• 21st Century Cures Act (Cures Act)
• acquisition
• alert
• analysis
• artificial intelligence (AI)
• Artificial Intelligence of Things (AIoT)
• chief information officer
• chief technical officer
• chief technology officer
• cloud computing
• cognitive science
• communication science
• computer science
• computer-based information system
• Consolidated Health Informatics (CHI)
• data
• dissemination
• document
• electronic health information (EHI)
• electronic health record (EHR)
• Federal Health Information Exchange (FHIE)
• feedback
• health information exchange (HIE)
• Health Level Seven International (HL7)
• Health New England
• Indiana Health Information Exchange (IHIE)
• information
• information science
• information system (IS)
• information technology (IT)
• input
• interface
• Internet of Things (IoT)
• Internet2
• knowledge
• knowledge worker
• library science
• Massachusetts Health Data Consortium (MHDC)
• National Health Information Infrastructure (NHII)
• Nationwide Health Information Network (NHIN)
• Next Generation Internet (NGI)
• Office of the National Coordinator for Health Information Technology (ONC)
• outcome
• output
• processing
• Rapid Syndromic Validation Project (RSVP)
• report
• social science
• stakeholder
• summary
• synthesis
• telecommunications

This chapter explores information, information systems (ISs), and information science as one of the building blocks of informatics (Figure 2-1). The key word here, of course, is information. Information and information processing are central to the work of health care. Healthcare professionals are known as knowledge workers because they deal with and process information on a daily basis to make it meaningful and inform their practice.

Figure 2-1 Building Blocks of Nursing Informatics

The four building blocks of nursing informatics include nursing science, computer science, cognitive science, and information science.

Healthcare information is complex and abounds with concerns and issues, such as ownership, access, disclosure, exchange, security, privacy, disposal, and dissemination. The widespread implementation of electronic health records (EHRs) has promoted collaboration among the public- and private-sector stakeholders on a wide-ranging variety of healthcare information solutions. Some of the collaborative initiatives that we have seen over the years include Health Level Seven International (HL7), Consolidated Health Informatics (CHI), National Health Information Infrastructure (NHII), Nationwide Health Information Network (NHIN), Next Generation Internet (NGI), Internet2, and iHealth records in the cloud. There are also health information exchange (HIE) systems, such as NHS Connecting for Health, eHealth Initiative, Federal Health Information Exchange (FHIE), Indiana Health Information Exchange (IHIE), Massachusetts Health Data Consortium (MHDC), Health New England, State of New Mexico's Rapid Syndromic Validation Project (RSVP), Southeast Michigan e-Prescribing Initiative, and Tennessee Volunteer eHealth Initiative (ASPE, n.d.; Goldstein et al., 2007; HL7 International, 2022; Western Governors University, 2021). Many of these projects and initiatives were sparked by the HITECH Act of 2011, which set the 2014 deadline for implementing EHRs and provided the impetus for HIE initiatives. In addition, the Office of the National Coordinator for Health Information Technology (ONC) is responsible for implementing key provisions of the 21st Century Cures Act (Cures Act) to promote interoperability and the access, exchange, and use of electronic health information (EHI) and information blocking (Department of Health and Human Services, 2020). It is quite evident from the previous brief listing that there is a need to remedy today's healthcare information technology (IT) concerns, challenges, and issues. One of the main issues deals with how to manage healthcare information to make it meaningful. It is important to understand how people obtain, manipulate, use, share, and dispose of information. This chapter deals with the information piece of this complex puzzle.

Suppose someone states the number 99.5. What does that represent? It could be a radio station or a score on a test. Now suppose someone says that Ms. Howsunny's temperature is 99.5°F. What does that convey? With that information, we now know that 99.5 is her temperature. The data (99.5) was processed into the information that 99.5°F is a specific person's temperature. Data are raw facts. Information is processed data that has meaning. Healthcare professionals constantly process data and information to provide the best possible care for their patients.

Many types of data exist, such as alphabetic, numeric, audio, image, and video data. Alphabetic, or alpha, data refer to letters; numeric data refer to numbers; and alphanumeric data combine both letters and numbers. These data include all text and the numeric outputs of digital monitors. Some of the alphanumeric data encountered by healthcare professionals are in the form of patients' names, identification numbers, or medical record numbers. Audio data refer to sounds, noises, or tones-for example, monitor alerts or alarms, taped or recorded messages, and other sounds. Image data include graphics and pictures, such as graphic monitor displays or recorded electrocardiograms, radiographs, magnetic resonance imaging (MRI) outputs, and computed tomography (CT) scans. Video data refer to animations, moving pictures, or moving graphics. Using these data, one may review the ultrasound of a pregnant patient; examine a patient's echocardiogram; watch an animated video for professional development; or learn how to operate a new technology tool, such as a pump or monitoring system. The data we gather, such as heart and lung sounds or X-rays, help us produce information. For example, if a patient's X-rays show a fracture, the image is then interpreted into information about the fracture, such as whether it is a spiral, compound, or hairline fracture. This information is then processed into knowledge, and a treatment plan is formulated, based on the healthcare professional's wisdom.

The integrity and quality of the data, rather than the form, are what matter. Integrity refers to whole, complete, correct, and consistent data (Figure 2-2). Data integrity can be compromised through human error; viruses, worms, or other computer bugs; hardware failures or crashes; transmission errors; or hackers entering the system. Figure 2-3 illustrates some of the ways that data can be compromised. IT helps to decrease these errors by putting safeguards into place, such as backing up files on a routine basis, error detection for transmissions, and user interfaces that help people enter the data correctly. High-quality data are relevant and accurately represent their corresponding concepts. Data are dirty when a database contains errors, such as duplicate, incomplete, or outdated records. One of the authors (D.M.) found 50 cases of tongue cancer in a database that she examined for data quality. When the records were tracked down and analyzed and the dirty data removed, only one case of tongue cancer remained. In this situation, the data for the same person had been entered erroneously 49 times. The major problem was with the patient's identification number and name: the number had been changed or the name misspelled repeatedly. If researchers had taken the number of cases in that defined population as 50, they would have concluded that tongue cancer was an epidemic, which would have resulted in flawed information that is not meaningful. As this example demonstrates, it is imperative that data be clean if the goal is to have quality information. The data that are processed into information must be of high quality and integrity to create meaning to inform assessments and decision-making.

Figure 2-2 Data Integrity

An illustration of a large sea wave symbolizes data integrity. Quality data is depicted as the wave, emphasizing attributes of being whole, complete, correct, and consistent.

Figure 2-3 Threats to Data Integrity

An illustration depicts the threats to data integrity.

The threats are as follows. Human errors like incorrect data entry and spelling errors; malware such as viruses, worms, spam, and ransomware; transmission errors involving connectivity issues, data corruption, and lost data; and machine errors including hardware failures and software crashes.

To be valuable and meaningful, information must be of good quality. Its value relates directly to how the information informs decision-making. Characteristics of valuable, quality information include accessibility, security, timeliness, accuracy, relevancy, completeness, flexibility, reliability, objectivity, utility, transparency, verifiability, and reproducibility.

Accessibility is a must; the right users must be able to obtain the right information at the right time and in the right format to meet their needs. Getting meaningful information to the right users at the right time is as vital as generating the information in the first place. The right users are those who are authorized to obtain the data and information they are seeking. Security is a major challenge because unauthorized users must be blocked while at the same time authorized users must have open and easy access. (See Chapter 12, Electronic Security.)

Timely information means that the information is available when it is needed for the right purpose and at the right time. Knowing who won the lottery last week does not help you to know whether someone won it today. Accurate information means that there are no errors in the data and information. Relevant information is a subjective descriptor in that the information must be relevant, or applicable, to the user's needs. For example, if a healthcare provider is trying to decide whether a patient needs insulin and they have only the patient's CT scan information, then the healthcare provider would not be able to make that determination because the available information is not relevant for that specific need. However, if the healthcare provider needed information about the CT scan, then the information would be relevant.

Complete information contains all the necessary essential data. For example, if a healthcare provider needs to contact the only relative listed for the patient and that relative's contact information is listed but the approval for that person to be a contact is missing, then this information would be considered incomplete. Flexible information means that the information can be used for a variety of purposes. Information concerning the inventory of supplies on a nursing unit, for example, can be used by nurses who need to know whether an item is available for use for a patient. The nurse manager accesses this same information to help decide which supplies need to be ordered, to determine which items are used most frequently, and to do an economic assessment of any waste.

Reliable information comes from clean data that are gathered from authoritative and credible sources. Objective information is as close to the truth as one can get; it is not subjective or biased but rather is factual and impartial. For example, if someone states something, then a determination must be made as to whether that person is reliable and whether what they are stating is objective or tainted by their own perspective.

Utility refers to the ability to provide the right information at the right time to the right person for the right purpose. Transparency allows users to apply their intellect to accomplish their tasks while the tools housing the information disappear into the background. Verifiable information means that one can check to prove that the information is correct. Reproducibility refers to the ability to produce the same information again.

Information is acquired by either actively looking for it or having it conveyed by the environment. All the senses (i.e., vision, hearing, touch, smell, and taste) are used to gather input from the surrounding world, and as technologies mature, more and more input will be obtained through the senses. Currently, people receive information from computers (output) through vision, hearing, or touch (input), and the response (output) to the computer (input) is the interface with technology. Gesture recognition is increasing, and interfaces that incorporate such technology will change the way people become informed. Daily, many people accessing the internet are seeking or imparting information. Individuals are constantly discovering or rediscovering, learning or relearning, or becoming informed or reinformed and purging outdated information as new information is acquired. The information acquired through these processes is added to their personal knowledge base. Knowledge is the awareness and understanding of a set of information and ways that information can be made useful to support a specific task or arrive at a decision. This knowledge building is an ongoing process engaged in while a person is conscious and going about their normal daily activities.

Information science has evolved over the past 50 or so years as a field of scientific inquiry and professional practice. It can be thought of as the science of information, studying the application and usage of information and knowledge in organizations and the interface or interaction between people, organizations, and ISs. This extensive, interdisciplinary science integrates features from cognitive science, communication science, computer science, library science, and social science. Information science is primarily concerned with the input, processing, output, and feedback of data and information through technology integration with a focus on comprehending the perspective of the stakeholders involved and then applying IT as needed. It is systemically based and deals with the big picture, rather than with the individual pieces, of technology.

Information science can also be related to determinism. Specifically, it is a response to technological determinism, which is the belief that technology develops by its own laws and realizes its own potential, limited only by the material resources available, and that it therefore must be regarded as an autonomous system that controls and ultimately permeates all other subsystems of society. In addition, “The [determinism] theory holds that the universe is utterly rational because complete knowledge of any given situation assures that unerring knowledge of its future is also possible” (Britannica, n.d., para. 1).

This approach sets the tone for the study of information as it applies to itself, the people, the technology, and the varied sciences that are contextually related based on the needs of the setting or organization. What is important is the interface between the stakeholders and their systems and the ways they generate, use, and locate information. According to Cornell University (n.d.), information science explores “the interactions between people and technology, how technology is shaping individual lives and social groups, as well as how the ways that people use technology can shape new developments” (para. 1). Information science is an interdisciplinary, people-oriented field that explores and enhances the interchange of information to transform society through communication science, computer science, cognitive science, library science, and social science. Society is dominated by the need for information, and knowledge and information science focus on systems and individual users by fostering user-centered approaches that enhance society's information capabilities by effectively and efficiently linking people, information, and technology. This collaborative user-centered approach affects the configuration and mix of organizations and influences the nature of work-namely, how knowledge workers interact with and produce meaningful information and knowledge.

Information science enables the processing of information, which links people and technology. Humans are organic ISs, constantly acquiring, processing, and generating information or knowledge in their professional and personal lives. In fact, this high degree of knowledge characterizes humans as extremely intelligent organic machines. The premise of this text revolves around this concept, and the text is organized on the basis of the Foundation of Knowledge model, whose concepts are knowledge acquisition, knowledge processing, knowledge generation, and knowledge dissemination.

Information is data that are processed using knowledge. For information to be valuable or meaningful, it must be accessible, accurate, timely, complete, cost-effective, flexible, reliable, relevant, simple, verifiable, and secure. We are in an era distinguished by the explosive proliferation of information whereby we must assess relevancy as we process information, based on our knowledge and on each specific contextual situation. Knowledge is the awareness and understanding of an information set and ways that information can be made useful to support a specific task or arrive at a decision. As an example, if an architect were going to design a building, part of the knowledge necessary for developing a new building would be understanding how the building will be used, what size of building would be needed compared to the available building space, and how many people would have or need access to this building. Therefore, the work of choosing or rejecting facts based on their significance or relevance to a particular task, such as designing a building, is also based on a type of knowledge used in the process of converting data into information. Information can then be considered data made functional through the application of knowledge. Knowledge is generative (having the ability to originate and produce, or generate) in nature. Knowledge must also be viable. Knowledge viability refers to applications that offer accessible, accurate, and timely information obtained from a variety of resources and methods and presented in a manner to provide the necessary elements to generate knowledge.

Information science and computational tools are extremely important in enabling the processing of data, information, and knowledge in health care. In the healthcare environment, the hardware, software, networking, algorithms, and human organic ISs work together to create meaningful information and generate knowledge. The links between information processing and scientific discovery are paramount. However, without the ability to generate practical results that can be disseminated, the processing of data, information, and knowledge is for naught. The ability of machines (inorganic ISs) to support and facilitate the functioning of people (human organic ISs) is what refines, enhances, and evolves nursing practice by generating knowledge. This knowledge represents five rights: the right information, accessible by the right people in the right settings, applied the right way at the right time.

An important and ongoing process is the struggle to integrate new knowledge with old knowledge to enhance wisdom. Wisdom is the ability to act appropriately; it assumes actions directed by one's own wisdom. Wisdom uses knowledge and experience to heighten common sense and insight to exercise sound judgment in practical matters. It is developed through knowledge, experience, insight, and reflection. Sometimes wisdom is thought of as the highest form of common sense, which results from accumulated knowledge, or erudition (i.e., deep, thorough learning) or enlightenment (i.e., education that results in understanding and the dissemination of knowledge). It is the ability to apply valuable and viable knowledge, experience, understanding, and insight while being prudent and sensible. Knowledge and wisdom are not synonymous because knowledge abounds with others' thoughts and information, whereas wisdom is focused on one's own mind and the synthesis of one's own experience, insight, understanding, and knowledge.

If clinicians are inundated with data without the ability to process them, the situation results in too much data and too little wisdom. Consequently, it is crucial that clinicians have viable ISs at their fingertips to facilitate the acquisition, sharing, and use of knowledge while maturing their wisdom, and it is this process that leads to empowerment.

Information science is multidisciplinary in that it encompasses aspects of computer science, cognitive science, social science, communication science, and library science to deal with obtaining, gathering, organizing, manipulating, managing, storing, retrieving, recapturing, disposing of, distributing, and broadcasting information. Information science encompasses everything that pertains to information and can be defined as the study of ISs. This science originated as a subdiscipline of computer science as practitioners sought to understand and rationalize the management of technology within organizations. It has since matured into a major field of management and is now an important area of research in management studies. Moreover, information science has expanded its scope to examine the human-computer interaction and the interactions of people, ISs, and corporations. It is taught at all major universities and business schools worldwide.

Modern-day organizations have become intensely aware of the fact that information and knowledge are potent resources that must be cultivated and honed to meet their needs. Thus, information science, or the study of ISs-that is, the application and usage of knowledge-focuses on why and how technology can be put to best use to serve the information flow within an organization.

Information science affects information interfaces and influences how people interact with information and subsequently develop and use knowledge. The information a person acquires is added to their knowledge base. Knowledge is the awareness and understanding of an information set and the ways that information can be made useful to support a specific task or arrive at a decision.

Healthcare organizations are affected by and rely on the evolution of information science to enhance the recording and processing of routine and intimate information while facilitating human-to-human and human-to-system communication, delivery of healthcare products, dissemination of information, and enhancement of the organization's business transactions. Unfortunately, the benefits and enhancements of information science technology have also brought to light new risks, such as glitches, loss of information, and hackers who can steal identities and information. Solid leadership, guidance, and vision are vital to the maintenance of cost-effective business performance and safe, cutting-edge information technologies for the organization. This field studies all facets of the building and use of information. The emergence of information science and its effect on information have also influenced how people acquire and use knowledge.

Information science has already had a tremendous effect on society and will undoubtedly expand its sphere of influence further as it continues to evolve and innovate human activities at all levels. What visionaries only dreamed of is now possible and part of reality, but the future has yet to fully unfold in this important arena.

Consider the following scenario: You have just been hired by a large healthcare facility. You enter the personnel office and are told that you must learn a new language to work on the unit where you have been assigned, a language that is particular to this unit only. If you had been assigned to a different unit, you would have needed to learn another language that is specific to that unit, and so on. Because of the differences in various units' languages, interdepartmental sharing and information exchange (known as interoperability) are severely hindered.

This scenario might seem far-fetched, but it is how workers once operated in health care-in silos. There was a system for the laboratory, one for finance, one for clinical departments, and so on. As healthcare organizations have come to appreciate the importance of communication, tracking, and research, however, they have developed or purchased ISs that can be integrated to handle the needs of the entire organization.

Information and IT have become major resources for all types of organizations, and health care is no exception (Table 2-1). IT helps to shape a healthcare organization in conjunction with personnel, money, materials, and equipment. Many healthcare facilities have hired chief information officers (CIOs) or chief technical officers (CTOs), also known as chief technology officers. The CIO is involved with the IT infrastructure, and sometimes this role is expanded to include the position of chief knowledge officer. The CTO is focused on organizationally based scientific and technical issues and is responsible for technological research and development as part of the organization's products and services. The CTO and CIO must be visionary leaders for the organization because so much of the business of health care relies on solid infrastructures that generate potent and timely information and knowledge. In some organizations, the CTO and CIO positions are interchangeable, but in others the CTO reports to the CIO. These positions will become critical roles as companies continue to shift from being product to knowledge oriented and as they begin emphasizing the production process itself rather than the product. In health care, ISs must be able to handle the volume of data and information necessary to generate the needed information and knowledge for best practices because the goal is to provide the highest-quality patient care.

ISs deal with the development, use, and management of an organization's IT infrastructure. An IS acquires data, or inputs; processes data through the retrieval, analysis, or synthesis of those data; disseminates, or outputs, the data in the form of reports, documents, summaries, alerts, or outcomes; and provides for responses, or feedback. Quality decision-making and problem-solving skills are vital to the development of effective and valuable ISs. Today's organizations now recognize that their most precious asset is their information, as represented by their employees, experience, competence, and innovative approaches, all of which are dependent on a robust information network that encompasses the IT infrastructure.

In an ideal world, all ISs would be fluid in their ability to adapt to any and all users' needs. They would be internet oriented and global so that resources are available to everyone. Think of cloud computing. It is just the beginning point from which ISs will expand and grow in their ability to provide meaningful information to their users. As technologies advance, so will the skills and capabilities to comprehend and realize what ISs can become. As wearable tracking technologies and other health-related mobile applications expand, more robust and timely health data will be generated, and these data will need to be processed into meaningful information. “Practitioners and medical researchers can look forward to technologies that enable them to apply data analysis to develop new insights into finding cures for difficult diseases. Healthcare CIOs and other IT leaders can expect to be called upon to manage all the new data and devices that will be transforming healthcare as we know it” (Schindler, 2015, para. 2). Devices with sensors communicating with each other are collectively known as the Internet of Things (IoT), which expands the future possibilities for health care tremendously. The IoT is made up of complex social, technical, procedural, and policy considerations that are constantly evolving for a variety of users such as healthcare professionals (Airtel Business, 2022). The IoT enables the connecting and exchanging of data with other devices and systems from anywhere to anywhere. This IoT can share and collect data and information with minimal human intervention. Essentially, the sensor-collected data are transmitted to another technology, which triggers an action or an alert that prompts feedback for an action. Now think about the combination of artificial intelligence (AI) and the IoT, called the Artificial Intelligence of Things (AIoT), which represents the nurturing of the development of the intellectual properties of the devices we use. This blending of AI and the IoT infrastructure helps us attain more efficient and effective operations, enhances human-technology interfacing and interactions, and improves data and information management and analytics (Dhi Energy, 2022). It will be important to follow the continued evolution of AIoT within and outside of the healthcare arena. It is essential to continue to develop and refine functional, robust, and visionary ISs that meet the current meaningful information needs while evolving systems that are even better prepared to handle the future information and knowledge needs of the healthcare industry.