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.

Digital health: a path to validation.

Digital health solutions continue to grow in both number and capabilities. Despite these advances, the confidence of the various stakeholders - from patients and clinicians to payers, industry and regulators - in medicine remains quite low. As a result, there is a need for objective, transparent, and standards-based evaluation of digital health products that can bring greater clarity to the digital health marketplace. We believe an approach that is guided by end-user requirements and formal assessment across technical, clinical, usability, and cost domains is one possible solution. For digital health solutions to have greater impact, quality and value must be easier to distinguish. To that end, we review the existing landscape and gaps, highlight the evolving responses and approaches, and detail one pragmatic framework that addresses the current limitations in the marketplace with a path toward implementation.

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.

Intensive care unit providers more quickly and accurately assess risk of multiple harms using an engineered safety display.

Project Emerge took a systems engineering approach to reduce avoidable harm in the intensive care unit. We developed a socio-technology solution to aggregate and display information relevant to preventable patient harm. We compared providers' efficiency and ability to assess and assimilate data associated with patient-safety practice compliance using the existing electronic health record to Emerge, and evaluated for speed, accuracy, and the number of mouse clicks required. When compared to the standard electronic health record, clinicians were faster (529 ± 210 s vs 1132 ± 344 s), required fewer mouse clicks (42.3 ± 15.3 vs 101.3 ± 33.9), and were more accurate (24.8 ± 2.7 of 28 correct vs 21.2 ± 2.9 of 28 correct) when using Emerge. All results were statistically significant at a p-value < 0.05 using Wilcoxon signed-rank test (n = 18). Emerge has the potential to make clinicians more productive and patients safer by reducing the time and errors when obtaining information to reduce preventable harm.

Developing a Comprehensive Model of Intensive Care Unit Processes: Concept of Operations.

OBJECTIVES: This study aimed to use a systems engineering approach to improve performance and stakeholder engagement in the intensive care unit to reduce several different patient harms. METHODS: We developed a conceptual framework or concept of operations (ConOps) to analyze different types of harm that included 4 steps as follows: risk assessment, appropriate therapies, monitoring and feedback, as well as patient and family communications. This framework used a transdisciplinary approach to inventory the tasks and work flows required to eliminate 7 common types of harm experienced by patients in the intensive care unit. The inventory gathered both implicit and explicit information about how the system works or should work and converted the information into a detailed specification that clinicians could understand and use. PROTOTYPE CONOPS TO ELIMINATE HARM: Using the ConOps document, we created highly detailed work flow models to reduce harm and offer an example of its application to deep venous thrombosis. In the deep venous thrombosis model, we identified tasks that were synergistic across different types of harm. We will use a system of systems approach to integrate the variety of subsystems and coordinate processes across multiple types of harm to reduce the duplication of tasks. Through this process, we expect to improve efficiency and demonstrate synergistic interactions that ultimately can be applied across the spectrum of potential patient harms and patient locations. CONCLUSIONS: Engineering health care to be highly reliable will first require an understanding of the processes and work flows that comprise patient care. The ConOps strategy provided a framework for building complex systems to reduce patient harm.

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.