Risk adjustment for benchmarking nursing home infection surveillance data: A narrative review

Area of Science:

• Infection Control
• Healthcare Quality Improvement
• Epidemiology

Background:

• The United States lacked a national surveillance system for infections in long-term care facilities (LTCF) until recently.
• This absence of data prevents the establishment of national benchmarks for LTCF infection rates, hindering quality improvement efforts.
• A key challenge in reporting healthcare-associated infection data is accounting for facility and patient characteristics that influence infection benchmarks.

Purpose of the Study:

• To review published infection rates in US LTCFs and assess variability.
• To identify facility- and resident-level risk factors for infection applicable to risk adjustment models.
• To examine existing attempts at risk-adjusting LTCF infection rates and efforts to develop specific models for benchmarking.

Main Methods:

• Literature review of published infection rates in US LTCFs.
• Analysis of studies identifying facility- and resident-level risk factors for infection.
• Review of published risk adjustment models and benchmarking efforts for LTCF infections.

Main Results:

• Significant variability exists in published LTCF infection rates.
• Numerous facility- and resident-level risk factors influencing infection rates have been identified.
• Various approaches to risk-adjusting LTCF infection rates have been attempted, with ongoing development of specific models.

Conclusions:

• Further research is needed to refine risk adjustment methodologies for LTCF infection rates.
• Development of robust risk adjustment models is crucial for effective benchmarking and public reporting.
• Improved risk adjustment will facilitate research and enhance quality improvement initiatives in LTCFs.