The EFFECT (End-oF-liFE-CommunicaTion) Study: The Acceptability, Feasibility, and Potential Impact of Using Mortality Prediction Scores for Initiating End-of-Life Goals of Care Communication in the Adult Intensive Care Unit

Purpose: The purpose of this dissertation was to determine the acceptability, feasibility, and potential impact of using Severity of Illness (SOI) mortality risk prediction scores for initiating end-of-life (EOL) goals-of-care communication in the adult Intensive Care Unit (ICU). First, an integrative review was conducted to evaluate the psychometric properties of existing SOI scoring systems and their ability to predict mortality in the adult ICU population as the basis for clinical care and provider-patient/family communication. Next, an integrative review of interventions that can guide researchers in reducing surrogate burden was conducted as the basis for conducting research that may impact surrogates of dying patients in the ICU. Finally, a mixed-methods study was conducted to determine the acceptability and feasibility of having providers use SOI mortality prediction scores for their patients as part of routine care and investigate providers’ intentions to change practice related to goals-of-care communication as a result of awareness of the scores. Problem: While healthcare teams recognize that profoundly ill patients in adult ICUs may die, many families are caught by surprise when their loved one dies in a setting with the most advanced technology and intense care available. ICU deaths account for about 20% of patient deaths in US hospitals and this rate is increasing due in part to deficiencies in EOL care communication that can compromise quality of EOL care and increase resource utilization. Previous studies suggest that communication about EOL goals-of-care is infrequent among healthcare providers, patients, and families; often occurs late in the course of illness; and relies on family members to act as patient surrogates in discussions. Furthermore, despite advances in healthcare quality, family members remain more dissatisfied with communication in the ICU than with other aspects of care. Mechanisms for increasing the timeliness and frequency of discussions about EOL goals-of-care are needed. Specific Aims: Aim 1. Evaluate four valid SOI instruments to determine which instrument, or combination of instruments, is the best fit for the study site, given providers’ perceived feasibility of use. Aim 2. Evaluate the acceptability and feasibility of having providers use SOI mortality prediction scores for their patients as part of routine workflow and practice. Aim 3. Evaluate providers’ intentions to change their practice related to goals-of-care communication with patients and/or their families as a result of awareness of SOI mortality prediction scores. Design: First, an integrative review was conducted to evaluate the psychometric properties of existing SOI scoring systems and their ability to predict mortality in the adult ICU. This review provided the foundational knowledge needed in the selection of SOI systems that were used in aim 1. Next, an integrative review of interventions that can guide researchers in reducing surrogate burden was conducted. This review provided foundational knowledge needed for designing a study that may impact surrogates of dying patients in the ICU. Lastly, an explanatory mixed-methods study was conducted to determine the acceptability and feasibility of having providers use SOI mortality prediction scores for their patients as part of routine care and investigate providers’ intentions to change practice related to goals-of-care communication as a result of awareness of the scores. Self-efficacy theory was used as the theoretical underpinning for the design of this study, specifically aim 3. Findings: Based on discrimination alone, the first integrative review found APACHE IV to be superior, but the VA ICU, SICULA, and SOFA Max were close with ‘very good’ discrimination. The second integrative review revealed six levels of intervention, from the personal ‘Direct Care of the Surrogate’ to the population-based ‘Legal/Regulatory’ and provided a framework to assist researchers when designing and conducting research that involves surrogates. The dissertation study found the use of mortality risk prediction scores as part of routine workflow and practice to be acceptable and feasible – providers agreed to participate, patient mortality risk were evaluated by the instrument chosen by the providers (i.e., the Sequential Organ Failure Assessment - SOFA), and overall, participants found use of daily mortality prediction scores possible in their setting. However, there was some disagreement related to the use of SOFA scores as an effective way for determining patient mortality risk. Based on themes that emerged from interviews, providers with limited ICU experience were eager and accepting of the mortality risk scores while those with vast experience found the scores to be an adjunct to their own intuition; though all acknowledged the benefit of looking at daily scores or ‘trends’. The most substantial of all themes identified was the need to consider SOFA scores in relation to patient context; a number alone should not determine mortality risk and whether a goals-of-care conversation needs to occur. Conclusion: This dissertation study found that overall, participants indicated that using mortality prediction scores as part of their daily workflow was acceptable and feasible. Use of SOFA scores for potentially increasing EOL goals-of-care conversations appears to be most beneficial for providers with limited ICU experience. Large-scale studies are needed to determine the effect of using mortality risk predictions on patient EOL outcomes

Do N-terminal pro-brain natriuretic peptide levels determine the prognosis of community acquired pneumonia?

Objective: Pneumonia is a leading cause of mortality worldwide, especially in theelderly. The use of clinical risk scores to determine prognosis is complex and thereforeleads to errors in clinical practice. Pneumonia can cause increases in the levels of cardiacbiomarkers such as N-terminal pro-brain natriuretic peptide (NT-proBNP). The prognosticrole of the NT-proBNP level in community acquired pneumonia (CAP) remains unclear.The aim of this study was to evaluate the prognostic role of the NT-proBNP level in patientswith CAP, as well as its correlation with clinical risk scores. Methods: Consecutiveinpatients with CAP were enrolled in the study. At hospital admission, venous bloodsamples were collected for the evaluation of NT-proBNP levels. The Pneumonia SeverityIndex (PSI) and the Confusion, Urea, Respiratory rate, Blood pressure, and age ? 65years (CURB-65) score were calculated. The primary outcome of interest was all-causemortality within the first 30 days after hospital admission, and a secondary outcomewas ICU admission. Results: The NT-proBNP level was one of the best predictors of30-day mortality, with an area under the curve (AUC) of 0.735 (95% CI: 0.642-0.828; p< 0.001), as was the PSI, which had an AUC of 0.739 (95% CI: 0.634-0.843; p < 0.001),whereas the CURB-65 had an AUC of only 0.659 (95% CI: 0.556-0.763; p = 0.006).The NT-proBNP cut-off level found to be the best predictor of ICU admission and 30-day mortality was 1,434.5 pg/mL. Conclusions: The NT-proBNP level appears to be agood predictor of ICU admission and 30-day mortality among inpatients with CAP, witha predictive value for mortality comparable to that of the PSI and better than that of theCURB-65 score

Development of machine learning schemes for use in non-invasive and continuous patient health monitoring

Stephanie Baker developed machine learning schemes for the non-invasive and continuous measurement of blood pressure and respiratory rate from heart activity waveforms. She also constructed machine learning models for mortality risk assessment from vital sign variations. This research contributes several tools that offer significant advancements in patient monitoring and wearable healthcare

Outcome prediction in intensive care with special reference to cardiac surgery

The development, use, and understanding of severity of illness scoring systems has advanced rapidly in the last decade; their weaknesses and limitations have also become apparent. This work follows some of this development and explores some of these aspects. It was undertaken in three stages and in two countries. The first study investigated three severity of illness scoring systems in a general Intensive Care Unit (ICU) in Cape Town, namely the Acute Physiology and Chronic Health Evaluation (APACHE II) score, the Therapeutic Intervention Scoring System (TISS), and a locally developed organ failure score. All of these showed a good relationship with mortality, with the organ failure score the best predictor of outcome. The TISS score was felt to be more likely to be representative of intensiveness of medical and nursing management than severity of illness. The APACHE II score was already becoming widely used world-wide and although it performed less well in some diagnostic categories (for example Adult Respiratory Distress Syndrome) than had been hoped, it clearly warranted further investigation. Some of the diagnosis-specific problems were eliminated in the next study which concentrated on the application of the APACHE II score in a cardiothoracic surgical ICU in London. Although group predictive ability was statistically impressive, the predictive ability of APACHE II in the individual patient was limited as only very high APACHE II scores confidently predicted death and then only in a small number of patients. However, there were no deaths associated with an APACHE II score of less than 5 and the mortality was less than 1 % when the APACHE II score was less than 10. Finally, having recognised the inadequacies in mortality prediction of the APACHE II score in this scenario, a study was undertaken to evaluate a novel concept: a combination of preoperative, intraoperative, and postoperative (including APACHE II and III) variables in cardiac surgery patients admitted to the same ICU. The aim was to develop a more precise method of predicting length of stay, incidence of complications, and ICU and hospital outcome for these patients. There were 1008 patients entered into the study. There was a statistically significant relationship between increasing Parsonnet (a cardiac surgery risk prediction score), APACHE II, and APACHE III scores and mortality. By forward stepwise logistic regression a model was developed for the probability of hospital death. This model included bypass time, need for inotropes, mean arterial pressure, urea, and Glasgow Coma Scale. Predictive performance was evaluated by calculating the area under the receiver operating characteristic (ROC) curve. The derived model had an area under the ROC curve 0.87, while the Parsonnet score had an area of 0.82 and the APACHE II risk of dying 0.84. It was concluded that a combination of intraoperative and postoperative variables can improve predictive ability

Ventilatory ratio : a simple bedside index to monitor ventilatory efficiency

A lack of a simple index that monitors ventilatory efficiency at the bedside has meant that oxygenation has been the predominant variable that is used to monitor adequacy of ventilatory strategies and disease severity in mechanically ventilated patients. Due to complexities in its measurement, deadspace ventilation, the traditional method to track ventilatory failure, has failed to become integral in the management of mechanically ventilated patients. Ventilatory ratio (VR) is an easy to calculate index that uses variables measured at the bedside: [Mathematical equation appears here. To view, please open pdf attachment] where [Symbols appears here. To view, please open pdf attachment] is taken to be 100 ml.kg-1.min-1 based on predicted body weight and [Symbols appears here. To view, please open pdf attachment] is taken to be 5 kPa. Physiological analysis of VR dictates that it is influenced by deadspace fraction and CO2 production. Physiological analysis of VR was validated in a benchside lung model and a high fidelity computational cardiopulmonary physiology model. The impact of CO2 production on VR was investigated in patients undergoing laparoscopic surgery who received exogenous intraperitoneal CO2. This showed that delta values of the 2 variables were linear. The variability of CO2 production was examined in ICU patients and results of the study showed that variability of CO2 production was small. In an ICU population correlation of VR was stronger with deadspace in comparison to CO2 production. Of these two variables, deadspace had the greater effect on VR. The clinical uses of VR were examined in 4 databases of ICU patients. VR was significantly higher in non-survivors compared to survivors. Higher values of VR were associated with increased mortality and more ventilator days. A rising values of VR over time was also associated with worse outcome. VR is a simple bedside index that provides clinicians with useful information regarding ventilatory efficiency and is associated with outcome

A Case for Delirium Risk Prediction Models to Aid in Triaging Resources to those Most at Risk an Integrative Literature Review

Abstract Delirium is a complex syndrome resulting from compounding effects of acute illness, comorbidities, and the environment. It results in adverse outcomes: elevated mortality rates, length of stay, readmissions, institutionalization, long-term cognitive changes, and diminished quality of life. The rate of iatrogenic delirium is astounding, ranging from 10%-89%. There are no curative treatments; thus, primary prevention is the key. The purpose of this literature review is to identify and critique the research for the accuracy of risk stratification and feasibility in practice. Support for interventions that prevent delirium is mounting; however, interventions are resource-intensive and often not implemented. Researchers have responded to this problem by developing risk stratification tools to triage interventions toward those of the highest risk. There is evidence that some of the models\u27 implementation is successful; however, they are not yet widely operationalized. A compilation of seven published models of risk prediction was critiqued and compared using the Stetler Model of Evidence-Based Practice as a guiding model. The Newcastle-Ottawa Scale and the Critical Appraisal and the Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS checklist) are employed to aid in the critical appraisal, evaluation of the study\u27s quality, and aid in data abstraction. The models show the ability to stratify risk. Still, their effectiveness in practice cannot be studied without directed interventions because they risk prediction models are created to aid healthcare staff in making clinical decisions. Therefore, a complete clinical pathway with evidence-based interventions should be employed with a delirium risk prediction model to triage the interventions to patients at the highest risk. Recommendations are to implement an automated electronic model (automatic calculation using the EMR or a machine learning model) into clinical practice along with a delirium prevention care pathway. Electronic versions of risk scores allow for an opportunity to achieve clinical efficiency and show statistical superiority to the other models. Published evidence on the impact of the models is diminutive. Their ability to triage patients and aid in clinical decision-making should be published in an impact study. Keywords: Delirium, risk assessment, risk prediction, risk model, risk score, patient safety, patient-centered outcomes researc