PMID- 36993433
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20231027
DP  - 2023 Mar 16
TI  - Screening for the High-Need Population Using Single Institution Versus State-Wide 
      Admissions Discharge Transfer Feed.
LID - rs.3.rs-2565761 [pii]
LID - 10.21203/rs.3.rs-2565761/v1 [doi]
AB  - 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((R)) 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.
FAU - Balucan, Francis Salvador
AU  - Balucan FS
AD  - Vanderbilt University Medical Center.
FAU - French, Benjamin
AU  - French B
AD  - Vanderbilt University.
FAU - Shi, Yaping
AU  - Shi Y
AD  - Vanderbilt University.
FAU - Kripalani, Sunil
AU  - Kripalani S
AD  - Vanderbilt University Medical Center.
FAU - Vasilevskis, Eduard E
AU  - Vasilevskis EE
AD  - Vanderbilt University Medical Center.
LA  - eng
GR  - UL1 TR002243/TR/NCATS NIH HHS/United States
PT  - Preprint
DEP - 20230316
PL  - United States
TA  - Res Sq
JT  - Research square
JID - 101768035
UIN - BMC Health Serv Res. 2023 Oct 17;23(1):1111. PMID: 37848976
PMC - PMC10055535
COIS- Competing interests We have no conflicts of interest to disclose.
EDAT- 2023/03/31 06:00
MHDA- 2023/03/31 06:01
PMCR- 2023/03/29
CRDT- 2023/03/30 02:52
PHST- 2023/03/31 06:00 [pubmed]
PHST- 2023/03/31 06:01 [medline]
PHST- 2023/03/30 02:52 [entrez]
PHST- 2023/03/29 00:00 [pmc-release]
AID - rs.3.rs-2565761 [pii]
AID - 10.21203/rs.3.rs-2565761/v1 [doi]
PST - epublish
SO  - Res Sq [Preprint]. 2023 Mar 16:rs.3.rs-2565761. doi: 10.21203/rs.3.rs-2565761/v1.