In this study we proposed a new strategy to measure cost-effectiveness of second opinion program on spine surgery, using as measure of effectiveness the minimal important change (MIC) in the quality ...of life reported by patients, including the satisfaction questionnaire regarding the treatment and direct medical costs.
Retrospective analysis of patients with prior indication for spine surgery included in a second opinion program during May 2011 to May 2019. Treatment costs and outcomes were compared considering each patients' recommended treatment before and after the second opinion. Costs were measured under the perspective of the hospital, including hospital stay, surgical room, physician and staff fees and other costs related to hospitalization when surgery was performed and physiotherapy or injection costs when a conservative treatment was recommended. Reoperation costs were also included. For comparison analysis, we used data based on our clinical practice, using data from patients who underwent the same type of surgical procedure as recommended by the first referral. The measure of effectiveness was the percentage of patients who achieved the MIC in quality of life measured by the EQ-5D-3 L 2 years after starting treatment. An incremental cost-effectiveness ratio (ICER) was calculated.
Based upon the assessment of 1,088 patients that completed the entire second opinion process, conservative management was recommended for 662 (60.8%) patients; 49 (4.5%) were recommended to injection and 377 (34.7%) to surgery. Complex spine surgery, as arthrodesis, was recommended by second opinion in only 3.7% of cases. The program resulted in financial savings of -$6,705 per patient associated with appropriate treatment indication, with an incremental effectiveness of 0.077 patients achieving MIC when compared to the first referral, resulting in an ICER of $-87,066 per additional patient achieving the MIC, ranging between $-273,016 and $-41,832.
After 2 years of treatment, the second opinion program demonstrated the potential for cost-offsets associated with improved quality of life.
To determine risk factors for the development of long coronavirus disease 2019 (COVID-19) in healthcare personnel (HCP).
We conducted a case-control study among HCP who had confirmed symptomatic ...COVID-19 working in a Brazilian healthcare system between March 1, 2020, and July 15, 2022. Cases were defined as those having long COVID according to the Centers for Disease Control and Prevention definition. Controls were defined as HCP who had documented COVID-19 but did not develop long COVID. Multiple logistic regression was used to assess the association between exposure variables and long COVID during 180 days of follow-up.
Of 7,051 HCP diagnosed with COVID-19, 1,933 (27.4%) who developed long COVID were compared to 5,118 (72.6%) who did not. The majority of those with long COVID (51.8%) had 3 or more symptoms. Factors associated with the development of long COVID were female sex (OR, 1.21; 95% CI, 1.05-1.39), age (OR, 1.01; 95% CI, 1.00-1.02), and 2 or more SARS-CoV-2 infections (OR, 1.27; 95% CI, 1.07-1.50). Those infected with the SARS-CoV-2 δ (delta) variant (OR, 0.30; 95% CI, 0.17-0.50) or the SARS-CoV-2 o (omicron) variant (OR, 0.49; 95% CI, 0.30-0.78), and those receiving 4 COVID-19 vaccine doses prior to infection (OR, 0.05; 95% CI, 0.01-0.19) were significantly less likely to develop long COVID.
Long COVID can be prevalent among HCP. Acquiring >1 SARS-CoV-2 infection was a major risk factor for long COVID, while maintenance of immunity via vaccination was highly protective.
ABSTRACT Objective This study describes epidemiological and clinical features of patients with confirmed infection by SARS-CoV-2 diagnosed and treated at Hospital Israelita Albert Einstein , which ...admitted the first patients with this condition in Brazil. Methods In this retrospective, single-center study, we included all laboratory confirmed COVID-19 cases at Hospital Israelita Albert Einstein , São Paulo, Brazil, from February until March 2020. Demographic, clinical, laboratory and radiological data were analyzed. Results A total of 510 patients with a confirmed diagnosis of COVID-19 were included in this study. Most patients were male (56.9%) with a mean age of 40 years. A history of a close contact with a positive/suspected case was reported by 61.1% of patients and 34.4% had a history of recent international travel. The most common symptoms upon presentation were fever (67.5%), nasal congestion (42.4%), cough (41.6%) and myalgia/arthralgia (36.3%). Chest computed tomography was performed in 78 (15.3%) patients, and 93.6% of those showed abnormal results. Hospitalization was required for 72 (14%) patients and 20 (27.8%) were admitted to the Intensive Care Unit. Regarding clinical treatment, the most often used medicines were intravenous antibiotics (84.7%), chloroquine (45.8%) and oseltamivir (31.9%). Invasive mechanical ventilation was required by 65% of Intensive Care Unit patients. The mean length of stay was 9 days for all patients (22 and 7 days for patients requiring or not intensive care, respectively). Only one patient (1.38%) died during follow-up. Conclusion These results may be relevant for Brazil and other countries with similar characteristics, which are starting to deal with this pandemic.
Abstract Objective To evaluate the technical notes (TNs) issued by the Center for Technical Support of the Judiciary (Núcleo de Apoio Técnico do Poder Judiciário, NAT-Jus, in Portuguese) of the ...Brazilian Ministry of Justice regarding lawsuits against the Brazilian Unified Health System (Sistema Único de Saúde, SUS, in Portuguese) concerning bladder/ureteral cancer, in order to better advise the formulation of public policies regarding oncologic care. Materials and Methods A cross-sectional study on the TNs issued by NAT-Jus regarding lawsuits from patients against SUS from 2019 to 2023 concerning bladder or ureteral cancer. Results A total of 137 TNs were issued. Most plaintiffs were male patients (70.8%), with a mean age of 69.1 ± 17.6 years. The lawsuits were filed in an attempt to obtain medications (67%), medical care or procedures (26%), or other health products (7%). The most common medications requested were immuno-oncology (IO) therapeutic agents, in 66 cases (pembrolizumab, avelumab, nivolumab, and atezolizumab), followed by the Bacillus Calmette-Guerin (BCG) vaccine (n = 13), chemotherapeutic agents in 5 cases, erdafitinib in 2 cases, and enfortumab vedotin in 1 case. Pembrolizumab was the medication most frequently requested by patients undergoing treatment for bladder or ureteral cancer. Out of more than 50 thousand TNs, there were 1,349 requests for this medication. Bladder or ureteral cancer was responsible for 3.4% of all the demands for pembrolizumab. It is also notable that lawsuits were more common in the Southern (n = 47), followed by the Southeastern (n = 26), Northeastern (n = 20), and Midwestern (n = 6) regions. The lawsuits in the South were more often related to expensive medications. In the Northeast and Midwest, there were proportionally more lawsuits demanding medical procedures. The Brazilian Federal Government lost the lawsuits, representing expenses of BRL 42.1 million with these novel medications within the period evaluated. Conclusion Bladder cancer treatment within SUS faces obstacles and shortages of essential medications. Moreover, advanced and costly therapies are not widely available, straining the public healthcare system and resulting in increasing legal costs. Collaboration among the government, the scientific community, and patient advocacy organizations is crucial to ensure the sustainability of SUS in the face of these challenges.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Developed models to forecast bed occupancy for up to 14 days and monitored errors for 365 days.
Telemedicine calls from COVID-19 patients correlated with the number of patients hospitalized in the next 8 days.
OBJECTIVETo analyze the impact of COVID-19 on emergency department metrics at a large tertiary reference hospital in Brazil. METHODSA retrospective analysis of consecutive emergency department ...visits, from January 1, 2020, to November 21, 2020, was performed and compared to the corresponding time frame in 2018 and 2019. The volume of visits and patients' demographic and clinic characteristics were compared. All medical conditions were included, except confirmed cases of COVID-19. RESULTSA total of 138,138 emergency department visits occurred during the study period, with a statistically significant (p<0.01) reduction by 52% compared to both 2018 and 2019. This decrease was more pronounced for pediatric visits - a drop by 71% in comparison to previous years. Regarding clinical presentation, there was a decrease of severe cases by 34.7% and 37.6%, whereas mild cases decreased by 55.2% and 56.2% when comparing 2020 to 2018 and 2019, respectively. A 30% fall in the total volume of hospital admission from emergency department patients was observed during the study period, but accompanied by a proportional increase in monthly admission rates since April 2020. CONCLUSIONThe COVID-19 pandemic led to a 52% fall in attendance at our emergency department for other conditions, along with a proportional increase in hospital admission rates of COVID-19 patients. Healthcare providers should raise patient awareness not to delay seeking medical treatment of severe conditions that require care at the emergency department.
Robust data comparing long COVID in hospitalized and non-hospitalized patients in middle-income countries are limited.
A retrospective cohort study was conducted in Brazil, including hospitalized and ...non-hospitalized patients. Long COVID was diagnosed at 90-day follow-up using WHO criteria. Demographic and clinical information, including the depression screening scale (PHQ-2) at day 30, was compared between the groups. If the PHQ-2 score is 3 or greater, major depressive disorder is likely. Logistic regression analysis identified predictors and protective factors for long COVID.
A total of 291 hospitalized and 1,118 non-hospitalized patients with COVID-19 were included. The prevalence of long COVID was 47.1% and 49.5%, respectively. Multivariable logistic regression showed female sex (odds ratio OR = 4.50, 95% confidence interval (CI) 2.51-8.37), hypertension (OR = 2.90, 95% CI 1.52-5.69), PHQ-2 > 3 (OR = 6.50, 95% CI 1.68-33.4) and corticosteroid use during hospital stay (OR = 2.43, 95% CI 1.20-5.04) as predictors of long COVID in hospitalized patients, while female sex (OR = 2.52, 95% CI 1.95-3.27) and PHQ-2 > 3 (OR = 3.88, 95% CI 2.52-6.16) were predictors in non-hospitalized patients.
Long COVID was prevalent in both groups. Positive depression screening at day 30 post-infection can predict long COVID. Early screening of depression helps health staff to identify patients at a higher risk of long COVID, allowing an early diagnosis of the condition.
To describe and compare the clinical characteristics and outcomes of patients admitted to intensive care units during the first and second waves of the COVID-19 pandemic.
In this retrospective ...single-center cohort study, data were retrieved from the Epimed Monitor System; all adult patients admitted to the intensive care unit between March 4, 2020, and October 1, 2021, were included in the study. We compared the clinical characteristics and outcomes of patients admitted to the intensive care unit of a quaternary private hospital in São Paulo, Brazil, during the first (May 1, 2020, to August 31, 2020) and second (March 1, 2021, to June 30, 2021) waves of the COVID-19 pandemic.
In total, 1,427 patients with COVID-19 were admitted to the intensive care unit during the first (421 patients) and second (1,006 patients) waves. Compared with the first wave group median (IQR), the second wave group was younger 57 (46-70) versus 67 (52-80) years; p<0.001, had a lower SAPS 3 Score 45 (42-52) versus 49 (43-57); p<0.001, lower SOFA Score on intensive care unit admission 3 (1-6) versus 4 (2-6); p=0.018, lower Charlson Comorbidity Index 0 (0-1) versus 1 (0-2); p<0.001, and were less frequently frail (10.4% versus 18.1%; p<0.001). The second wave group used more noninvasive ventilation (81.3% versus 53.4%; p<0.001) and high-flow nasal cannula (63.2% versus 23.0%; p<0.001) during their intensive care unit stay. The intensive care unit (11.3% versus 10.5%; p=0.696) and in-hospital mortality (12.3% versus 12.1%; p=0.998) rates did not differ between both waves.
In the first and second waves, patients with severe COVID-19 exhibited similar mortality rates and need for invasive organ support, despite the second wave group being younger and less severely ill at the time of intensive care unit admission.
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