Department of Pediatrics, MedStar Georgetown University Hospital, Washington, DC, USA.
Division of Community Pediatrics, MedStar Georgetown University Hospital, 4200 Wisconsin Ave NW 4th Floor, Washington, DC, 20016, USA.
J Med Syst. 2022 Aug 30;46(10):65. doi: 10.1007/s10916-022-01858-4.
Asthma in childhood is a common and costly chronic disease. Quality asthma care can lead to better control of asthma thus decreasing use of health services. The gold standard for pediatric asthma diagnosis and management is the National Heart, Lung and Blood Institute (NHLBI) guidelines for Diagnosis and Management of Asthma which center on precisely establishing the severity of asthma, as this precise classification delineates appropriate therapy. However, navigating these guidelines is a challenge for primary care providers that creates a barrier to providing quality care. We aim to improve precision in asthma severity classification in the community healthcare setting through the development of an electronic asthma decision support tool (eADST) incorporating NHLBI guidelines embedded within the electronic health record system. We developed an algorithm for the eADST to guide the health care provider to the appropriate classification and subsequent therapy. We engaged our health system's electronic health record informatics team and together developed and revised the tool. We launched the tool in three academic community clinics and measured precision in asthma classification in the twelve months prior to the availability of the tool and the twelve months following the launch. We found a significant improvement in precision of asthma severity classification following the launch, a necessary first step in improvement of asthma care. The next step will be to evaluate the impact of the tool on asthma outcomes.
儿童哮喘是一种常见且昂贵的慢性疾病。高质量的哮喘护理可以更好地控制哮喘，从而减少对卫生服务的使用。儿科哮喘诊断和管理的金标准是美国国立心肺血液研究所（NHLBI）的哮喘诊断和管理指南，该指南侧重于准确确定哮喘的严重程度，因为这种精确分类划定了适当的治疗方法。然而，对于初级保健提供者来说，这些指南是一个挑战，这是提供高质量护理的障碍。我们旨在通过开发电子哮喘决策支持工具（eADST）来提高社区医疗保健环境中哮喘严重程度分类的准确性，该工具将 NHLBI 指南嵌入电子健康记录系统中。我们为 eADST 开发了一个算法，以指导医疗保健提供者进行适当的分类和随后的治疗。我们聘请了我们的医疗系统的电子健康记录信息学团队，共同开发和修订了该工具。我们在三个学术社区诊所推出了该工具，并在工具可用之前的 12 个月和推出后的 12 个月内测量了哮喘分类的准确性。我们发现，在推出该工具后，哮喘严重程度分类的准确性有了显著提高，这是改善哮喘护理的必要的第一步。下一步将评估该工具对哮喘结果的影响。
