Reliable Integrative Assessment of Health Care Needs in Elderly Persons: The INTERMED for the Elderly (IM-E)

J Psychosom Res. 2011 Feb;70(2):169-78. doi: 10.1016/j.jpsychores.2010.09.003. Epub 2010 Dec 8.

Abstract

Objective: With the increasing prevalence of multiple conditions in older age, the high prevalence of mental disorders, and the many social challenges facing elderly people, a high-risk patient group in need of interdisciplinary (biological, psychological, and social) care is emerging. The INTERMED interview is an integrative assessment method that identifies patients with complex health care needs. The aim of this study was to develop and evaluate the INTERMED for the Elderly (IM-E), specifically for use in populations of elderly persons.

Methods: In focus groups conducted with the authors of the original INTERMED, the variables and anchor points that had to be adjusted to the needs and situation of the elderly and to the demands of a population-based study were discussed and altered. The final version of the IM-E was conducted with 42 elderly persons. Participants were doubly scored by two trained raters; the interrater reliability [intraclass correlation coefficient (ICC) (2,1)] was calculated.

Results: The IM-E was well accepted by the elderly persons interviewed. ICCs for the various domains of the IM-E ranged between .87 and .95, while the ICC for the sum score was .95. Regarding the cutoff point of 20/21 for patients with complex health care needs, a κ of .75 was achieved.

Conclusions: The IM-E is a reliable integrative assessment instrument. It is well suited for epidemiological settings to adequately describe the percentage of elderly patients with complex health care needs. In clinical settings, it can be used to identify elderly patients in need of interdisciplinary care.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Delivery of Health Care, Integrated
  • Focus Groups
  • Humans
  • Interviews as Topic
  • Middle Aged
  • Needs Assessment* / standards
  • Observer Variation
  • Reproducibility of Results