Related Experiment Video
Updated: Aug 15, 2026
Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
Published on: February 8, 2019
The Deterioration Early Warning System for aged residential care: a feasibility study with qualitative analysis
Julie Daltrey1, Michal Boyd2, Jacqualine Robinson3
1Professional Teaching Fellow, Nurse Practitioner, School of Nursing, Faculty of Medical and Health Sciences, The University of Auckland, Grafton, Auckland, New Zealand.
Aim:
The Deterioration Early Warning System (DEWS) is a unique process, co-designed and developed in New Zealand, to support residential aged care (RAC) staff in the timely identification of, and response to, acute deterioration. This study aimed to test the effectiveness of DEWS and the feasibility of its implementation within the RAC sector.
Method:
This type 2 feasibility-implementation study was planned and evaluated in line with the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Focus group semi-structured interviews were conducted and template thematic analysis was undertaken to provide descriptive and interpretive data themes.
Results:
Findings from this study support DEWS as an effective process for the timely identification of, and response to, acute deterioration in people living in care. Implementation was found to be feasible, with participants recommending the system's adoption across the RAC sector.
Conclusion:
Participants recommended DEWS to the RAC sector for its capacity to support the multidisciplinary team with the timely identification of and response to acute deterioration. However, future implementation of DEWS is contingent on digitalisation and integration within existing information technology infrastructure.
More Related Videos
06:52Assessment of Dependence in Activities of Daily Living Among Older Patients in an Acute Care Unit
Published on: September 30, 2020
11:21Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
