Difference between revisions of "ENTERPRISE IMAGING"

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The increasing adoption of Electronic Health Record (EHR) systems has been driven in part by Meaningful Use requirements, with a goal towards optimizing health system performance.  The EHR facilitates the integration of previously paper-based or otherwise disparate information sources such as clinical documentation/charting, medication records, billing, laboratory results, and radiology reports, and to a certain extent can provide a limited ability to view the associated Digital Imaging and Communication in Medicine (DICOM)-standard imaging studies.  A large and growing quantity of image-rich clinical content obtained in non-traditional settings such as during clinical office visits or during procedures is, however,  not currently accessible outside the point-of-acquisition in most environments.  Inaccessible imaging is often repeated, leading to increased costs and, in the case of x-ray or nuclear medicine-based studies, increased radiation exposure to the patient.  A model for Enterprise Imaging is emerging as a method to optimize the secure capture and storage of all relevant clinical imaging across the enterprise, and to facilitate the sharing of this content via an integrated EHR viewer.
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== Background == 
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The role of the [[EHR]] with respect to imaging services has historically been to function as an interface to the Radiology Information System ([[RIS]]) for study ordering and retrieval of results.  More mature implementations typically provide additional but limited functionality to view images via hyperlink within an external [[PACS]] (Picture Archiving and Communications System) viewer.  While this system has functioned relatively well to date with respect to traditional [[DICOM]] radiology imaging services obtained within the context of the local enterprise, a wealth of important and information-rich multimedia clinical imaging present both within and extrinsic to the enterprise is not typically accessible through most current EHR implementations.  Such (typically non-DICOM) clinical content is routinely acquired at point-of-care in both the inpatient and outpatient settings by multiple disciplines.  Examples include photographic images of a patient's skin cancer taken during an outpatient dermatology visit ([[imaging informatics]]), ophthalmic imaging of the retina,  digitally-captured images and/or video during endoscopic or orthopedic procedures, and forensic imaging taken during evaluation of suspected sexual or child abuse cases.  A standardized workflow for the acquisition, storage, indexing, retrieval, and security of this nontraditional content is typically not homogeneous across an enterprise, therefore limiting its availability within most current EMR systems.  A model for Enterprise Imaging is emerging as a method to optimize the secure capture and storage of all relevant clinical imaging across the enterprise, and to facilitate the sharing of this content via an integrated EHR viewer.
  
  
 +
== Sources of Imaging Content ==
 +
The acquisition and primary interpretation of medical images was historically considered the purview of radiology, with conventional film radiography representing the bulk of imaging procedures. The spectrum of available imaging studies has now exploded to include both contrast and non-contrast computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound (US), as well as the functional studies of nuclear medicine. Imaging is no longer isolated to the radiology department. Clinical providers from almost every discipline now frequently engage in some form of point-of-care imaging, including optical static or cine imaging obtained during endoscopic and arthroscopic procedures, and medical photography.
  
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== Enterprise Imaging:  Overview
 
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==
 
  
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The Institute for Healthcare Improvement (IHI) Triple Aim describes a framework for optimizing healthcare system performance that includes a focus on patient experience, population health, and cost reduction (Institute for Healthcare Improvement, 2016).  An important component of achieving this optimization is coordination of care within and across the clinical enterprise, both to reduce the volume of unnecessary and/or duplicated services, and to foster better patient outcomes through improved communication.   
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== Workflow for Image Acquisition and Management  ==
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The role of the EHR with respect to imaging services has historically been to function as an interface to the Radiology Information System (RIS) for study ordering and retrieval of results.  More mature implementations typically provide additional but limited functionality to view images via hyperlink within an external PACS (Picture Archiving and Communications System) viewer.  While this system has functioned relatively well to date with respect to traditional DICOM radiology imaging services obtained within the context of the local enterprise, a wealth of important and information-rich multimedia clinical imaging present both within and extrinsic to the enterprise is not typically accessible through most current EHR implementations.  Such (typically non-DICOM) clinical content is routinely acquired at point-of-care in both the inpatient and outpatient settings by multiple disciplines.  Examples include photographic images of a patient's skin cancer taken during an outpatient dermatology visit, ophthalmic imaging of the retina,  digitally-captured images and/or video during endoscopic or orthopedic procedures, and forensic imaging taken during evaluation of suspected sexual or child abuse cases.  A standardized workflow for the acquisition, storage, indexing, retrieval, and security of this nontraditional content is typically not homogeneous across an enterprise, therefore limiting its availability within most current EMR systems.  Collaborative efforts are currently underway to address this gap in available clinical information through development of an Enterprise Imaging model.
+
Multimedia clinical content is being acquired with increasing frequency and volume by numerous specialties across the medical enterprise, outside the traditional domains of radiology.  While much of this imaging is currently obtained via the orders-based/SWF model using traditional modalities (e.g., the use of ultrasound by cardiology and OB/GYN), a growing volume of non-traditional “visible light” modality imaging is obtained by other specialties such as dermatology, ophthalmology, dentistry, and endoscopy. Imaging in these specialties is often obtained ad-hoc or incidentally during the clinical encounter within the context of a locally-defined workflow model, and is typically not the primary purpose for the visit (Cram, 2016).  The purpose of imaging by these specialties could be to complement the clinical visit or procedure, or to document relevant findings for follow-up and/or billing purposes. Example use cases would include visible-light photography of a suspicious lesion being examined in a primary care or dermatology clinic, bedside ultrasound (FAST scan) performed in the ER for trauma, or digital capture images of a suspicious lesion observed during an endoscopic procedure. Similar to the transition in radiology from film-based to digital storage, the digitization of pathology will enable review of the relevant images along with the diagnostic report within the EHR. Concerns have been raised, however, regarding the lack of a DICOM standard (Kalinski, 2012).  The ability to organize, index, store, secure, and retrieve this emerging content across the clinical enterprise requires adoption of a coherent standards-based model.  
  
 +
The typical workflow associated with this and similar types of multimedia content, assuming a defined workflow even exists, is typically heterogeneous across the clinical enterprise.  Imaging of this nature, not originated through a traditional EHR order system, is considered unsolicited and typically does not require a separate, dedicated image interpretation report for billing purposes.  Relevant image findings or descriptions thereof may instead be incorporated into the applicable progress or procedure notes within the EHR directly or through third-party applications.  Acquired image content is often stored locally by the provider, either on an in-office computer hard drive or local area network storage device, and most often is not readily available or searchable across the broader enterprise via the EHR or other systems.  Application of a more traditional, orders-based model to facilitate the integration of imaging content across the enterprise is not considered a logistically viable solution because of the intrinsically ad hoc nature of image acquisition in these settings (Cram, 2016).  Solutions including the use of order sets automatically created along with a scheduled encounter are not typically feasible due to the fact that it may not be known prior to the encounter what imaging, if any, will be needed. The use of discrete and specific image orders of appropriate granularity of metadata to enable meaningful search and retrieval would be required in order to correctly index the image content within the EHR with respect to image type, anatomic location, etc.  It would not be useful, for example, to have a photograph of a wound obtained to monitor healing if the patient has numerous other clinical photos indexed in their record simply as type:  “Clinical Photograph”.  More robust metadata descriptors could include “Clinical Photograph, Left Hand”, or “Digital Capture, Arthroscopic, Right Knee”, etc.  A robust granularity would be to also include designation of anatomic position (e.g., anterior vs. lateral).  The correct designation body part has been described as being likely the most important piece of metadata for enabling search and sorting across specialties, and a standard ontology for the purposes of body part mapping has been advocated (Towbin, 2016). To achieve interoperability, this data along with appropriate patient identifiers must be communicated to, or entered directly at the modality, reconciled with other patient identifiers that may be used elsewhere within the enterprise (typically by assignment of a unique Master Patient Identifier (MPI), and along with the acquired images be routed back to the EHR using an appropriate standards-based methods such as DICOM and HL7.
  
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== Enterprise Imaging, Defined
 
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==
 
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The Health Information Management Systems Society (HIMSS) and the Society for Imaging Informatics in Medicine (SIIM) have recently created a combined Enterprise Imaging Workgroup (Healthcare Information and Management Systems Society, 2016).  The stated mission of this workgroup includes providing “an effective point of connection for clinicians and IT professionals to engage in the advancement of enterprise imaging strategies” (Healthcare Information and Management Systems Society, 2014).  Enterprise Imaging has been defined by the workgroup as “a set of strategies, initiatives and workflows implemented across a healthcare enterprise to consistently and optimally capture, index, manage, store, distribute, view, exchange, and analyze all clinical imaging and multimedia content to enhance the electronic health record” (Roth,  2016a, Introduction section, para. 3). The availability of a complete longitudinal clinical record, including the incorporation of medical images along with diagnostic reports, saves physician time, increases confidence in deciding treatment plans, and sometimes alters management (Iyer, 2010).  The ability to directly view relevant clinical images can aid assessment of the patient’s current condition as well as changes over time (e.g., fracture healing, tumor size). The importance of developing an enterprise imaging strategy has been highlighted by inclusion as a criterion option for achieving Stage 2 of Meaningful Use (Centers for Medicare & Medicaid Services, 2012).  A series of white papers by the HIMSS-SIMM Enterprise Imaging workgroup, including issues of governance, infrastructure, implementation strategy, workflow, secure image exchange, EHR integration, and analytics is currently in press, scheduled for publication in the October 2016 issue of the Journal of Digital Imaging (Society for Imaging Informatics in Medicine, 2016). 
 
  
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== EHR Image Viewing Considerations ==
 +
The goal of a robust and successfully-implemented enterprise imaging system is the ability to access relevant image and multimedia content consolidated in logical fashion within the electronic health record in context with other clinical documentation at the point-of-care. The concept of an integrated image viewer within the EHR is not new; departmental PACS applications frequently include the ability to view DICOM images via hyperlink or similar method within an enabled thin-client-type viewer application.  This functionality was adequate for clinical review of standard-modality images in the context of a traditional order-based framework, but is unsuitable to serve the disparate need of clinicians seeking to view non-traditional and encounter-based multimedia content. This need can instead be met through inclusion of a multi-specialty “universal” enterprise viewer capable of displaying a broad range of content types.  The collaborative SIIM-HIMSS member workgroup on Enterprise Imaging defines an enterprise viewer as “a thin-client or zero-client application used on any off-the-shelf device to distribute, display, and manipulate multi-specialty image, video, audio, and scanned documents stored in separate centralized archives through, or standalone from, the EHR” (Roth,  2016c, Introduction section, para. 5).
  
  
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== Sources of Imaging Content
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== Characteristics of an Enterprise EHR Viewer ==
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==
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−
The acquisition and primary interpretation of medical images was historically considered the purview of radiology, with conventional film radiography representing the bulk of imaging procedures. The spectrum of available imaging studies has now exploded to include both contrast and non-contrast computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound (US), as well as the functional studies of nuclear medicine. Imaging is no longer isolated to the radiology department. Clinical providers from almost every discipline now frequently engage in some form of point-of-care imaging, including optical static or cine imaging obtained during endoscopic and arthroscopic procedures, and medical photography.
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−
 
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Governance
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This plethora of clinical imaging, although rich in information, is not necessarily obtained or stored in a format that would permit integration with or accessibility from the EHR.  Images are often taken on personal and/or mobile devices, stored insecurely, and non-indexed.  The technical infrastructure and workflow processes necessary to effectively manage this growing volume of multi-modality clinical content within the enterprise context and to share this information with outside entities do not yet exist in most institutions. Further, the culture within an organization may be such that a strong governance structure must be first implemented to manage and develop strategies for overcoming inherent interdepartmental personal and professional obstacles. The very nature of enterprise imaging necessitates a move away from the traditional departmental/silo model of imaging governance and into a more broad governance structure (Roth, 2016b). 
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Workflows for Image Acquisition and Management
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Orders-based (Scheduled) Workflow Model
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The traditional orders-based workflow model of clinical image acquisition begins with the referring physician placing an order for a specific imaging study to answer a particular clinical question (e.g., CT angiogram -- concern for pulmonary embolus).  This would be considered a solicited imaging request in the traditional model.  Once the order is received by the imaging department, either directly through the RIS from the EHR/HIS or entered manually in the case of a written order, a record is created and linked to the patient's demographic information.  This record is then transmitted to the imaging modality, typically using the DICOM Modality Worklist standard (Digital Imaging and Communications in Medicine, 2013). The DICOM Modality worklist (DMW) assigns a unique study accession number, and ensures both accurate and consistent communication of  patient /order metadata (e.g., name, birth date, exam type, body part/anatomic region, etc.), all linked to the assigned accession number, between the modality, EMR, RIS, and PACS (Gale,  2000).  At the imaging modality, the technologist retrieves the scheduled patient via the worklist and performs the requested examination.  The completed study, linked to the unique accession number and accompanying patient/order metadata, is sent to the PACS for nearline storage, viewing, and primary diagnostic interpretation.  This process is defined by the IHE (Integrating the Healthcare Enterprise) Scheduled Workflow (SWF) standard to ensure data consistency and availability between each step of the process (Figure 2).  Following diagnostic interpretation, the images are typically sent to an archive system, and the diagnostic report availability is transmitted back to the EHR via an HL7 message.  Clinicians can then view the textual report, and if desired can often click on an embedded hyperlink to view the complete study or selected images via an embedded viewer.  A key concept for traditional orders-based workflow is that the acquisition of clinical imaging is typically the sole intended purpose of the scheduled encounter.  For billing purposes, order-based workflows typically result in separate charges for technical (image acquisition) and professional (image interpretation) fees. 
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Figure 2: IHE Scheduled Workflow, from Integrating the Healthcare Enterprise.  (2013). Scheduled wWorkflow.  Retrieved August 30, 2016 from the IHE Wiki:  http://wiki.ihe.net/index.php/Sscheduled_wWorkflow.
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−
 
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Encounter-based Workflow Model
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−
Multimedia clinical content is being acquired with increasing frequency and volume by numerous specialties across the medical enterprise, outside the traditional domains of radiology.  While much of this imaging is currently obtained via the orders-based/SWF model using traditional modalities (e.g., the use of ultrasound by cardiology and OB/GYN), a growing volume of non-traditional “visible light” modality imaging is obtained by other specialties such as dermatology, ophthalmology, dentistry, and endoscopy. Imaging in these specialties is often obtained ad-hoc or incidentally during the clinical encounter within the context of a locally-defined workflow model, and is typically not the primary purpose for the visit (Cram, 2016).  The purpose of imaging by these specialties could be to complement the clinical visit or procedure, or to document relevant findings for follow-up and/or billing purposes. Example use cases would include visible-light photography of a suspicious lesion being examined in a primary care or dermatology clinic, bedside ultrasound (FAST scan) performed in the ER for trauma, or digital capture images of a suspicious lesion observed during an endoscopic procedure. Similar to the transition in radiology from film-based to digital storage, the digitization of pathology will enable review of the relevant images along with the diagnostic report within the EHR. Concerns have been raised, however, regarding the lack of a DICOM standard (Kalinski, 2012).  The ability to organize, index, store, secure, and retrieve this emerging content across the clinical enterprise requires adoption of a coherent standards-based model.   
+
−
The typical workflow associated with this and similar types of multimedia content, assuming a defined workflow even exists, is typically heterogeneous across the clinical enterprise.  Imaging of this nature, not originated through a traditional EHR order system, is considered unsolicited and typically does not require a separate, dedicated image interpretation report for billing purposes.  Relevant image findings or descriptions thereof may instead be incorporated into the applicable progress or procedure notes within the EHR directly or through third-party applications.  Acquired image content is often stored locally by the provider, either on an in-office computer hard drive or local area network storage device, and most often is not readily available or searchable across the broader enterprise via the EHR or other systems.  Application of a more traditional, orders-based model to facilitate the integration of imaging content across the enterprise is not considered a logistically viable solution because of the intrinsically ad hoc nature of image acquisition in these settings (Cram, 2016).  Solutions including the use of order sets automatically created along with a scheduled encounter are not typically feasible due to the fact that it may not be known prior to the encounter what imaging, if any, will be needed. The use of discrete and specific image orders of appropriate granularity of metadata to enable meaningful search and retrieval would be required in order to correctly index the image content within the EHR with respect to image type, anatomic location, etc.  It would not be useful, for example, to have a photograph of a wound obtained to monitor healing if the patient has numerous other clinical photos indexed in their record simply as type:  “Clinical Photograph”.  More robust metadata descriptors could include “Clinical Photograph, Left Hand”, or “Digital Capture, Arthroscopic, Right Knee”, etc.  A robust granularity would be to also include designation of anatomic position (e.g., anterior vs. lateral).  The correct designation body part has been described as being likely the most important piece of metadata for enabling search and sorting across specialties, and a standard ontology for the purposes of body part mapping has been advocated (Towbin, 2016). To achieve interoperability, this data along with appropriate patient identifiers must be communicated to, or entered directly at the modality, reconciled with other patient identifiers that may be used elsewhere within the enterprise (typically by assignment of a unique Master Patient Identifier (MPI), and along with the acquired images be routed back to the EHR using an appropriate standards-based methods such as DICOM and HL7.
+
−
EHR Image Viewing Considerations
+
−
The goal of a robust and successfully-implemented enterprise imaging system is the ability to access relevant image and multimedia content consolidated in logical fashion within the electronic health record in context with other clinical documentation at the point-of-care. The concept of an integrated image viewer within the EHR is not new; departmental PACS applications frequently include the ability to view DICOM images via hyperlink or similar method within an enabled thin-client-type viewer application.  This functionality was adequate for clinical review of standard-modality images in the context of a traditional order-based framework, but is unsuitable to serve the disparate need of clinicians seeking to view non-traditional and encounter-based multimedia content. This need can instead be met through inclusion of a multi-specialty “universal” enterprise viewer capable of displaying a broad range of content types.  The collaborative SIIM-HIMSS member workgroup on Enterprise Imaging defines an enterprise viewer as “a thin-client or zero-client application used on any off-the-shelf device to distribute, display, and manipulate multi-specialty image, video, audio, and scanned documents stored in separate centralized archives through, or standalone from, the EHR” (Roth,  2016c, Introduction section, para. 5).
+
−
Characteristics of an Enterprise EHR Viewer
+
 
Viewing of imaging-related content within the EHR including associated diagnostic reports is performed as part of daily inpatient and ambulatory clinical activity by multiple stakeholders throughout the enterprise, including physician and nursing staff,  physician extenders, technologists, and more recently patients.  Each user has their own need for image consumption, be it for diagnostic interpretation or clinical review, and a successful integrated viewing platform will provide access to a broad range of tools, interface options, and speed to enable the appropriate degree of interaction required to support the given use case.   
 
Viewing of imaging-related content within the EHR including associated diagnostic reports is performed as part of daily inpatient and ambulatory clinical activity by multiple stakeholders throughout the enterprise, including physician and nursing staff,  physician extenders, technologists, and more recently patients.  Each user has their own need for image consumption, be it for diagnostic interpretation or clinical review, and a successful integrated viewing platform will provide access to a broad range of tools, interface options, and speed to enable the appropriate degree of interaction required to support the given use case.   
 +
 
Given the limitations of EHR-integrated PACS thin-client, and other EHR viewing solutions, the alternative to a universal viewer may require support for multiple viewers specific to individual content types and associated integration profiles to allow interoperability with disparate departmental and/or specialty archives.  The implementation of an enterprise viewer, along with a scalable, consolidated VNA, allows simplification of network architecture and a single system through which the EHR must search to find relevant content (Oosterwijk, 2012).
 
Given the limitations of EHR-integrated PACS thin-client, and other EHR viewing solutions, the alternative to a universal viewer may require support for multiple viewers specific to individual content types and associated integration profiles to allow interoperability with disparate departmental and/or specialty archives.  The implementation of an enterprise viewer, along with a scalable, consolidated VNA, allows simplification of network architecture and a single system through which the EHR must search to find relevant content (Oosterwijk, 2012).
 +
 
The EHR is accessed on multiple device platforms, including desktop computers, laptops, tablets, and even smartphones (Khanna, 2016).  To facilitate speed of data transmission on mobile devices, modern enterprise viewers employ convert lossless DICOM objects into lossy or lossless non-DICOM formats (Roth, 2016c).  For the case of a file containing a large number of images, such as an echocardiogram or CT angiogram, speed of transmission is enhanced by conversion to a compressed/lossy format such as JPEG using discrete cosine transfer.  This method would be appropriate for non-diagnostic image review.  The alternative JPEG2000 format allows for either lossless (or reversible lossy) compression via an integer wavelet transform, and would be appropriate for diagnostic image review and/or streaming of large data sets (Branstetter, 2009).
 
The EHR is accessed on multiple device platforms, including desktop computers, laptops, tablets, and even smartphones (Khanna, 2016).  To facilitate speed of data transmission on mobile devices, modern enterprise viewers employ convert lossless DICOM objects into lossy or lossless non-DICOM formats (Roth, 2016c).  For the case of a file containing a large number of images, such as an echocardiogram or CT angiogram, speed of transmission is enhanced by conversion to a compressed/lossy format such as JPEG using discrete cosine transfer.  This method would be appropriate for non-diagnostic image review.  The alternative JPEG2000 format allows for either lossless (or reversible lossy) compression via an integer wavelet transform, and would be appropriate for diagnostic image review and/or streaming of large data sets (Branstetter, 2009).
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EHR Viewer Security
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== EHR Viewer Security ==
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An integrated EHR viewer will ideally launch within the context of a secure Uniform Resource Locator (URL) through an API (Application Programming Interface) at the imaging study level, thus becoming a seamless extension of the EHR.  Access would ideally be made through existing EHR authentication, permitting application of access controls and permissions appropriate to the individual user's role.  Security is enhanced if images are stripped of patient-identifying metadata, including conversion from DICOM to non-DICOM format if applicable, before being stored on the local device. Permissions may be required to access certain image content deemed to be “sensitive”, e.g., medical photography documentation of sexual or child abuse.  Similar to other EHR activities, the use of the image viewer would be subject to logging and the generation of audit records using the IHE Audit Trail and Node Authentication (ATNA) profile to ensure appropriate unionization and HIPPA compliance (Integrating the Healthcare Enterprise, 2015).
 
An integrated EHR viewer will ideally launch within the context of a secure Uniform Resource Locator (URL) through an API (Application Programming Interface) at the imaging study level, thus becoming a seamless extension of the EHR.  Access would ideally be made through existing EHR authentication, permitting application of access controls and permissions appropriate to the individual user's role.  Security is enhanced if images are stripped of patient-identifying metadata, including conversion from DICOM to non-DICOM format if applicable, before being stored on the local device. Permissions may be required to access certain image content deemed to be “sensitive”, e.g., medical photography documentation of sexual or child abuse.  Similar to other EHR activities, the use of the image viewer would be subject to logging and the generation of audit records using the IHE Audit Trail and Node Authentication (ATNA) profile to ensure appropriate unionization and HIPPA compliance (Integrating the Healthcare Enterprise, 2015).
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Conclusion
 
−
The adoption of a successful enterprise-imaging strategy will enable the more complete delivery of a longitudinal medical record by integrating a currently disparate wealth of non-traditional, typically non-DICOM clinical imaging to within reach of the EHR alongside more traditional DICOM imaging. An overview of the strategy has been provided, along with descriptions of required workflows, challenges, and technology considerations for metadata-rich content acquisition and enterprise viewing.  A significant development opportunity exists for improved workflow models, especially with respect to encounter-based imaging.  Consideration of enterprise imaging requirements should play a significant role during the continued development of EHR and image management/sharing systems, in order to advance the goals of the IHI Triple Aim and improve the overall delivery of quality healthcare services.
 
  
−
�References
+
 
 +
== References ==
 +
 
 
Bialecki, B., Park, J., Tilkin, M. (2016). Using object storage technology vs. vendor neutral archives for an image data repository infrastructure. J Digit Imaging. 29:460-465. doi:10.1007/s10278-016-9867-z
 
Bialecki, B., Park, J., Tilkin, M. (2016). Using object storage technology vs. vendor neutral archives for an image data repository infrastructure. J Digit Imaging. 29:460-465. doi:10.1007/s10278-016-9867-z
 
Branstetter, B.F., Ed. (2009). Practical imaging informatics. New York, NY: Springer, pp 136.  
 
Branstetter, B.F., Ed. (2009). Practical imaging informatics. New York, NY: Springer, pp 136.  

Revision as of 02:52, 30 April 2017

Background

The role of the EHR with respect to imaging services has historically been to function as an interface to the Radiology Information System (RIS) for study ordering and retrieval of results. More mature implementations typically provide additional but limited functionality to view images via hyperlink within an external PACS (Picture Archiving and Communications System) viewer. While this system has functioned relatively well to date with respect to traditional DICOM radiology imaging services obtained within the context of the local enterprise, a wealth of important and information-rich multimedia clinical imaging present both within and extrinsic to the enterprise is not typically accessible through most current EHR implementations. Such (typically non-DICOM) clinical content is routinely acquired at point-of-care in both the inpatient and outpatient settings by multiple disciplines. Examples include photographic images of a patient's skin cancer taken during an outpatient dermatology visit (imaging informatics), ophthalmic imaging of the retina, digitally-captured images and/or video during endoscopic or orthopedic procedures, and forensic imaging taken during evaluation of suspected sexual or child abuse cases. A standardized workflow for the acquisition, storage, indexing, retrieval, and security of this nontraditional content is typically not homogeneous across an enterprise, therefore limiting its availability within most current EMR systems. A model for Enterprise Imaging is emerging as a method to optimize the secure capture and storage of all relevant clinical imaging across the enterprise, and to facilitate the sharing of this content via an integrated EHR viewer.


Sources of Imaging Content

The acquisition and primary interpretation of medical images was historically considered the purview of radiology, with conventional film radiography representing the bulk of imaging procedures. The spectrum of available imaging studies has now exploded to include both contrast and non-contrast computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound (US), as well as the functional studies of nuclear medicine. Imaging is no longer isolated to the radiology department. Clinical providers from almost every discipline now frequently engage in some form of point-of-care imaging, including optical static or cine imaging obtained during endoscopic and arthroscopic procedures, and medical photography.


Workflow for Image Acquisition and Management

Multimedia clinical content is being acquired with increasing frequency and volume by numerous specialties across the medical enterprise, outside the traditional domains of radiology. While much of this imaging is currently obtained via the orders-based/SWF model using traditional modalities (e.g., the use of ultrasound by cardiology and OB/GYN), a growing volume of non-traditional “visible light” modality imaging is obtained by other specialties such as dermatology, ophthalmology, dentistry, and endoscopy. Imaging in these specialties is often obtained ad-hoc or incidentally during the clinical encounter within the context of a locally-defined workflow model, and is typically not the primary purpose for the visit (Cram, 2016). The purpose of imaging by these specialties could be to complement the clinical visit or procedure, or to document relevant findings for follow-up and/or billing purposes. Example use cases would include visible-light photography of a suspicious lesion being examined in a primary care or dermatology clinic, bedside ultrasound (FAST scan) performed in the ER for trauma, or digital capture images of a suspicious lesion observed during an endoscopic procedure. Similar to the transition in radiology from film-based to digital storage, the digitization of pathology will enable review of the relevant images along with the diagnostic report within the EHR. Concerns have been raised, however, regarding the lack of a DICOM standard (Kalinski, 2012). The ability to organize, index, store, secure, and retrieve this emerging content across the clinical enterprise requires adoption of a coherent standards-based model.

The typical workflow associated with this and similar types of multimedia content, assuming a defined workflow even exists, is typically heterogeneous across the clinical enterprise. Imaging of this nature, not originated through a traditional EHR order system, is considered unsolicited and typically does not require a separate, dedicated image interpretation report for billing purposes. Relevant image findings or descriptions thereof may instead be incorporated into the applicable progress or procedure notes within the EHR directly or through third-party applications. Acquired image content is often stored locally by the provider, either on an in-office computer hard drive or local area network storage device, and most often is not readily available or searchable across the broader enterprise via the EHR or other systems. Application of a more traditional, orders-based model to facilitate the integration of imaging content across the enterprise is not considered a logistically viable solution because of the intrinsically ad hoc nature of image acquisition in these settings (Cram, 2016). Solutions including the use of order sets automatically created along with a scheduled encounter are not typically feasible due to the fact that it may not be known prior to the encounter what imaging, if any, will be needed. The use of discrete and specific image orders of appropriate granularity of metadata to enable meaningful search and retrieval would be required in order to correctly index the image content within the EHR with respect to image type, anatomic location, etc. It would not be useful, for example, to have a photograph of a wound obtained to monitor healing if the patient has numerous other clinical photos indexed in their record simply as type: “Clinical Photograph”. More robust metadata descriptors could include “Clinical Photograph, Left Hand”, or “Digital Capture, Arthroscopic, Right Knee”, etc. A robust granularity would be to also include designation of anatomic position (e.g., anterior vs. lateral). The correct designation body part has been described as being likely the most important piece of metadata for enabling search and sorting across specialties, and a standard ontology for the purposes of body part mapping has been advocated (Towbin, 2016). To achieve interoperability, this data along with appropriate patient identifiers must be communicated to, or entered directly at the modality, reconciled with other patient identifiers that may be used elsewhere within the enterprise (typically by assignment of a unique Master Patient Identifier (MPI), and along with the acquired images be routed back to the EHR using an appropriate standards-based methods such as DICOM and HL7.


EHR Image Viewing Considerations

The goal of a robust and successfully-implemented enterprise imaging system is the ability to access relevant image and multimedia content consolidated in logical fashion within the electronic health record in context with other clinical documentation at the point-of-care. The concept of an integrated image viewer within the EHR is not new; departmental PACS applications frequently include the ability to view DICOM images via hyperlink or similar method within an enabled thin-client-type viewer application. This functionality was adequate for clinical review of standard-modality images in the context of a traditional order-based framework, but is unsuitable to serve the disparate need of clinicians seeking to view non-traditional and encounter-based multimedia content. This need can instead be met through inclusion of a multi-specialty “universal” enterprise viewer capable of displaying a broad range of content types. The collaborative SIIM-HIMSS member workgroup on Enterprise Imaging defines an enterprise viewer as “a thin-client or zero-client application used on any off-the-shelf device to distribute, display, and manipulate multi-specialty image, video, audio, and scanned documents stored in separate centralized archives through, or standalone from, the EHR” (Roth, 2016c, Introduction section, para. 5).


Characteristics of an Enterprise EHR Viewer

Viewing of imaging-related content within the EHR including associated diagnostic reports is performed as part of daily inpatient and ambulatory clinical activity by multiple stakeholders throughout the enterprise, including physician and nursing staff, physician extenders, technologists, and more recently patients. Each user has their own need for image consumption, be it for diagnostic interpretation or clinical review, and a successful integrated viewing platform will provide access to a broad range of tools, interface options, and speed to enable the appropriate degree of interaction required to support the given use case.

Given the limitations of EHR-integrated PACS thin-client, and other EHR viewing solutions, the alternative to a universal viewer may require support for multiple viewers specific to individual content types and associated integration profiles to allow interoperability with disparate departmental and/or specialty archives. The implementation of an enterprise viewer, along with a scalable, consolidated VNA, allows simplification of network architecture and a single system through which the EHR must search to find relevant content (Oosterwijk, 2012).

The EHR is accessed on multiple device platforms, including desktop computers, laptops, tablets, and even smartphones (Khanna, 2016). To facilitate speed of data transmission on mobile devices, modern enterprise viewers employ convert lossless DICOM objects into lossy or lossless non-DICOM formats (Roth, 2016c). For the case of a file containing a large number of images, such as an echocardiogram or CT angiogram, speed of transmission is enhanced by conversion to a compressed/lossy format such as JPEG using discrete cosine transfer. This method would be appropriate for non-diagnostic image review. The alternative JPEG2000 format allows for either lossless (or reversible lossy) compression via an integer wavelet transform, and would be appropriate for diagnostic image review and/or streaming of large data sets (Branstetter, 2009).


EHR Viewer Security

An integrated EHR viewer will ideally launch within the context of a secure Uniform Resource Locator (URL) through an API (Application Programming Interface) at the imaging study level, thus becoming a seamless extension of the EHR. Access would ideally be made through existing EHR authentication, permitting application of access controls and permissions appropriate to the individual user's role. Security is enhanced if images are stripped of patient-identifying metadata, including conversion from DICOM to non-DICOM format if applicable, before being stored on the local device. Permissions may be required to access certain image content deemed to be “sensitive”, e.g., medical photography documentation of sexual or child abuse. Similar to other EHR activities, the use of the image viewer would be subject to logging and the generation of audit records using the IHE Audit Trail and Node Authentication (ATNA) profile to ensure appropriate unionization and HIPPA compliance (Integrating the Healthcare Enterprise, 2015).


References

Bialecki, B., Park, J., Tilkin, M. (2016). Using object storage technology vs. vendor neutral archives for an image data repository infrastructure. J Digit Imaging. 29:460-465. doi:10.1007/s10278-016-9867-z Branstetter, B.F., Ed. (2009). Practical imaging informatics. New York, NY: Springer, pp 136. Centers for Medicare & Medicaid Services. (2012). Stage 2 Eligible Professional Meaningful Use, Menu Set Measures, Measure 3 of 6. Retrieved from https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/downloads/Stage2_EPMenu_3_ImagingResults.pdf. Cram, D., Roth, C.J., Towbin, A.J. (2016). Orders- versus encounters-based image capture: Implications pre- and post-procedure workflow, technical and build capabilities, resulting, analytics and revenue capture: HIMSS-SIIM Collaborative White Paper. J Digit Imaging. In press. doi:10.1007/s10278-016-9888-7 Digital Imaging and Communications in Medicine (DICOM). (2013). K.6 SOP class definitions. Retrieved from http://dicom.nema.org/dicom/2013/output/chtml/part04/sect_K.6.html. Gale, M.E., Gale, D.R. (2000). DICOM modality worklist: An essential component in a PACS environment. J Digit Imaging. 13(3):101-8. doi:10.1007/BF03168381 Healthcare Information and Management Systems Society (HIMSS). (2014). HIMSS-SIIM Joint Workgroup Charter [PDF]. Retrieved from http://s3.amazonaws.com/rdcms-himss/files/production/public/FileDownloads/HIMSS%20-%20SIIM%20Workgroup%20Charter.pdf. Healthcare Information and Management Systems Society (HIMSS). (2016). Enterprise Imaging. Retrieved August 30, 2016, from http://www.himss.org/library/clinical-informatics/enterprise-imaging. Institute for Healthcare Improvement. (2016). The IHI triple aim. Retrieved from http://www.ihi.org/engage/initiatives/tripleaim/pages/default.aspx. Integrating the Healthcare Enterprise. (2015). Audit trail and node authentication. Retrieved from the IHE Wiki: http://wiki.ihe.net/index.php/audit_trail_and_node_authentication. Integrating the Healthcare Enterprise. (2013). Scheduled workflow. Retrieved from the IHE Wiki: http://wiki.ihe.net/index.php/scheduled_workflow. Iyer, V.R., Hahn P.F., Blaszkowsky, L.S., Thayer S.P., Halpern E.F., Harisinghani M.G. (2010). Added value of selected images embedded into radiology reports to referring clinicians. J Am Coll Radiol. 7(3):205-10. doi: 10.1016/j.jacr.2009.10.014 Kalinski, T., Zwönitzer, R., Roßner, M., Hofmann, H., Roessner, A., Guenther, T. (2012). Digital imaging and communications in medicine (DICOM) as standard in digital pathology. Histopathology, 61: 132–134. doi:10.1111/j.1365-2559.2012.04243.x Khanna, R.R., Wachter, R.M., Blum, M. (2016). Reimagining Electronic Clinical Communication in the Post-Pager, Smartphone Era. JAMA. 315(1):21-22. doi:10.1001/jama.2015.17025 Oosterwijk, H. (2012). What Is a VNA, Anyway? [PDF]. Available at http://otechimg.com/publications/pdf/What_is_a_VNA_anyway.pdf. Roth, C.J., Lannum, L.M., Persons, K.R. (2016a). A Foundation for Enterprise Imaging: HIMSS-SIIM Collaborative White Paper. J Digit Imaging. doi:10.1007/s10278-016-9882-0 Roth, C.J., Lannum, L.M., Dennison, D.K., et al. (2016b). The Current State and Path Forward For Enterprise Image Viewing: HIMSS-SIIM Collaborative White Paper. J Digit Imaging. doi:10.1007/s10278-016-9887-8 Roth, C.J., Lannum, L.M., Joseph, C.L. (2016c). Enterprise Imaging Governance: HIMSS-SIIM Collaborative White Paper. J Digit Imaging. doi:10.1007/s10278-016-9883-z Society for Imaging Informatics in Medicine (SIIM). (2016). HIMSS-SIIM Enterprise Imaging Workgroup Collaborative White Papers. Retrieved from http://siim.org/page/himss_siim_white_pap. Towbin, A.J., Roth, C.J., Bronkalla, M., Cram, D. (2016). Workflow Challenges of Enterprise Imaging: HIMSS-SIIM Collaborative White Paper. J Digit Imaging. doi:10.1007/s10278-016-9897

Submitted by (Erik S. Storm, DO)

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