Predictive validity of a frailty measure (GFI) and a case complexity measure (IM-E-SA) on healthcare costs in an elderly populationPeters, L. L., Burgerhof, J. G. M., Boter, H., Wild, B., Buskens, E. & Slaets, J. P. J., Nov-2015, In : Journal of Psychosomatic Research. 79, 5, p. 404-411 8 p.
Research output: Contribution to journal › Article › Academic › peer-review
Objectives: Measures of frailty (Groningen Frailty Indicator, GFI) and case complexity (INTERMED for the Elderly, IM-E-SA) may assist healthcare professionals to allocate healthcare resources. Both instruments have been evaluated with good psychometric properties. Limited evidence has been published about their predictive validity. Thus, our aim is to evaluate the predictive validity of both instruments on healthcare costs.
Methods: Multivariate linear regression models were developed to estimate associations between the predictors frailty (GFI) and/or case complexity (IM-E-SA) and the healthcare costs (in log transformed) in the following year. All models were adjusted for demographics and the presence of morbidity.
Results: In the multivariate regression analyses the continuous scores of the GFI and IM-E-SA remained significant predictors for total healthcare costs. Adjusted beta s for GFI and IM-E-SA were respectively 0.14 (95% CI 0.10-0.18) and 0.06 (95% CI 0.04-0.07). The corresponding explained variance (R-2) for both models was 0.40. Frailty remained a significant predictor of long-term care costs (adjusted beta 0.13 [95% CI 0.09-0.16]), while case complexity was a significant predictor of curative care costs (adjusted beta 0.03 195% CI 0.02-0.05]).
Conclusions: The GFI and IM-E-SA both accurately predict total healthcare costs in the following year. (C) 2015 Elsevier Inc. All rights reserved.
|Number of pages||8|
|Journal||Journal of Psychosomatic Research|
|Publication status||Published - Nov-2015|
- Frailty, Case complexity, Healthcare costs, Long-term care costs, Curative care costs, Predictive validity, REPORT SCREENING INSTRUMENTS, OLDER-PEOPLE, CLINICAL INSTRUMENT, SERVICE NEEDS, INDICATOR, COMMUNITY, ACCURACY, MODEL