ISSN: 0970-938X (Print) | 0976-1683 (Electronic)

Biomedical Research

An International Journal of Medical Sciences


Practice of surgeon-nurse integrated management in emergency treatment of severe complications following thyroid gland surgery

Objective: The study was conducted to summarize the experience of Surgeon-Nurse Integrated Management (SNIM) in emergency treatment of severe complications following thyroid gland surgery.

Methods: The retrospective analysis was performed on clinical data of 1,945 cases with thyroid tumor who were admitted to our hospital between January 2013 and March 2016. Also, the procedures of SNIM in emergency treatment for severe complications following surgery were summarized.

Results: SNIM was introduced to our department in 2008 and was modified based on original one in January 2013. In this study, 1,945 cases received surgical treatment. SNIM was executed since admission of these patients, including assessment of patients, design of medical care plan, regular assessment of complications after surgery for thyroid gland using the Postoperative Complications Modular Evaluation Sheet (PCMES) on shift basis, early detection of severe postoperative complicates and immediate treatment by collaboration with surgeons. After modification of the SNIM, patient satisfaction increased by 5.9%. The mean duration of stay was reduced by 3.4 d. Most surgeons and nurses believed that the modified SNIM was better to demonstrate professional skills of nurses and enhance collaboration with surgeons in management following thyroid gland surgery.

Conclusion: SNIM enables adequate assessment of medical condition and enhances surgeon-nurse cooperation during perioperative period. With such management, it is possible to make regular assessment of patients following surgery and provide immediate treatment if any severe postoperative complications are identified, which helps promote recovery following surgery and improve recovery rate and quality of life.

Author(s): Xiaojuan Jiang, Bo Gao, Fujie Yu, Yi Tang, Jiaqun Zou, Jin Zhang, Lisha Jiang, Jie Yan, Donglin Luo
Abstract | Full-Text | PDF

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