Introduction Patient blood management (PBM), an evidence-based, patient-centred approach for optimising blood health, faces significant implementation challenges despite regulatory support, and this study explores its adoption within a Portuguese hospital to enhance education, develop tailored protocols and address healthcare system complexities, thereby contributing a unique perspective to the global discourse on PBM in Portuguese-speaking countries. This study will evaluate the clinical outcomes and cost-effectiveness of implementing a PBM programme in elective surgical patients at a tertiary Portuguese hospital, with secondary objectives focusing on preoperative anaemia prevalence and aetiology, PBM protocol adherence, transfusion practices guided by viscoelastic tests and the impact of cell salvage techniques. Methods A baseline evaluation will be conducted in 2018, and postintervention assessments will follow from 2019 to 2024. The control group comprised patients who underwent selected elective surgeries—including cardiac, general, orthopaedic, urological and gynaecological procedures—during 2018 without exposure to targeted PBM interventions. The intervention group consisted of patients scheduled for the same elective surgeries, who were referred for preanaesthesia evaluation to identify the need for PBM interventions. These interventions, where indicated, were implemented during the preoperative phase and extended to the intraoperative and postoperative periods to ensure a comprehensive and standardised approach to PBM application. Data will be extracted from pseudoanonymised medical records, ensuring full compliance with ethical standards and data protection regulations. Statistical analyses will be performed using robust methods suitable for categorical and continuous variables, enabling the evaluation of temporal trends and the overall effectiveness of PBM interventions in improving clinical outcomes. Ethics and dissemination Our research has been ethically approved by the Vila Nova de Gaia/Espinho Hospital Centre’s Ethical Health Committee (approval number 196/2023–1). We plan to disseminate our findings through posters, lectures at conferences and in scientific journals.

Background/Objectives: Postoperative complications following adult cardiac surgery are biologically interrelated, yet most machine learning models predict single outcomes. We developed an explainable multi-output model integrating routinely collected clinical variables and patient blood management (PBM) biomarkers to predict multiple postoperative outcomes simultaneously, with complementary mono-output analyses for selected endpoints. Methods: This retrospective single-center cohort included 1414 adults undergoing cardiac surgery. In total, 513 complete cases were analyzed. Thirteen outcomes were modeled, including major binary complications and ICU/ward length of stay. An initial 80:20 train–test split was used only for algorithm screening across six candidate multi-output regressors and training-set-defined feature subsets. The selected regressor was then evaluated across five random states, and global permutation feature importance was used for multi-output explainability. Mono-output binary analyses using the selected regressor and the same training-set-only feature-selection workflow were evaluated along with accuracy, precision, recall/sensitivity, and F1-scores. Results: The Decision Tree Regressor was selected. Across five random states, global multi-output performance was R² = 0.83, MSE = 1.296, RMSE = 1.132, MAE = 0.298, and MAPE = 0.128. Based on global multi-output permutation importance, creatinine, ferritin, platelet count, estimated glomerular filtration rate, preoperative red blood cell units, and EuroSCORE II were ranked the highest. Atrial fibrillation had the lowest mono-output F1-score (0.719), whereas acute kidney injury, postoperative bleeding, infection, and 1-year hospital readmission yielded F1-scores of 0.928, 0.970, 0.963, and 0.975, respectively. Conclusions: This proof-of-concept study shows the feasibility of explainable multi-output modeling for postoperative outcomes after adult cardiac surgery using clinical and PBM variables. However, external validation is required prior to clinical use.

BACKGROUND: Patient blood management (PBM) has been shown to improve patient outcomes and optimise resource use. However, the systematic collection and analysis of patient-reported outcome measures (PROMs) remains challenging, limiting their integration into PBM pathways and into value-based healthcare (VBHC) strategies. OBJECTIVE(S): This study aims to evaluate the feasibility and adherence to an automated VBHC digital tool for PROMs collection in a population of cardiac surgical patients, within the context of PBM implementation. DESIGN: A single-centre, pragmatic, prospective feasibility study. SETTING: A tertiary Portuguese hospital considering data from 1 March to 6 September 2024. A total of 12 professionals were actively involved in the patient journey design. PATIENTS: A total of 221 patients (65.2% men, mean age 66.7 ± 9.9 years) with a scheduled cardiothoracic surgery were included. Main outcome measures: Percentage of planned interactions successfully completed. RESULTS: A two-phase digital PROMs journey was implemented in less than 2 months. A total of 638 interactions were completed by 221 patients, resulting in a global completion proportion of 72.1%. 36-Item Short Form Survey Instrument (SF-36) and BPI questionnaires, completed by 77% of patients, results at 90 days compared to results at initial evaluation (SF-36 physical: t = -0.424, P = 0.681; mental: Z = 33.0, P = 1.000; Brief Pain Inventory (BPI) Pain Severity and Interference: Z = 23.0, P = 0.646). The PHQ-9, completed by 76% of patients, identified five severe and nine moderately severe depression cases. Educational content had a 73.9% reading completion proportion across 303 views. CONCLUSIONS: We showed the feasibility of implementing a digital tool to monitor patient PROMs, along with its adoption by patients and health professionals. This strategy has the potential to contribute to improving healthcare professionals’ motivation, access to real-world data, personalised monitoring, and allowing for faster implementation of corrective actions, with an impact on patients’ outcomes and costs.

Background/Objectives: Preoperative anemia and iron deficiency increase transfusion risk in cardiac surgery. We evaluated outcomes associated with a Patient Blood Management (PBM) pathway and assessed the robustness of these associations to baseline imbalance and secular trends. Methods: This single-center retrospective cohort study compared PBM patients treated in 2019, 2022, and 2023 with historical controls from 2017–2018. Outcomes included red blood cell (RBC) transfusion, length of stay, readmission, mortality, safety events, and costs. Analyses included multivariable regression, propensity-score matching (PSM), inverse probability of treatment weighting (IPTW), and adjacent-period matching. The hospital-perspective cost-consequence analysis used 2024-unit costs, bootstrap confidence intervals (CI), and log-link models. Results: Among 1374 patients (764 PBM; 610 No-PBM controls), any RBC transfusion occurred in 17.3% versus 39.2%, and transfusion of >2 units occurred in 2.6% versus 15.1%. The adjusted odds ratios were 0.30 (95% CI, 0.23–0.39) and 0.14 (95% CI, 0.08–0.24), respectively. PSM yielded 519 pairs, and sensitivity analyses were concordant. The adjusted overall direct-cost ratio was 0.75 (95% CI, 0.68–0.82), with an adjusted marginal mean difference of −EUR 5196 (bootstrap 95% CI, −EUR 6965 to −EUR 3485). Recorded incidences of myocardial infarction, stroke, thromboembolism, and cumulative infection were low and did not differ significantly between cohorts; hypophosphatemia and treatment-specific adverse reactions were not systematically assessed. Adjacent-period matching did not confirm a reduction in 12-month readmission, and mortality was similar between cohorts. Conclusions: PBM was associated with lower transfusion rates, shorter hospitalization, and lower direct costs. Residual temporal confounding limits causal interpretation, and the economic findings do not constitute formal cost-effectiveness results.