Jonathan M C Lam1, Walter P Wodchis. 1. Health Policy Management and Evaluation, University of Toronto, 155 College Street, Toronto, Ontario.
Abstract
BACKGROUND: Population-based diagnosis- and condition-specific health-related quality of life (HRQoL) scores are required for decision-making and research purposes. These HRQoL scores do not exist for hospital-based long-term care (LTC) residents. OBJECTIVE: To estimate the impact of 60 diseases and 15 conditions on caregiver-assessed preference-based HRQoL. METHODS: Residents in hospital-based LTC facilities in Ontario, Canada were identified from administrative databases containing resident minimum data set (MDS) assessments completed between August 1st, 2003 and March 31st, 2008. A preference-based HRQoL measure, the MDS Health-Status Index (MDS-HSI) score, was calculated for 66,193 residents. Average MDS-HSI scores and multivariate linear regression models were used to estimate the impact of the diagnoses and conditions, respectively. RESULTS: After adjusting for age, sex, and other diagnoses, aphasia exhibited the largest negative relationship to the MDS-HSI (-0.085), followed by cancer (-0.072) and Alzheimer disease (-0.062). Cancer was also the second most prevalent diagnosis (27.6%). Lack of balance was a common condition (87.3%) and it had the greatest negative relationship to MDS-HSI scores among the 15 conditions (-0.099). The diagnoses and conditions regression models had R values of 0.12 and 0.34, respectively, suggesting that clinical conditions provided better explanatory variables for the MDS-HSI than diagnoses. CONCLUSIONS: The findings suggest that diseases affect preference-based HRQoL differently in a hospital-based LTC population compared with previous studies in the general population. The population-based MDS-HSI scores from this study can be used as reference values in cost-effectiveness analyses for hospital-based LTC populations.
BACKGROUND: Population-based diagnosis- and condition-specific health-related quality of life (HRQoL) scores are required for decision-making and research purposes. These HRQoL scores do not exist for hospital-based long-term care (LTC) residents. OBJECTIVE: To estimate the impact of 60 diseases and 15 conditions on caregiver-assessed preference-based HRQoL. METHODS: Residents in hospital-based LTC facilities in Ontario, Canada were identified from administrative databases containing resident minimum data set (MDS) assessments completed between August 1st, 2003 and March 31st, 2008. A preference-based HRQoL measure, the MDS Health-Status Index (MDS-HSI) score, was calculated for 66,193 residents. Average MDS-HSI scores and multivariate linear regression models were used to estimate the impact of the diagnoses and conditions, respectively. RESULTS: After adjusting for age, sex, and other diagnoses, aphasia exhibited the largest negative relationship to the MDS-HSI (-0.085), followed by cancer (-0.072) and Alzheimer disease (-0.062). Cancer was also the second most prevalent diagnosis (27.6%). Lack of balance was a common condition (87.3%) and it had the greatest negative relationship to MDS-HSI scores among the 15 conditions (-0.099). The diagnoses and conditions regression models had R values of 0.12 and 0.34, respectively, suggesting that clinical conditions provided better explanatory variables for the MDS-HSI than diagnoses. CONCLUSIONS: The findings suggest that diseases affect preference-based HRQoL differently in a hospital-based LTC population compared with previous studies in the general population. The population-based MDS-HSI scores from this study can be used as reference values in cost-effectiveness analyses for hospital-based LTC populations.
Authors: Luke Mondor; Colleen J Maxwell; Susan E Bronskill; Andrea Gruneir; Walter P Wodchis Journal: Qual Life Res Date: 2016-04-06 Impact factor: 4.147
Authors: Jane S Paulsen; Martha Nance; Ji-In Kim; Noelle E Carlozzi; Peter K Panegyres; Cheryl Erwin; Anita Goh; Elizabeth McCusker; Janet K Williams Journal: Prog Neurobiol Date: 2013-09-11 Impact factor: 11.685
Authors: Aleksi J Sihvonen; Pablo Ripollés; Vera Leo; Jani Saunavaara; Riitta Parkkola; Antoni Rodríguez-Fornells; Seppo Soinila; Teppo Särkämö Journal: eNeuro Date: 2021-06-17