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

• Published in: PloS one Vol. 14; no. 8; p. e0220369
• Main Authors: Pérez-Benito, Francisco Javier, Sáez, Carlos, Conejero, J Alberto, Tortajada, Salvador, Valdivieso, Bernardo, García-Gómez, Juan M
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 07-08-2019; Public Library of Science (PLoS)
• Subjects: Bias; Cancer; Comorbidity; Computer and Information Sciences; Conditioning; Electronic health records; Electronic Health Records - trends; Electronic medical records; Electronic records; Emergency medical care; Engineering; Engineering and Technology; Evaluation; Health care; Hospitals; Humans; Influence; Information management; Medical care quality; Medical records; Medicine and Health Sciences; Methods; Patient Discharge; Patient Transfer; Patients; People and places; Physical Sciences; Quality; Quality assessment; Quality control; Quality of Health Care; Reengineering; Reengineering (Management); Reengineering (process); Relocation; Research and Analysis Methods; Spain; Surgery; Temporal variability; Variability; Spain
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0220369

To evaluate the effects of Process-Reengineering interventions on the Electronic Health Records (EHR) of a hospital over 7 years.
Temporal 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.
Four 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.
TVA 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.
The 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.