The use of the Minimum Data Set to identify depression in the elderly.

To determine whether depression in the elderly in institutionalized settings could be identified using the mood indicators in the Minimum Data Set (MDS) 2.0 (Section E1, Items A-P).Descriptive study.Three nursing homes in the southeastern part of the country.Residents aged 65 and above.The items in "Indicators of Depression, Anxiety and Sad Mood" on the MDS 2.0 were used to identify observable features of depression in the elderly. The Cornell Scale for Depression in Dementia (CSDD) was used to validate the MDS indicators. Consensus analysis, which controls raters' bias, raters' ability, and item difficulty, was used to analyze data.No depressive patterns were detected using the MDS indicators. On the CSDD, distinct depressive features were identified: anxiety, sadness, lack of reaction to pleasant events, irritability, agitation, multiple physical complaints, loss of interest, appetite loss, and lack of energy.The incongruent findings on the MDS indicators the CSDD may be reflective of the assessment process used with the MDS rather than its ability to identify features of elderly depression. The practice of allowing nondirect caregivers to complete the MDS may have serious implications for the accuracy of the data collected.

Duke Scholars

Author Cristina Cu Hendrix School of Nursing