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Asthma electronic medical records in primary care: an integrative review
Janice P Minard1, Scott E Turcotte, M Diane Lougheed
1Department of Medicine, Division of Respirology, Queen's University, Kingston, Ontario, Canada. minardj@KGH.KARI.NET
Background:
Quality management, evaluation, and surveillance of asthma may be enhanced by access to and utilization of an asthma electronic medical record (EMR) in primary care.
Purpose:
To describe the current status, support tools, and utility of asthma EMRs in primary care.
Methods:
An integrative review of the literature published between 1996 and 2008 was completed using Ovid MEDLINE, EMBASE, and CINAHL databases. Key search terms included asthma, medical records, computerized, primary health care, primary care, family physician, family practice, chronic disease, COPD, neoplasm, diabetes mellitus, and cardiovascular disease. Articles related to concepts, systems in development, and sources such as acute care and pharmacy EMRs were excluded. Each article was reviewed by two reviewers.
Results:
Of 309 articles identified, 76 met the inclusion criteria. Twenty-two percent were specific to asthma, 78% pertained to other chronic diseases and/or the overall status of an EMR in primary care. The literature varied in methodology, topics of discussion and value of data. Articles describing an asthma EMR most often reported on decision support tools (n = 3) and/or utility (n = 14), specifically the ability to predict mortality and assess severity and timeliness of diagnosis. A primary care EMR containing a validated asthma minimum data set was not found. Three themes emerged from the review: status (description of users, functionalities and adoption issues), tools (decision support tools to enhance knowledge uptake), and utility (data quality, extraction and outcomes).
Conclusions:
There is a paucity of asthma elements in EMRs in primary care, with the exception of discussion of decision support tools and utility. Integration of a more robust asthma EMR in primary care, including a minimum data set, standardized terminology, and validated indicators, may further enhance care and enable outcomes monitoring.
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Clinical Assessment for Asthma:
This is the first step in diagnosing and managing asthma. It includes:
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Asthma is classified as allergic and non-allergic. Allergens such as dust mites, pollen, and pet dander trigger allergic asthma, while factors like cold air, intense emotions, or exercise can induce non-allergic asthma.
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Asthma-II: Pathophysiology and Classification
Additionally, environmental and genetic factors play crucial roles in determining an individual's susceptibility to asthma and the severity of their condition.
Critical processes in asthma pathophysiology include:
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