|Title: ||Jack's Crown and Jill's Hip: A Falls Algorithm to Optimize Best Practices and Resources|
|Jack's Crown and Jill's Hip: A Falls Algorithm to Optimize Best Practices and Resources|
|P.I. Institution Name:||University of Maryland Medical Center|
|Contact Address:||, Baltimore, MD, USA|
|Co-Authors:||Mary Arnett; Michele Zimmer|
|PURPOSE: The purpose was to develop an algorithm that complements the Morse Fall Risk Assessment and interventions. Patients most at-risk for falling are weak or have an impaired gait and overestimate or forget their limitations. An algorithm provides a guide to: 1) identify the highest risk patients within the High and Critical fall risk groups, 2) select best practices, 3) select interventions to minimize the $130,000 cost of dedicated observers (sitters), and 4) reduce the unfilled sitter orders. Description: Nurses use an electronic Morse assessment tool to level patients into standard, high, or critical fall risk. Interventions are selected per risk level. On some units, nurses are faced with almost all patients scored as high or critical risk. The dilemma is how to prioritize resources. The tendency is to order a sitter from the limited sitter pool. The lack of sitters and patient protection, while minimizing restraints and preventing falls, can be a source of stress and frustration for staff. The prescriber may be reluctant to discontinue a sitter order. Nurses identified a need for guidance in selecting alternative resources such as a lap belt fastened in front, removal lap trays, chair alarms and low beds. An algorithm was developed by staff nurses which 1) quickly identifies patients with both physical and mental vulnerability, 2) maximizes restraint alternatives, 3) engages the family to partner in care, and 4) promotes selection of the best alternative resource before requesting a sitter from the limited pool. EVALUATION: The algorithm helps nurses identify and protect weak or unsteady patients who overestimate their abilities but who may be cognitively intact. It helps to maximize interventions beyond the locked bed, sitters, and restraints. It helps decrease variability of care within and across units. Despite the tool's limited pilot, the overall hospital falls rate is below benchmark - 2.18 (hospital) versus 3.40 (Maryland Hospital Association) and 3.71 (NDNQI). Preliminary impact measures point to nurse satisfaction and reduced fall rates and injuries from falls. It is expected that the use of the algorithm will also decrease sitter costs. 2009 National Teaching Institute Creative Solutions Abstracts. Crit Care Nurse. 2009;29(2):e1-e28. Available at: http://ccn.aacnjournals.org/cgi/reprint/29/2/e1|
|Repository Posting Date: ||26-Oct-2011 |
|Date of Publication: ||17-Oct-2011 |
|Appears in Collections: ||AACN - American Association of Critical Care Nurses|
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