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《Journal of Radiology Nursing》2022,41(2):123-128
ObjectiveThe objective of this study was to reduce errors in a pathologic specimen with the help of a protocol systematizing the pathology specimen management process in the operating room.Materials and methodThis quasi-experimental study was carried out in the operating room unit of a research and training hospital. A protocol systematizing the process of specimen management in secure surgical pathology and prepared in light of the current literature was used as an intervention, and the effectiveness of the protocol was tested.ResultsIt was determined that the rate of adverse events decreased from .3226% (68 of 21,078) to .032% (6 of 18,706) after the protocol systematizing the surgical pathology specimen management process prepared by the researchers, and the protocol was found to be effective by 90% (P = .03).ConclusionBased on the data obtained in this study, we recommend the use of a pathologic specimen management protocol in the operating room. 相似文献
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《Diagnostic and interventional imaging》2020,101(9):555-564
PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%. 相似文献
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目的运用PDCA循环的质量管理方法,改进居家养老护理文件书写质量。方法对现存的护理质量不合格项目进行原因分析、制定改进计划、组织实施、效果评价。结果改进后的居家养老护理文件书写合格率达到98%。结论通过应用PDCA循环质量管理工具进行护理质量管理,使该中心居家养老护理文件书写水平得到大幅度提高,同时促进了该中心护理管理质量的提升。 相似文献
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Lauren Thaete 《Progress in Palliative Care》2019,27(1):10-13
Effective communication between clinicians, patients, and families at end of life is associated with better clinical outcomes. A large body of literature describes the key skills needed for effective communication. We believe that clinicians could also benefit from communication skills more commonly associated with business or law negotiations. We will demonstrate via analogy (i.e. buying a house) how four key business/law negotiation techniques – 1. Determine your Reservation and Aspiration Value; 2. Separate People from their Positions; 3. Separate Positions from Interests; and 4. Logrolling of Interests – can be applied to a difficult family meeting in a home hospice patient. 相似文献
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Julia H. Vermylen Gordon J. Wood Elaine R. Cohen Jeffrey H. Barsuk William C. McGaghie Diane B. Wayne 《Journal of pain and symptom management》2019,57(3):682-687