Content area
To provide a synopsis of issues about clinical information systems for nurses not schooled in nursing informatics.
The past, present, and future of clinical computing, including major factors resulting in the early hospital information systems (HIS) and decision support systems (DSS) in the United States, current advances and issues in managing clinical information, and future trends and issues.
Literature review and analysis.
The first HIS and DSS were used in the late 1960s and were focused on applications for acute care. The change from fee-for-service to managed care required a change in the design of clinical information systems toward more patient-centered systems that span the care continuum, such as the computer-based patient record (CPR). Current difficulties with CPR systems include lack of systems integration, data standardization, and implementation. Increased advances in information and technology integration and increased use of the Internet for health information will shape the future of clinical information systems.
Full text
Healthy Policy and Systems
Purpose: To provide a synopsis of issues about clinical information systems for nurses not schooled in nursing informatics.
Organizing construct: The past, present, and future of clinical computing, including major factors resulting in the early hospital information systems (HIS) and decision support systems (DSS) in the United States, current advances and issues in managing clinical information, and future trends and issues.
Methods: Literature review and analysis.
Findings and Conclusions: The first HIS and DSS were used in the late 1960s and were focused on applications for acute care. The change from fee-for-service to managed care required a change in the design of clinical information systems toward more patient-centered systems that span the care continuum, such as the computer-based patient record (CPR). Current difficulties with CPR systems include lack of systems integration, data standardization, and implementation. Increased advances in information and technology integration and increased use of the Internet for health information will shape the future of clinical information systems.
JOURNAL OF NURSING SCHOLARSHIP, 2001; 33:1, 75-81. (C) 2001 SIGMA THETA TAU INTERNATIONAL.
[Key words: information systems, nursing informatics, HIS, DSS, computer-based patient records]
During the late 20th century, information systems (IS) have become increasingly prevalent in healthcare. What were the influences that led to early advances in clinical computing? What are the current trends in clinical computing, and what can nurses expect in the future? This article is a synopsis of these issues for nurses not schooled in informatics. Although this discussion is specific to American health care facilities, the findings may apply in other countries as well.
Historical Influences of Information Systems in Clinical Care
The development of IS has been linked to changing needs in the healthcare industry. The U.S. healthcare industry in the 19th century was a charitable, community-based effort to care for the sick and needy (Kissinger & Borchardt, 1996) and was comprised of stand-alone healthcare services for episodic, acute care. Patients' records were maintained by healthcare providers with little need to share information among providers or settings.
Throughout the 20th century, the healthcare industry expanded, fueled in large part by the federal government. In the 1950s, the emphasis was on increasing the number and quality of healthcare facilities. The Hill-Burton Act provided funds for this bricks and mortar development of facilities. Then in the 1960s, passage of legislation supporting Medicare and Medicaid increased access to healthcare and virtually guaranteed that healthcare settings would be amply reimbursed for their services (Kissinger & Borchardt, 1996). Throughout the era of expansion in healthcare, health records continued to be paper-based and provider-centered. Availability and assurance of a steady cash flow to inpatient facilities for providing care allowed healthcare providers, particularly physicians, to develop innovations such as new pharmacologic agents, advanced surgical procedures, and sophisticated diagnostic techniques.
The application of computer technology to clinical care was one of these innovations. Because of a stable healthcare environment through the 1960s and 1970s, and the increasing availability and lower cost for computer technology, physicians and others began investigating the use of this technology to address healthcare needs. Early efforts were directed at developing hospital information systems and tools for decision support.
Hospital Information Systems
Hospital information systems (HIS) are large, computerized databases used to store health and administrative information. Early systems were focused on communicating orders for acute care and reporting results from ancillary departments such as pharmacy and laboratory. However, functions of HIS varied from institution to institution.
The development of one of the first systems, Technicon Medical Information Systems (now Technicon Data Systems or TDS), began in 1965 at El Camino Hospital in Mountain View, California, in conjunction with Lockheed Missiles and Space Company (Wiederhold & Perreault, 1990). When TDS was first used on a patient care unit in 1971, it had capabilities for a suite of complex clinical, ancillary and administrative functions. Physicians' orders were communicated to ancillary departments, results were retrieved for laboratory tests and radiology reports, and nursing care planning and documentation were included (Barrett, Barnum, Gordon, & Pesut, 1975). According to a formal evaluation of the system, TDS supported substantially all information handling for nurses, physicians, and personnel in ancillary departments, including dietary, medical records, pharmacy, laboratory, radiology, respiratory therapy, and business offices (Barrett et al., 1975). The considerable functions provided by TDS were especially remarkable given the limited computing capabilities elsewhere in the nation.
Other HIS followed soon after (see Table 1). The HELP system at Latter-day Saints (LDS) hospital in Salt Lake City, Utah, and the HIS at the National Institutes of Health Clinical Center in Bethesda, Maryland, were two of the most publicized systems, supporting a broad range of acute care functions, from order entry and results reporting to clinical care documentation. Early versions of HELP provided for bedside monitoring in intensive care units, laboratory automation, and interpretation of electrocardiograms. Beginning in the early 1970s functions were expanded to include additional portions of patients' records and decision support (Kuperman, Gardner, & Pryor, 1991). Capitalizing on the success of TDS at El Camino, the National Institutes of Health (NIH) staff also implemented a TDS HIS that had similar broad functions to support clinical care. This system was notable for its capability to track patients' problems of interest to nurses, patient care goals, and nursing orders (Cook & McDowell, 1980). The framework developed by NIH nurses for nursing documentation (Romano, McCormick, & McNeely, 1982) served the agency well for over 20 years.
Another well publicized information system is the Department of Defense's $1.6 billion Composite Health Care System (CHCS), developed in the 1980s as a follow up to the earlier ancillary TRIMIS systems. CHCS was expected to provide complex support for clinical care among ambulatory and acute care settings in more than 140 military clinics and hospitals. Because of funding constraints and legislation prohibiting the Department of Defense from developing computer-based patient records, CHCS was implemented with functions primarily supporting laboratory, radiology, pharmacy, and patient-appointment scheduling (GAO, 1992). Capabilities for results retrieval and E-mail spanned the care continuum across inpatient and ambulatory settings. Unfortunately, CHCS order entry and patient appointment capabilities were usable only in ambulatory settings (General Accounting Office [GAO], 1992) and support for clinical documentation was never funded (Major Automated Information Systems Review Council [MAISRC], 1998). Similarly, the HIS at Regenstrieff (see Table 1) had support for order communication and ancillary departments, but nursing functions were not developed (McDonald, Blevins, Tierney & Martin, 1988).
The early clinical computing efforts such as those listed in Table 1 were restricted to major tertiary care centers and large government projects. Their foci were on support to acute care, the mainstay of the 1980s when these systems were developed. Institutional HIS were developed or adapted over many years or decades. For example, the HELP system at LDS hospital in Salt Lake City, Utah, has been under gradual development since the late 1960s (Kuperman et al., 1991). CHCS was tailored for military healthcare during its 10-year implementation beginning in 1988. Although functions varied, these early HIS were greatly modified to be integrated with unique care delivery methods, usually at one particular site.
Despite the success of these systems, support for clinical care and nursing practice was limited in the 1970s and 1980s (Ozbolt, Abraham, & Schultz, 1990). Hospitals' survival in this era was in fee-for-service reimbursement; therefore, executives often implemented computerized billing functions first. Care functions were not a priority.
In the late 1980s, HIS' vendors began developing and marketing clinical applications. Major vendors such as Shared Medical Systems, HBOC, Cerner, and others offered capabilities for care plans, nursing documentation, and other functions useful to nurses. The American Nurses' Association published guidelines for nursing information systems in the early 1990s to help guide development of nursing-centered applications (Zielstorff, Hudgings, & Grobe, 1993).
Many early systems are still in use today, and replacements are planned for the military's CHCS, LDS hospital's HELP and the HIS at the NIH Clinical Center. Major vendors often offer applications for nursing activities, but support among institutions remains uneven. For example, CHCS (MAISRC, 1998) and HIS at Registrieff (McDonald et al., 1999) still do not have computing capabilities to support clinical nursing activities. In addition to these early HIS, decision support systems were being developed in the 1980s.
Decision Support Systems
Computerized Decision Support Systems (DSS) are used in patient care decision-making. Haug, Gardner, and Evans (1999) defined four categories of decision support: (a) alerting the care provider to situations of concern, (b) critiquing previous decisions, (c) suggesting interventions at the direct request of the care provider, and (d) retrospective quality assurance reviews.
Dr. Warner was one of the first people interested in using computers to support clinical decision making. As early as the 1950s, he began developing an application for use in diagnosis of congenital heart defects (Warner, Toronto, Veasey, & Stephenson, 1961). Warner's program, called Iliad, along with others such as DxExplain, Internist-I, MYCIN, and QMR, were initial efforts aimed at assisting medical diagnoses (Berner et al., 1994).
Although the earliest DSS were targeted toward support for medical practice, they were also being developed to support nursing practice. The earliest nursing application was the Creighton Online Multiple Modular Expert System or COMMES. Developed in the 1970s, it assisted nurses in care planning activities. The COMMES application was evaluated among several settings and found to be useful in some locations (Thompson, Ryan, & Baggs, 1991). Later DSS prototypes were developed to assist with determining nursing diagnoses (Bradburn, Zeleznikow, & Adams, 1993; Chang & Hirsch, 1991) and training staff to help prevent incontinence in institutionalized, long-term care patients (Petrucci et al., 1992).
Like HIS the earliest DSS were focused more on medical than on nursing care. However, because of the complexities in developing DSS, applications in both disciplines were for a more circumscribed portion of the entire care process such as assistance with determining an appropriate patient care plan. Also DSS were not extensively used because they typically were kept on separate computers from the HIS. The expectation was that providers would enter all needed data into both systems (Miller & Geissbuhler, 1999). Few practitioners were willing to take the time to enter this additional data. Therefore, the early DSS had their greatest use as teaching tools for nursing and medical students and were never well integrated into clinical care.
Current Trends in Clinical Computing
In the late 1980s, a shift occurred from a retrospective, fee-for-service reimbursement structure to a prospective fixedcost structure. Nevertheless, healthcare inflation continued and precipitated a widespread movement toward managed care. With managed care, the traditional physician-oriented focus was shifted to a payer-oriented focus emphasizing health promotion, disease prevention, and cost containment. Concurrently, questions about the appropriateness of medical decisions and the effectiveness of medical care provided momentum for the outcomes movement. To support these shifting foci, integrated healthcare delivery networks were developed by consolidating diverse types of healthcare settings. These integrated enterprises changed not only healthcare delivery structures and processes but also the types of information technology (IT) required to support them.
The Computer-based Patient Record
A computer-based patient record (CPR) is needed to effectively track patient care within managed care networks. A CPR is essential for integrated healthcare networks to be able to accomplish strategic goals of fusing business and clinical operations. The Institute of Medicine (IOM) report on improving patient records (Dick & Steen, 1991) indicated trends toward integration within the healthcare industry and the importance of having a CPR to support these new care delivery methods (HIMSS, 1996). The IOM's recommendations also indicated the need for a longitudinal CPR to integrate and manage all clinical information throughout a person's lifetime in many locations. This new vision for managing clinical information was centered on patient care data across the lifespan and the increasingly important role of interdisciplinary clinical teams (Dick & Steen, 1991).
Advantages of integrated information systems were widely and enthusiastically discussed during the 1990s. Data replication and redundancy would be reduced, information consistency would be enhanced, and availability and accuracy of information would be improved. These systems would facilitate the knowledge work of clinicians, improve the quality of clinical decision-making, and in turn would lead to positive patient care and organizational outcomes.
In addition, the projected financial savings of computerized records are substantial. In ambulatory settings, early clinical intervention and fewer patients' visits can lead to an estimated savings of $15.3 billion a year (HIMSS, 1996). Bossard's presentation and Mulqueen's study (as cited in HIMSS, 1996) indicated that implementation of a CPR could yield annual savings of $12.7 to $36 billion in hospital costs related to decreased adverse reactions, record storage, staff time, more rapid retrieval of clinical information, and improved record review.
Dorenfest-SIAD (1990) presented data from a 1990 national market survey conducted with participants at 3,000 hospitals and estimated that investments in clinical IS were increasing at a rate of 20% to 40% per year. Although integrated clinical IS are the linchpin of emerging healthcare enterprises, the deployment of systems has been slow and fraught with problems.
The Present Status of CPR Systems
Implementing a CPR requires more cooperation and integration between system designers and implementers than was required in the previous isolated efforts of developing HIS and DSS. A fully implemented CPR includes integrated DSS. These applications have not been widely implemented for several reasons. A great investment of labor is needed to develop the knowledge base for a DSS. This initial investment, especially when cost-consciousness is an issue, limits the number of sites willing to devote adequate resources to the task. Standard vocabularies needed for DSS are not yet completed, and effectiveness of the systems has not been fully evaluated. Furthermore, legal and ethical responsibilities for the care recommendations offered in DSS have not yet been fully addressed (Miller & Geissbuhler, 1999).
A notable exception to lack of integrated DSS is the HELP system. For example, the Antibiotic Assistant and the Adult Respiratory Distress Syndrome (ARDS) functions have been successful applications for determining appropriate antibiotic orders and managing patients on mechanical ventilation, respectively (East et al., 1999; Evans, Pestotnik, Classen, & Burke, 1993; Heermann, Thompson, & East, 1999). These applications have been successful largely because of the availability of: (a) the HELP HIS repository of patient data for running the algorithmic rules, (b) a structured vocabulary for decision-making, and (c) a large cadre of researchers and developers interested in DSS.
The development of integrated systems has been built upon tools such as the master patient index and data standardization efforts of the 1990s. A master patient index has a standard number or other organizing element for each patient, thus facilitating data integration for all care episodes across settings and allowing easy information access and retrieval (Adragna, 1998).
Data standardization efforts include standard terms available in classification systems for nursing diagnoses (NANDA), nursing interventions (Nursing Intervention Classification), procedures, and others (Henry, Holzemer, Randell, Hsieh, & Miller, 1997). Although use of standardized terminologies is far from universal, groups such as the American National Standards Institute (ANSI) Healthcare Informatics Standards Board Vocabulary Working Group and the Computer-based Patient Records Institute Working Group on Codes and Structures continue to work toward developing and adopting standard, detailed clinical terminology (Chute, Cohn, & Campbell, 1998).
Despite the promise of integrated systems and solid foundational work to facilitate that integration, CPR efforts have frequently been unsuccessful because of lack of compatibility among various computer applications or systems, differing infrastructure support needs, and cost of the systems. In what have been primarily cost-conservative approaches, integrated IS have been focused on vertical integration with one specific computer system rather than on the horizontal integration among different computer systems; the latter is required for effective patient-centered designs (Matthews & Newell, 1999). Even when these narrow integration efforts are well managed, lengthy system development often makes the final system obsolete because evolving clinical practices have changed during the development and integration phase.
Other persistent problems have been related to consensusbuilding, revising a traditional discipline-specific focus to one which is more interdisciplinary, and gaining a better understanding of the support needs of practitioners. All these issues involve human and organizational challenges and have impeded rapid and successful deployment of CPR systems within integrated healthcare networks.
Several ongoing challenges remain for developing and successfully deploying CPR systems in emerging healthcare networks. Steps toward that goal require the resources of time, money, and people to include (a) strategic planning that links decisions about clinical strategy, care delivery process requirements, and investment in technology; (b) developing standard and effective data models that describe clinical activities, data definitions, and approaches for data integrity; (c) defining common practice standards (i.e., nomenclature, clinical vocabulary, and protocols); (d) addressing efficient, economic, and effective clinical practice processes before automation; (e) investing in "peopleware" (i.e., clinicians and other user groups), particularly in education and training; (f) collaborating, educating, and self-- assessing for quality improvement in an unequivocally interdisciplinary way; (g) rewarding for creativity and innovation; (h) exploring risk-sharing and partnership opportunities with vendors; and (i) refining cost-effectiveness approaches to better support long-term decisions (HIMSS, 1996; Matthews & Newell, 1999).
The Future of Clinical Computing in Healthcare
The healthcare model of the future is not yet certain and healthcare costs show a new surge of inflation. Managed care has become the norm in many sectors of the US and the focus is on outcomes management, care delivery among various settings, and information to support evidence-based practice. Thus, the future of IS for patient care is secure but still uncertain. Two significant trends are important for patient care in the future: integration efforts and the Internet.
Information and Technology Integration
Although implementation of CPR systems is progressing more slowly than was initially anticipated, the trend toward such systems is evident. Siwicki (1999) said that 11% of healthcare facilities had fully computerized systems and 32% had installed CPR hardware and software. As these numbers increase, emphasis will shift from integration of data within one health network to sharing among networks. This change will be made possible by continued advances in data standardization, increased use of the Internet in healthcare, and the implementation of existing technical standards. Furthermore, Web technology, satellites to speed communication, availability of portable computing devices, and other integrated technologies will make computing capability accessible for providers and patients (Jadad, 1999). All institutions, not just major ones, will need clinical computing capabilities not just to be ahead of the competition but to remain viable. These changes could allow more complete and integrated decision support for providers as knowledge workers.
Future providers will be more accepting of IT as a routine part of patient care, much as the telephone is considered a tool for care today. For them, the initial and sometimes painful change to computerized care will be over. The ubiquitous presence of computers in society and the need for technology to help meet regulatory requirements will mandate use of IS in all healthcare facilities. New issues will be how to optimize use of IS in practice (Staggers, Gassert, & Skiba, in press). Providers will need "intuitive" tools to tailor applications quickly to their own practices. This need will be crucial, because providers need applications that fit the way they think and work, especially regarding interdependencies of teams providing patient care. Thus, clinicians will be beyond the current focus on basic computer literacy skills and fundamental information access; they will focus on information synthesis and analysis.
This optimistic view of the future is dependent on the successful resolution of complicated legal, privacy, and security issues (Christiansen, 1999). When data are shared among institutions, the capability of others, such as insurance agencies, to access information can increase. Furthermore, easy availability of information can tempt curious clinicians to access information they should not. How individuals protect health information in integrated systems is a grave concern.
Part of the solution in the US may be contained in the Health Insurance Portability and Accountability Act (HIPAA) of 1996, which includes strict limits on disclosure and use of healthcare information with potential criminal penalties (Christiansen, 1999). HIPAA designers delineated, in part, the development of: (a) national provider identifiers, (b) national patient identifiers, and (c) mandates for individual health information protection. HIPAA does not specifically show how patient information is to be protected, but it does specify penalties for not creating methods to protect patients' confidentiality. The details of implementation are to be issued in regulations from the Department of Health and Human Services. Then, administrators at each institution will develop specific policies and technical strategies to protect patient information.
Internet
Vast amounts of health information are already available on the Internet (Kim, Eng, Deering, & Maxfield, 1999). The University of Utah hospitals and clinics (2000) alone has over 800 patient education documents in both Spanish and English on its Web site. High-speed data lines in world communities and widespread satellites for communication will enable even easier and less expensive access to Internet information (Jadad, 1999).
Consumer informatics and patient-centered information systems (PCIS) will increase. Rather than just record systems useful primarily to providers, new systems will allow information use, data input, and treatment decision-making by patients themselves. An example is Kaiser Permanente's Web strategy (Cross, 2000) for patients to access and input data into clinical systems.
Clinicians are aware that health information on the Internet is of variable quality (Tillman, 1998). Increased availability of information does not guarantee quality. Therefore, clinicians and patients need many critical appraisal skills to evaluate health information on the Internet. Clinicians in formal programs of learning may be more assured than others of receiving evaluation criteria (Kim et al., 1999; Tillman, 1998). People outside these programs, including patients, may not learn how to critically appraise sources and content of information, interpret information to people of varying cultures, and identify good sources of information and Web sites for them (Staggers et al., in press).
Formal programs of study should be shifted from teaching basic computer skills to focusing on high level cognitive functions to manage clinical information with technology. Another strategy may be to have health topics available in a condensed and validated format, such as a digest of reliable sources with high quality information for providers and patients (Jadad, 1999).
Increasingly available health information can allow transformation of clinicians' roles from health experts to information brokers (Clark, 2000). Clinicians are no longer the sole sources of health information, so they will have the responsibility to know, understand, and interpret sources of information to patients and others. Patients are already challenging clinicians with information from the Internet. Clinicians will need a repertoire of skills to engage patients in meaningful dialogues about treatment options. Nurses could be critical purveyors of information, directing patients to valid Websites, identifying reliable sources of information, and teaching evaluation skills to patients.
Communications among providers and patients have been transformed with IT. Patients can now send electronic mail (e-mail) to providers to request simple actions such as prescription refills. The prevalence of e-mail is such that authors are now advising clinicians about coping with e-mail from patients (Lewis, 2000). In the future, patients will likely demand more of these relatively effortless and low-cost communications with clinicians. How clinicians revise their practices to include time to process e-mail from patients will be an organizational and reimbursement issue. How executives redefine productivity will need to include e-mail transactions and Internet activities.
Groups of patients sometimes offer each other health advice in chat rooms and other electronic groups rather than relying on clinicians for advice. Some entrepreneurs even offer to search the Internet for patients and request fees higher than those charged by clinicians for consultations (Jadad, 1999). For providers, the time needed to validate or counter these additional sources of information will not be squeezed into a 10-minute office visit.
For motivated patients of the future, finding on-line information about their diseases, conditions, or therapies will expand. Thus, many of the same evaluation and informational skills being taught to providers should also be taught to patients. The shift in information power and control toward patients is already evident. Some patients request electronic copies of their health information from various healthcare networks and compile their own health records. Patients could perhaps decide which providers have access to which pieces of their health data.
What happens, then, to people without access to IT or without motivation to use Internet resources? Clinicians may need a repertoire of skills and resources to deal with both ends of the spectrum, from highly informed and electronically linked to uninformed and isolated people.
Conclusions
Early hospital information and decision support systems were separate, institution- and provider-centered applications. As managed care began, the vision for IS changed to incorporate longitudinal views of health records. Despite the appeal, this vision has yet to be realized. Information integration to support patient care continues but requires resolution of legal, privacy, and security issues. Continued information and technology integration plus the availability of health information on the Internet can expand patients' information and power, redefine nurses' roles, and create truly patient-centered health records.
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Nancy Staggers, RN, PhD, FAAN, Gamma Rho, Associate Professor; Cheryl Bagley Thompson, RN, PhD, Gamma Rho, Associate Professor; Rita Snyder-- Halpern, RN, PhD, C, CNAA, Gamma Rho, Associate Professor. All at University of Utah, Salt Lake City, UT. The authors thank Col. Bonnie Jennings, RN, DNSc, FAAN, for her thoughtful review of this manuscript. Correspondence to Dr. Staggers, College of Nursing, University of Utah, 10 S. 2000 E. Front, Salt Lake City, UT 84112. E-mail: nancy.staggers@nurs. utah.edu
Accepted for publication August 18, 2000.
Copyright Sigma Theta Tau International, Inc., Honor Society of Nursing First Quarter 2001