Child Health Nurs Res.  2019 Jan;25(1):56-64. 10.4094/chnr.2019.25.1.56.

Meta-analysis of the Diagnostic Test Accuracy of Pediatric Inpatient Fall Risk Assessment Scales

Affiliations
  • 1Assistant Professor, Department of Nursing, Gangneung-Wonju National University, WonJu, Korea.
  • 2Professor, Department of Nursing, Inha University, Incheon, Korea.
  • 3Associate Professor, Department of Nursing, Gangneung-Wonju National University, WonJu, Korea.
  • 4PhD Candidate, Department of Nursing, Korea University, Seoul, Korea. lmk2169@hanmail.net

Abstract

PURPOSE
This study was conducted to obtain data for the development of an effective fall risk assessment tool for pediatric inpatients through a systematic review and meta-analysis of the diagnostic test accuracy of existing scales.
METHODS
A literature search using Medline, Science Direct, CINAHL, EMBASE, and the Cochrane Library was performed between March 1 and 31, 2018. Of 890 identified papers, 10 were selected for review. Nine were used in the meta-analysis. Stata version 14.0 was used to create forest plots of sensitivity and specificity. A summary receiver operating characteristic curve was used to compare all diagnostic test accuracies.
RESULTS
Four studies used the Humpty Dumpty Falls Scale. The most common items included the patient's diagnoses, use of sedative medications, and mobility. The pooled sensitivity and specificity of the nine studies were .79 and .36, respectively.
CONCLUSION
Considering the low specificity of the pediatric fall risk assessment scales currently available, there is a need to subdivide scoring categories and to minimize items that are evaluated using nurses' subjective judgment alone. Fall risk assessment scales should be incorporated into the electronic medical record system and an automated scoring system should be developed.

Keyword

Falls; Risk; Sensitivity and specificity; Pediatrics

MeSH Terms

Accidental Falls
Diagnosis
Diagnostic Tests, Routine*
Electronic Health Records
Forests
Humans
Inpatients*
Judgment
Pediatrics
Risk Assessment*
ROC Curve
Sensitivity and Specificity
Weights and Measures*
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