UMGC Emerging Health Information Technologies Paper

As an HIM manager, you are allowing the use of BYOD on your organizational network. But before you do so, you need to develop and implement a BYOD policy to be followed by all users. Develop a BYOD use policy entailing:

The rationale of the policy (importance for the organization).

Who can use BYOD and why?

• What information the BYOD users can access? (Doctors, nurses, administrators, office staff)
• Which technology they should use to ensure secure communication between their devices and the organizational network? Why this specific tech.?

  

• How would you ensure that the BYOD meet HIPAA compliance requirement?
• Any other requirements you consider specific to your organization that the users must meet.

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Title: UMGC Emerging Health Information Technologies Paper

Copyright 2013. AHIMA Press. All rights reserved. May not be reproduced in any form without permission from the publisher, except fair uses permitted under U.S. or applicable copyright law. Health Information Systems: Supporting Technologies and Systems Development Healthcare organizations are under increased pressure to control costs and improve efficiency. At the same time, they are experiencing increased demands to ensure patient safety, reduce medical errors, improve the quality of care, promote access, and ensure compliance with privacy and security regulations. Many healthcare organizations are looking to informatics to help them respond to these pressures and provide high-quality services in a more cost-effective manner. The use of computer technology to manage data and information means that well-trained and skilled individuals with knowledge about both healthcare and computerized information technologies are needed to manage (design, develop, select, and maintain) health data and information systems. It also means that healthcare organizations must prioritize the computer technologies and information systems (IS) to deploy in their institution. This chapter introduces the field of informatics as it is currently being applied in the healthcare industry. Also, it describes the current and emerging technologies used to support the delivery of healthcare and the management and communication of patient information. It discusses strategic information systems planning, the systems development life cycle (SDLC), information resource management, and the role of the health information managers in planning, selecting, and implementing healthcare information systems. The Field of Informatics Informatics is the science of information management. It uses computers to manage data and information and support decision-making activities. In short, informatics can be summarized by the following statement: “A person working in partnership with an information resource is ‘better’ than a person unassisted” (Friedman 2009, 169). The management of data and information includes the generation, collection, organization, validation, analysis, storage, and integration of data, as well as the dissemination, communication, presentation, utilization, transmission, and safeguarding of information. The healthcare industry is information intensive. One needs to spend only a day with a healthcare provider or clinician to realize that the largest percentage of healthcare professional activities relates to managing massive amounts of data and information. This includes obtaining and documenting information about patients, consulting with colleagues, staying abreast of the current literature, determining strategies for patient care, interpreting laboratory data and test results, and conducting research. Healthcare informatics is the field of information science concerned with the management of all aspects of health data and information through the application of computers and computer technologies. The State of Healthcare Informatics Historically, the healthcare industry has not valued informatics to the same degree that other industries have. 83 The healthcare industry has been perceived as slow to both understand computerized information management and to incorporate it effectively into the work environment. Perhaps this is because the data and information requirements of the healthcare industry are more demanding than those of other industries in a number of areas. These areas include implications of violations of privacy, support for personal values, responsibility for public health, complexity of the knowledge base and terminology, perception of high risk and pressure to make critical decisions rapidly, poorly defined outcomes, and support for the diffusion of power (Stead and Lorenzi 1999, 343). The use of information technologies to improve the healthcare delivery system gained attention in the early 1990s through the early 2000s through the publication of several reports from the Institute of Medicine that highlighted patient safety concerns and discussed how health information technologies can be used to improve care delivery. Momentum was gained with the establishment of the Office of the National Coordinator for Health Information Technology (ONC) in 2004. In 2008, ONC published the Federal Health Information Technology Strategic Plan, which defined a number of goals, objectives, and strategies that bring together all federal efforts in health IT in a coordinated fashion. The purpose of the plan is to guide the advancement of health IT throughout the federal government through 2012. More recently the Health Information Technology for Economic and Clinical Health (HITECH) provision of the American Recovery and Reinvestment Act of 2009 (ARRA) authorized the Centers for Medicare and Medicaid Services (CMS) to provide reimbursement incentives for eligible professionals and hospitals who are successful in becoming “meaningful users” of certified electronic health record (EHR) technology. Examples of healthcare informatics successes are steadily growing. Charge collection and billing, automated laboratory testing and reporting, clinical documentation, computerized provider order entry (CPOE), patient and provider scheduling, diagnostic imaging, and secondary data use make up a distinguished list of healthcare informatics successes, proving what is doable and supporting further investment. Today’s task for informatics is to design, develop, and implement computer information systems that enable healthcare organizations to accomplish visions for providing the highest-quality care in the most effective way. Applied healthcare informatics emphasizes the use of the computer-based applications in delivering and documenting healthcare services (AMIA 2005). Therefore, applied healthcare informatics is the application of information technology to functions and activities that are closely aligned with the domains of practice associated with the health information management (HIM) profession. EBSCO Publishing : eBook Academic Collection (EBSCOhost) – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS AN: 667492 ; Kathleen M. LaTour, Shirley Eichenwald.; Health Information Management: Concepts, Principles, and Practice, Fourth Edition Account: s4264928.main.eds 05_AB103311_ch04.indd 83 12/21/12 7:19 PM 84 Chapter 4 Check Your Understanding 4.1 Instructions: Answer the following questions on a separate piece of paper. 1. How are the disciplines of information management and informatics related? How are they different? 2. Why are data and information so crucial to a healthcare professional’s daily work? 3. Why is the healthcare industry perceived as being less proactive than other industries in the area of computerized information systems? How can this perception be changed? Current and Emerging Information Technologies in Healthcare To examine the information resources and systems that enable healthcare organizations to accomplish their visions in the most effective way, HIM professionals must possess fundamental knowledge of the components of computer-based information systems. This includes possessing knowledge of system hardware, software, and service components; communication and networking components; the Internet and its derived technologies; and system architectures. For the purposes of this chapter, it is assumed that students have acquired this basic knowledge through other, generic computer system courses and related textbooks. Next, it is appropriate that HIM professionals review some of the current and emerging information technologies used to specifically support the delivery of healthcare as well as the management and communication of health data and information within the healthcare setting. To do this, five categories of current and emerging technologies in healthcare are discussed in this chapter: ●● Supporting capture of various types of data and formats ●● Supporting efficient access to, and flow of, data and information ●● Supporting managerial and clinical decision making ●● Supporting diagnosis, treatment, and care of patients ●● Supporting security of data and information Technologies Supporting the Capture of Different Types of Data and Formats The information technologies currently in use for healthcare applications, as well as the new technologies being developed, support the capture of many different data types and formats that are all used to support the clinical services and administrative functions performed in every healthcare setting. Clinical Data Repository An EHR system consists of not one or even two or more products. Rather, it is a concept that consists of a host of integrated, component information systems and technologies. The clinical data repository is a component of the EHR that captures data. The automated files that make up the EHR system’s component information systems and technologies consist of different data types, and the data in the files consist of different data formats. Some data formats are structured and some are unstructured. For example, the data elements in a patient’s automated laboratory order, result, or demographic or financial information system are coded and alphanumeric. Their fields are predefined and limited. In other words, the type of data is discrete, and the format of these data is structured. Consequently, when a healthcare professional searches a database for one or more coded, discrete data elements based on the search parameters, the search engine can easily find, retrieve, and manipulate the element. However, the format of the data contained in a patient’s transcribed radiology or pathology result, history and physical (H&P), or clinical note system using wordprocessing technology is unstructured. Free-text data, as opposed to discrete, structured data, are generated by word processors, and their fields are not predefined and limited. Consequently, data embedded in unstructured text are not easily retrieved by the search engine. (See the section on speech recognition technology and natural language processing later in this chapter). Diagnostic image data, such as a digital chest x-ray or a computed tomography (CT) scan stored in a diagnostic image management system, represent a different type of data called bit-mapped data. However, the format of bit-mapped data also is unstructured. Saving each bit of the original image creates the image file. In other words, the image is a raster image, the smallest unit of which is a picture element or pixel. Together, hundreds of pixels simulate the image. Some diagnostic image data are based on analog, photographic films, such as an analog chest x-ray. These analog films must be digitally scanned, using film digitizers, to digitize the data. Other diagnostic image data are based on digital modalities, such as computed radiography (CR), CT, magnetic resonance (MR), or nuclear medicine. Document image data are yet another type of data that are bit mapped and the format of which is unstructured. These data are based on analog paper documents or on analog photographic film documents. Most often, analog paper-based documents contain handwritten notes, marks, or signatures. However, such documents can include preprinted documents (such as forms), photocopies of original documents, or computer-generated documents available only in hard copy. Analog photographic film-based documents (that is, photographs) are processed using an analog camera EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 84 12/21/12 7:19 PM Health Information Systems: Supporting Technologies and Systems Development and film, similar to analog chest x-rays. Therefore, both the analog paper-based and the photographic film-based documents must be digitally scanned, using scanning devices that are similar to facsimile machines. In addition, the EHR system’s component information systems and technologies consist of other data types, the formats of which are also unstructured. Real audio data consist of sound bytes, such as digital heart sounds. Motion or streaming video/frame data, such as cardiac catheterizations, consist of digital film attributes, such as fast forwarding. The files that consist of vector graphic (or signal tracing) data are created by saving lines plotted between a series of points, accounting for the familiar electrocardiograms (ECGs), electroencephalograms (EEGs), and fetal heart rate (FHR) tracings. When more than one unstructured data type is present in an information system, the data and system they represent are referred to as multimedia. Clearly, the EHR system is multimedia. Figure 4.1 shows the different types of data and their sources found in EHR system- component information systems. (See chapter 5 for a complete discussion of the types of data captured within the EHR and chapters 6, 7, and 8 for discussion of the practices required to ensure the quality of data collected in EHR systems.) technology in healthcare. The technology remains approximately 98 percent accurate (Nuance Communications 2008). Typically, systems offering approximately 98 percent accuracy still may not be acceptable for efficient and often lengthy clinical dictation purposes. Consequently, many still consider speech recognition an emerging technology. Today, speech recognition technology is speaker independent with continuous speech input. Speaker independence does not require extensive training. The software is already trained to recognize generic speech and speech patterns. Continuous speech input does not require the user to pause between words to let the computer distinguish between the beginning and ending of words. However, the user is required to be careful in the enunciation of words. Although speech recognition vocabularies are expanding due to faster and more powerful computer hardware, only limited clinical vocabularies have been developed. Limited vocabulary-based speech recognition systems require the user to say words that are known or taught to the system. In healthcare, limited clinical vocabulary–based specialties such as radiology, emergency medicine, and psychiatry have realized significant benefits for dictation from the technology. The ultimate goal in speech recognition technology is to be able to talk to a computer’s central processor and rapidly create vocabularies for applications without collecting any speech samples (in other words, without training). It includes being able to talk at natural speed and intonation and in no specific manner. It also includes having the computer understand what the user wants to say (the context of the word or words) and then apply the correct commands or words as Speech Recognition Technology For more than 20 years, the concept of generating an immediately available, legible, final, signed note or report based on computer speech input has been the catalyst for the development and application of different forms of speech recognition Figure 4.1. 85 EHR data types and their sources Laboratory Orders/ Results Handwritten Notesand Drawings Medication Orders/ MARs Signed Patient Consent Forms Discrete, Structured Data Document Image Data Transcribed Radiology/Pathology Reports Other Transcribed Reports UBs and Itemized Bills Ultrasound and Cardiac Catheterization Examinations Unstructured Text Data MPI/Registration Diagnostic Image Data Vector Graphic Video Data Audio Data Data Voice Annotations Online Charting and Documentation CT MR Digital X-rays Nuclear Medicine Pathology/Histology Images ECG*/EEG/Fetal Signal Tracings Heart Sounds *ECG is the more correct term, but EKG is more widely used. © Deborah Kohn 2001. EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 85 12/21/12 7:19 PM 86 Chapter 4 coded data in a structured format. Finally, it includes identifying a user’s voice and encrypting the voiceprint. Over the next years and decades, clinical vocabularies and algorithms will continue to improve, true speaker independence will be achieved, and natural language understanding will ultimately make structured dictation a reality. Natural Language Processing Technology Natural language processing technology considers sentence structure (syntax), meaning (semantics), and context to accurately process and extract free-text data, including speech data for application purposes. As such, it differs from simple Boolean word search programs (simply combining search terms with AND, OR, NOT, or NEAR) that often complement speech recognition technology–based systems. For example, the narratives “no shortness of breath, chest pain aggravated by exercise” and “no chest pain, shortness of breath aggravated by exercise” look the same to a Boolean word search engine when looking for occurrences of “chest” and “pain” in the same sentence. This Boolean word search approach retrieves approximately 20 percent of the answer 20 percent of the time. It is rife with false positives and false negatives. On the other hand, natural language processing technology knows the difference in the narratives’ meanings. For example, for health record coding applications, it teaches computers to understand English well enough to “read” transcribed reports and notes and then find certain key concepts (not merely words) by identifying the many different phrasings of the concept. By “normalizing” these concepts, different phrases of the same content can all be compared with one another for statistical purposes. For example, “the patient thinks he has angina” and “the doctor thinks the patient has angina” have different meanings from a coding perspective (Schnitzer 2000, 96). By employing statistical or rules-based algorithms, natural language processing technology can then compare and code these similar expressions accurately and quickly. Autocoding and computer-assisted coding are the terms commonly used to describe natural language processing technology’s method of extracting and subsequently translating dictated and then transcribed free-text data, or dictated and then computer-generated discrete data, into ICD or CPT codes for clinical and financial applications such as patient billing and health record coding. Text mining and data mining are the terms commonly used to describe the process of extracting and then quantifying and filtering free-text data and discrete data, respectively. Early results of several formative studies suggest that natural language processing technology improves health record coding productivity and consistency without sacrificing quality (Warner 2000, 78). More recent studies suggest that accuracy of natural language processing varies across applications and it is critical to have processes defined to review, edit, approve, and finalize (AHIMA 2011). Despite the studies’ outcomes, vendors continue to integrate natural language processing technology within health record coding reference tools, coding guidelines, drug databases, and legacy information systems to provide complete patient billing, health record coding, and other applications with little or no human intervention. Electronic Document/Content Management Systems A document is any analog or digital, formatted, and preserved “container” of data or information, collectively referred to as content. The document is a well-worn and very useful human construct, but unless data contained within documents are formatted, accompanied by print-like qualities, such as headings or bolding, data are difficult to interpret. It is for this reason that documents, and not data, are required for evidentiary disclosure and discovery purposes. To settle legal disputes, the transaction presentation, not representation, is required for all business record documents. In healthcare organizations, this involves the retrieval of the bill document, the consultation report document, the photograph document, the image document, and so on. An electronic document/content management (ED/ CM) system is any electronic system that manages an organization’s analog and digital documents and content (that is, not just the data) to realize significant improvements in business work processes. Like most information systems, the ED/ CM system consists of a number of component technologies that support both digital and analog document and content management. These component technologies are discussed in the following sections. Document Imaging Technology Document imaging technology is one of the many ED/CM system component technologies. This technology electronically captures, stores, identifies, retrieves, and distributes documents that are not generated digitally or are generated digitally but are stored on paper for distribution purposes. Currently, in healthcare provider organizations, documents that typically are not generated in a digital format, are stored on paper and are candidates for this technology. They include handwritten physician problem lists and notes; “fill-in-the-blank” typeset nursing forms; preprinted Conditions of Treatment forms; and external documents (documents from the outside). By digitally scanning the documents, the technology converts the analog data on the document into digital, bitmapped, document images, discussed in a previous section of this chapter. As more and more documents are created, distributed, and stored digitally, the dependence on, and use of, this technology decreases. Document Management Technology For every type of document as well as for every section or part of a document, document management technology automatically organizes, assembles, secures, and shares documents. Some of the more common document management EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 86 12/21/12 7:19 PM Health Information Systems: Supporting Technologies and Systems Development technology functions include document version control, check in–check out control, document access control, and text and word searches. Electronic Records Management Technology Business records are bound by legal and regulatory requirements. Consequently, formats for long-term preservation, storage media for long-term viability, and strategies for record migration and accessibility are required. Electronic records management technology includes components that must ensure the authenticity, security, and reliability of an organization’s electronic records. For example, mass storage is required for the massive amounts of structured and unstructured data as well as the large number and kind of documents stored in ED/CM systems. The major, mass storage medium used in ED/CM systems is magnetic, including disk (for example, redundant array of independent disks [RAID], network attached storage [NAS], content addressable storage [CAS]) or tape options. For extraordinarily large amounts of data and lengthy document archive requirements, the optical medium might be used, including compact disk–read only memory (CD-ROM), CD-recordable, digital versatile disk (DVD; read only or recordable), or magnetooptical-based write once read many (WORM) options. In addition, ED/CM system records must be properly classified under appropriate categories so that appropriate legal and regulatory retention rules can be applied. Users must determine how to identify these records so that the records and record documents can be deleted, purged, or destroyed at a defined point in their life cycle. 87 One of the more recent trends for ERM is to store the coded, report-formatted output data natively and convert the data to Extensible Markup Language (XML) or HyperText Markup Language (HTML) when needed. In healthcare provider organizations, such documents generated by COLD/ERM technology typically include “green bar” financial system reports, Uniform Bills (UBs)/CMS 1500s, laboratory cumulative result summary reports, and transcribed, word-processed medical reports. Automated Forms-Processing Technology Automated forms-processing (e-forms) technology allows users to electronically enter data into online forms and electronically extract the data from the online forms for various data-manipulation purposes. Powerful contextual verification processes have made such operations highly accurate. In addition, the form document is stored in a form format, as the user sees it on the screen, for ease of interpretation. Digital Signature Management Technology Digital signature management technology offers both signer and document authentication for analog or digital documents. Signer authentication is the ability to identify the person who digitally signed the document. Implementation of the technology is such that any unauthorized person will not be able to use the digital signature. Document authentication ensures that the document and the signature cannot be altered (unless both the original document and the change document are shown). As such, document authentication prevents the document signer from repudiating that fact. Workflow and Business Process Management Technology Business process management (BPM) technology allows computers to add and extract value from document content as the documents move throughout an organization. The documents can be assigned, routed, activated, and managed through system-controlled rules that mirror business operations and decision processes. For example, in healthcare organizations, workflow technology automatically routes electronic documents into electronic in-baskets of its department clerks or supervisors for disposition decisions. Diagnostic Imaging Technologies Diagnostic imaging technology (medical imaging) consists of using tools to capture images of the human body that can be used for clinical decision making. Picture archiving and communication systems (PACS) provide one example of diagnostic imaging technology where images taken from multiple sources (CT scans or MRIs, for example) are archived electronically for organizational access. Ultrasound technology, such as that used for echocardiography, is also considered imaging technology. Computer Output Laser Disk/Enterprise Report Management Technology Computer output laser disk/enterprise report management (COLD/ERM) technology electronically stores, manages, and distributes documents that are generated in a digital format and whose output data are report formatted and print-stream originated. Unfortunately, documents that are candidates for this technology too often are printed to paper or microform for distribution and storage purposes. COLD/ERM technology not only electronically stores the report-formatted documents but also distributes them with fax, e-mail, web, and traditional hard-copy print processes. Check Your Understanding 4.2 Instructions: Answer the following questions on a separate piece of paper. 1. Provide an example of structured and unstructured data formats and an example of discrete and free-text data types. 2. What is a key advantage to structured data when searching a database? 3. What are the similarities and differences between a diagnostic image and a document image? 4. Provide a healthcare example for each of the following data types: real audio data, motion or streaming data, and signal or vector graphic data. EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 87 12/21/12 7:19 PM 88 Chapter 4 5. What is the difference between (a) speech recognition technology and natural language processing technology and (b) natural language processing searching and Boolean searching? 6. What is an ED/CM system? 7. Explain the value of the following technologies: document imaging technology, workflow and BPM technology, COLD/ ERM technology, automated forms technology, and digital signature management technology. Technologies Supporting Efficient Access to, and Flow of, Data and Information There are many current and emerging information technologies used to support efficient access to, and flow of, healthcare data and information. For purposes of this chapter, the following technologies are highlighted: ●● Automatic recognition technologies ●● Enterprise master patient indexes and identity management ●● Electronic data interchange (EDI) and e-commerce ●● Secure messaging systems ●● Web-derived technologies and applications Automatic Recognition Technologies Several technologies are used in healthcare to recognize analog items automatically, such as tangible materials or documents, or to recognize characters and symbols from analog items. Character and symbol recognition technologies recognize electronically scanned characters or symbols from analog items, enabling the identified data to be quickly, accurately, and automatically entered into digital systems. Other recognition technologies identify the actual items. Character and Symbol Recognition Technologies Character and symbol recognition technologies include barcoding, optical character recognition (OCR), and gesture recognition technologies. Bar-Coding Technology Almost three decades ago, the bar code symbol was standardized for the healthcare industry, making it easier to adopt bar-coding technology and to realize its potential. Since then, bar-coding applications have been adopted for labels, patient wristbands, specimen containers, business/employee/ patient records, library reference materials, medication packages, dietary items, paper documents, and more. Benefits have been realized by the uniform consistency in the development of commercially available software systems, fewer procedural variations in healthcare organizations using the technology, and the flexibility to adopt standard specifications for functions while retaining current systems. Because virtually every tangible item in the clinical setting, including the patient, can be assigned a bar code with an associated meaning, it is not surprising to find bar coding as the primary tracking, identification, inventory data-capture, and even patient safety medium in healthcare organizations. With bar-coding technology, an individual’s computer data-entry rate can be increased by 8- to 12-fold in applications such as patient medication tracking, supply requisitioning, or chart/film tracking. For example, a function such as hand-keying paper chart/film locations into a computer that once took a healthcare professional eight hours to perform now can be done in 30 to 45 minutes with bar-coding technology. In addition to eliminating time spent, bar-coding technology eliminates most of the mounds of paperwork (worksheets, count sheets, identification sheets, and the like) that are still associated with traditional computer keyboard entry. When bar-coding systems are interfaced to these types of healthcare information systems, the bar code can be used to enter the data, especially repetitive data, saving additional processing time and paper generation. More importantly, the data input error rates with bar coding are as close to zero as most IT professionals think is possible. For all intents and purposes, bar-coded data, with an error rate of approximately three transactions in 1 million, can be considered error free. Thus, it is a most effective remedy for medication errors when used to ensure that the right medication dose is administered to the right patient. Optical Character Recognition Technology Like bar coding, optical character recognition (OCR) technology was invented to reduce manual data input, or handkeying. OCR technology recognizes machine-generated characters (for example, preprinted numbers and letters) by interpreting the scanned, bit-mapped shapes of the characters’ images and then converting the characters into computerprocessable codes. OCR technology was initially used to automatically identify financial accounts consisting of preprinted Arabic numbers and Roman letters using the E13B font on thousands of paper-based documents, such as bank checks. OCR has since been perfected to recognize the full set of preprinted typeset fonts as well as point sizes. The best OCR systems compensate for imperfectly formed characters and scanned pages by employing characteristics such as deskewing, broken character repair, and redaction. De-skewing “straightens” oblique characters, broken character repair “fixes” incomplete characters, and redaction “hides” superfluous characters. OCR is used to perform everything from indexing scanned documents to digitizing full text. Its ability to dramatically reduce manual data input, or hand-keying, while increasing input speed represents the best aspect of this technology. EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 88 12/21/12 7:19 PM Health Information Systems: Supporting Technologies and Systems Development Unfortunately, like other technologies, OCR has been perfected but is not perfect. The approximately 98 percent recognition rate realized by most OCR systems (Prime Recognition 2008) may not be sufficient for the kind of text recognition applications OCR software is designed to perform. In addition, after an analog document is scanned by OCR technology, the data become unstructured, free-text data. As with all unstructured text data, when a healthcare professional needs to search the text, the search engine cannot easily find, retrieve, and manipulate one or more data elements embedded in text. Gesture Recognition Technology The recognition of constrained or unconstrained, handwritten, English language free text (print or cursive, upper- or lower-case, characters or symbols) typically stored on paperbased, analog documents is known as intelligent character recognition (ICR) technology. The recognition of handmarked characters in defined areas of, typically, paper-based analog documents is known as mark sense technology. Collectively, these technologies are referred to as gesture recognition technologies. Mark sense technology detects the presence or absence of hand-marked characters on analog documents. Consequently, it is used for processing analog questionnaires, surveys, and tests, such as filled-in circles by Number 2 pencils on SAT exam forms. ICR technology is quite an elaborate informationprocessing technique. An operation such as the detection of lines or the beginnings of words in sections of handwritten text can be accomplished with relative ease in the normal case. However, subsequent tasks turn out to be extraordinarily complicated. These include segmentation of the words into individual characters and assignment of the individual characters to a definite class of characters, such as words. Consequently, ICR error rates remain high. As such, ICR technology is being adopted slowly, primarily into the data-entry activities of certain types of pen-based computer devices, such as handheld devices. Neural networks remain the leading ICR technology. These networks are modeled on the way synapses work in the brain: processing information by recognizing patterns of signals. As such, they adapt themselves into shifting configurations based on what they encounter. In other words, they change as they grow and learn. Consequently, for each handwritten character or symbol recognized by ICR technology, a confidence level is expressed internally as a percentage and a user picks the threshold below which he or she wants to flag uncertain characters or symbols. Like speech recognition technology, a training or setup period is required for this emerging technology. Other Recognition Technologies Automatic recognition technologies that identify actual items include radio frequency identification (RFID) and intelligent document recognition (IDR) technologies. 89 Radio Frequency Identification Technology Radio frequency identification (RFID) technology works in the following manner: Chips that emit radio signals are embedded in analog items and products. The signals are read and captured by receivers. The receivers act as data collectors and send the signals to PCs on a network, allowing the items and products to be tracked. RFID’s applicability in the healthcare industry is limited only by the imagination. Like bar codes, it is being used to track moveable patients, clinicians, medications, and equipment. As such, in a wireless environment, conceivably, RFID could replace bar codes for these applications. The greatest challenges regarding RFID technology are cost and privacy and security concerns. Intelligent Document Recognition Technology Recently, an automatic recognition technology has been developed to recognize types of analog documents or forms, eliminating the need for bar codes or other characters and symbols that identify the documents or forms. Intelligent document recognition (IDR) technology trains itself to identify document or form types and to sort the information accordingly for subsequent data entry. This training process requires a period of continuously scanning each type of document or form. As such, the pattern of document and form layouts and information locations educates the system to recognize the document or form for future recognition situations. Enterprise Master Patient Indexes and Identity Management Too often, breakdowns in patient identification cause patient record errors that threaten data integrity. The most common error occurs when healthcare provider organization registration personnel fail to locate existing patient information in the organization’s master patient index (MPI), including the patient’s unique identification number. The patient is then assigned another record (in other words, a duplicate record) and a new file is created in the database. When this error occurs, it is unclear into which database file the patient’s data should be entered. This often results in unnecessary duplicate tests, billing problems, and increased legal exposure in the case of adverse treatment outcomes. Another common error occurs when registration personnel incorrectly register a patient under another person’s existing, unique identification number. This error of overlay results in the merging of two different patients’ data into one file. The clinical risks are obvious. As healthcare organizations continue to come together into integrated delivery networks (IDNs), the probability increases that information about a patient is spread across multiple databases and in multiple formats. In addition, the information is updated and accessed by multiple transaction processing systems and personnel. This causes problems when the IDN begins to assemble information about a EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 89 12/21/12 7:19 PM 90 Chapter 4 patient in order to deliver care across diverse systems and encounters. Longitudinal applications, such as the EHR system, cannot be successful. Consequently, healthcare provider organizations are developing strategic initiatives for enterprise master patient indexes (EMPIs). In the broad sense, this involves the increasingly important service referred to as identity management. EMPIs provide access to multiple repositories of information from overlapping patient populations that are maintained in separate systems and databases. This occurs through an indexing scheme to all unique patient identification numbers and information in all the organizations’ databases. As such, EMPIs become the cornerstones of healthcare system integration projects. EMPIs work in two ways. At the back end, EMPIs coordinate recordkeeping. The indexes receive information from multiple systems that need no modification. The receiving is often performed through an integration gateway or engine. The enterprise index tests to see whether the patient is identified in all of the systems; if not, it may assign a unique identification number or other, related identifier as well as correlate records throughout the enterprise. At the front end, EMPIs receive requests from existing registration systems to send data to these systems. Usually, these existing registration systems need some reprogramming to enable them to request and receive data from the EMPI. Currently, there is no consistent, accepted trigger event and standard data format to do this. EMPI building is complex. Variations in information systems, data capture, and organizational goals and objectives present multiple challenges to integrating patient data. For example, EMPI building involves a multitude of decision points. These include deciding whether to employ centralized or distributed data storage; whether to maintain limited, additional information such as allergies and encounter histories or robust information such as problem lists; and whether to establish batch processing or real-time communication between the registration system and the EMPI. In addition, EMPIs include complex capabilities. These capabilities include merging records pertaining to the same person using probabilistic matching and algorithms, maintaining source systems’ pointers, removing duplicate records, and providing a common user interface. Finally, after technical and organizational issues are overcome, the purely operational tasks of linking patients across multiple entities and episodes of care and maintaining these linkages are difficult and can be costly. Secure Messaging Systems Messaging systems electronically deliver data and information to users. As such, e-mail systems are messaging systems. However, secure messaging systems reduce the security concerns that surround e-mail but retain the benefits of proactive, traceable, and personalized messaging. These systems are not transaction (data) processing systems. Also known as secure notification delivery systems, these systems store and forward content to users in an asynchronous, “anytime” mode. In healthcare, secure messaging systems are often referred to as clinical messaging systems because these systems are important, pervasive tools that are included in a broad set of contextual collaboration tools for clinicians. Other clinical collaboration tools include synchronous, real-time tools, such as instant messaging, chat servers, and web or media conferencing. However, secure clinical messaging is the most heavily used because it crosses time zones, can be done in each clinical user’s own time frame, and gives clinical recipients time to think over and then respond to issues, such as notifications of abnormal laboratory test results. In addition, clinical messaging does not require all participants to be available at the same time and eliminates the scheduling problems associated with the real-time tools. Secure clinical messaging systems work in the following manner: When a clinical information system (CIS) generates a patient alert regarding a possible drug interaction or an anomalous test result, the secure clinical messaging system immediately routes the alert, along with patient data, to a caregiver’s designated pager number, fax machine number, telephone number, or e-mail address. In turn, clinicians can securely send these alerts to other, related clinicians. Also, messages can be automatically escalated to the next available caregiver if the original caregiver does not respond within a predefined time frame. In addition, messages can be tracked throughout the care delivery network. Most of today’s secure clinical messaging systems fall into one of four architectures: peer-to-peer networking, a message staging server installed inside the network’s firewall, a staging server installed outside the firewall (usually hosted), and a wholly outsourced service (Tabar 2003). Electronic Data Interchange and E-Commerce Electronic data interchange (EDI) allows the transfer (incoming and outgoing) of information directly from one computer to another by using flexible, standard formats. These formats function as a common language among many different healthcare “trading” or “business” partners (payers, government agencies, financial institutions, employer groups, healthcare providers, suppliers, and claims processors) who have agreed to exchange the information electronically but use a wide variety of application software with incompatible native formats. In the healthcare industry, with its traditionally strong reliance on paper-intensive processes, the goal of EDI is to eliminate the administrative nightmares of transferring paper documents back and forth between these partners and then hand-keying the information into the partners’ disparate computer systems. EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 90 12/21/12 7:19 PM Health Information Systems: Supporting Technologies and Systems Development With widespread acceptance of the Internet and its derived technologies, such as the web, the term e-commerce began to replace the term EDI. Today, e-commerce is used to describe the integration of all aspects of business-to-business (B2B) and business-to-consumer (B2C) activities, processes, and communications, including EDI. In addition, the term e-health is now used to describe the application of e-commerce in the healthcare industry. Several principles and concepts of e-health directly relate to EDI principles and concepts. These include the links among the healthcare trading and business partners; the links to healthcare equipment and supply vendors, providers, and health plans; and the transactions for exchanging data on healthcare eligibility, referrals, claims, and so forth. Web-Derived Technologies and Applications Web Portals No one information system (IS) can provide all the applications, data types, and data formats needed by all of the healthcare industry’s diverse healthcare organizations and users. Consequently, most healthcare provider organizations maintain multiple, disparate “feeder” applications for their data repositories. Depending on their size and systems acquisition philosophies, some healthcare provider organizations maintain and often integrate large numbers of disparate feeder applications, and others maintain and integrate at least two or three. Each disparate feeder application for the repository has a unique user interface, uses different data nomenclature, and takes limited advantage of data standards. Therefore, it is not only difficult to integrate the information from the disparate systems into the repositories, but it is also difficult for the organizations’ users to learn and interact with the different systems. Today, the term clinical workstation is still used to describe the presentation of healthcare data and the launching of applications in the most effective way for healthcare providers. However, for all intents and purposes, the concept of web-based, clinician/physician portals has replaced the concept of the clinical workstation. A web portal is a single point of personalized access (an entryway) through which one can find and deliver information (content), applications, and services. Web portals began in the consumer market as an integration strategy rather than a solution. Portals offered users of the large, public, online Internet service provider websites, such as AOL, fast, centralized access (via a web browser) to an array of Internet services and information found on those websites. Consequently, like clinical workstations, clinician/physician web portals first were seen as a way for clinicians to easily access (via a web browser) the healthcare provider organizations’ multiple sources of structured and unstructured data from any network-connected device. Like clinical workstations, clinician/physician web portals evolved into 91 an effective medium for providing access to multiple applications as well as the data. And because clinician/physician portals are based on Internet technologies, they became the access points to sources of data and applications both internal and external to the organization. In addition, clinician/physician web portals provide simplified, automated methods of creating taxonomy, or classifying data. Consumer portals, such as Yahoo.com, provide good examples of this, whereby files and data corresponding to food, fashion, and travel are organized for easy access. Finally, true clinician/physician web portals have at least one search engine and allow customization at the role and individual level. As such, search engines must be able to search e-mails, file servers, web servers, and databases; and customization must allow users to create individual, relevant views. The clinical benefits of these portal features and functions are obvious. With the success of clinician/physician web portals and the trend toward improving patient engagement in healthcare through technology, a growing number of healthcare provider and payer organizations have established web portals for their patients/members. Each participant receives an account on the web portal with a unique log-in and password. Typical payer-based portal uses include accessing membership information and choosing a primary care physician. Typical provider-based portal uses include requesting prescription renewals, scheduling appointments, and asking questions of providers via secure messaging. Increasingly, patient/member web portals are allowing patients to pay their bills online and to securely view all or portions of their provider-based, electronic health record, such as current medical conditions, medications, allergies, and test results. Although patients/members access the portals over the Internet, all the information, including the secure messaging applications, resides on the provider’s or payer’s secured servers. As such, these portals dovetail well with privacy and security regulations, which empower patients/consumers with the authority to determine who can have access to their healthcare information. Also, patients can use the portal to notify providers if their EHR is incorrect. As consumers seek to take a larger role in their healthcare, such patient/member “entryways” to information (content), applications, and services are expected to become more common. Intranets and Extranets Web-based information systems and applications cannot continue to proliferate without creating web-based intranets designed to enhance communication among an organization’s internal employees and facilities and webbased extranets designed to enhance communication among an organization’s external business partners. This is true because intranets link every employee within an organization via an easy-to-navigate, comprehensive network devoted to internal business operations and extranets link an organization’s external business partners with the same EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 91 12/21/12 7:19 PM 92 Chapter 4 comprehensive network but one that is devoted to external business operations. For example, private, secure networks provide every healthcare organization employee with basic information, such as message boards, employee handbooks, manuals, mail, cafeteria menus, newsletters, directories, and contact lists. Also, they are used for the development of the organization’s EHR. Restricted access to intranets by authorized users provides assurances that the general Internet public cannot access this private, secure network. However, through its intranet, a healthcare organization can access the Internet’s servers for general Internet mail and messaging. Extranets connect intranets that exist outside an organization’s firewall. For example, typically, an IDN’s autonomous care facilities (for example, acute care, long-term care, home healthcare), each with its own intranet, need to communicate between and among themselves via secure e-mail or other collaboration tools. As such, the facilities connect the various intranets and form an extranet. Web Content Management Systems Web content management systems label and track the exponential increase in and variety of information that is placed on a website so that the information can be easily located, modified, and reused. These systems are a critical component in personalizing an organization’s web-based intranet and extranet, web portal, and page content for site users and visitors. They also provide crucial versioning and globalization capabilities. Versioning enables each of the website’s content components to be tracked individually. Then, as the content changes, each iteration of the content can be identified and the overall website can be recreated as it existed at any specific point in time. Globalization enables the look and feel of an organization’s website to be managed centrally, while specific content is managed for local requirements, such as regional healthcare language or procedure differences. system-independent vocabularies and protocols, such as simple object access protocols (SOAP) to transfer the data; universal description, discovery, and integration (UDDI) to list what services are available; and web services description language (WSDL) to describe the services available. Healthcare organizations have been gradually installing web services to ease integration of disparate web-based and legacy applications, often written in incompatible languages. This ensures that the organizations’ applications interoperate and that healthcare organizations can more easily choose tools for important interorganizational and regional data sharing. (See figure 4.2.) Open Source Technology Open source software products are applications whose source (human-readable) code is freely available to anyone who is interested in downloading the code. Advantages of open source technology include its availability, it extensibility to be customized, and the collaborative nature of the product in which a community of developers and users can interact, review, and improve upon each other’s ideas. Disadvantages of open source technology include the need for skilled developers within an organization to take advantage of the benefits noted earlier as well as a lack of dependable technical support. According to the open source definition maintained by Open Source Initiative (2012), ten criteria must be met to qualify a software program as open source. ●● Free redistribution: Free redistribution is allowed and royalty payments are prohibited ●● Source code: The program must include source code ●● Derived works: Modifications and derived works are allowed ●● Integrity of author’s source code: The integrity of the original source code must be preserved ●● No discrimination against any person or groups: The Web Services Web services technology is a platform for software applications (or services) whose basic communication mechanism is XML, the universal language of the web and the accepted format for data exchange over the Internet. In addition, web services technology utilizes web-based infrastructure protocols, such as HTTP and transmission control protocol/Internet protocol (TCP/IP). As such, web services technology allows programs written in different languages and on different operating systems to communicate with each other in a standards-based way. In short, web services technology is an open, standardized way of integrating disparate, web browser–based and other applications. By using XML messages to format and tag data, web services technology allows for data interchange without the need for translation. In addition, the messages use license must not discriminate against any person or group ●● No discrimination against fields of endeavor: The license must not restrict anyone from making use of the program in a specific field of endeavor ●● Distribution of license: The license remains with the program even if it is redistributed ●● License must not be specific to a product: The rights attached to the program must not depend on the program’s being part of a particular software distribution ●● License must not restrict other software: The license must not insist that all other programs distributed on the same medium be open source software ●● License must be technology neutral: No provision of the license may be predicated on any individual technology or style of interface EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 92 12/21/12 7:19 PM Health Information Systems: Supporting Technologies and Systems Development 93 Figure 4.2. Web services Client or Presentation Tier Browser, Patient/Physician Portal XML, HTTP Server or Rules Tier Web Application Server Farm Service-Oriented Architecture (SOA) Framework Physician Access WS Patient Access WS ADT/Charge Capture WS Scheduling/ Charge Capture WS Problem List WS Identity Manager WS Order Entry Results WS Image Store WS Text Document WS Web Services UDDI WSDL SOAP XML, ODBC, HL7 Data Sources Tier Database Servers and Legacy Platforms Siemens HIS IDX RIS Misys LIS Emageon PACS Allscripts EMR Amisys Managed Care GEMSIT MUSE ECG SoftMed Transcription © Deborah Kohn 2005. Check Your Understanding 4.3 Instructions: Answer the following questions on a separate piece of paper. 1. Provide a healthcare example for each of the following automatic recognition technologies: bar coding, OCR, ICR, RFID, and IDR. 2. How are the concepts of EDI, e-commerce, and e-health interrelated? 3. What is driving the heightened interest in EMPI technology within the healthcare industry? 4. Explain why secure clinical messaging is often preferred over real-time tools such as instant messaging or chats. 5. What is the primary purpose of the clinical workstation and the clinician/physician portal? 6. How do web portals established by providers or payers assist consumers in taking a larger role in their healthcare? 7. What is the difference between an intranet and an extranet? Provide an example of how each can be used in healthcare. 8. Describe the benefits and drawbacks of open source technology. Technology Supporting Managerial and Clinical Decision Making Many current and emerging information technologies are used to support managerial and clinical decision making. For the purposes of this chapter, the following technologies and systems are highlighted: ●● Data warehouses and data marts ●● Decision support systems Data Warehouses and Data Marts Data warehouses are large, centralized, enterprise-wide collections of all the historical, demographic, and transactional data and information about businesses that are used to support managerial or, in the case of healthcare provider organizations, clinical decision-making processes (database data are typically structured and discrete). Generally, only two kinds of operations occur in a data warehouse: data warehousing and data mining. This is referred to as the nonvolatility of warehouse data. Data warehousing is the acquisition of all the business data and information from potentially EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 93 12/21/12 7:19 PM 94 Chapter 4 multiple, cross-platform sources, such as legacy databases, departmental databases, and online transaction–based databases, and then the warehouse storage of all the data in one consistent format. Data mining is the probing and extracting of all the business data and information from the warehouse and then the quantifying and filtering of the data for analysis purposes. The model of the data warehouse database is typically subject oriented. In other words, the data within the data warehouse are organized along subject lines (customer, product, patient, clinician) rather than along operational lines (accounting, management, medicine, surgery) in order to be accessible and useful across the enterprise. Generally, for day-to-day operations, a healthcare organization needs relatively current data and each operational unit needs only its own data. That is why relational and object-oriented database models for data repositories are well-suited for online/real-time transaction processing (OLTP). But for large-scale, retrospective data analysis, for which online/real-time analytical processing (OLAP) is designed, a healthcare organization generally needs not just its current status but also a historical record over time or time variance, encompassing all the organizational operating units by subject for comparison purposes. In healthcare, data warehouses have been used primarily for the following applications (Henchey 1998, 68): ●● Clinical management: For example, every day, patient clinical data are fed into the warehouse from multiple sources to contribute to enterprise-wide best practices and to identify areas of excessive variation from best practices. ●● Operations management: For example, sophisticated analytical tools, such as cost accounting, case-based budgeting, and variance analysis tools, are included with the warehouse to determine new healthcare market opportunities. ●● Outcomes management: For example, data mining is conducted to study patient health status or other factors, such as satisfaction, that contribute to clinical outcomes. ●● Population management: For example, to proactively manage the health of plan members, data mining helps the organization to predict utilization or identify at-risk members requiring case management. ●● Revenue management: For example, the data warehouse assists healthcare financial analysts in addressing all the different contractual and regulatory reimbursement formulas. With revenue based on a mix of several dimensions, such as fee-for-service, capitation, and risk pooling, only the data warehouse can provide a complete picture of the enterprise’s revenue stream and the factors controlling it. A data warehouse cannot simply be bought and installed. Its implementation requires the integration of many products within its architecture. For example, often data warehouses require advanced data warehousing and mining techniques and tools. The software must be able to locate data that often are stored on multiple servers that may include any type of machine or operating system. The software must be able to maintain metadata (indexed data about the data), such as what indexes the acquired data use. Further, the software must be able to recognize data duplication and exceptions as well as issue alerts when data are not present or have been corrupted. Data marts can be thought of as miniaturized data warehouses. Data marts are usually geared to the needs of a specific department, group, or business operational unit. Because data marts are considerably smaller in both size and complexity than data warehouses, some healthcare organizations build data marts as a way of testing data warehouses on smaller, more focused scales. What many are finding, though, is that data marts can easily proliferate into a collection of incompatible data stores with accessibility or utility limited to the department or operational unit that designed the mart. Decision Support Systems Decision support systems (DSSs) are interactive computer systems that intend to help decision makers use data and models to identify and solve problems and make decisions. A great deal of innovation is occurring related to DSSs, and the technologies of which they are comprised are changing rapidly. Generally, DSSs are based on either a data repository model or a data warehouse model. Both transfer data from an operational environment (either in real time or retrospectively, in batches at fixed intervals) to a decision-making environment, and both organize the data in a form suitable to decision support applications. Power (1997) suggests that DSSs can be classified based on one or more of the following five categories: ●● Communications-driven DSSs emphasize communi- cations, collaboration, and shared decision-making support. A simple Internet bulletin board or threaded e-mail is the most elementary level of functionality in this type of DSS. ●● Data-driven DSSs emphasize access to and manipulation of internal, and sometimes external, structured business data. Simple file systems accessed by query and retrieval tools provide the most elementary level of functionality in this type of DSS. ●● Document- or graphics-driven DSSs focus on the retrieval and management of unstructured business data. Basic document- or graphics-driven DSSs exist in the form of web-based search engines. ●● Knowledge-driven DSSs can suggest or recommend actions to decision makers. These DSSs are person-tocomputer systems with specialized problem-solving expertise. The expertise consists of knowledge about a particular domain, understanding of problems within that domain, and skill at solving some of those problems. EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 94 12/21/12 7:19 PM Health Information Systems: Supporting Technologies and Systems Development 95 ●● Model-driven DSSs emphasize access to and manipu- ●● Easy to use (typically mouse or touch screen driven) lation of a model, for example, statistical, financial, optimization, and simulation models. Simple statistical and analytical tools provide the most elementary level of functionality in this type of DSS. ●● Capable of being used directly by executives without A wide variety of DSSs and related tools and technologies exist in healthcare, most of which can be classified as hybrids of the preceding categories. These systems include, but are not limited to, clinical/medical decision support systems, management information systems (MISs), executive information systems (EISs), geographic information systems (GISs), and expert decision support systems. See chapter 5 for an in-depth discussion of clinical/medical decision support systems. Management Information Systems Typically, management information systems (MISs) refer to the broad range of data-, document-, or knowledge-driven DSSs that provide information concerned with an organization’s administrative functions (in other words, those functions that are associated with the provision and utilization of services). In addition, DSS-based MISs enable management to interrogate the computer on an ad hoc basis for various kinds of information within the organization so as to predict the effect of potential decisions. As such, DSS-based MISs provide information to people who must query these systems to make disposition decisions about valuable resources in a timely, accurate, and complete manner. Such systems are crucial for the effective administration of any organization and include, but are not limited to, general accounting and financial systems, customer relationship management (CRM) systems, enterprise resource planning (ERP) systems, and operations and plant management systems. Executive Information Systems Executive information systems (EISs) are DSSs that support the decision making of senior managers. As such, they provide direct online access to timely, accurate, and actionable information about aspects of a business that are of particular interest to a senior healthcare manager. Typically, this information is provided in a useful and navigable format so that managers can identify broad strategic issues and then explore the information to find the root causes of those issues. According to Kelly (2001), the following EIS features and functions are essential: ●● Specifically tailored to executives’ information needs ●● Capable of accessing data about specific issues and problems ●● Capable of aggregating data into meaningful reports ●● Provide extensive online analysis tools, including trend analysis, exception reporting, and drill-down or datamining capabilities ●● Capable of accessing a broad range of internal and external data assistance ●● Capable of presenting information in a graphical form Geographic Information Systems In the strictest sense, geographic information systems (GISs) are DSSs capable of assembling, storing, manipulating, and displaying geographically referenced data and information. In other words, GISs identify data according to their locations. The applications of GISs in healthcare extend from practical community-based services to sophisticated studies on a global scale. For example, pediatricians consult community-based GISs to observe neighborhoods with high concentrations of lead and decide whether lead screenings would be appropriate for certain patients. Technologies Supporting the Diagnosis, Treatment, and Care of Patients Many current and emerging information technologies are used to support the diagnosis, treatment, and care of patients. For the purposes of this chapter, the following technologies are highlighted: ●● Physiological signal processing systems ●● Point-of-care information systems ●● Mobile and wireless technology and devices ●● Automated care plans, clinical practice guidelines, clinical pathways, and protocols ●● Telemedicine/telehealth ●● EHR systems ●● Personal health records Physiological Signal Processing Systems The human body is a rich source of signals that carry vital information about underlying physiological processes. Traditionally, such signals have been used in clinical diagnosis as well as in the study of the functional behavior of internal organs. Earlier in this chapter, physiological signal processing systems, such as ECG, EEG, and FHR tracing systems, were mentioned because these systems store data based on the body’s signals and create output based on the lines plotted between the signals’ points. The data type used by these systems is referred to as signal tracing or vector graphic data. Physiological signal processing systems measure biological signals. Also, they help to integrate the medical science of analyzing the signals with such disciplines as biomedical engineering, computer graphics, mathematics, diagnostic image processing, computer vision, and pattern EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 95 12/21/12 7:19 PM 96 Chapter 4 recognition. The integration of these disciplines allows these systems to electronically compile measurement equations, estimate the signals’ parameters, and characterize the feedback elements. For example, the computer-based analysis of the neuromuscular system, the definition of cardiovascular system models, the control of cardiac pacemakers, the regulation of blood sugar levels, and the development of artificial organs not only serve patient diagnostic and care purposes but also support the development and simulation of instrumentation for physiological research and clinical investigation. Point-of-Care Information Systems Computer systems that allow healthcare providers to capture and retrieve data and information at the location where the healthcare service is performed have come a long way since hard-wired computer terminals with green screens were first placed at the patient’s bedside more than 25 years ago. Functionally, almost every type of patient clinical and administrative application has been introduced to provide care services at the bedside, in the exam room, at the home, or even on the patient, as in medical monitoring. Technologically, massive changes have occurred in these systems’ platforms, footprints, and networking capabilities. For example, many acute care facilities have installed clinical point-of-care information systems that, among other services, provide online medication order entry, profiles, administration schedules, and records. The records include information about medications not given (with reasons) as well as related information such as fluid balances, physical assessments, laboratory test results, and vital signs. All medications, including unit doses, are bar coded and scanned at or near the patient’s bedside along with the patient’s wristband and the caregiver’s identification badge. This prompts a safety edit, documents administration of the medication, and generates the charge. Other acute-care facilities have installed administrative point-ofcare (or service) systems that have eliminated admitting areas. Inpatients are greeted at the door with their room assignments, and roving admissions representatives visit patients in the assigned rooms to complete all the admission procedures. Typically, point-of-care information systems use portable, handheld, wireless devices to enable entry of the data by a bar code scanner, keypad, or touch screen. Also, the devices are used to upload and download information to and from hard-wired workstations. Retrieval of the data occurs at the wireless device or on wall-mounted or portable, cart-based computers. The data also can be entered and retrieved on hard-wired workstations located in areas outside the point of care, such as central areas at patient care units, back offices, central or satellite pharmacies, and physician lounges, homes, and offices. Mobile and Wireless Technology and Devices Perhaps the biggest influence on, as well as challenge for, point-of-care information systems and their use comes from recent, significant advances in wireless technology and smaller, mobile devices. For the healthcare industry, the successful integration of wireless technology and smaller, mobile devices with point-of-care software supports and enhances the clinician’s decision-making processes. True wireless systems use wireless networks and wireless devices to access and transmit data in real time. At the basic level, wireless technology is based on the use of radio waves. For the purposes of this chapter, the technology is divided into two categories: (1) regulated and unregulated, and (2) wide area and in-building. For years, healthcare organizations have used in-building wireless point-of-care information systems, such as telemetry systems. These systems were based on existing technologies and use a portion of the radio spectrum reserved for industrial, scientific, and medical purposes (ISM band). Individual licenses are not required for these types of systems. Also, provider organizations have long used wide-area wireless technology to support ISs, such as point-of-care systems. This technology involves microwave systems that are based on fixed, point-to-point wireless technology used to connect buildings in a campus network. Microwave systems are regulated and require licenses and compliance with Federal Trade Commission (FCC) procedures. Until recently, most in-building wireless systems were proprietary. However, adoption of the Institute of Electrical and Electronic Engineers wireless technology standard (IEEE 802.11) has begun to provide a reasonable level of standardization. The IEEE 802.11 standard allows data transmission speeds of up to 11 megabits per second, is relatively low power, and does not require licenses for installation and use. The IEEE 802.11b is an international standard that provides a method for wireless connectivity to fixed and portable devices within a local area. As such, this standard allows interoperability among multiple vendor products. But it is the widespread adoption of cellular telephone technology that has significantly advanced the development of wireless technology and, consequently, its support for point-of-care systems. A brief look at most healthcare organization today turns up mobile phones, two-way pagers, Internet-enabled telephones (also known as smart phones), tablets, and personal digital assistants (PDAs). Mobile devices improve point-of-care systems by allowing clinicians to use a device personalized to their individual workflows, such as clinical (for example, e-prescribing), dictation, and billing workflows, not functions. In addition, mobile devices provide clinicians the information they need anytime, anywhere, and on any network-addressable device. EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 96 12/21/12 7:19 PM Health Information Systems: Supporting Technologies and Systems Development Automated Clinical Care Plans, Practice Guidelines, Pathways, and Protocols The terms used to describe clinical practice mandates, care process guides or pathways, disease management protocols, and decision algorithms are not well standardized. They tend to be used informally and interchangeably, often resulting in miscommunication among healthcare professionals. Consequently, when clinical care plans, practice guidelines, pathways, and protocols are automated and used by multidisciplinary teams, patient care can be adversely affected unless the definitions of these various terms are clearly understood by all. For example: ●● Clinical care plans are created for individual patients by healthcare providers for a specific time period. Typically, clinical care plans are based on the healthcare provider’s training. ●● Clinical practice guidelines are recommendations based on systematic statements or clinical algorithms of proven care options. Often professional organizations and associations, health plans, and government agencies such as the Agency for Healthcare Research and Quality (AHRQ) develop these guidelines. ●● Clinical (or critical) pathways (CareMaps) delineate standardized, day-to-day courses of care for a group of patients with the same diagnosis or procedure to achieve consistent outcomes. Typically, pathways (CareMaps) are developed by the local healthcare organization or health plan. ●● Clinicians often use the term protocol to refer to the written documents that guide or specify a practice, including clinical practice guidelines and clinical pathways. Strictly speaking, however, protocols are more detailed care plans for individual patients based on investigations performed by professional societies, drug companies, or individual researchers (Bufton 1999, 258). Providers now recognize the enormous variation there is in how they diagnose, treat, and care for patients. Consequently, there is a trend to use guidelines, formalized pathways, and protocols that have emerged from clinical research (evidence-based medicine) in order to reduce variation and improve care outcomes. Automating these guidelines, pathways, and protocols for easier access by healthcare providers is a first step. As automated clinical documentation systems are implemented, there is a trend to incorporate automated clinical pathways and care plans into providers’ notes. In short, clinical care plans, guidelines, pathways, and protocols, as well as drug formularies and other clinical knowledge bases, are becoming automated for easier access and use by healthcare providers, as well as for easier updating and maintenance. Many healthcare organizations purchase subscriptions from agencies, societies, or research 97 companies to gain access to peer-reviewed libraries of clinical practice guidelines and clinical knowledge bases. They do so in order to efficiently download periodic updates of this content into their transaction-based or analytic systems. The challenge for automated care plans, practice guidelines, pathways, and protocols is that, like clinical workstations and web portals, no one form of clinical documentation or one view of the information suits everyone or all situations. Therefore, automated plans, guidelines, pathways, and protocols require customization capabilities to help individuals and groups better share knowledge to reach similar decisions about patient care. Automated drawing tools and anatomical diagrams are other documentation options. Telemedicine/Telehealth Interactive, patient–provider consultations across gulfs of time and space represent what is often referred to as classic telemedicine or telehealth. However, the field has always encompassed a multitude of strategies for moving clinical knowledge and expertise instead of moving people. As such, telemedicine/telehealth systems, like EHR systems, are concepts made up of several cost-effective technologies used to bridge geographic gaps between patients and providers. In other words, telemedicine/telehealth is not videoconferencing technology. Rather, it is clinically adequate, interactive media conferencing (for example, video conferencing) integrated with other technologies. It can be dynamic and include interactive (or real-time processing) technology, or it can be static and include store-and-forward (or batch processing) technology. It includes telecommunications and remote control–based biomedical technologies. It utilizes inroom systems, roll-abouts, desktop systems, and handheld units. Often it is integrated with component technologies of the EHR system and derived technologies of the Internet. The access and ability to transmit patient records and the integration with reference databases on the Internet all play into the telemedicine/telehealth model. Telemedicine/telehealth is not a new way to deliver healthcare. It takes existing ways of delivering healthcare and enhances them, such as enhancing patient–provider consultations via “electronic house calls.” It extends care to underserved populations, whether they are located in rural or urban areas, and redefines the healthcare organization’s community. It transfers clinical information between places of lesser and greater medical capability and expertise. Like medicine in general, telemedicine/telehealth technology is made up of a number of specialties and subspecialties. Some examples include telecardiology, teledermatology, telesurgery, telepsychiatry, teleradiology, and telepathology, among many others. The telemedicine/telehealth specialty that has been around for the longest time and, perhaps, is the most notable is teleradiology. Even today, spurred by a rising demand for sophisticated imaging tests as well as a smaller pool of EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 97 12/21/12 7:19 PM 98 Chapter 4 radiologists from which to recruit, teleradiology is taking advantage of the speedy Internet transfer of medical data to outsourced radiologists who provide preliminary interpretations of scans during their normal business hours. In addition, since the early 1990s, the University of Pittsburgh Medical Center, the Mayo Clinic, and other prestigious provider organizations have employed dynamic telepathology interactions. Teleradiology and telepathology specialties are considered first-generation telemedicine/telehealth systems and services because they do not rely on patient interaction. The second-generation telemedicine/telehealth systems and services involve those specialties relying on patient interaction and consultations. These include teleophthalmology, telepsychiatry, telehome healthcare, and so on. The latest generation of telemedicine/telehealth systems and services involves patient interaction beyond the consultation. For example, in October 2001, telesurgeons in New York City performed the world’s first complete (that is, from start to finish) telesurgery by successfully operating on the gallbladder of a patient in France. This was accomplished by sending high-speed signals through fiber-optic cables across the Atlantic Ocean to robots in a Strasbourg clinic. As both a clinical and technological endeavor, telemedicine/telehealth plays a key role in the integration of managing patient care and in the more efficient management of the information systems that support it. However, overcoming multiple technical challenges remains a concern. These challenges include the lack of systems interoperability and network integration as well as metropolitan broad bandwidth limitations. Other challenges that require overcoming complex behavioral, economic, and ethical constraints are physician resistance; lack of consistent, proven cost-effectiveness; lack of consistent, proven medical effectiveness; and concerns for safety. Electronic Health Record Systems An EHR system is not one or even two or more “products.” Rather, it is a concept that consists of a host of integrated, component information systems and technologies. See chapter 5 for a full discussion of electronic health record systems—components, capabilities, selection considerations, and implementation strategies. Personal Health Records Personal health records (PHRs) electronically populate elements or subsets of protected health information (PHI) from provider organization databases into the electronic records of authorized patients, their families, other providers, and sometimes health payers and employers. A range of people and groups maintain the records, including the patients, their families, and other providers. The development of PHRs parallels the consumer-centrism described earlier and long evident in other vertical market industries, such as banking, where consumers maintain and examine their activities 24 hours a day in a secure electronic environment. PHRs come in a variety of forms and formats, with no standard design or model yet to emerge. In recent years, American Health Information Management Association (AHIMA) has vigorously promoted the use of PHRs and has provided definitions and attributes for standardization. For example, AHIMA defines the PHR as “an electronic, lifelong resource of health information needed by individuals to make health decisions. Individuals own and manage the information in the PHR, which comes from healthcare providers and the individual. The PHR is maintained in a secure and private environment, with the individual determining rights of access. The PHR does not replace the legal record of any provider” (AHIMA 2005). Currently, the most common PHR variations and models include: ●● Shared data record: The shared data record model consumes the largest number of PHRs and is the most effective. Here, both provider (or employer or health plan) and patient maintain the record. In addition, the provider (or employer or health plan) supports the record. As such, the patient receives and adds information over time. The focus of this model is to keep track of health events, medications, or specific physiological indicators, such as exercise and nutrition. ●● EHR extensions: The EHR extensions model extends the EHR into cyberspace so that an authorized patient can access the provider’s record and check on the record’s content. Often this model also allows an authorized patient to extract data from the healthcare provider’s record. The record is still maintained by the provider but is available to the patient in an online format. ●● Provider-sponsored information management: The provider-sponsored information management model represents provider-sponsored information management by creating communication vehicles between patient and provider. Such vehicles can include reminders for immunizations or flu shots, appointment scheduling or prescription refill capabilities, and monitoring tools for disease management in which regular collection of data from the patient is required. Recently, the preceding models have been enhanced by the introduction of software platforms that propose to store a patient’s PHR in a health “vault” or “bank.” Under these models, data can be added and viewed electronically by the patient and any other individuals or healthcare providers to whom the patient allows permission. Several issues are at stake. The first is whether a provider organization will be willing to work with a PHR. For example, increasing consumer demand for useful PHRs will make it mandatory that an EHR system be capable of sending and receiving data from a PHR. Another issue is whether a patient can trust the network that is transmitting his or her information. Currently, large-scale deployment and adoption EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 98 12/21/12 7:19 PM Health Information Systems: Supporting Technologies and Systems Development of Internet-based PHRs remains slow because of ongoing privacy and security challenges, especially with PHR or PHR-related software vendors that are not considered Health Insurance Portability and Accountability Act (HIPAA) “covered entities.” Such vendors cannot be held accountable to comply with HIPAA’s existing patient privacy and information security regulations. In 2002, the American Society for Testing and Materials (ASTM) Committee E31 (Healthcare Informatics), Subcommittee 26 established a standard for PHRs on the Internet. Content for the standard was based on the e-health tenets developed by AHIMA in 2000. In 2007, Health Level Seven (HL7) announced the approval of the Personal Health Record System Functional Model (PHR-S FM) as a Draft Standard for Trial Use. The PHR-S FM defines the functions that may be present in PHR systems and provides guidelines that facilitate health information exchange (HIE) among different PHR systems and between PHR and EHR systems. Web 2.0 and Web 3.0 Web 2.0 is considered the second generation of Internetbased services that emphasizes online collaboration and sharing among users. Some of these applications and technologies include blogs, social networks, content communities, wikis, and podcasts. Web 2.0 tools are characterized by being highly collaborative and participative, using multiple data sources and multimedia, and connecting communities through conversation and an open environment that is virtually available at any time. Although the first generation of Internet services was passive in nature, the Web 2.0 users are actively engaged through the creation of their own content, participating in discussions and communities, and sharing their own videos, photos, and information. In the healthcare industry, Web 2.0 technologies and tools commonly are referred to as Health 2.0. Many consumers and providers are using Health 2.0 tools to better manage their health and that of their patients. Blogs are used to share clinical education information, wikis are used as healthcare reference tools, podcasting is used to provide continuing education for healthcare providers, and social networking is used by patients to develop condition-related communities. On the other hand, legal and ethical issues must be considered with the use of such technologies and tools. For example, the privacy of the patient and the confidentiality and transparency of the information must be addressed. Additionally, liability issues and the value of intellectual property come into play. Because the nature of Web 2.0/Health 2.0 is inherently open and collaborative, Web 2.0/Health 2.0 restrictions are few, and there is little control over data and information that is available for open distribution. Consequently, while the power of the Web 2.0/Health 2.0 technologies and tools is clear, also is the importance of harnessing its power for the greater good of the healthcare industry. Technologists are beginning to discuss the concept of Web 2.0/Health 3.0. While the definitions vary widely, Web 3.0 99 will likely focus on expanding the participatory and collaborative nature of social networks that defined Web 2.0 to include more real-time video and three-dimensional elements. Other commentators argue that Web 3.0 will adopt semantic web standards, thereby allowing computers to read and generate content similar to humans. Check Your Understanding 4.4 Instructions: Answer the following questions on a separate piece of paper. 1. What features differentiate a data warehouse from a data repository? 2. Provide at least five distinct examples of diagnostic tests that involve physiological signal processing. 3. What patient data are typically collected and viewed (accessed) by care providers using point-of-care systems? 4. What is driving the increased use of computerized care protocols in healthcare? 5. Describe how second- and third-generation telehealth applications differ in functionality from first-generation applications such as teleradiology. 6. Describe the differences among the following three common models for the PHR: shared data record, EHR extensions, and provider-sponsored information management. 7. Describe the ways consumers use Web 2.0/Health 2.0 tools to manage their health and the subsequent issues that must be managed by healthcare providers. Technologies Supporting the Security of Data and Information Many current and emerging information technologies are used to support the security of healthcare data and information. They are the same technologies used to support the security of data and information in most vertical market industries. What sets the healthcare vertical market industry apart is the application of the technologies according to the second portion (Title II) of HIPAA, which mandates the protection of health information. For the purposes of this chapter, the following technologies are highlighted: ●● Encryption and cryptography ●● Biometrics technology ●● Firewall systems ●● Audit trails Encryption and Cryptography Computer technology’s greatest strengths also are its greatest weaknesses. For example, computer technology, especially EBSCOhost – printed on 1/21/2023 12:38 PM via UNIVERSITY OF MARYLAND GLOBAL CAMPUS. All use subject to https://www.ebsco.com/terms-of-use 05_AB103311_ch04.indd 99 12/21/12 7:19 PM 100 Chapter 4 the Internet and its derived technologies, easily allows anyone to send and receive information. However, it also easily allows anyone to intercept a transmission. Cryptography is an applied science in which mathematics transforms intelligible data and information into unintelligible strings of characters and back again. Encryption technology uses cryptography to code digital data and information. This is so that the information can be transmitted over communications media and the sender of the information can be sure that only a recipient who has an authorized decoding “key” can make sense of the information. There are two broad categories of encryption. The first category is symmetric or single-key encryption. Here, each computer uses software that assigns a secret key or code. One computer uses the key to code the message, and the other computer uses the same key to decode the message before the recipient can read it. This form of encryption requires both computers to have the same key. The second category is asymmetric or public key infrastructure (PKI) encryption. PKI does not require that both computers have the same key to decode messages. A private key is known to one computer, which gives a public key to the other computer with which it wants to exchange encrypted data. The public key can be stored anywhere it is convenient, such as on a website or within an e-mail. The second computer decodes the encrypted message by using the public key and its own private key. To prevent abuse, some type of authority is needed to serve as a trusted third party. A certification authority (CA) is an independent licensing agency that vouches for the individual’s identity and relationship to the individual’s public key. Acting as a type of electronic notary public, a CA verifies and stores a sender’s public and private encryption keys and issues a digital certificate or “seal of authenticity” to the recipient. These keys come in various strengths or levels of security. The strengths vary not only according to the algorithm that codes the data but also on how well the encoding and decoding keys are maintained. The more bits a key has, the harder it is to break the code without massive computer assistance. For Internet sites, the use of private and public keys is handled behind the scenes by users’ computer browsers and the web servers for the sites. For example, when a healthcare Internet user performs an online, interactive business transaction, a secure socket layer (SSL) PKI is used to exchange sensitive healthcare data and information. PKI is becoming the de facto encryption technology for secure data transfers and online authentication. As such, its use will enable healthcare organizations to meet HIPAA’s regulations concerning the security of data and electronic signatures. Biometrics Technology Biometrics technology verifies a person’s identity by measuring (comparing different mathematical representations of) biological and physical features or traits unique to the individual. For example, in signature verification technology, the biometrics of a handwritten signature are measured to confirm the identity of an individual. In data access technology, the biometrics of a hand (hand geometry), fingerprint (fingerprint matching), eye (iris or retinal scanning), voice (voice verification), or facial feature (facial image recognition) are measured to confirm the individual’s identity. Unique, positive identification or verification without the fear of replication or duplication for access to confidential health information is critical. As such, HIPAA requires a mechanism to ensure the authentication of the user and to restrict the user only to those systems that he or she is authorized to access. But because positive identification is so reliable as a personal identifier, individuals might feel that their privacy is threatened or compromised. Fingerprint matching is the oldest and most popular type of biometrics technology. Everyone has unique, immutable fingerprints made of a series of ridges, furrows, and minute points or contours on the surface of the finger that form a pattern. Retinal scanning is quite accurate because it involves analyzing the layer of blood vessels at the back of the eye. But it is not as popular an identification technology because of the close contact users must make with a scanning device and thus is unfriendly for users wearing eyeglasses or contact lenses. Iris scanning is less intrusive than retinal scanning but is considered clumsy to use. Facial image recognition requires an unobtrusive, digital camera to develop a dynamic, facial image of the user. Unfortunately, matching dynamic images is not as easy as matching static images, such as two or more fingerprints or iris scans. Therefore, positive identification based on multiple biometrics technologies currently has the most promising potential for authentication purpose…

Healthcare Information Technology Trends 

The organization I work with as a nurse largely utilizes health information technologies for patient care. The institution uses different technologies including electronic health records, telehealth, barcode system for medication administration, personalized medical records, and teleconferencing. It also utilizes the personalized tracking systems for patients with chronic illnesses such as heart disease and diabetes. The organization updates its technologies on a regular basis to ensure they are up-to-date and efficient. The technology trends in the organization are associated with a number of challenges. One of them is the high cost of updating the technologies used in the organization. The need for regular updates increases the costs incurred in the organization, which affects the sustainability of the systems (Xiao et al., 2018). The other challenge is the increased risk for loss of data during the updates and transfer of data across systems. Data loss will affect the efficiency of operations in the organization. Despite the above challenges, the technologies have several benefits for the organization (Keshta & Odeh, 2021). One of the benefits is the improvement in the safety of care given to patients. Technologies such as barcode system of medication administration have reduced significantly the risk and rate of medication errors in the organization. The technologies have also improved the efficiency of service provision in the organization (Menachemi et al., 2018). For example, electronic health records have increased the ease in access to patient data and use in making health-related decisions.  

The technologies are however associated with some risks. One of them is the increased risk of loss of data integrity. Third parties can access the private and confidential data of the patients, leading to loss of data integrity (Xiao et al., 2018). I believe that the use of telehealth in chronic disease management is one of the most promising technologies that will affect nursing practice. Telehealth technology has proven effective in improving the safety, quality, and efficiency in chronic disease management. The technology reduces healthcare costs, increased patient and provider interaction, and eliminates barriers to care for patients (Jin et al., 2019; Rutledge et al., 2021). For example, it reduces the need for unnecessary hospital visits by patients. Therefore, it will transform the future of nursing significantly.  

References UMGC Emerging Health Information Technologies Paper

Jin, K., Khonsari, S., Gallagher, R., Gallagher, P., Clark, A. M., Freedman, B., Briffa, T., Bauman, A., Redfern, J., & Neubeck, L. (2019). Telehealth interventions for the secondary prevention of coronary heart disease: A systematic review and meta-analysis. European Journal of Cardiovascular Nursing, 18(4), 260–271. https://doi.org/10.1177/1474515119826510 

Keshta, I., & Odeh, A. (2021). Security and privacy of electronic health records: Concerns and challenges. Egyptian Informatics Journal, 22(2), 177–183. https://doi.org/10.1016/j.eij.2020.07.003 

Menachemi, N., Rahurkar, S., Harle, C. A., & Vest, J. R. (2018). The benefits of health information exchange: An updated systematic review. Journal of the American Medical Informatics Association, 25(9), 1259–1265. https://doi.org/10.1093/jamia/ocy035 

Rutledge, C. M., O’Rourke, J., Mason, A. M., Chike-Harris, K., Behnke, L., Melhado, L., Downes, L., & Gustin, T. (2021). Telehealth Competencies for Nursing Education and Practice. Nurse Educator, 46(5), 300–305. https://doi.org/10.1097/NNE.0000000000000988 

Xiao, C., Choi, E., & Sun, J. (2018). Opportunities and challenges in developing deep learning models using electronic health records data: A systematic review. Journal of the American Medical Informatics Association, 25(10), 1419–1428. https://doi.org/10.1093/jamia/ocy068