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Zhou X, Ye Y, Jin A, Pan Z, Xu Z, Ding S, Yan J, Cheng Y, Huang Y, Cao K, Xie W, Zhang J, Xu L, Zhou W, Huang L. Development and implementation of evidence-based, nurse-leading early warning model and healthcare quality improvement project for transplant-associated thrombotic microangiopathy: a mixed-methods, before-and-after study. BMC Nurs 2024; 23:535. [PMID: 39113009 PMCID: PMC11304727 DOI: 10.1186/s12912-024-02093-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 06/13/2024] [Indexed: 08/11/2024] Open
Abstract
OBJECTIVE The early identification and diagnosis of transplant-associated thrombotic microangiopathy (TA-TMA) are essential yet difficult in patients underwent hematopoietic stem cell transplantation (HSCT). To develop an evidence-based, nurse-leading early warning model for TA-TMA, and implement the healthcare quality review and improvement project. METHODS This study was a mixed-methods, before-and-after study. The early warning model was developed based on quality evidence from literature search. The healthcare quality review and improvement project mainly included baseline investigation of nurse, improvement action and effectiveness evaluation. The awareness and knowledge of early parameter of TA-TMA among nurses and the prognosis of patients underwent HSCT were compared before and after the improvement. RESULTS A total of 1 guideline, 1 evidence synthesis, 4 expert consensuses, 10 literature reviews, 2 diagnostic studies, and 9 case series were included in the best evidence. The early warning model including warning period, high-risk characteristics and early manifestation of TA-TMA was developed. The improvement action, including staff training and assessment, suspected TA-TMA identification and patient education, was implemented. The awareness and knowledge rate of early parameter of TA-TMA among nurses significantly improved after improvement action (100% vs. 26.7%, P < 0.001). The incidence of TA-TMA was similar among patients underwent HSCT before and after improvement action (2.8% vs. 1.2%, P = 0.643), while no fall event occurred after improvement action (0 vs. 1.2%, P < 0.001). CONCLUSION The evidence-based early warning model and healthcare quality improvement project could enhance the awareness and knowledge of TA-TMA among healthcare providers and might improve the prognosis of patients diagnosed with TA-TMA.
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Affiliation(s)
- Xiaoyu Zhou
- Department of Nursing, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Yishan Ye
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Aiyun Jin
- Department of Nursing, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Zhengwen Pan
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Zhe Xu
- Department of Nursing, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Shuyi Ding
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Jiali Yan
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Yin Cheng
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Yixuan Huang
- Department of Nursing, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Kai Cao
- Department of Nursing, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Wei Xie
- Department of Nursing, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Jianli Zhang
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Liwei Xu
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Weiwei Zhou
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China
| | - Lihua Huang
- Department of Nursing, The First Affiliated Hospital, Zhejiang University School of Medical, Hangzhou, China.
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Hu CY, Sun LC, Lin MY, Chen MH, Hsu HT. Validating the accuracy of the Hendrich II Fall Risk Model for hospitalized patients using the ROC curve analysis. Kaohsiung J Med Sci 2024; 40:404-412. [PMID: 38366376 DOI: 10.1002/kjm2.12807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 01/01/2024] [Accepted: 01/04/2024] [Indexed: 02/18/2024] Open
Abstract
This retrospective study was conducted at a medical center in southern Taiwan to assess the accuracy of the Hendrich II Fall Risk Model (HIIFRM) in predicting falls. Sensitivity, specificity, accuracy, and optimal cutoff points were analyzed using receiver operating characteristic (ROC) curves. Data analysis was conducted using information from the electronic medical record and patient safety reporting systems, capturing 303 fall events and 47,146 non-fall events. Results revealed that at the standard threshold of HIIFRM score ≥5, the median score in the fall group was significantly higher than in the non-fall group. The top three units with HIIFRM scores exceeding 5 were the internal medicine (50.6%), surgical (26.5%), and oncology wards (14.1%), indicating a higher risk of falls in these areas. ROC analysis showed an HIIFRM sensitivity of 29.5% and specificity of 86.3%. The area under the curve (AUC) was 0.57, indicating limited discriminative ability in predicting falls. At a lower cutoff score (≥2), the AUC was 0.75 (95% confidence interval: 0.666-0.706; p < 0.0001), suggesting acceptable discriminative ability in predicting falls, with an additional identification of 101 fall events. This study emphasizes the importance of selecting an appropriate cutoff score when using the HIIFRM as a fall risk assessment tool. The findings have implications for fall prevention strategies and patient care in clinical settings, potentially leading to improved outcomes and patient safety.
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Affiliation(s)
- Chieh-Ying Hu
- Integrated Long-Term Care Services Center, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Li-Chen Sun
- Department of Nursing, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Ming-Yen Lin
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Mei-Hsing Chen
- Superintendent Office, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
- Center for Quality Management and Patient Safety, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Hsin-Tien Hsu
- School of Nursing, Kaohsiung Medical University, Kaohsiung, Taiwan
- Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
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