M Mofizul Islam1, Ian S McRae1, Laurann Yen1, Tanisha Jowsey1, Jose M Valderas2. 1. Australian Primary Health Care Research Institute, Australian National University, Australian Capital Territory. 2. Health Services and Policy Research, University of Exeter Medical School, England, UK.
Abstract
OBJECTIVE: To examine the effect of various morbidity clusters of chronic diseases on health-related time use and to explore factors associated with heavy time burden (more than 30 hours/month) of health-related activities. METHODS: Using a national survey, data were collected from 2,540 senior Australians. Natural clusters were identified using cluster analysis and clinical clusters using clinical expert opinion. We undertook a set of linear regressions to model people's time use, and logistic regressions to model heavy time burden. RESULTS: Time use increases with the number of chronic diseases. Six of the 12 diseases are significantly associated with higher time use, with the highest effect for diabetes followed by depression; 18% reported a heavy time burden, with diabetes again being the most significant disease. Clusters and dominant comorbid groupings do not contribute to predicting time use or time burden. CONCLUSIONS: Total number of diseases and specific diseases are useful determinants of time use and heavy time burden. Dominant groupings and disease clusters do not predict time use. IMPLICATIONS: In considering time demands on patients and the need for care co-ordination, care providers need to be aware of how many and what specific diseases the patient faces.
OBJECTIVE: To examine the effect of various morbidity clusters of chronic diseases on health-related time use and to explore factors associated with heavy time burden (more than 30 hours/month) of health-related activities. METHODS: Using a national survey, data were collected from 2,540 senior Australians. Natural clusters were identified using cluster analysis and clinical clusters using clinical expert opinion. We undertook a set of linear regressions to model people's time use, and logistic regressions to model heavy time burden. RESULTS: Time use increases with the number of chronic diseases. Six of the 12 diseases are significantly associated with higher time use, with the highest effect for diabetes followed by depression; 18% reported a heavy time burden, with diabetes again being the most significant disease. Clusters and dominant comorbid groupings do not contribute to predicting time use or time burden. CONCLUSIONS: Total number of diseases and specific diseases are useful determinants of time use and heavy time burden. Dominant groupings and disease clusters do not predict time use. IMPLICATIONS: In considering time demands on patients and the need for care co-ordination, care providers need to be aware of how many and what specific diseases the patient faces.
Authors: Matt P Malcolm; Karen E Atler; Arlene A Schmid; Tara C Klinedinst; Laura A Grimm; Tasha P Marchant; David R Marchant Journal: Clin Diabetes Date: 2018-07