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Roth CJ, Petersilge CA, Cram D, Garriott K, Lannum L, Carey CK, Medina N, Kwiatkoski T, Whitfill JT, Towbin AJ. Celebrating 10 Years of the HIMSS-SIIM Enterprise Imaging Community and Enterprise Imaging Informatics. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024:10.1007/s10278-024-01141-7. [PMID: 38858262 DOI: 10.1007/s10278-024-01141-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 05/06/2024] [Accepted: 05/07/2024] [Indexed: 06/12/2024]
Abstract
In response to the growing recognition of enterprise imaging as a critical component of healthcare's digital transformation, in 2014, the Healthcare Information and Management Systems Society (HIMSS) and the Society for Imaging Informatics in Medicine (SIIM) signed a Memorandum of Understanding to form the HIMSS-SIIM Enterprise Imaging Community (HSEIC). At the time of the agreement, the two organizations decided to collaborate to lead enterprise imaging development, advancement, and adoption. This paper celebrates the past 10 years of the HSEIC's thought leadership, industry partnerships, and impact while also looking ahead to identify enterprise imaging challenges to solve in the next decade.
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Affiliation(s)
| | - Cheryl A Petersilge
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- , Vidagos, Chagrin Falls, OH, USA
| | - Dawn Cram
- Department of Research and Development, PaxeraHealth, Newton, MA, USA
| | | | - Lou Lannum
- , Lannum & Associates, Cleveland, OH, USA
| | - Cheryl K Carey
- Society for Imaging Informatics in Medicine, Leesburg, VA, USA
| | - Nikki Medina
- Society for Imaging Informatics in Medicine, Leesburg, VA, USA
| | - Tammy Kwiatkoski
- Healthcare Information and Management Systems Society, Chicago, IL, USA
| | - James T Whitfill
- HonorHealth, Scottsdale, AZ, USA
- University of Arizona College of Medicine - Phoenix, Phoenix, AZ, USA
| | - Alexander J Towbin
- Department of Radiology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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Roth CJ, Petersilge C, Clunie D, Towbin AJ, Cram D, Primo R, Li X, Berkowitz SJ, Barnosky V, Krupinski EA. HIMSS-SIIM Enterprise Imaging Community White Papers: Reflections and Future Directions. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024; 37:429-443. [PMID: 38336948 PMCID: PMC11031499 DOI: 10.1007/s10278-024-00992-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/23/2024] [Indexed: 02/12/2024]
Affiliation(s)
| | - Cheryl Petersilge
- Vidagos University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | | | - Alexander J Towbin
- Department of Radiology, Cincinnati Children's Hospital, Cincinnati, OH, USA.
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
| | - Dawn Cram
- PaxeraHealth, 85 Wells Ave Suite 120, Newton, MA, 02459, USA
| | - Rik Primo
- Primo Medical Imaging Informatics Inc, Chicago, IL, USA
| | - Xin Li
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Seth J Berkowitz
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, 02115, USA
| | - Victoria Barnosky
- Robert Morris University, Moon Township, Suazio, Philadelphia, PA, USA
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Dhamija A, Perry LA, OConnor TJ, Ulland L, Slavik E, Towbin AJ. Development and Implementation of a Semi-Automated Workflow for Point-of-Care Ultrasound Billing and Documentation Within an Electronic Health Record. J Digit Imaging 2023; 36:395-400. [PMID: 36385677 PMCID: PMC10039213 DOI: 10.1007/s10278-022-00742-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 11/09/2022] [Accepted: 11/09/2022] [Indexed: 11/17/2022] Open
Abstract
Point-of-care ultrasound (POCUS) is widely used for both diagnostic and therapeutic purposes. With its many advantages, including ease of use, real-time multisystem assessment, affordability, availability, and accuracy, it has been adopted by all medical specialties. Despite its advantages, the lack of standard workflow and automated billing solutions makes it difficult to launch a comprehensive POCUS program. In this work, we describe how we created and implemented an efficient standardized EHR-based workflow for POCUS that has been used across multiple division and settings within our organization.
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Affiliation(s)
- Akhil Dhamija
- Department of Radiology, Cincinnati Children's Hospital, Cincinnati, OH, USA
- Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Laurie A Perry
- Department of Radiology, Cincinnati Children's Hospital, Cincinnati, OH, USA
| | - Timothy J OConnor
- Department of Radiology, Cincinnati Children's Hospital, Cincinnati, OH, USA
| | - Lisa Ulland
- Department of Radiology, Cincinnati Children's Hospital, Cincinnati, OH, USA
| | - Evan Slavik
- Department of Radiology, Cincinnati Children's Hospital, Cincinnati, OH, USA
| | - Alexander J Towbin
- Department of Radiology, Cincinnati Children's Hospital, Cincinnati, OH, USA.
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
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Abstract
As resources in the healthcare environment continue to wane, leaders are seeking ways to continue to provide quality care bounded by the constraints of a reduced budget. This manuscript synthesizes the experience from a number of institutions to provide the healthcare leadership with an understanding of the value of an enterprise imaging program. The value of such a program extends across the entire health system. It leads to operational efficiencies through infrastructure and application consolidation and the creation of focused support capabilities with increased depth of skill. An enterprise imaging program provides a centralized foundation for all phases of image management from every image-producing specialty. Through centralization, standardized image exchange functions can be provided to all image producers. Telehealth services can be more tightly integrated into the electronic medical record. Mobile platforms can be utilized for image viewing and sharing by patients and providers. Mobile tools can also be utilized for image upload directly into the centralized image repository. Governance and data standards are more easily distributed, setting the stage for artificial intelligence and data analytics. Increased exposure to all image producers provides opportunities for cybersecurity optimization and increased awareness.
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Persons KR, Nagels J, Carr C, Mendelson DS, Primo H“R, Fischer B, Doyle M. Interoperability and Considerations for Standards-Based Exchange of Medical Images: HIMSS-SIIM Collaborative White Paper. J Digit Imaging 2021; 33:6-16. [PMID: 31768898 PMCID: PMC7064628 DOI: 10.1007/s10278-019-00294-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
This white paper explores the considerations of standards-based interoperability of medical images between organizations, patients, and providers. In this paper, we will look at three different standards-based image exchange implementations that have been deployed to facilitate exchange of images between provider organizations. The paper will describe how each implementation uses applicable technology and standards; the image types that are included; and the governance policies that define participation, access, and trust. Limitations of the solution or non-standard approaches to solve challenges will also be identified. Much can be learned from successes elsewhere, and those learnings will point to recommendations of best practices to facilitate the adoption of image exchange.
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Affiliation(s)
| | - Jason Nagels
- Manager Clinical Program at HDIRS, Ontario, Canada
| | - Chris Carr
- Director of Informatics at RSNA, Chicago, IL USA
| | | | | | - Bernd Fischer
- ITH Icoserve Technology for Healthcare GmbH, Innsbruck, Austria
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McCarthy N, Dahlan A, Cook TS, Hare NO, Ryan ML, St John B, Lawlor A, Curran KM. Enterprise imaging and big data: A review from a medical physics perspective. Phys Med 2021; 83:206-220. [DOI: 10.1016/j.ejmp.2021.04.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 03/24/2021] [Accepted: 04/06/2021] [Indexed: 02/04/2023] Open
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Primo H, Bishop M, Lannum L, Cram D, Nader A, Boodoo R. 10 Steps to Strategically Build and Implement your Enterprise Imaging System: HIMSS-SIIM Collaborative White Paper. J Digit Imaging 2020; 32:535-543. [PMID: 31177360 PMCID: PMC6646642 DOI: 10.1007/s10278-019-00236-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
An enterprise imaging (EI) strategy is an organized plan to optimize the electronic health record (EHR) so that healthcare providers have intuitive and immediate access to all patient clinical images and their associated documentation, regardless of source. We describe ten steps recommended to achieve the goal of implementing EI for an institution. The first step is to define and access all images used for medical decision-making. Next, demonstrate how EI is a powerful strategy for enhancing patient and caregiver experience, improving population health, and reducing cost. Then, it is recommended that one must understand the specialties and their clinical workflow challenges as related to imaging. Step four is to create a strategy to improve quality of care and patient safety with EI. Step five demonstrates how EI can reduce costs. Then, show how EI can help enhance the patient experience. Step seven suggests how EI can enhance the work life of caregivers and step eight describes how to develop EI governance. Step nine describes the plan to implement an EI project, and finally, step 10, to understand cybersecurity from a patient safety perspective and to protect images from accidental and malicious intrusion.
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Affiliation(s)
- Henri Primo
- Primo Medical Imaging Informatics, Inc, Chicago, IL 60646 USA
| | | | | | - Dawn Cram
- The Gordian Knot Group, LLC, Fort Lauderdale, FL USA
| | - Abe Nader
- Medical Imaging & Medical Imaging Informatics, Inova Health System, Falls Church, VA USA
| | - Roger Boodoo
- Diagnosis Protocol & Clinical Informatics Fellow, University of Illinois Hospital and Health Sciences System, Chicago, IL 60612 USA
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Kayhart D. Using an Existing DICOM Infrastructure to Enhance the Availability, Quality, and Efficiency of Imaging Throughout the Healthcare Enterprise. J Digit Imaging 2020; 32:75-80. [PMID: 30187314 PMCID: PMC6382629 DOI: 10.1007/s10278-018-0118-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Managing the capture, label, and storage of medical imaging performed by nonradiology departments at the point of care has become a core issue for many health systems. In contrast to the well-organized and controlled workflows enjoyed by radiology, nonradiology imaging and its associated workflows are often chaotic. Left on their own, many nonradiology departments simply fend for themselves, finding ways to capture and store their imaging that meets the critical need, while falling far short of the ideal. The focus of this study was to build and implement a software solution for nonradiology image management for a large, multi-specialty health system. Once developed, the solution was deployed and results were collected from users via survey and by comparison of available pre- and post-implementation statistics. The results show high rates of satisfaction among users, evidence of cost savings from decommissioning redundant systems, staff time savings, and fewer storage failures.
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Affiliation(s)
- Dan Kayhart
- Marshfield Clinic Health System, 1000 North Oak Ave, Marshfield, WI, 54449, USA.
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10
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Pantanowitz L, Sharma A, Carter AB, Kurc T, Sussman A, Saltz J. Twenty Years of Digital Pathology: An Overview of the Road Travelled, What is on the Horizon, and the Emergence of Vendor-Neutral Archives. J Pathol Inform 2018; 9:40. [PMID: 30607307 PMCID: PMC6289005 DOI: 10.4103/jpi.jpi_69_18] [Citation(s) in RCA: 108] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 10/28/2018] [Indexed: 12/13/2022] Open
Abstract
Almost 20 years have passed since the commercial introduction of whole-slide imaging (WSI) scanners. During this time, the creation of various WSI devices with the ability to digitize an entire glass slide has transformed the field of pathology. Parallel advances in computational technology and storage have permitted rapid processing of large-scale WSI datasets. This article provides an overview of important past and present efforts related to WSI. An account of how the virtual microscope evolved from the need to visualize and manage satellite data for earth science applications is provided. The article also discusses important milestones beginning from the first WSI scanner designed by Bacus to the Food and Drug Administration approval of the first digital pathology system for primary diagnosis in surgical pathology. As pathology laboratories commit to going fully digitalize, the need has emerged to include WSIs into an enterprise-level vendor-neutral archive (VNA). The different types of VNAs available are reviewed as well as how best to implement them and how pathology can benefit from participating in this effort. Differences between traditional image algorithms that extract pixel-, object-, and semantic-level features versus deep learning methods are highlighted. The need for large-scale data management, analysis, and visualization in computational pathology is also addressed.
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Affiliation(s)
- Liron Pantanowitz
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Ashish Sharma
- Department of Biomedical Informatics, Emory University, GA, USA
| | - Alexis B. Carter
- Department of Pathology and Laboratory Medicine, Children's Healthcare of Atlanta, GA, USA
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA
| | - Alan Sussman
- Department of Computer Science, University of Maryland, College Park, MD, USA
| | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA
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Herrmann MD, Clunie DA, Fedorov A, Doyle SW, Pieper S, Klepeis V, Le LP, Mutter GL, Milstone DS, Schultz TJ, Kikinis R, Kotecha GK, Hwang DH, Andriole KP, Iafrate AJ, Brink JA, Boland GW, Dreyer KJ, Michalski M, Golden JA, Louis DN, Lennerz JK. Implementing the DICOM Standard for Digital Pathology. J Pathol Inform 2018; 9:37. [PMID: 30533276 PMCID: PMC6236926 DOI: 10.4103/jpi.jpi_42_18] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 08/06/2018] [Indexed: 11/29/2022] Open
Abstract
Background: Digital Imaging and Communications in Medicine (DICOM®) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been defined; however, adoption by vendors and in the field is pending. Here, we implemented the essential aspects of the standard and assessed its capabilities and limitations in a multisite, multivendor healthcare network. Methods: We selected relevant DICOM attributes, developed a program that extracts pixel data and pixel-related metadata, integrated patient and specimen-related metadata, populated and encoded DICOM attributes, and stored DICOM files. We generated the files using image data from four vendor-specific image file formats and clinical metadata from two departments with different laboratory information systems. We validated the generated DICOM files using recognized DICOM validation tools and measured encoding, storage, and access efficiency for three image compression methods. Finally, we evaluated storing, querying, and retrieving data over the web using existing DICOM archive software. Results: Whole slide image data can be encoded together with relevant patient and specimen-related metadata as DICOM objects. These objects can be accessed efficiently from files or through RESTful web services using existing software implementations. Performance measurements show that the choice of image compression method has a major impact on data access efficiency. For lossy compression, JPEG achieves the fastest compression/decompression rates. For lossless compression, JPEG-LS significantly outperforms JPEG 2000 with respect to data encoding and decoding speed. Conclusion: Implementation of DICOM allows efficient access to image data as well as associated metadata. By leveraging a wealth of existing infrastructure solutions, the use of DICOM facilitates enterprise integration and data exchange for digital pathology.
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Affiliation(s)
| | | | - Andriy Fedorov
- Department of Radiology, Surgical Planning Laboratory, Brigham and Women's Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Sean W Doyle
- MGH and BWH Center for Clinical Data Science, Boston, MA, USA
| | | | - Veronica Klepeis
- Harvard Medical School, Boston, MA, USA.,Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | - Long P Le
- Harvard Medical School, Boston, MA, USA.,Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | - George L Mutter
- Harvard Medical School, Boston, MA, USA.,Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - David S Milstone
- Harvard Medical School, Boston, MA, USA.,Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - Thomas J Schultz
- Enterprise Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Ron Kikinis
- Department of Radiology, Surgical Planning Laboratory, Brigham and Women's Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Gopal K Kotecha
- MGH and BWH Center for Clinical Data Science, Boston, MA, USA
| | - David H Hwang
- Harvard Medical School, Boston, MA, USA.,Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - Katherine P Andriole
- MGH and BWH Center for Clinical Data Science, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA.,Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| | - A John Iafrate
- Harvard Medical School, Boston, MA, USA.,Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | - James A Brink
- Harvard Medical School, Boston, MA, USA.,Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Giles W Boland
- Harvard Medical School, Boston, MA, USA.,Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| | - Keith J Dreyer
- MGH and BWH Center for Clinical Data Science, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA.,Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Mark Michalski
- MGH and BWH Center for Clinical Data Science, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA.,Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Jeffrey A Golden
- Harvard Medical School, Boston, MA, USA.,Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - David N Louis
- Harvard Medical School, Boston, MA, USA.,Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | - Jochen K Lennerz
- Harvard Medical School, Boston, MA, USA.,Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
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The Current State and Path Forward For Enterprise Image Viewing: HIMSS-SIIM Collaborative White Paper. J Digit Imaging 2018; 29:567-73. [PMID: 27473474 PMCID: PMC5023528 DOI: 10.1007/s10278-016-9887-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Clinical specialties have widely varied needs for diagnostic image interpretation, and clinical image and video image consumption. Enterprise viewers are being deployed as part of electronic health record implementations to present the broad spectrum of clinical imaging and multimedia content created in routine medical practice today. This white paper will describe the enterprise viewer use cases, drivers of recent growth, technical considerations, functionality differences between enterprise and specialty viewers, and likely future states. This white paper is aimed at CMIOs and CIOs interested in optimizing the image-enablement of their electronic health record or those who may be struggling with the many clinical image viewers their enterprises may employ today.
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Abstract
Care providers today routinely obtain valuable clinical multimedia with mobile devices, scope cameras, ultrasound, and many other modalities at the point of care. Image capture and storage workflows may be heterogeneous across an enterprise, and as a result, they often are not well incorporated in the electronic health record. Enterprise Imaging refers to 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. This paper is intended to introduce Enterprise Imaging as an important initiative to clinical and informatics leadership, and outline its key elements of governance, strategy, infrastructure, common multimedia content, acquisition workflows, enterprise image viewers, and image exchange services.
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Clunie DA, Dennison DK, Cram D, Persons KR, Bronkalla MD, Primo HR. Technical Challenges of Enterprise Imaging: HIMSS-SIIM Collaborative White Paper. J Digit Imaging 2016; 29:583-614. [PMID: 27576909 PMCID: PMC5023533 DOI: 10.1007/s10278-016-9899-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Abstract
This white paper explores the technical challenges and solutions for acquiring (capturing) and managing enterprise images, particularly those involving visible light applications. The types of acquisition devices used for various general-purpose photography and specialized applications including dermatology, endoscopy, and anatomic pathology are reviewed. The formats and standards used, and the associated metadata requirements and communication protocols for transfer and workflow are considered. Particular emphasis is placed on the importance of metadata capture in both order- and encounter-based workflow. The benefits of using DICOM to provide a standard means of recording and accessing both metadata and image and video data are considered, as is the role of IHE and FHIR.
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Affiliation(s)
- David A Clunie
- Pixelmed Publishing LLC., 943 Heiden Rd, Bangor, PA, 18013, USA.
| | - Don K Dennison
- Don K Dennison Solutions Inc., 205 Fern Cres, Waterloo, ON, N2V 2P9, Canada
| | - Dawn Cram
- Department of Information Technology, University of Miami Health System, Miami, FL, 33136, USA
| | - Kenneth R Persons
- Mayo Clinic and Foundation, 200 First St. SW, Pb 2-58, Rochester, MN, 55905, USA
| | - Mark D Bronkalla
- Merge Healthcare, 900 Walnut Ridge Drive, Hartland, WI, 53029, USA
| | - Henri Rik Primo
- Digital Health Services, Siemens Healthineers, 65 Valley Stream Parkway, Malvern, PA, 19355, USA
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