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9. Language and pain predict persistent depression among seriously ill home care clients.

14. A multi-stage process to develop quality indicators for community-based palliative care using interRAI data

19. Analyzing Mobility Patterns of Older Adults with Dementia Using GPS Technology

20. Additional file 2 of Prognosis does not change the landscape: palliative home care clients experience high rates of pain and nausea, regardless of prognosis

21. Additional file 1 of Prognosis does not change the landscape: palliative home care clients experience high rates of pain and nausea, regardless of prognosis

23. Development and validation of a prediction model of poor performance status and severe symptoms over time in cancer patients (PROVIEW+)

26. What should be measured to assess the quality of community-based palliative care? Results from a collaborative expert workshop.

29. Effect of Early Palliative Care on End-of-Life Health Care Costs: A Population-Based, Propensity Score--Matched Cohort Study.

36. Development and Validation of Caregiver Risk Evaluation (CaRE): A New Algorithm to Screen for Caregiver Burden.

38. Cross-Sectional Nutrition Profile of Palliative Home Care Clients in Ontario and Performance of the interRAI Palliative Care Nutrition Clinical Assessment Protocol.

39. Trajectory of psychosocial symptoms among home care patients with cancer at end-of-life.

40. A Deterioration in Hearing Is Associated With Functional and Cognitive Impairments, Difficulty With Communication, and Greater Health Instability.

41. Combined impairments in vision, hearing and cognition are associated with greater levels of functional and communication difficulties than cognitive impairment alone: Analysis of interRAI data for home care and long-term care recipients in Ontario

47. Older Adults With a Combination of Vision and Hearing Impairment Experience Higher Rates of Cognitive Impairment, Functional Dependence, and Worse Outcomes Across a Set of Quality Indicators.

50. Changes in social engagement and depression predict incident loneliness among seriously ill home care clients.

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