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Realizing Quality & Experience Benefits Through EHR Adoption & Use: A Conceptual Model.

Gurprit K Randhawa¹

¹Clinical Improvements & Informatics, Island Health, Victoria, BC.

Studies in Health Technology and Informatics

|February 12, 2019

Summary

This study presents a conceptual model for Electronic Health Record (EHR) adoption and use, detailing components for quality and experience benefits. The model, with over 130 metrics, aids in planning and evaluating EHR implementations.

Keywords:

Benefits Realization Conceptual Model Electronic Health Records

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Area of Science:

Health Informatics
Information Systems Research
Healthcare Management

Background:

Electronic Health Records (EHRs) are crucial for modern healthcare delivery.
Understanding the factors influencing EHR adoption and use is essential for maximizing benefits.
Existing frameworks lack a comprehensive model integrating technology adoption with healthcare quality and experience.

Purpose of the Study:

To present a comprehensive conceptual model for Electronic Health Record (EHR) adoption and use.
To identify key constructs, antecedents, and moderator variables influencing EHR implementation success.
To outline benefit areas (quality and experience) at multiple levels (micro, meso, macro).

Main Methods:

Developed a conceptual model based on a review of technology adoption/use and healthcare quality frameworks.
Identified 42 constructs, including six key constructs, three antecedents, and four moderator variables.
Operationalized the model by identifying over 130 metrics for construct measurement.

Main Results:

The conceptual model integrates micro, meso, and macro levels of EHR adoption and use.
It specifies key constructs, antecedents, and moderators impacting EHR implementation.
The model includes two primary benefit areas: quality of care and patient experience.

Conclusions:

The developed EHR adoption and use (EAU) model provides a framework for understanding and evaluating EHR implementations.
The model's operationalization with over 130 metrics allows for empirical testing and practical application.
Further testing of the EAU model is recommended to validate its utility in diverse healthcare settings.