ABSTRACT
Blackground and objective: Virtual healthcare models, usually between healthcare professionals and patients, have developed strongly during the coronavirus disease 2019 (COVID-19) pandemic, but there are not data of models between clinicians. Our objective is to analyse the impact of the COVID-19 pandemic on the activity and health outcomes of the universal e-consultation program for patient referrals between primary care physicians and the Cardiology Department in our area. Methods: Patients with at least one e-consultation between 2018 and 2021 were selected. We analysed the impact of the COVID-19 pandemic on activity and waiting time for care, hospitalizations and mortality, taking as a reference the consultations carried out during 2018. Results: We analysed 25,121 patients. Through logistic regression analysis, it was observed that a shorter delay in care and resolution of the e-consultation without the need for face-to-face care were associated with a better prognosis. The COVID-19 pandemic periods (2019-2020 and 2020-2021) were not associated with worse health outcomes compared to 2018. Conclusions: The results of our study show a significant reduction in e-consult referrals during the first year of the COVID-19 pandemic with a subsequent recovery in the demand for care without the pandemic periods being associated with worse outcomes. The reduction in the time elapsed for solving the e-consult and no need for in-person visit were associated with better outcomes.
ABSTRACT
Background and objective Virtual healthcare models, usually between healthcare professionals and patients, have developed strongly during the coronavirus disease 2019 (COVID-19) pandemic, but there are no data corresponding to models between clinicians. An analysis was made of the impact of the COVID-19 pandemic upon the activity and health outcomes of the universal e-consultation program for patient referrals between primary care physicians and the Cardiology Department in our healthcare area. Methods Patients with at least one e-consultation between 2018 and 2021 were selected. We analyzed the impact of the COVID-19 pandemic upon activity and waiting time for care, hospitalizations and mortality, taking as reference the consultations carried out during 2018. Results A total of 25,121 patients were analyzed. Logistic regression analysis showed a shorter delay in care and resolution of the e-consultation without the need for face-to-face care to be associated to a better prognosis. The COVID-19 pandemic periods (2019–2020 and 2020–2021) were not associated to poorer health outcomes compared to 2018. Conclusions The results of our study show a significant reduction in e-consultation referrals during the first year of the COVID-19 pandemic, with a subsequent recovery in the demand for care, and without the pandemic periods being associated to poorer outcomes. The reduction in time elapsed for resolving the e-consultations and no need for face-to-face visits were associated to improved outcomes.
ABSTRACT
BACKGROUND AND OBJECTIVE: Virtual healthcare models, usually between healthcare professionals and patients, have developed strongly during the coronavirus disease 2019 (COVID-19) pandemic, but there are no data corresponding to models between clinicians. An analysis was made of the impact of the COVID-19 pandemic upon the activity and health outcomes of the universal e-consultation program for patient referrals between primary care physicians and the Cardiology Department in our healthcare area. METHODS: Patients with at least one e-consultation between 2018 and 2021 were selected. We analyzed the impact of the COVID-19 pandemic upon activity and waiting time for care, hospitalizations and mortality, taking as reference the consultations carried out during 2018. RESULTS: A total of 25,121 patients were analyzed. Logistic regression analysis showed a shorter delay in care and resolution of the e-consultation without the need for face-to-face care to be associated to a better prognosis. The COVID-19 pandemic periods (2019-2020 and 2020-2021) were not associated to poorer health outcomes compared to 2018. CONCLUSIONS: The results of our study show a significant reduction in e-consultation referrals during the first year of the COVID-19 pandemic, with a subsequent recovery in the demand for care, and without the pandemic periods being associated to poorer outcomes. The reduction in time elapsed for resolving the e-consultations and no need for face-to-face visits were associated to improved outcomes.
Subject(s)
COVID-19 , Cardiologists , General Practitioners , Remote Consultation , Humans , COVID-19/epidemiology , Pandemics , Referral and ConsultationABSTRACT
Background: Healthcare systems are under prominent stress due to the COVID-19 pandemic. A fast and simple triage is mandatory to screen patients who will benefit from early hospitalization, from those that can be managed as outpatients. There is a lack of all-comers scores, and no score has been proposed for western-world population. Aims: To develop a fast-track risk score valid for every COVID-19 patient at diagnosis. Methods: Single-center, retrospective study based on all the inhabitants of a healthcare area. Logistic regression was used to identify simple and wide-available risk factors for adverse events (death, intensive care admission, invasive mechanical ventilation, bleeding >BARC3, acute renal injury, respiratory insufficiency, myocardial infarction, acute heart failure, pulmonary emboli, or stroke). Results: Of the total healthcare area population, 447.979 inhabitants, 965 patients (0.22%), were diagnosed with COVID-19. A total of 124 patients (12.85%) experienced adverse events. The novel SODA score (based on sex, peripheral O2 saturation, presence of diabetes, and age) demonstrated good accuracy for adverse events prediction (area under ROC curve 0.858, CI: 0.82-0.98). A cut-off value of <2 points identifies patients with low risk (positive predictive value [PPV] for absence of events: 98.9%) and a cut-off of >5 points, high-risk patients (PPV 58.8% for adverse events). Conclusions: This quick and easy score allows fast-track triage at the moment of diagnosis for COVID-19 using four simple variables: age, sex, SpO2, and diabetes. SODA score could improve preventive measures taken at diagnosis in high-risk patients and also relieve resources by identifying very low-risk patients.