Literature DB >> 30338476

Implementation and Benefits of a Vendor-Neutral Archive and Enterprise-Imaging Management System in an Integrated Delivery Network.

Chen Sirota-Cohen1, Beverly Rosipko2, Daniel Forsberg3, Jeffrey L Sunshine2.   

Abstract

The use of digital imaging has substantially grown in recent decades, in traditional services, new specialties, and departments. The need to share these data among departments and caregivers necessitated central archiving systems that are able to communicate with various viewing applications and electronic medical records. This promoted the development of modern vendor neutral archive (VNA) systems. The need to aggregate and share imaging data from various departments promoted the development of enterprise-imaging (EI) solutions that replace departmental silos of data with central healthcare enterprise databases. To describe the implementation process of a VNA-EI solution in a large health system and its outcomes. We review the background of VNA and EI solutions development and describe the characteristics and advantages of such systems. We then describe our experience in implementation of these solutions in a large integrated healthcare delivery network in northeast Ohio. We then present the process, challenges, costs, advantages, and outcomes of such implementation. The VNA and EI solution was launched in December 2015 and is still ongoing. It currently includes 54 radiology and 26 cardiology sites affiliated with the University Hospitals health system. This process was associated with more than 10% cost savings, 30% reduction in storage costs, superior support for disaster recovery, and 80% decrease in unscheduled outages. All these were achieved despite a 120% increase in archive retrieval needs and a 40% growth in image production. Implementation of a VNA and EI solution was successful and resulted in numerous measurable and qualitative improvements in a large and growing health system.

Keywords:  Diagnostic imaging; Medical informatics; Patient-centered care; Radiology information systems

Mesh:

Year:  2019        PMID: 30338476      PMCID: PMC6456740          DOI: 10.1007/s10278-018-0142-3

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


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Journal:  J Digit Imaging       Date:  2020-02       Impact factor: 4.056

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Review 3.  Artificial Intelligence in Pathology: From Prototype to Product.

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Journal:  J Pathol Inform       Date:  2021-03-22

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