Journal article
Inferring patient transfer networks between healthcare facilities
Health services and outcomes research methodology, Vol.22(1), pp.1-15
05/07/2021
DOI: 10.1007/s10742-021-00249-5
Abstract
Constructing accurate patient transfer networks between hospitals is critical for understanding the spread of healthcare associated infections through statistical and mathematical modeling, and for determining optimal screening and treatment strategies. The Healthcare Cost & Utilization Project (HCUP) State Inpatient Databases (SID) provide valuable information on patient transfers from publicly obtainable claims databases, yet often give an incomplete picture due to missingness of patient tracking identifiers. We designed a novel imputation algorithm that enabled us to estimate the true number of patient transfers between each pair of hospitals in a state over a specified time period and age group in the presence of these missing identifiers. We then validated the algorithm’s performance through a series of simulation experiments using the HCUP SID, and finally tested the algorithm on multiple states’ genuine data. Our proposed method significantly reduced the total mean squared error in predicting the true number of transfers amongst hospitals for all simulation experiments, and it also yielded epidemic simulations that more closely approximated those corresponding to the true patient transfer network.
Details
- Title: Subtitle
- Inferring patient transfer networks between healthcare facilities
- Creators
- Samuel A JusticeDaniel K SewellAaron C MillerJacob E SimmeringPhilip M PolgreenCDC MInD-Healthcare Program
- Resource Type
- Journal article
- Publication Details
- Health services and outcomes research methodology, Vol.22(1), pp.1-15
- DOI
- 10.1007/s10742-021-00249-5
- ISSN
- 1387-3741
- eISSN
- 1572-9400
- Grant note
- DOI: 10.13039/100000030, name: Centers for Disease Control and Prevention, award: 5 U01 CK000531-02, U01 CK000594-01-00
- Language
- English
- Date published
- 05/07/2021
- Academic Unit
- Pulmonary, Critical Care, and Occupational Medicine; Infectious Diseases; Health Management and Policy; Epidemiology; Biostatistics; Pharmacy Practice and Science; Injury Prevention Research Center; Public Policy Center (Archive); Internal Medicine
- Record Identifier
- 9984214792002771
Metrics
27 Record Views