ABSTRACT
Nutrient management on US dairy farms must balance an array of priorities, some of which conflict. To illustrate nutrient management challenges and opportunities across the US dairy industry, the USDA Agricultural Research Service Dairy Agroecosystems Working Group (DAWG) modeled 8 confinement and 2 grazing operations in the 7 largest US dairy-producing states using the Integrated Farm System Model (IFSM). Opportunities existed across all of the dairies studied to increase on-farm feed production and lower purchased feed bills, most notably on large dairies (>1,000 cows) with the highest herd densities. Purchased feed accounted for 18 to 44% of large dairies' total operating costs compared with 7 to 14% on small dairies (<300 milk cows) due to lower stocking rates. For dairies with larger land bases, in addition to a reduction in environmental impact, financial incentives exist to promote prudent nutrient management practices by substituting manure nutrients or legume nutrients for purchased fertilizers. Environmental priorities varied regionally and were principally tied to facility management for dry-lot dairies of the semi-arid western United States (ammonia-N emissions), to manure handling and application for humid midwestern and eastern US dairies (nitrate-N leaching and P runoff), and pasture management for dairies with significant grazing components (nitrous oxide emissions). Many of the nutrient management challenges identified by DAWG are beyond slight modifications in management and require coordinated solutions to ensure an environmentally and economically sustainable US dairy industry.
Subject(s)
Animal Feed/standards , Animal Nutritional Physiological Phenomena , Cattle/physiology , Dairying/methods , Animals , Female , Manure , Nutritional Requirements , Phosphorus , United States , United States Department of AgricultureABSTRACT
BACKGROUND AND OBJECTIVES: Traditional methods of resident evaluation have several limitations, including recall bias and memory decay. We developed a real-time, computerized, data-based evaluation system and determined 1) the feasibility of using such a system in an ambulatory care teaching center and 2) the types of evaluation data such a computer-based evaluation system provides to residency directors, faculty, and residents. METHODS: We developed Precept-Assist, a computerized, data-based evaluation system. Reports from the system provide quantitative data, summative reports, and qualitative comments regarding specific competencies of residents. Following each precepting encounter between a faculty member and a resident, the faculty member entered into the system an array of coded information on the resident's level of performance, competencies achieved, and procedural skills. RESULTS: We have entered more than 15,000 pieces of evaluative data on 4,504 precepting encounters. The average time to enter data was about 40 seconds per encounter. Reports were generated to monitor each resident's progress through the program. The information was used to generate learning plans tailored to each resident's needs. CONCLUSIONS: Precept-Assist was useful for evaluating the performance of residents in this study.
Subject(s)
Computers , Educational Measurement/methods , Internship and Residency , Employee Performance Appraisal/methods , Family Practice/education , Feasibility Studies , HumansABSTRACT
BACKGROUND: A patient at the Tatem-Brown Family Practice Center with many medical problems asked for advice about elective surgical resection of a large abdominal aortic aneurysm. METHODS: The best course of action was not obvious, so a decision tree was constructed using data from the medical literature and the patient's rating of several quality of life issues. RESULTS: Elective surgery was the optimal choice for this patient, but the decision was sensitive to values chosen for two variables in the decision model. CONCLUSION: Decision analysis has benefits in a family practice residency. Residents become familiar with vigorous literature review and decision-analytic tools and principles. They gain a deeper knowledge of the patient, due to the need to understand the patient's relative values for potential outcomes of medical intervention.
