Validation of the Minimum Data Set in identifying hospitalization events and payment source

Area of Science:

• Health Services Research
• Gerontology
• Health Informatics

Background:

• Nursing home residents are a vulnerable population with complex healthcare needs.
• Accurate tracking of hospitalizations and payment sources is crucial for quality assessment and resource allocation in nursing homes.

Purpose of the Study:

• To assess the accuracy of the Minimum Data Set (MDS) for identifying hospitalization events.
• To evaluate the MDS's reliability in determining payment sources (Medicare/Medicaid) for nursing home residents.

Main Methods:

• Utilized 2003 MDS data linked with Medicare (MedPAR, denominator) and Medicaid (MAX) claims files from four states.
• Established a "gold standard" by linking MDS and claims data to calculate error rates.
• Analyzed false negative and false positive rates for hospitalization and payment source identification.

Main Results:

• MDS hospitalization event identification showed false negative rates of 6.8%-19.5% and false positive rates of 12.0%-15.7%.
• Medicare payment source identification by MDS had low false negatives (0.4%-1.1%) but high false positives (6.1%-14.9%).
• MDS alone was insufficient for Medicaid payment source identification, with high false negative rates (11.0%-55.3%).

Conclusions:

• The accuracy of the Minimum Data Set (MDS) in identifying hospitalizations and payment sources is not uniform across states.
• Findings suggest the MDS requires careful validation based on its specific application and the intended use of the data.