THE CENTRALITY OF INFORMATION TO HEALTH CARE DELIVERY

Information and information exchange are crucial to the delivery of care on all levels of the health care delivery system—the patient, the care team, the health care organization, and the encompassing political-economic environment. To diagnose and treat individual patients effectively, individual care providers and care teams must have access to at least three major types of clinical information—the patient's health record, the rapidly changing medical-evidence base, and provider orders guiding the process of patient care. In addition, they need information on patient preferences and values and important administrative information, such as the status and availability of supporting resources (personnel, hospital beds, etc.).

To integrate these critical information streams, they will also need training/education, decision-support, information-management, and communications tools. For individual patients to participate as informed, “controlling” partners in the design and administration of their own care, they must also have access to much the same kind of information and education, decision-support, and communications tools—in a “patient-accessible/usable” form.

At the organizational level, hospitals and clinics need clinical, financial, and administrative data/information to measure, assess, control, and improve the quality and productivity of their operations. At the environmental level, federal/state funding and regulatory agencies and research institutions need information on the health status of populations and the quality and productivity/performance of care providers and organizations to execute regulatory oversight, protect and advance the public health (surveillance/monitoring), evaluate new forms of care, accelerate research, and disseminate new medical knowledge/evidence.

As discussed in Chapter 3, information and information exchange are also critical to the tactical and strategic applications of systems-engineering tools at all four levels of the system, especially for strategic applications of enterprise-management tools and risk analysis and management tools at the organizational and environmental levels.

FROM ELECTRONIC MEDICAL RECORDS TO A NATIONAL HEALTH INFORMATION INFRASTRUCTURE

The idea of transforming paper medical records into electronic medical records (EMRs) was first considered in the mid-1960s, when early prototype systems were developed. A number of large integrated health care provider organizations were early adopters of EMR systems, including Massachusetts General Hospital (COSTAR) in the 1960s, Indiana University Medical School (Regenstrief Medical Record System) in the early 1970s, and others (Kass-Bartelmes et al., 2002; Lindberg, 1979). However, there was little diffusion of these systems in the next two decades. In 1991 and 1997, IOM issued reports documenting the magnitude and implications of the large information-technology gap in U.S. health care and called for the adoption of EMRs as a first, critical step in moving health care delivery toward information/communications-technology-supported improvements in quality performance achieved in other industries (IOM, 1991, 1997).

Building on these studies, a series of reports by IOM, the National Committee on Vital and Health Statistics (NCVHS), and other organizations in the past five years have documented the profound negative impact of the information/ communications technology deficit on patient safety, the number of medical errors, and the quality and cost of care; every one of these reports calls for the development of a comprehensive health care information infrastructure (e.g., NHII) to help close the gap (IOM, 2000, 2001, 2003, 2004; NCHVS, 2001; NRC, 2000).

In Information for Health: A Strategy for Building the National Health Information Infrastructure, NCVHS described the NHII as both infrastructure and a defined set of components linked explicitly to health care delivery processes (NCVHS, 2001). IOM (2004) summarized the NCVHS definition as follows:

The NHII is defined as “a set of technologies, standards, applications, systems, values, and laws that support all facets of individual health, health care, and public health”… It encompasses an information network based on Internet protocols, common standards, timely knowledge transfer, and transparent government processes with the capability for information flows across three dimensions: (1) personal health, to support individuals in their own wellness and health care decision making; (2) health care providers, to ensure access to complete and accurate patient data around the clock and to clinical decision support systems; and (3) public health, to address and track public health concerns and health education campaigns.

This stream of reports from IOM, NCVHS, and others catalyzed a number of actions in the private and public sectors intended to lay the groundwork for and build momentum toward realization of the NHII (IOM, 2004; PITAC, 2004; Thompson and Brailer, 2004; Yasnoff et al., 2004). Inspired by the 1999 IOM report, To Err Is Human, the Leapfrog Group for Patient Safety, a coalition of large companies established expressly for the purpose of using their market power as major purchasers of health care to encourage care providers to improve the safety, quality, and efficiency of health care. The Leapfrog Group called on all health care provider organizations serving Leapfrog members' employees to use information/communications systems (EMRs and computerized physician order entry [CPOE] systems in particular) (see paper by Milstein in this volume).

In April 2004, progress toward an NHII was given new impetus when President Bush called for national implementation of EMRs and announced the creation of the Office of the National Coordinator for Health Information Technology (ONCHIT) in the U.S. Department of Health and Human Services (DHHS); Dr. David Brailer was appointed the first national coordinator. In July, DHHS released a report outlining a 10-year plan to build an NHII, including the creation of electronic health records (EHRs), for all Americans (Thompson and Brailer, 2004). In November 2004, ONCHIT issued a Request for Information (RFI) for a National Health Information Network (NHIN), soliciting proposals for ways to advance interoperability and standards. As of early 2005, ONCHIT had received more than 500 responses from a wide variety of organizations and collaboratives.

One of the respondents to the RFI, the Interoperability Consortium, an alliance of eight information-technology systems vendors (Accenture, Cisco, CSC, Hewlett-Packard, IBM, Intel, Microsoft, and Oracle), describes the current challenges to interoperability:

Dozens of communities and innovative networks across America have begun implementing information exchange solutions—yet they are following no common pathway, no uniform standards, and have established no basis for eventual information exchange among them or with the important national information networks already in existence. A common framework is needed to guide and maximize the value of the enthusiastic efforts already in the field.

In its preliminary blueprint for NHIN, the Interoperability Consortium (2005) stresses that the NHIN must be part of an agenda for the comprehensive transformation of health care delivery:

The NHIN should be approached as an IT-enabled clinical transformation initiative that fuses technology and process reengineering in order to achieve its stated objectives of improving quality and decreasing costs. Performance metrics must be established to monitor progress, and incentives should be aligned (and periodically adjusted) to reward actual benefit realization. Conversely, the costs attached to supporting and monitoring the effectiveness of this transformation agenda should be included in the NHIN's total cost of ownership.

To meet these requirements, the NHII/NHIN must be a secure, reliable, and adaptable national infrastructure capable of connecting and supporting highly distributed, varied, independently managed, multi-tiered, intra-institutional, clinical information/communications technology systems and applications. This infrastructure would vastly expand the information gathering, exchange, processing, and application capabilities of stakeholders at all four levels of the health care system.

FOUNDATIONS OF A NATIONAL HEALTH INFORMATION INFRASTRUCTURE

The components of a national health information infrastructure can be divided into three interrelated categories: (1) health care data standards and technical infrastructure; (2) core clinical applications, including EHRs, CPOE systems, digital sources of medical knowledge, and decision-support tools; and (3) information/communications systems.

Core Clinical Applications

Clinical information systems provide a mechanism for sharing data collected from various sources (e.g., EHRs in care settings that may include personal health record systems maintained by patients or their representatives). Data become available to clinical information systems via direct entry at the point of care, off-line entry through abstraction from other media, such as handwritten notes, and data collected by other systems, such as laboratory systems or monitoring devices. The data can take many forms—including free text, coded data, speech, document imaging, clinical imaging (e.g., x-rays), and video. In the following section, four core components of clinical information systems are described: (1) EHRs; (2) CPOE systems; (3) digital sources of medical evidence; and (4) decision-support tools. These descriptions are followed by a discussion of human/ information systems interface design and software dependability issues.

Electronic Health Records

The electronic capture of patient-specific clinical information is critical to many health care information/ communications technology applications. Attention has been focused in the creation of EHRs since the 1960s, and in 1991, IOM set forth a vision and issued a call for nationwide implementation of computer-based patient records that would be paperless and instantly available throughout the health care system in forms readily understandable to physicians and other providers at point of care and specialists, perhaps in a different location (IOM, 1991). However, the rate of progress toward realizing this vision has been glacial.

Only a fraction of hospitals have implemented comprehensive EHR systems, although many have made progress in certain areas, such as computerized reporting of laboratory results (Brailer, 2003). Rates of adoption of EHR systems are higher in ambulatory care settings—probably about 5 to 10 percent of physician's offices—but these systems vary greatly in content and functionality (IOM, 2004). Although some cases of failed EHR systems have been documented, many more examples show cost savings and quality improvements yielded by EHR systems (Clayton in this volume; Littlejohns et al., 2003; Pestotnik et al., 1996; Wang et al. 2003).

EHRs have been instituted in health care settings in the public and private sectors, and a few communities and systems have implemented secure systems for the exchange of data among providers, suppliers, patients, and other authorized users. Among these are the Veterans Health Administration (see Box 4-1), Mayo Clinic (see Box 4-2), New England Healthcare Electronic Data Interchange Network, Indiana Network for Patient Care, Santa Barbara County Care Data Exchange, Patient Safety Institute's National Benefit Trust Network, and the Markle Foundation Healthcare Collaborative Network (CareScience, 2003; Kolodner and Douglas, 1997; Markle Foundation, 2003; New England Healthcare EDI Network, 2002; Overhage, 2003; Patient Safety Institute, 2002; Zachariah in this volume).

BOX 4-1

Veterans Health Information Systems and Technology Architecture. The Veterans Health Information Systems and Technology Architecture (VistA) supports a continuum of care, from intensive care units and other inpatient areas, to outpatient care settings, (more...)

BOX 4-2

Automation of Clinical Practice at Mayo Clinic. The Automation of the Clinical Practice (ACP) Project at Mayo Clinic in Jacksonville, Florida, undertaken in 1993, includes computer-based patient records and mechanisms for automated charging and order (more...)

All of these are exceptions to the rule, however. In most hospitals, orders for medications, laboratory tests, and other services are still written on paper, and many hospitals do not even have the capability of delivering laboratory results and other test results in automated form. The same situation prevails in most small practice settings, where little if any progress has been made toward creating electronic records (IOM, 2004).

A patient's EHR must also include long-term data and information about the patient's daily life. This information will be useful not only in the planning and delivery of progressive care, but will also provide evidence for assessing different clinical interventions. Systems-engineering tools and techniques are available for modeling and determining the information needs of a “system” that can deliver progressive care and evaluate that system's performance.

Patient-centered health care delivery in the broadest sense must also focus on what the patient really wants from the entire health care community—the best physical and mental function in daily living possible within the constraints of the patient's physical condition. The key word here is “system,” that is, coordinated care, including care in the clinic, the hospital, home, rehabilitation facility, skilled nursing facility, long-term care facility, hospice, and perhaps social and societal programs. NHII is a first step toward obtaining data and information necessary for coordinating care in the clinic and hospital.

The management of large databases, which are essential to comprehensive core clinical applications for information/ communications systems, remains a critical determinant. Although databases are effectively managed in select locations, efforts must continue to develop secure, dispersed, multiagent databases that can serve both providers and patients effectively and efficiently.

Computerized Physician Order Entry Systems

Using CPOE systems for entering orders for tests, drugs, and other procedures has led to reductions in transcription errors, which have led to demonstrable improvements in patient safety. When CPOE systems are integrated with other core clinical applications, their impact on patient safety is even greater. One component of a CPOE system is computerized decision support. CPOE systems that include data on patient diagnoses, current medications, and history of drug interactions or allergies can significantly reduce prescribing errors (Bates et al., 1998, 1999; Leapfrog Group, 2000).

CPOE systems also improve the quality of care by increasing clinician compliance with standard guidelines of care, thereby reducing variations in care. For example, a 1998 study by Shojania et al. found that CPOE, combined with the use of a vancomycin guideline, reduced the use of this over-prescribed antibiotic by 32 percent. A study of CPOE use at one large academic medical center (Brigham and Women's Hospital) by Teich et al. (2000) estimated that the overall annual cost savings from reductions in drug costs, laboratory tests, and diagnostic studies and the prevention of adverse drug events were roughly $5 to 10 million annually.

Despite many documented benefits of CPOE systems—improvements in the quality of patient care, decreases in medication errors, and decreases in overall costs—they have not been widely implemented. In the only study that has rigorously examined the adoption of CPOE by hospitals in the United States, less than 2 percent of hospitals were found to have CPOE systems completely or partially available and to require that physicians use them (Ash et al., 1998). Nevertheless, a few success stories have been well documented, notably the Brigham and Women's Hospital in Boston, Massachusetts, and the Regenstrief Medical Record Systems.

Studies indicate that there are multiple barriers to the effective use of CPOE systems, including the lack of education and training of physicians, problems with user-interface designs, concerns about accuracy and reliability, high upfront fixed and ongoing maintenance costs, a lack of leadership commitment, difficulties in coordinating the introduction of new applications among varied care delivery settings and functions, and poor integration of CPOE systems with existing work processes and other information/ communications systems, both clinical (e.g., digital sources of evidence, decision-support tools) and administrative (Boodman, 2005; Durieux, 2005; Garg et al., 2005; Sarata, 2002; Tang in this volume; Wears and Berg, 2005).

To address these problems, a template for patients, based on the current database, could be customized by the physician using evidence-based standards as the “orders” for each patient. One of the most frequent causes of errors and failures to carry out planned treatments has been a lack of integration of orders and results. Branching logic based on results can be used to verify that each step in the treatment is accomplished. The system described would not only reduce errors, such as missed handoffs and unnecessary waiting times, it would also interact with enterprise systems for supply-chain management and capacity planning.

Digital Sources of Evidence and Knowledge

Another key component of the health information infrastructure, digital sources of evidence—including bibliographic references, evidence-based clinical guidelines, and comparative databases—is essential for evidence-based practice. Currently, most digital sources of evidence are stand-alone systems that are not integrated into clinical information systems. The challenge for practitioners is to use these sources of evidence in combination with their experience and expertise to make clinical decisions (Bakken, 2001). However, as the medical-evidence base continues to expand exponentially and more and more clinicians accept the validity of best-demonstrated practices for diagnosis and treatment, there is mounting interest in integrating rapidly expanding digital sources of evidence (including genomic and phenotypic [clinical] data) into decision-support tools that can be fully integrated into care processes.

At the same time, fueled by the rapidly expanding medical-evidence base, there is a growing awareness among care professionals of the need for customization of best demonstrated practice rules for almost all patients. In the past five years, a new field has emerged, “predictive medicine” (i.e., the use of mathematical and statistical strategies to mine phenotypic [clinical] databases to identify and treat high-risk patients and to individualize treatment strategies). Another emerging area is translational medicine, the use of the results of the genome project to predict and customize treatment.

Decision-Support Tools

The standardization of health care data, the development of digital sources of medical evidence and knowledge, and the creation of EHRs will all facilitate the use of decision-support tools, which are key components of clinical information systems. Decision-support tools that are fully integrated into the care process will enable both care providers and patients to access medical knowledge relevant to the patient's care. They may, for example, identify negative interactions between a drug the patient is already taking and an additional drug that might be prescribed.

A necessary platform for decision-support tools is the clinical-data repository, a database that collects and stores patient care information from diverse sources. Clinical-event monitors, which work with clinical-data repositories in support of real-time delivery of care, are usually triggered by clinical events (e.g., a patient visit, a medication order, a new laboratory result), either when data representing the event enter a repository or when a provider uses a clinical information system. The event monitor combines clinical rules, the triggering event, and information present in the repository to generate alerts, reminders, and other messages important to the delivery of care.

For more than 20 years, departmental systems (e.g., laboratory, x-ray) have had internal computerized systems that control operations and report results. But there is no health care process-management system in which all information concerning a patient's history is gathered in one place in standardized text where the appropriateness and strategy of orders for patient care can be checked. Equally important, a health care process-management system would ensure that the result of each step in treatment was entered into the record and communicated to all relevant parties. The collection of data, the consideration of the decision support offered, followed by the ordering and carrying out of the diagnostic and or treatment plan is an iterative process. As results are entered, the next steps in the care process are instituted.

Human-Computer Interfaces

Because the value of computerized clinical systems depends on how well they support care decisions in the service of patients, the development and implementation of information/communications systems that provide support and increase connectivity among health care providers will require “human-factors” research. This area of research, which combines expertise in cognitive and software engineering, behavioral science and cooperative work, and computer and cognitive sciences, focuses on the development of techniques and concepts that facilitate interactions between people and computers (Winograd and Woods, 1997; Woods, 2000).

Usefulness and usability in software-intensive systems cannot be achieved by patching “user-friendly” interfaces onto user-hostile system architectures. Health care computer systems have been administrator-centered or billing-centered systems rather than provider-centered or patient-centered systems. However, software and telecommunications capabilities are being expanded, although slowly, to achieve continuity of care without losing sight of economic and other pressures (Box 4-3).

BOX 4-3

Designing Computer Systems for Health Care. Software-intensive systems are the norm for all modern high-performance systems. But simply extending the reach of computer technology will not guarantee high performance in a complex setting like health care. (more...)

A recent study concludes that there is an urgent need for more “research and development in innovative and efficient human-machine interfaces that are optimized for use in the health care sector” (PITAC, 2004). Areas for research include hardware interfaces, as well as sociological and psychological aspects of the use of computerized systems by physicians and other health care workers. The human-computer/information systems interface should be a high priority for health care. The study identifies targets for research: “improved medical-domain voice-recognition data conversion systems; improved automated entry of instrument data; and automated methods for converting both new and legacy electronic data to normalized form” (PITAC, 2004).

Software Dependability

In systems in which software is an element in the critical path, a variety of serious problems have plagued organizations, including lack of dependability and/or usability, the high cost of system failure, high maintenance requirements, and difficulties in updating systems. Because software-intensive systems perform valuable functions, the consequences of failure are generally serious. For example, developers may assemble modules, each apparently dependable, but, when they are integrated, problems and weaknesses emerge. Usability failures are also an issue. For example, if there are too many steps in a program for a user to follow or if a program is too complicated, various “work arounds” will be developed, and patient safety or some other critical parameter may be compromised.

In some cases, the initial software-intensive system may be dependable, but changes in use over time may lead to changes in the software that lead, in turn, to unnoticed side effects that can introduce weaknesses in the system. Another type of failure can occur when cost overruns in the development process prevent the project from ever reaching the commercialization stage. In some instances, noncritical software that interacts directly or indirectly with critical functions introduces failures and weaknesses (NRC, 2004; Rae et al., 2003). As these and other forms of software-system failure show, investments in clinical information systems must be complemented by investments in research on software dependability.

Summary

The implementation of core clinical applications of information/communications systems has progressed very slowly because of costs, possible disruptions to current operations, problems with overlapping legacy systems, and problems with the use and integration of various systems. Opportunities for improvement (and research) include: better human-computer system interfaces; software to improve the interoperability of systems from various vendors; systems and accompanying business models for spreading costs among multiple users; and software dependability in the context of health care delivery.

COMMUNICATIONS TECHNOLOGIES

The delivery of quality care, especially in a highly fragmented delivery system, requires that both clinicians and patients have access to complete patient information and decision-support tools and that communications among clinicians and between clinicians and patients are effective. The Internet and the World Wide Web have provided patients with unprecedented access to health information and made possible more continuous, asynchronous communication between patients and their care providers. These technologies for asynchronous communication have enabled the development of self-care educational tools/modules, such as University of Wisconsin's Comprehensive Health Enhancement Support System (CHESS), which promotes informed health monitoring and decision making by giving patients access to disease-specific information (see paper by Gustafson in this volume). The case example of CareGroup Healthcare System (see Halamka in this volume) illustrates many of the challenges and opportunities associated with building fixed-line information/communication networks that increase connectivity and information exchange between patients and clinicians, as well as among dispersed elements of the care team.

Meeting the current and emerging communications needs of health care will require a combination of wireless and fixed-line networks. Because of financial constraints, creating different systems for different settings will not be feasible, however. Vendors of hardware and software components of the system will need system transparency, which can only be achieved once standards have been adopted. The challenge will be to generate a robust, but flexible system that can be duplicated in many different circumstances without requiring major modifications; the system must be based on technology that can be rapidly diffused and at low cost. Five technical factors are important in planning for the implementation of communication networks: (1) bandwidth requirements and availability; (2) latency in transmission throughout the network; (3) continuous availability of the network; (4) confidentiality and security of data; and (5) ubiquity of access to the network (NRC, 2000).

Enabling patients to communicate effectively with health care providers without face-to-face meetings will require many improvements in electronic communications. The Internet and World Wide Web provide a framework for communication links, and a few large provider organizations have demonstrated the potential of these technologies. But making them accessible to large populations in a health care community will require experimentation and research (Perlin et al., 2004). Other issues that must be addressed include ensuring the confidentiality and security of transmissions and health care data. In the long term, sensors that register a patient's vital signs and transmit data via wireless links could greatly improve the “connectivity” between patients and health care providers.

MICROELECTRONIC SYSTEMS AND EMERGING MODES OF COMMUNICATION

The emerging technologies in wireless communications and microelectronic systems described in this section have the potential to advance the patient-centeredness and quality performance of the health care delivery system and to change the structure of care delivery in the process. Microelectronics promises to be a powerful tool for meeting quality and productivity challenges in health care delivery, provided that resources can be marshaled in a rational way. The microelectronics revolution began in the 1950s with the advent of integrated circuits and has since revolutionized data processing, communications, and control. The number of transistors that can be integrated on a silicon chip the size of a finger-nail has increased from about 2,000 on the first micro-processor (1971) to about 200,000,000 today; the speed of these chips has increased more than a thousand-fold. At the same time, the number of bits of memory on a chip has increased by a factor of more than a million, and costs have decreased just as precipitously. Low-cost disk storage is now approaching a density of more than 40 gigabytes per square inch. In short, the processing and storage of data, the creation of information and knowledge based on those data, and the efficacy of decisions have improved exponentially.

Therapeutic Uses

WIMS may also have therapeutic uses. The development of wireless implantable microsystems has been the subject of research for 40 years or more, but, to date, few devices have been developed besides pacemakers. Pacemakers have become increasingly sophisticated electronically, but their interfaces with the body are primarily via electrodes. Nevertheless, they have set the stage for the emergence of new devices in the coming decade. For example, cardiovascular catheters have been used for diagnosing cardiac conditions for many years, and pressure sensors small enough to be mounted directly on catheters have existed for some time (Chau and Wise, 1988; Ji et al., 1992). In fact, catheter-based electronics for improving diagnostic capabilities are long overdue. Another example is stents, which are widely used for treating coronary occlusions and now have chemical coatings to prevent re-stenosis. In the near future, stents may also be used as platforms for instrumentation, such as wireless sensors for monitoring blood pressure or blood flow that could be activated by a radio frequency wand positioned over the chest. Significant challenges remain involving range, accuracy, and size, but such systems may be feasible soon (Collins, 1967; DeHennis and Wise, 2002; Stangel et al., 2001).

Wireless sensors could also be used in intracranial, intraocular (glaucoma), and intra-arterial applications. Miniature biocompatible packages that can exist for many decades in the body are also being developed for long-term use in chronic conditions (Ziaie et al., 1996).

WIMS could also have a dramatic impact on the treatment of conditions involving the central nervous system. More than 90,000 cochlear implants are in use worldwide today, enabling many profoundly deaf and severely hearing-impaired individuals to function normally in a hearing world (House and Berliner, 1991; Spelman, 1999). Even though their performance is still limited and there is some opposition to them in the deaf community, these devices may render most kinds of deafness treatable disorders in the next two decades. In the United States alone, more than 2 million people are profoundly deaf, and 20 million are severely hearing impaired.

There is considerable interest in treating other neurological disorders using WIMS. Visual prostheses have recently received considerable attention but are still at a very early stage of development (Lui, 2002). The same is true of prostheses for severe epilepsy and paralysis. For example, an implanted electrode array might detect the onset of an epileptic seizure and provide local electrical stimulation or drug delivery to prevent the spread of the seizure. Functional neuromuscular stimulation (FNS) is being used to help quadriplegics stand and even walk, and the use of dense electrode arrays to capture control signals directly from the motor cortex has recently enabled primates to control robotic arms (Chapin et al., 1999; Serruya et al., 2002; Taylor et al., 2002) and humans to control cursors in operating a computer interface (Donoghue, 2004). Combining FNS with cortical control could lead to at least limited closed-loop activation of paralyzed limbs (Wise et al., 2004). And the use of deep brain stimulation in the subthalamic nucleus to eliminate the manifestations of Parkinson's disease has yielded impressive results and is now approved for human use (Limousin et al., 1998). Although all of these devices are still at a relatively early stage of development (Table 4-1), some are gaining acceptance now, and many could be in wide use in the next 20 years, which could substantially impact the quality of health care and the costs of rehabilitation.

TABLE 4-1

Status of Wireless Devices for Treating Neurological Disorders.

CONCLUSION

Timely, accurate information is critical to the efficient operation of large dispersed systems. Although the health care system has been slow to recognize this, efforts are now under way to rectify the situation. But it is imperative that research, development, demonstration, and training be expanded and accelerated.

Putting together a system that can make use of information microtechnology, nanotechnology, and biotechnology and ensure that applications are widely available and affordable will require coordination at the national level among device manufacturers, clinicians, and hospital systems. A successful health care system would use information/ communications technologies in ways that would be largely invisible to patients but would improve care, reduce costs, and provide patient-centered care. However, unless the approach is coordinated, the impact of new technologies could improve health care for a few but increase costs for everyone else and move the overall system even farther away from providing patient-centered care.

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Footnotes

1

The Institute of Medicine's “Action Plan for Setting Data Standards” includes two specific recommendations in each of three key areas: Clinical data standards: “…federal government health care programs should incorporate into their contractual and regulatory requirements standards already approved by the secretaries of DHHS, the Veterans Administration, and the Department of Defense…[and] AHRQ should provide support for accelerated completion of HL7 version 3.0, specifications for the HL& clinical document architecture and implementation guidelines, and analysis of alternative methods for addressing the need to support patient safety by instituting a unique health identifier for individuals.” Clinical terminologies: “AHRQ should undertake a study of the core terminologies, supplemental terminologies, and standards mandated by the Health Insurance Portability and Accountability Act to identify areas of overlap and gaps in the terminologies to address patient safety requirements…[and] The National Library of Medicine should provide support for the accelerated completion of RxNorm for clinical drugs, and develop high-quality mappings among the core terminologies and supplemental terminologies identified by the CHI and NCVHS.” Knowledge representation: “The National Library of Medicine should provide support for the development of standards for evidence-based knowledge representation…AHRQ, in collaboration with NIH, the FDA, and other agencies should provide support for the development of a generic guideline representation model for use in representing clinical guidelines in a computer-executable format that can be employed in decision support tools” (IOM, 2004).