3
Computer-Based Patient Record Technologies

User needs, both of individuals and of cohesive communities, are paramount in the design and development of computer-based patient record systems. Designers and vendors of CPR systems must understand such needs, as well as how the systems will be used and what demands users will place on the systems. The discussion of user requirements in Chapter 2 sets the stage for explaining in this chapter the attributes of technologies required to create CPR systems in the 1990s.

This chapter has three main goals: (1) to highlight technologies relevant to CPR systems, (2) to convey what is possible with existing technologies, and (3) to emphasize what will be required to build state-of-the-art CPR systems in the 1990s. The chapter also provides some insight into the current state of existing clinical information systems that possess features crucial to the development of state-of-the-art CPR systems. Finally, it discusses the technological barriers that still must be overcome before CPR systems can become well established.

Technological Building Blocks for CPR Systems

No clinical information system in 1990 is sufficiently comprehensive to serve as a complete model for future CPR systems. That is, no operational clinical information system in 1990 can manage the entire patient care record with all its inherent complexities. A few existing clinical information systems are beginning to approach the CPR system capabilities envisioned by the committee. None of these is yet complete, but some might appropriately be called today's CPR systems. Therefore, the committee sometimes



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--> 3 Computer-Based Patient Record Technologies User needs, both of individuals and of cohesive communities, are paramount in the design and development of computer-based patient record systems. Designers and vendors of CPR systems must understand such needs, as well as how the systems will be used and what demands users will place on the systems. The discussion of user requirements in Chapter 2 sets the stage for explaining in this chapter the attributes of technologies required to create CPR systems in the 1990s. This chapter has three main goals: (1) to highlight technologies relevant to CPR systems, (2) to convey what is possible with existing technologies, and (3) to emphasize what will be required to build state-of-the-art CPR systems in the 1990s. The chapter also provides some insight into the current state of existing clinical information systems that possess features crucial to the development of state-of-the-art CPR systems. Finally, it discusses the technological barriers that still must be overcome before CPR systems can become well established. Technological Building Blocks for CPR Systems No clinical information system in 1990 is sufficiently comprehensive to serve as a complete model for future CPR systems. That is, no operational clinical information system in 1990 can manage the entire patient care record with all its inherent complexities. A few existing clinical information systems are beginning to approach the CPR system capabilities envisioned by the committee. None of these is yet complete, but some might appropriately be called today's CPR systems. Therefore, the committee sometimes

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--> refers to current CPR systems, meaning those clinical information systems that are beginning to approximate the ideal CPR system envisioned by the committee for the future (see Chapter 2). The committee selected and reviewed nine technologies that are significant for CPR systems. They include (1) databases and database management systems, (2) workstations, (3) data acquisition and retrieval, (4) text processing, (5) image processing and storage, (6) data-exchange and vocabulary standards, (7) system communications and network infrastructure, (8) system reliability and security, and (9) linkages to secondary databases. This section describes the key attributes of these crucial technologies. Databases and Database Management Systems It is important to distinguish between the clinical data—that is, the computer-based patient record, or CPR—and the system that captures and processes those data—that is, the CPR system. CPR functions relate to the collection of data, such as patients' medical problems, diagnoses, treatments, and other important patient information, including follow-up data and quality measures. CPR system functions relate to storage capacity, response time, reliability, security, and other similar attributes, but the system relies on the collection of clinical data, the core CPR, to support virtually all of its activities. Databases The most desirable database model for CPR systems involves either (1) a distributed database design—that is, a system with physically distributed computers and databases but with logical central control of the entire record; or (2) a centrally integrated physical database design—that is, a centrally located, complete CPR within a single computer-stored database (see Figure 3-1);1 or (3) some hybrid or mix of these two approaches. In any case, the key requirements are central control and organizational integrity of the entire record for each individual patient. Central control permits authorized persons using a terminal located anywhere in the information system to access the entire integrated patient record or any of its parts, regardless of the locations of any other departmental subsystems where the various data items may have originated. (Access is allowed only on the basis of parameters specific to authorized users.) 1   The selection of the database management system that undergirds a CPR system is critical to the performance and success of the system. Several publications during the past decade have discussed this issue: Barnett et al. (1982); Pryor et al. (1983), Wiederhold (1986), Kirby et al. (1987), McDonald et al. (1988), Whiting-O'Keefe et al. (1988), Wilton and McCoy (1989), Canfield et al. (1990), Friedman et al. (1990), and Hammond et al. (1990).

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--> FIGURE 3-1 Centralized vs. distributed computer-based patient record.

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--> Although the feasibility of the distributed database design (see the righthand panel of Figure 3-1) has recently gained support from the development of networking technologies, most current clinical information systems that might qualify as CPR systems use a centralized design (the left-hand panel of Figure 3-1). The CPR systems of today cannot as yet acquire and retrieve all patient care data directly. Instead, they rely on data transmitted to the CPR system through interfaces with departmental subsystems; the data are subsequently entered into the CPR using applications programmed on the CPR system. One major factor that differentiates current CPR systems is the extent to which they use local area networks, or LANs, to access departmental subsystems and stand-alone databases containing portions of the CPR. Today's CPR systems place great emphasis on providing at least a ''view" of a complete, centralized patient record (Hammond et al., 1990). If the patient's clinical data are physically distributed among several computers in a network, a comprehensive view of the record of a given patient can be achieved only by retrieving and assembling the pertinent data from each computer on the network where patient data reside. Although this scenario has a number of advocates and some advantages, it also has several severe problems (Margulies et al., 1989; Hammond et al., 1990). A careful analysis of the two contrasting models shown in Figure 3-1 may be helpful in understanding the main problems. In the distributed system, the patient record is physically distributed among several computer systems but at the same time is functionally integrated. This means that a variety of distributed patient care applications will generate and use patient care data in the distributed CPR. It also means that individual records may require multiple data structures (or data files), which tends to lengthen data retrieval times. Another problem with a distributed system is that data synchrony—that is, the correct sequencing of a patient's time-stamped data that are entered into the system at the same time but from different sources—must be guaranteed at both the applications and the database management system (DBMS) levels. Perhaps the most significant problem with the distributed database approach, however, is the increased potential it carries for circumventing CPR confidentiality mechanisms. Because portions of the patient's record are distributed among several different computers, ensuring confidentiality becomes more difficult. Every computer has its own vulnerabilities, and each one that is added to a network represents another node that must be protected and another potential entry point for unauthorized access (National Research Council, 1991). Database Management Systems A major technological issue is the complexity of the data that will eventually reside in the CPR. The CPR of the future will consist of many

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--> different kinds of data, including text, graphics, images, numerical data, sound, and full-motion video. To design a functionally integrated database system that accommodates such diversity is a sizable technical challenge. The CPR is so complex that no single database management system is capable of optimally storing and retrieving the full range of patient data (Hammond et al., 1990). As a result, CPR system developers have used a variety of complementary DBMSs to address these complexities. This multiple-DBMS approach is most common when the CPR system uses the distributed database scenario; in that case, each subsystem often uses a different DBMS. Because the CPR is distributed across many connected subsystems, each subsystem will probably use a DBMS that is particularly suited to the kind of data most frequently stored in that subsystem. The collection of appropriate databases that results offers advantages of efficiency in manipulating and storing the CPR complex data. Some CPR system developers have even created their own proprietary database management systems, tailored to the CPR's particular complexities. The selection or creation of the DBMS that will support the CPR is among the first and most crucial steps in developing a CPR system. Several database management systems or architectures have evolved in recent years. Four important ones developed by commercial vendors are hierarchical, relational, text-oriented, and object-oriented databases. Each of these architectures has its own particular strengths and weaknesses. Architects of current CPR systems (both commercial and private) have mainly used hierarchical, relational, or text-oriented models. Viable object-oriented database management systems have been introduced only recently and are not yet in widespread use. Workstations Three general classes of workstations seem likely to prevail in future CPR systems. First, "smart" terminals with data entry pointer/selector devices (e.g., mouse, touch-screen, light-pen, or voice) will be used for data input and retrieval; they may also support "windowing" and medium-resolution imaging. These terminals will use a graphical user interface (GUI) and communicate with file servers, compute servers, and rule servers2 in a local area network 2   As computers have become smaller, more powerful, and more affordable, individual computer systems have been dedicated to functions common to many applications and users in a network. For example, data files may be stored in a computer dedicated to serving the filing needs of network users, hence the name file server. Similarly, network users executing computationally intensive applications (e.g., three-dimensional reconstruction of images of an artery) require access to computers capable of serving rapid computation needs, hence the name compute server. Another commonly needed capability on a network is access to systems capable of rapidly executing rules for decision support, hence the name rule server. As medical decision support systems become more robust, rule servers will play an increasingly important role in health care network.

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--> Second, hand-held terminals or computers, or other similar semiportable devices, will facilitate either manual or voice entry of data into the CPR. These relatively portable devices will be used at the bedside by practitioners. Third, fully configured workstations (e.g., complete with a mouse, accelerated processors, GUI, and large storage capacities) may well become one of the more powerful tools ever devised for health care professionals and may ultimately come to be considered indispensable. Data Acquisition and Data Retrieval Data Acquisition Data acquisition for the CPR remains an exceptionally challenging topic within the field of medical informatics.3 Ideally, data in the CPR should be entered at its source (e.g., the site of patient care) by the record's primary user; they should be entered only once, and they should be accessible to all portions of the CPR system that use that particular data item. Data entry at the source by members of the health care team remains a sensitive issue. Yet the most commonly used alternative, data entry by an intermediary (e.g., a clerk or a transcriptionist) has several disadvantages: (1) it often introduces errors because the person who has direct information about the patient is not the person entering the data; (2) it delays the timely availability and transmittal of potentially critical information; (3) it makes immediate feedback to health care professionals (in the form of alerts or alarms generated by detectable errors or conflicting orders) impossible; and (4) it interferes with the decision maker's ability to use linked databases and other on-line knowledge bases designed to assist health care professionals in the clinical decision making process. Two keys to the success of next-generation CPR systems are ease of use and proper incentives for data entry at the data source (Young, 1987; Safran et al., 1989). Data Retrieval The organization of data displays that can quickly convey crucial information needed in a particular setting (e.g., in the intensive care unit) or by a certain user (e.g., a surgeon) is also a challenge (Stead and Hammond, 1987; Silva et al., 1990). Because much of the patient record can be presented as text, tables, or graphs (e.g., trends in laboratory values), most CPR systems today display data on low-cost monitors capable of high-resolution 3   Greenes and Shortliffe (1990) define medical informatics as "the field that concerns itself with the cognitive, information processing, and communication tasks of medical practice, education, and research, including the information science and technology to support these tasks."

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--> graphics. Although these displays cannot deliver, for example, high-definition radiological images, they can produce hard-copy printouts of display screens, graphs and tables, and signals such as those needed for an electrocardiogram (ECG). A complete on-line CPR reduces the necessity for printing multipart copies of these printouts. A short response time has proven to be an important factor in successful CPR systems (Bleich and Slack, 1989). This requirement refers primarily to retrieving data, but it is equally important for inputting data. In future CPR systems, the displays and reporting formats of CPR data are likely to be configured or modified by users. Thus, the same data may be presented differently, or in different combinations, to different health care professionals, each of whom has differing "views" or "windows" into the same CPR (see Chapter 2). Customizing data in this way is a difficult capability to implement but will produce a system that is much more attractive to end users. Text Processing To establish a diagnosis, physicians and other health care professionals use patient information in a textual form—for example, the patient history and the results of the physical examination. With a CPR system, professionals search for and retrieve such text from database systems using query languages, which in the past were often idiosyncratic to a particular system. In recent years, gradual progress has been made in standardizing such languages. Natural language understanding, or the ability of the computer system to selectively extract meaning from textual data, has been slower to evolve because of its inherently greater complexity (Obermeier, 1989). Compounding this complexity is the slow development of efforts to encourage a more uniform vocabulary in health care. Automated speech-recognition systems may help to add uniformity and consistency to vocabularies for the CPR by encouraging the speaker to use clinically relevant, yet consistent, terminology. In the 1990s, text-processing systems for translating the narrative found in discharge summaries and other parts of the CPR are likely to be used to generate codes for billing. As text-processing systems improve in accuracy and performance, they may be used to extract significant phrases or attributes from the CPR that could assist the user in searching related databases. For example, attributes derived from the CPR might be matched against the terms and concepts in the National Library of Medicine's (NLM) Unified Medical Language System (UMLS; Humphreys and Lindberg, 1989). Improved text-processing systems would make it possible to use data from the CPR, in conjunction with the UMLS, to lead practitioners

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--> to an array of related information sources, including medical literature and other pertinent knowledge bases (Lindberg and Humphreys, 1990). Image Processing and Storage Medical imaging today includes diagnostic images or pictures obtained by film scanners, computed radiography (CR), magnetic resonance (MR), computed tomography (CT), ultrasound, and nuclear medicine sources. The medical images generated by these technologies and found in today's patient records are typically two-dimensional, still pictures. The increasing digitization of data, however, will expand the capabilities of such technologies. For example, digital data permit varying intensity resolution (number of measurable levels of gray), which allows the computer to display images with medium to high contrast. In the near future, digital images will be routinely available in many radiology departments. New technological developments are expected to lead to a new generation of picture archiving and communications systems (PACSs), which will be installed in many radiology departments by the mid-1990s. PACSs permit the electronic storage, transmission, and display of medical images throughout a medical facility and offer many advantages not available with conventional film. For example, two or more physicians can simultaneously examine exact duplicates of an image at their respective and sometimes distant locations, discuss the interpretation of the image, and together formulate plans for optimal patient management. Imaging systems in the near future will eliminate concerns about the current status or location of an image, such as "missing" or "in transit." Imaging is routinely used not only radiologists but also by ophthalmologists, dermatologists, pathologists, dentists, and other specialists. Indeed, images have become an essential part of the complete patient record. Yet although the record is incomplete without images, the typical paper record environment stores images separately from the chart itself. CPR systems of the future, when appropriately linked to PACSs, will allow health care professionals to view images at the computer workstation in a timely fashion. Data-Exchange and Vocabulary Standards In today's health care environment, health care professionals, managers, policymakers, regulators, and educators need increasing amounts of accurate health care data in machine-readable form to support intelligent decision making. All such data must be collected, aggregated (when they come from diverse sources), and transmitted among disparate systems. The

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--> aggregation and dissemination of existing and future health care data mandate the development of standards, both to exchange health care data and to encourage more consistent medical vocabulary, especially in those portions of the CPR containing natural language text. Developing such standards requires a coordinated approach. Efforts to develop data-exchange standards for components of the CPR have only recently gained significant momentum in the United States. Because so much is at stake in this sizable medical market—a market that remains largely untapped from the vendors' point of view—standards take on an even more prominent role in fostering the evolution of the required technologies. Currently, there are several related efforts to standardize and facilitate the exchange of health data. HL 7 and Medix, as well as standards from the American Society for Testing and Materials (ASTM), the American College of Radiologists/National Electrical Manufacturers Association (ACR/NEMA), and others are representative of the current movement to formulate data-exchange standards.4 Several promising vocabulary developments are relevant to CPR systems. These include a planned new edition of the Systematized Nomenclature of Medicine (SNOMED); the Read Clinical Classification in Great Britain; the ASTM Standard Guide for Nosologic Standards and Guides for Construction of New Biomedical Nomenclature, which is now completed and ready for distribution (ASTM, 1989); and the NLM's UMLS project. The overall goal of UMLS is to help users retrieve relevant biomedical 4   HL 7 is a specification for a health data interchange standard designed to facilitate the transfer of health data resident on different and disparate computer systems in a health care setting. For example, HL 7 facilitates the transfer of laboratory results, pharmacy data, and other information for a patient to a central hospital system without concern for whether such systems are supplied by the same vendor or manufacturer. HL 7 is not, however, designed to support the transfer of the entire patient record. For example, it does not address the transfer of image data (such as those from a PACS). The Institute of Electronic and Electrical Engineers (IEEE) has begun to develop Medix, a comprehensive health data-exchange standard. It is the only standard for which its developers have stated an objective of eventually supporting transfer of the entire patient record, although it is not yet mature enough to do so routinely in a health care setting. Medix is also the only health care data standard that has declared an intention to support the International Standards Organization's (ISO) Open Systems Interconnect (OSI) model. ASTM has sponsored committees (e.g., E 31.12 and E 31.14) on computerized systems that are dedicated to standards directly related to the transfer of clinical data, such as those found in the patient record. Among other topics, these ASTM standards committees have focused on naming conventions and have proposed data element names for clinical data found in the patient record. They have also addressed specifications for transferring clinical laboratory data messages between independent computer systems. ACR/NEMA have joined together to establish a functioning standard designed to transfer images between disparate computer systems (especially different PACSs).

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--> information from multiple machine-readable sources, even though different vocabularies and classifications may have been used in these sources. One of the new knowledge sources being developed to support this goal is a metathesaurus, which will link related terms and concepts from a variety of existing biomedical vocabularies and classifications. System Communications and Network Infrastructure Caring for patients naturally requires many health care workers to interact frequently. As discussed in Chapter 2, health care is information-intensive, which implies a strong emphasis on the communication and transmission of information to many people in diverse places. The patient information conveyed is complex and appears in all possible modalities, including text, images, voices and sounds, signals, and video. This board array of information needs to be available in such diverse locations as the bedside, the hospital department, professional offices, emergency settings including mobile units, and the home. Technologies to support communications of all kinds are evolving at an unprecedented rate. With the advent of fiber optics, in particular, transmitting the diversity of information contained in the CPR will soon be feasible at high-speeds and low-costs. Of great significance is the evolving Integrated Services Digital Network (ISDN), an all-digital network capable of high-speed transmission of all modalities (data, voice, graphics, or video) over public telephone networks. In the 1990s, the transition from analog to fully digital switches is expected to occur throughout much of the United States. This transition to an all-digital network, when complete, will have wide-ranging implications for improving health care because it will open a new era for communication of all types of information, including that contained in the CPR. System Reliability and Security Chapter 2 presented brief explanations of system reliability, system security, and data security. System security is achieved through appropriate system design and the use of physical security measures directed toward protection of the computing environment and equipment. For example, techniques for security include software and hardware features, physical measures such as locks and badges, identification numbers or codes, passwords, and an informed, security-conscious staff (National Research Council, 1991). A data integrity control policy has at least four essential components: (1) security measures, (2) procedural controls, (3) assigned responsibility, and (4) audit trails. It is especially important to allow access to the CPR system

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--> only to those with a need to know and to certify their identity before permitting access. In addition, the CPR system must be capable of providing different levels of data confidentiality as required for its various users. Audits of all legitimate users of CPR systems must be conducted regularly to remind and assure patients and staff that strict confidentiality is being maintained and measured. Such periodic audits should help deter any attempts by staff to breach confidentiality. Members of the health care team who record patient data in the record are responsible for such entries, but in a hospital or clinic, physicians typically still have primary responsibility for ensuring the record's accuracy. As documentation of health care shifts from paper to computer-based records, practitioners will maintain their responsibility to document patient care, but the data will reside within CPR systems. Legal, professional, and accrediting standards must be revised to specify appropriate new roles and responsibilities associated with the shift from the paper chart to the CPR. In the aggregate, current CPR systems seem to use limited measures for ensuring patient confidentiality. Most CPR systems do not approach the levels of security or confidentiality that airlines or banks, for example, maintain to protect their less sensitive information. Future CPR systems must implement stricter measures to protect confidentiality (National Research Council, 1991). Linkages to Secondary Databases Many clinically relevant registries and databases have evolved in recent years and are of particular interest to health care professionals as they attempt to improve the quality of patient care. Increasingly, these collections of secondary data will be extracted from primary data in CPRs in such a way as to protect the confidentiality and identity of individual patients. Thus, patient records will collect all data on all problems for a single patient; clinical research databases will collect all data on one problem for many patients. For policymakers, the secondary collection of relevant (nonconfidential) clinical information on large populations of patients will support their development of policy strategies and general assessments of quality and outcomes of care. Hundreds of databases are available or are now evolving; some of these resources should be linked with the CPR to provide clinical decision support when needed. Some current CPR systems already offer linkages to knowledge and research databases. Most CPR systems, however, lack this capacity, owing primarily to the complexity and cost of developing such linkages. Health care professionals are beginning to appreciate the support offered by timely access to a diverse array of external information sources in providing care.

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--> Second, systems should be speaker independent; that is, the system should be able to recognize words spoken by any individual who might speak without first ''training" the system to recognize the words spoken by that individual. Third, systems for general medicine require large vocabularies; some domains and subdomains, for example, may require vocabularies in excess of 30,000 words or meaningful phrases. As vocabularies expand, both the costs and error rates generally become intolerable. Emerging voice-recognition technology is likely to ease the inputting of clinical data in future CPR systems, but the successful experiences discussed earlier with such systems as HELP, THERESA, and DIOGENE confirm the existence of currently available alternative approaches to capturing crucial clinical data (including text) in the CPR. Text Processing Assuming that text can be conveniently entered into the clinical system through voice-recognition technology or other means, the problem then becomes one of effectively analyzing in an automated way the content and meaning of the textual data. The raw material for epidemiological analysis and for effectiveness and outcomes studies is primarily text from patient records, which must be converted to coded data. For accurate comparisons, patient record data must be correctly transformed into precise, unambiguous codes that represent specific characteristic processes. Text processing is generally considered to be a complex operation; its application to the data in the CPR, with its special and diverse vocabularies, further complicates the challenge of implementing it as a system capability. Often, the more experienced the practitioner, the more succinct or abbreviated the notes in the record. The notes thus may consist of abbreviations, acronyms, and mnemonics, which could be difficult to interpret, even by other health care professionals. Although text processors have improved markedly in recent years, they can approach but never exceed the quality of written or dictated information. Therefore, the quality of patient records can be improved only through more disciplined approaches to consistent vocabulary in the record. Although technology (voice-input or menu-driven input systems) can artificially impose more consistent terminology, practitioners should be encouraged as a rule to avoid idiosyncratic terminology and to use more formal, well-defined vocabularies. Additional technological research is needed in this area, as well as studies of incentives for behavioral change, before CPR systems can reach their full potential. Confidentiality and Security Among the important priorities for the 1990s is the further development

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--> FIGURE 3.2 Three-zone confidentiality model. of technology to ensure fully the privacy and confidentiality of patient data in the CPR. Indeed, as discussed in Chapter 4, societal and legal concerns about privacy and confidentiality must be satisfactorily resolved before wide-scale implementation of the CPR can occur. Many technologies are available to ensure CPR security and integrity, but, in general, they have not been adequately deployed or embedded in present CPR systems. Recent research has proposed a three-zone medical confidentiality model (Figure 3-2). In this model, extremely sensitive information, which would always be held confidential, resides in the innermost zone and might not always find its way into the CPR. The outermost zone contains the least sensitive information, which may or may not be confidential. The area between these two zones is the one containing sensitive information, probably related mainly to illnesses and health problems; it is likely to be the largest area in terms of volume of the CPR and the one most frequently associated with traditional medical confidentiality requirements. The figure illustrates why CPR systems must address confidentiality adequately at multiple levels. Patients should be permitted to name the portions of their record that are to remain totally confidential (i.e., the innermost information zone). Practitioners may also designate elements of the CPR as highly confidential. Most of the emphasis on confidentiality has involved protecting patient-related information in the CPR, but confidentiality

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--> issues may also pertain to others engaged in providing health care. For example, all members of the health care team deserve the same level of protection against unauthorized access or abuse of information in the CPR that applies to the patient. One important method for ensuring confidentiality, and data and program integrity, is to allow access to the CPR system only to those with a need to know and then to certify positively their identity before granting access. Fortunately, the problem of implementing measures to ensure confidentiality and privacy is not unique to medicine. Confidentiality issues are important in several areas outside health care such as finance and banking, libraries, and communications, and these sectors may offer approaches that could be tailored to the needs of health care users. For example, future CPR systems must be capable of providing different levels of data confidentiality as required by their users. Psychiatric data are a case in point: they must be available only to the patient's psychiatrist. In addition, some sensitive data for drug abuse, alcoholism, and similarly sensitive diagnoses must be protected by legal and professional rules and regulations. Health Data-Exchange Standards Progress toward developing acceptable standards for transferring an entire CPR has been slow, primarily because standards development has been largely ad hoc. Still, although such progress is meager in comparison to what is needed, it appears impressive when one considers that it has been accomplished virtually without government funding and without substantial industry-wide commitment. Nevertheless, the lack of funding for and coordination of standards development for CPRs can constitute a major barrier to CPR development, testing, and deployment. What is perhaps of even greater concern, given the current limited support for standards development, is the potential long-term negative impact of premature standards development. Without substantially better coordination and greater funding relatively soon, standards may evolve that may later prove to be inadequate, and neither as well conceived nor as robust as the standards needed to support a broad array of future CPR applications. Before an actual exchange of clinical data can take place, agreement must be reached on what is being transferred. Many vendors and government agencies have independently developed their own internal clinical data dictionaries. These dictionaries differ in terms of the actual data elements included, naming conventions, definitions, and relationships among data elements. No attempt has yet been made to create a composite clinical data dictionary (CCDD) using input provided by these and other groups interested in the CPR (Figure 3-3). For example, the federal government alone has at least three distinct clinical data dictionaries (namely, those of DoD, the VA, and the Health Care

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--> FIGURE 3-3 Concept of a composite clinical data dictionary. Abbreviations: ACR/NEMA, American College of Radiologists/National Electrical Manufacturers Association; AHA, American Hospital Association; AMA, American Medical Association; AMIA, American Medical Informatics Association; AMRA, American Medical Record Association; ANA, American Nurses Association; ASTM, American Society for Testing Materials; DoD, Department of Defense: HCFA, Health Care Financing Administration; IEEE, Institute of Electronic and Electrical Engineers; ISO, International Standards Organization; JCAHO, Joint Commission on Accreditation of Healthcare Organizations; VA, Department of Veterans Affairs. Financing Administration); each of these has evolved independently and largely without coordination. Because no CCDD yet exists, the evolution of data-exchange standards has been limited and will remain so until a CCDD or some similar coordinating mechanism is developed. Once a CCDD is created and perpetually maintained, any number of relevant subsets can be generated from this defined universe of clinical content. Standard definitions of subsets (or "templates," as shown in Figure 3-3) can be prepared, and data-exchange standards can then be used to carry

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--> out the actual data transfers. For example, one potential template might be HCFA's Uniform Clinical Data Set (UCDS), a collection of approximately 1,600 data elements (Krakauer, 1990). Over time, many other relevant data sets for varied purposes are likely to be generated using subsets from the universe of data elements defined in the CCDD. For example, emergency room (ER) physicians might designate a small set of clinical data elements from the CCDD (such a subset could be the ER template) that are required to facilitate appropriate care in an emergency setting. This template could then be used to formulate an appropriate health data-exchange standard to perform the actual transfer of patient data between disparate CPR systems. The diversity of patient record data is likely to continue as a number of different vendors and mix of institutions, service bureaus, reimbursement agencies, and governmental agencies increase their use of clinical data. It is essential, therefore, that development and promotion of standards for data representation and data exchange be major priorities. Without such standards, it will be impossible to support the necessary exchange of CPR data among the different interested organizations and institutions. Summary Although progress has been steady over the past two decades in developing complete CPR systems, and although several powerful clinical information systems have become operational in recent years, as yet not one is capable of supporting the complete CPR. Most of the former technological barriers to developing CPR systems have now or are about to disappear, and no technological breakthroughs are needed to implement CPR systems. Nevertheless, further maturation of a few emerging technologies, such as voice-input or voice-recognition and text-processing systems, would facilitate the development of state-of-the-art CPR systems in the 1990s. Many different standards must be developed, tested, and deployed before the CPR can realize its full potential. Standards to facilitate the exchange of health care data are needed now so that clinical data may be aggregated and analyzed to support improved decision making. When clinical data from CPR systems are pooled in regional and national databases and made available through networks, they will constitute a vast information resource on which to base health care policy, clinical studies of effectiveness and appropriateness, and equitable reimbursement policies. Standards are also needed for the development of more secure CPR systems. All of this effort should focus on ensuring the integrity of the clinical data in the CPR and on patient confidentiality. Confidentiality of health data in CPR systems is crucial to the success of these systems. Further, confidentiality must be maintained not only for the patient but for all health care professionals and especially for members of the health care team.

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--> Although powerful new technologies and standards will greatly facilitate the realization of the CPR, they alone are not sufficient to overcome the barriers to its routine use. The primary barriers to realizing complete CPR systems are not technical but rather behavioral or organizational in nature. The next chapter explores various means for overcoming such barriers. References Andrews, R. D., and C. Beauchamp. 1989. A clinical database management system for improved integration of the Veterans Affairs hospital information system. Journal of Medical Systems 13:309–320. ASTM (American Society for Testing Materials). 1989. Standard Guide for Nosologic Standards and Guides for Construction of New Biomedical Nomenclature. Report No. E 1284-89. Philadelphia, Pa. Barnett, G. O. 1984. The application of computer-based medical record systems in ambulatory care. New England Journal of Medicine 310:1643–1650. Barnett, G. O., R. Zielstorff, J. Piggins, M. McLatchey, M. Morgan, S. Barnett, D. Shusman, K. Brown, F. Weidman-Dahl, and G. McDonnell. 1982. COSTAR: A comprehensive medical information system for ambulatory care. Pp. 8–18 in Proceedings of the Sixth Symposium on Computer Applications in Medical Care, ed. B. I. Blum. Washington, D.C.: IEEE Computer Society Press. Benda, C. 1989. Are doctors computer-compatible? Are computers physician-friendly? Minnesota Medicine 3:146–150. Blau, M. L. 1990. Emergency physicians gain malpractice discount. Physicians News Digest 6:2–3. Bleich, H. L., and W. V. Slack. 1989. Clinical computing. M.D. Computing 6:133–135. Bleich, H. L., C. Safran, and W. V. Slack. 1989. Departmental and laboratory computing in two hospitals. M.D. Computing 6:149–155. Blum, B. I., ed. 1984. Information Systems for Patient Care. New York: Springer-Verlag. Blum, B. I., ed. 1986. Clinical Information Systems. New York: Springer-Verlag. Canfield, K., B. Bray, and S. Huff. 1990. Representation and database design for clinical information. Pp. 350–353 in Proceedings of the Fourteenth Symposium on Computer Applications in Medical Care, ed. R. A. Miller. Washington, D.C.: IEEE Computer Society Press. Dayhoff, R. E., D. L. Maloney, and P. M. Kuzmak. 1990. Examination of architectures to allow integration of image data with hospital information systems. Pp. 694–698 in Proceedings of the Fourteenth Symposium on Computer Applications in Medical Care, ed. R. A. Miller. Washington, D.C.: IEEE Computer Society Press. Friedman, C., G. Hripcsak, S. B. Johnson, J. J. Cimino, and P. D. Clayton. 1990. A generalized relational scheme for an integrated clinical patient database. Pp. 335–339 in Proceedings of the Fourteenth Annual Symposium on Computer Applications in Medical Care, ed. R. A. Miller. Washington, D.C.: IEEE Computer Society Press. GAO (General Accounting Office). 1988. Use of Information Technology in Hospitals.

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--> Lindberg, D. A. B., and B. L. Humphreys. 1990. The UMLS knowledge sources: Tools for building better user interfaces. Pp. 121–125 in Proceedings of the Fourteenth Annual Symposium on Computer Applications in Medical Care, ed. R. A. Miller. Washington, D.C.: IEEE Computer Society Press. Mandell, S. F. 1987. Resistance to computerization: An examination of the relationship between resistance and the cognitive style of the clinician. Journal of Medical Systems 4:311–318. Margulies, D. M., R. Ribitzy, A. Elkowitz, and D. P. McCallie. 1989. Implementing an integrated hospital information system at Children's Hospital. Pp. 627–631 in Proceedings of the Thirteenth Annual Symposium on Computer Applications in Medical Care, ed. L. C. Kingsland. New York: IEEE Computer Society Press. McDonald, C. J., L. Blevins, W. M. Tierney, and D. K. Martin. 1988. The Regenstrief medical records. M.D. Computing 5:34–47. Miller, R. A., M. A. McNeil, S. M. Challinor, F. E. Masarie, and J. D. Myers. 1986. Status report. The INTERNIST-I: Quick medical reference project . Western Journal of Medicine 145:816–822. National Research Council. 1991. Computers at Risk: Safe Computing in the Information Age. Washington, D.C.: National Academy Press. Obermeier, K. 1989. Natural Language Processing Technologies in Artificial Intelligence: The Science and Industry Perspective. London: Ellis Horwood Limited. Pryor, T. A., R. M. Gardner, P. D. Clayton, and H. R. Warner. 1983. The HELP system. Journal of Medical Systems 7:87–102. Pryor, T. A., R. M. Gardner, P. D. Clayton, and H. R. Warner. 1984. The HELP system. Pp. 109–128 in Information Systems for Patient Care , ed. B. I. Blum. New York: Springer-Verlag. Safran, C., D. Porter, J. Lightfoot, C. D. Rury, L. H. Underhill, H. L. Bleich, and W. V. Slack. 1989. ClinQuery: A system for on-line searching of data in a teaching hospital. Annals of Internal Medicine 111:751–756. Scherrer, J. R., R. H. Baud, D. Hochstrasser, and R. Osman. 1990. An integrated hospital information system in Geneva. M.D. Computing 7:81–89. Shortliffe, E. H. 1987. Computer programs to support clinical decision making. Journal of the American Medical Association 258:61–66. Silva, J. S., A. J. Zawilski, and J. O'Brian. 1990. The physician workstation: An intelligent "front end" to a hospital information system. Pp. 764–767 in Proceedings of the Fourteenth Symposium on Computer Applications in Medical Care, ed. R. A. Miller. Washington, D.C.: IEEE Computer Society Press. Slack, W. V. 1989. The soul of a new system: A modern parable. M.D. Computing 6:137–140. Spencer, W. A., and C. Vallbona. 1965. Applications of computers in clinical practice. Journal of the American Medical Association 191:121–125. Stead, W. W., and W. E. Hammond. 1987. Demand-oriented medical records: Toward a physician workstation. Pp. 275–280 in Proceedings of the Eleventh Annual Symposium on Computer Applications in Medical Care , ed. W. W. Stead. Washington, D.C.: IEEE Computer Society Press. Stead, W. W., and W. E. Hammond. 1988. Computer-based medical records: The centerpiece of TMR. M.D. Computing 5:48–62.

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--> Summerfield, A. B., and E. Empey. 1965. Computer-based Information Systems for Medicine: A Survey and Brief Discussion of Current Projects . Santa Monica, Calif.: Systems Development Corporation. Walker, H. K. 1989. Grady Memorial's integrated database. Computers in Healthcare March:36–42. Warner, H. R., C. M. Olmsted, and B. D. Rutherford. 1972. HELP: A program for medical decision making. Computers and Biomedical Research 5:65. Weed, L. L. 1968. Medical records that guide and teach. New England Journal of Medicine 278:593–600, 652–657. Weed, L. L. (in press). New Premises and New Tools for Medical Practice and Medical Education. New York: Springer-Verlag. Whiting-O'Keefe, Q. E., A. Whiting, and J. Henke. 1988. The STOR clinical information system. M.D. Computing 5:48–62. Wiederhold, G. 1986. Views, objects and databases. Computer 19:37–44. Wilton, R. W., and J. M. McCoy. 1989. Outpatient clinic information system based on distributed database technology. Pp. 372–376 in Proceedings of the Thirteenth Symposium on Computer Applications in Medical Care , ed. L. C. Kingsland. New York: IEEE Computer Society. Young, D. W. 1987. What makes doctors use computers? Discussion Paper. Pp. 8–14 in Use and Impact of Computers in Clinical Medicine, ed. J. G. Anderson and S. J. Jay. New York: Springer-Verlag. Zibrak, J. D., M. S. Roberts, L. Nelick-Cohen, and M. Peterson. 1990. Creating an environment conductive to physician participation in a hospital information system. Pp. 779–783 in Proceedings of the Fourteenth Symposium on Computer Applications in Medical Care, ed. R. A. Miller. Washington, D.C.: IEEE Computer Society Press. Appendix: the Computer-based Patient Record System Vendor Survey The members of the Institute of Medicine study committee agreed that their deliberations would be enhanced by access to data on commercial clinical information systems and on the perspectives of those who develop and market them. The committee's Technology Subcommittee therefore conducted an informal survey to solicit basic information from vendors active in the computer-based patient record system market. Twelve vendors associated with clinical information systems (including three hardware manufacturers) responded. This appendix briefly summarizes findings and conclusions derived by the subcommittee from the responses to the survey. General Observations The range of responses, both to the survey as a whole and to the individual items within it, indicated substantial differences among members of the software development industry about the operational definition of the

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--> computer-based patient record and the data that should be captured in it. Vendor responses suggested that the industry viewed direct data entry as desirable, but they also reflected industry pessimism about whether physicians and nurses could be convinced to actually enter data (although three vendors stated that they had implemented systems in which direct data entry by practitioners was occurring). Other impediments to the immediate implementation of CPRs today, as opposed to in the future, included the cost of the system, general resistance to change within the health care industry, the need for data sharing among many different kinds of systems (including departmental systems), and the lack of a good decision support system. Vendors showed more agreement in their view of the forces that could propel the medical record environment into the computer age. Most cited the increasingly broad range of medical record users, which mandates a patient record with expanded access. Strong consensus emerged regarding the CPR as a tool with the potential to benefit every aspect of the health care environment. Vendors also voiced some skepticism, however, that the CPR could receive the broad-based, organization-wide support required for its implementation and use in a hospital. According to the vendor responses, technologies commonly believed to be 5 to 10 years distant are, in fact, already being employed in workable CPR systems. Three vendors claimed that they had implemented a full-scale electronic medical record in a hospital environment: one in a facility of unspecified size, the second in a hospital of 176 beds, and the third in a large, urban teaching hospital of more than 900 beds. Two of these vendors offered decision support systems, one of which was described as a powerful report-writing system and the other as an actual interactive decision support system. The survey responses also indicated that direct data entry by patient care practitioners was feasible, resistance to change notwithstanding, provided the CPR system was user-friendly and was perceived as improving quality and reducing costs for the hospital, clinic, or practice. Taken together, the survey responses appeared to suggest that the environment is right for the implementation of CPRs in hospitals—that is, if enough of the system's beneficiaries can be convinced that such a comprehensive system justifies the difficulties of implementation. Survey Findings FINDING 1. Close reading of the responses generates some skepticism about whether all of the named products meet the requirements of a comprehensive CPR system. This may be the case in part because too few of the necessary patient record components have been automated. FINDING 2. The majority of the systems noted in the survey operate in

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--> multiprocessor environments, a configuration that arises in response to a hospital's demands for flexible implementation and system expandability. This trend can be expected to continue. All but one of the systems are designed to run on the hardware of a particular vendor; the exception is a system adaptable to any hardware that uses UNIX. For the most part, the systems described in the survey do not employ the most advanced terminal technologies, even though these technologies are no longer new on the market. The one exception to this generalization—the vendor whose product is adaptable to many different types of computer hardware—supports both windowing and point-and-click technologies. FINDING 3. System costs, including installation, are likely to be in the range of $2 million to $6 million for a medium-sized hospital. Annual maintenance costs for each system could be substantial—approximately 10 percent of the purchase or lease price. FINDING 4. With the exception of a single software vendor, the industry is moving slowing in solving one crucial problem: ease of data entry. Although such devices as the mouse and the light pen are commonly used in other industries, and even in home computing, they are rarely found in health care computing. The only vendor that offers evidence of having solved the problem of convincing physicians and nurses to use the system is the same vendor that has exploited these technologies most fully. The same conclusion may be drawn with regard to flexible output devices: the vendor that offers the most flexible data entry methods also supports the most varied output, including terminal windowing, and has the most flexible hardware requirements. FINDING 5. The survey responses are informative regarding vendor attitudes toward the state-of-the-art in CPR systems, but they may not be helpful in defining the actual state-of-the-art. The committee found it surprising that the software vendors who responded to the survey should so heavily emphasize hardware improvements as the necessary step in advancing to comprehensive CPRs and CPR systems. FINDING 6. The last set of findings was based on a group of open-ended questions to which only a few vendors responded. In general, they seem reluctant to lay out in detail imaginative ideas regarding the impact of computerized systems on the industry their systems are intended to serve, namely, the health care industry. Thus, the committee found it disturbing that the vendors appeared pessimistic, perhaps unintentionally, about surmounting the difficulties involved in implementing the CPR—especially given the success that some have had in overcoming certain technological and behavioral problems associated with CPR implementation.