THE SPECIALTY OF NURSING INFORMATICS

Within the field of health care informatics, nursing has developed the specialty of nursing informatics to delineate the contribution made by nurses in an environment of interdisciplinary teams and patient-centered care. Nursing informatics has been defined as a combination of computer science, information science, and nursing science designed to assist in the management and processing of nursing data, information, and knowledge to support the practice of nursing and the delivery of nursing care (Graves & Corcoran, 1989).

Staggers and Thompson (2002) note that in the three decades since the inception of the specialty of nursing informatics, several definitions to describe the specialty have been proposed, including definitions that are technology oriented, those that are conceptual in nature, and ones that focus on the role of nurses practicing nursing informatics. From this comprehensive analysis, Staggers and Thompson added to the definition of nursing informatics to include the concepts of integration of data, information, and knowledge to support patients. In addition, the authors recognized the importance of using technologies to support nurses’ decision making (Staggers and Thomson, 2002, p. 260).

Most recently, the American Nurses Association (2008) has endorsed the concepts from informatics pioneers and describes the field of nursing informatics as follows:

As nurses interact with consumers and other health care providers, they use a vast array of information technologies to support and enhance the care provided to clients. Consider the following case study:

Mr. Lazarus has been undergoing cancer chemotherapy for treatment of lymphoma in an outpatient oncology center. Mr. Lazarus has been experiencing cancer-related fatigue for which he is being treated with erythropoietin–alpha (Visovsky & Schneider, 2003). In the past 24 hours, he has developed fever, chills, and pleuritic chest pain and is experiencing a productive cough. He has been admitted to the hospital for suspected pneumonia. On admission, the history of Mr. Lazarus’s condition and the treatment regimen at the outpatient center are transferred electronically to establish an electronic client record.

On initial examination in the medical unit, the previous history and physical data are available to the resident physician, Dr. Cassidy, allowing him to update the client record with the information required to care for Mr. Lazarus during this acute episode of his illness. Following the initial workup, a chest x-ray is obtained and blood is drawn. While Mr. Lazarus is being evaluated by Nurse Matthews, the radiologist is reading the x-ray film and subsequently enters the results directly, using a point-of-care application that is part of a larger point-to-point integrated clinical information system. At the same time, the technician in the clinical laboratory is entering the results of the culture and sensitivity testing of the sputum sample directly into the integrated system.

Nurse Matthews and Dr. Cassidy are able to retrieve these results using the point-of-care system at the patient’s bedside. Dr. Cassidy confirms the diagnosis and prescribes the appropriate antibiotic by entering it directly into the point-of-care system. The order is transmitted to the pharmacy, where it is immediately filled and transported to the unit, allowing Nurse Matthews to begin the antibiotic treatment. Nurse Matthews has been entering Mr. Lazarus’s vital signs using a hand-held computer throughout the shift and is able to access a graphical depiction of the temperature, blood pressure, pulse, and respirations. She notes that his temperature is slowly returning to normal and his respirations are less rapid. In providing comprehensive care, Nurse Matthews logs into the database and queries the Nursing Interventions Classification related to care for patients receiving chemotherapy and receives information about nursing activities appropriate to this clinical condition.

Mr. Lazarus’s pneumonia has subsided, and he has recovered enough to return home; yet he continues to experience cancer-related fatigue. Because he lives alone, a community health nurse initially follows his care at home. In addition to monitoring Mr. Lazarus’s pulmonary and hematologic status through use of a point-of-care communication device that connects directly to the medical center, the community health nurse institutes therapies to combat the cancer-related fatigue. These interventions include receiving aromatherapy and foot soaks (Kohara et al., 2004), engaging in bedside physical therapy to prevent deconditioning (Crannell & Stone, 2008), setting priorities for essential activities, pacing his activities, and napping for short intervals as needed (Visovsky & Schneider, 2003). When Mr. Lazarus no longer requires the personal services of the community health nurse, he will be followed through a telehealth application for clinical consultations with specialists at the medical center. Mr. Lazarus makes use of a videophone that connects him directly to the medical center to receive medical and nursing care and advice. Mr. Lazarus continues to be treated directly at the medical center when needed, but his visits to the center are less frequent because he has gained access to the center via videophone.

This case study shows the seamless depiction, transmittal, and storage of data that are needed to provide the sophisticated level of care for Mr. Lazarus. Let’s take a closer look at some of the many health care informatics applications integral to nursing that support this level of care.

POINT-OF-CARE COMPUTING

Point-of-care computing allows the health care practitioner to process patient care data at the point where the service is being provided. In Mr. Lazarus’s case, the point-of-care computing took place in a variety of settings, including his bedside, the pharmacy, and the radiology department. Using point-of-care computing increases the accuracy of data capture, affords rapid processing, and decreases redundancy in record keeping. Point-of-care applications are becoming routine applications in health care settings. All point-of care technologies rely on the concept of networking. Networking means that communications equipment is used to connect two or more computers and their resources (Capron & Johnson, 2004). Networks can be classified as local-area networks (LANs) or wide-area networks (WANs). A local-area network is a computer network in a hospital, a clinic, or an office. A wide-area network is a network that provides communication services to more than one hospital, clinic, or office.

As the use of point-of-care technologies increases, nurses are concerned with how these technologies affect their workflow patterns. For example, Whittemore and Moll (2008) analyzed nurses’ opinions of the use of computers on wheels (COWs) as compared with workstations on wheels (WOWs) at All Children’s Hospital in Florida. Nurses found many workflow problems with the COWs, including the small screen size; the heavy, burdensome equipment; the lack of adequate battery power; and finally, the lack of the ability to discern how much battery life was left in the computer. The technological and ergonomic problems with the COWs led to nurses avoiding the use of the computers on wheels altogether. After asking nurses what they look for in a mobile computer, overwhelmingly, the nurses asked for “mobile workstations that had a smaller footprint, a height-adjustable work surface, the ability to add or upgrade components as needed, and the ability to provide on-screen battery-charge status” (Whittemore & Moll, 2008, p. 34). When the information technology (IT) department installed the workstations on wheels (WOWs), nurses were quick to use the system and wanted to have a system at their fingertips at all times. In a similar vein, Anderson (2009) describes how mobile carts using networking as a point-of-care technology give nurses easy access to information systems, diagnostic equipment, bar code readers, laboratory specimen analysis, and diagnostic equipment. Nationally, nurses in a number of hospitals are using mobile systems, some consisting of tablets on carts to ease use on the patient unit. Lights over the mobile system’s medication drawer enable nurses to retrieve drugs at night without turning on the light in the patient’s room. These point-of-care systems offer nurses the ability to provide care at the patient’s bedside while accessing all the relevant information needed to meet the patient’s needs and to document the impact that nursing practice has on patient outcomes. Ultimately, the use of point-of-care computing enables a more efficient means of patient assessment and treatment. Using these technologies, patients such as Mr. Lazarus have an increased likelihood of receiving quality, cost-effective care.

THE ELECTRONIC HEALTH RECORD

According to the Health Information Management Systems Society (HIMSS) (www.himss.org/ASP/topics_ehr.asp), the electronic health record (EHR) is a longitudinal electronic record of patient health information generated by one or more encounters in any care delivery setting. Included in this information are patient demographics, progress notes, problems, medication, vital signs, past medical history, immunizations, laboratory data, and radiology reports. The EHR automates and streamlines the clinician’s workflow. It has the ability to generate a complete record of a clinical patient encounter, while also supporting other care-related activities directly or indirectly via interface, including evidence-based decision support, quality management, and outcomes reporting. All EHRs include administrative components. In addition, most commercial EHRs combine data from large ancillary services such as pharmacy, laboratory, and radiology. The EHR also contains clinical care components, including nursing plans, medication administration records (MAR), and computerized patient order entry (CPOE) (MITRE Corporation, 2006). Clinical decision support can also be built into the EHR. The administrative components of the EHR include such things as registration, discharge, and transfer (RADT) data. These data are key components of the EHR and can uniquely identify an individual based on name, demographics, next of kin, employer information, chief complaint, patient disposition, and other identifying data (MITRE Corporation, 2006).

Laboratory systems are designed to interface with the EHR using a unique identifier for each patient. Radiology systems tie together patient radiology data and images. Pharmacy systems are highly automated systems that provide medications in a streamlined way to patients. The pharmacy system has built-in alerts and can be used to prevent occurrences of adverse medication interaction and decrease the chance of a patient receiving the incorrect medication or incorrect dose of a medication. Computerized physician order entry allows physicians and other care providers to order laboratory, pharmacy, and radiology services electronically (MITRE Corporation, 2006). Clinical documentation is a valuable component of the EHR and can increase the quality of care received by patients while streamlining the workflow process for care providers. Some examples of clinical documentation include physician, nurse, and other clinician notes; flow sheets; perioperative notes; discharge summaries, advance directives or living wills; and medical record/chart tracking (MITRE Corporation, 2006). Medical devices can also be integrated into the EHR and can be used to provide patient alerts and up-to-date physiological data.

A major issue in the successful implementation of the EHR is the use of standards to describe, code, and translate each piece of data residing in the EHR. Because many EHR systems use modules or systems that interact with one another, it is imperative that data be coded using a standard format so that they are interoperable—that is, data can move seamlessly within the EHR and between and among the systems that interface with the EHR. Key standards needed within the EHR are “clinical vocabularies, healthcare message exchanges, and EHR ontologies (i.e., content and structure of the data entities in relation to each other)” (MITRE Corporation, 2006, p. 9). Several clinical vocabularies play a strategic role in providing access to computerized clinical information. In a subsequent section of this chapter, a description of nursing languages and vocabularies is provided to illustrate how standards are formulated for use within the EHR. Other clinical vocabularies that are standardized for use in the EHR include the International Classification of Disease (ICD), the Systematized Nomenclature of Medicine (SNOMED), and Health Level 7. In practical terms, once the data are organized and structured in a standardized manner for the EHR, these data are then available to support health care delivery, to enhance clinician workflow, and to document patient outcomes.

Electronic health records are implemented in a variety of ways in health care settings. In Mr. Lazarus’s case, while he is being treated in the hospital, Nurse Matthews can access his EHR using a hand-held device. At the same time the nurse can use other technologies such as a pulse oximeter and a blood analyzing system to ascertain physiological measures that can assist in her assessment of his health status. These technologies can be integrated in such a way that all data are automatically uploaded into Mr. Lazarus’s EHR, which is maintained in a central location accessible through a hard-wired network.

TELEHEALTH

Demiris, Doorenbos, and Towle (2009) define telehealth as “the use of videoconferencing and/or other telecommunication technologies to enable communication between patients and health care providers separated by geographical distance” (p. 128). Two primary modes of telehealth transmission are available: (1) interactive live video and (2) the store-and-forward method. The live method is much more costly than the store-and-forward method; this is a consideration in any telehealth application. Equipment required for telehealth includes a computer platform, which is the hardware and software combination that makes up the basic functionality of a computer; a network protocol, which is a set of rules for the exchange of data between two or more computers; and an LAN and/or a WAN that allows practitioners to share data and resources among several computers over a local or wide geographical area (Capron & Johnson, 2004). Patients such as Mr. Lazarus can benefit from telehealth applications that aim at promoting independence and empowerment (Demiris et al., 2009).

Many examples of successful telehealth applications have been developed by health care practitioners. For instance, Walsh and Coleman (2005) launched a pilot telehealth program for individuals with the diagnoses of heart disease and diabetes who reside in an area within a radius of approximately 20 miles from the main office of a visiting nurse association (VNA). Initially, patients were taught to use monitoring equipment to assess daily blood pressure, glucose, and other physiological measures related to their chronic conditions. The physiological measures gathered by the patient were used as the basis for health assessment during each telehealth encounter. Video with magnifying capabilities was used to assess wounds and to monitor healing and, furthermore, to allow a nurse to view the label on medication bottles currently being used by patients in their homes while the nurse remained in the VNA main office. A unique aspect of the system is the empowerment of older adult patients to participate actively in their care from the comfort of their own homes. The telehealth system used in this pilot project demonstrated cost savings, increased patient satisfaction, and maintenance of a level of independence that, ultimately, translates into improved health status and quality of life for older adult patients experiencing chronic health problems.

Switzer et al. (2009) describe a web-based telestroke system called Remote Evaluation of Acute Ischemic Stroke (REACH) that assists in the evaluation and treatment of individuals living in rural areas in Georgia who present with symptoms of acute stroke. The web-based system allows a stroke specialist to obtain a medical history, examine the patient with live video, and review computed tomography studies. The use of this telesystem has afforded patients the opportunity to receive tissue plasminogen activator (tPA) before being transported to a tertiary medical center. The system allows physicians to make clinical decisions based on actual physiological data rather than rely on treatment using the telephone alone. As a result, outcomes for these stroke patients have been greatly enhanced.

In another telehealth application, Balamurugan et al. (2009) describe a pilot study using a telesystem to offer a diabetes self-management system for patients with diabetes living in rural Arkansas. The telehealth platform consisted of T-1 connections between the larger university hospital and the rural private hospital. The program itself utilized a tele-educational unit consisting of a combination of didactic presentation, demonstration, and interactive discussions using the American Diabetes Association–recommended curriculum for diabetes education (Balamurugan et al., 2009). The program comprised six biweekly group sessions; of the 38 enrollees in the study, 25 individuals completed the program. These individuals demonstrated improved knowledge about their diabetes, indicated more self-efficacy, and reported more frequent self-care practices to manage their diabetes. The program demonstrated that education and disease management for chronic illnesses can be achieved through a telehealth application.

Returning once again to our case study, we can see how telehealth applications could assist Mr. Lazarus to obtain high-quality care, including interactions with specialists, by means of telecommunications and the efficient receipt and transfer of data to support the nursing care he is receiving at home. Also, Mr. Lazarus can receive support by communicating with a cancer support group using technologies such as an electronic chat room wherein cancer patients share information and advice with one another.

CLINICAL DECISION SUPPORT SYSTEMS

A clinical decision support system (CDSS) is another health care informatics application that assists nurses in providing quality patient care. Anderson and Willson (2008) described a CDSS as a computer application that matches patient characteristics with an expert knowledge base to provide a solution to a clinical problem using specific recommendations embedded in the system. A CDSS increases the nurse’s decision-making effectiveness when he or she is faced with a complex clinical situation that has more than one plausible choice of treatment and a certain amount of risk associated with each of the treatment choices. CDSS may address a single complex problem, or it can be embedded within a clinical information system or an EHR to broadly address patients’ clinical problems.

Anderson and Willson (2008) reviewed nursing CDSS to determine those systems that support evidenced-based practice for nursing care. Examples of systems that support evidenced-based care include a computerized emergency triage system called the Toowoomba Adult Triage Trauma Tool (TATTT) (Ely et al., 2005); a 24-hour telephone advice line developed for advising individuals to appropriate levels of health care in the United Kingdom (O’Cathain, Sampson, Munor, Thomas, & Nicholl, 2004); and a computer-assisted system for implementing clinical practice guidelines for pressure ulcer treatment (Clark et al., 2005).

The TATTT (Ely et al., 2005) was developed to provide an evidence-based method of triage assessment and classification of patients presenting for care in an emergency setting. The system used the Australasian Triage Scale (ATS), which categorizes patients into five groups based on how severe and/or life-threatening the patient’s presenting condition is. Using this scale, patients are triaged by indicating immediately life-threatening conditions (immediate care) to less urgent (care within 120 minutes). Ten triage nurses who used the computerized TATTT (Ely et al., 2005) in a simulated setting reported that the tool accurately assessed patients, was easy to use, and increased their confidence in triaging patients in an emergency setting.

In the United Kingdom, 24 nurses were studied using a CDSS system among 12 health care sites (O’Cathain et al., 2004). The system was devised to provide safe, consistent health care recommendations regarding the most appropriate health care service to contact or to advise self-care. Nurses in the study reported that the system provided consistency in decision making among nurses with different clinical backgrounds. However, nurses noted that the system was not able to consider contextual information such as chronicity of a health problem or past medical history. In this case, if deemed appropriate, nurses were able to override the software based on their own clinical decision-making skills. Overall, the study nurses felt that both the software and the nurse were essential to clinical decision making. They described a process of ”dual decision making,“ with the nurse as active decision maker seeking confirmation or looking for agreement with the suggestions provided by the system.

The CDSS described by Clark et al. (2005) was aimed at addressing the specific complex problem of pressure ulcers, a clinical condition associated with a high level of patient suffering, as well as high health care costs. The automated CDSS implemented evidence-based clinical practice guidelines for treating pressure ulcers. The study was conducted among primary, secondary, and tertiary health care settings in a large urban health region in Canada. Nurses used the CDSS in seven health facilities (one acute, one extended care, four intermediate care, and one home care) to select optimal, evidence-based care strategies for treating pressure ulcers, as well as to record, analyze, and aggregate data related to the quality and costs of pressure ulcer treatment. The findings of the study showed that although the system was perceived as helpful related to assessing risk for pressure ulcers and developing the appropriate plan of care, nurses experienced some technical difficulties with the system and these difficulties lowered the nurses’ perception of the usability of the system. The authors concluded that with support from nursing leadership and attendance to mitigating technical difficulties, the system has potential for augmenting nurses’ decision making in caring for patients with pressure ulcer and for providing data to guide evidence-based practice.

Although the systems described here demonstrate some of the positive aspects, as well as challenges, for nursing when engaging technology in the form of CDSS, with regard to Mr. Lazarus’s case, it is likely that Nurse Matthews will use a broad CDSS for assistance in clinical decision making. Suppose Mr. Lazarus continues to experience fever, chills, and pleuritic chest pain despite the treatment for pneumonia that has been instituted. Nurse Matthews could use a clinical decision support system that is embedded in Mr. Lazarus’s EHR to relate these specific clinical findings to the condition of lymphoma. In essence, Nurse Matthews would have available the combined knowledge of many experts in the field and would be able to get immediate, specific feedback to augment her own intuitive skills. A CDSS would provide Nurse Matthews with evidence-based, objective data to assist her in understanding how a differential diagnosis is made related to these new symptoms exhibited by Mr. Lazarus.