Missing data at follow-up: The case of the interRAI home care assessment instrument in Belgium

Background : In Belgium, a web application BelRAI was developed to support the use of interRAI Home Care assessments. However, not all clients have had a follow-up assessment. Objectives : To examine the prevalence of incomplete assessments at 6-month follow-up and to compare the profiles of persons with and without missing data. Design : Observational study of interRAI Home Care data and data from the Belgian Intermutuality Agency. Setting : Home care in Belgium. Participants : Healthcare professionals using BelRAI in the context of an evaluation of home care interventions to delay institutio... Mehr ...

Verfasser: Vanneste, Dirk
De Almeida Mello, Johanna
Macq, Jean
Van Audenhove, Chantal
Declercq, Anja
Dokumenttyp: Artikel
Erscheinungsdatum: 2016
Verlag/Hrsg.: Elsevier Ltd
Schlagwörter: BelRAI / Dropouts / Geriatric assessment / InterRAI / Loss to follow-up / Missing data
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-26994103
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : http://hdl.handle.net/2078.1/176739

Background : In Belgium, a web application BelRAI was developed to support the use of interRAI Home Care assessments. However, not all clients have had a follow-up assessment. Objectives : To examine the prevalence of incomplete assessments at 6-month follow-up and to compare the profiles of persons with and without missing data. Design : Observational study of interRAI Home Care data and data from the Belgian Intermutuality Agency. Setting : Home care in Belgium. Participants : Healthcare professionals using BelRAI in the context of an evaluation of home care interventions to delay institutionalization of frail older people. Methods : Descriptive statistics were calculated based on demographic characteristics and outcome measures. Poisson regressions for the relative risk of institutionalization and for the relative risk of death were performed for a period of 6 and 12 months. Results : In a sample of 4987 persons (mean age 79.90), two groups were determined: a group without and a group with missing data at 6-month follow-up. At baseline, the group with missing data at follow-up has a worse health status than the group without missing data. Persons with missing data at 6-month follow-up had a 3.63 higher chance of dying between 6 and 12 months after baseline, a 3.43 higher chance for institutionalization at 6 months, and a 2.87 higher chance for institutionalization at 12 months. Conclusion : In this study, missing data at follow-up is not a random occurrence. The findings are important for healthcare professionals and for researchers working with longitudinal data. Further study is required to research possible solutions.