A Standardized Framework for Evaluating Surgical Enhanced Recovery Pathways: A Recommendations Statement from the TDABC in Health-care Consortium.

Background: Innovative methodologies to redesign care delivery are being applied to increase value in health care, including the creation of enhanced recovery pathways (ERPs) for surgical patients. However, there is a lack of standardized methods to evaluate ERP implementation costs. Objectives: This Recommendations Statement aims to introduce a standardized framework to guide the economic evaluation of ERP care-design initiatives, using the Time-Driven Activity-Based Costing (TDABC) methodology. Methods: We provide recommendations on using the proposed framework to support the decision-making processes that incorporate ERPs. Since ERPs are usually composed of activities distributed throughout the patient care pathway, the framework can demonstrate how the TDABC may be a valuable method to evaluate the incremental costs of protocol implementation. Our recommendations are based on the review of available literature and expert opinions of the members of the TDABC in Healthcare Consortium. Results: The ERP framework, composed of 11 steps, was created describing how the techniques and methods can be applied to evaluate the economic impact of an ERP and guide health-care leaders to optimize the decision-making process of incorporating ERPs into health-care settings. Finally, six recommendations are introduced to demonstrate that using the suggested framework could increase value in ERP care-design initiatives by reducing variability in care delivery, educating multidisciplinary teams about value in health, and increasing transparency when managing surgical pathways. Conclusions: Our proposed standardized framework can guide decisions and support measuring improvements in value achieved by incorporating the perioperative redesign protocols.

ABC2-SPH risk score for in-hospital mortality in COVID-19 patients: development, external validation and comparison with other available scores.

OBJECTIVES: The majority of available scores to assess mortality risk of coronavirus disease 2019 (COVID-19) patients in the emergency department have high risk of bias. Therefore, this cohort aimed to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients and to compare this score with other existing ones. METHODS: Consecutive patients (≥ 18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March-July, 2020. The model was validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. RESULTS: Median (25-75th percentile) age of the model-derivation cohort was 60 (48-72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count, and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829-0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833-0.885]) and Spanish (0.894 [95% CI 0.870-0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). CONCLUSIONS: An easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation was designed and validated for early stratification of in-hospital mortality risk of patients with COVID-19.

Clinical characteristics and outcomes of patients hospitalized with COVID-19 in Brazil: Results from the Brazilian COVID-19 registry.

OBJECTIVES: To describe the clinical characteristics, laboratory results, imaging findings, and in-hospital outcomes of COVID-19 patients admitted to Brazilian hospitals. METHODS: A cohort study of laboratory-confirmed COVID-19 patients who were hospitalized from March 2020 to September 2020 in 25 hospitals. Data were collected from medical records using Research Electronic Data Capture (REDCap) tools. A multivariate Poisson regression model was used to assess the risk factors for in-hospital mortality. RESULTS: For a total of 2,054 patients (52.6% male; median age of 58 years), the in-hospital mortality was 22.0%; this rose to 47.6% for those treated in the intensive care unit (ICU). Hypertension (52.9%), diabetes (29.2%), and obesity (17.2%) were the most prevalent comorbidities. Overall, 32.5% required invasive mechanical ventilation, and 12.1% required kidney replacement therapy. Septic shock was observed in 15.0%, nosocomial infection in 13.1%, thromboembolism in 4.1%, and acute heart failure in 3.6%. Age >= 65 years, chronic kidney disease, hypertension, C-reactive protein ≥ 100mg/dL, platelet count < 100×109/L, oxygen saturation < 90%, the need for supplemental oxygen, and invasive mechanical ventilation at admission were independently associated with a higher risk of in-hospital mortality. The overall use of antimicrobials was 87.9%. CONCLUSIONS: This study reveals the characteristics and in-hospital outcomes of hospitalized patients with confirmed COVID-19 in Brazil. Certain easily assessed parameters at hospital admission were independently associated with a higher risk of death. The high frequency of antibiotic use points to an over-use of antimicrobials in COVID-19 patients.