Developing minimum clinical standards for physiotherapy in South African ICUs: A qualitative study

Rationale, aims, and objectives: Physiotherapists are integral members of the intensive care unit (ICU) team. Clinicians working in ICU are dependent on their own experience when making decisions regarding individual patient management thus resulting in variation in clinical practice. No formalized clinical practice guidelines or standards exist for the educational profile or scope of practice requirements for ICU physiotherapy. This study explored perceptions of physiotherapists on minimum clinical standards that ICU physiotherapists should adhere to for delivering safe, effective physiotherapy services to critically ill patients. Method: Experienced physiotherapists offering a service to South African ICUs were purposively sampled. Three focus group sessions were held in different parts of the country to ensure national participation. Each was audio recorded. The stimulus question posed was “What is the minimum standard of clinical practice needed by physiotherapists to ensure safe and independent practice in South African ICUs?” Three categories were explored, namely, knowledge, skill, and attributes. Themes and subthemes were developed using the codes identified. An inductive approach to data analysis was used to perform conventional content analysis. Results: Twenty-five physiotherapists participated in 1 of 3 focus group sessions. Mean years of ICU experience was 10.8 years (±7.0; range, 3-33). Three themes emerged from the data namely, integrated medical knowledge, multidisciplinary teamwork, and physiotherapy practice. Integrated medical knowledge related to anatomy and physiology, conditions that patients present with in ICU, the ICU environment, pathology and pathophysiology, and pharmacology. Multidisciplinary teamwork encompassed elements related to communication, continuous professional development, cultural sensitivity, documentation, ethics, professionalism, safety in ICU, and technology. Components related to physiotherapy practice included clinical reasoning, handling skills, interventions, and patient care. Conclusions: The information obtained will be used to inform the development of a list of standards to be presented to the wider national physiotherapy and ICU communities for further consensus-building activities

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care

Does Culture Influence the Needs of Critical Care Families?

Purpose: This study explores ICU patient\u27s family member needs, particularly Vietnamese and Latino families. Design: Convenience sampling at 24 bed ICU in acute care community hospital serving ethnically diverse population. Methods: Non-experimental survey with pretest-posttest design using Demographic sheet, Critical Family Needs Inventory (CCFNI), and Needs Met Inventory (NMI). Information pamphlets were distributed. Data analysis was by ethnic groups using measures of central tendency and descriptive statistics. Findings: CCFNI results indicate family members of all ethnicities experience the same priority of needs; support and information are top two needs. English, Spanish and Vietnamese pamphlets met information needs of the majority of the recipients

Triage and Ongoing Care for Critically Ill Patients in the Emergency Department: Results from a National Survey of Emergency Physicians

Introduction: We conducted a cross-sectional study at the Icahn School of Medicine at Mount Sinai to elicit emergency physician (EP) perceptions regarding intensive care unit (ICU) triage decisions and ongoing management for boarding of ICU patients in the emergency department (ED). We assessed factors influencing the disposition decision for critically ill patients in the ED to characterize EPs’ perceptions about ongoing critical care delivery in the ED while awaiting ICU admission.Methods: Through content expert review and pilot testing, we iteratively developed a 25-item written survey targeted to EPs, eliciting current ICU triage structure, opinions on factors influencing ICU admission decisions, and views on caring for critically ill patients “boarding” in the ED for >4-6 hours.Results: We approached 732 EPs at a large, national emergency medicine conference, achieving 93.6% response and completion rate, with 54% academic and 46% community participants. One-fifth reported having formal ICU admission criteria, although only 36.6% reported adherence. Common factors influencing EPs’ ICU triage decisions were illness severity (91.1%), ICU interventions needed (87.6%), and diagnosis (68.2%), while ICU bed availability (13.5%) and presence of other critically ill patients in ED (10.2%) were less or not important. While 72.1% reported frequently caring for ICU boarders, respondents identified high patient volume (61.3%) and inadequate support staffing (48.6%) as the most common challenges in caring for boarding ICU patients.Conclusion: Patient factors (eg, diagnosis, illness severity) were seen as more important than system factors (eg, bed availability) in triaging ED patients to the ICU. Boarding ICU patients is a common challenge for more than two-thirds of EPs, exacerbated by ED volume and staffing constraints

Automated Measurement of Adherence to Traumatic Brain Injury (TBI) Guidelines using Neurological ICU Data

Using a combination of physiological and treatment information from neurological ICU data-sets, adherence to traumatic brain injury (TBI) guidelines on hypotension, intracranial pressure (ICP) and cerebral perfusion pressure (CPP) is calculated automatically. The ICU output is evaluated to capture pressure events and actions taken by clinical staff for patient management, and are then re-expressed as simplified process models. The official TBI guidelines from the Brain Trauma Foundation are similarly evaluated, so the two structures can be compared and a quantifiable distance between the two calculated (the measure of adherence). The methods used include: the compilation of physiological and treatment information into event logs and subsequently process models; the expression of the BTF guidelines in process models within the real-time context of the ICU; a calculation of distance between the two processes using two algorithms (“Direct” and “Weighted”) building on work conducted in th e business process domain. Results are presented across two categories each with clinical utility (minute-by-minute and single patient stays) using a real ICU data-set. Results of two sample patients using a weighted algorithm show a non-adherence level of 6.25% for 42 mins and 56.25% for 708 mins and non-adherence of 18.75% for 17 minutes and 56.25% for 483 minutes. Expressed as two combinatorial metrics (duration/non-adherence (A) and duration * non-adherence (B)), which together indicate the clinical importance of the non-adherence, one has a mean of A=4.63 and B=10014.16 and the other a mean of A=0.43 and B=500.0