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Development and Evaluation of Socio-Technical Metrics to Inform HIT Adaptation

$144,172R21FY2016HSAHRQ

Ohio State University, Columbus OH

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Abstract

Abstract: During the past 10 years, several policies, such as the Health Information Technology for Economic and Clinical Health Act (HITECH), have led to accelerated HIT implementation in healthcare settings, especially the implementation of electronic health record (EHR) systems. Adopting new technology requires the redesign of individual and collective workflows and results in changes in both organizational structure and processes. HIT adoption is often evaluated using adoption rates, acceptance, and clinical quality measures; however, although these measures are helpful to assess the maturity of HIT implementation, they do not inform organizational or human factors that could delay or cause the mission of HIT to fail. Given that the technical features of HIT interact with the social features of a healthcare work environment, there is significant value in studying HIT from a socio-technical perspective. Since HIT implementation is a process, not an outcome, we hypothesize that HIT adoption can be assessed through the understanding of the progress of HIT adaptation. The proposed research will be conducted at The Ohio State University Wexner Medical Center (OSUWMC), which is one of the largest academic medical centers in the country, with a rich diversity of specialties, workplace cultures, and collaboration dynamics. Despite a common EHR infrastructure (Epic), the progress of HIT adaptation differs from one department/unit to another because of different adoption start dates and trajectories. We will use a socio-technical theory as the foundational theoretical guidance for this project and engage in concurrent collection of both quantitative and qualitative data - a concurrent transformative mixed methods design. We will identify measures and create instruments to evaluate the progress and status of HIT adaptation. Our instrument development and validation process is aligned to the NIH PROMIS® methodological specification for best-demonstrated practice in instrument development and validation. The success of this project will offer an innovative approach and demonstrate the use of socio-technical theory to evaluate and accelerate the progress of HIT adaptation, which is essential for current, ongoing EHR optimization in the healthcare environment.

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