Health in a Virtual Environment (HIVE): A Novel Continuous Remote Monitoring Service for Inpatient Management.

The aim of this study was to describe the implementation of a novel 50-bed continuous remote monitoring service for high-risk acute inpatients treated in non-critical wards, known as Health in a Virtual Environment (HIVE). We report the initial results, presenting the number and type of patients connected to the service, and assess key outcomes from this cohort. This was a prospective, observational study of characteristics and outcomes of patients connected to the HIVE continuous monitoring service at a major tertiary hospital and a smaller public hospital in Western Australia between January 2021 and June 2023. In the first two and a half years following implementation, 7541 patients were connected to HIVE for a total of 331,118 h. Overall, these patients had a median length of stay of 5 days (IQR 2, 10), 11.0% (n = 833) had an intensive care unit admission, 22.4% (n = 1691) had an all-cause emergency readmission within 28 days from hospital discharge, and 2.2% (n = 167) died in hospital. Conclusions: Our initial results show promise, demonstrating that this innovative approach to inpatient care can be successfully implemented to monitor high-risk patients in medical and surgical wards. Future studies will investigate the effectiveness of the program by comparing patients receiving HIVE supported care to comparable patients receiving routine care.

Transfusion strategy trials excluding patients transfused outside the trial study period are more likely to report a trend favoring restrictive strategies: a meta-analysis.

OBJECTIVES: Some large, randomized trials investigating red cell transfusion strategies have significant numbers of transfusions administered outside the trial study period. We sought to investigate the potential impact of this methodological issue. STUDY DESIGN AND SETTING: Meta-analysis of randomized controlled trials (RCTs) comparing liberal vs restrictive transfusion strategies in cardiac surgery and acute myocardial infarction patients. The outcome of interest was 30-day or in-hospital mortality. RESULTS: In cardiac surgery, the pooled risk ratio for mortality was 0.83 (95% confidence interval [CI] 0.62-1.12, P = .22) times lower in the restrictive group when compared to the liberal group in trials applying a transfusion strategy throughout the patient's entire perioperative period, and 1.33 (95% CI 0.84-2.11, P = .22) times higher in the restrictive group in trials not applying transfusion strategies throughout the entire perioperative period. When combined, the risk ratio for mortality was 0.98 (95% CI 0.73-1.32, P = .89). In patients with acute myocardial infarction, the risk ratio for mortality was 0.72 (95% CI 0.40-1.28, P = .26) times lower in the restrictive group when compared to the liberal group in 1 trial excluding patients administered the intervention prerandomization and 1.19 (95% CI 0.96-1.47, P = .11) times higher in the restrictive group in 1 trial including patients receiving the intervention prerandomization. When combined the risk ratio for mortality was 1.00 (0.62-1.59, P = .99). CONCLUSION: Though not statistically significant, there was a consistent difference in trends between RCTs administering significant numbers of transfusion outside the trial study period compared to those that did not. The implications of our results may extend to RCTs in other settings that ignore if and how frequently an investigated therapy is administered outside the trial window.

A further update on mortality and morbidity in patients with very low hemoglobin levels who decline blood transfusion.

BACKGROUND: In the past two decades, researchers have published mortality and morbidity rates in patients with very low hemoglobin levels declining blood transfusion. The clinical knowledge and tools available for the management of patients who decline transfusions have grown since these publications. The aim of our study was to provide a further update on outcomes associated with severe anemia in these patients. STUDY DESIGN AND METHODS: A retrospective observational study of patients declining allogeneic blood transfusions with nadir hemoglobin levels ≤8 g/dL treated at The Institute for Blood Management, HELIOS Klinikum Gotha, Germany. Outcomes were in-hospital mortality within 30 days and composite morbidity or mortality, with morbidity events defined as acute myocardial infarction, cardiac failure, wound infection, arrhythmia, and pneumonia. RESULTS: Between June 2008 and June 2021, The Institute for Blood Management treated 2841 admissions of which 159 (5.6%) recorded nadir hemoglobin levels ≤8 g/dL. Of these, five (3.1%) patients died in hospital within 30 days, including four (4.8%) patients admitted for surgical procedures and one (1.4%) medical admission. There was a significant increase in the unadjusted proportion of composite morbidity or mortality events with severity of nadir hemoglobin, with each gram decrease in hemoglobin associated with a 1.48 (95% confidence interval = 1.05-2.09; p = .025) times increase. CONCLUSION: Our comparatively lower proportion of patients reaching hemoglobin levels ≤8 g/dL and lower mortality rates suggest outcomes in patients with severe anemia is modifiable with the application of current patient blood management and bloodless medicine and surgery strategies.

Data and Metrics for Patient Blood Management: A Narrative Review and Practical Guide.

Data collection, analysis, and reporting are fundamental for a successful hospital-based patient blood management program; however, very little has been published on the topic. Our aim was to synthesize evidence from a literature review to provide a detailed, practical list of outcome metrics, and the required data collection(s) to inform implementation. Ovid MEDLINE and PubMed were searched for any full-text original research articles published from inception to the year 2020. We included any studies reporting the implementation of interventions or programs study authors defined as "patient blood management" and extracted information on data collected and metrics reported. We included 45 studies describing the implementation of a patient blood management program and/or strategies. The outcomes reported by these studies were grouped into 1 of 36 metrics. We compiled a list of 65 relevant data elements to collect, and their potential source hospital information systems: patient administration, laboratory, transfusion/blood bank, operating room, pharmacy, emergency department, and intensive care unit. We further categorized patient blood management data systems into basic, intermediate, and advanced based on the combination of different information systems sourced. The results of this review can be used to inform patient blood management programs in planning what data collection(s) are needed, where these data can be sourced from, and how they can be analyzed.

Penny-wise and pound-foolish: the challenges of preoperative anaemia management.

The timely correction of anaemia before major surgery is important for optimising perioperative patient outcomes. However, multiple barriers have precluded the global expansion of preoperative anaemia treatment programmes, including misconceptions about the true cost/benefit ratio for patient care and health system economics. Institutional investment and buy-in from stakeholders could lead to significant cost savings through avoided complications of anaemia and red blood cell transfusions, and through containment of direct and variable costs of blood bank laboratories. In some health systems, billing for iron infusions could generate revenue and promote growth of treatment programmes. The aim of this work is to galvanise integrated health systems worldwide to diagnose and treat anaemia before major surgery.

Multivariable statistical models to predict red cell transfusion in elective surgery.

BACKGROUND: Predicting red cell transfusion may assist in identifying those most likely to benefit from patient blood management strategies. Our objective was to identify a simple statistical model to predict transfusion in elective surgery from routinely available data. MATERIALS AND METHODS: Our final multicentre cohort consisted of 42,546 patients and contained the following potential predictors of red cell transfusion known prior to admission: patient age, sex, pre-admission hemoglobin, surgical procedure, and comorbidities. Missing data were handled by multiple imputation methods. The outcome measure of interest was administration of a red cell transfusion. We used multivariable logistic regression models to predict transfusion, and evaluated the performance by applying a 10-fold cross-validation. Model accuracy was assessed by comparing the area under the receiver operating characteristics curve. After applying an optimal probability cut-off we measured model accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. RESULTS: 7.0% (n=2,993) of the study population received a red cell transfusion. Our most simple model predicted red cell transfusion based on admission hemoglobin and surgical procedure with a multiply imputed estimated area under the curve of 0.862 (0.856, 0.864). The estimated accuracy, sensitivity, specificity, positive predictive, and negative predictive values at the probability cut-off of 0.4 were 0.934, 0.257, 0.986, 0.573, and 0.946 respectively. DISCUSSION: A small number of variables available prior to admission can predict red cell transfusion with very good accuracy. Our model can be used to flag high-risk patients most likely to benefit from pre-operative patient blood management measures.

Perioperative inappropriate red blood cell transfusions significantly increase total costs in elective surgical patients, representing an important economic burden for hospitals.

Background: Red blood cell (RBC) transfusions in surgical patients are associated with increased morbidity a hospital stay. However, little is known about how clinical and economic outcomes differ between appropriately and inappropriately transfused patients. We hypothesized that inappropriate RBC transfusions in elective surgical patients would significantly increase hospital cost. The aim of this study was to quantify the economic burden associated with inappropriate RBC transfusions. Methods: We retrospectively included all adult patients admitted for elective non-cardiac surgery between January 2014 and March 2020. Patients were divided into three groups (not transfused, appropriately transfused and inappropriately transfused). The primary outcome was the excess in hospital cost in patients inappropriately transfused compared to non-transfused patients. Costs were calculated using a bottom-up approach and involving cost calculation on a granular level. According to international guidelines, transfusions were considered appropriate if administered with an ASA score of 1-2 and the last hemoglobin level measured before transfusion < 70 g/L, or with an ASA score ≥ 3 and the last hemoglobin level < 80 g/L. Cases where RBC transfusions were deemed necessary regardless of the Hb levels were reviewed by the patient blood management (PBM) board and classified accordingly. Secondary outcomes included total transfusion rate, transfusion index, and length of hospital stay. Statistical analysis was carried out by multivariable regression models. Results: During the study period there were 54,922 consecutive surgical admissions, of these 1,997 received an RBC transfusion, with 1,125 considered inappropriate. The adjusted cost of each inappropriate RBC transfusions was estimated in United States dollars (USD) 9,779 (95% CI, 9,358 - 10,199; p < 0.001) and totaled USD 11,001,410 in our series. Inappropriately transfused patients stayed 1.6 times (95% CI, 1.5-1.6; p < 0.001) longer in hospital (10.6 days vs. 6.7 days) than non-transfused patients and a mean 2.35 RBC units per patient were administered. Conclusion: Inappropriate RBC transfusions in elective surgical patients seem to be common and may represent a significant economic burden. In our experience, inappropriate transfusions significantly increased hospital costs by an average of USD 9,779 compared to non-transfused patients. Through specific PBM policy, hospitals may improve cost-effectiveness of their elective surgical activity by lowering inappropriate transfusions.

Hospital-Acquired Infection, Length of Stay, and Readmission in Elective Surgery Patients Transfused 1 Unit of Red Blood Cells: A Retrospective Cohort Study.

BACKGROUND: Most patients transfused red blood cells in elective surgery receive small volumes of blood, which is likely to be discretionary and avoidable. We investigated the outcomes of patients who received a single unit of packed red blood cells during their hospital admission for an elective surgical procedure when compared to those not transfused. METHODS: This retrospective cohort study included elective surgical admissions to 4 hospitals in Western Australia over a 6-year period. Participants were included if they were at least 18 years of age and were admitted for elective surgery between July 2014 and June 2020. We compared outcomes of patients who had received 1 unit of red blood cells to patients who had not been transfused. To balance differences in patient characteristics, we weighted our multivariable regression models using the inverse probability of treatment. In addition to propensity score weighting, our multivariable regression models adjusted for hemoglobin level, surgical procedure, patient age, gender, comorbidities, and the transfusion of fresh-frozen plasma or platelets. Outcomes studied were hospital-acquired infection, hospital length of stay, and all-cause emergency readmissions within 28 days. RESULTS: Overall, 767 (3.2%) patients received a transfusion of 1 unit of red blood cells throughout their admission. In the propensity score weighted analysis, the transfusion of a single unit of red blood cells was associated with higher odds of hospital-acquired infection (odds ratio, 3.94; 95% confidence interval [CI], 2.99-5.20; P < .001). Patients who received 1 unit of red blood cells throughout their admission were more likely to have a longer hospital stay (rate ratio, 1.57; 95% CI, 1.51-1.63; P < .001) and had 1.42 (95% CI, 1.20-1.69; P < .001) times higher odds of 28-day readmission. CONCLUSIONS: These results suggest that avoidance of even small volumes of packed red blood cells may prevent adverse clinical outcomes. This may encourage hospital administrators to implement strategies to avoid the transfusion of even small volumes of red blood cells by applying patient blood management practices.

Machine Learning-Based Mortality Prediction of Patients at Risk During Hospital Admission.

OBJECTIVES: The ability to predict in-hospital mortality from data available at hospital admission would identify patients at risk and thereby assist hospital-wide patient safety initiatives. Our aim was to use modern machine learning tools to predict in-hospital mortality from standardized data sets available at hospital admission. METHODS: This was a retrospective, observational study in 3 adult tertiary care hospitals in Western Australia between January 2008 and June 2017. Primary outcome measures were the area under the curve for the receiver operating characteristics curve, the F1 score, and the average precision of the 4 machine learning algorithms used: logistic regression, neural networks, random forests, and gradient boosting trees. RESULTS: Using our 4 predictive models, in-hospital mortality could be predicted satisfactorily (areas under the curve for neural networks, logistic regression, random forests, and gradient boosting trees: 0.932, 0.936, 0.935, and 0.935, respectively), with moderate F1 scores: 0.378, 0.367, 0.380, and 0.380, respectively. Average precision values were 0.312, 0.321, 0.334, and 0.323, respectively. It remains unknown whether additional features might improve our models; however, this would result in additional efforts for data acquisition in daily clinical practice. CONCLUSIONS: This study demonstrates that using only a limited, standardized data set in-hospital mortality can be predicted satisfactorily at the time point of hospital admission. More parameters describing patient's health are likely needed to improve our model.

Physician autonomy and patient rights: lessons from an enforced blood transfusion and the role of patient blood management.

This article provides an ethical and medico-legal analysis of ruling no. 465 of 30 May 2018 issued by the Court of Termini Imerese (Palermo) and confirmed on appeal on 11 November 2020, which, in the absence of similar historical precedents in Europe, convicted a medical doctor of a crime of violent assault for having ordered the administration of a blood transfusion to a patient specifically declining blood transfusion on religious grounds. We analyse the Court's decision regarding the identification of assault in performing the blood transfusion and its decision not to accept exculpatory urgent 'necessity' as a defence. In addition, we present an updated revision of the current standard of care in transfusion medicine as well as the ethical principles governing the patient's declining of transfusion. In doing so, we highlight that respect for the patient's self-determination in declining transfusions and respect for the professional autonomy of the doctor protecting the safety and life of the patient could be equally satisfied by applying the current peer-reviewed evidence.

Associations of a Preoperative Anemia and Suboptimal Iron Stores Screening and Management Clinic in Colorectal Surgery With Hospital Cost, Reimbursement, and Length of Stay: A Net Cost Analysis.

BACKGROUND: In 2016, a preoperative clinic was implemented to screen, evaluate, and manage anemia and suboptimal iron stores at a major tertiary care medical center in Western Australia. Few studies compare the costs and reimbursements associated with preoperative anemia and suboptimal iron stores management. The objective of our study was to conduct a net cost analysis associated with the implementation of this clinic. METHODS: We designed a retrospective cohort study involving elective colorectal surgical admissions over a 3-year period. The baseline year selected was the 2015-2016 financial year, with outcomes in the 2016-2017 and 2017-2018 year compared to baseline. The study perspective was the Western Australian Health System. Hospital costs were extracted from the health service clinical costing system, which captures costs at the admission level. The primary outcome was net cost, defined as gross cost minus reimbursement (or funding) received. RESULTS: Our 3-year study included 544 admissions for elective colorectal surgery. After the implementation of the preoperative clinic, 73.4% (n = 257) of admissions were screened for anemia and suboptimal iron stores, and 31.4% (n = 110) received intravenous iron. In our adjusted analysis, when comparing the final year (2017-2018) with baseline (2015-2016), the units of red blood cells transfused per admission decreased 53% (142 vs 303 units per 1000 discharges; P = .006), and mean hospital length of stay decreased 15% (7.7 vs 9.1 days; P = .008). When comparing the final year with baseline, rectal resection admissions were associated with a mean decrease in the net cost of Australian dollar (A$) 7619 (95% confidence interval, 4230-11,008; P < .001) between 2015-2016 and 2017-2018. For small and large bowel procedures, there was a mean decrease of A$6744 (95% confidence interval, 2430-11,057; P = .002). CONCLUSIONS: The implementation of a preoperative anemia and suboptimal iron stores screening and management clinic in elective colorectal surgery was associated with reductions in red cell transfusions, length of stay, and net costs.

Systematic reviews and meta-analyses comparing mortality in restrictive and liberal haemoglobin thresholds for red cell transfusion: an overview of systematic reviews.

BACKGROUND: There are no overviews of systematic reviews investigating haemoglobin thresholds for transfusion. This is important as the literature on transfusion thresholds has grown considerably in recent years. Our aim was to synthesise evidence from systematic reviews and meta-analyses of the effects of restrictive and liberal transfusion strategies on mortality. METHODS: This was a systematic review of systematic reviews (overview). We searched MEDLINE, Embase, Web of Science Core Collection, PubMed, Google Scholar, and the Joanna Briggs Institute EBP Database, from 2008 to 2018. We included systematic reviews and meta-analyses of randomised controlled trials comparing mortality in patients assigned to red cell transfusion strategies based on haemoglobin thresholds. Two independent reviewers extracted data and assessed methodological quality. We assessed the methodological quality of included reviews using AMSTAR 2 and the quality of evidence pooled using an algorithm to assign GRADE levels. RESULTS: We included 19 systematic reviews reporting 33 meta-analyses of mortality outcomes from 53 unique randomised controlled trials. Of the 33 meta-analyses, one was graded as high quality, 15 were moderate, and 17 were low. Of the meta-analyses presenting high- to moderate-quality evidence, 12 (75.0%) reported no statistically significant difference in mortality between restrictive and liberal transfusion groups and four (25.0%) reported significantly lower mortality for patients assigned to a restrictive transfusion strategy. We found few systematic reviews addressed clinical differences between included studies: variation was observed in haemoglobin threshold concentrations, the absolute between group difference in haemoglobin threshold concentration, time to randomisation (resulting in transfusions administered prior to randomisation), and transfusion dosing regimens. CONCLUSIONS: Meta-analyses graded as high to moderate quality indicate that in most patient populations no difference in mortality exists between patients assigned to a restrictive or liberal transfusion strategy. TRIAL REGISTRATION: PROSPERO CRD42019120503.

Machine learning-based prediction of transfusion.

BACKGROUND: The ability to predict transfusions arising during hospital admission might enable economized blood supply management and might furthermore increase patient safety by ensuring a sufficient stock of red blood cells (RBCs) for a specific patient. We therefore investigated the precision of four different machine learning-based prediction algorithms to predict transfusion, massive transfusion, and the number of transfusions in patients admitted to a hospital. STUDY DESIGN AND METHODS: This was a retrospective, observational study in three adult tertiary care hospitals in Western Australia between January 2008 and June 2017. Primary outcome measures for the classification tasks were the area under the curve for the receiver operating characteristics curve, the F1 score, and the average precision of the four machine learning algorithms used: neural networks (NNs), logistic regression (LR), random forests (RFs), and gradient boosting (GB) trees. RESULTS: Using our four predictive models, transfusion of at least 1 unit of RBCs could be predicted rather accurately (sensitivity for NN, LR, RF, and GB: 0.898, 0.894, 0.584, and 0.872, respectively; specificity: 0.958, 0.966, 0.964, 0.965). Using the four methods for prediction of massive transfusion was less successful (sensitivity for NN, LR, RF, and GB: 0.780, 0.721, 0.002, and 0.797, respectively; specificity: 0.994, 0.995, 0.993, 0.995). As a consequence, prediction of the total number of packed RBCs transfused was also rather inaccurate. CONCLUSION: This study demonstrates that the necessity for intrahospital transfusion can be forecasted reliably, however the amount of RBC units transfused during a hospital stay is more difficult to predict.