A single-entry model and wait time for hip and knee replacement in eastern health region of Newfoundland and Labrador 2011–2019

Background A single-entry model in healthcare consolidates waiting lists through a central intake and allows patients to see the next available health care provider based on the prioritization. This study aimed to examine whether and to what extent the prioritization reduced wait times for hip and knee replacement surgeries. Method The survival regression method was used to estimate the effects of priority levels on wait times for consultation and surgery for hip and knee replacements. The sample data included patients who were referred to the Orthopedic Central Intake clinic at the Eastern Health region of Newfoundland and Labrador and had surgery of hip and knee replacements between 2011 and 2019. Result After adjusting for covariates, the hazard of having consultation booked was greater in patients with priority 1 and 2 than those in priority 3 when and at 90 days after the referral was made for both hip and knee replacements. Regarding wait time for surgery after the decision for surgery was made, while the hazard of having surgery was lower in priority 2 than in priority 3 when and indifferent at 182 days after the decision was made, it was not significantly different between priority 1 and priority 3 among hip replacement patients. Priority levels were not significantly related to the hazard of having surgery for a knee replacement after the decision for surgery was made. Overall, the hazard of having surgery after the referral was made by a primary care physician was greater for patients in high priority than those in low priority. Preferring a specific surgeon indicated at referral was found to delay consultation and it was not significantly related to the total wait time for surgery. Incomplete referral forms prolonged wait time for consultation and patients under age 65 had a longer total wait time than those aged 65 or above. Conclusion Patients with high priority could have a consultation booked earlier than those with low priority and prioritization in a single entrance model shortens the total wait time for surgery. However, the association between priority levels and wait for surgery after the decision for surgery was made has not well-established.

Hydrodynamics of High-Speed Planing Craft: Savitsky Method and 2D+t Approach

The progressive interest in high-speed planing craft has made it crucial to conduct more accurate assessments of the behavior of these vessels in motion. In this paper, a 2D+t approach is employed to predict the resistance, trim and wetted length of a prismatic planing craft cruising in calm water. Although this approach is based on original Zarnick 2D+t model, the hydrodynamic force is estimated using experimental wedge drop experiments in conjunction with the Logvinovich wedge water entry model. The analysis is repeated employing Savitsky prediction method and results are compared with that of towing tank measurements of Naples series. The comparison shows that the Savitsky prediction results match very well with the experimental data. The 2D+t approach also shows reasonable outcomes for the trim and wetted length. However, this approach slightly underestimates the resistance of the craft at very low Froude numbers.

Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study

Background Healthcare associated infections (HAI) are a major burden for the healthcare system and associated with prolonged hospital stay, increased morbidity, mortality and costs. Healthcare associated urinary tract infections (HA-UTI) accounts for about 20–30% of all HAI’s, and with the emergence of multi-resistant urinary tract pathogens, the total burden of HA-UTI will most likely increase. Objective The aim of the current study was to develop two predictive models, using data from the index admission as well as historic data on a patient, to predict the development of UTI at the time of entry to the hospital and after 48 hours of admission (HA-UTI). The ultimate goal is to predict the individual patient risk of acquiring HA-UTI before it occurs so that health care professionals may take proper actions to prevent it. Methods Retrospective cohort analysis of approx. 300 000 adult admissions in a Danish region was performed. We developed models for UTI prediction with five machine-learning algorithms using demographic information, laboratory results, data on antibiotic treatment, past medical history (ICD10 codes), and clinical data by transformation of unstructured narrative text in Electronic Medical Records to structured data by Natural Language Processing. Results The five machine-learning algorithms have been evaluated by the performance measures average squared error, cumulative lift, and area under the curve (ROC-index). The algorithms had an area under the curve (ROC-index) ranging from 0.82 to 0.84 for the entry model (T = 0 hours after admission) and from 0.71 to 0.77 for the HA-UTI model (T = 48 hours after admission). Conclusion The study is proof of concept that it is possible to create machine-learning models that can serve as early warning systems to predict patients at risk of acquiring urinary tract infections during admission. The entry model and the HA-UTI models perform with a high ROC-index indicating a sufficient sensitivity and specificity, which may make both models instrumental in individualized prevention of UTI in hospitalized patients. The favored machine-learning methodology is Decision Trees to ensure the most transparent results and to increase clinical understanding and implementation of the models.

La combinatoria de peur con verbos en un diccionario sintáctico-combinatorio bilingüe francés-español (TACTICOMB)

Corpus-based combinatorial dictionaries are spreading, some for the general public and others for a specialized audience. We have also recently found some recent projects of bilingual combinatorial dictionaries that show the need for a reflection on the interface between the two languages. In our case, our goal is to design a bilingual French-Spanish combinatorial dictionary (TACTICOMB) that serves effectively for production and translation by combining semantic, syntactic and combinatorial elements and by developing the notion of mesostructure, the interface for passing from one language to another. We will illustrate the design of the dictionary through an entry model for combinatory of the noun peur with verbs.

A Local-Exchange Model of Folding Chain Surface of Polymer Crystal Based on Worm-Like Chain Model within Single-Chain in Mean-Field Theory

The structure of amorphous layer of folding surface controls the properties of the polymer lamellar crystal, which consists of chains with a loop conformation. The surface tension depends on the length and the distance between two injection points of the loop which involving the reptation motion and lateral exchange motion of the stems. In the present work, a local-exchange motion model based on the worm-like chain model is developed to investigate the effects of lateral motion of stems on the release the surface tension. The optimal distance between two injection points is determined by the balance of chain bending energy and conformational entropy. The numerical results provide evidences to the adjacent re-entry model for various loop lengths. A possible explanation involving density of injection points is proposed to interpret the mechanism.

An integrated-dynamic mode of entry model: global MNEs entering into emerging markets

Purpose The purpose of this paper is to develop a conceptual model for the mode of entry in a particular case of global MNEs entering into emerging markets. Design/methodology/approach The conceptual model builds on institutional theory and follows an integrated approach of entry mode theories using bargaining theory, the liability of foreignness and local legitimacy. Findings The conceptual model introduces five propositions. Research limitations/implications The study has policy implications for emerging market institutions. Also, the model highlights the significance of long-term vision in global MNEs’ sustainability. However, the model excludes the MNEs’ internal institutions, home country institutions, as well as institutional and cognitive distances. Originality/value The conceptual model addresses the dynamics of MNEs’ entry decisions with long-term strategic vision. It helps to recognize the global MNEs’ internalization of the host country’s formal and informal institutions when the bargaining power is in imbalance.

Improving the quality of care with a single-entry model of referral for total joint replacement: a preimplementation/postimplementation evaluation

ObjectivesWe assessed: (1) waiting time variation among surgeons; (2) proportion of patients receiving surgery within benchmark and (3) influence of the Winnipeg Central Intake Service (WCIS) across five dimensions of quality: accessibility, acceptability, appropriateness, effectiveness, safety.DesignPreimplementation/postimplementation cross-sectional design comparing historical (n=2282) and prospective (n=2397) cohorts.SettingRegional, provincial health authority.ParticipantsPatients awaiting total joint replacement of the hip or knee.InterventionsThe WCIS is a single-entry model (SEM) to improve access to total hip replacement (THR) or total knee replacement (TKR) surgery, implemented to minimise variation in total waiting time (TW) across orthopaedic surgeons and increase the proportion of surgeries within 26 weeks (benchmark). Impact of SEMs on quality of care is poorly understood.Primary and secondary outcome measuresPrimary outcomes related to ‘accessibility’: waiting time variation across surgeons, waiting times (Waiting Time 2 (WT2)=decision to treat until surgery and TW=total waiting time) and surgeries within benchmark. Analysis included descriptive statistics, group comparisons and clustered regression.ResultsVariability in TW among surgeons was reduced by 3.7 (hip) and 4.3 (knee) weeks. Mean waiting was reduced for TKR (WT2/TW); TKR within benchmark increased by 5.9%. Accessibility and safety were the only quality dimensions that changed (post-WCIS THR and TKR). Shorter WT2 was associated with post-WCIS (knee), worse Oxford score (hip and knee) and having medical comorbidities (hip). Meeting benchmark was associated with post-WCIS (knee), lower Body Mass Index (BMI) (hip) and worse Oxford score (hip and knee).ConclusionsThe WCIS reduced variability across surgeon waiting times, with modest reductions in overall waits for surgery. There was improvement in some, but not all, dimensions of quality.