Browsing by Subject "Safety"

Background

Methods

Results

Conclusions

When designing controllers, it is important to consider their stability and safety. However, this can become difficult as the system's complexity increases. This work presents results on the persistent feasibility and stability of externally switching systems. This extends the previous results in the area, which were restricted to narrow classes of systems. The work begins with centralized systems and evolves to explore distributed classes of systems. As with other areas of control system design, distributed methods provide solutions to overcome scaling problems. There are several different tools used in this work to extend the class of systems for which safety and stability assurances can be made. Polytopic sets and their evolution under linear dynamics are used extensively. The parallelization of complex algorithms is another important tool used in these results. Parallelization is a key benefit of distributed systems and prevents the results from falling into the curse of dimensionality. Finally, novel methods of approximating and bounding values are developed, which further reduces the results' numerical complexity. While these approximations do introduce some conservatism, it is often less than the redundancy required in place of formal analysis. The full results of this work advance the study of externally switched systems to applications that, in the past, would not have been possible to study. While fully maturing the field is far too large a goal for any single doctoral dissertation, my contributions include several important advancements that have utility as stand-alone results and provide rich opportunities for future advancements in the field.

Background: Patient safety is critical to prevent medical errors and to improve clinical outcomes. The need to implement programs in patient safety is increasingly recognized as a prime component of healthcare delivery in low- and middle- income countries (LMICs). The goal for our study is to assess the implementation of a patient safety program in Guatemala.

Methods: We used a mixed-methods approach to assess implementation of a patient safety program in the pediatric perioperative unit in Hospital Roosevelt, Guatemala. We collected data from unit staff respondents (n=16) using a qualitative de novo survey, the Evidence-Based Practice Attitude Scale-36 (EBPAS-36) survey, and a semi-structured interview. Interviews and surveys were conducted in Spanish, translated, and analyzed in English using NVivo v12. Quantitative data were analyzed to compare group means across survey domains. Data were triangulated, with final analysis guided by the Consolidated Framework for Implementation Research (CFIR). Data were collected over a 10-day period in July 2018.

Results: Responses underscored several emergent thematic determinants representing the Inner Setting and Characteristics of Individuals CFIR domains, indicating a gap in knowledge of patient safety programs and attitude towards the use of evidence-based patient safety programs. Though respondents expressed an openness and willingness to adopt patient safety practices, few existing practices are in place to prevent medical errors.

Conclusions: The main determinants which affect the implementation of an evidence-based patient safety program in the pediatric perioperative unit in Guatemala are related to the internal structure and culture of the unit, and not to external factors or the intervention itself. Positive attitudes and knowledge of patient safety practices are insufficient to overcome the challenges towards implementation. A framework for future implementation should include education and communication programs, adaptation of existing practices to increase leadership engagement, and use of tools to create a strong culture of safety.

The US Food and Drug Administration (FDA) provides guidelines for maximum acoustic output for diagnostic ultrasound imaging through metrics such as intensity, Mechanical Index (MI), and Thermal Index (TI). However, even within these guideline values, if the acoustic exposure levels used do not benefit image quality, they represent an unnecessary risk to patient safety. Ultrasound users have control over many settings, including ones that directly and indirectly change the acoustic output, and the user is largely responsible for deciding how to manage the safety risks based on on-screen displays of MI and TI. The FDA and professional societies advise users to observe the ALARA (as low as reasonably achievable) principle with regard to acoustic exposure, but several studies have shown that the majority of ultrasound users do not monitor safety indices. To address this discrepancy, an adaptive ultrasound method has been developed that could be used to automatically adjust acoustic exposure in real-time in response to image quality feedback.

In this work, MI was used as the measure of acoustic output, and lag-one coherence (LOC) was the image quality feedback parameter. LOC is the average spatial correlation between backscattered echoes received on neighboring ultrasound transducer array elements. Previous work has shown that LOC is predictive of local signal-to-noise ratio (SNR), and that it is sensitive to incoherent acoustic clutter and temporally-incoherent noise. During B-mode ultrasound imaging, LOC was monitored as MI was adjusted, and the data consistently formed a sigmoid shape. At lower MI values, LOC increased quickly with increasing output, but at higher MI values, increases in acoustic output often did not translate to increased image quality. This relationship was consistent for other image quality metric-versus-MI data, including contrast, contrast-to-noise ratio (CNR), and generalized contrast-to-noise ratio (gCNR).

The MI value at which the LOC began to approach an asymptote was denoted the "ALARA MI.” In this work, ALARA MI values were calculated for a range of obstetric imaging targets that are scanned during anatomy exams, including placenta, fetal abdomen, heart, kidney, bladder, stomach, ventricles, and extremities. The placenta data had the lowest median ALARA MI (0.59) and the fetal heart data had the highest (0.83). There was considerable variation in the ALARA MI values, even for the same participant, so frequent updates to the acoustic output settings would be recommended during live scanning. Additionally, the correlation between the ALARA MI and the LOC achieved at that setting was found to be very weak.

Initially, a fixed region of interest (ROI) was used for acoustic output optimization. This would require the structure to be aligned with the ROI and the optimization process to be manually initiated. Considering the demands on the sonographer during clinical ultrasound scanning, it would not be feasible to add these steps every time a new imaging window is used. An automated ROI-selection algorithm was developed that would allow the entire adaptive acoustic output selection process to happen without user input. This algorithm used envelope-detected B-mode image data that are readily available on clinical scanners to identify where to perform the optimization. Testing on clinical placenta and fetal abdomen data showed that it reliably recommended good regions for acoustic output optimization.

The results of this work suggest that near-maximum image quality can be achieved with a lower acoustic output level than is currently used clinically, and automated acoustic output adjustments could enable more consistent observation of the ALARA principle. In the future, this could be extended to other ultrasound modes, such as Doppler imaging, and additional acoustic output metrics could be incorporated.

Preliminary assessment of temporal SNR was performed, and a wide range of temporal SNR levels is associated with the ALARA MI settings found in this study. Future work may also investigate using a temporal SNR threshold to determine the ALARA output level. Spatial coherence measurements, such as LOC, reflect the degradation in image quality from acoustic clutter and electronic noise, and temporal coherence is affected by motion and electronic noise. Although motion is an important factor in clinical imaging, temporal coherence does not require access to channel data, so these calculations would be easier to implement on existing scanners. These trade-offs are important to consider when attempting to capture the underlying electronic noise level to inform an automated ALARA ultrasound system.

Given a system's mathematical model, controller synthesis involves designing inputs to ensure desired responses. As models get more complicated to capture systems' behavior, so does synthesis. For instance, nonlinearities in differential equations invalidate linear design tools. Moreover, the state and input are typically constrained by physical limitations or safety concerns. Satisfying these constraints complicates the design. Further, since no model is perfect, the controller should account for the inevitable discrepancies. This thesis develops practical design tools by imposing specific structures on controllers and exploiting key structures in dynamical models.

The first part of this dissertation develops an offline, Lyapunov-based synthesis method for constrained control-affine systems that ensures stability and safety alongside secondary performance objectives. By limiting the search for the controller and Lyapunov function to continuous piecewise affine (CPA) functions, the Lyapunov conditions that must hold at all points in a compact set are turned into a non-convex program with a finite number of constraints defined on the vertices of a triangulated region. The non-convex program is then solved using a sequence of conservative, but well-posed semi-definite programs. This eliminates a priori design choices as well as taxing, non-convex optimizations common to existing methods. Two techniques to enlarge the region of attraction are discussed, including a state-dependent switched controller that further alleviates computations. Together with triangulation refinements, the method provides an efficient synthesis tool for constrained control-affine systems.

The second part focuses on systems modeled by a combination of subsystems. First, the previous part's method is adjusted to design for piecewise affine systems. For these systems, an important source of conservatism in design by CPA functions is eliminated, making the method competitive to those that rely on S-procedure or complex optimizations. Second, a method of constraint enforcement in presence of mode-dependent, additive disturbances for time-dependent switched systems is given. This approach extends an existing method that solves the problem for the deterministic case. The dwell-time characteristic of the external switching signal is exploited to design recursively feasible, switched tube-based model predictive controllers (MPCs). The online computations remain the same as that of a non-switched tube-based MPC.