Enhancing Consultation Efficiency Through Medical Informatics: A Scalable Field Clinic Model for the Pandemic Response in Taiwan.

Publication date: Jun 25, 2025

Background: During the COVID-19 pandemic, a high-volume field clinic was rapidly established in Taichung, Taiwan, to manage patients with mild symptoms and reduce hospital burden. To streamline workflow and support timely care, a tailored medical informatics system was developed and implemented midway through clinic operations. Methods: We conducted a retrospective observational study analyzing data from 8287 patients who visited the clinic between 20 May and 4 June 2022. Patients were divided into two groups based on whether they received care before or after the informatics system was introduced (28 May). The primary outcomes included consultation volume, physician workload distribution, and operational efficiency during peak hours. A secondary analysis examined the subgroup receiving antiviral prescriptions. Results: After system implementation, the total number of consultations during peak hours increased significantly (from 138. 6 to 199. 0, a 43. 5% increase; p = 0. 001), along with the average number of consultations per physician (from 12. 3 to 22. 5, an 83% increase; p = 0. 003). Similar trends were observed in the subgroup receiving antiviral therapy, despite the complexity of prescribing decisions. These prescribing trends suggest improved identification of high-risk patients and more timely antiviral initiation, which are critical for reducing disease progression and preventing hospitalization. Conclusions: The integration of a targeted medical informatics system significantly improved consultation efficiency and workload equity in a field clinic setting. This experience highlights a scalable model for digitally enhanced, rapid-response outpatient care during public health emergencies.

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Concepts Keywords
Covid COVID-19
Healthcare electronic health record
June field clinic
Rapidly health informatics
Taiwan public health emergency
workflow optimization

Semantics

Type Source Name
disease MESH COVID-19 pandemic
disease MESH disease progression
disease MESH emergencies
disease MESH infection
drug DRUGBANK Spinosad
drug DRUGBANK Coenzyme M
disease MESH critically ill
drug DRUGBANK Etoperidone
disease IDO site
disease IDO facility
drug DRUGBANK Ritonavir
disease IDO symptom
drug DRUGBANK Methionine
disease IDO history
drug DRUGBANK Oxygen
drug DRUGBANK Medical air

Original Article

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