Magnus Björkgren

Validity and reliability of Resource Utilization Groups (RUG-III) in Finnish long-term care facilities

Resource Utilization Groups, Version III (RUG-III) is a case-mix system developed in the USA for classification of long-term care residents. This paper examines the validity and reliability of an adapted 22-group version of RUG-III (RUG-III/22) for use in long-term care facilities in Finland. Finnish cost weights for RUG-III/22 groups are calculated and different methods for their computation are evaluated. The study sample (1,964 residents) was collected in 1995 - 96 from ten long-term care facilities in Finland. RUG-III/22 alone explained 38.2% of the variance of total patient-specific (nursing + auxiliary staff) per diem cost. Resource use within RUG groups was relatively homogeneous. Other predictors of resource use included age, gender and length of stay. RUG-III/22 also met the standard for good reliability (i.e. a kappa value of 0.6 or higher) for crucial classification items, such as activities of daily living and high correlation between assessments based on relative cost.

Measuring efficiency of long-term care units in Finland.

Data Envelopment Analysis (DEA) was used to measure the nursing care efficiency of 64 long-term care units in Finland. New approaches introduced for evaluating efficiency were unit/ward level analysis, and the case-mix classification Resource Utilization Groups (RUG-III). Efficiency determinations were based on four DEA measures: cost, technical, allocative, and scale efficiency. The results indicated considerable variation in efficiency between units, suggesting that efficiency could be improved through better management and allocation of resources. Larger units seemingly operated more efficiently than smaller units. Allocative inefficiency resulted from using too many registered nurses and aides, and too few licensed practical nurses.

Case-mix adjustment and efficiency measurement:

Aims: The importance of using valid case-mix systems in long-term care is addressed by comparing the predictive power of different case-mix models, and by applying them in the calculation of technical efficiency scores of care units. Methods: To construct different case-mix models a statistical clustering technique (Automatic Interaction Detection) was used. Technical efficiency score were calculated using data envelopment analysis (DEA). Results: The Resource Utilization Groups (RUG-III/22) classification explained 39% of resident specific cost, compared with 16% for a functional dependency scale in the Finnish patient information system HILMO. Conclusion: When assessing the economic performance of long-term care units it is important to pay attention to the predictive validity of the case-mix measure to be used. The choice of case-mix measure significantly affected how units were rated in efficiency.

Association between Rehabilitation Care Practices and CAre Quality in Long-Term Care Facilities.

This article analyzes the association between rehabilitation care practices and quality outcomes in Finland and represents unit-level (n = 256) associations between rehabilitation nursing and quality outcomes. Units classified as units providing a high frequency of rehabilitation care practices had better outcomes in 2 of 5 quality outcomes.

Applying RUG-III for reimbursement of nursing facility care

The Resource Utilization Groups (RUG-III) case-mix classification is becoming an internationally accepted methodology for determining payment for nursing facility and care. In this paper we discuss the key concepts of case-mix reimbursement and several different payment approaches based on RUG-III. In discussing the empirical evidence of case-mix reimbursement, we draw especially on the US experience. Clearly, the success of case-mix reimbursement depends not only on the payment design, but also on the ability to foresee market conditions and the regulatory environment in which the payment system is being implemented. Moreover, we demonstrate the need to develop a case-mix based reimbursement in Finland, where institutional long-term care is mainly provided by the public sector. Finally, we propose that developing financial reward systems based on quality and performance could be important additions to existing case-mix payment systems, as market mechanisms and government regulation of quality may not offer sufficient incentives to provide optimal care.

409 Using rai-hc assessment instrument to classify home care clients in Finland based on fire emergency evacuation capacity

Background When an uncontrollable fire is detected in a building there may be a 2–3 minutes window for the occupants to move to safety. Poor physical function and cognition may become critical factors in an evacuation situation. In this study a novel functional scale measuring emergency evacuation capacity of home care clients is presented. Methods A fire security expert visited about 250 home care clients assessing their evacuation capacities. For the evacuation capacity three categories were used: 1) is able to evacuate; 2) may be able; 3) unable to evacuate. This data was linked to comprehensive assessments of clients functional and health status performed by home care nurses using the interRAI Home Care Assessment Instrument (RAI-HC). The goal was to investigate whether the evacuation capacity classification can be explained in terms of RAI-HC variables. As the mathematical method we have employed “classification and regression trees” (CART). Results A fire evacuation capacity scale “EVAC” was developed using four levels of cognitive function as major categories. These categories were split into final groups based on performance in physical function. For each group we calculated the average capacity score ranging from 0 to 1 based on the dependent variable. Conclusions The evacuation scale gives an estimate of a client’s ability to get out in case of a fire. The scale can be used to single out high risk persons for which compensatory safety technology may be required. The scale could reduce costs in assessing evacuation capacity of home care clients.