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Daddato AE, Dollar B, Lum HD, Burke RE, Boxer RS. Identifying Patient Readmissions: Are Our Data Sources Misleading?. Journal of The American Medical Directors Association. 2019 Aug 1; 20(8):1042-1044.
BACKGROUND: The accuracy of data is vital to identifying hospitalization outcomes for clinical trials. Patient attrition and recall bias affects the validity of patient-reported outcomes, and the growing prevalence of Medicare Advantage (MA) could mean Fee-for-Service (FFS) claims are less reliable for ascertaining hospital utilization. Statewide health information exchanges (HIEs) may be a more complete data source but have not been frequently used for research. DESIGN: Secondary analysis comparing identification of readmissions using 3 different acquisition approaches. SETTING: Randomized controlled trial of heart failure (HF) disease management in 37 skilled nursing facilities (SNFs). PARTICIPANTS: Patients with HF discharged from the hospital to SNF. MEASURES: Readmissions up to 60 days post-SNF admission collected by patient self-report, recorded by nursing home (NH) staff during the SNF stay, or recorded in the state HIE. RESULTS: Among 657 participants (mean age 79 ± 10 years, 49% with FFS), 295 unique readmissions within 60 days of SNF admission were identified. These readmissions occurred among 221 patients. Twenty percent of all readmissions were found using only patient self-report, 28% were only recorded by NH staff during the SNF stay, and 52% were identified only using the HIE. The readmission rate (first readmission only) based only on patient self-report and direct observation was 18% rather than 34% with the addition of the enhanced HIE method. CONCLUSIONS AND IMPLICATIONS: More than one-quarter (34%) of HF patients were rehospitalized within 60 days post SNF admission. Use of a statewide HIE resulted in identifying an additional 153 admissions, 52% of all the readmissions seen in this study. Without use of an HIE, nearly half of readmissions would have been missed as a result of incomplete patient self-report or loss to follow-up. Thus, HIEs serve as an important resource for researchers to ensure accurate outcomes data.