Performance analysis and scheduling strategies for ambulatory surgical facilities

Ambulatory surgery is a procedure that does not require an overnight hospital stay and is cost effective and efficient. The goal of this research is to develop an ASF operational model which allows management to make key decisions. This research develops and utilizes the simulation software ARENA based model to accommodate: (a) Time related uncertainties – Three system uncertainties characterize the problem (ii) Surgery time variance (ii) Physician arrival delay and (iii) Patient arrival delay; (b) Resource Capture Complexities – Patient flows vary significantly and capture/utilize both staffing and/or physical resources at different points and varying levels; and (c) Processing Time Differences – Patient care activities and surgical operation times vary by type and have a high level of variance between patient acuity within the same surgery type. A multi-dimensional ASF non-clinical performance objective is formulated and includes: (i) Fixed Labor Costs – regular time staffing costs for two nurse groups and medical/tech assistants, (i i) Overtime Labor Costs – staffing costs beyond the regular schedule, (i i i) Patient Delay Penalty – Imputed costs of waiting time experienced patients, and (iv) Physician Delay Penalty – Imputed costs of physicians having to delay surgical procedures due to ASF causes (limited staffing, patient delays, blocked OR, etc.). Three ASF decision problems are studied: (i) Optimize Staffing Resources Levels - Variations in staffing levels though are inversely related to patient waiting times and physician delays. The decision variable is the number of staff for three resource groups, for a given physician assignment and surgery profile. The results show that the decision space is convex, but decision robustness varies by problem type. For the problems studied the optimal levels provided 9% to 28% improvements relative to the baseline staffing level. The convergence rate is highest for less than optimal levels of Nurse-A. The problem is thus amenable to a gradient based search. (ii) Physician Block Assignment - The decision variables are the block assignments and the patient arrivals by type in each block. Five block assignment heuristics are developed and evaluated. Heuristic #4 which utilizes robust activity estimates (75% likelihood) and generates an asymmetrical resource utilization schedule, is found to be statistically better or equivalent to all other heuristics for 9 out of the 10 problems and (iii) Patient Arrival Schedule – Three decision variables in the patient arrival control (a) Arrival time of first patient in a block (b) The distribution and sequence of patients for each surgery type within the assigned windows and (c) The inter arrival time between patients, which could be constant or varying. Seven scheduling heuristics were developed and tested. Two heuristics one based on Palmers Rule and the other based on the SPT (Shortest Processing Time) Rule gave very strong results

Evolutionary-Based Online Motion Planning Framework for Quadruped Robot Jumping

Offline evolutionary-based methodologies have supplied a successful motion planning framework for the quadrupedal jump. However, the time-consuming computation caused by massive population evolution in offline evolutionary-based jumping framework significantly limits the popularity in the quadrupedal field. This paper presents a time-friendly online motion planning framework based on meta-heuristic Differential evolution (DE), Latin hypercube sampling, and Configuration space (DLC). The DLC framework establishes a multidimensional optimization problem leveraging centroidal dynamics to determine the ideal trajectory of the center of mass (CoM) and ground reaction forces (GRFs). The configuration space is introduced to the evolutionary optimization in order to condense the searching region. Latin hypercube sampling offers more uniform initial populations of DE under limited sampling points, accelerating away from a local minimum. This research also constructs a collection of pre-motion trajectories as a warm start when the objective state is in the neighborhood of the pre-motion state to drastically reduce the solving time. The proposed methodology is successfully validated via real robot experiments for online jumping trajectory optimization with different jumping motions (e.g., ordinary jumping, flipping, and spinning).Comment: IROS202

Insulin resistance predicts progression of de novo atherosclerotic plaques in patients with coronary heart disease: a one-year follow-up study

BACKGROUND: The aim of our study was to explore and evaluate the relationship between insulin resistance and progression of coronary atherosclerotic plaques. With the great burden coronary heart disease is imposing on individuals, healthcare professionals have already embarked on determining its potential modifiable risk factors in the light of preventive medicine. Insulin resistance has been generally recognized as a novel risk factor based on epidemiological studies; however, few researches have focused on its effect on coronary atherosclerotic plaque progression. METHODS: From June 7, 2007 to December 30, 2011, 366 patients received their index coronary angiogram and were subsequently found to have coronary atherosclerotic plaques or normal angiograms were consecutively enrolled in the study by the department of cardiology at the Ruijin Hospital, which is affiliated to the Shanghai Jiaotong University School of Medicine. All patients had follow-up angiograms after the 1-year period for evaluating the progression of the coronary lesions. The modified Gensini score was adopted for assessing coronary lesions while the HOMA-IR method was utilized for determining the state of their insulin resistance. Baseline characteristics and laboratory test results were described and the binomial regression analysis was conducted to investigate the relationship between insulin resistance and coronary atherosclerotic plaque progression. RESULTS: Index and follow-up Gensini scores were similar between the higher insulin lower insulin resistant groups (9.09 ± 14.33 vs 9.44 ± 12.88, p = 0.813 and 17.21 ± 18.46 vs 14.09 ± 14.18, p =0.358). However the Gensini score assessing coronary lesion progression between both visits was significantly elevated in the higher insulin resistant group (8.13 ± 11.83 versus 4.65 ± 7.58, p = 0.019). Multivariate logistic binomial regression analysis revealed that insulin resistance (HOMA-IR > 3.4583) was an independent predictor for coronary arterial plaque progression (OR = 4.969, p = 0.011). We also divided all the participants into a diabetic (n = 136) and a non-diabetic group (n = 230), and HOMA-IR remained an independent predictor for atherosclerosis plaque progression. CONCLUSIONS: Insulin resistance is an independent predictor of atherosclerosis plaque progression in patients with coronary heart disease in both the diabetic and non-diabetic population

Incidence of patients with bone metastases at diagnosis of solid tumors in adults: a large population-based study

Background: Bones are one of the most common metastatic sites for solid malignancies. Bone metastases can significantly increase mortality and decrease the quality of life of cancer patients. In the United States, around 350,000 people die each year from bone metastases. This study aimed to analyze and update the incidence and prognosis of bone metastases with solid tumors at the time of cancer diagnosis and its incidence rate for each solid cancer.Methods: We used the Surveillance, Epidemiology, and End Results (SEER) database to find patients diagnosed with solid cancers originating from outside the bones and joints between 2010 and 2016. Data were stratified by age, sex, and race. Patients with a tumor in situ or with an unknown bone metastases stage were excluded. We then selected most of the sites where cancer often occurred, leaving 2,207,796 patients for the final incidence analysis. For the survival analysis, patients were excluded if they were diagnosed at their autopsy or on their death certificate, or had unknown follow-ups. The incidence of bone metastases and overall survival was compared between patients with different primary tumor sites.Results: We identified 2,470,634 patients, including 426,594 patients with metastatic disease and 113,317 patients with bone metastases, for incidence analysis. The incidence of bone metastases among the metastatic subset was 88.74% in prostate cancer, 53.71% in breast cancer, and 38.65% in renal cancer. In descending order of incidence, there were patients with other cancers in the genitourinary system (except for renal, bladder, prostate, and testicular cancer) (37.91%), adenocarcinoma of the lung (ADC) (36.86%), other gynecologic cancers (36.02%), small- cell lung cancer (SCLC) (34.56%), non-small cell lung cancer not otherwise specified and others [NSCLC (NOS/others)] (33.55%), and bladder (31.08%) cancers. The rate of bone metastases is 23.19% in SCLC, 22.50% in NSCLC (NOS/others), 20.28% in ADC, 8.44% in squamous cell carcinoma of the lung (SCC), and 4.11% in bronchioloalveolar carcinoma [NSCLC (BAC)]. As for the digestive system, the overall bone metastases rate was 7.99% in the esophagus, 4.47% in the gastric cancer, 4.42% in the hepatobiliary cancer, 3.80% in the pancreas, 3.26% in other digestive organs, 1.24% in the colorectum, and 1.00% in the anus. Overall, the incidence rate of bone metastases among the entire cohort in breast and prostate cancer was 3.73% and 5.69%, respectively.Conclusions: The results of this study provide population-based estimates for the incidence rates of patients with bone metastases at initial diagnosis of their solid tumor. The findings can help clinicians to early detect bone metastases by bone screening to anticipate the occurrence of symptoms and favorably improve the prognosis

Leg Trajectory Planning for Quadruped Robots with High-Speed Trot Gait

In this paper, a single leg platform for quadruped robots is designed based on the motivation of high-speed locomotion. The leg is designed for lightweight and low inertia with a structure of three joints by imitating quadruped animals. Because high acceleration and extensive loadings will be involved on the legs during the high-speed locomotion, the trade-off between the leg mass and strength is specifically designed and evaluated with the finite element analysis. Moreover, quadruped animals usually increase stride frequency and decrease contact time as the locomotion speed increases, while maintaining the swing duration during trot gait. Inspired by this phenomenon, the foot-end trajectory for quadruped robots with a high-speed trot gait is proposed. The gait trajectory is planned for swing and stance phase; thus the robot can keep its stability with adjustable trajectories while following a specific gait pattern. Especially for the swing phase, the proposed trajectory can minimize the maximum acceleration of legs and ensure the continuity of position, speed, and acceleration. Then, based on the kinematics analysis, the proposed trajectory is compared with the trajectory of Bézier curve for the power consumption. Finally, a simulation with Webots software is carried out for verifying the motion stability with two trajectory planning schemes respectively. Moreover, a motion capture device is used for evaluating the tracking accuracy of two schemes for obtaining an optimal gait trajectory suitable for high-speed trot gait

Multi-parameter evaluation of lumbar intervertebral disc degeneration using quantitative magnetic resonance imaging techniques

Objective: To quantitatively evaluate lumbar disc degeneration with recently-developed quantitative magnetic resonance imaging (MRI) techniques. A series of MRI parameters, including T2*, T1rho relaxation time, apparent diffusion coefficient and gagCEST, were compared and correlated with the Pfirrmann semi-quantitative classification of lumbar intervertebral disc degeneration; the most accurate and relevant MRI parameters of lumbar disc degeneration were identified. Materials and Methods: Thirty-seven subjects (age range, 18-74 years) with non-specific low back pain (LBP) for more than 6 months were enrolled. The L1/2-L5/S1 discs of each subject were measured and then analyzed. Results: The gagCEST value of the discs showed the best negative correlation with degeneration level (nucleus pulposus: r = -0.951, P < 0.001; annulus fibrosus: r = -0.938, P < 0.001). The discriminant analysis results showed that this parameter also had the highest correct rate using a single index (gagCEST discriminant accuracy = 82%). Conclusion: Early stage lumbar disc degeneration can be quantitatively evaluated with MRI using the chemical exchange saturation transfer technique

Mechanical properties of a new fully prefabricated staggered flip-down slab

Prefabricated slab has been widely used in the global construction industry due to energy saving, environmental protection, and good economic advantages. In this paper, a new type of fully prefabricated staggered flip-down slab without cast-in-situ operation has been proposed. First, the experiments were carried out on the new slab. The structural performance of the new slab was compared with the cast-in-situ slabs and composite slabs of the same specification. The experimental results showed that the ultimate bearing capacity of the new slab meets the requirements for practical utilization. On this basis, an additional CFRP sheet could be pasted on the bottom initial seam between prefabricated slabs to enhance the integrity and prevent cracks. Then, the whole loading process of the slab was simulated, and the results were consistent with the experimental results. Finally, through experiments and parametric analysis, recommendations for improvement were put forward to enhance the mechanical properties of this kind of slab