Walk-In Appointments: An Observational, Cross-Sectional Study of Family Medicine in Central Portugal

无需预约的就诊:葡萄牙中部家庭医学的一项观察性横断面研究

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Abstract

INTRODUCTION: Walk-in appointments (WIA) are intended to respond to acute situations or exacerbations of chronic pathology and are part of the clinical activity of a family doctor. It is necessary to know the reasons that lead patients to resort to this type of consultation and to understand whether these reasons are suitable for it, in accordance with the internal regulations of the two family health units (FHUs), so that we can properly adjust the offer of this kind of appointment or correct mistakes if it isn't being properly used. OBJECTIVES: Our goal was to characterize WIA in two FHUs during the first half of 2022, according to the frequency of reasons for the consultation, diagnosis using ICPC-2, patient referral, and adequacy of this type of appointment in accordance with the internal regulations of each FHU. METHODS: An observational cross-sectional study was performed, whose population was the patients observed in WIA from January to June 2022 in each FHU. Data was collected by a resident doctor in each FHU. An analysis was performed, anonymously, in accordance with the approved protocol. Descriptive and inferential statistics were performed. RESULTS: In a sample of 363 WIA, most patients were women (219 (60.3%)), and the mean age was 47.5 years. The highest number of appointments took place on Tuesdays (80 (22.0%)) and in May (73 (20.1%)). The most frequent reason for consultation was R05 "Cough" (50 (13.8%)), and the most frequently coded assessment was A98 "Health maintenance/prevention" (76 (20.9%)). Of the studied appointments, 144 (39.7%) did not meet the established criteria for this kind of appointment. CONCLUSION: There is a need to invest in health education, so that the public can be made aware of the specific indications for WIA versus a scheduled appointment. It is also crucial to emphasize the importance of complete, clear, and standardized consult notes associated with accurately classifying using ICPC-2.

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