請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21319
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 楊立偉(Li-wei Yang) | |
dc.contributor.author | Min-Huey Chung | en |
dc.contributor.author | 鍾明惠 | zh_TW |
dc.date.accessioned | 2021-06-08T03:31:00Z | - |
dc.date.copyright | 2019-08-20 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-08-13 | |
dc.identifier.citation | Alderden, J., Pepper, G. A., Wilson, A., Whitney, J. D., Richardson, S., Butcher, R., . . . Cummins, M. R. (2018). Predicting Pressure Injury in Critical Care Patients: A Machine-Learning Model. American Journal Critical Care, 27(6), 461-468. doi:10.4037/ajcc2018525
Alderden, J., Whitney, J. D., Taylor, S. M., & Zaratkiewicz, S. (2011). Risk profile characteristics associated with outcomes of hospital-acquired pressure ulcers: a retrospective review. Critical Care Nurse, 31(4), 30-43. Amir, Y., Lohrmann, C., Halfens, R. J., & Schols, J. M. (2017). Pressure ulcers in four Indonesian hospitals: prevalence, patient characteristics, ulcer characteristics, prevention and treatment. International Wound Journal, 14(1), 184-193. Arnold-Long, M., Ayer, M., & Borchert, K. (2017). Medical device–related pressure injuries in long-term acute care hospital setting. Journal of Wound, Ostomy and Continence Nursing, 44(4), 325-330. Børsting, T. E., Tvedt, C. R., Skogestad, I. J., Granheim, T. I., Gay, C. L., & Lerdal, A. (2018). Prevalence of pressure ulcer and associated risk factors in middle‐and older‐aged medical inpatients in Norway. Journal of Clinical Nursing, 27(3-4), e535-e543. Bergstrom, N. (1987). The Braden Scale for predicting pressure sore risk. Nursing Research, 36(4), 205-210. Bhattacharya, S., & Mishra, R. (2015). Pressure ulcers: current understanding and newer modalities of treatment. Indian journal of plastic surgery: official publication of the Association of Plastic Surgeons of India, 48(1), 4. Black, J. M., Cuddigan, J. E., Walko, M. A., Didier, L. A., Lander, M. J., & Kelpe, M. R. (2010). Medical device related pressure ulcers in hospitalized patients. International Wound Journal, 7(5), 358-365. Bredesen, I. M., Bjøro, K., Gunningberg, L., & Hofoss, D. (2015). The prevalence, prevention and multilevel variance of pressure ulcers in Norwegian hospitals: a cross-sectional study. International Journal of Nursing Studies, 52(1), 149-156. Brito, P. A., de Vasconcelos Generoso, S., & Correia, M. I. T. D. (2013). Prevalence of pressure ulcers in hospitals in Brazil and association with nutritional status—a multicenter, cross-sectional study. Nutrition, 29(4), 646-649. Cox, J. (2011). Predictors of pressure ulcers in adult critical care patients. American Journal of Critical Care, 20(5), 364-375. Davies, M. (2005). The advantage of using relational databases for large corpora: Speed, advanced queries, and unlimited annotation. International Journal of Corpus Linguistics, 10(3), 307-334. Defloor, T., De Bacquer, D., & Grypdonck, M. H. (2005). The effect of various combinations of turning and pressure reducing devices on the incidence of pressure ulcers. International Journal of Nursing Studies, 42(1), 37-46. Edlich, R., Winters, K. L., Woodard, C. R., Buschbacher, R. M., Long III, W. B., Gebhart, J. H., & Ma, E. K. (2004). Pressure ulcer prevention. Journal of Long-term Effects of Medical Implants, 14(4). Fauroux, B., Lavis, J.-F., Nicot, F., Picard, A., Boelle, P.-Y., Clément, A., & Vazquez, M.-P. (2005). Facial side effects during noninvasive positive pressure ventilation in children. Intensive Care Medicine, 31(7), 965-969. Freire, S. M., Sundvall, E., Karlsson, D., & Lambrix, P. (2012). Performance of XML databases for epidemiological queries in archetype-based EHRs. Paper presented at the Scandinavian Conference on Health Informatics 2012; October 2-3; Linköping; Sverige. Fu Shaw, L., Chang, P.-C., Lee, J.-F., Kung, H.-Y., & Tung, T.-H. (2014). Incidence and predicted risk factors of pressure ulcers in surgical patients: experience at a medical center in Taipei, Taiwan. BioMed Research International, 2014. González‐Méndez, M. I., Lima‐Serrano, M., Martín‐Castaño, C., Alonso‐Araujo, I., & Lima‐Rodríguez, J. S. (2018). Incidence and risk factors associated with the development of pressure ulcers in an intensive care unit. Journal of clinical nursing, 27(5-6), 1028-1037. Gulledge, T. (2006). What is integration? Industrial Management & Data Systems, 106(1), 5-20. Gunningberg, L., Hommel, A., Bååth, C., & Idvall, E. (2013). The first national pressure ulcer prevalence survey in county council and municipality settings in Sweden. Journal of Evaluation in Clinical Practice, 19(5), 862-867. Guo, D. (2010). Integrating medical data and images in a database management system: Google Patents. Halfens, R., Van Achterberg, T., & Bal, R. (2000). Validity and reliability of the Braden scale and the influence of other risk factors: a multi-centre prospective study. International Journal of Nursing Studies, 37(4), 313-319. Hameed, S. A., Hassan, A., Shabnam, S., Miho, V., & Khalifa, O. (2008). An efficient emergency, healthcare, and medical information system. International Journals of Biometric and Bioinformatics, 2(5), 1-9. Hoffmann, B., & Rohe, J. (2010). Patient safety and error management: what causes adverse events and how can they be prevented? Deutsches Arzteblatt International, 107(6), 92. Igarashi, A., Yamamoto-Mitani, N., Gushiken, Y., Takai, Y., Tanaka, M., & Okamoto, Y. (2013). Prevalence and incidence of pressure ulcers in Japanese long-term-care hospitals. Archives of Gerontology and Geriatrics, 56(1), 220-226. Jiang, Q., Li, X., Qu, X., Liu, Y., Zhang, L., Su, C., . . . Jia, J. (2014). The incidence, risk factors and characteristics of pressure ulcers in hospitalized patients in China. International journal of clinical and experimental pathology, 7(5), 2587. Joint Commission of Taiwan. (2018). Taiwan Patient safety Reporting system. Retrieved from http://www.patientsafety.mohw.gov.tw/Content/Messagess/Contents.aspx?SiteID=2&MmmID=621316242156723353 Kaewprag, P., Newton, C., Vermillion, B., Hyun, S., Huang, K., & Machiraju, R. (2015). Predictive modeling for pressure ulcers from intensive care unit electronic health records. AMIA Summits on Translational Science Proceedings, 2015, 82. Khor, H. M., Tan, J., Saedon, N. I., Kamaruzzaman, S. B., Chin, A. V., Poi, P. J., & Tan, M. P. (2014). Determinants of mortality among older adults with pressure ulcers. Archives of Gerontology and Geriatrics, 59(3), 536-541. Kohn, L. T., Corrigan, J., & Donaldson, M. S. (2000). To err is human: building a safer health system (Vol. 6): National academy press Washington, DC. Lahmann, N. A., Halfens, R. J., & Dassen, T. (2005). Prevalence of pressure ulcers in Germany. Journal of clinical nursing, 14(2), 165-172. Lavin, M., & Nathan, M. (1998). System and method for managing patient medical records: Google Patents. Medical Advisory Secretariat. (2009). Pressure Ulcer Prevention: An Evidence-Based Analysis. Ontario Health Technology Assessment Series, 9(2), 1. Mentat. (2016). Streaming Random Forest. Retrieved from https://blog.ment.at/streaming-random-forest-90d39277d71f Moon, M., & Lee, S.-K. (2017). Applying of decision tree analysis to risk factors associated with pressure ulcers in long-term care facilities. Healthcare informatics research, 23(1), 43-52. National Pressure Ulcer Advisory Panel. (2016). NPUAP Pressure Injury Stages. Retrieved from https://www.npuap.org/resources/educational-and-clinical-resources/npuap-pressure-injury-stages/ Pacurariu, A., Plueschke, K., McGettigan, P., Morales, D. R., Slattery, J., Vogl, D., . . . Cave, A. (2018). Electronic healthcare databases in Europe: descriptive analysis of characteristics and potential for use in medicines regulation. BMJ open, 8(9), e023090. Pronovost, P. J., Morlock, L. L., Sexton, J. B., Miller, M. R., Holzmueller, C. G., Thompson, D. A., . . . Wu, A. W. (2008). Improving the value of patient safety reporting systems Advances in Patient Safety: New Directions and Alternative Approaches (Vol. 1: Assessment): Agency for Healthcare Research and Quality. Raju, D., Su, X., Patrician, P. A., Loan, L. A., & McCarthy, M. S. (2015). Exploring factors associated with pressure ulcers: a data mining approach. International Journal of Nursing Studies, 52(1), 102-111. Setoguchi, Y., Ghaibeh, A. A., Mitani, K., Abe, Y., Hashimoto, I., & Moriguchi, H. (2016). Predictability of pressure ulcers based on operation duration, transfer activity, and body mass index through the use of an alternating decision tree. The Journal of Medical Investigation, 63(3.4), 248-255. Sim, K. S., Chong, S. S., Tso, C. P., Nia, M. E., Chong, A. K., & Abbas, S. F. (2014). Computerized database management system for breast cancer patients. SpringerPlus, 3(1), 268. Su, C.-T., Wang, P.-C., Chen, Y.-C., & Chen, L.-F. (2012). Data mining techniques for assisting the diagnosis of pressure ulcer development in surgical patients. Journal of medical systems, 36(4), 2387-2399. Suzumura, T., Trent, S., Tatsubori, M., Tozawa, A., & Onodera, T. (2008). Performance comparison of web service engines in php, java and c. Paper presented at the 2008 IEEE International Conference on Web Services. Tang, L., & Liu, H. (2005). Bias analysis in text classification for highly skewed data. Paper presented at the Fifth IEEE International Conference on Data Mining (ICDM'05). Thomas, E. J., Studdert, D. M., Burstin, H. R., Orav, E. J., Zeena, T., Williams, E. J., . . . Brennan, T. A. (2000). Incidence and types of adverse events and negligent care in Utah and Colorado. Medical Care, 261-271. Tschannen, D., Bates, O., Talsma, A., & Guo, Y. (2012). Patient-specific and surgical characteristics in the development of pressure ulcers. American Journal of Critical Care, 21(2), 116-125. Vanderwee, K., Defloor, T., Beeckman, D., Demarré, L., Verhaeghe, S., Van Durme, T., & Gobert, M. (2011). Assessing the adequacy of pressure ulcer prevention in hospitals: a nationwide prevalence survey. BMJ Quality & Safety, 20(3), 260-267. Williams, H. E., & Lane, D. (2004). Web Database Applications with PHP and MySQL: Building Effective Database-Driven Web Sites: ' O'Reilly Media, Inc.'. World Health Organization. (2017). Patient safety: making health care safer. Retrieved from https://apps.who.int/iris/handle/10665/255507 Yamaguti, W. P., Moderno, E. V., Yamashita, S. Y., Gomes, T. G., Maida, A. L. V., Kondo, C. S., . . . de Brito, C. M. (2014). Treatment-related risk factors for development of skin breakdown in subjects with acute respiratory failure undergoing noninvasive ventilation or CPAP. Respiratory care, 59(10), 1530-1536. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21319 | - |
dc.description.abstract | 透過管理醫療照護中的異常事件可以幫助管理階層檢測錯誤、分析其性質和原因、並建立預防錯誤的機制。然而大多數異常事件資訊管理系統未提供事件預測功能,而異常事件相關研究也多使用小樣本。因此本研究開發一個異常事件資料庫與管理資訊系統,提供臨床人員應用於異常事件的管理與預防。本文以壓傷為例,研究目的與方法包括:(1)設計異常事件關聯式資料庫,包括藥物、跌倒、管路、壓傷及針扎事件,本文以壓傷為例;(2)建立應用程式網頁服務,供使用者資料管理、查詢、及產生異常事件統計圖表;(3)提供使用者於網頁中以決策樹模型找出異常事件傷害程度的重要因子。本研究以機器學習中的隨機森林模性預測醫院壓傷事件嚴重程度,結果之正確率達54.5~64.4%。影響壓傷事件傷害程度最重要的因素是發生的單位,其餘則包括發生部位、骨突處反覆摩擦、使用輔具、長時間固定姿位、Barden Scale分數等。本系統除了方便醫療人員對院內的異常事件進行報表檢核,決策樹模型結果亦可供單位人員參考,對於異常事件的預防與管理有重要的貢獻,以提升病人安全。 | zh_TW |
dc.description.abstract | By managing adverse events in medical care, administrator can detect errors, analyze nature and causes of adverse events, and establish mechanisms to prevent them. However, most adverse event information management systems do not provide event prediction function, and most adverse event related research uses a small sample. Therefore, the present research develops an adverse event cloud database and management information system to provide clinical personnel for the management and prevention of adverse events. The specific methods and objectives include: (1) Designing and establishing an adverse event database with MySQL, including drugs events, falls events, tubing events, pressure injury and needle stick injury; (2) Building an application web service with PHP for user to manage data, search events, and generate statistical charts of adverse events; (3) Providing users explore important factors of damage of adverse events with decision tree model function in the web page. In this study, the random forest model was used to predict the severity of hospital pressure injuries, and the correct rate was 54.5~64.4%. The most important factors affecting the degree of pressure injury in the adverse events were the occurred units. The others include the site of occurrence, repeated friction at the apophysis, the use of assistive devices, long-term fixed posture, and Barden Scale score. In addition to facilitating medical personnel to report on adverse events in the hospital, this system also provides decision tree model results. These can be reference for clinical and have important contributions to the prevention and management of adverse events, and finally to enhance patient safety. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T03:31:00Z (GMT). No. of bitstreams: 1 ntu-108-P06E41010-1.pdf: 2620147 bytes, checksum: 7d2efdcdbce65bbdecd2e28288d03de1 (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | 口試委員會審定書………………………………………………….…… i
誌謝………………………………………………………………………. ii 中文摘要…………………………………………………………………..iii 英文摘要…………………………………………………..……..………. iv 第一章 前言……………………………………………..…..…………..1 1.1 研究背景及重要性………………………………..…..…………1 1.2 研究動機………………………………………..…..……………2 1.3 研究目的………………………………………..……………..…3 第二章 文獻查證……………………………….……..…………….......5 2.1 護理品管異常事件之定義……………………..…..……………5 2.2 護理品管壓傷事件之危險因素………………..…..……………5 2.3 資料庫系統……………..……………………..…..………..……6 2.4 護理品管壓傷事件之預測方法……..………….…..………….. 7 2.5 護理品管資料庫技術提升指標與市場需求評估.....……..…… 9 第三章 研究方法………………………………………….………….... 12 3.1 系統概念與架構…………………………………….………… 12 3.2 資料庫模式(Database Schema)…………………………..…… 13 3.3 系統功能架構……………………………….…….………...… 18 3.4 模型分析……………………………………..…...…………… 19 第四章 研究結果……………………………..…..……….………….... 21 4.1 壓傷病人基本資料…………………………..….…..………… 21 4.2 壓傷傷害分級…………………………………….…………… 24 4.3 壓傷隨機森林模型………………………….………………….27 4.4 資料管理系統…………………………………….…..…………35 第五章 討論…………………………………………………………...... 41 第六章 結論與建議……………………………………………..…….... 45 參考文獻………………..……..………………………………….………47 附錄 ……………………….…………………………………………54 | |
dc.language.iso | zh-TW | |
dc.title | 護理品管壓傷資料庫與複合式查詢功能之建立與操作 | zh_TW |
dc.title | Implementation and Operation of Pressure Injury Database and Compound Query in Nursing Quality Control | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 查士朝(Shi-Cho Cha),郭建良(Chien-Liang David Kuo) | |
dc.subject.keyword | 異常事件,雲端資料庫,資訊系統,決策樹, | zh_TW |
dc.subject.keyword | adverse events,cloud database,information system,decision tree, | en |
dc.relation.page | 61 | |
dc.identifier.doi | 10.6342/NTU201902641 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2019-08-14 | |
dc.contributor.author-college | 進修推廣學院 | zh_TW |
dc.contributor.author-dept | 事業經營碩士在職學位學程 | zh_TW |
顯示於系所單位: | 事業經營碩士在職學位學程 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-108-1.pdf 目前未授權公開取用 | 2.56 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。