Credit Scoring Models in Illinois by Farm Type: Hog, Dairy, Beef and Grain

Employing a logit model and farm-level data for Illinois from 1995 to 2004, this study explores the importance of farm-type differences in the development of credit scoring models. Apart from the conclusion that regional credit scoring models specific to each farm type are needed, the following are identified as the most pertinent factors for explaining creditworthiness: previous years working capital to gross farm return, the debt-to-asset ratio, and return on farm assets. Furthermore, beef farms have a larger marginal effect compared to grain farms on the probability of the farmer being highly creditworthy. Hog farms differ from grain farms in how the following financial characteristics affect farmer creditworthiness: solvency, profitability, and financial efficiency. These separate credit scoring models result in increased expected profit for the lender, better capital management, less bankruptcy, and less burden on the government and tax payers.creditworthiness, credit scoring, cut-off point, farm type, FBFM, Agricultural Finance,

Closing Communication Gaps for Unplanned Surgical Patients: One Pre-Op Checklist at a Time

Problem: Unplanned, inpatient surgical patients were experiencing poor outcomes and dissatisfaction with their overall care. This surgical patient population also lacked communication from their healthcare teams with regard to plans of care throughout their hospital stays. Context: This was a quality improvement project for the unplanned, inpatient surgical patient population in the Central Valley of California. Approximately 13% of this hospital’s surgical patients required post-surgical care in the inpatient units. These patients, according to unfavorable HCAHPS scores, experienced unsatisfying care and insufficient communication from their healthcare teams, including physicians and nurses. Intervention: This project implemented an Add-On Communication Tool for the unplanned surgical patients entering the operating room (OR) from the emergency department (ED) or inpatient units. Most importantly, this project reestablished the standard work of completing the pre-op checklist for all surgical patients, which is already part of the patient’s electronic medical record (EMR) in Epic HealthConnect. Measures: Measures for this quality improvement project included the pre-op checklist completion rate for all add-on, unplanned surgical patients of this hospital, including the use of the Add-On Communication Tool. The outcome measure for this project was improved communication among healthcare professionals and patients, as seen in HCAHPS scores for the unplanned, inpatient surgical patient population. Results: The pre-op checklist completion project for all unplanned, surgical patients achieved successful results over the last 10 months. Since implementation, completion rates from October 2020 to July 2021 averaged 76%, exceeding the original target of 65% for this timeframe. Additionally, the HCAHPS star rating also increased, from 2.9 stars for the 2020 performance year to 3.6 stars as of June 2021 open data. Conclusions: This project proved that effective and collaborative communication between healthcare professionals and engaged patients led to better health outcomes following unplanned surgical procedures. Consequently, patients were more satisfied and willing to comply with postoperative care instructions. Moreover, these enhanced interventions shortened hospital stays and expedited post-surgical recoveries. Keywords: unplanned surgery, pre-op checklist, surgery checklist, surgical checklist, preoperative surgical care, inpatient surgery, surgery HCAHP

Credit Scoring Models: A Comparison between Crop and Livestock Farms

This paper uses FBFM (Illinois Farm Business Farm Management Association) data to analyze several key factors in the decision to categorize borrowers into acceptable or problematic and to classify borrowers across five classes. Net worth does not play significant role in the decision process for livestock farms, whereas it is significantly important for crop farms. For livestock farms, tenure ratio is not significant across classes and is generally not significant across categories depending on the cut off point used to describe acceptable or problematic borrower. However, it is significant for crop farms. Working capital to gross farm return, return on farm assets, and asset turnover ratio are all significant for both farm types. The operating expense to gross farm return is not an independent variable for livestock farms whereas an independent and significant variable for crop farms.Financial Economics,

Lacrimal gland tumors in Turkey: types, frequency, and outcomes.

AIM: To evaluate the clinical, radiological, and treatment features of lacrimal gland tumors. METHODS: Retrospective review of 99 eyes of 92 patients with lacrimal gland tumors diagnosed and managed in a single institution between January 1999 and March 2017. Clinical and radiological features, histopathology, treatment methods, and prognosis were evaluated. RESULTS: The mean patient age was 40.3 (range: 7-80)y. The diagnosis was made histopathologically in 91 (91.9%) tumors and on a clinical and radiological basis in 8 (8.1%) tumors. Final diagnoses included idiopathic orbital inflammation (pseudotumor) in 46 (46.5%) lesions, pleomorphic adenoma in 14 (14.1%), adenoid cystic carcinoma in 12 (12.1%), granulomatous inflammation in 10 (10.1%), lymphoma in 5 (5.0%), benign reactive lymphoid hyperplasia in 3 (3.0%), dacryops in 3 (3.0%), carcinoma ex pleomorphic adenoma in 2 (2.0%), adenocarcinoma in 1 (1.0%), dermoid cyst in 1 (1.0%), cavernous hemangioma in 1 (1.0%), and leukemic infiltration in 1 (1.0%). Non-epithelial tumors comprised 64.6% ( CONCLUSION: Overall, 65% of lacrimal gland tumors were of non-epithelial origin and 32% of epithelial origin. By histopathology and clinical evaluation, 79% of lacrimal gland tumors were benign. The most common lacrimal gland tumors include idiopathic orbital inflammation (46.5%), epithelial (32.3%), and lymphoproliferative (8.1%) lesions

How do Design Heuristics Affects Outcomes?

How do designers explore design solution spaces? The typical paradigm underlying design education is project-based learning focusing on solving design problems. However, this learning approach provides open-ended design tasks for students to work on through the entire process of design. It assumes a high level of independent learning within the specific project context, and require students to transfer lessons learned to new design problems [Pietersen 2002]. When students later face a new unstructured, ambiguous design problem, they may find it challenging to apply lessons from prior project experiences. The critique method is often used to help students think more critically about their work; however, it does not provide training on how to make use of the experience in later design tasks. How do students successfully learn to address design problems? An important stage in the design process is “ideation,” which, when successful, entails applying creative thinking skills to generate novel solutions. Designers often experience limitations in generating diverse concepts [Bruseberg and McDonagh-Philp 2002]. In design pedagogy, the need for divergent thinking (generating many, varied possible solutions) is well recognized; however, instructors often do not have specific strategies about how to generate designs to teach to their students. Creative tools would help designers to generate more creative and diverse ideas during design. In previous work, we identified successful creative strategies in the fields of engineering design and industrial design [Yilmaz et al. 2010], [Yilmaz and Seifert 2010], [Yilmaz and Seifert 2011]. When tested with engineering students, the “Design Heuristics” were shown to improve the creativity of resulting designs and to produce more variety in the designs generated [Daly et al. 2011]. In the present study, we tested whether providing Design Heuristics to industrial design students would improve their design outcomes

Design Heuristics in Engineering Concept Generation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94902/1/j.2168-9830.2012.tb01121.x.pd

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