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Multicenter validation of a computer-based clinical decision support tool for glucose control in adult and pediatric intensive care units.

ABSTRACT: Hyperglycemia during critical illness is common, and intravenous insulin therapy (IIT) to normalize blood glucose improves outcomes in selected populations. Methods differ widely in complexity, insulin dosing approaches, efficacy, and rates of hypoglycemia. We developed a simple bedside-computerized decision support protocol (eProtocol-insulin) that yields promising results in the development center. We examined the effectiveness and safety of this tool in six adult and five pediatric intensive care units (ICUs) in other centers.We required attending physicians of eligible patients to independently intend to use intravenous insulin to normalize blood glucose. We used eProtocol-insulin for glucose control for a duration determined by the clinical caregivers. Adults had an anticipated length of stay of 3 or more days. In pediatric ICUs, we also required support or intended support with mechanical ventilation for greater than 24 hours or with a vasoactive infusion. We recorded all instances in which eProtocol-insulin instructions were not accepted and all blood glucose values. An independent data safety and monitoring board monitored study results and subject safety. Bedside nurses were selected randomly to complete a paper survey describing their perceptions of quality of care and workload related to eProtocol-insulin use.Clinicians accepted 93% of eProtocol-insulin instructions (11,773/12,645) in 100 adult and 48 pediatric subjects. Forty-eight percent of glucose values were in the target range. Both of these results met a priori-defined efficacy thresholds. Only 0.18% of glucose values were < or =40 mg/dl. This is lower than values reported in prior IIT studies. Although nurses reported eProtocol-insulin required as much work as managing a mechanical ventilator, most nurses felt eProtocol-insulin had a low impact on their ability to complete non-IIT nursing activities.A multicenter validation demonstrated that eProtocol-insulin is a valid, exportable tool that can assist clinicians in achieving control of glucose in critically ill adults and children.

SUBMITTER: Thompson BT

PROVIDER: S-EPMC2769731 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature

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Multicenter validation of a computer-based clinical decision support tool for glucose control in adult and pediatric intensive care units.

Thompson B Taylor BT Orme James F JF Zheng Hui H Luckett Peter M PM Truwit Jonathon D JD Willson Douglas F DF Duncan Hite R R Brower Roy G RG Bernard Gordon R GR Curley Martha A Q MA Steingrub Jay S JS Sorenson Dean K DK Sward Kathy K Hirshberg Ellie E Morris Alan H AH

Journal of diabetes science and technology 20080501 3

<h4>Introduction</h4>Hyperglycemia during critical illness is common, and intravenous insulin therapy (IIT) to normalize blood glucose improves outcomes in selected populations. Methods differ widely in complexity, insulin dosing approaches, efficacy, and rates of hypoglycemia. We developed a simple bedside-computerized decision support protocol (eProtocol-insulin) that yields promising results in the development center. We examined the effectiveness and safety of this tool in six adult and five ...[more]

PMID: 19885199

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Project description:Individuals acting as surrogate decision makers for critically ill patients frequently struggle in this role and experience high levels of long-term psychological distress. Prior interventions designed to improve the sharing of information by the clinical team with surrogate decision makers have demonstrated little effect on surrogates' outcomes or clinical decisions. In this report, we describe the study protocol and corresponding intervention fidelity monitoring plan for a multicenter randomized clinical trial testing the impact of a multifaceted surrogate support intervention (Four Supports) on surrogates' psychological distress, the quality of decisions about goals of care, and healthcare use. We will randomize the surrogates of 300 incapacitated critically ill patients at high risk of death and/or severe long-term functional impairment to receive the Four Supports intervention or an education control. The Four Supports intervention adds to the intensive care unit (ICU) team a trained interventionist (family support specialist) who delivers four types of protocolized support-emotional support; communication support; decisional support; and, if indicated, anticipatory grief support-to surrogates through daily interactions during the ICU stay. The primary outcome is surrogates' symptoms of anxiety and depression at 6-month follow-up, measured with the Hospital Anxiety and Depression Scale. Prespecified secondary outcome measures are the Patient Perception of Patient Centeredness Scale (modified for use with surrogates) and Impact of Event Scale scores at 3- and 6-month follow-up, respectively, together with ICU and hospital lengths of stay and total hospital cost among decedents. The fidelity monitoring plan entails establishing and measuring adherence to the intervention using multiple measurement methods, including daily checklists and coding of audiorecorded encounters. This approach to intervention fidelity may benefit others designing and testing behavioral interventions in the ICU setting. Clinical trial registered with www.clinicaltrials.gov (NCT01982877).

Project description:IntroductionDigital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations. It calculates a risk score for several rheumatic diseases. We ran a pilot study retrospectively testing Rheumatic? for its ability to differentiate symptoms from existing or emerging immune-mediated rheumatic diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics.Materials and methodsThe performance of Rheumatic? was tested using in three university rheumatology centers: (A) patients at Risk for RA (Karolinska Institutet, n = 50 individuals with musculoskeletal complaints and anti-citrullinated protein antibody positivity) (B) patients with early joint swelling [dataset B (Erlangen) n = 52]. (C) Patients with early arthritis where the clinician considered it likely to be of auto-immune origin [dataset C (Leiden) n = 73]. In dataset A we tested whether Rheumatic? could predict the development of arthritis. In dataset B and C we tested whether Rheumatic? could predict the development of an immune-mediated rheumatic diseases. We examined the discriminative power of the total score with the Wilcoxon rank test and the area-under-the-receiver-operating-characteristic curve (AUC-ROC). Next, we calculated the test characteristics for these patients passing the first or second expert-based Rheumatic? scoring threshold.ResultsThe total test scores differentiated between: (A) Individuals developing arthritis or not, median 245 vs. 163, P < 0.0001, AUC-ROC = 75.3; (B) patients with an immune-mediated arthritic disease or not median 191 vs. 107, P < 0.0001, AUC-ROC = 79.0; but less patients with an immune-mediated arthritic disease or not amongst those where the clinician already considered an immune mediated disease most likely (median 262 vs. 212, P < 0.0001, AUC-ROC = 53.6). Threshold-1 (advising to visit primary care doctor) was highly specific in dataset A and B (0.72, 0.87, and 0.23, respectively) and sensitive (0.67, 0.61, and 0.67). Threshold-2 (advising to visit rheumatologic care) was very specific in all three centers but not very sensitive: specificity of 1.0, 0.96, and 0.91, sensitivity 0.05, 0.07, 0.14 in dataset A, B, and C, respectively.ConclusionRheumatic? is a web-based patient-centered multilingual diagnostic tool capable of differentiating immune-mediated rheumatic conditions from other musculoskeletal problems. The current scoring system needs to be further optimized.

Project description:BACKGROUND:Physicians often find significant challenges in assessing automobile driving in persons with mild cognitive impairment and mild dementia and deciding when to report to transportation administrators. Care must be taken to balance the safety of patients and other road users with potential negative effects of issuing such reports. OBJECTIVE:The aim of this study was to assess whether a computer-based Driving in Dementia Decision Tool (DD-DT) increased appropriate reporting of patients with mild dementia or mild cognitive impairment to transportation administrators. METHODS:The study used a parallel-group cluster nonblinded randomized controlled trial design to test a multifaceted knowledge translation intervention. The intervention included a computer-based decision support system activated by the physician-user, which provides a recommendation about whether to report patients with mild dementia or mild cognitive impairment to transportation administrators, based on an algorithm derived from earlier work. The intervention also included a mailed educational package and Web-based specialized reporting forms. Specialists and family physicians with expertise in dementia or care of the elderly were stratified by sex and randomized to either use the DD-DT or a control version of the tool that required identical data input as the intervention group, but instead generated a generic reminder about the reporting legislation in Ontario, Canada. The trial ran from September 9, 2014 to January 29, 2016, and the primary outcome was the number of reports made to the transportation administrators concordant with the algorithm. RESULTS:A total of 69 participating physicians were randomized, and 36 of these used the DD-DT; 20 of the 35 randomized to the intervention group used DD-DT with 114 patients, and 16 of the 34 randomized to the control group used it with 103 patients. The proportion of all assessed patients reported to the transportation administrators concordant with recommendation did not differ between the intervention and the control groups (50% vs 49%; Z=-0.19, P=.85). Two variables predicted algorithm-based reporting-caregiver concern (odds ratio [OR]=5.8, 95% CI 2.5-13.6, P<.001) and abnormal clock drawing (OR 6.1, 95% CI 3.1-11.8, P<.001). CONCLUSIONS:On the basis of this quantitative analysis, in-office abnormal clock drawing and expressions of concern about driving from caregivers substantially influenced physicians to report patients with mild dementia or mild cognitive impairment to transportation administrators, but the DD-DT tool itself did not increase such reports among these expert physicians. TRIAL REGISTRATION:ClinicalTrials.gov NCT02036099; https://clinicaltrials.gov/ct2/show/NCT02036099 (Archived by WebCite at http://www.webcitation.org/6zGMF1ky8).

Project description:BackgroundAcute kidney injury (AKI) affects a large proportion of the critically ill and is associated with worse patient outcomes. Early identification of AKI can lead to earlier initiation of supportive therapy and better management. In this study, we evaluate the impact of computerized AKI decision support tool integrated with the critical care clinical information system (CCIS) on patient outcomes. Specifically, we hypothesize that integration of AKI guidelines into CCIS will decrease the proportion of patients with Stage 1 AKI deteriorating into higher stages of AKI.MethodsThe study was conducted in two intensive care units (ICUs) at University Hospitals Bristol, UK, in a before (control) and after (intervention) format. The intervention consisted of the AKIN guidelines and AKI care bundle which included guidance for medication usage, AKI advisory and dashboard with AKI score. Clinical data and patient outcomes were collected from all patients admitted to the units. AKI stage was calculated using the Acute Kidney Injury Network (AKIN) guidelines. Maximum AKI stage per admission, change in AKI stage and other metrics were calculated for the cohort. Adherence to eGFR-based enoxaparin dosing guidelines was evaluated as a proxy for clinician awareness of AKI.ResultsEach phase of the study lasted a year, and a total of 5044 admissions were included for analysis with equal numbers of patients for the control and intervention stages. The proportion of patients worsening from Stage 1 AKI decreased from 42% (control) to 33.5% (intervention), p = 0.002. The proportion of incorrect enoxaparin doses decreased from 1.72% (control) to 0.6% (intervention), p < 0.001. The prevalence of any AKI decreased from 43.1% (control) to 37.5% (intervention), p < 0.05.ConclusionsThis observational study demonstrated a significant reduction in AKI progression from Stage 1 and a reduction in overall development of AKI. In addition, a reduction in incorrect enoxaparin dosing was also observed, indicating increased clinical awareness. This study demonstrates that AKI guidelines coupled with a newly designed AKI care bundle integrated into CCIS can impact patient outcomes positively.

Project description:ObjectiveTo describe the clinical characteristics of children and adolescents admitted to intensive care with confirmed COVID-19.MethodProspective, multicenter, observational study, in 19 pediatric intensive care units. Patients aged 1 month to 19 years admitted consecutively (March-May 2020) were included. Demographic, clinical-epidemiological features, treatment, and outcomes were collected. Subgroups were compared according to comorbidities, age < 1 year, and need for invasive mechanical ventilation. A multivariable logistic regression model was used for predictors of severity.ResultsSeventy-nine patients were included (ten with multisystemic inflammatory syndrome). Median age 4 years; 54% male (multisystemic inflammatory syndrome, 80%); 41% had comorbidities (multisystemic inflammatory syndrome, 20%). Fever (76%), cough (51%), and tachypnea (50%) were common in both groups. Severe symptoms, gastrointestinal symptoms, and higher inflammatory markers were more frequent in multisystemic inflammatory syndrome. Interstitial lung infiltrates were common in both groups, but pleural effusion was more prevalent in the multisystemic inflammatory syndrome group (43% vs. 14%). Invasive mechanical ventilation was used in 18% (median 7.5 days); antibiotics, oseltamivir, and corticosteroids were used in 76%, 43%, and 23%, respectively, but not hydroxychloroquine. The median pediatric intensive care unit length-of-stay was five days; there were two deaths (3%) in the non- multisystemic inflammatory syndrome group. Patients with comorbidities were older and comorbidities were independently associated with the need for invasive mechanical ventilation (OR 5.5; 95% CI, 1.43-21.12; p = 0.01).ConclusionsIn Brazilian pediatric intensive care units, COVID-19 had low mortality, age less than 1 year was not associated with a worse prognosis, and patients with multisystemic inflammatory syndrome had more severe symptoms, higher inflammatory biomarkers, and a greater predominance of males, but only comorbidities and chronic diseases were independent predictors of severity.

Project description:Objetivo Descrever as características clínicas de crianças e adolescentes internados em unidade de terapia intensiva com COVID‐19 confirmada. Método Estudo prospectivo, multicêntrico, observacional, em 19 unidades de terapia intensiva pediátrica. Foram incluídos pacientes entre um mês e 19 anos, admitidos consecutivamente (março a maio de 2020). As características demográficas, clínico‐epidemiológicas, o tratamento e os resultados foram coletados. Os subgrupos foram comparados de acordo com as comorbidades, idade < 1 ano e necessidade de ventilação mecânica invasiva. Um modelo de regressão logística multivariável foi utilizado para preditores de gravidade. Resultados Setenta e nove pacientes foram incluídos (10 com síndrome inflamatória multi-ssistêmica). Mediana de idade, quatro anos; 54% eram do sexo masculino (síndrome inflamatória multissistêmica, 80%); 41% tinham comorbidades (síndrome inflamatória multissistêmica, 20%). Febre (76%), tosse (51%) e taquipneia (50%) foram comuns nos dois grupos. Sintomas graves egastrointestinais e marcadores inflamatórios mais elevados foram mais frequentes na presença de síndrome inflamatória multissistêmica. Infiltrados intersticiais pulmonares foram comuns em ambos os grupos, mas o derrame pleural foi mais prevalente no grupo com síndrome inflamatória multissistêmica (43% vs. 14%). A ventilac¸ão mecânica invasiva foi utilizada em 18% (mediana 7,5 dias); antibióticos, oseltamivir e corticosteroides foram utilizados em 76%, 43% e 23%, respectivamente, mas não a hidroxicloroquina. A mediana do tempo de permanência na unidade de terapia intensiva pediátrica foi de 5 dias; duas mortes ocorreram (3%) no grupo não- síndrome inflamatória multissistêmica. Os pacientes com comorbidades eram mais velhos, e as comorbidades foram independentemente associadas à necessidade de ventilac¸ão mecânica invasiva(OR 5,5; IC95%, 1,43-21,12; P 0,01). Conclusões Nas unidades de terapia intensiva pediátrica brasileiras, a COVID‐19 apresentou baixa mortalidade, a idade inferior a um ano não foi associada a um pior prognóstico, os pacientes com síndrome inflamatória multissistêmica apresentaram sintomas mais graves, biomarcadores inflamatórios mais elevados e uma grande predominância no sexo masculino, mas apenas a presença de comorbidades e doenças crônicas foi um preditor independente de gravidade.

Dataset Information

Multicenter validation of a computer-based clinical decision support tool for glucose control in adult and pediatric intensive care units.

Publications

Multicenter validation of a computer-based clinical decision support tool for glucose control in adult and pediatric intensive care units.

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