| Summary: | 碩士 === 國立陽明大學 === 生物醫學資訊研究所 === 106 === Background: Pulmonary embolism is a rare disease characterized by nonspecific clinical signs and symptoms ranging from asymptomatic to severe shock or death. Therefore, it is difficult to diagnose and easily overlooked. In emergency department, it is not uncommon that patients with pulmonary embolism treated as other diseases eventually became worse or die. The current diagnosis of pulmonary embolism often relies only on the subjective experience of clinicians. The diagnosis algorithms or risk assessment scoring systems provided by medical guidelines or textbooks are very complicated , difficult to remember and time-consuming. Clinicians often hard to use them. Although they have the value of diagnosis, they are not practical or feasible.
Purpose: This study aims to develop a mobile applications (App) as an adjunct to emergency clinicians in decision-making diagnostic support for pulmonary embolism. To analyze whether this App is feasible to emergency physicians and is useful for decision-making support on the diagnosis of pulmonary embolism.
Research Methods: In view of the popularity of mobile devices, there are many mobile medical applications on the market, but there is no one specifically designed for pulmonary embolism, and the relevant medical Apps are also not symptom-oriented (the doctor's diagnostic thinking process begins from patient’s symptom). Nowadays, we develop a mobile App that integrates risk factors, diagnosis algorithm and risk assessment scoring system of pulmonary embolism with symptoms-oriented approach. The research is divided into three stages: the first is to analyze the need of the App from emergency physicians in medical center when asking them to simulate the App ; the second is the practical application of the App in real emergency environment for the feasibility assessment; Finally, we use the system usability scale (SUS) to analyze the usability of the App.
Findings: In the first stage, the analysis of the simulation showed: 88% of physicians think a tool which integrated diagnostic algorithm and risk assessment scoring system is helpful in the diagnosis of pulmonary embolism, 77% of physicians think this application is easy to use and 64% users can quickly (<6 minutes) use this application for decision making. In the second stage, a total of 48 patients met the symptoms of pulmonary embolism, and finally we enrolled 16 patients in our study. One of enrolled patients was diagnosed pulmonary embolism under our App assisted decision-making. In the third stage, the SUS score of our App is 75.24 (> the average score of 68). It means our App is in good to excellent rating.
Conclusion: The App used in this study has good requirement and availability for emergency clinicians. It is also practical for using the App in real emergency environments and in real patients in Taiwan. It can rapidly support emergency clinical physicians in diagnostic decision of pulmonary embolism, we wish we can continue to assess the actual impact after using the App in the clinical setting in the future.
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