Nursing home case mix. Patient classification by nursing resource use

Area of Science:

• Gerontology
• Health Services Research
• Nursing Administration

Background:

• Nursing home patient classification is crucial for resource allocation.
• Existing methods may not accurately capture the nuances of nursing care needs.
• Understanding patient acuity is vital for efficient healthcare management.

Purpose of the Study:

• To develop and validate a model for classifying nursing home patients based on nursing resource use.
• To identify patient characteristics that predict significant differences in care requirements.
• To improve the accuracy of nursing resource allocation in long-term care facilities.

Main Methods:

• A study involving 558 Medicaid nursing home patients across 12 Virginia facilities.
• Data collected via nursing staff self-reports of care delivery and validated by work sampling.
• Patient health and functional status assessed using a standardized instrument.
• Classification and Regression Trees (AID) analysis employed for patient grouping.

Main Results:

• A six-group classification model was developed, demonstrating homogeneity in nursing resource utilization within each group.
• Patients were categorized based on specialized care needs (e.g., nutritional issues, quadriplegia, wounds, coma, rehabilitation potential) and non-specialized needs (e.g., Activities of Daily Living impairment, feeding assistance).
• The highest resource-utilizing group consumed nearly four times the resources of the lowest group.
• The model explained 53% of the variance in nursing resource use.

Conclusions:

• The developed model effectively classifies nursing home patients according to nursing resource needs.
• The classification system highlights significant disparities in care requirements among patient groups.
• This model offers a valuable tool for optimizing nursing staff allocation and resource management in nursing homes.