Author
Listed:
- Jessica Brier
- Moalem Carolyn
- Marsha Haverly
- Mary Ellen Januario
- Cynthia Padula
- Ahuva Tal
- Henia Triosh
Abstract
Aims and objectives To develop a clinical algorithm to guide nurses' critical thinking through systematic surveillance, assessment, actions required and communication strategies. To achieve this, an international, multiphase project was initiated. Background Patients receive hospital care postoperatively because they require the skilled surveillance of nurses. Effective assessment of postoperative patients is essential for early detection of clinical deterioration and optimal care management. Despite the significant amount of time devoted to surveillance activities, there is lack of evidence that nurses use a consistent, systematic approach in surveillance, management and communication, potentially leading to less optimal outcomes. Several explanations for the lack of consistency have been suggested in the literature. Design Mixed methods approach. Methods Retrospective chart review; semi‐structured interviews conducted with expert nurses (n = 10); algorithm development. Results Themes developed from the semi‐structured interviews, including (1) complete, systematic assessment, (2) something is not right (3) validating with others, (4) influencing factors and (5) frustration with lack of response when communicating findings were used as the basis for development of the Surveillance Algorithm for Post‐Surgical Patients. Conclusion The algorithm proved beneficial based on limited use in clinical settings. Further work is needed to fully test it in education and practice. Relevance to clinical practice The Surveillance Algorithm for Post‐Surgical Patients represents the approach of expert nurses, and serves to guide less expert nurses' observations, critical thinking, actions and communication. Based on this approach, the algorithm assists nurses to develop skills promoting early detection, intervention and communication in cases of patient deterioration.
Suggested Citation
Jessica Brier & Moalem Carolyn & Marsha Haverly & Mary Ellen Januario & Cynthia Padula & Ahuva Tal & Henia Triosh, 2015.
"Knowing ‘something is not right’ is beyond intuition: development of a clinical algorithm to enhance surveillance and assist nurses to organise and communicate clinical findings,"
Journal of Clinical Nursing, John Wiley & Sons, vol. 24(5-6), pages 832-843, March.
Handle:
RePEc:wly:jocnur:v:24:y:2015:i:5-6:p:832-843
DOI: 10.1111/jocn.12670
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Citations
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Cited by:
- Emily Rohde & Elizabeth Domm, 2018.
"Nurses’ clinical reasoning practices that support safe medication administration: An integrative review of the literature,"
Journal of Clinical Nursing, John Wiley & Sons, vol. 27(3-4), pages 402-411, February.
- Claire Foley & Maura Dowling, 2019.
"How do nurses use the early warning score in their practice? A case study from an acute medical unit,"
Journal of Clinical Nursing, John Wiley & Sons, vol. 28(7-8), pages 1183-1192, April.
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