An ontology-based nurse call management system (oNCS) with probabilistic priority assessment

<p>Abstract</p> <p>Background</p> <p>The current, place-oriented nurse call systems are very static. A patient can only make calls with a button which is fixed to a wall of a room. Moreover, the system does not take into account various factors specific to a situation. In the future, there will be an evolution to a mobile button for each patient so that they can walk around freely and still make calls. The system would become person-oriented and the available context information should be taken into account to assign the correct nurse to a call.</p> <p>The aim of this research is (1) the design of a software platform that supports the transition to mobile and wireless nurse call buttons in hospitals and residential care and (2) the design of a sophisticated nurse call algorithm. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff members and patients into account. Additionally, the priority of a call probabilistically depends on the risk factors, assigned to a patient.</p> <p>Methods</p> <p>The <it>ontology-based Nurse Call System (oNCS) </it>was developed as an extension of a <it>Context-Aware Service Platform</it>. An ontology is used to manage the profile information. Rules implement the novel nurse call algorithm that takes all this information into account. Probabilistic reasoning algorithms are designed to determine the priority of a call based on the risk factors of the patient.</p> <p>Results</p> <p>The <it>oNCS </it>system is evaluated through a prototype implementation and simulations, based on a detailed dataset obtained from Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls amongst nurses and the assignment of priorities to calls are compared for the <it>oNCS </it><it>system </it>and the current, place-oriented nurse call system. Additionally, the performance of the system is discussed.</p> <p>Conclusions</p> <p>The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the <it>oNCS system </it>significantly improves the assignment of nurses to calls. Calls generally have a nurse present faster and the workload-distribution amongst the nurses improves.</p

Temporal Artery versus Bladder Thermometry during Adult Medical-Surgical Intensive Care Monitoring: An Observational Study

Abstract Background We sought to evaluate agreement between a new and widely implemented method of temperature measurement in critical care, temporal artery thermometry and an established method of core temperature measurement, bladder thermometry as performed in clinical practice. Methods Temperatures were simultaneously recorded hourly (n = 736 observations) using both devices as part of routine clinical monitoring in 14 critically ill adult patients with temperatures ranging ≥1°C prior to consent. Results The mean difference between temporal artery and bladder temperatures measured was -0.44°C (95% confidence interval, -0.47°C to -0.41°C), with temporal artery readings lower than bladder temperatures. Agreement between the two devices was greatest for normothermia (36.0°C to < 38.3°C) (mean difference -0.35°C [95% confidence interval, -0.37°C to -0.33°C]). The temporal artery thermometer recorded higher temperatures during hypothermia (< 36°C) (mean difference 0.66°C [95% confidence interval, 0.53°C to 0.79°C]) and lower temperatures during hyperthermia (≥38.3°C) (mean difference -0.90°C [95% confidence interval, -0.99°C to -0.81°C]). The sensitivity for detecting fever (core temperature ≥38.3°C) using the temporal artery thermometer was 0.26 (95% confidence interval, 0.20 to 0.33), and the specificity was 0.99 (95% confidence interval, 0.98 to 0.99). The positive likelihood ratio for fever was 24.6 (95% confidence interval, 10.7 to 56.8); the negative likelihood ratio was 0.75 (95% confidence interval, 0.68 to 0.82). Conclusions Temporal artery thermometry produces somewhat surprising disagreement with an established method of core temperature measurement and should not to be used in situations where body temperature needs to be measured with accuracy

Use of patients’ classification instruments: analysis of the brazilian production of knowledge

Objective To analyze the production of scientific knowledge about the use of patients’ classification instruments in care and management practice in Brazil. Method Integrative literature review with databases search in: Latin American and Caribbean Literature on Health Sciences (LILACS), Medical Literature Analysis and Retrieval System on-line (MEDLINE), Cumulative Index to Nursing and Allied Health Literature (CINAHL) and SCOPUS, between January 2002 through December 2013. Results 1,194 studies were found, 31 met the inclusion criteria. We observed a higher number of studies in the category care plans and workload (n=15), followed by the category evaluation of psychometric properties (n=14). Conclusion Brazilian knowledge production has not yet investigated some purposes of using instruments for classifying patients in professional nursing practice. The identification of unexplored areas can guide future research on the topic