Prospectively defined indicators to improve the safety and quality of care for critically ill patients: a report from the Task Force on Safety and Quality of the European Society of Intensive Care Medicine (ESICM)

Characteristics and outcomes of trauma patients with unplanned intensive care unit admissions: Bounce backs and upgrades comparison

BACKGROUND

The need for an emergency upgrade of a hospitalized trauma patient from the floor to the trauma intensive care unit (ICU) is an unanticipated event with possible life-threatening consequences. Unplanned ICU admissions are associated with increased morbidity and mortality and are an indicator of trauma service quality. Two different types of unplanned ICU admissions include upgrades (patients admitted to the floor then moved to the ICU) and bounce backs (patients admitted to the ICU, discharged to the floor, and then readmitted to the ICU). Previous studies have shown that geriatric trauma patients are at higher risk for unfavorable outcomes.

AIM

To analyze the characteristics, management and outcomes of trauma patients who had an unplanned ICU admission during their hospitalization.

METHODS

This institutional review board approved, retrospective cohort study examined 203 adult trauma patients with unplanned ICU admission at an urban level 1 trauma center over a six-year period (2017-2023). This included 134 upgrades and 69 bounce backs. Analyzed variables included: (1) Age; (2) Sex; (3) Comorbidities; (4) Mechanism of injury (MOI); (5) Injury severity score (ISS); (6) Glasgow Coma Scale (GCS); (7) Type of injury; (8) Transfusions; (9) Consultations; (10) Timing and reason for unplanned admission; (11) Intubations; (12) Surgical interventions; (13) ICU and hospital lengths of stay; and (14) Mortality.

RESULTS

Unplanned ICU admissions comprised 4.2% of total ICU admissions. Main MOI was falls. Mean age was 70.7 years, ISS was 12.8 and GCS was 13.9. Main injuries were traumatic brain injury (37.4%) and thoracic injury (21.7%), and main reason for unplanned ICU admission was respiratory complication (39.4%). The 47.3% underwent a surgical procedure and 46.8% were intubated. Average timing for unplanned ICU admission was 2.9 days. Bounce backs occurred half as often as upgrades, however had higher rates of transfusions (63.8% vs 40.3%, P = 0.002), consultations (4.8 vs 3.0, P < 0.001), intubations (63.8% vs 38.1%%, P = 0.001), longer ICU lengths of stay (13.2 days vs 6.4 days, P < 0.001) and hospital lengths of stay (26.7 days vs 13.0 days, P < 0.001). Mortality was 25.6% among unplanned ICU admissions, 31.9% among geriatric unplanned ICU admissions and 11.9% among all trauma ICU patients.

CONCLUSION

Unplanned ICU admissions constituted 4.2% of total ICU admissions. Respiratory complications were the main cause of unplanned ICU admissions. Bounce backs occurred half as often as upgrades, but were associated with worse outcomes.

Grading Scores for Identifying Patients at Risk of Delayed Cerebral Ischemia and Neurological Outcome in Spontaneous Subarachnoid Hemorrhage: A Comparison of Receiver Operator Curve Analysis

BACKGROUND

Numerous grading scales were proposed for subarachnoid hemorrhage (SAH) to assess the likelihood of unfavorable neurological outcomes (UO) and the risk of delayed cerebral ischemia (DCI). We aimed to validate the Hemorrhage, Age, Treatment, Clinical Status, and Hydrocephalus (HATCH) score and the VASOGRADE, a simple grading scale for prediction of DCI after aneurysmal SAH.

METHODS

This was a retrospective single-center study of patients with nontraumatic SAH (January 2016 to December 2021) admitted to the intensive care unit. We performed a receiver operating characteristic (ROC) curve analysis to assess the discriminative ability of the HATCH and the VASOGRADE to identify patients who had UO at 3 months (defined as Glasgow Outcome Scale score of 1-3), hospital mortality, and DCI and compared their performance with the World Federation of Neurosurgical Surgeons, the modified Fisher, the Sequential Organ Failure Assessment, and the Acute Physiology and Chronic Health Evaluation II scales. We performed a multivariate logistic regression analysis to assess the association between HATCH and UO at 3 months and between VASOGRADE and DCI.

RESULTS

We included 262 consecutive patients with nontraumatic SAH. DCI was observed in 82 patients (31.3%), whereas 78 patients (29.8%) died during hospital stay and 133 patients (51%) had UO at 3 months. HATCH was independently associated with UO (odds ratio 1.61, 95% confidence interval [CI] 1.36-1.90) and had an area under the ROC curve (AUROC) of 0.83 (95% CI 0.77-0.88), comparable to the Acute Physiology and Chronic Health Evaluation II (AUROC 0.84, 95% CI 0.79-0.89) and Sequential Organ Failure Assessment (AUROC 0.83, 95% CI 0.77-0.88).

CONCLUSIONS

Hemorrhage, Age, Treatment, Clinical Status, and Hydrocephalus and VASOGARDE scores had a good performance to predict UO or in-hospital mortality and DCI, respectively; however, their performance did not outperform nonspecific routinely used scores.

Reducing administrative burden by implementing a core set of quality indicators in the ICU: a multicentre longitudinal intervention study

BACKGROUND

The number of quality indicators for which clinicians need to record data is increasing. For many indicators, there are concerns about their efficacy. This study aimed to determine whether working with only a consensus-based core set of quality indicators in the intensive care unit (ICU) reduces the time spent on documenting performance data and administrative burden of ICU professionals, and if this is associated with more joy in work without impacting the quality of ICU care.

METHODS

Between May 2021 and June 2023, ICU clinicians of seven hospitals in the Netherlands were instructed to only document data for a core set of quality indicators. Time spent on documentation, administrative burden and joy in work were collected at three time points with validated questionnaires. Longitudinal data on standardised mortality rates (SMR) and ICU readmission rates were gathered from the Dutch National Intensive Care registry. Longitudinal effects and differences in outcomes between ICUs and between nurses and physicians were statistically tested.

RESULTS

A total of 390 (60%), 291 (47%) and 236 (40%) questionnaires returned at T0, T1 and T2. At T2, the overall median time spent on documentation per day was halved by 30 min (p<0.01) and respondents reported fewer unnecessary and unreasonable administrative tasks (p<0.01). Almost one-third still experienced unnecessary administrative tasks. No significant changes over time were found in joy in work, SMR and ICU readmission.

CONCLUSIONS

Implementing a core set of quality indicators reduces the time ICU clinicians spend on documentation and administrative burden without negatively affecting SMR or ICU readmission rates. Time savings can be invested in patient care and improving joy in work in the ICU.

Effect of Tele-ICU on Clinical Outcomes of Critically Ill Patients: The TELESCOPE Randomized Clinical Trial

Importance

Despite its implementation in several countries, there has not been a randomized clinical trial to assess whether telemedicine in intensive care units (ICUs) could improve clinical outcomes of critically ill patients.

Objective

To determine whether an intervention comprising daily multidisciplinary rounds and monthly audit and feedback meetings performed by a remote board-certified intensivist reduces ICU length of stay (LOS) compared with usual care.

Design, Setting, and Participants

A parallel cluster randomized clinical trial with a baseline period in 30 general ICUs in Brazil in which daily multidisciplinary rounds performed by board-certified intensivists were not routinely available. All consecutive adult patients (aged ≥18 years) admitted to the participating ICUs, excluding those admitted due to justice-related issues, were enrolled between June 1, 2019, and April 7, 2021, with last follow-up on July 6, 2021.

Intervention

Remote daily multidisciplinary rounds led by a board-certified intensivist through telemedicine, monthly audit and feedback meetings for discussion of ICU performance indicators, and provision of evidence-based clinical protocols.

Main Outcomes and Measures

The primary outcome was ICU LOS at the patient level. Secondary outcomes included ICU efficiency, in-hospital mortality, incidence of central line-associated bloodstream infections, ventilator-associated events, catheter-associated urinary tract infections, ventilator-free days at 28 days, patient-days receiving oral or enteral feeding, patient-days under light sedation, and rate of patients with oxygen saturation values under that of normoxemia, assessed using generalized linear mixed models.

Results

Among 17 024 patients (1794 in the baseline period and 15 230 in the intervention period), the mean (SD) age was 61 (18) years, 44.7% were female, the median (IQR) Sequential Organ Failure Assessment score was 6 (2-9), and 45.5% were invasively mechanically ventilated at admission. The median (IQR) time under intervention was 20 (16-21) months. Mean (SD) ICU LOS, adjusted for baseline assessment, did not differ significantly between the tele-critical care and usual care groups (8.1 [10.0] and 7.1 [9.0] days; percentage change, 8.2% [95% CI, -5.4% to 23.8%]; P = .24). Results were similar in sensitivity analyses and prespecified subgroups. There were no statistically significant differences in any other secondary or exploratory outcomes.

Conclusions and Relevance

Daily multidisciplinary rounds conducted by a board-certified intensivist through telemedicine did not reduce ICU LOS in critically ill adult patients.

Trial Registration

ClinicalTrials.gov Identifier: NCT03920501.

Improving medication safety for intensive care patients transitioning to a hospital ward: development of a theory-informed intervention package

BACKGROUND

Care of critically ill patients is complex, requiring effective collaboration co-ordination and communication across care teams and professions. Medicines are a fundamental component of the acute interventions intensive care unit (ICU) patients receive, requiring frequent review and optimisation according to patient needs. ICU patients recovering to transfer to a hospital ward are at risk of medication transition errors, contributing to poorer patient and health-system outcomes. We aimed to develop of a theory-informed intervention package to improve medication safety for ICU patients transferring to a hospital ward.

METHODS

We conducted a qualitative study comprising two UK face-to-face focus group meetings in April and May 2022. There were ten participants in each meeting (7-8 healthcare professionals and 2-3 patient and public representatives). Each meeting had four foci: (i) What needs to change (intervention targets)? (ii) What are the core intervention components? (iii) What will the intervention components change and how (mechanisms of action), and what key outcomes will the changes impact on? (iv) What are the barriers and facilitators to intervention delivery? A background to the problem and previous intervention development work was provided. Meetings were digitally recorded and transcribed verbatim. Iterative analyses, informed by the Behaviour Change Wheel framework, were conducted to provide a behavioural diagnosis, identify key behaviour change techniques and outline the mechanisms of action through which the intervention might impact on key outcome.

RESULTS

We identified what needs to change to improve medication safety for UK ICU patients on this care transition. A theory-informed intervention package was developed, based on seven core intervention components (e.g., medication review (targeted), task organisation and prioritisation). For each intervention component the mechanism of action, targeted change, and key outcomes were identified (e.g., medication review (targeted); action planning; decreases problematic polypharmacy; decreased preventable adverse drug events). Barriers and facilitators to intervention component delivery were described.

CONCLUSIONS

We developed a theory-informed core intervention package to address the limitations in medication safety for ICU patients transferring to a hospital ward. Understanding what needs to change, and the accompanying facilitators provides a basis for intervention feasibility testing and refinement prior to future evaluation of effectiveness.

Role of Charlson comorbidity index in predicting intensive care unit readmission in patients with aortic aneurysm

The purpose of this study was to investigate the value of the Charlson comorbidity index (CCI) in predicting intensive care unit (ICU) readmission in aortic aneurysm (AA) patients. Patient information came from the Medical Information Mart for Intensive Care- IV (MIMIC-IV) database. The relationship between CCI and ICU readmission was analyzed by restricted cubic spline, generalized linear regression, trend analysis, and hierarchical analysis. The clinical value of CCI in predicting ICU readmission was analyzed by receiver operating characteristic curve, decision curve analysis, XGBoost regression, and random forest regression. A total of 523 patients with AA were enrolled in the study. Patients with AA who were readmitted to the ICU had higher width of red blood cell distribution width (RDW) and higher CCI. CCI had better performance and clinical net benefit for predicting ICU readmission than RDW. An independent nonlinear relationship was found between CCI and ICU readmission. The trend analysis suggested that the risk of ICU readmission increased with higher CCI scores. The hierarchical analysis showed that their association was mainly found in surgery requirement populations regardless of AA types. Further, CCI was found to have better clinical value in predicting ICU readmission of thoracic aortic aneurysm (TAA) patients undergoing surgery. Age, renal disease, chronic lung disease, and dementia were important components of CCI in predicting ICU readmission of TAA patients undergoing surgery. CCI was independently associated with the ICU readmission of AA patients in a positive relationship and had more favorable prediction performance in TAA patients who underwent surgery.

Association Between In-hospital Mortality and the Institutional Factors of Intensive Care Units with a Focus on the Intensivist-to-bed Ratio: A Retrospective Cohort Study

Purpose: To elucidate the relationship between in-hospital mortality and the institutional factors of intensive care units (ICUs), with a focus on the intensivist-to-bed ratio. Methods: A retrospective cohort study was conducted using a Japanese ICU database, including adult patients admitted between April 1, 2020 and March 31, 2021. We used a multilevel logistic regression model to investigate the associations between in-hospital mortality and the following institutional factors: the intensivist-to-bed ratios on weekdays or over weekends/holidays, different work shifts, hospital-to-ICU-bed ratio, annual-ICU-admission-to-bed ratio, type of hospital, and the presence of other medical staff. Results: The study population comprised 46 503 patients admitted to 65 ICUs. The in-hospital mortality rate was 8.1%. The median numbers of ICU beds and intensivists were 12 (interquartile range [IQR] 8-14) and 4 (IQR 2-9), respectively. In-hospital mortality decreased significantly as the intensivist-to-bed ratio at 10 am on weekdays increased: the average contrast indicated a 20% (95% confidence interval [CI]: 1%-38%) reduction when the ratio increased from 0 to 0.5, and a 38% (95% CI: 9%-67%) reduction when the ratio increased from 0 to 1. The other institutional factors did not present a significant effect. Conclusions: The intensivist-to-bed ratio at 10 am on weekdays had a significant effect on in-hospital mortality. Further investigation is needed to understand the processes leading to improved outcomes.

Update on the Epimed Monitor Adult ICU Database: 15 years of its use in national registries, quality improvement initiatives and clinical research

In recent decades, several databases of critically ill patients have become available in both low-, middle-, and high-income countries from all continents. These databases are also rich sources of data for the surveillance of emerging diseases, intensive care unit performance evaluation and benchmarking, quality improvement projects and clinical research. The Epimed Monitor database is turning 15 years old in 2024 and has become one of the largest of these databases. In recent years, there has been rapid geographical expansion, an increase in the number of participating intensive care units and hospitals, and the addition of several new variables and scores, allowing a more complete characterization of patients to facilitate multicenter clinical studies. As of December 2023, the database was being used regularly for 23,852 beds in 1,723 intensive care units and 763 hospitals from ten countries, totaling more than 5.6 million admissions. In addition, critical care societies have adopted the system and its database to establish national registries and international collaborations. In the present review, we provide an updated description of the database; report experiences of its use in critical care for quality improvement initiatives, national registries and clinical research; and explore other potential future perspectives and developments.

Time-to-surgery paradigms: wait time and surgical outcomes in critically Ill patients who underwent emergency surgery for gastrointestinal perforation

BACKGROUND

Waiting time for emergency abdominal surgery have been known to be linked to mortality. However, there is no clear consensus on the appropriated timing of surgery for gastrointestinal perforation. We investigated association between wait time and surgical outcomes in emergency abdominal surgery.

METHODS

This single-center retrospective cohort study evaluated adult patients who underwent emergency surgery for gastrointestinal perforations between January 2003 and September 2021. Risk-adjusted restricted cubic splines modeled the probability of each mortality according to wait time. The inflection point when mortality began to increase was used to define early and late surgery. Outcomes among propensity-score matched early and late surgical patients were compared using percent absolute risk differences (RDs, with 95% CIs).

RESULTS

Mortality rates began to rise after 16 h of waiting. However, early and late surgery groups showed no significant differences in 30-day mortality (11.4% vs. 5.7%), ICU stay duration (4.3 ± 7.5 vs. 4.3 ± 5.2 days), or total hospital stay (17.4 ± 17.0 vs. 24.7 ± 23.4 days). Notably, patients waiting over 16 h had a significantly higher ICU readmission rate (8.6% vs. 31.4%). The APACHE II score was a significant predictor of 30-day mortality.

CONCLUSIONS

Although we were unable to reveal significant differences in mortality in the subgroup analysis, we were able to find an inflection point of 16 h through the RCS curve technique.

TRIAL REGISTRATION

Formal consent was waived due to the retrospective nature of the study, and ethical approval was obtained from the institutional research committee of our institution (B-2110-714-107) on 6 October 2021.

Quality Indicators in Adult Critical Care Medicine

Quality indicators are increasingly used in the intensive care unit (ICU) to compare and improve the quality of delivered healthcare. Numerous indicators have been developed and are related to multiple domains, most importantly patient safety, care timeliness and effectiveness, staff well-being, and patient/family-centered outcomes and satisfaction. In this review, we describe pertinent ICU quality indicators that are related to organizational structure (such as the availability of an intensivist 24/7 and the nurse-to-patient ratio), processes of care (such as ventilator care bundle), and outcomes (such as ICU-acquired infections and standardized mortality rate). We also present an example of a quality improvement project in an ICU indicating the steps taken to attain the desired changes in quality measures.

The Influence of Potential Organ Donors on Standardized Mortality Ratios and ICU Benchmarking

OBJECTIVES

The standardized mortality ratio (SMR) is a common metric to benchmark ICUs. However, SMR may be artificially distorted by the admission of potential organ donors (POD), who have nearly 100% mortality, although risk prediction models may not identify them as high-risk patients. We aimed to evaluate the impact of PODs on SMR.

DESIGN

Retrospective registry-based multicenter study.

SETTING

Twenty ICUs in Finland, Estonia, and Switzerland in 2015-2017.

PATIENTS

Sixty thousand forty-seven ICU patients.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We used a previously validated mortality risk model to calculate the SMRs. We investigated the impact of PODs on the overall SMR, individual ICU SMR and ICU benchmarking. Of the 60,047 patients admitted to the ICUs, 514 (0.9%) were PODs, and 477 (93%) of them died. POD deaths accounted for 7% of the total 6738 in-hospital deaths. POD admission rates varied from 0.5 to 18.3 per 1000 admissions across ICUs. The risk prediction model predicted a 39% in-hospital mortality for PODs, but the observed mortality was 93%. The ratio of the SMR of the cohort without PODs to the SMR of the cohort with PODs was 0.96 (95% CI, 0.93-0.99). Benchmarking results changed in 70% of ICUs after excluding PODs.

CONCLUSIONS

Despite their relatively small overall number, PODs make up a large proportion of ICU patients who die. PODs cause bias in SMRs and in ICU benchmarking. We suggest excluding PODs when benchmarking ICUs with SMR.

Heart rate complexity helps mortality prediction in the intensive care unit: A pilot study using artificial intelligence

BACKGROUND

In intensive care units (ICUs), accurate mortality prediction is crucial for effective patient management and resource allocation. The Simplified Acute Physiology Score II (SAPS-2), though commonly used, relies heavily on comprehensive clinical data and blood samples. This study sought to develop an artificial intelligence (AI) model utilizing key hemodynamic parameters to predict ICU mortality within the first 24 h and assess its performance relative to SAPS-2.

METHODS

We conducted an analysis of select hemodynamic parameters and the structure of heart rate curves to identify potential predictors of ICU mortality. A machine-learning model was subsequently trained and validated on distinct patient cohorts. The AI algorithm's performance was then compared to the SAPS-2, focusing on classification accuracy, calibration, and generalizability.

MEASUREMENTS AND MAIN RESULTS

The study included 1298 ICU admissions from March 27th, 2015, to March 27th, 2017. An additional cohort from 2022 to 2023 comprised 590 patients, resulting in a total dataset of 1888 patients. The observed mortality rate stood at 24.0%. Key determinants of mortality were the Glasgow Coma Scale score, heart rate complexity, patient age, duration of diastolic blood pressure below 50 mmHg, heart rate variability, and specific mean and systolic blood pressure thresholds. The AI model, informed by these determinants, exhibited a performance profile in predicting mortality that was comparable, if not superior, to the SAPS-2.

CONCLUSIONS

The AI model, which integrates heart rate and blood pressure curve analyses with basic clinical parameters, provides a methodological approach to predict in-hospital mortality in ICU patients. This model offers an alternative to existing tools that depend on extensive clinical data and laboratory inputs. Its potential integration into ICU monitoring systems may facilitate more streamlined mortality prediction processes.

Prognostic factors for critically ill surgical patients with unplanned intensive care unit readmission: Developing a novel predictive scoring model for predicting readmission

BACKGROUND

Unplanned readmission to the surgical intensive care unit has been demonstrated to worsen patient outcomes. Our objective was to identify risk factors and outcomes associated with unplanned surgical intensive care unit readmission and to develop a predictive scoring model to identify patients at high risk of readmission.

METHODS

We retrospectively analyzed patients admitted to the surgical intensive care unit (2020-2021) and categorized them as either with or without unplanned readmission.

RESULTS

Of 1,112 patients in the derivation cohort, 76 (6.8%) experienced unplanned surgical intensive care unit readmission, with sepsis being the leading cause of readmission (35.5%). Patients who were readmitted had significantly higher in-hospital mortality rates than those who were not. Multivariate analysis identified congestive heart failure, high Sequential Organ Failure Assessment-Hepatic score, use of carbapenem during surgical intensive care unit stay, as well as factors before surgical intensive care unit discharge such as inadequate glycemic control, positive fluid balance, low partial pressure of oxygen in arterial blood/fraction of inspired oxygen ratio, and receipt of total parenteral nutrition as independent predictors for unplanned readmission. The scoring model developed using these predictors exhibited good discrimination between readmitted and non-readmitted patients, with an area under the curve of 0.74. The observed rates of unplanned readmission for scores of <4 points and ≥4 points were 4% and 20.2% (P < .001), respectively. The model also demonstrated good performance in the validation cohort, with an area under the curve of 0.74 and 19% observed unplanned readmission rate for scores ≥4 points.

CONCLUSION

Besides congestive heart failure, clinicians should meticulously re-evaluate critical variables such as the Sequential Organ Failure Assessment-Hepatic score, partial pressure of oxygen in arterial blood/fraction of inspired oxygen ratio, glycemic control, and fluid status before releasing the patient from the surgical intensive care unit. It is crucial to determine the reasons for using carbapenems during surgical intensive care unit stay and the causes for the inability to discontinue total parenteral nutrition before discharging the patient from the surgical intensive care unit.

Ethisch begründet entscheiden in der Intensivmedizin

The process recommendations of the Ethics Section of the German Interdisciplinary Association for Intensive Care and Emergency Medicine (DIVI) for ethically based decision-making in intensive care medicine are intended to create the framework for a structured procedure for seriously ill patients in intensive care. The processes require appropriate structures, e.g., for effective communication within the treatment team, with patients and relatives, legal representatives, as well as the availability of palliative medical expertise, ethical advisory committees and integrated psychosocial and spiritual care services. If the necessary competences and structures are not available in a facility, they can be consulted externally or by telemedicine if necessary. The present recommendations are based on an expert consensus and are not the result of a systematic review or a meta-analysis.

Machine Learning for Benchmarking Critical Care Outcomes

OBJECTIVES

Enhancing critical care efficacy involves evaluating and improving system functioning. Benchmarking, a retrospective comparison of results against standards, aids risk-adjusted assessment and helps healthcare providers identify areas for improvement based on observed and predicted outcomes. The last two decades have seen the development of several models using machine learning (ML) for clinical outcome prediction. ML is a field of artificial intelligence focused on creating algorithms that enable computers to learn from and make predictions or decisions based on data. This narrative review centers on key discoveries and outcomes to aid clinicians and researchers in selecting the optimal methodology for critical care benchmarking using ML.

METHODS

We used PubMed to search the literature from 2003 to 2023 regarding predictive models utilizing ML for mortality (592 articles), length of stay (143 articles), or mechanical ventilation (195 articles). We supplemented the PubMed search with Google Scholar, making sure relevant articles were included. Given the narrative style, papers in the cohort were manually curated for a comprehensive reader perspective.

RESULTS

Our report presents comparative results for benchmarked outcomes and emphasizes advancements in feature types, preprocessing, model selection, and validation. It showcases instances where ML effectively tackled critical care outcome-prediction challenges, including nonlinear relationships, class imbalances, missing data, and documentation variability, leading to enhanced results.

CONCLUSIONS

Although ML has provided novel tools to improve the benchmarking of critical care outcomes, areas that require further research include class imbalance, fairness, improved calibration, generalizability, and long-term validation of published models.

Frequency, Characteristics, and Outcomes of Patients Requiring Early PICU Readmission

OBJECTIVES

Readmission to the PICU is associated with worse outcomes, but factors associated with PICU readmission within the same hospitalization remain unclear. We sought to describe the prevalence of, and identify factors associated with, early PICU readmission.

METHODS

We performed a retrospective analysis of PICU admissions for patients aged 0 to 26 years in 48 tertiary care children's hospitals between January 1, 2016 and December 31, 2019 in the Pediatric Health Information System. We defined early readmission as return to the PICU within 2 calendar days of floor transfer during the same hospitalization. Generalized linear mixed models were used to analyze associations between patient and clinical variables, including complex chronic conditions (CCC) and early PICU readmission.

RESULTS

The results included 389 219 PICU admissions; early PICU readmission rate was 2.5%. Factors with highest odds of early PICU readmission were CCC, with ≥4 CCCs (reference: no CCC[s]) as highest odds of readmission (adjusted odds ratio [95% confidence interval]: 4.2 [3.8-4.5]), parenteral nutrition (2.3 [2.1-2.4]), and ventriculoperitoneal shunt (1.9 [1.7-2.2]). Factors with decreased odds of PICU readmission included extracorporeal membrane oxygenation (0.4 [0.3-0.6]) and cardiopulmonary resuscitation (0.8 [0.7-0.9]). Patients with early PICU readmissions had longer overall length of stay (geometric mean [geometric SD]: 18.2 [0.9] vs 5.0 [1.1] days, P < .001) and increased odds of mortality (1.7 [1.5-1.9]).

CONCLUSIONS

Although early PICU readmissions within the same hospitalization are uncommon, they are associated with significantly worse clinical outcomes. Patients with medical complexity and technology dependence are especially vulnerable.

Perioperative risk factors associated with unplanned neurological intensive care unit readmission following elective supratentorial brain tumor resection

OBJECTIVE

The aim of this study was to describe the clinical and procedural risk factors associated with the unplanned neurosurgical intensive care unit (NICU) readmission of patients after elective supratentorial brain tumor resection and serves as an exploratory analysis toward the development of a risk stratification tool that may be prospectively applied to this patient population.

METHODS

This was a retrospective observational cohort study. The electronic medical records of patients admitted to an institutional NICU between September 2018 and November 2021 after elective supratentorial brain tumor resection were reviewed. Demographic and perioperative clinical factors were recorded. A prognostic model was derived from the data of 4892 patients recruited between September 2018 and May 2021 (development cohort). A nomogram was created to display these predictor variables and their corresponding points and risks of readmission. External validation was evaluated using a series of 1118 patients recruited between June 2021 and November 2021 (validation cohort). Finally, a decision curve analysis was performed to determine the clinical usefulness of the prognostic model.

RESULTS

Of the 4892 patients in the development cohort, 220 (4.5%) had an unplanned NICU readmission. Older age, lesion type, Karnofsky Performance Status (KPS) < 70 at admission, longer duration of surgery, retention of endotracheal intubation on NICU entry, and longer NICU length of stay (LOS) after surgery were independently associated with an unplanned NICU readmission. A total of 1118 patients recruited between June 2021 and November 2021 were included for external validation, and the model's discrimination remained acceptable (C-statistic = 0.744, 95% CI 0.675-0.814). The decision curve analysis for the prognostic model in the development and validation cohorts showed that at a threshold probability between 0.05 and 0.8, the prognostic model showed a positive net benefit.

CONCLUSIONS

A predictive model that included age, lesion type, KPS < 70 at admission, duration of surgery, retention of endotracheal intubation on NICU entry, and NICU LOS after surgery had an acceptable ability to identify elective supratentorial brain tumor resection patients at high risk for an unplanned NICU readmission. These risk factors and this prediction model may facilitate better resource allocation in the NICU and improve patient outcomes.

Evaluation of ICUs and weight of quality control indicators: an exploratory study based on Chinese ICU quality data from 2015 to 2020

This study aimed to explore key quality control factors that affected the prognosis of intensive care unit (ICU) patients in Chinese mainland over six years (2015-2020). The data for this study were from 31 provincial and municipal hospitals (3425 hospital ICUs) and included 2 110 685 ICU patients, for a total of 27 607 376 ICU hospitalization days. We found that 15 initially established quality control indicators were good predictors of patient prognosis, including percentage of ICU patients out of all inpatients (%), percentage of ICU bed occupancy of total inpatient bed occupancy (%), percentage of all ICU inpatients with an APACHE II score ⩾15 (%), three-hour (surviving sepsis campaign) SSC bundle compliance (%), six-hour SSC bundle compliance (%), rate of microbe detection before antibiotics (%), percentage of drug deep venous thrombosis (DVT) prophylaxis (%), percentage of unplanned endotracheal extubations (%), percentage of patients reintubated within 48 hours (%), unplanned transfers to the ICU (%), 48-h ICU readmission rate (%), ventilator associated pneumonia (VAP) (per 1000 ventilator days), catheter related blood stream infection (CRBSI) (per 1000 catheter days), catheter-associated urinary tract infections (CAUTI) (per 1000 catheter days), in-hospital mortality (%). When exploratory factor analysis was applied, the 15 indicators were divided into 6 core elements that varied in weight regarding quality evaluation: nosocomial infection management (21.35%), compliance with the Surviving Sepsis Campaign guidelines (17.97%), ICU resources (17.46%), airway management (15.53%), prevention of deep-vein thrombosis (14.07%), and severity of patient condition (13.61%). Based on the different weights of the core elements associated with the 15 indicators, we developed an integrated quality scoring system defined as F score=21.35%xnosocomial infection management + 17.97%xcompliance with SSC guidelines + 17.46%×ICU resources + 15.53%×airway management + 14.07%×DVT prevention + 13.61%×severity of patient condition. This evidence-based quality scoring system will help in assessing the key elements of quality management and establish a foundation for further optimization of the quality control indicator system.

Transitions and empowerment theory: A framework for nursing interventions during intensive care unit patient transition

OBJECTIVES

1) To explore the main characteristics of intensive care unit transition according to patients' lived experience and 2) To identify nursing therapeutics to facilitate patients' transition from the intensive care unit to the inpatient unit.

METHODOLOGY

Secondary Analysis (SA) of the findings of a descriptive qualitative study on the experience of patients admitted to an ICU during the transition to the inpatient unit, based on the Nursing Transitions Theory. Data for the primary study were generated from 48 semi-structured interviews of patients who had survived critical illness in 3 tertiary university hospitals.

RESULTS

Three main themes were identified during the transition of patients from the intensive care unit to the inpatient unit: 1) nature of ICU transition, 2) response patterns and 3) nursing therapeutics. Nurse therapeutics incorporates information, education and promotion of patient autonomy; in addition to psychological and emotional support.

CONCLUSIONS

Transitions Theory as a theoretical framework helps to understand patients' experience during ICU transition. Empowerment nursing therapeutics integrates the dimensions aimed at meeting patients' needs and expectations during ICU discharge.

Predicting Mortality Following Traumatic Brain Injury or Subarachnoid Hemorrhage: An Analysis of the Validity of Standardized Mortality Ratios Obtained From the APACHE II and ICNARC H-2018 Models

INTRODUCTION

Standardized mortality ratios (SMRs), calculated using the Acute Physiology, Age, Chronic Health Evaluation II (APACHE II) and Intensive Care National Audit and Research Centre H-2018 (ICNARC H-2018 ) risk prediction models, are widely used in UK intensive care units (ICUs) to measure and compare the quality of critical care delivery. Both models incorporate an assumption of Glasgow Coma Score (GCS) if an actual GCS without sedation is not recordable in the first 24 hours after ICU admission. This study assesses the validity of the APACHE II and ICNARC H-2018 models to predict mortality in ICU patients with traumatic brain injury (TBI) or aneurysmal subarachnoid hemorrhage (aSAH) in whom GCS is related to outcomes.

METHODS

In a retrospective analysis, the SMR calculated by the APACHE II and ICNARC H-2018 models for all UK ICU admissions in a 1-year period was compared with calculated SMRs in TBI/aSAH patients and at 3 GCS groups. Data for patients admitted to a single tertiary neurocritical care unit were similarly analyzed.

RESULTS

Both models predicted mortality well for the overall TBI/aSAH population; SMR (95% confidence interval) was 1.00 (0.96-1.04) and 0.99 (0.95-1.03) for the APACHE II and ICNARC H-2018 models, respectively. When analyzed by GCS grouping, both models underpredicted mortality in TBI/aSAH patients with GCS ≤8 (SMR, 1.1 [1.05-1.15]) and "unrecordable" GCS (SMR, 1.88 [1.77-1.99]). Similar findings were identified in the local data analysis.

DISCUSSION

The APACHE II and ICNARC H-2018 models predicted mortality well for the overall TBI/aSAH ICU population but underpredicted mortality when GCS was ≤8 or "unrecordable." This raises questions about the accuracy of these risk prediction models in TBI/aSAH patients and their use to evaluate treatments and compare outcomes between centers.

Quality indicators in intensive care medicine for Germany - fourth edition 2022

The measurement of quality indicators supports quality improvement initiatives. The German Interdisciplinary Society of Intensive Care Medicine (DIVI) has published quality indicators for intensive care medicine for the fourth time now. After a scheduled evaluation after three years, changes in several indicators were made. Other indicators were not changed or only minimally. The focus remained strongly on relevant treatment processes like management of analgesia and sedation, mechanical ventilation and weaning, and infections in the ICU. Another focus was communication inside the ICU. The number of 10 indicators remained the same. The development method was more structured and transparency was increased by adding new features like evidence levels or author contribution and potential conflicts of interest. These quality indicators should be used in the peer review in intensive care, a method endorsed by the DIVI. Other forms of measurement and evaluation are also reasonable, for example in quality management. This fourth edition of the quality indicators will be updated in the future to reflect the recently published recommendations on the structure of intensive care units by the DIVI.

Understanding medication safety involving patient transfer from intensive care to hospital ward: a qualitative sociotechnical factor study

OBJECTIVE

To understand the sociotechnical factors affecting medication safety when intensive care patients are transferred to a hospital ward. Consideration of these medication safety factors would provide a theoretical basis, on which future interventions can be developed and evaluated to improve patient care.

DESIGN

Qualitative study using semistructured interviews of intensive care and hospital ward-based healthcare professionals. Transcripts were anonymised prior to thematic analysis using the London Protocol and Systems Engineering in Patient Safety V.3.0 model frameworks.

SETTING

Four north of England National Health Service hospitals. All hospitals used electronic prescribing in intensive care and hospital ward settings.

PARTICIPANTS

Intensive care and hospital ward healthcare professionals (intensive care medical staff, advanced practitioners, pharmacists and outreach team members; ward-based medical staff and clinical pharmacists).

RESULTS

Twenty-two healthcare professionals were interviewed. We identified 13 factors within five broad themes, describing the interactions that most strongly influenced the performance of the intensive care to hospital ward system interface. The themes were: Complexity of process performance and interactions; Time pressures and considerations; Communication processes and challenges; Technology and systems and Beliefs about consequences for the patient and organisation.

CONCLUSIONS

The complexity of the interactions on the system performance and time dependency was clear. We make several recommendations for policy change and further research based on improving: availability of hospital-wide integrated and functional electronic prescribing systems, patient flow systems, sufficient multiprofessional critical care staffing, knowledge and skills of staff, team performance, communication and collaboration and patient and family engagement.

Time spent on documenting quality indicator data and associations between the perceived burden of documenting these data and joy in work among professionals in intensive care units in the Netherlands: a multicentre cross-sectional survey

OBJECTIVES

The number of indicators used to monitor and improve the quality of care is debatable and may influence professionals' joy in work. We aimed to assess intensive care unit (ICU) professionals' perceived burden of documenting quality indicator data and its association with joy in work.

DESIGN

Cross-sectional survey.

SETTING

ICUs of eight hospitals in the Netherlands.

PARTICIPANTS

Health professionals (ie, medical specialists, residents and nurses) working in the ICU.

MEASUREMENTS

The survey included reported time spent on documenting quality indicator data and validated measures for documentation burden (ie, such documentation being unreasonable and unnecessary) and elements of joy in work (ie, intrinsic and extrinsic motivation, autonomy, relatedness and competence). Multivariable regression analysis was performed for each element of joy in work as a separate outcome.

RESULTS

In total, 448 ICU professionals responded to the survey (65% response rate). The overall median time spent on documenting quality data per working day is 60 min (IQR 30-90). Nurses spend more time documenting these data than physicians (medians of 60 min vs 35 min, p<0.01). Most professionals (n=259, 66%) often perceive such documentation tasks as unnecessary and a minority (n=71, 18%) perceive them as unreasonable. No associations between documentation burden and measures of joy in work were found, except for the negative association between unnecessary documentations and sense of autonomy (β=-0.11, 95% CI -0.21 to -0.01, p=0.03).

CONCLUSIONS

Dutch ICU professionals spend substantial time on documenting quality indicator data they often regard as unnecessary. Despite the lacking necessity, documentation burden had limited impact on joy in work. Future research should focus on which aspects of work are affected by documentation burden and whether diminishing the burden improves joy in work.

The risk assessment tool for intensive care unit readmission: A systematic review and meta-analysis

OBJECTIVE

To review and evaluate existing risk assessment tools for intensive care unitreadmission.

METHODS

Nine electronic databases (Medline, CINAHL, Web of Science, Cochrane Library, Embase, Sino Med, CNKI, VIP, and Wan fang) were systematically searched from their inception to September 2022. Two authors independently extracted data from the literature included. Meta-analysis was performed under the bivariate modeling and summary receiver operating characteristic curve method.

RESULTS

A total of 29 studies were included in this review, among which 11 were quantitatively Meta-analyzed. The results showed Stability and Workload Index for Transfer: Sensitivity = 0.55, Specificity = 0.65, Area under curve = 0.63. And Early warning score: Sensitivity = 0.78, Specificity = 0.83, Area under curve = 0.88. The remaining tools included scores, nomograms, machine learning models, and deep learning models. These studies, with varying reports on thresholds, case selection, data preprocessing, and model performance, have a high risk of bias.

CONCLUSION

We cannot identify a tool that can be used directly in intensive care unit readmission risk assessment. Scores based on early warning score are moderately accurate in predicting readmission, but there is heterogeneity and publication bias that requires model adjustment for local factors such as resources, demographics, and case mix. Machine learning models present a promising modeling technique but have a high methodological bias and require further validation.

IMPLICATIONS FOR CLINICAL PRACTICE

Using reliable risk assessment tools is essential for the early identification of unplanned intensive care unit readmission risk in critically ill patients.  A reliable risk assessment tool must be developed, which is the focus of further research.

Effectiveness of an intensive care telehealth programme to improve process quality (ERIC): a multicentre stepped wedge cluster randomised controlled trial

PURPOSE

Supporting the provision of intensive care medicine through telehealth potentially improves process quality. This may improve patient recovery and long-term outcomes. We investigated the effectiveness of a multifaceted telemedical programme on the adherence to German quality indicators (QIs) in a regional network of intensive care units (ICUs) in Germany.

METHODS

We conducted an investigator-initiated, large-scale, open-label, stepped-wedge cluster randomised controlled trial enrolling adult ICU patients with an expected ICU stay of ≥ 24 h. Twelve ICU clusters in Berlin and Brandenburg were randomly assigned to three sequence groups to transition from control (standard care) to the intervention condition (telemedicine). The quality improvement intervention consisted of daily telemedical rounds guided by eight German acute ICU care QIs and expert consultations. Co-primary effectiveness outcomes were patient-specific daily adherence (fulfilled yes/no) to QIs, assessed by a central end point adjudication committee. Analyses used mixed-effects logistic modelling adjusted for time. This study is completed and registered with ClinicalTrials.gov (NCT03671447).

RESULTS

Between September 4, 2018, and March 31, 2020, 1463 patients (414 treated on control, 1049 on intervention condition) were enrolled at ten clusters, resulting in 14,783 evaluated days. Two randomised clusters recruited no patients (one withdrew informed consent; one dropped out). The intervention, as implemented, significantly increased QI performance for "sedation, analgesia and delirium" (adjusted odds ratio (99.375% confidence interval [CI]) 5.328, 3.395-8.358), "ventilation" (OR 2.248, 1.198-4.217), "weaning from ventilation" (OR 9.049, 2.707-30.247), "infection management" (OR 4.397, 1.482-13.037), "enteral nutrition" (OR 1.579, 1.032-2.416), "patient and family communication" (OR 6.787, 3.976-11.589), and "early mobilisation" (OR 3.161, 2.160-4.624). No evidence for a difference in adherence to "daily multi-professional and interdisciplinary clinical visits" between both conditions was found (OR 1.606, 0.780-3.309). Temporal trends related and unrelated to the intervention were detected. 149 patients died during their index ICU stay (45 treated on control, 104 on intervention condition).

CONCLUSION

A telemedical quality improvement program increased adherence to seven evidence-based German performance indicators in acute ICU care. These results need further confirmation in a broader setting of regional, non-academic community hospitals and other healthcare systems.

Development of a quality indicator set to measure and improve quality of ICU care in low- and middle-income countries

PURPOSE

To develop a set of actionable quality indicators for critical care suitable for use in low- or middle-income countries (LMICs).

METHODS

A list of 84 candidate indicators compiled from a previous literature review and stakeholder recommendations were categorised into three domains (foundation, process, and quality impact). An expert panel (EP) representing stakeholders from critical care and allied specialties in multiple low-, middle-, and high-income countries was convened. In rounds one and two of the Delphi exercise, the EP appraised (Likert scale 1-5) each indicator for validity, feasibility; in round three sensitivity to change, and reliability were additionally appraised. Potential barriers and facilitators to implementation of the quality indicators were also reported in this round. Median score and interquartile range (IQR) were used to determine consensus; indicators with consensus disagreement (median < 4, IQR ≤ 1) were removed, and indicators with consensus agreement (median ≥ 4, IQR ≤ 1) or no consensus were retained. In round four, indicators were prioritised based on their ability to impact cost of care to the provider and recipient, staff well-being, patient safety, and patient-centred outcomes.

RESULTS

Seventy-one experts from 30 countries (n = 45, 63%, representing critical care) selected 57 indicators to assess quality of care in intensive care unit (ICU) in LMICs: 16 foundation, 27 process, and 14 quality impact indicators after round three. Round 4 resulted in 14 prioritised indicators. Fifty-seven respondents reported barriers and facilitators, of which electronic registry-embedded data collection was the biggest perceived facilitator to implementation (n = 54/57, 95%) Concerns over burden of data collection (n = 53/57, 93%) and variations in definition (n = 45/57, 79%) were perceived as the greatest barrier to implementation.

CONCLUSION

This consensus exercise provides a common set of indicators to support benchmarking and quality improvement programs for critical care populations in LMICs.

Reorganization of Intensive Care Units for the COVID-19 pandemic: effects on nursing sensitive outcomes

BACKGROUND

Since the first months of 2020 COVID-19 patients who were seriously ill due to the development of ARDS, required admission to the intensive care unit to ensure potentially life-saving mechanical ventilation and support for vital functions. To cope with this emergency, an extremely rapid reorganization of premises, services and staff, to dedicate an entire intensive care unit exclusively to SARS-CoV-2 patients and increasing the number of beds was essential. The aim of the study was to evaluate the effects of reorganization of the COVID-19 intensive care unit in terms of nursing sensitive outcomes.

METHODS

a retrospective observational study was conducted to compare nursing sensitive outcomes between pre-COVID period and COVID period.

RESULTS

Falls (0.0 and 0.4%, respectively), physical restraint (1.8 and 1.1%, respectively), and pressure ulcers (8.0 and 3.0%, respectively) were similar in the COVID and in the pre-COVID group. After adjusting for gender, age, BMI, and number of comorbidities, the incidence of bloodstream infections was significantly higher in the COVID group than in the pre-COVID group. There were no statistically significant differences in the incidence between the two groups regarding other evaluated outcomes.

CONCLUSION

The selected nursing sensitive outcomes maintained similar values in the pre-COVID and COVID patient groups. Healthcare-related infections rate must be considered an important alarm signal of quality of nursing care especially in conditions of excessive workload, stress and the presence of less experienced staff increase.

Medication-related interventions to improve medication safety and patient outcomes on transition from adult intensive care settings: a systematic review and meta-analysis

BACKGROUND

Patients recovering from an episode in an intensive care unit (ICU) frequently experience medication errors on transition to the hospital ward. Structured handover recommendations often underestimate the challenges and complexity of ICU patient transitions. For adult ICU patients transitioning to a hospital ward, it is currently unclear what interventions reduce the risks of medication errors.The aims were to examine the impact of medication-related interventions on medication and patient outcomes on transition from adult ICU settings and identify barriers and facilitators to implementation.

METHODS

The systematic review protocol was preregistered on PROSPERO. Six electronic databases were searched until October 2020 for controlled and uncontrolled study designs that reported medication-related (ie, de-prescribing; medication errors) or patient-related outcomes (ie, mortality; length of stay). Risk of bias (RoB) assessment used V.2.0 and ROBINS-I Cochrane tools. Where feasible, random-effects meta-analysis was used for pooling the OR across studies. The quality of evidence was assessed by Grading of Recommendations, Assessment, Development and Evaluations.

RESULTS

Seventeen studies were eligible, 15 (88%) were uncontrolled before-after studies. The intervention components included education of staff (n=8 studies), medication review (n=7), guidelines (n=6), electronic transfer/handover tool or letter (n=4) and medicines reconciliation (n=4). Overall, pooled analysis of all interventions reduced risk of inappropriate medication continuation at ICU discharge (OR=0.45 (95% CI 0.31 to 0.63), I2=55%, n=9) and hospital discharge (OR=0.39 (95% CI 0.2 to 0.76), I2=75%, n=9). Multicomponent interventions, based on education of staff and guidelines, demonstrated no significant difference in inappropriate medication continuation at the ICU discharge point (OR 0.5 (95% CI 0.22 to 1.11), I2=62%, n=4), but were very effective in increasing de-prescribing outcomes on hospital discharge (OR 0.26 (95% CI 0.13 to 0.55), I2=67%, n=6)). Facilitators to intervention delivery included ICU clinical pharmacist availability and participation in multiprofessional ward rounds, while barriers included increased workload associated with the discharge intervention process.

CONCLUSIONS

Multicomponent interventions based on education of staff and guidelines were effective at achieving almost four times more de-prescribing of inappropriate medication by the time of patient hospital discharge. Based on the findings, practice and policy recommendations are made and guidance is provided on the need for, and design of theory informed interventions in this area, including the requirement for process and economic evaluations.

Putting measurement on a diet: development of a core set of indicators for quality improvement in the ICU using a Delphi method

Background

The number and efficacy of indicators used to monitor and improve the quality of care in Intensive Care Units (ICU) is debatable. This study aimed to select a consensus-based core set of indicators for effective quality improvement in the ICU.

Methods

A Delphi study with a panel of intensivists, ICU nurses, and former ICU patients or relatives (n = 34) from general, teaching, and academic hospitals. Panelists completed a questionnaire in which they scored 69 preselected quality indicators on relevance using a nine-point Likert scale. Indicators were categorized using the rated relevance score into: ‘accepted, ‘equivocal’ and ‘excluded’. Questionnaire results were discussed in focus groups to reach consensus on the final set.

Results

Response rates for the questionnaire and focus groups were 100 and 68%, respectively. Consensus was reached on a final set of 17 quality indicators including patient reported outcome measures (PROMs) and patient reported experience measures (PREMs). Other quality indicators relate to the organization and outcome of ICU care, including safety culture, ICU standardized mortality ratio, and the process indicator ‘learning from and improving after serious incidents’.

Conclusions

ICU clinicians and former patients and relatives developed a consensus-based core set of ICU quality indicators that is relatively short but comprehensive and particularly tailored to end-users needs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08236-3.

Delphi study to derive expert consensus on a set of criteria to evaluate discharge readiness for adult ICU patients to be discharged to a general ward-European perspective

Background/purpose

Discharge decisions in Intensive Care Unit (ICU) patients are frequently taken under pressure to free up ICU beds. In the absence of established guidelines, the evaluation of discharge readiness commonly underlies subjective judgements. The challenge is to come to the right decision at the right time for the right patient. A premature care transition puts patients at risk of readmission to the ICU. Delayed discharge is a waste of resources and may result in over-treatment and suboptimal patient flow. More objective decision support is required to assess the individual patient’s discharge readiness but also the current care capabilities of the receiving unit.

Methods

In a modified online Delphi process, an international panel of 27 intensive care experts reached consensus on a set of 28 intensive care discharge criteria. An initial evidence-based proposal was developed further through the panelists’ edits, adding, comments and voting over a course of 5 rounds. Consensus was defined as achieved when ≥ 90% of the experts voted for a given option on the Likert scale or in a multiple-choice survey. Round 1 to 3 focused on inclusion and exclusion of the criteria based on the consensus threshold, where round 3 was a reiteration to establish stability. Round 4 and 5 focused on the exact phrasing, values, decision makers and evaluation time frames per criterion.

Results

Consensus was reached on a standard set of 28 ICU discharge criteria for adult ICU patients, that reflect the patient’s organ systems ((respiratory (7), cardiovascular (9), central nervous (1), and urogenital system (2)), pain (1), fluid loss and drainages (1), medication and nutrition (1), patient diagnosis, prognosis and preferences (2) and institution-specific criteria (4). All criteria have been specified in a binary decision metric (fit for ICU discharge vs. needs further intensive therapy/monitoring), with consented value calculation methods where applicable and a criterion importance rank with “mandatory to be met” flags and applicable exceptions.

Conclusion

For a timely identification of stable intensive care patients and safe and efficient care transitions, a standardized discharge readiness evaluation should be based on patient factors as well as organizational boundary conditions and involve multiple stakeholders.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08160-6.

Neurocritical Care Performance Measures Derived from Electronic Health Record Data are Feasible and Reveal Site-Specific Variation: A CHoRUS Pilot Project

BACKGROUND

We evaluated the feasibility and discriminability of recently proposed Clinical Performance Measures for Neurocritical Care (Neurocritical Care Society) and Quality Indicators for Traumatic Brain Injury (Collaborative European NeuroTrauma Effectiveness Research in TBI; CENTER-TBI) extracted from electronic health record (EHR) flowsheet data.

METHODS

At three centers within the Collaborative Hospital Repository Uniting Standards (CHoRUS) for Equitable AI consortium, we examined consecutive neurocritical care admissions exceeding 24 h (03/2015-02/2020) and evaluated the feasibility, discriminability, and site-specific variation of five clinical performance measures and quality indicators: (1) intracranial pressure (ICP) monitoring (ICPM) within 24 h when indicated, (2) ICPM latency when initiated within 24 h, (3) frequency of nurse-documented neurologic assessments, (4) intermittent pneumatic compression device (IPCd) initiation within 24 h, and (5) latency to IPCd application. We additionally explored associations between delayed IPCd initiation and codes for venous thromboembolism documented using the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) system. Median (interquartile range) statistics are reported. Kruskal-Wallis tests were measured for differences across centers, and Dunn statistics were reported for between-center differences.

RESULTS

A total of 14,985 admissions met inclusion criteria. ICPM was documented in 1514 (10.1%), neurologic assessments in 14,635 (91.1%), and IPCd application in 14,175 (88.5%). ICPM began within 24 h for 1267 (83.7%), with site-specific latency differences among sites 1-3, respectively, (0.54 h [2.82], 0.58 h [1.68], and 2.36 h [4.60]; p < 0.001). The frequency of nurse-documented neurologic assessments also varied by site (17.4 per day [5.97], 8.4 per day [3.12], and 15.3 per day [8.34]; p < 0.001) and diurnally (6.90 per day during daytime hours vs. 5.67 per day at night, p < 0.001). IPCds were applied within 24 h for 12,863 (90.7%) patients meeting clinical eligibility (excluding those with EHR documentation of limiting injuries, actively documented as ambulating, or refusing prophylaxis). In-hospital venous thromboembolism varied by site (1.23%, 1.55%, and 5.18%; p < 0.001) and was associated with increased IPCd latency (overall, 1.02 h [10.4] vs. 0.97 h [5.98], p = 0.479; site 1, 2.25 h [10.27] vs. 1.82 h [7.39], p = 0.713; site 2, 1.38 h [5.90] vs. 0.80 h [0.53], p = 0.216; site 3, 0.40 h [16.3] vs. 0.35 h [11.5], p = 0.036).

CONCLUSIONS

Electronic health record-derived reporting of neurocritical care performance measures is feasible and demonstrates site-specific variation. Future efforts should examine whether performance or documentation drives these measures, what outcomes are associated with performance, and whether EHR-derived measures of performance measures and quality indicators are modifiable.

Development of a quality assurance tool for intensive care units in Lebanon during the COVID-19 pandemic

BACKGROUND

During the coronavirus disease (COVID-19) pandemic, low- and middle-income countries have rapidly scaled up intensive care unit (ICU) capacities. Doing this without monitoring the quality of care poses risks to patient safety and may negatively affect patient outcomes. While monitoring the quality of care is routine in high-income countries, it is not systematically implemented in most low- and middle-income countries. In this resource-scarce context, there is a paucity of feasibly implementable tools to monitor the quality of ICU care. Lebanon is an upper middle-income country that, during the autumn and winter of 2020-1, has had increasing demands for ICU beds for COVID-19. The World Health Organization has supported the Ministry of Public Health to increase ICU beds at public hospitals by 300%, but no readily available tool to monitor the quality of ICU care was available.

OBJECTIVE

The objective with this study was to describe the process of rapidly developing and implementing a tool to monitor the quality of ICU care at public hospitals in Lebanon.

METHODS

In the midst of the escalating pandemic, we applied a systematic approach to develop a realistically implementable quality assurance tool. We conducted a literature review, held expert meetings and did a pilot study to select among identified quality indicators for ICU care that were feasible to collect during a 1-hour ICU visit. In addition, a limited set of the identified indicators that were quantifiable were specifically selected for a scoring protocol to allow comparison over time as well as between ICUs.

RESULTS

A total of 44 quality indicators, which, using different methods, could be collected by an external person, were selected for the quality of care tool. Out of these, 33 were included for scoring. When tested, the scores showed a large difference between hospitals with low versus high resources, indicating considerable variation in the quality of care.

CONCLUSIONS

The proposed tool is a promising way to systematically assess and monitor the quality of care in ICUs in the absence of more advanced and resource-demanding systems. It is currently in use in Lebanon. The proposed tool may help identifying quality gaps to be targeted and can monitor progress. More studies to validate the tool are needed.

Quality metrics and outcomes among critically ill patients in China: results of the national clinical quality control indicators for critical care medicine survey 2015-2019

BACKGROUND

It is crucial to improve the quality of care provided to ICU patient, therefore a national survey of the medical quality of intensive care units (ICUs) was conducted to analyze adherence to quality metrics and outcomes among critically ill patients in China from 2015 to 2019.

METHODS

This was an ICU-level study based on a 15-indicator online survey conducted in China. Considering that ICU care quality may vary between secondary and tertiary hospitals, direct standardization was adopted to compare the rates of ICU quality indicators among provinces/regions. Multivariate analysis was performed to identify potential factors for in-hospital mortality and factors related to ventilator-associated pneumonia (VAP), catheter-related bloodstream infections (CRBSIs), and catheter-associated urinary tract infections (CAUTIs).

RESULTS

From the survey, the proportions of structural indicators were 1.83% for the number of ICU inpatients relative to the total number of inpatients, 1.44% for ICU bed occupancy relative to the total inpatient bed occupancy, and 51.08% for inpatients with Acute Physiology and Chronic Health Evaluation II scores ≥15. The proportions of procedural indicators were 74.37% and 76.60% for 3-hour and 6-hour surviving sepsis campaign bundle compliance, respectively, 62.93% for microbiology detection, 58.24% for deep vein thrombosis prophylaxis, 1.49% for unplanned endotracheal extubations, 1.99% for extubated inpatients reintubated within 48 hours, 6.38% for unplanned transfer to the ICU, and 1.20% for 48-hour ICU readmission. The proportions of outcome indicators were 1.28‰ for VAP, 3.06‰ for CRBSI, 3.65‰ for CAUTI, and 10.19% for in-hospital mortality. Although the indicators varied greatly across provinces and regions, the treatment level of ICUs in China has been stable and improved based on various quality control indicators in the past 5 years. The overall mortality rate has dropped from 10.19% to approximately 8%.

CONCLUSIONS

The quality indicators of medical care in China's ICUs are heterogeneous, which is reflected in geographic disparities and grades of hospitals. This study is of great significance for improving the homogeneity of ICUs in China.

The Austrian ICU survey : A questionnaire-based evaluation of intensive care medicine in Austria

Background

While structures of intensive care medicine in Austria are well defined, data on organisational and medical practice in intensive care units (ICUs) have not been systematically evaluated.

Methods

In this explorative survey, organisational and medical details of ICUs in Austria were collected using an online questionnaire consisting of 147 questions.

Results

Out of 249 registered ICUs 73 (29.3%) responded, 60 were adult, 10 pediatric/neonatal ICUs and 19, 25 and 16 ICUs were located in level I, II and III hospitals, respectively. Of the respondents 89% reported that the ICU director was board-certified in intensive care medicine. Consultants were constantly present in 78% of ICUs during routine working hours and in 45% during nights and weekends. The nurse:bed ratio varied between 1:1 and 1:2 in 74% during day shifts and 60% during night shifts. Routine physiotherapist rounds were reported to take place daily except weekends in 67% of ICUs. Common monitoring techniques were reported to be in routine or occasional use in 85% and 83% of ICUs, respectively. The majority of ICUs provided daily visiting hours ranging between 2–12 h. Waiting rooms for relatives were available in 66% and an electronic documentation system in 66% of ICUs. Written protocols were available in 70% of ICUs.

Conclusion

The Austrian ICU survey suggests that ICUs in Austria are clearly structured, well-organized and well-equipped and have a high nurse:bed ratio. In view of the relatively low return rate we cannot exclude that a selection bias has led to overestimation of the survey findings.

Supplementary Information

The online version of this article (10.1007/s00508-021-02002-x) contains supplementary material, which is available to authorized users.

Nursing workload on the day of discharge from the intensive care unit is associated with readmission

PURPOSE

To verify whether there is an association between the Nursing Activities Score (NAS) on the day of discharge from the intensive care unit and readmission..

MATERIALS AND METHODS

A retrospective cohort study of all patients admitted to the intensive care unit of Hospital Ernesto Dornelles, Porto Alegre, Brazil, who were discharged to the ward from October 2018 to December 2019. We collected demographic and clinical variables of the patients and the Nursing Activities Scoreon the day of discharge. Patients were followed up until the day of hospital discharge or death.

RESULTS

We included 1045 patients in the final sample. One hundred eighty-eight (18.0%) patients were readmitted, in addition there were two (0.2%) unexpected deaths that occurred in the ward. The median NAS was 59.9 (50.9-67.3), which was higher in the bivariate analysis in patients who were readmitted (64.0, 55.7-71.4) than in patients who were not readmitted (58.7, 49.7-66.1) (p < 0.001). Patients with a Nursing Activities Score  ≥ 60.0 and < 60.0 had rates of readmission of 23.4% and 12.7%, respectively (p < 0.001). After multivariable adjustment, the Nursing Activities Score at discharge maintained an association with readmission. In addition, in the Cox regression, the Nursing Activities Score as a dichotomous variable was independently associated with readmission (adjusted HR 1.560; CI 1.146-2.125; p = 0.005).

CONCLUSIONS

We found that the nursing workload, assessed by the Nursing Activities Score at the time of discharge from the intensive care unit, was associated with risk of readmission..

White Paper on Early Critical Care Services in Low Resource Settings

This White Paper has been formally accepted for support by the International Federation for Emergency Medicine (IFEM) and by the World Federation of Intensive and Critical Care (WFICC), put forth by a multi-specialty group of intensivists and emergency medicine providers from low- and low-middle-income countries (LMICs) and high-income countries (HiCs) with the aim of 1) defining the current state of caring for the critically ill in low-resource settings (LRS) within LMICs and 2) highlighting policy options and recommendations for improving the system-level delivery of early critical care services in LRS.

LMICs have a high burden of critical illness and worse patient outcomes than HICs, hence, the focus of this White Paper is on the care of critically ill patients in the early stages of presentation in LMIC settings. In such settings, the provision of early critical care is challenged by a fragmented health system, costs, a health care workforce with limited training, and competing healthcare priorities.

Early critical care services are defined as the early interventions that support vital organ function during the initial care provided to the critically ill patient—these interventions can be performed at any point of patient contact and can be delivered across diverse settings in the healthcare system and do not necessitate specialty personnel.

Currently, a single “best” care delivery model likely does not exist in LMICs given the heterogeneity in local context; therefore, objective comparisons of quality, efficiency, and cost-effectiveness between varying models are difficult to establish. While limited, there is data to suggest that caring for the critically ill may be cost effective in LMICs, contrary to a widely held belief. Drawing from locally available resources and context, strengthening early critical care services in LRS will require a multi-faceted approach, including three core pillars: education, research, and policy.

Education initiatives for physicians, nurses, and allied health staff that focus on protocolized emergency response training can bridge the workforce gap in the short-term; however, each country’s current human resources must be evaluated to decide on the duration of training, who should be trained, and using what curriculum.

Understanding the burden of critical Illness, best practices for resuscitation, and appropriate quality metrics for different early critical care services implementation models in LMICs are reliant upon strengthening the regional research capacity, therefore, standard documentation systems should be implemented to allow for registry use and quality improvement.

Policy efforts at a local, national and international level to strengthen early critical care services should focus on funding the building blocks of early critical care services systems and promoting the right to access early critical care regardless of the patient’s geographic or financial barriers. Additionally, national and local policies describing ethical dilemmas involving the withdrawal of life-sustaining care should be developed with broad stakeholder representation based on local cultural beliefs as well as the optimization of limited resources.

Multifaceted intervention including Facebook-groups to improve guideline-adherence in ICU: A quasi-experimental interrupted time series study

BACKGROUND

The impact of social media, with its speed, reach and accessibility, in interventions aimed to improve adherence to guidelines such as assessment of Pain, Agitation/Sedation and Delirium (PAD) in intensive care is not described. Therefore, the primary objective of this quality improvement study was to evaluate the impact of a multifaceted intervention including audit and feedback of quality indicators (QI) via Facebook-groups, educational events and engagement of opinion leaders on adherence to PAD-guidelines in four ICUs.

METHODS

A quasi-experimental interrupted time series study with eight monthly data points in the two phases Before and Intervention was designed. Proportion of nursing shifts with documented PAD-assessment (PAD-QIs) were retrieved from the electronical medical chart from included adult ICU patient-stays in four participating ICUs. Difference between the two time periods was assessed using generalised mixed model for repeated measures with unstructured covariance matrix, and presented as Beta (B) with 95% confidence interval (CI).

RESULTS

Finally, 1049 ICU patient-stays were analysed; 534 in Before and 515 in Intervention. All three PAD-QIs significantly increased in Intervention by 31% (B = 30.7, 95%CI [25.7 to 35.8]), 26% (B = 25.8, 95%CI [19.4 to 32.2]) and 34% (B = 33.9, 95%CI [28.4 to 39.4]) in pain, agitation/sedation and delirium, respectively.

CONCLUSION

A multifaceted intervention including use of Facebook-groups was associated with improved guideline-adherence in four ICUs, as measured with process PAD-QIs of PAD assessment. Further research on use of social media to improve guideline adherence is warranted, particularly as social distancing impacts clinical education and training and new approaches are needed.

Evaluation of quality indicators for nutrition and metabolism in critically ill patients: role of the pharmacist

OBJECTIVE

To assess compliance in a Spanish intensive care unit (ICU) with 8 of the 13 quality indicators of the Spanish Society of Intensive Medicine and Coronary Units (Sociedad Española de Medicina Intensiva y Unidades Coronarias, SEMICyUC) related to nutrition and metabolism in critically ill patients.

PATIENTS AND METHODS

The study included all patients over 18 years of age with an ICU stay of >48 hours between January and May 2019. The pharmacist was integrated into the daily activity of the multidisciplinary team of a 20-bed ICU to monitor and carry out the control of the quality indicators of the SEMICyUC. Studied indicators refer to: nutritional risk assessment and nutritional status (three indicators), glycaemic control, calculation of calorie-protein requirements, and use of early enteral nutrition or adequate parenteral nutrition. Compliance with each indicator was measured as the percentage of patients.

RESULTS

110 patients were included and 73 (66.4%) were male. Compliance results were: blood glucose range (90.7%), severe hypoglycaemia (0%), identification of patients at nutritional risk (58.2%) or with possible refeeding syndrome (8.9%), assessment of nutritional status at admission (58.2%), calculation of calorie-protein requirements (77.8%), early enteral nutrition (96.4%), and adequate use of parenteral nutrition (37.8%) CONCLUSION: Compliance with indicators related to glycaemic control and artificial nutrition (enteral and parenteral nutrition) was higher than reference standards, but there is a need to improve compliance with indicators related to nutritional risk and status at ICU admission. The hospital pharmacist integrated into the ICU multidisciplinary team can add value to the nutrition monitoring and quality indicators of the nutritional process of the critical patient, providing safe and effective nutritional therapy to patients.

Actionable processes of care important to patients and family who experienced a prolonged intensive care unit stay: Qualitative interview study

AIM

To use positive deviance to identify actionable processes of care that may improve outcomes and experience from the perspectives of prolonged intensive care unit (ICU) stay survivors and family members.

DESIGN

Prospective qualitative interview study in two geographically distant settings: Canada (2018/19) and the United Kingdom (2019/20).

METHODS

Patient and family participant inclusion criteria comprised: aged over 18 years, ICU stay in last 2 years of over 7 days, able to recall ICU stay and provided informed consent. We conducted semi-structured in-person or telephone interviews. Data were analysed using a positive deviance approach.

RESULTS

We recruited 29 participants (15 Canadian; 14 UK). Of these, 11 were survivors of prolonged ICU stay and 18 family members. We identified 22 actionable processes (16 common to Canadian and UK participants, 4 Canadian only and 2 UK only). We grouped processes under three themes: physical and functional recovery (nine processes), patient psychological well-being (seven processes) and family relations (six processes). Most commonly identified physical/functional processes were regular physiotherapy, and fundamental hygiene and elimination care. For patient psychological well-being: normalizing the environment and routines, and alleviating boredom and loneliness. For family relations: proactive communication, flexible family visiting and presence with facilities for family. Our positive deviance analysis approach revealed that incorporation of these actionable processes into clinical practice was the exception as opposed to the norm perceived driven by individual acts of kindness and empathy as opposed to standardized processes.

CONCLUSION

Actionable processes of care important to prolonged ICU stay survivors and family members differ from those frequently used in ICU quality improvement (QI) tools.

IMPACT

Our study emphasizes the need to develop QI tools that standardize delivery of actionable processes important to patients and families experiencing a prolonged ICU stay. As the largest healthcare professional group, nurses can play an essential role in leading this.

Factors influencing family member perspectives on safety in the intensive care unit: a systematic review

PURPOSE

Patient safety has developed as a strong marker for healthcare quality. Safety matters are important in the intensive care unit (ICU) where complex clinical decisions are made, intensive technology is used, and families hold a unique role. The aim of this review was to identify and describe factors that influence family member's perceptions of safety in the adult ICU.

DATA SOURCES

Searches were conducted between September and November 2018 and repeated in July 2020 using CINAHL, MEDLINE (EBSCO), PubMed and PsycINFO databases.

STUDY SELECTION

Published primary studies undertaken in adult ICUs and involving adult family member participants exploring safety or feeling safe. No date restrictions were applied.

DATA EXTRACTION

A data extraction form collected information about sample, study design, data collection methods and results from each paper. Methodological quality was assessed using the QualSyst tools for qualitative and quantitative studies. Narrative synthesis was undertaken.

RESULTS OF DATA SYNTHESIS

Twenty papers were included with 11 papers published since 2010. The majority of papers reported on qualitative studies (n = 16). Four factors were identified that influenced whether family members felt that the patient was safe in ICU: family visiting, information and communication, caring and professional competence.

CONCLUSION

In detailing specific practices that make families feel safe and unsafe in ICU, these review findings provide a structure for clinicians, educators and researchers to inform future work and gives opportunity for the family role in patient safety to be reconsidered.

Costs and Cost-Utility of Critical Care and Subsequent Health Care: A Multicenter Prospective Study

OBJECTIVES

The number of critical care survivors is growing, but their long-term outcomes and resource use are poorly characterized. Estimating the cost-utility of critical care is necessary to ensure reasonable use of resources. The objective of this study was to analyze the long-term resource use and costs, and to estimate the cost-utility, of critical care.

DESIGN

Prospective observational study.

SETTING

Seventeen ICUs providing critical care to 85% of the Finnish adult population.

PATIENTS

Adult patients admitted to any of 17 Finnish ICUs from September 2011 to February 2012, enrolled in the Finnish Acute Kidney Injury (FINNAKI) study, and matched hospitalized controls from the same time period.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We primarily assessed total 3-year healthcare costs per quality-adjusted life-years at 3 years. We also estimated predicted life-time quality-adjusted life-years and described resource use and costs. The costing year was 2016. Of 2,869 patients, 1,839 (64.1%) survived the 3-year follow-up period. During the first year, 1,290 of 2,212 (58.3%) index episode survivors were rehospitalized. Median (interquartile range) 3-year cumulative costs per patient were $49,200 ($30,000-$85,700). ICU costs constituted 21.4% of the total costs during the 3-year follow-up. Compared with matched hospital controls, costs of the critically ill remained higher throughout the follow-up. Estimated total mean (95% CI) 3-year costs per 3-year quality-adjusted life-years were $46,000 ($44,700-$48,500) and per predicted life-time quality-adjusted life-years $8,460 ($8,060-8,870). Three-year costs per 3-year quality-adjusted life-years were $61,100 ($57,900-$64,400) for those with an estimated risk of in-hospital death exceeding 15% (based on the Simplified Acute Physiology Score II).

CONCLUSIONS

Healthcare resource use was substantial after critical care and remained higher compared with matched hospital controls. Estimated cost-utility of critical care in Finland was of high value.

Adverse Events After Transition From ICU to Hospital Ward: A Multicenter Cohort Study

OBJECTIVES

To examine adverse events and associated factors and outcomes during transition from ICU to hospital ward (after ICU discharge).

DESIGN

Multicenter cohort study.

SETTING

Ten adult medical-surgical Canadian ICUs.

PATIENTS

Patients were those admitted to one of the 10 ICUs from July 2014 to January 2016.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Two ICU physicians independently reviewed progress and consultation notes documented in the medical record within 7 days of patient's ICU discharge date to identify and classify adverse events. The adverse event data were linked to patient characteristics and ICU and ward physician surveys collected during the larger prospective cohort study. Analyses were conducted using multivariable logistic regression. Of the 451 patients included in the study, 84 (19%) experienced an adverse event, the majority (62%) within 3 days of transfer from ICU to hospital ward. Most adverse events resulted only in symptoms (77%) and 36% were judged to be preventable. Patients with adverse events were more likely to be readmitted to the ICU (odds ratio, 5.5; 95% CI, 2.4-13.0), have a longer hospital stay (mean difference, 16.1 d; 95% CI, 8.4-23.7) or die in hospital (odds ratio, 4.6; 95% CI, 1.8-11.8) than those without an adverse event. ICU and ward physician predictions at the time of ICU discharge had low sensitivity and specificity for predicting adverse events, ICU readmissions, and hospital death.

CONCLUSIONS

Adverse events are common after ICU discharge to hospital ward and are associated with ICU readmission, increased hospital length of stay and death and are not predicted by ICU or ward physicians.