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: 8125003
• 负责人: Elsbeth Kalenderian
• 金额: $ 73.35万
• 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/8125003
• 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.

电子健康记录（EHR）的出现为改善国家健康提供了前所未有的临床研究机会。牙科在利用EHR的力量方面处于独特的地位，因为几乎所有的美国牙科学校都使用相同的EHR，axiUm。20所使用axiUm的牙科学校组成了口腔健康相关信息学联盟（COHRI），并同意将其数据存款一个共同的登记处。该注册中心将成为有史以来最大的口腔健康研究数据库。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。中心各学校商定了一个标准化的诊断术语EZcodes，其中包括并扩展了现有的诊断术语。然而，为了有用，这些术语必须一致且正确地输入EHR。我们的初步研究表明，目前情况并非如此，axiUm中的诊断术语输入过程效率低下且容易出错。目的：该提案的目标是提高诊断术语的利用率，降低术语输入的错误率，提高供应商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。具体目标：（1）我们将识别EHR工作流程中诊断条目的认知和功能障碍，并与牙科诊断术语进行接口。(2)我们将改进电子健康记录的工作流程和诊断术语的接口，以及试点的诊断术语，以减少电子健康记录诊断条目的认知和功能障碍。(3)我们将传播和评估采用最终诊断术语和诊断术语的电子健康记录接口。设计和方法：在哈佛牙科医学院的领导下，四所COHRI学校将参与这一努力，两所测试学校和两所对照学校。经过初步评估后，这两所测试学校将经历一个迭代的基于认知的EHR和诊断术语细化过程，直到创建最终的诊断模块。我们将在试验学校和对照学校实施该模块，并将评估改进对实现我们的目标的影响。至少，该提案中的四所学校将采用该模块，每年有超过80 000名患者就诊超过250 000次。最后，我们将向所有50所使用axiUm的学校传播诊断模块，使这些学校能够进行有效的基于诊断的评估。 公共卫生相关性：20所牙科学校已同意将其电子健康记录（EHR）中的数据联合收割机结合起来，这将产生有史以来最大的口腔健康研究数据库。这项工作的范围受到以下事实的限制：尽管牙科医生提供了正确的治疗，但他们并没有一致或正确地将诊断数据输入EHR。在这项提案中，我们将使用人机交互的方法来提高牙医对牙科诊断进入EHR的满意度，增加诊断进入的频率，减少诊断进入时的错误，并增加采用在EHR中输入牙科诊断的牙科学校的数量。