Clinician satisfaction with computer decision support in the intensive care unit

The Effect of Clinical Decision Support Systems on Patients, Nurses, and Work Environment in ICUs: A Systematic Review

This study aimed to examine the impact of clinical decision support systems on patient outcomes, working environment outcomes, and decision-making processes in nursing. The authors conducted a systematic literature review to obtain evidence on studies about clinical decision support systems and the practices of ICU nurses. For this purpose, the authors searched 10 electronic databases, including PubMed, CINAHL, Web of Science, Scopus, Cochrane Library, Ovid MEDLINE, Science Direct, Tr-Dizin, Harman, and DergiPark. Search terms included "clinical decision support systems," "decision making," "intensive care," "nurse/nursing," "patient outcome," and "working environment" to identify relevant studies published during the period from the year 2007 to October 2022. Our search yielded 619 articles, of which 39 met the inclusion criteria. A higher percentage of studies compared with others were descriptive (20%), conducted through a qualitative (18%), and carried out in the United States (41%). According to the results of the narrative analysis, the authors identified three main themes: "patient care outcomes," "work environment outcomes," and the "decision-making process in nursing." Clinical decision support systems, which target practices of ICU nurses and patient care outcomes, have positive effects on outcomes and show promise in improving the quality of care; however, available studies are limited.

Closed-Loop Controlled Fluid Administration Systems: A Comprehensive Scoping Review

Physiological Closed-Loop Controlled systems continue to take a growing part in clinical practice, offering possibilities of providing more accurate, goal-directed care while reducing clinicians’ cognitive and task load. These systems also provide a standardized approach for the clinical management of the patient, leading to a reduction in care variability across multiple dimensions. For fluid management and administration, the advantages of closed-loop technology are clear, especially in conditions that require precise care to improve outcomes, such as peri-operative care, trauma, and acute burn care. Controller design varies from simplistic to complex designs, based on detailed physiological models and adaptive properties that account for inter-patient and intra-patient variability; their maturity level ranges from theoretical models tested in silico to commercially available, FDA-approved products. This comprehensive scoping review was conducted in order to assess the current technological landscape of this field, describe the systems currently available or under development, and suggest further advancements that may unfold in the coming years. Ten distinct systems were identified and discussed.

Optimizing a decision support system for damage-control resuscitation using mixed methods human factors analysis

BACKGROUND

Damage-control resuscitation (DCR) improves trauma survival; however, consistent adherence to DCR principles through multiple phases of care has proven challenging. Clinical decision support may improve adherence to DCR principles. In this study, we designed and evaluated a DCR decision support system using an iterative development and human factors testing approach.

METHODS

The phases of analysis included initial needs assessment and prototype design (Phase 0), testing in a multidimensional simulation (Phase 1), and testing during initial clinical use (Phase 2). Phase 1 and Phase 2 included hands-on use of the decision support system in the trauma bay, operating room, and intensive care unit. Participants included trauma surgeons, trauma fellows, anesthesia providers, and trauma bay and intensive care unit nurses who provided both qualitative and quantitative feedback on the initial prototype and all subsequent iterations.

RESULTS

In Phase 0, 14 (87.5%) of 16 participants noted that they would use the decisions support system in a clinical setting. Twenty-four trauma team members then participated in simulated resuscitations with decision support where 178 (78.1%) of 228 of tasks were passed and 27 (11.8%) were passed with difficulty. Twenty-three (95.8%) completed a postsimulation survey. Following iterative improvements in system design, Phase 2 evaluation included 21 trauma team members during multiple real-world trauma resuscitations. Of these, 15 (71.4%) completed a formal postresuscitation survey. Device-level feedback on a Likert scale (range, 0-4) confirmed overall ease of use (median score, 4; interquartile range, 4-4) and indicated the system integrated well into their workflow (median score, 3; interquartile range, 2-4). Final refinements were then completed in preparation for a pilot clinical study using the decision support system.

CONCLUSIONS

An iterative development and human factors testing approach resulted in a clinically useable DCR decision support system. Further analysis will determine its applicability in military and civilian trauma care.

LEVEL OF EVIDENCE

Therapeutic/Care Management, Level V.

Modeling Fluid Resuscitation by Formulating Infusion Rate and Urine Output in Severe Thermal Burn Adult Patients: A Retrospective Cohort Study

Acute burn injuries are among the most devastating forms of trauma and lead to significant morbidity and mortality. Appropriate fluid resuscitation after severe burn, specifically during the first 48 hours following injury, is considered as the single most important therapeutic intervention in burn treatment. Although many formulas have been developed to estimate the required fluid amount in severe burn patients, many lines of evidence showed that patients still receive far more fluid than formulas recommend. Overresuscitation, which is known as “fluid creep,” has emerged as one of the most important problems during the initial period of burn care. If fluid titration can be personalized and automated during the resuscitation phase, more efficient burn care and outcome will be anticipated. In the present study, a dynamic urine output based infusion rate prediction model was developed and validated during the initial 48 hours in severe thermal burn adult patients. The experimental results demonstrated that the developed dynamic fluid resuscitation model might significantly reduce the total fluid volume by accurately predicting hourly urine output and has the potential to aid fluid administration in severe burn patients.