Prioritizing Health Care Solutions for Pressure Ulcers Using the Quality Function Deployment Process.

Reducing the incidence and morbidity of pressure ulcers remains a leading national priority in patient safety. However, the optimal strategy for a hospital or health system to address this safety goal is not straightforward given the number and complexity of available solutions. Leveraging techniques from systems engineering, such as the quality function deployment process, may provide a transparent and objective way to address this challenge. A detailed and practical application of quality function deployment is presented that demonstrates the value of applying engineering practices for prioritizing solutions for pressures ulcers specifically and can easily be adapted to other conditions.

Automated, Web-Based Solution for Bidirectional EHR-Infusion Pump Communication.

Smart Agent is a web-based solution for establishing bidirectional communication between an infusion pump and an electronic health record (EHR). It eliminates the need for clinician double check of medication administration using an infusion pump. Because the clinician already is using the EHR to review patient health information and update status, the addition of the web service would help eliminate the potential for human error when using a manual system. The Smart Agent process encompasses the reading of pertinent patient data from the EHR, determination of a new medication dosage based on an internal protocol, input of the dosage into an infusion pump, confirmation of the medication dosage acceptance at the infusion pump, and recording the medication change back into the EHR. The widespread use of Smart Agent-type algorithms with bidirectional communication capabilities would result in safer, more efficient provision of care, as well as better value.

Demonstration of a semi-autonomous hybrid brain-machine interface using human intracranial EEG, eye tracking, and computer vision to control a robotic upper limb prosthetic.

To increase the ability of brain-machine interfaces (BMIs) to control advanced prostheses such as the modular prosthetic limb (MPL), we are developing a novel system: the Hybrid Augmented Reality Multimodal Operation Neural Integration Environment (HARMONIE). This system utilizes hybrid input, supervisory control, and intelligent robotics to allow users to identify an object (via eye tracking and computer vision) and initiate (via brain-control) a semi-autonomous reach-grasp-and-drop of the object by the MPL. Sequential iterations of HARMONIE were tested in two pilot subjects implanted with electrocorticographic (ECoG) and depth electrodes within motor areas. The subjects performed the complex task in 71.4% (20/28) and 67.7% (21/31) of trials after minimal training. Balanced accuracy for detecting movements was 91.1% and 92.9%, significantly greater than chance accuracies (p < 0.05). After BMI-based initiation, the MPL completed the entire task 100% (one object) and 70% (three objects) of the time. The MPL took approximately 12.2 s for task completion after system improvements implemented for the second subject. Our hybrid-BMI design prevented all but one baseline false positive from initiating the system. The novel approach demonstrated in this proof-of-principle study, using hybrid input, supervisory control, and intelligent robotics, addresses limitations of current BMIs.

Enhancing the quality of care in the intensive care unit: a systems engineering approach.

This article presents an overview of systems engineering and describes common core principles found in systems engineering methodologies. The Patient Care Program Acute Care Initiative collaboration between the Armstrong Institute of the Johns Hopkins School of Medicine and the Gordon and Betty Moore Foundation, which will use systems engineering to reduce patient harm in the intensive care unit, is introduced. Specific examples of applying a systems engineering approach to the Patient Care Program Acute Care Initiative are presented.