Impossible decision? An investigation of risk trade-offs in the intensive care unit

In the intensive care unit (ICU), clinicians must often make risk trade-offs on patient care. For example, on deciding whether to discharge a patient before they have fully recovered in order to create a bed for another, sicker, patient. When misjudged, these decisions can negatively influence patient outcomes: yet it can be difficult, if not impossible, for clinicians to evaluate with certainty the safest course of action. Using a vignette-based interview methodology, a naturalistic decision-making approach was utilised to study this phenomena. The decision preferences of ICU clinicians (n=24) for two common risk trade-off scenarios were investigated. Qualitative analysis revealed the sample of clinicians to reach different, and sometimes oppositional, decision preferences. These practice variations emerged from differing analyses of risk, how decisions were ‘framed’ (e.g. philosophies on care), past experiences, and perceptions of group and organisational norms. Implications for patient safety and clinical decision-making are discussed

A Model to Create an Efficient and Equitable Admission Policy for Patients Arriving to the Cardiothoracic ICU

To develop queuing and simulation-based models to understand the relationship between ICU bed availability and operating room schedule to maximize the use of critical care resources and minimize case cancellation while providing equity to patients and surgeons. Queuing theory and computer simulation can be used to model case flow through a cardiothoracic operating room and ICU. A dynamic admission policy that looks at current waiting time and expected ICU length of stay allows for increased equity between patients with only minimum losses of efficiency. This dynamic admission policy would seem to be a superior in maximizing case-flow. These results may be generalized to other surgical ICUs

Real-World Industry Collaboration within a Mechatronics Class

This paper describes the implementation and assessment of an innovative senior/graduate level mechatronics (robotics) module that integrated structured and unstructured learning experiences, in collaboration with an industry partner. With real-world constraints and expectations, students designed and delivered a product as the final project. In fall 2007, the corporate partner provided state-of-the-art, programmable robotic kits with a user-friendly programming environment. The assigned project was to design a biomedical robot to work in a hospital intensive care unit (ICU) to perform tasks such as transporting supplies or delivering paperwork. Students with diverse skills and majors were grouped in ten teams, two to three students each. Student learning activities included designing a robot from a box of FisherTechnik materials, without the aid of instruction manuals; writing program code using the PCS environment; and integrating hardware and software. After four weeks of building, training, and testing, each team’s robot was unique. In the final competition, each robot was assigned to a particular room in the ICU to perform a specific task. Overall, the results indicated that the students gained hands-on experience with the state-of-art technology and effectively applied the conceptual course content to a real application

Bidirectional spectroreflectometer manual

Bidirectional spectroreflectometer manua

Discrete event simulation model for planning Level 2 “step-down” bed needs using NEMS

In highly congested hospitals it may be common for patients to overstay at Intensive Care Units (ICU) due to blockages and imbalances in capacity. This is inadequate clinically, as patients occupy a service they no longer need; operationally, as it disrupts flow from upstream units; and financially as ICU beds are more expensive than ward beds. Step-down beds, also known as Level 2 beds, have become an increasingly popular and less expensive alternative to ICU beds to deal with this issue. We developed a discrete event simulation model that estimates Level 2 bed needs for a large university hospital. The model innovates by simulating the entirety of the hospital’s inpatient flow and most importantly, the ICU’s daily stochastic flows based on a nursing workload scoring metrics called “Nine Equivalents of Nursing Manpower Use Score” (NEMS). Using data from a large academic hospital, the model shows the benefits of Level 2 beds in improving both patient flow and costs

Providing care quality by design: a new measure to assess hospital ward layouts

Which hospital ward layout works best? In the past, one response to this question has been to design layouts that minimise walking distances of healthcare workers, and increase the time spent with their patients. However, new research suggests that good face-to-face communication between doctors and nurses crucially impacts the health and safety of patients. Taking this into account, this research proposes a new single measure called Spaces for Communication Index (SCI). It assesses communication opportunities arising from the layout, and shows that a high index is associated with the provision of good healthcare. Six NHS wards were first studied in depth by collecting detailed information about movement and communication patterns of healthcare workers. The index was developed on this basis. Thirty-one NHS wards were then selected, based on their quality of care rating. These were used to test the index. Each ward was analysed with the Space Syntax method, which investigated the size of visual fields of healthcare workers on everyday movement paths through the ward. Large viewsheds provide good visibility and awareness of the environment. As a result, they accrue more communication opportunities by virtue of the layout. Statistical analysis was also used to test if the index can predict care quality. Other factors such as distances between key areas, number of patient beds or ward size were tested, too. Results showed that the higher the index, the better the quality of care. The other factors were not related to healthcare quality. In terms of design, these results highlight the importance of the openness of spaces that healthcare workers traverse to get from one key area to another. This research contributes to the development of an objective method that designers can use to compare different nursing unit designs, and anticipate the care quality that would be provided to patients