Data-driven, cross-disciplinary collaboration: lessons learned at the largest academic health center in Latin America during the COVID-19 pandemic.

Introduction: The COVID-19 pandemic has prompted global research efforts to reduce infection impact, highlighting the potential of cross-disciplinary collaboration to enhance research quality and efficiency. Methods: At the FMUSP-HC academic health system, we implemented innovative flow management routines for collecting, organizing and analyzing demographic data, COVID-related data and biological materials from over 4,500 patients with confirmed SARS-CoV-2 infection hospitalized from 2020 to 2022. This strategy was mainly planned in three areas: organizing a database with data from the hospitalizations; setting-up a multidisciplinary taskforce to conduct follow-up assessments after discharge; and organizing a biobank. Additionally, a COVID-19 curated collection was created within the institutional digital library of academic papers to map the research output. Results: Over the course of the experience, the possible benefits and challenges of this type of research support approach were identified and discussed, leading to a set of recommended strategies to enhance collaboration within the research institution. Demographic and clinical data from COVID-19 hospitalizations were compiled in a database including adults and a minority of children and adolescents with laboratory confirmed COVID-19, covering 2020-2022, with approximately 350 fields per patient. To date, this database has been used in 16 published studies. Additionally, we assessed 700 adults 6 to 11 months after hospitalization through comprehensive, multidisciplinary in-person evaluations; this database, comprising around 2000 fields per subject, was used in 15 publications. Furthermore, thousands of blood samples collected during the acute phase and follow-up assessments remain stored for future investigations. To date, more than 3,700 aliquots have been used in ongoing research investigating various aspects of COVID-19. Lastly, the mapping of the overall research output revealed that between 2020 and 2022 our academic system produced 1,394 scientific articles on COVID-19. Discussion: Research is a crucial component of an effective epidemic response, and the preparation process should include a well-defined plan for organizing and sharing resources. The initiatives described in the present paper were successful in our aim to foster large-scale research in our institution. Although a single model may not be appropriate for all contexts, cross-disciplinary collaboration and open data sharing should make health research systems more efficient to generate the best evidence.

Telemedicine in Brazil: Teleconsultations at the Largest University Hospital in the Country.

The coronavirus disease (COVID-19) pandemic leveraged telemedicine worldwide mainly due to the need for social distancing, patient safety, and infection prevention. The Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP) was a key reference site in the treatment of COVID-19 severe cases in the country. To continue patient's health care, it became necessary to increase the number of teleconsultations and standardize it institutionally. Herein, we briefly described how the HCFMUSP improved the teleconsultation health care service during the COVID-19 pandemic, highlighting the implementation of important innovations and the throughout standardization process, including patients and professional workflow. We also detailed the methodology used to implement or improve teleconsultation in a medical/multidisciplinary specialty at HCFMUSP. All these efforts made the HCFMUSP reach the goal of converting 15% of all face-to-face consultations into teleconsultations only in 2021. In addition, there were more than 370,000 teleconsultations until the end of 2022. Our experience has shown that having a supporting team, a digital certification process, and the data integration were key factors toward the successful implementation of the teleconsultation services. We believe that progressing toward teleconsultation will improve the population covered by health care services in Brazil, as well as contribute to a reduction of waiting time, and solving costs to health care institutions and patients. We expect this report of our experience in teleconsultation implementation could inspire and guide other health care institutions in the development of telemedicine.

Prediction of intensive care admission and hospital mortality in COVID-19 patients using demographics and baseline laboratory data.

INTRODUCTION: Optimized allocation of medical resources to patients with COVID-19 has been a critical concern since the onset of the pandemic. METHODS: In this retrospective cohort study, the authors used data from a Brazilian tertiary university hospital to explore predictors of Intensive Care Unit (ICU) admission and hospital mortality in patients admitted for COVID-19. Our primary aim was to create and validate prediction scores for use in hospitals and emergency departments to aid clinical decisions and resource allocation. RESULTS: The study cohort included 3,022 participants, of whom 2,485 were admitted to the ICU; 1968 survived, and 1054 died in the hospital. From the complete cohort, 1,496 patients were randomly assigned to the derivation sample and 1,526 to the validation sample. The final scores included age, comorbidities, and baseline laboratory data. The areas under the receiver operating characteristic curves were very similar for the derivation and validation samples. Scores for ICU admission had a 75% accuracy in the validation sample, whereas scores for death had a 77% accuracy in the validation sample. The authors found that including baseline flu-like symptoms in the scores added no significant benefit to their accuracy. Furthermore, our scores were more accurate than the previously published NEWS-2 and 4C Mortality Scores. DISCUSSION AND CONCLUSIONS: The authors developed and validated prognostic scores that use readily available clinical and laboratory information to predict ICU admission and mortality in COVID-19. These scores can become valuable tools to support clinical decisions and improve the allocation of limited health resources.

Prediction of intensive care admission and hospital mortality in COVID-19 patients using demographics and baseline laboratory data

Abstract Introduction: Optimized allocation of medical resources to patients with COVID-19 has been a critical concern since the onset of the pandemic. Methods: In this retrospective cohort study, the authors used data from a Brazilian tertiary university hospital to explore predictors of Intensive Care Unit (ICU) admission and hospital mortality in patients admitted for COVID-19. Our primary aim was to create and validate prediction scores for use in hospitals and emergency departments to aid clinical decisions and resource allocation. Results: The study cohort included 3,022 participants, of whom 2,485 were admitted to the ICU; 1968 survived, and 1054 died in the hospital. From the complete cohort, 1,496 patients were randomly assigned to the derivation sample and 1,526 to the validation sample. The final scores included age, comorbidities, and baseline laboratory data. The areas under the receiver operating characteristic curves were very similar for the derivation and validation samples. Scores for ICU admission had a 75% accuracy in the validation sample, whereas scores for death had a 77% accuracy in the validation sample. The authors found that including baseline flu-like symptoms in the scores added no significant benefit to their accuracy. Furthermore, our scores were more accurate than the previously published NEWS-2 and 4C Mortality Scores. Discussion and conclusions: The authors developed and validated prognostic scores that use readily available clinical and laboratory information to predict ICU admission and mortality in COVID-19. These scores can become valuable tools to support clinical decisions and improve the allocation of limited health resources.

The Impact of Artificial Intelligence on Waiting Time for Medical Care in an Urgent Care Service for COVID-19: Single-Center Prospective Study.

BACKGROUND: To demonstrate the value of implementation of an artificial intelligence solution in health care service, a winning project of the Massachusetts Institute of Technology Hacking Medicine Brazil competition was implemented in an urgent care service for health care professionals at Hospital das Clínicas of the Faculdade de Medicina da Universidade de São Paulo during the COVID-19 pandemic. OBJECTIVE: The aim of this study was to determine the impact of implementation of the digital solution in the urgent care service, assessing the reduction of nonvalue-added activities and its effect on the nurses' time required for screening and the waiting time for patients to receive medical care. METHODS: This was a single-center, comparative, prospective study designed according to the Public Health England guide "Evaluating Digital Products for Health." A total of 38,042 visits were analyzed over 18 months to determine the impact of implementing the digital solution. Medical care registration, health screening, and waiting time for medical care were compared before and after implementation of the digital solution. RESULTS: The digital solution automated 92% of medical care registrations. The time for health screening increased by approximately 16% during the implementation and in the first 3 months after the implementation. The waiting time for medical care after automation with the digital solution was reduced by approximately 12 minutes compared with that required for visits without automation. The total time savings in the 12 months after implementation was estimated to be 2508 hours. CONCLUSIONS: The digital solution was able to reduce nonvalue-added activities, without a substantial impact on health screening, and further saved waiting time for medical care in an urgent care service in Brazil during the COVID-19 pandemic.

Timing to Intubation COVID-19 Patients: Can We Put It Off until Tomorrow?

BACKGROUND: The decision to intubate COVID-19 patients receiving non-invasive respiratory support is challenging, requiring a fine balance between early intubation and risks of invasive mechanical ventilation versus the adverse effects of delaying intubation. This present study analyzes the association between intubation day and mortality in COVID-19 patients. METHODS: We performed a unicentric retrospective cohort study considering all COVID-19 patients consecutively admitted between March 2020 and August 2020 requiring invasive mechanical ventilation. The primary outcome was all-cause mortality within 28 days after intubation, and a Cox model was used to evaluate the effect of time from onset of symptoms to intubation in mortality. RESULTS: A total of 592 (20%) patients of 3020 admitted with COVID-19 were intubated during study period, and 310 patients who were intubated deceased 28 days after intubation. Each additional day between the onset of symptoms and intubation was significantly associated with higher in-hospital death (adjusted hazard ratio, 1.018; 95% CI, 1.005-1.03). CONCLUSION: Among patients infected with SARS-CoV-2 who were intubated and mechanically ventilated, delaying intubation in the course of symptoms may be associated with higher mortality. TRIAL REGISTRATION: The study protocol was approved by the local Ethics Committee (opinion number 3.990.817; CAAE: 30417520.0.0000.0068).

Building an outpatient telemedicine care pilot using Scrum-like framework within a medical residency program.

OBJECTIVES: A good health care does not only depend on good medical practice, but also needs great management of its resources, which are generally short. In this sense, PROAHSA has been training new health managers since 1972. With the arrival of the COVID-19 pandemic, it was clear that medicine will go through a new phase, where telehealth will be present in this "Improved Normal". This report is about how a pilot teleconsultation study was carried out for HCFMUSP patients through the Scrum-like framework. It is to deploy a pilot of remote assistance involving a doctor and a patient in the Ambulatory of Hepatology and Liver Transplantation of HCFMUSP. METHODS: We applied the Scrum-like framework to carry out this work with an interdisciplinary multifunctionality team. RESULTS: A full telemedicine service flow was implemented within eight weeks using existing infrastructure and resources implementing the Scrum methodology. Twenty-three teleconsultations were scheduled and eight guides built. CONCLUSION: Scrum framework has a great potential to improve the training of students and to conclude pilot projects.

Differences in children and adolescents with SARS-CoV-2 infection: a cohort study in a Brazilian tertiary referral hospital

OBJECTIVES: To compare demographic/clinical/laboratory/treatments and outcomes among children and adolescents with laboratory-confirmed coronavirus disease 2019 (COVID-19). METHODS: This was a cross-sectional study that included patients diagnosed with pediatric COVID-19 (aged <18 years) between April 11, 2020 and April 22, 2021. During this period, 102/5,951 (1.7%) of all admissions occurred in neonates, children, and adolescents. Furthermore, 3,962 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection samples were processed in patients aged <18 years, and laboratory-confirmed COVID-19 occurred in 155 (4%) inpatients and outpatients. Six/155 pediatric patients were excluded from the study. Therefore, the final group included 149 children and adolescents (n=97 inpatients and 52 outpatients) with positive SARS-CoV-2 results. RESULTS: The frequencies of sore throat, anosmia, dysgeusia, headache, myalgia, nausea, lymphopenia, pre-existing chronic conditions, immunosuppressive conditions, and autoimmune diseases were significantly reduced in children and adolescents (p<0.05). Likewise, the frequencies of enoxaparin use (p=0.037), current immunosuppressant use (p=0.008), vasoactive agents (p=0.045), arterial hypotension (p<0.001), and shock (p=0.024) were significantly lower in children than in adolescents. Logistic regression analysis showed that adolescents with laboratory-confirmed COVID-19 had increased odds ratios (ORs) for sore throat (OR 13.054; 95% confidence interval [CI] 2.750-61.977; p=0.001), nausea (OR 8.875; 95% CI 1.660-47.446; p=0.011), and lymphopenia (OR 3.575; 95% CI 1.355-9.430; p=0.010), but also had less hospitalizations (OR 0.355; 95% CI 0.138-0.916; p=0.032). The additional logistic regression analysis on patients with preexisting chronic conditions (n=108) showed that death as an outcome was significantly associated with pediatric severe acute respiratory syndrome (SARS) (OR 22.300; 95% CI 2.341-212.421; p=0.007) and multisystem inflammatory syndrome in children (MIS-C) (OR 11.261; 95% CI 1.189-106. 581; p=0.035). CONCLUSIONS: Half of the laboratory-confirmed COVID-19 cases occurred in adolescents. Individuals belonging to this age group had an acute systemic involvement of SARS-CoV-2 infection. Pediatric SARS and MIS-C were the most important factors associated with the mortality rate in pediatric chronic conditions with COVID-19.

Building an outpatient telemedicine care pilot using Scrum-like framework within a medical residency program

OBJECTIVES: A good health care does not only depend on good medical practice, but also needs great management of its resources, which are generally short. In this sense, PROAHSA has been training new health managers since 1972. With the arrival of the COVID-19 pandemic, it was clear that medicine will go through a new phase, where telehealth will be present in this "Improved Normal". This report is about how a pilot teleconsultation study was carried out for HCFMUSP patients through the Scrum-like framework. It is to deploy a pilot of remote assistance involving a doctor and a patient in the Ambulatory of Hepatology and Liver Transplantation of HCFMUSP. METHODS: We applied the Scrum-like framework to carry out this work with an interdisciplinary multifunctionality team. RESULTS: A full telemedicine service flow was implemented within eight weeks using existing infrastructure and resources implementing the Scrum methodology. Twenty-three teleconsultations were scheduled and eight guides built. CONCLUSION: Scrum framework has a great potential to improve the training of students and to conclude pilot projects.

Characteristics and outcomes of patients with COVID-19 admitted to the ICU in a university hospital in São Paulo, Brazil - study protocol

OBJECTIVES: We designed a cohort study to describe characteristics and outcomes of patients with coronavirus disease (COVID-19) admitted to the intensive care unit (ICU) in the largest public hospital in Sao Paulo, Brazil, as Latin America becomes the epicenter of the pandemic. METHODS: This is the protocol for a study being conducted at an academic hospital in Brazil with 300 adult ICU beds dedicated to COVID-19 patients. We will include adult patients admitted to the ICU with suspected or confirmed COVID-19 during the study period. The main outcome is ICU survival at 28 days. Data will be collected prospectively and retrospectively by trained investigators from the hospital's electronic medical records, using an electronic data capture tool. We will collect data on demographics, comorbidities, severity of disease, and laboratorial test results at admission. Information on the need for advanced life support and ventilator parameters will be collected during ICU stay. Patients will be followed up for 28 days in the ICU and 60 days in the hospital. We will plot Kaplan-Meier curves to estimate ICU and hospital survival and perform survival analysis using the Cox proportional hazards model to identify the main risk factors for mortality. ClinicalTrials.gov: NCT04378582. RESULTS: We expect to include a large sample of patients with COVID-19 admitted to the ICU and to be able to provide data on admission characteristics, use of advanced life support, ICU survival at 28 days, and hospital survival at 60 days. CONCLUSIONS: This study will provide epidemiological data about critically ill patients with COVID-19 in Brazil, which could inform health policy and resource allocation in low- and middle-income countries.