Grannis, Shaun
Enhancing Patient Matching in Support of Operational Health Information Exchange
Description
This project will enhance novel algorithms for matching patient health information across data sources, implement them, and evaluate their accuracy.
Grant Number
R01 HS023808
Principal Investigator(s)
A simple two-step procedure using the Fellegi-Sunter model for frequency-based record linkage.
Citation
Xu H, Li X, Grannis S. A simple two-step procedure using the Fellegi-Sunter model for frequency-based record linkage. J Appl Stat. 2021 May 4;49(11):2789-2804. doi: 10.1080/02664763.2021.1922615. PMID: 35909667; PMCID: PMC9336505.
Principal Investigator
The data-adaptive Fellegi-Sunter model for probabilistic record linkage: Algorithm development and validation for incorporating missing data and field selection.
Citation
Li X, Xu H, Grannis S. The data-adaptive Fellegi-Sunter model for probabilistic record linkage: Algorithm development and validation for incorporating missing data and field selection. J Med Internet Res. 2022 Sep 29;24(9):e33775. doi: 10.2196/33775. PMID: 36173664; PMCID: PMC9562057.
Principal Investigator
A framework for a consistent and reproducible evaluation of manual review for patient matching algorithms.
Citation
Gupta AK, Kasthurirathne SN, Xu H, Li X, Ruppert MM, Harle CA, Grannis SJ. A framework for a consistent and reproducible evaluation of manual review for patient matching algorithms. J Am Med Inform Assoc. 2022 Nov 14;29(12):2105-2109. doi: 10.1093/jamia/ocac175. PMID: 36305781; PMCID: PMC9667171.
Principal Investigator
Machine learning approaches to identify nicknames from a statewide Health Information Exchange.
Citation
Kasthurirathne SN, Grannis SJ. Machine learning approaches to identify nicknames from a statewide Health Information Exchange. AMIA Jt Summits Transl Sci Proc. 2019 May 6;2019:639-647. PMID: 31259019; PMCID: PMC6568128.
Principal Investigator
Comparison of supervised machine learning and probabilistic approaches for record linkage.
Citation
McNutt, A.T., Grannis, S.J., Bo, N., Xu, H., Kasthurirathne, S. N.(2020, March). Comparison of supervised machine learning and probabilistic approaches for record linkage. AMIA Informatics summit 2020 Conference Proceedings.
Principal Investigator
Evaluating two approaches for parameterizing the Fellegi-Sunter patient matching algorithm to optimize accuracy.
Citation
Grannis, S., Kasthurirathne, S., Bo, N., Xu, H. (2019). Evaluating two approaches for parameterizing the Fellegi-Sunter patient matching algorithm to optimize accuracy. Medinfo conference proceedings
Principal Investigator
Incorporating conditional dependence in latent class models for probabilistic record linkage: Does it matter?.
Citation
Huiping Xu. Xiaochun Li. Changyu Shen. Siu L. Hui. Shaun Grannis. "Incorporating conditional dependence in latent class models for probabilistic record linkage: Does it matter?." Ann. Appl. Stat. 13 (3) 1753 - 1790, September 2019. https://doi.org/10.1214/19-AOAS1256
Principal Investigator
Evaluating the effect of data standardization and validation on patient matching accuracy.
Citation
Grannis SJ, Xu H, Vest JR, Kasthurirathne S, Bo N, Moscovitch B, Torkzadeh R, Rising J. Evaluating the effect of data standardization and validation on patient matching accuracy. J Am Med Inform Assoc. 2019 May 1;26(5):447-456. doi: 10.1093/jamia/ocy191. PMID: 30848796; PMCID: PMC7787357.
Principal Investigator