Psychometric evaluation of the Decision Support System (DSS) for municipal nurses encountering health deterioration among older adults

Abstract

Abstract Background A valid and reliable tool is crucial for municipal registered nurses (RNs) to make quick decisions in older adults who show rapid signs of health deterioration. The aim of this study was to investigate the psychometric properties of the Decision Support System (DSS) among older adults in the municipal healthcare system. Methods Firstly, we utilized the Rasch dichotomous model to analyze the DSS assessments (n=281) that were collected from municipal RNs working with older adults in the municipal healthcare system. We examined the properties of the DSS in terms of its unidimensionality, item fit, and separation indices. Secondly, to investigate inter-rater agreement in using the DSS, four experienced municipal RNs used the DSS to assess 60 health deterioration scenarios presented by one human patient simulators. The 60 DSS assessments were then analyzed using the ICC (2,1), percentage agreement, and Cohen κ statistics. Results The sample of older adults had a mean age of 82.8 (SD 11.7). The DSS met the criteria for unidimensionality, although two items did not meet the item fit statistics when all the DSS items were analyzed together. The person separation index was 0.47, indicating a limited level of separation among the sample. The item separation index was 11.43, suggesting that the DSS has good ability to discriminate between and separate the items. At the overall DSS level, inter-rater agreements were good according to the ICC. At the individual DSS item level, the percentage agreements were 75% or above, while the Cohen κ statistics ranged from 0.46 to 1.00. Conclusions The Rasch analysis revealed that the psychometric properties of the instrument were acceptable, although further research with a larger sample size and more items is needed. The DSS has the potential to assist municipal RNs in making clinical decisions regarding health deterioration in older adults, thereby avoiding unnecessary emergency admission and helping to alleviate emergency department overcrowding.