A proposed method for identifying Interfacility transfers in Medicare claims data

Area of Science:

• Health Services Research
• Health Informatics
• Cardiovascular Medicine

Background:

• Accurate identification of interfacility transfers (IFTs) is crucial for understanding patient care pathways and resource allocation within the healthcare system.
• Existing methods for identifying IFTs in large administrative datasets like Medicare claims may be suboptimal, potentially leading to undercounting and misrepresentation of patient populations.
• ST-Elevation Myocardial Infarction (STEMI) patients often require complex care involving transfers between facilities, making them a relevant model population for evaluating transfer identification methods.

Purpose of the Study:

• To develop and validate a novel method for consistently identifying interfacility transfers (IFTs) within Medicare claims data.
• To compare the performance of the proposed IFT identification method against existing approaches using a cohort of patients with ST-Elevation Myocardial Infarction (STEMI).
• To assess the demographic and geographic characteristics of patients identified as IFTs using both methods, focusing on rural and lower-income populations.

Main Methods:

• Utilized 100% Medicare inpatient and outpatient Standard Analytic Files and 5% Carrier Files from 2011-2020.
• Employed an observational, cross-sectional study design to compare patient characteristics between the proposed and existing IFT identification methods.
• Focused the analysis on Medicare beneficiaries aged 65 and older diagnosed with STEMI.

Main Results:

• The proposed method identified 62,668 more IFTs than the existing method (86,128 vs. 23,460).
• A separately billable interfacility ambulance trip was associated with a higher percentage of IFTs under the proposed method (86% vs. 79%).
• Patients identified via the proposed method were more likely to reside in rural and lower-income counties and were located farther from critical care facilities (p < 0.001).

Conclusions:

• The conventional method of identifying IFTs based on two consecutive inpatient claims leads to significant undercounting.
• The proposed method provides a more comprehensive identification of IFTs, better reflecting the healthcare needs of rural and underserved populations.
• Improved IFT identification is essential for equitable resource allocation and understanding care access for vulnerable patient groups.