Impact of planning horizon length on traits in an economic breeding goal and ranking of selection candidates in beef cattle.

In beef production herds, unique situations such as breeding system, economic parameters, and current phenotypic performance can affect the emphasis of traits in the breeding goal and consequently the weighting of traits within a selection index. An often overlooked component of breeding goals is the planning horizon, or the time span to consider the economic impact of a selection decision, that varies between enterprises. A platform for constructing economic selection indexes (iGENDEC) was used to determine the impact of planning horizon length, breeding system, and sale endpoint on the relative emphasis of traits in the breeding goal and the re-ranking of selection candidates.

Molecular Mechanisms Associated with the Development of the Metritis Complex in Dairy Cattle.

The metritis complex (MC), a group of post-partum uterine diseases, is associated with increased treatment costs and reduced milk yield and fertility. The goal of this study was to identify genetic variants, genes, or genomic regions that modulate MC disease. A genome-wide association study was performed using a single-locus mixed linear model of 1967 genotypes (624,460 SNPs) and metritis complex records.

Evaluating preferences for colorectal cancer screening in individuals under age 50 using the Analytic Hierarchy Process.

Background: In 2021, the United States Preventive Services Task Force updated their recommendation, stating that individuals ages 45-49 should initiate screening for colorectal cancer. Since several screening strategies are recommended, making a shared decision involves including an individual's preferences. Few studies have included individuals under age 50.

Voice Interface Technology Adoption by Patients With Heart Failure: Pilot Comparison Study.

Background: Heart failure (HF) is associated with high mortality rates and high costs, and self-care is crucial in the management of the condition. Telehealth can promote patients' self-care while providing frequent feedback to their health care providers about the patient's compliance and symptoms. A number of technologies have been considered in the literature to facilitate telehealth in patients with HF.

Categorization of birth weight phenotypes for inclusion in genetic evaluations using a deep neural network.

Birth weight (BW) serves as a valuable indicator of the economically relevant trait of calving ease (CE), and erroneous data collection for BW could impact genetic evaluations for CE. The objective of the current study was to evaluate the use of deep neural networks (DNNs) for classifying contemporary groups (CGs) based on the method used to generate BW phenotypes. CGs (n = 120,000,000) ranging between 10 and 250 animals were simulated assuming 12 data collection and CG formation scenarios that could impact CG phenotypic variance, including weights recorded with a digital scale (REAL), hoof tape (TAPE), erroneous data collection (DIRTY), and those that were fabricated (FAB).

A continuous-time Markov model for estimating readmission risk for hospital inpatients.

Research concerning hospital readmissions has mostly focused on statistical and machine learning models that attempt to predict this unfortunate outcome for individual patients. These models are useful in certain settings, but their performance in many cases is insufficient for implementation in practice, and the dynamics of how readmission risk changes over time is often ignored. Our objective is to develop a model for aggregated readmission risk over time - using a continuous-time Markov chain - beginning at the point of discharge.

Impact of Global Budget Revenue Policy on Emergency Department Efficiency in the State of Maryland.

Introduction: On January 1, 2014, the State of Maryland implemented the Global Budget Revenue (GBR) program. We investigate the impact of GBR on length of stay (LOS) for inpatients in emergency departments (ED) in Maryland.

Methods: We used the Hospital Compare data reports from the Centers for Medicare and Medicaid Services (CMS) and CMS Cost Reports Hospital Form 2552-10 from January 1, 2012-March 31, 2016, with GBR hospitals from Maryland and hospitals from West Virginia (WV), Delaware (DE), and Rhode Island (RI).

Genetic correlations among weight and cumulative productivity of crossbred beef cows.

Mature weight of beef cows in the United States has been increasing as a correlated response to selection for calf growth. Unfavorable genetic correlations between cow weight and various measures of female fertility, stayability, and lifetime production suggest declining cow productivity might also be expected as a correlated response to growth selection. National cattle evaluations, however, show increasing trends for stayability and sustained fertility.

Impact of Health Policy Changes on Emergency Medicine in Maryland Stratified by Socioeconomic Status.

Introduction: On January 1, 2014, the financing and delivery of healthcare in the state of Maryland (MD) profoundly changed. The insurance provisions of the Patient Protection and Affordable Care Act (ACA) began implementation and a major revision of MD's Medicare waiver ushered in a Global Budget Revenue (GBR) structure for hospital reimbursement. Our objective was to analyze the impact of these policy changes on emergency department (ED) utilization, hospitalization practices, insurance profiles, and professional revenue.

Comparison of alternative approaches to single-trait genomic prediction using genotyped and non-genotyped Hanwoo beef cattle.

Background: Genomic predictions from BayesA and BayesB use training data that include animals with both phenotypes and genotypes. Single-step methodologies allow additional information from non-genotyped relatives to be included in the analysis. The single-step genomic best linear unbiased prediction (SSGBLUP) method uses a relationship matrix computed from marker and pedigree information, in which missing genotypes are imputed implicitly.

Computational strategies for alternative single-step Bayesian regression models with large numbers of genotyped and non-genotyped animals.

Background: Two types of models have been used for single-step genomic prediction and genome-wide association studies that include phenotypes from both genotyped animals and their non-genotyped relatives. The two types are breeding value models (BVM) that fit breeding values explicitly and marker effects models (MEM) that express the breeding values in terms of the effects of observed or imputed genotypes. MEM can accommodate a wider class of analyses, including variable selection or mixture model analyses.

Drivers of ED efficiency: a statistical and cluster analysis of volume, staffing, and operations.

Study Objective: The percentage of patients leaving before treatment is completed (LBTC) is an important indicator of emergency department performance. The objective of this study is to identify characteristics of hospital operations that correlate with LBTC rates.

Methods: The Emergency Department Benchmarking Alliance 2012 and 2013 cross-sectional national data sets were analyzed using multiple regression and k-means clustering.

The impact of electronic health record implementation on emergency physician efficiency and patient throughput.

Background: In emergency departments (EDs), the implementation of electronic health records (EHRs) has the potential to impact the rapid assessment and management of life threatening conditions. In order to quantify this impact, we studied the implementation of EHRs in the EDs of a two hospital system.

Methods: using a prospective pre-post study design, patient processing metrics were collected for each ED physician at two hospitals for 7 months prior and 10 months post-EHR implementation.

Contribution of interfacility patient movement to overall methicillin-resistant Staphylococcus aureus prevalence levels.

Objectives: The effect of patient movement between hospitals and long-term care facilities (LTCFs) on methicillin-resistant Staphylococcus aureus (MRSA) prevalence levels is unknown. We investigated these effects to identify scenarios that may lead to increased prevalence in either facility type.

Methods: We used a hybrid simulation model to simulate MRSA transmission among hospitals and LTCFs.

The impact of hospital utilization on patient readmission rate.

We investigate the issue of patient readmission at a large academic hospital in the U.S. Specifically, we look for evidence that patients discharged when post-operative unit utilization is high are more likely to be readmitted.

Examining the discharge practices of surgeons at a large medical center.

We investigate the discharge practices at a large medical center. Specifically, we look for indications that patients are being discharged sooner because of hospital bed-capacity constraints. Using survival analysis techniques, we find statistically significant evidence to indicate that surgeons adjust their discharge practices to accommodate the surgical schedule and number of available recovery beds.