools that adopt axiUm's dental diagnosis module. SPECIFIC AIMS: (1) We will identify cognitive and functional impediments to diagnosis entry in the EHR workflow and interface to the dental diagnostic terms. (2) We will make refinements to the EHR workflow and interface to the diagnostic terms, as well as the diagnostic terminology at pilot sites to reduce the cognitive and functional impediments to diagnosis entry in the EHR. (3) We will disseminate and evaluate the adoption of the finalized diagnostic terminology and EHR interface to the diagnostic terms. DESIGN AND METHODS: Headed by the Harvard School of Dental Medicine, four COHRI schools will participate in this effort, two test and two control schools. After an initial evaluation, the two test schools will undergo an iterative cognitively-based EHR and diagnostic term refinement process until a final diagnosis module is created. We will implement the module at the test and control schools and will evaluate the impact of the refinements in terms of achieving our objectives. At a minimum, the four schools within this proposal will adopt the module, where over 80,000 patients make over 250,000 visits per year. Finally, we will disseminate the diagnosis module to all 50 schools that use axiUm, empowering these schools to make efficient diagnosis-based evaluations. PUBLIC HEALTH RELEVANCE: Twenty dental schools have agreed to combine data from their electronic health records (EHRs), which will result in the largest oral health research database ever created. The scope of this effort is limited by the fact that, though they provide the correct treatment, dental clinicians do not enter diagnostic data into the EHR consistently or correctly. In this proposal, we will use human-computer interaction methods to increase dentist satisfaction with the dental diagnosis entry into the EHR, increase how often diagnoses are entered, decrease mistakes made while entering the diagnosis, and increase the number of dental schools that adopt entering dental diagnoses in their EHR.

描述（由申请人提供）：电子健康记录（EHR）的出现为改善国民健康提供了前所未有的临床研究机会。牙科是独特的定位，以利用电子病历的力量，因为几乎所有的美国牙科学校使用相同的电子病历，axiUm。使用axiUm的20所牙科学校已经成立了口腔健康相关信息学联盟（COHRI），并同意将他们的数据存放在一个共同的注册表中。这个登记处将成为有史以来最大的口腔健康研究数据库。对这些数据的一致整合的一个重要障碍是缺乏统一接受的牙科诊断术语。COHRI学校已经同意了一个标准化的诊断术语，EZcodes，它涵盖并扩展了现有的诊断术语。然而，为了有用，这些术语必须一致和正确地输入到电子病历中。我们的初步研究表明，目前情况并非如此，axiUm的诊断术语输入过程效率低下，容易出错。目的：本提案的目标是提高诊断术语的使用率，降低术语输入的错误率，提高提供者对输入过程的满意度，并增加采用axiUm牙科诊断模块的COHRI学校的数量。具体目的：(1)我们将确定在EHR工作流程和牙科诊断术语界面中诊断进入的认知和功能障碍。(2)我们将完善电子病历的工作流程和诊断术语的接口，以及试点地点的诊断术语，以减少在电子病历中诊断输入的认知和功能障碍。(3)我们将传播和评估最终诊断术语和电子病历诊断术语接口的采用情况。设计和方法：以哈佛大学牙科医学院为首，四所COHRI学院将参与这项工作，两所测试学校和两所对照学校。在初步评估之后，两所测试学校将经历一个迭代的基于认知的电子病历和诊断术语改进过程，直到创建最终的诊断模块。我们将在测试和控制学校实施该模块，并根据实现我们的目标来评估改进的影响。至少，该提案中的四所学校将采用该模块，每年有超过80,000名患者进行超过250,000次访问。最后，我们将把诊断模块推广到使用axiUm的所有50所学校，使这些学校能够进行有效的基于诊断的评估。