Screening for the high-need population using single institution versus state-wide admissions discharge transfer feed.

BACKGROUND: Access to programs for high-needs patients depending on single-institution electronic health record data (EHR) carries risks of biased sampling. We investigate a statewide admission, discharge, and transfer feed (ADT) in assessing equity in access to these programs. METHODS: This is a retrospective cross-sectional study. We included high-need patients at Vanderbilt University Medical Center (VUMC) 18 years or older, with at least three emergency visits (ED) or hospitalizations in Tennessee from January 1 to June 30, 2021, including at least one at VUMC. We used the Tennessee ADT database to identify high-need patients with at least one VUMC ED/hospitalization. Then, we compared this population with high-need patients identified using VUMC's Epic® EHR database. The primary outcome was the sensitivity of VUMC-only criteria for identifying high-need patients compared to the statewide ADT reference standard. RESULTS: We identified 2549 patients with at least one ED/hospitalization and assessed them as high-need based on the statewide ADT. Of those, 2100 had VUMC-only visits, and 449 had VUMC and non-VUMC visits. VUMC-only visit screening criteria showed high sensitivity (99.1%, 95% CI: 98.7 - 99.5%), showing that the high-needs patients admitted to VUMC infrequently access alternative systems. Results showed no meaningful difference in sensitivity when stratified by patient's race or insurance. CONCLUSIONS: ADT allows examination for potential selection bias when relying upon single-institution utilization. In VUMC's high-need patients, there's minimal selection bias when depending on same-site utilization. Further research must understand how biases vary by site and durability over time.

Screening for the High-Need Population Using Single Institution Versus State-Wide Admissions Discharge Transfer Feed.

Background: Access to programs for high-needs patients depending on single-institution electronic health record data (EHR) carries risks of biased sampling. We investigate a statewide admissions, discharge, transfer feed (ADT), in assessing equity in access to these programs. Methods: This is a retrospective cross-sectional study. We included high-need patients at Vanderbilt University Medical Center (VUMC), who were 18 years or older, with minimum three emergency visits (ED) or hospitalizations in Tennessee from January 1 to June 30, 2021, including at least one at VUMC. We used the Tennessee ADT database to identify high-need patients with at least one VUMC ED/hospitalization, then compared this population with high-need patients identified using VUMC's Epic® EHR database. The primary outcome was the sensitivity of VUMC-only criteria for identifying high-need patient when compared to statewide ADT reference standard. Results: We identified 2549 patients that had at least one ED/hospitalization and were assessed to be high-need based on the statewide ADT. Of those, 2100 had VUMC-only visits, and 449 had VUMC and non-VUMC visits. VUMC-only visit screening criteria showed high sensitivity (99.1%, 95% CI: 98.7% - 99.5%), indicating that the high-needs patients admitted to VUMC infrequently access alternative systems. Results demonstrated no meaningful difference in sensitivity when stratified by patient's race or insurance. Conclusions: ADT allows examination for potential selection bias when relying upon single-institution utilization. In VUMC's high-need patients, there's minimal selection bias when relying upon same-site utilization. Further research needs to understand how biases may vary by site, and durability over time.