Critical Care Information System Research Articles

Continuous Blood Pressure Indices During the First 72 Hours and Functional Outcome in Patients with Spontaneous Intracerebral Hemorrhage.

Management of intracerebral hemorrhage (ICH) is challenged by limited therapeutic options and a complex relationship between blood pressure (BP) dynamics, especially BP variability (BPV) and ICH outcome. In an exploratory analysis of prospectively collected data on consecutive patients with nontraumatic ICH between 2015 and 2020, continuous BP accessed via an arterial line extracted from the Intellispace Critical Care and Anesthesia information system (Philips Healthcare) was analyzed over the first 72 h post admission. Arterial lines were used as part of standard clinical practice in the intensive care, ensuring high fidelity and real-time data essential for acute care settings. BPV was assessed through successive variation (SV), standard deviation (SD), and coefficient of variation using all available BP measurements. Multivariate regression models were applied to evaluate the association between BPV indices and functional outcome at 3 months. Among 261 patients (mean age 69.6 ± 15.2 years, 47.9% female, median National Institutes of Health Stroke Scale [NIHSS] score 6 [interquartile range 2-12]) analyzed, lower systolic BP upon admission (< 140 mm Hg) and lower systolic BPV were significantly associated with favorable outcome, whereas higher diastolic BPV correlated with improved outcomes. In the multivariate analysis, diastolic BPV (SD, SV) within the first 72 h post admission emerged as an independent predictor of good functional outcome (modified Rankin Scale score < 3; odds ratio 1.123, 95% confidence interval CI 1.008-1.184, p = 0.035), whereas systolic BPV (SD) showed a negative association. Patients with better outcomes also exhibited distinct clinical characteristics, including younger age, lower median NIHSS scores, and less prevalence of anticoagulation therapy upon admission. This study shows the prognostic value of BPV in the acute phase of ICH. Lower systolic BPV (SD) and higher diastolic BPV (SD, SV) were associated with better functional outcomes, challenging traditional BP management strategies. These findings might help to tailor a personalized BP management in ICH.

Heart Rate Variability and Functional Outcomes of Patients with Spontaneous Intracerebral Hemorrhage.

The relationship between heart rate variability (HRV) changes potentially indicating autonomic dysregulation following spontaneous intracerebral hemorrhage (ICH) and functional outcome has not yet been fully elucidated. This study investigated the effects of HRV during the initial 96 h after admission on 90-day functional outcome in ICH patients. We included patients with spontaneous ICH in a prospective cohort single-center study. Continuous HR data were retrieved from the Intellispace Critical Care and Anesthesia information system (Philips Healthcare) and analyzed within the following time intervals: 0-2, 0-8, 0-12, 0-24, 0-48, 0-72, and 8-16, 16-24, 24-48, 48-72, 72-96 h after admission. HRV was determined from all available HR values by calculating the successive variability (SV), standard deviation (SD), and coefficient of variation (CV). Low HRV was set as SD ≤ 11.4 ms, and high HRV as SD > 11.4 ms. The clinical severity of ICH was assessed using the National Institutes of Health Stroke Scale (NIHSS) and functional outcome using the modified Rankin Scale (mRS). Good functional outcome was defined as mRS 0-2. The cohort included 261 ICH patients (mean age ± SD 69.6 ± 16.5 years, 48.7% female, median NIHSS 6 (2, 12), median ICH score 1 (0, 2), of whom 106 (40.6%) had good functional outcome. All patients had the lowest HRV at admission, which increased during the first two days. Comparing ICH patients with low HRV (n = 141) and high HRV (n = 118), those with good outcome showed significantly lower HRV during the first three days (0-72 h: HRV SD good outcome 10.6 ± 3.5 ms vs. poor outcome 12.0 ± 4.0 ms; p = 0.004). Logistic regression revealed that advanced age, high premorbid mRS, and high NIHSS at admission were significant predictors of poor functional outcome, while reduced SD of HRV showed a non-significant trend towards good functional outcome (0-72 h: OR 0.898; CI 0.800-1.008; p = 0.067). Our results indicate autonomic dysfunction with sympathetic hyperactivity after spontaneous ICH, as reflected by the evidence of the lower HRV in the first days. Initially increased sympathetic tone appears to have a protective effect, as suggested by the comparatively lower HRV in patients with good functional outcome at the first days.

Continuous arterial blood pressure indices and early hematoma expansion in patients with spontaneous intracerebral hemorrhage

BackgroundBlood pressure variability (BPV) and its potential association with early hematoma expansion (HE) in intracerebral hemorrhage (ICH) remains to be fully elucidated. Our study explores the potential link between BPV within the first 24 h after admission and HE in ICH. MethodsIn a prospective cohort single-center study, we analyzed consecutive patients with spontaneous ICH. Continuous BP data via an arterial line extracted from the Intellispace Critical Care and Anesthesia information system (Philips Healthcare) were analyzed over 0–2, 0–8, 0–12, and 0–24 h intervals post-admission. BPV was assessed through successive variability (SV), standard deviation (SD), and coefficient of variation (CV) using all available BP measurements. Early HE was defined as an absolute [≥ 6 ml] or relative [≥ 33 %] increase in ICH volume on 24-hours follow-up brain imaging. Secondary endpoints were the influence of BP on admission and other potential risk factors for HE. ResultsAmong 305 ICH-patients (mean age ± SD 70.1 ± 14.9 years, 47.9 % female, median NIHSS 6 (3, 13), median ICH score 1 (1, 2)), 41 (13.4 %) experienced HE. HE-patients had higher NIHSS (p = 0.015), ICH-score (p = 0.005), ICH volume (p < 0.001) and higher pre-anticoagulation treatment (p = 0.004) on admission. There was no difference in BPV comparing ICH-patients with HE to those without. However, patients with HE had significantly lower diastolic BP (76.6 ± 14.8 vs. 86.3 ± 19.7 mmHg, p = 0.005) and MAP (103.2 ± 22.4 vs. 112.2 ± 22.6, p = 0.027) on admission. This pattern of lower diastolic BP persisted across the first 24 h. Logistic regression revealed larger ICH volume and pre-existing anticoagulation as significant predictors of HE, with higher initial diastolic BP reducing HE risk. Hemorrhages ≥ 30 cm3 showed significantly lower initial diastolic BP, MAP, and BPV across all time frames compared to ICH < 30 cm3. ConclusionsBPV within the first 24 h was not associated with HE. Lower diastolic BP on admission, anticoagulation use, and larger ICH volume are potential predictors for HE. However, larger hemorrhage size (>30 cm3) experienced lower absolute BP and BPV indices and worse clinical outcomes. These findings suggest a nuanced relationship between BP dynamics and ICH severity, underscoring the need for individualized BP management in acute ICH care. Further research is necessary to explore these relationships and optimize treatment strategies.

Retracted: The Design of Critical Care Information System Supporting Clinical Decision Based on Deep Learning Recognition Method

Retracted: The Design of Critical Care Information System Supporting Clinical Decision Based on Deep Learning Recognition Method

The Design of Critical Care Information System Supporting Clinical Decision Based on Deep Learning Recognition Method

In recent years, the clinical decision support system (CDSS) has been gradually improved, which effectively reduces the probability of doctors’ misdiagnosis or missed diagnosis. Therefore, the clinical decision support system has always been a research hotspot, deep learning and collaborative filtering technologies are developing rapidly, and more and more are applied to different fields. Based on the deep learning technology, this paper conducts in-depth research on the methods of assisted diagnosis of clinical diseases and prediction of clinical high-risk diseases in the field of CDSS. Aiming at the problem of clinical decision support system, this article analyzes the deep learning identification method in depth and is committed to applying machine deep learning to clinical decision-making, changing the lack of information and its challenges to clinical decision-making. Based on previous studies, two unsupervised learning methods based on machine learning are proposed, namely user collaborative filtering and RBM, to improve CDSS. The experimental results show that the overall performance of the RBM-based method is the best. When the missing degree of the two data sets is 30.6%, the classification accuracy rate is still more than 92.8%.

Variation in antibiotic use across intensive care units (ICU): A population-based cohort study in Ontario, Canada.

Antibiotics are commonly used in intensive care units (ICUs), yet differences in antibiotic use across ICUs are unknown. Herein, we studied antibiotic use across ICUs and examined factors that contributed to variation. We conducted a retrospective cohort study using data from Ontario's Critical Care Information System (CCIS), which included 201 adult ICUs and 2,013,397 patient days from January 2012 to June 2016. Antibiotic use was measured in days of therapy (DOT) per 1,000 patient days. ICU factors included ability to provide ventilator support (level 3) or not (level 2), ICU type (medical-surgical or other), and academic status. Patient factors included severity of illness using multiple-organ dysfunction score (MODS), ventilatory support, and central venous catheter (CVC) use. We analyzed the effect of these factors on variation in antibiotic use. Overall, 269,351 patients (56%) received antibiotics during their ICU stay. The mean antibiotic use was 624 (range 3-1460) DOT per 1,000 patient days. Antibiotic use was significantly higher in medical-surgical ICUs compared to other ICUs (697 vs 410 DOT per 1,000 patient days; P < .0001) and in level 3 ICUs compared to level 2 ICUs (751 vs 513 DOT per 1,000 patient days; P < .0001). Higher antibiotic use was associated with higher severity of illness and intensity of treatment. ICU and patient factors explained 47% of the variation in antibiotic use across ICUs. Antibiotic use varies widely across ICUs, which is partially associated with ICUs and patient characteristics. These differences highlight the importance of antimicrobial stewardship to ensure appropriate use of antibiotics in ICU patients.

External validation of a prognostic model for intensive care unit mortality: a retrospective study using the Ontario Critical Care Information System.

PurposeTo externally validate an intensive care unit (ICU) mortality prediction model that was created using the Ontario Critical Care Information System (CCIS), which includes the Multiple Organ Dysfunction Score (MODS).MethodsWe applied the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) recommendations to a prospective longitudinal cohort of patients discharged between 1 July 2015 and 31 December 31 2016 from 90 adult level-3 critical care units in Ontario. We used multivariable logistic regression with measures of discrimination, calibration-in-the-large, calibration slope, and flexible calibration plots to compare prediction model performance of the entire data set and for each ICU subtype.ResultsAmong 121,201 CCIS records with ICU mortality of 11.3%, the C-statistic for the validation data set was 0.805. The C-statistic ranged from 0.775 to 0.846 among the ICU subtypes. After intercept recalibration to adjust the baseline risk, the mean predicted risk of death matched actual ICU mortality. The calibration slope was close to 1 with all CCIS data and ICU subtypes of cardiovascular and community hospitals with low ventilation rates. Calibration slopes significantly less than 1 were found for ICUs in teaching hospitals and community hospitals with high ventilation rates whereas coronary care units had a calibration slope significantly higher than 1. Calibration plots revealed over-prediction in high risk groups to a varying degree across all cohorts.ConclusionsA risk prediction model primarily based on the MODS shows reproducibility and transportability after intercept recalibration. Risk adjusting models that use existing and feasible data collection can support performance measurement at the individual ICU level.Electronic supplementary materialThe online version of this article (10.1007/s12630-020-01686-5) contains supplementary material, which is available to authorized users.

Acute antiepileptic drug use in intensive care units.

In intensive care units (ICUs), antiepileptic drugs (AEDs) are used for manifold indications. This is the first study to assess the prevalence of acute AED use in ICUs and to identify associated clinical variables. All patients in seven adult ICUs of a German university hospital in 2016 were retrospectively evaluated. Data were extracted from the computerized critical care information system and manually reviewed. Acute AED treatments were defined as initiated during ICU treatment or ≤ 6h before ICU admission, excluding benzodiazepines and sedatives. Among 2335 patients evaluated, 8.8% received acutely started AEDs: 5.1% due to epileptic seizures, mostly acute symptomatic, and 3.7% for other indications like pain, post-hypoxic myoclonus, and singultus. Following multivariable analyses, acute AED use was independently associated with intracranial reasons for ICU admission and long durations of ICU stay, but not with increased disease severity scores or mortality. Levetiracetam was the substance most frequently used to treat epileptic seizures (88%) as was pregabalin for other conditions (49%). Among surviving patients, acute AEDs were continued beyond ICU discharge in 86% if seizure-related and in 78% if not seizure-related, even if there was no evident need for long-term AED treatment. One out of eleven ICU patients receives acute AEDs, in almost half of cases for non-seizure indications. Acute AED use is a marker for intracranial ICU indications and prolonged ICU treatments. Usually, newer-generation AEDs are employed with favourable pharmacokinetic and safety profiles. However, whenever possible, acutely started AED should be discontinued before discharge from ICU.

Functional requirements of critical care information systems (CCIS) from the users’ perspective

IntroductionCritical care information systems (CCIS) are computer software systems specialized for supporting the data processing tasks of clinical staff in intensive care units (ICUs). Reports on the impact of CCIS vary strongly from large benefits to harmful impact. One factor causing these inconsistent results is a large functional heterogeneity of the currently available systems, as no standards exist. Therefore, the aim of this study was to derive recommendations for a minimum range of functions that CCIS should incorporate from the perspective of clinical users. Materials and MethodsWe performed a web-based survey targeting clinical ICU staff in Germany. Participants rated the usefulness of pre-defined CCIS functions (36 for physicians / 31 for nurses) between 0-5. To capture confounders that might influence the ratings, we recorded 18 individual and workplace characteristics. ResultsThe 912 participants rated all but three of the investigated functions as useful with median scores of 4-5. A multivariable analysis showed that the ratings were influenced by whether CCIS were used on the participants’ wards, by the rating of the function quality of the used CCIS, the years of work experience and whether the participant was a physician or a nurse. ConclusionsClinical ICU staff considers all but three of the here investigated CCIS functions as useful. Even though we identified a variety of factors influencing the usefulness ratings, their influence is rather small and thus does not limit the validity of our findings. Accordingly, we commend the functions identified as useful to be incorporated in CCIS.

Reorganizing Care With the Implementation of Electronic Medical Records: A Time-Motion Study in the PICU.

To assess caregivers' patient care time before and after the implementation of a reorganization of care plan with electronic medical records. A prospective, observational, time-motion study. A level 3 PICU. Nurses and orderlies caring for intubated patients during an 8-hour work shift before (2008-2009) and after (2016) implementation of reorganization of care in 2013. The reorganization plan included improved telecommunication for healthcare workers, increased tasks delegated to orderlies, and an ICU-specific electronic medical record (Intellispace Critical Care and Anesthesia information system, Philips Healthcare). Time spent completing various work tasks was recorded by direct observation, and proportion of time in tasks was compared for each study period. A total of 153.7 hours was observed from 22 nurses and 14 orderlies. There was no significant difference in the proportion of nursing patient care time before (68.8% [interquartile range, 48-72%]) and after (55% [interquartile range, 51-57%]) (p = 0.11) the reorganization with electronic medical record. Direct patient care task time for nurses was increased from 27.0% (interquartile range, 30-37%) before to 34.7% (interquartile range, 33-75%) (p = 0.336) after, and indirect patient care tasks decreased from 33.6% (interquartile range, 23-41%) to 18.6% (interquartile range, 16-22%) (p = 0.036). Documentation time significantly increased from 14.5% (interquartile range, 12-22%) to 26.2% (interquartile range, 23-28%) (p = 0.032). Nursing productivity ratio improved from 28.3 to 26.0. A survey revealed that nursing staff was satisfied with the electronic medical record, although there was a concern for the maintenance of oral communication in the unit. The reorganization of care with the implementation of an ICU-specific electronic medical record in the PICU did not change total patient care provided but improved nursing productivity, resulting in improved efficiency. Documentation time was significantly increased, and concern over reduced oral communication arose, which should be a focus for future electronic improvement strategies.

Physician satisfaction with a critical care clinical information system using a multimethod evaluation of usability

IntroductionPhysician satisfaction with electronic medical records has often been poor. Usability has frequently been identified as a source for decreased satisfaction. While surveys can identify many issues, and are logistically easier to administer, they may miss issues identified using other methods This study sought to understand the level of physician satisfaction and usability issues associated with a critical care clinical information system (eCritical Alberta) implemented throughout the province of Alberta, Canada. MethodAll critical care attending physicians using the system were invited to participate in an online survey. Questions included components of the User Acceptance of Information Technology and Usability Questionnaire as well as free text feedback on system components. Physicians were also invited to participate in a think aloud test using simulated scenarios. The transcribed think aloud text and questionnaire were subjected to textual analysis. Results82% of all eligible physicians completed the on-line survey (n = 61). Eight physicians were invited and seven completed the think aloud test. Overall satisfaction with the system was moderate. Usability was identified as a significant factor contributing to satisfaction. The major usability factors identified were system response time and layout. The think aloud component identified additional factors beyond those identified in the on-line survey. ConclusionThis study found a modestly high level of physician satisfaction with a province-wide clinical critical care information system. Usability continues to be a significant factor in physician satisfaction. Using multiple methods of evaluation can capture the benefits of a large sample size and deeper understanding of the issues.

The effect of nursing participation in the design of a critical care information system: a case study in a Chinese hospital

BackgroundIntensive care information systems (ICIS) are continuously evolving to meet the ever changing information needs of intensive care units (ICUs), providing the backbone for a safe, intelligent and efficient patient care environment. Although beneficial for the international advancement in building smart environments to transform ICU services, knowledge about the contemporary development of ICIS worldwide, their usage and impacts is limited. This study aimed to fill this knowledge gap by researching the development and implementation of an ICIS in a Chinese hospital, nurses’ use of the system, and the impact of system use on critical care nursing processes and outcomes.MethodsThis descriptive case study was conducted in a 14-bed Respiratory ICU in a tertiary hospital in Beijing. Participative design was the method used for ICU nurses, hospital IT department and a software company to collaboratively research and develop the ICIS. Focus group discussions were conducted to understand the subjective perceptions of the nurses toward the ICIS. Nursing documentation time and quality were compared before and after system implementation. ICU nursing performance was extracted from the annual nursing performance data collected by the hospital.ResultsA participative design process was followed by the nurses in the ICU, the hospital IT staff and the software engineers in the company to develop and implement a highly useful ICIS. Nursing documentation was fully digitized and was significantly improved in quality and efficiency. The wrong data, missing data items and calculation errors were significantly reduced. Nurses spent more time on direct patient care after the introduction of the ICIS. The accuracy and efficiency of medication administration was also improved. The outcome was improvement in ward nursing performance as measured by ward management, routine nursing practices, disinfection and isolation, infection rate and mortality rate.ConclusionsNurses in this ICU unit in China actively participated in the ICIS development and fully used the system to document care. Introduction of the ICIS led to significant improvement in quality and efficiency in nursing documentation, medication order transcription and administration. It allowed nurses to spend more time with patients to improve quality of care. These led to improvement in overall nursing performance. Further study should investigate how the ICIS system contributes to the improvement in decision making of ICU nurses and intensivists.

Investigation of the Usability of Computerized Critical Care Information Systems in Germany.

The term "usability" describes how effectively, efficiently, and with what level of user satisfaction an information system can be used to accomplish specific goals. Computerized critical care information systems (CCISs) with high usability increase quality of care and staff satisfaction, while reducing medication errors. Conversely, systems lacking usability can interrupt clinical workflow, facilitate errors, and increase charting time. The aim of this study was to investigate and compare usability across CCIS currently used in Germany. In this study, German intensive care unit (ICU) nurses and physicians completed a specialized, previously validated, web-based questionnaire. The questionnaire assessed CCIS usability based on three rating models: an overall rating of the systems, a model rating technical usability, and a model rating task-specific usability. We analyzed results from 535 survey participants and compared eight different CCIS commonly used in Germany. Our results showed that usability strongly differs across the compared systems. The system ICUData had the best overall rating and technical usability, followed by the platforms ICM and MetaVision. The same three systems performed best in the rating of task-specific usability without significant differences between each other. Across all systems, overall ratings were more dependent on ease-of-use aspects than on aspects of utility/functionality, and the general scope of the functions offered was rated better than how well the functions are realized. Our results suggest that manufacturers should shift some of their effort away from the development of new features and focus more on improving the ease-of-use and quality of existing features.

Health IT Usability Focus Section: Data Use and Navigation Patterns among Medical ICU Clinicians during Electronic Chart Review.

Background A detailed understanding of electronic health record (EHR) workflow patterns and information use is necessary to inform user-centered design of critical care information systems. While developing a longitudinal medical record visualization tool to facilitate electronic chart review (ECR) for medical intensive care unit (MICU) clinicians, we found inadequate research on clinician–EHR interactions. Objective We systematically studied EHR information use and workflow among MICU clinicians to determine the optimal selection and display of core data for a revised EHR interface. Methods We conducted a direct observational study of MICU clinicians performing ECR for unfamiliar patients during their routine daily practice at an academic medical center. Using a customized manual data collection instrument, we unobtrusively recorded the content and sequence of EHR data reviewed by clinicians. Results We performed 32 ECR observations among 24 clinicians. The median (interquartile range [IQR]) chart review duration was 9.2 (7.3–14.7) minutes, with the largest time spent reviewing clinical notes (44.4%), laboratories (13.3%), imaging studies (11.7%), and searching/scrolling (9.4%). Historical vital sign and intake/output data were never viewed in 31% and 59% of observations, respectively. Clinical notes and diagnostic reports were browsed ≥10 years in time for 60% of ECR sessions. Clinicians viewed a median of 7 clinical notes, 2.5 imaging studies, and 1.5 diagnostic studies, typically referencing a select few subtypes. Clinicians browsed a median (IQR) of 26.5 (22.5–37.25) data screens to complete their ECR, demonstrating high variability in navigation patterns and frequent back-and-forth switching between screens. Nonetheless, 47% of ECRs begin with review of clinical notes, which were also the most common navigation destination. Conclusion Electronic chart review centers around the viewing of clinical notes among MICU clinicians. Convoluted workflows and prolonged searching activities indicate room for system improvement. Using study findings, specific design recommendations to enhance usability for critical care information systems are provided.

A Multisite Survey Study of EMR Review Habits, Information Needs, and Display Preferences among Medical ICU Clinicians Evaluating New Patients.

The electronic chart review habits of intensive care unit (ICU) clinicians admitting new patients are largely unknown but necessary to inform the design of existing and future critical care information systems. We conducted a survey study to assess the electronic chart review practices, information needs, workflow, and data display preferences among medical ICU clinicians admitting new patients. We surveyed rotating residents, critical care fellows, advanced practice providers, and attending physicians at three Mayo Clinic sites (Minnesota, Florida, and Arizona) via email with a single follow-up reminder message. Of 234 clinicians invited, 156 completed the full survey (67% response rate). Ninety-two percent of medical ICU clinicians performed electronic chart review for the majority of new patients. Clinicians estimated spending a median (interquartile range (IQR)) of 15 (10-20) minutes for a typical case, and 25 (15-40) minutes for complex cases, with no difference across training levels. Chart review spans 3 or more years for two-thirds of clinicians, with the most relevant categories being imaging, laboratory studies, diagnostic studies, microbiology reports, and clinical notes, although most time is spent reviewing notes. Most clinicians (77%) worry about overlooking important information due to the volume of data (74%) and inadequate display/organization (63%). Potential solutions are chronologic ordering of disparate data types, color coding, and explicit data filtering techniques. The ability to dynamically customize information display for different users and varying clinical scenarios is paramount. Electronic chart review of historical data is an important, prevalent, and potentially time-consuming activity among medical ICU clinicians who would benefit from improved information display systems.

Design and validation of a questionnaire to evaluate the usability of computerized critical care information systems.

The implementation of computerized critical care information systems (CCIS) can improve the quality of clinical care and staff satisfaction, but also holds risks of disrupting the workflow with consecutive negative impacts. The usability of CCIS is one of the key factors determining their benefits and weaknesses. However, no tailored instrument exists to measure the usability of such systems. Therefore, the aim of this study was to design and validate a questionnaire that measures the usability of CCIS. Following a mixed-method design approach, we developed a questionnaire comprising two evaluation models to assess the usability of CCIS: (1) the task-specific model rates the usability individually for several tasks which CCIS could support and which we derived by analyzing work processes in the ICU; (2) the characteristic-specific model rates the different aspects of the usability, as defined by the international standard "ergonomics of human-system interaction". We tested validity and reliability of the digital version of the questionnaire in a sample population. In the sample population of 535 participants both usability evaluation models showed a strong correlation with the overall rating of the system (multiple correlation coefficients ≥0.80) as well as a very high internal consistency (Cronbach's alpha ≥0.93). The novel questionnaire is a valid and reliable instrument to measure the usability of CCIS and can be used to study the influence of the usability on their implementation benefits and weaknesses.

To develop a regional ICU mortality prediction model during the first 24h of ICU admission utilizing MODS and NEMS with six other independent variables from the Critical Care Information System (CCIS) Ontario, Canada.

BackgroundIntensive care unit (ICU) scoring systems or prediction models evolved to meet the desire of clinical and administrative leaders to assess the quality of care provided by their ICUs. The Critical Care Information System (CCIS) is province-wide data information for all Ontario, Canada level 3 and level 2 ICUs collected for this purpose. With the dataset, we developed a multivariable logistic regression ICU mortality prediction model during the first 24 h of ICU admission utilizing the explanatory variables including the two validated scores, Multiple Organs Dysfunctional Score (MODS) and Nine Equivalents Nursing Manpower Use Score (NEMS) followed by the variables age, sex, readmission to the ICU during the same hospital stay, admission diagnosis, source of admission, and the modified Charlson Co-morbidity Index (CCI) collected through the hospital health records.MethodsThis study is a single-center retrospective cohort review of 8822 records from the Critical Care Trauma Centre (CCTC) and Medical-Surgical Intensive Care Unit (MSICU) of London Health Sciences Centre (LHSC), Ontario, Canada between 1 Jan 2009 to 30 Nov 2012. Multivariable logistic regression on training dataset (n = 4321) was used to develop the model and validate by bootstrapping method on the testing dataset (n = 4501). Discrimination, calibration, and overall model performance were also assessed.ResultsThe predictors significantly associated with ICU mortality included: age (p < 0.001), source of admission (p < 0.0001), ICU admitting diagnosis (p < 0.0001), MODS (p < 0.0001), and NEMS (p < 0.0001). The variables sex and modified CCI were not significantly associated with ICU mortality. The training dataset for the developed model has good discriminating ability between patients with high risk and those with low risk of mortality (c-statistic 0.787). The Hosmer and Lemeshow goodness-of-fit test has a strong correlation between the observed and expected ICU mortality (χ2 = 5.48; p > 0.31). The overall optimism of the estimation between the training and testing data set ΔAUC = 0.003, indicating a stable prediction model.ConclusionsThis study demonstrates that CCIS data available after the first 24 h of ICU admission at LHSC can be used to create a robust mortality prediction model with acceptable fit statistic and internal validity for valid benchmarking and monitoring ICU performance.Electronic supplementary materialThe online version of this article (doi:10.1186/s40560-016-0143-6) contains supplementary material, which is available to authorized users.

Developing and expanding hospital antimicrobial stewardship: The Ontario experience.

Mount Sinai Hospital and University Health Network, two academic health science centres in Toronto, Ontario, jointly established a robust, well-resourced antimicrobial stewardship program (ASP). Over the course of four years, we spread our program to five intensive care units (ICUs), learned which change management practices worked and which did not, and leveraged our ICU successes to other areas of our hospitals. We identified the following two factors as critical to establishing ASPs in hospitals: strong leadership with clear accountability; and valid, reliable data to monitor progress. Subsequently we have led the spread of our program to 14 academic hospital ICUs, and more recently we leveraged to help community hospitals implement ASPs without in-house infectious diseases specialists. We introduced three new data fields into the provincial critical care information system: days of antibacterial therapy, days of antifungal therapy, and ICU-onset C. difficile, which will help standardize data collection moving forward. This model-starting with academic health sciences centres, and antimicrobial stewardship experts and leaders who are then supported to mentor and develop new experts and leaders-could be copied in other jurisdictions both within and outside of Canada.

A case study evaluation of a Critical Care Information System adoption using the socio-technical and fit approach

BackgroundClinical information systems have long been used in intensive care units but reports on their adoption and benefits are limited. This study evaluated a Critical Care Information System implementation. MethodsA case study summative evaluation was conducted, employing observation, interview, and document analysis in operating theatres and 16-bed adult intensive care units in a 400-bed Malaysian tertiary referral centre from the perspectives of users (nurses and physicians), management, and information technology staff. System implementation, factors influencing adoption, fit between these factors, and the impact of the Critical Care Information System were evaluated after eight months of operation. ResultsPositive influences on system adoption were associated with technical factors, including system ease of use, usefulness, and information relevancy; human factors, particularly user attitude; and organisational factors, namely clinical process-technology alignment and champions. Organisational factors such as planning, project management, training, technology support, turnover rate, clinical workload, and communication were barriers to system implementation and use. Recommendations to improve the current system problems were discussed. Most nursing staff positively perceived the system's reduction of documentation and data access time, giving them more time with patients. System acceptance varied among doctors. System use also had positive impacts on timesaving, data quality, and clinical workflow. ConclusionsCritical Care Information Systems is crucial and has great potentials in enhancing and delivering critical care. However, the case study findings showed that the system faced complex challenges and was underutilised despite its potential. The role of socio-technical factors and their fit in realizing the potential of Critical Care Information Systems requires continuous, in-depth evaluation and stakeholder understanding and acknowledgement. The comprehensive and specific evaluation measures of the Human–Organisation–Technology Fit framework can flexibly evaluate Critical Care Information Systems.

Evaluation of the clinical process in a critical care information system using the Lean method: a case study

BackgroundThere are numerous applications for Health Information Systems (HIS) that support specific tasks in the clinical workflow. The Lean method has been used increasingly to optimize clinical workflows, by removing waste and shortening the delivery cycle time. There are a limited number of studies on Lean applications related to HIS. Therefore, we applied the Lean method to evaluate the clinical processes related to HIS, in order to evaluate its efficiency in removing waste and optimizing the process flow. This paper presents the evaluation findings of these clinical processes, with regards to a critical care information system (CCIS), known as IntelliVue Clinical Information Portfolio (ICIP), and recommends solutions to the problems that were identified during the study.MethodsWe conducted a case study under actual clinical settings, to investigate how the Lean method can be used to improve the clinical process. We used observations, interviews, and document analysis, to achieve our stated goal. We also applied two tools from the Lean methodology, namely the Value Stream Mapping and the A3 problem-solving tools. We used eVSM software to plot the Value Stream Map and A3 reports.ResultsWe identified a number of problems related to inefficiency and waste in the clinical process, and proposed an improved process model.ConclusionsThe case study findings show that the Value Stream Mapping and the A3 reports can be used as tools to identify waste and integrate the process steps more efficiently. We also proposed a standardized and improved clinical process model and suggested an integrated information system that combines database and software applications to reduce waste and data redundancy.