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Temporal variability analysis reveals biases in electronic health records due to hospital process reengineering interventions over seven years.

Authors :
Francisco Javier Pérez-Benito
Carlos Sáez
J Alberto Conejero
Salvador Tortajada
Bernardo Valdivieso
Juan M García-Gómez
Source :
PLoS ONE, Vol 14, Iss 8, p e0220369 (2019)
Publication Year :
2019
Publisher :
Public Library of Science (PLoS), 2019.

Abstract

ObjectiveTo evaluate the effects of Process-Reengineering interventions on the Electronic Health Records (EHR) of a hospital over 7 years.Materials and methodsTemporal Variability Assessment (TVA) based on probabilistic data quality assessment was applied to the historic monthly-batched admission data of Hospital La Fe Valencia, Spain from 2010 to 2016. Routine healthcare data with a complete EHR was expanded by processed variables such as the Charlson Comorbidity Index.ResultsFour Process-Reengineering interventions were detected by quantifiable effects on the EHR: (1) the hospital relocation in 2011 involved progressive reduction of admissions during the next four months, (2) the hospital services re-configuration incremented the number of inter-services transfers, (3) the care-services re-distribution led to transfers between facilities (4) the assignment to the hospital of a new area with 80,000 patients in 2015 inspired the discharge to home for follow up and the update of the pre-surgery planned admissions protocol that produced a significant decrease of the patient length of stay.DiscussionTVA provides an indicator of the effect of process re-engineering interventions on healthcare practice. Evaluating the effect of facilities' relocation and increment of citizens (findings 1, 3-4), the impact of strategies (findings 2-3), and gradual changes in protocols (finding 4) may help on the hospital management by optimizing interventions based on their effect on EHRs or on data reuse.ConclusionsThe effects on hospitals EHR due to process re-engineering interventions can be evaluated using the TVA methodology. Being aware of conditioned variations in EHR is of the utmost importance for the reliable reuse of routine hospitalization data.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
14
Issue :
8
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.bd4748b44ae741e5bef57d7537d0a8f0
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0220369