Lecture A offers a definition of patient monitoring systems, describes the purpose, attributes, and functions of patient monitoring systems, discusses the primary applications and how automation can improve quality of care, and analyzes how the integration of data from many sources assists in medical decision making. Lecture B discusses how telehealth communication technologies support clinical care, explains the effectiveness and economic benefit of telehealth, and examines the role smart technology in the home and remote links to health information systems play in enhancing the quality of patient care.
Welcome to Health Management Information Systems, Medical Imaging Systems.
The component, Health Management Information Systems, is a “theory” component that provides an introduction to health care applications and the systems that use them, health information technology standards, health-related data structures, and enterprise architecture in health care organizations.
Lecture a offers a definition of medical imaging, describes the purpose, processes, and management issues of medical imaging systems, analyzes the economic and technological factors that must be considered in the adoption of digital displays in radiology departments, looks at the major challenges with imaging systems faced by health care institutions and informaticians, and examines the future directions for imaging systems.
The Objectives for this unit, Medical Imaging Systems, are to:
- Examine the purposes, processes, and management issues related to the use of imaging systems in health care;
- Understand the economic and technological factors that must be considered in the adoption of digital displays in radiology departments;
- Describe the major challenges with imaging systems faced by health care institutions and informaticians; and
- Describe the future directions for imaging systems.
Before the purposes, processes, and management issues related to the use of imaging systems in health care are addressed, several terms will be defined. The first one is biomedical imaging from the National Library of Medicine (NLM).
The NLM (2004) defines biomedical imaging as “The science and the branch of medicine concerned with the development and use of imaging devices and techniques to obtain internal anatomic images and to provide biochemical and physiological analysis of tissues and organs” (para. 1).
Biomedical imaging includes technologies that capture, store, analyze and display at the organ, tissue, cellular, and molecular level using techniques such as computed tomography (CT), magnetic resonance imaging (MRI), interventional radiology, positron emission tomography (PET), single photon emission coherence tomography (SPECT), ultrasound imaging, and optical coherence tomography (OCT).
The next term that will be defined is medical imaging. According to NLM, medical imaging is “Any visual display of structural or functional patterns of organs or tissues for diagnostic evaluation. It includes measuring physiologic and metabolic responses to physical and chemical stimuli, as well as ultramicroscopy” (NLM, 2012, para. 4).
While radiology is often what comes to mind when medical imaging is mentioned, it is not limited to radiology. Other areas such as pathology, gastroenterology, and cardiology also fall under medical imaging.
The Society for Imaging Informatics in Medicine (SIIM) provides the following definition from Andriole (2006), “Medical imaging informatics is a relatively new multidisciplinary field that intersects with the biological sciences, health services, information sciences, medical physics, and engineering. Imaging informatics touches every aspect of the imaging chain from image creation and acquisition, to image distribution and management, to image storage and retrieval, to image processing, analysis and understanding, to image visualization and data navigation; to image interpretation, reporting, and communications. The field serves as the integrative catalyst for these processes and forms a bridge with imaging and other medical disciplines” (para 1-2).
An example of imaging informatics applications is a computerized axial tomography (CAT) scanner, which uses software algorithms to recreate a three-dimensional image of the body parts. Another example would be Picture Archiving and Communication System (PACS) which are a combination of hardware and software dedicated to the short and long term storage, retrieval, management, distribution, and presentation of images.
With an understanding of the various terms, let’s next examine the purposes related to the use of imaging systems in health care. According to Greenes and Brinkley (2006), “Imaging is a central part of the healthcare process for diagnosis, treatment planning, image-guided treatment, assessment or response to treatment, and estimation of prognosis. In addition, it plays important roles in medical communication and education, as well as research” (p. 627).
For example, imaging systems:
- Improve access to the studies. Remote viewing is possible and thereby expediting diagnosis and treatment.
- Enhance image communication. Images can be viewed by multiple clinicians at different locations.
- Decrease the amount of time it takes to provide a report back to an ordering physician. Images can be retrieved, interpreted, and a report back to the ordering physician expedited.
The purposes outlined in the last slide related to the use of imaging systems in health care are compelling. But what are the processes associated with the use of imaging systems in health care? Basically the three which cover Andriole’s “image chain” are:
- Acquisition and management of the digitized images would include image creation and acquisition, to image distribution and management, to image storage and retrieval.
- Image processing, analysis and understanding, to image visualization and data navigation, to image interpretation are a part of the interpretation of the images process.
- Image reporting and communication are pieces to the communication of the interpretations process.
The next slide shows a Picture Archiving and Communication System or PACS configuration that shows the processes.
According to Ralston & Coleman, (2010), “A Picture Archiving and Communication System stores, distributes, and displays medical images for interpretation or review” (p. 34).
As explained by Bhachu (2005), “a Picture Archiving and Communications System (PACS) data network is a computer network system designed to transfer, store and retrieve digital medical images for viewing at the right place, and at the right time. It integrates data from system to system, inside and outside healthcare departments, and ensures that images and image-related data are made available as needed at the point of care” (para. 5).
This image is an example of a facility-wide PACS configuration. At the center is the archiving and communication system (PACS) server. Digital acquisition devices, such as ultrasound (US), computed tomography (CT), mammography (mammo), are sent to the server. An electronic medical record (EMR) also supplies information to the server. The output from the server is to storage devices, and to reading stations, or to the Internet, where access is made available via a web browser to remote locations.
Bhachu (2005) notes, “The PACS data network should provide a seamlessly-integrated information management infrastructure within the department and the enterprise to improve care, service and productivity, while enhancing the quality of the work environment in a secure and reliable manner” (para. 7).
The transmission of data about a medical image from acquisition devices to storage devices requires a messaging format. Digital Imaging and Communications in Medicine (DICOM) is a standard for the electronic exchange of medical images and the data associated with the images. According to National Electrical Manufacturers Association (n.d.), “DICOM is a global information technology standard that is used in virtually all hospitals worldwide. Its current structure… is designed to ensure the interoperability of systems used to: produce, store, display, process, send, retrieve, query or print medical images and derived structured documents as well as to manage related workflow” (para. 1). DICOM defines both the file content and communication protocol.
Another communication standard format comes from Health Level Seven International, or HL7. According to HL7’s web site, HL7 is “an ANSI-accredited standards developing organization dedicated to providing a comprehensive framework and related standards for the exchange, integration, sharing, and retrieval of electronic health information that supports clinical practice and the management, delivery and evaluation of health services” (HL7, 2011, para. 1).
Message standards associated with patient demographic and exam ordering information, result reporting, and billing are addressed by HL7.
The Hospital Information System (HIS) and Radiology Information System (RIS) use HL7 while the PACS use DICOM. Both DICOM and HL7 support the integration among systems, which is discussed later on in this lecture.
There are a number of management issues that will need to be addressed with regards to imaging systems.
The first issue is storage. Managing the storage and retrieval of digital images involves on-line digital archiving, retrieval of images via the image databases, and transmission of images over communication networks. Once the image has been interpreted, it will need to be stored or electronically archived. While the industry is moving to digital images, film may still be in use. Storage of film involves file space. Film also requires material resources such as film and its jacket, along with staff resources to prepare it for storage, as well as to retrieve it when needed. For digital images the process changes so the identified film issues are eliminated or reduced. For example, as soon as image quality is verified, it can be sent immediately to an electronic archive thereby eliminating the need for shelved film storage.
According to Greenes and Brinkley (2006) “Image modalities differ substantially in their storage requirements, depending on the contrast and spatial resolution needed, the number of images or the size of the data sets, whether raw or processed data are stored, and whether data-compression techniques are used” (p. 634).
Also mentioned by Greenes and Brinkley (2006) is the need for the image archiving system to be able to manage not only on-line maintenance of active images, but must be able to store older image data. They suggest establishing “hierarchies of storage” to address concerns with speed of access. This would involve setting up a process that takes into account higher access mediums, such as a local workstation to storage on slower access mediums such as an optical disk. Greenes and Brinkley (2006) note the need to decide where to place image data based on patterns of expected use, and network traffic, when putting the plan together.
Another way to address storage issues would be with data compression. Krupinski (2010) noted “Compression reduces the volume of data to reduce image processing, transmission times, bandwidth requirements, and storage needs” (p. 106).
In addition to storage concerns, another management issue is image integration. Integration involves viewing stations, image databases, image management systems, and networks. Greenes and Brinkley (2006) state “The network configuration and the capacity of each part must be planned in relation to considerations such as patterns of expected use and cost” (p. 637).
Image transmission times would be different given choice of network method and degree of compression (Greenes and Brinkley, 2006).
Because of their own distinctive management issues, viewing station factors will be examined further on the next slide.
Image integration with other health care information is addressed later under major challenges.
Setting up workstations where radiologists will view and interpret digital images and referring clinicians will review the interpreted images pose their own unique management challenges. First, technological factors associated with digital displays will be discussed. Greenes and Brinkley (2006) point out that radiologist viewing consoles for image interpretation need to support general image manipulation operations and other operations that the radiologist performs while analyzing images. They stress “the ability to reshuffle images, to shift attention, to zoom in on a specific area, and to step back again to get an overview are all essential to the interpretive and analytic processes” and go on to further state “the design of practical image-interpretation workstations thus requires considerable human engineering and experimentation” (Greenes and Brinkley, 2006, p. 639, 641).
For referring clinicians, Greenes and Brinkley (2006) indicate their workstation “must be easily accessible and thus must be conveniently distributed throughout the institution, or throughout an extended integrated delivery network” (p. 641).
Regarding economic factors, Greenes and Brinkley (2006) make note of the fact that “costs for the network infrastructure and for image acquisition, storage, and review can be shared by the entire healthcare system rather than falling exclusively to radiology departments” (p. 641).
Just having a medical image is not of much benefit if it is not accessible for use by various applications. The ability to have an efficient image distribution and access process is dependent on the successful integration of multiple information systems. Connectivity, or integrating medical images with information systems, such as the hospital information system, is a major challenge for health care institutions and informaticians.
AHIMA defines hospital information system as “The comprehensive database containing all the clinical, administrative, financial, and demographic information about each patient served by a hospital” (AHIMA, 2012, p. 171). The HIS plays an integral part in providing the data about the patient such as what is captured at registration which helps maintain data consistency.
The Radiology Information System (RIS) is not the same as the HIS. RIS is one of the most recognizable components of a medical imaging system. The RIS is used by a radiology department to support the radiology department’s information needs by managing workflow of such things as maintaining the film library and digital archive, scheduling of patient examinations, registering of patients, distributing reports, and billing. According to Branstetter (2010), an RIS “Can receive orders from the Hospital Information System, or allow manual input of orders locally” (p. 438).
Greenes and Brinkley (2006), make note that “RISs have been implemented either as standalone systems or as components of HISs. In either case, an RIS must be integrated with other information systems within an institution to allow reconciliation of patient data, to support examination scheduling and results reporting, and to facilitate patient billing” (p. 643).
Medical imaging systems are likely to have their own informatics support, separate from that of hospital information systems which makes integration more difficult.
PACS is the other most recognizable component of a medical imaging system. As you will recall from previous material in this lecture, PACS deals with storage and communication of medical images. Integration is necessary between the components of the medical imaging system and HIS for PACS implementation to be successful. As Greenes and Brinkley (2006) explained, “Picture-archiving and communication system (PACS) image-management functions must be integrated with RISs and HISs. Because RIS (or, in some cases, an HIS) keeps track of examinations and associates them with patients, and a PACS keeps track of images and associates them with examinations, the task is to provide coordination between the examination data on the two systems” (p. 643).
Benefits to integration per Arenson, Andriole, Avrin, & Gould (2000) include “…economic advantages, secure rapid access to all clinical information on patients, including imaging studies, anytime and anywhere, enhances the quality of patient care, although it is difficult to quantify” (p. 145).
Another major challenge for health care institutions and informaticians is the selection of a method for producing and distributing image reports. Traditionally, this has been done through clinician dictation followed by a transcriptionist typing a report and then review and approval by the dictator.
Speech recognition is another way for clinicians to document his or her interpretation of an image. AHIMA defines speech recognition technology as “technology that translates speech to text (AHIMA, 2012, p. 321). There are two types of speech recognition: front-end and back-end. According to AHIMA (2003), “Front-end” speech recognition is the term generally used to describe a process where the dictator (end user) speaks into a microphone or headset attached to a PC. The recognized words are displayed as they are recognized, and the dictator is expected to correct misrecognitions. Server-based speech recognition takes place after the dictator has created audio input in much the same way as usual, and the process then takes place at the server level, or on the “back end” (para. 30).
The final reporting method option is structured. Fenton (as cited in van Bemmel & Musen, 1999) states “Structured data entry largely involves the use of forms and other tools to enter information. Forms or computer entry screens include defined data elements or fields, some of which may be mandatory, some of which may be optional. Often the content entered into the different fields is specified via lists or a predefined vocabulary. Sometimes the system will intelligently follow the data entry and, based on what is entered, determine the next fields needing completion” (p. 52).
Moving on to factors that will affect the future direction of imaging systems, there are several. The first is advances in medical imaging technology.
According to the Duke Center for Health Informatics (2009), “Medicare data indicate that medical imaging studies are the most frequently prescribed diagnostic procedure and the fastest growing physician service in the US health system” (para. 1). With this increase comes an increase in imaging data.
An example of an advance in medical imaging technology is from Goedert (2010) who stated “The Food and Drug Administration recently approved new medical imaging technology to process images and pinpoint regions of interest. The MED-SEG system from Largo, Md.-based Bartron Medical Imaging Inc. is based on a computer algorithm developed at NASA's Goddard Space Fight Center in Greenbelt, Md. The software groups an image's pixels together at different levels of detail to enable image segmentation to a higher level than currently available…” (para. 1).
Another recent development is the release of an expansion of the DICOM medical image exchange standard Supplement 145. According to a College of American Pathologists’ press release, “The standard will enable electronic display, sharing, storage, and management of the image of the “entire microscope slide”—or large images usually associated with pathology. It will also allow health care professionals flexibility, such as panning and zooming, when interacting with the image… The adoption of whole slide digital imaging into hospitals and laboratories is desirable for advancing pathology and improving patient care. Currently, most hospitals use a PACS (Picture Archiving and Communication System) to manage and store radiology images. Until now, PACS software and the DICOM core standard did not accommodate pathology whole slide images. Supplement 145, the new standard for ‘Whole Slide Microscopic Images,’ will facilitate health information interoperability of pathology medical images, various whole slide imaging equipment manufacturers, PACS, and electronic health records (EHRs)” (para. 2, 4-5).
There is an expectation that by 2013, DICOM will be required by all EHR systems that include imaging information as an integral part of the patient record.
A final factor affecting the future direction of imaging systems is the American Recovery and Reinvestment Act or ARRA and the associated Health Information Technology for Economic and Clinical Health (HITECH) provision. ARRA, officially Public Law 111-5 signed into law February 2009, provides many different stimulus opportunities, one of which is $19.2 billion for health IT. According to the Centers for Medicare and Medicaid Services (CMS), “The Medicare and Medicaid EHR Incentive Programs will provide incentive payments to eligible professionals, eligible hospitals and critical access hospitals (CAHs) as they adopt, implement, upgrade or demonstrate meaningful use of certified EHR technology” (CMS, 2011, para. 1).
On July 13, 2010, the Secretary of HHS published in the Federal Register a final rule that adopted standards, implementation specifications, and certification criteria for HIT. The final rule was released in conjunction with the Medicare and Medicaid EHR Incentive Programs final rule. The CMS regulations specify the objectives that providers must achieve in payment years 2011 and 2012 to qualify for incentive payments. The ONC regulations specify the technical capabilities that EHR technology must have to be certified and to support providers in achieving the “meaningful use” objectives.
The current plans are the inclusion of images in the certified EHR technology in Stage 2.
This concludes Medical Imaging Systems.
The first part of this lecture defined biomedical imaging, medical imaging, and medical imaging informatics, examined the purposes, processes, and management issues with regards to imaging systems. Specific factors related to storage concerns and image integration including viewing stations were scrutinized. Image integration with other health care information, another challenge faced by health care institutions and informaticians, was also discussed. The final topic covered was future directions.