Event Title

Poster Introductions III--Estimating Efficiency in Ontario's Long-Term Care Facilities: An Assessment Using Stochastic Frontier Analysis on Panel Data

Start Date

15-10-2009 5:15 PM

End Date

15-10-2009 5:30 PM

Description

Introduction: With uncertainty surrounding the true impact of the ageing population, financing the future of high quality long-term care (LTC) depends on two pivotal factors: cost control and more efficient use of resources. However, the relationships between inputs (and their costs), quality of care and operational efficiency - and what factors determine efficiency - are relatively understudied in the LTC sector.

Data Source: This study used data from The Residential Care Facilities Survey (RCFS), for the province of Ontario, collected between 1996 and 2006. The RCFS is a longitudinal census survey administered annually by Statistics Canada, to all LTC facilities operating in Canada that receive public funding. The RCFS contains information about the: 1) facility’s type, location, chain ownership and profit status; 2) quantity and cost of inputs employed (i.e. nursing staff, other medical staff, administrative staff, equipment, number of beds, etc.); 3) age, sex and morbidity distribution of residents; 4) number of patient days; and 5) number of deaths and discharges.

Methods: Using the stochastic frontier analysis (SFA) of panel data, this study assesses the determinants of operational efficiency in LTC facilities in Ontario, while controlling for quality of care. In keeping with the literature, output was measured in total resident days; capital inputs were estimated based on prescription drug and medical supplies expenditure, as well as total number of beds; and labour inputs were measured in cumulated paid hours of direct care and other staff (including RNs, physiotherapists/occupational therapists, other direct care staff, administration, dietary services staff, other general services staff, recreational staff, and etc.) in each LTC facility.

Conclusions: Our analysis revealed significant differences in performance by facility size, despite the fact that facilities are compensated at the same per diem rates, with larger LTC facilities operating more efficiently than smaller LTC facilities. We also found significant differences in performance by profit status and urban/rural location. The results also underline the importance of considering an array of quality indicators and controlling for endogeneity of quality.

Amy Hsu is a MSc candidate in the Department of Health Policy, Management and Evaluation under the supervision of Dr. Peter C. Coyte and Dr. Audrey Laporte. Her research interest is in performance measurement, especially pertaining to geriatrics and long-term care. Amy received her Honours BSc in Human Biology from the University of Toronto in 2008, and has a background in human genetics, sociology and religion.

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Oct 15th, 5:15 PM Oct 15th, 5:30 PM

Poster Introductions III--Estimating Efficiency in Ontario's Long-Term Care Facilities: An Assessment Using Stochastic Frontier Analysis on Panel Data

Introduction: With uncertainty surrounding the true impact of the ageing population, financing the future of high quality long-term care (LTC) depends on two pivotal factors: cost control and more efficient use of resources. However, the relationships between inputs (and their costs), quality of care and operational efficiency - and what factors determine efficiency - are relatively understudied in the LTC sector.

Data Source: This study used data from The Residential Care Facilities Survey (RCFS), for the province of Ontario, collected between 1996 and 2006. The RCFS is a longitudinal census survey administered annually by Statistics Canada, to all LTC facilities operating in Canada that receive public funding. The RCFS contains information about the: 1) facility’s type, location, chain ownership and profit status; 2) quantity and cost of inputs employed (i.e. nursing staff, other medical staff, administrative staff, equipment, number of beds, etc.); 3) age, sex and morbidity distribution of residents; 4) number of patient days; and 5) number of deaths and discharges.

Methods: Using the stochastic frontier analysis (SFA) of panel data, this study assesses the determinants of operational efficiency in LTC facilities in Ontario, while controlling for quality of care. In keeping with the literature, output was measured in total resident days; capital inputs were estimated based on prescription drug and medical supplies expenditure, as well as total number of beds; and labour inputs were measured in cumulated paid hours of direct care and other staff (including RNs, physiotherapists/occupational therapists, other direct care staff, administration, dietary services staff, other general services staff, recreational staff, and etc.) in each LTC facility.

Conclusions: Our analysis revealed significant differences in performance by facility size, despite the fact that facilities are compensated at the same per diem rates, with larger LTC facilities operating more efficiently than smaller LTC facilities. We also found significant differences in performance by profit status and urban/rural location. The results also underline the importance of considering an array of quality indicators and controlling for endogeneity of quality.

Amy Hsu is a MSc candidate in the Department of Health Policy, Management and Evaluation under the supervision of Dr. Peter C. Coyte and Dr. Audrey Laporte. Her research interest is in performance measurement, especially pertaining to geriatrics and long-term care. Amy received her Honours BSc in Human Biology from the University of Toronto in 2008, and has a background in human genetics, sociology and religion.