Derivation and validation of an algorithm to predict transitions from community to residential long-term care among persons with dementia—A retrospective cohort study

Objectives: To develop and validate a model to predict time-to-LTC admissions among individuals with dementia. Design: Population-based retrospective cohort study using health administrative data. Setting and participants: Community-dwelling older adults (65+) in Ontario living with dementia and assessed with the Resident Assessment Instrument for Home Care (RAI-HC) between April 1, 2010 and March 31, 2017. Methods: Individuals in the derivation cohort (n = 95,813; assessed before March 31, 2015) were followed for up to 360 days after the index RAI-HC assessment for admission into LTC. We used a multivariable Fine Gray sub-distribution hazard model to predict the cumulative incidence of LTC entry while accounting for all-cause mortality as a competing risk. The model was validated in 34,038 older adults with dementia with an index RAI-HC assessment between April 1, 2015 and March 31, 2017. Results: Within one year of a RAI-HC assessment, 35,513 (37.1%) individuals in the derivation cohort and 10,735 (31.5%) in the validation cohort entered LTC. Our algorithm was well-calibrated (Emax = 0.119, ICIavg = 0.057) and achieved a c-statistic of 0.707 (95% confidence interval: 0.703–0.712) in the validation cohort. Conclusions and implications: We developed an algorithm to predict time to LTC entry among individuals living with dementia. This tool can inform care planning for individuals with dementia and their family caregivers. Author summary: We developed and tested a new model to predict how long before people with dementia will be admitted to long-term care (LTC) facilities. Using routinely collected data on all older adults living in Ontario receiving home care between April 2010 and March 2017, we created our prediction model and tested its performance using various metrics. We found that, within a year of their initial assessment, about 35% of persons with dementia were admitted to LTC. We also determined that our model performed well. This model can help healthcare providers and families better plan for future care needs by providing a clearer picture of when someone with dementia might need to move to a long-term care facility.