UMGC Emerging Health Information Technologies Paper

UMGC Emerging Health Information Technologies Paper
Sample Answer for UMGC Emerging Health Information Technologies Paper Included After Question

UMGC Emerging Health Information Technologies Paper

Description

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.?

UMGC Emerging Health Information Technologies Paper
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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A Sample Answer For the Assignment: UMGC Emerging Health Information Technologies Paper
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 t