Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?

BACKGROUND: Gabaldi et al. utilized telemedicine data, web search trends, hospitalized patient characteristics, and resource usage data to estimate bed occupancy during the COVID-19 pandemic. The results showcase the potential of data-driven strategies to enhance resource allocation decisions for an effective pandemic response. OBJECTIVE: To develop and validate predictive models to estimate the number of COVID-19 patients hospitalized in the intensive care units and general wards of a private not-for-profit hospital in São Paulo, Brazil. METHODS: Two main models were developed. The first model calculated hospital occupation as the difference between predicted COVID-19 patient admissions, transfers between departments, and discharges, estimating admissions based on their weekly moving averages, segmented by general wards and intensive care units. Patient discharge predictions were based on a length of stay predictive model, assessing the clinical characteristics of patients hospitalized with COVID-19, including age group and usage of mechanical ventilation devices. The second model estimated hospital occupation based on the correlation with the number of telemedicine visits by patients diagnosed with COVID-19, utilizing correlational analysis to define the lag that maximized the correlation between the studied series. Both models were monitored for 365 days, from May 20th, 2021, to May 20th, 2022. RESULTS: The first model predicted the number of hospitalized patients by department within an interval of up to 14 days. The second model estimated the total number of hospitalized patients for the following 8 days, considering calls attended by Hospital Israelita Albert Einstein's telemedicine department. Considering the average daily predicted values for the intensive care unit and general ward across a forecast horizon of 8 days, as limited by the second model, the first and second models obtained R² values of 0.900 and 0.996, respectively and mean absolute errors of 8.885 and 2.524 beds, respectively. The performances of both models were monitored using the mean error, mean absolute error, and root mean squared error as a function of the forecast horizon in days. CONCLUSION: The model based on telemedicine use was the most accurate in the current analysis and was used to estimate COVID-19 hospital occupancy 8 days in advance, validating predictions of this nature in similar clinical contexts. The results encourage the expansion of this method to other pathologies, aiming to guarantee the standards of hospital care and conscious consumption of resources. BACKGROUND: Developed models to forecast bed occupancy for up to 14 days and monitored errors for 365 days. BACKGROUND: Telemedicine calls from COVID-19 patients correlated with the number of patients hospitalized in the next 8 days.

Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?

ABSTRACT Objective: To develop and validate predictive models to estimate the number of COVID-19 patients hospitalized in the intensive care units and general wards of a private not-for-profit hospital in São Paulo, Brazil. Methods: Two main models were developed. The first model calculated hospital occupation as the difference between predicted COVID-19 patient admissions, transfers between departments, and discharges, estimating admissions based on their weekly moving averages, segmented by general wards and intensive care units. Patient discharge predictions were based on a length of stay predictive model, assessing the clinical characteristics of patients hospitalized with COVID-19, including age group and usage of mechanical ventilation devices. The second model estimated hospital occupation based on the correlation with the number of telemedicine visits by patients diagnosed with COVID-19, utilizing correlational analysis to define the lag that maximized the correlation between the studied series. Both models were monitored for 365 days, from May 20th, 2021, to May 20th, 2022. Results: The first model predicted the number of hospitalized patients by department within an interval of up to 14 days. The second model estimated the total number of hospitalized patients for the following 8 days, considering calls attended by Hospital Israelita Albert Einstein's telemedicine department. Considering the average daily predicted values for the intensive care unit and general ward across a forecast horizon of 8 days, as limited by the second model, the first and second models obtained R² values of 0.900 and 0.996, respectively and mean absolute errors of 8.885 and 2.524 beds, respectively. The performances of both models were monitored using the mean error, mean absolute error, and root mean squared error as a function of the forecast horizon in days. Conclusion: The model based on telemedicine use was the most accurate in the current analysis and was used to estimate COVID-19 hospital occupancy 8 days in advance, validating predictions of this nature in similar clinical contexts. The results encourage the expansion of this method to other pathologies, aiming to guarantee the standards of hospital care and conscious consumption of resources.

Impact of COVID-19 pandemic on care of oncological patients: experience of a cancer center in a Latin American pandemic epicenter / Impacto da COVID-19 sobre o atendimento de pacientes oncológicos: experiência de um centro oncológico localizado em um epicentro Latino-Americano da pandemia

ABSTRACT Objective Since the rising of coronavirus disease 2019 (COVID-19) pandemic, there is uncertainty regarding the impact of transmission to cancer patients. Evidence on increased severity for patients undergoing antineoplastic treatment is posed against deferring oncologic treatment. We aimed to evaluate the impact of COVID-19 pandemic on patient volumes in a cancer center in an epicenter of the pandemic. Methods Outpatient and inpatient volumes were extracted from electronic health record database. Two intervals were compared: pre-COVID-19 (March to May 2019) and COVID-19 pandemic (March to May 2020) periods. Results The total number of medical appointments declined by 45% in the COVID-19 period, including a 56.2% decrease in new visits. There was a 27.5% reduction in the number of patients undergoing intravenous systemic treatment and a 57.4% decline in initiation of new treatments. Conversely, there was an increase by 309% in new patients undergoing oral chemotherapy regimens and a 5.9% rise in new patients submitted to radiation therapy in the COVID-19 period. There was a 51.2% decline in length of stay and a 60% reduction in the volume of surgical cases during COVID-19. In the stem cell transplant unit, we observed a reduction by 36.5% in length of stay and a 62.5% drop in stem cell transplants. Conclusion A significant decrease in the number of patients undergoing cancer treatment was observed after COVID-19 pandemic. Although this may be partially overcome by alternative therapeutic options, avoiding timely health care due to fear of getting COVID-19 infection might impact on clinical outcomes. Our findings may help support immediate actions to mitigate this hypothesis.

RESUMO Objetivo Desde o surgimento da pandemia da doença pelo coronavírus 2019 (COVID-19), há incerteza quanto ao impacto da transmissão para pacientes com câncer. As evidências sobre o aumento da gravidade para pacientes submetidos a tratamento antineoplásico são contra o adiamento do tratamento oncológico. Nosso objetivo foi avaliar o impacto da pandemia de COVID-19 em volumes de pacientes em um centro oncológico, em um epicentro da pandemia. Métodos Os volumes de pacientes ambulatoriais e de internação foram extraídos do banco de dados de prontuários eletrônicos. Dois intervalos foram comparados: períodos pré-COVID-19 (março a maio de 2019) e pandemia COVID-19 (março a maio de 2020). Resultados O número total de consultas médicas diminuiu 45% no período pandemia COVID-19, inclusive com redução de 56,2% nas novas consultas. Houve redução de 27,5% no número de pacientes em tratamento sistêmico intravenoso e de 57,4% no início de novos tratamentos. Por outro lado, ocorreram aumento de 309% em novos pacientes submetidos a regimes de quimioterapia oral e elevação de 5,9% em novos pacientes submetidos à radioterapia no período pandemia COVID-19. Observaram-se queda de 51,2% nos dias de internação e redução de 60% no volume de casos cirúrgicos durante a COVID-19. Na unidade de transplante de células-tronco, a redução foi de 36,5% nos dias de internação e de 62,5% nos transplantes de células-tronco. Conclusão Foi observado declínio significativo no número de pacientes em tratamento de câncer após a pandemia de COVID-19. Embora isso possa ser parcialmente superado por opções terapêuticas alternativas, evitar cuidados de saúde oportunos devido ao medo de contrair COVID-19 pode impactar nos resultados clínicos. Nossos resultados podem ajudar a apoiar ações imediatas para mitigar essa hipótese.

Impact of COVID-19 pandemic on care of oncological patients: experience of a cancer center in a Latin American pandemic epicenter.

OBJECTIVE: Since the rising of coronavirus disease 2019 (COVID-19) pandemic, there is uncertainty regarding the impact of transmission to cancer patients. Evidence on increased severity for patients undergoing antineoplastic treatment is posed against deferring oncologic treatment. We aimed to evaluate the impact of COVID-19 pandemic on patient volumes in a cancer center in an epicenter of the pandemic. METHODS: Outpatient and inpatient volumes were extracted from electronic health record database. Two intervals were compared: pre-COVID-19 (March to May 2019) and COVID-19 pandemic (March to May 2020) periods. RESULTS: The total number of medical appointments declined by 45% in the COVID-19 period, including a 56.2% decrease in new visits. There was a 27.5% reduction in the number of patients undergoing intravenous systemic treatment and a 57.4% decline in initiation of new treatments. Conversely, there was an increase by 309% in new patients undergoing oral chemotherapy regimens and a 5.9% rise in new patients submitted to radiation therapy in the COVID-19 period. There was a 51.2% decline in length of stay and a 60% reduction in the volume of surgical cases during COVID-19. In the stem cell transplant unit, we observed a reduction by 36.5% in length of stay and a 62.5% drop in stem cell transplants. CONCLUSION: A significant decrease in the number of patients undergoing cancer treatment was observed after COVID-19 pandemic. Although this may be partially overcome by alternative therapeutic options, avoiding timely health care due to fear of getting COVID-19 infection might impact on clinical outcomes. Our findings may help support immediate actions to mitigate this hypothesis.

Georeferencing of deaths from sepsis in the city of São Paulo

Abstract Objective The aim of the present study was to obtain information about deaths due to sepsis in São Paulo from 2004 to 2009 and their relationship with geographical distribution. Methods Causes of death, both main and secondary, were defined according to the codes of the International Classification of Disease version 10 (ICD-10) contained in the database. Sepsis, septic shock, multiple organ failure, pneumonia, urinary tract infection, peritonitis and other intraabdominal infections, skin and soft tissue infections (including surgical wound infection) and meningitis were considered as immediate cause of death or as the condition leading to the immediate cause of death related or associated to sepsis. Results In the analyzed period, there was a 15.3% increase in the absolute number of deaths from sepsis in São Paulo. The mean number of deaths during this period was 28,472 ± 1566. Most deaths due to sepsis and sepsis-related diseases over the studied period occurred in a hospital or health care facility, showing that most of the patients received medical care during the event that led to death. We observed a significant concentration of deaths in the most populous regions, tending more toward the center of the city. Conclusions Georeferencing data from death certificates or other sources can be a powerful tool to uncover regional epidemiological differences between populations. Our study revealed an even distribution of sepsis all over the inhabited areas of São Paulo.

Georeferencing of deaths from sepsis in the city of São Paulo.

OBJECTIVE: The aim of the present study was to obtain information about deaths due to sepsis in São Paulo from 2004 to 2009 and their relationship with geographical distribution. METHODS: Causes of death, both main and secondary, were defined according to the codes of the International Classification of Disease version 10 (ICD-10) contained in the database. Sepsis, septic shock, multiple organ failure, pneumonia, urinary tract infection, peritonitis and other intraabdominal infections, skin and soft tissue infections (including surgical wound infection) and meningitis were considered as immediate cause of death or as the condition leading to the immediate cause of death related or associated to sepsis. RESULTS: In the analyzed period, there was a 15.3% increase in the absolute number of deaths from sepsis in São Paulo. The mean number of deaths during this period was 28,472±1566. Most deaths due to sepsis and sepsis-related diseases over the studied period occurred in a hospital or health care facility, showing that most of the patients received medical care during the event that led to death. We observed a significant concentration of deaths in the most populous regions, tending more toward the center of the city. CONCLUSIONS: Georeferencing data from death certificates or other sources can be a powerful tool to uncover regional epidemiological differences between populations. Our study revealed an even distribution of sepsis all over the inhabited areas of São Paulo.

Temperature variation in the 24 hours before the initial symptoms of stroke.

UNLABELLED: A few studies have performed to evaluate the temperature variation influences over on the stroke rates in Brazil. METHOD: 176 medical records of inpatients were analyzed after having had a stroke between 2004 and 2006 at Hospital Israelita Albert Einstein. The temperature preceding the occurrence of the symptoms was recorded, as well as the temperature 6, 12 and 24 hours before the symptoms in 6 different weather substations, closest to their houses in São Paulo. RESULTS: Strokes occurred more frequently after a variation of 3 C between 6 and 24 hours before the symptoms. There were most hospitalizations between 23-24 C. CONCLUSION: Incidence of stroke on these patients was increased after a variation of 3 masculine Celsius within 24 hours before the ictus. The temperature variations could be an important factor in the occurrence of strokes in this population.

Temperature variation in the 24 hours before the initial symptoms of stroke / Variação da temperatura nas 24 horas anteriores aos sintomas iniciais do acidente vascular cerebral

A few studies have performed to evaluate the temperature variation influences over on the stroke rates in Brazil. METHOD: 176 medical records of inpatients were analyzed after having had a stroke between 2004 and 2006 at Hospital Israelita Albert Einstein. The temperature preceding the occurrence of the symptoms was recorded, as well as the temperature 6, 12 and 24 hours before the symptoms in 6 different weather substations, closest to their houses in São Paulo. RESULTS: Strokes occurred more frequently after a variation of 3ºC between 6 and 24 hours before the symptoms. There were most hospitalizations between 23-24ºC. CONCLUSION: Incidence of stroke on these patients was increased after a variation of 3º Celsius within 24 hours before the ictus. The temperature variations could be an important factor in the occurrence of strokes in this population.

Poucos trabalhos têm estudado a variação sazonal e de temperatura em acidente vascular cerebral (AVC) no Brasil. MÉTODO: Foram analisados 176 registros de pacientes com AVC no Hospital Israelita Albert Einstein entre 2004 e 2006. Foram anotadas as temperaturas ambientes do início dos sintomas, bem como as temperaturas de 6, 12 e 24 horas antes dos sintomas, em 6 diferentes subestações metereológicas mais próximas da casa do paciente em São Paulo. RESULTADOS: Houve aumento da incidência do AVC com a variação de 3ºC entre 6 e 24 horas antes do início dos sintomas. Houve um pico de internação entre 23-24ºC. CONCLUSÃO: A variação de temperatura de 3ºC nas 24 horas que antecederam o início dos sintomas pode ter sido um fator importante na ocorrência do AVC.

Melhoria de desempenho e desfechos (mortalidade) após implementação de um protocolo institucional de atendimento a pacientes sépticos / Improving performance and outcome (mortality) after implementation of a change-bundle approach for management of septic patients

Objetivo: Apesar da existência de diretrizes internacionais baseadasem evidência para o tratamento de pacientes com sepse grave e choque séptico, grande variação existe quanto às características do tratamento oferecido no nível individual. Métodos: Estudo do tipo “antes e depois” foi realizado na unidade de pronto atendimento e no centro de terapia intensiva de um hospital geral, terciário,privado, de 485 leitos. Foram incluídos 160 pacientes (94 na fase “pré-protocolo” e 66 na “pós-protocolo”). Um pacote de intervenções para as seis horas (pacote de ressuscitação) e para as 24 horas do início das disfunções orgânicas (pacote de manutenção) foi utilizado. Indicadores locais foram propostos e avaliados. Desfechos analisados: mortalidade hospitalar, permanência hospitalar e no centro deterapia intensiva, aderência aos pacotes e desempenho em relação aos indicadores. Resultados: Da “fase pré-protocolo” para a “fasepós-protocolo”, o local do diagnóstico mudou do centro de terapia intensiva (52 para 18,2%) para o departamento de emergência (26,6para 40,9%) e alas (17,0 para 36,4%). O número de hemoculturas colhidas antes do início dos antibióticos, o uso de drotrecogina alfa (ativada), o uso de corticóides e a aderência aos pacotes de seis e 24 horas foram significativamente maiores. Houve redução da taxade mortalidade hospitalar (56,4 versus 36,4, p = 0,01). Reduções ainda maiores ocorreram entre os pacientes mais graves (67,7 para 40,7%). Conclusões: A adoção de um protocolo institucional focado na mudança de comportamento, usando ferramentas de melhoria da qualidade, foi capaz de reduzir a mortalidade hospitalar e gerar mudanças de prática na equipe assistencial. Existe crescenteevidência de que a otimização dos processos de atendimento por meio da implementação de protocolos gerenciados direcionados à população com sepse pode reduzir a mortalidade. Por esses motivos, estratégias semelhantes deveriam ser empregadas rotineiramente.

Qualidade Hospitalar - Estudo de caso em hospitais selados pelo CQH - Programa de Controle de Qualidade Hospitalar / Hospital Quality – Case study in hospitals awarded the Hospital Quality Program (CQH) – complice seal

Estudo de caso em nove Hospitais detentores do CQH - Programa de Controle de Qualidade - situados na Região Metropolitana da Grande São Paulo. O objetivo da pesquisa foi descrever o Programa de Qualidade em exercício e caracterizar suas iniciativa e atividades de melhoria de qualidade dentro do contexto organizacional. Foram realizadas entrevistas com "gestores do programa ou comissão de qualidade" baseado em instrumento semi-estruturado e organizado segundo os critérios de excelência do Prêmio Malom Baldrege. Nos Hospitais em estudo, a liderança hospitalar apresentava um papel atuante como idealizador e promotor das atividades do programa. Ainda que seus administradores apresentassem diversas compreensões sobre a conceituação de qualidade e programas de avaliação, a busca pela melhoria de qualidade está presente e modificando a cultura organizacional, em prol de melhores processos e resultados como estratégia de competitividade e satisfação do cliente.