Application of a case-mix classification based on the functional autonomy of the residents for funding long-term care facilities

Abstract

Introduction: increasing public costs for the care of the elderly have created fundamental changes that are redefining the basic principles of health care funding. In the past, overall institutional funding was predominantly tied to spending. In view of the limitations of this approach to funding long-term care facilities, case-mix classification tries to take into account the characteristics of the residents as a tool for predicting costs. Recently, a new case-mix classification based on the functional autonomy profile of the residents - ISO-SMAF profile - was developed in the Province of Quebec, Canada. This classification can be used to change the funding system to base it on the functional autonomy characteristics of the residents. Objectives: the main objective of this study was to apply the ISO-SMAF classification to funding long-term care facilities in one area of the Province of Quebec and to compare the results of this new funding methodology to the formal methodology. Design: this study used a cross-sectional design. Methodology: the population under study comprised all residents of all 11 long-term care facilities in the Eastern Townships area of Quebec. Each resident was assessed using the Functional Autonomy Measurement System. The theoretical budget was calculated based on the adjusted cost per year associated with each ISO-SMAF profile derived from a previous economic study. Results: the theoretical budget based on the ISO-SMAF profiles may highlight the under- or over-funding of a facility when compared to the usual funding system based predominantly on the number of beds and hours of care. Conclusion: the results of this study show the feasibility of applying the new funding approach to long-term care facilities. However, implementation of the ISO-SMAF classification for funding must be supported by continued and computerised residents' medical files including the Functional Autonomy Measurement System.