AI systems in clinical practice

Decision support systems
Health Evaluation Through Logical Processing
Knowledge-based hospital information system

developed by clinical domains keywords
Department of Medical Informatics, University of Utah, Salt Lake City Multiple Knowledge-based hospital information system
location commissioned status
Hospitals of Intermountain Health Care (IHC), Utah. A trademark of the 3M Corporation. 1975 [Haug et al, 2003] or 1967 [Gardner et al, 1999]. In routine use. HELP II is under development.


"HELP was the first hospital information system to collect patient data needed for clinical decision-making and at the same time incorporate a medical knowledge base and inference engine to assist the clinician in making decisions"   [Gardner et al, 1999].
HELP is a complete knowledge based hospital information system. It supports not only the routine applications of an HIS including ADT, Order Entry/Charge Capture, Pharmacy, Radiology, Nursing documentation, ICU Monitoring, but also supports a robust decision support function. The decision support system has been actively incorporated into the functions of the routine HIS applications. Decision support has been used to provide alerts/reminders, data interpretation, patient diagnosis, patient management suggestions and clinical protocols. Activation of the decision support is provided interactively within the applications and asynchronously through data and time drive mechanisms. The data driven activations is instantiated as clinical data is stored in the patient's computerized medical record. Time driven activation of medical logic is triggered at defined time periods. The HELP system supports an integrated database structure which facilitates the decision support fucntions of HELP. The database structure also lends itself to design of application independent patient reports.


Gardner RM, Pryor TA, Warner HR. The HELP hospital information system: update 1998. Int J Med Inf. 1999 Jun;54(3):169-82.

[PubMed]   [ScienceDirect]

" The HELP hospital information system has been operational at LDS Hospital since 1967. The system initially supported a heart catheterization laboratory and a post open heart Intensive Care Unit. Since the initial installation the system has been expanded to become an integrated hospital information system providing services with sophisticated clinical decision-support capabilities to a wide variety of clinical areas such as laboratory, nurse charting, radiology, pharmacy, etc. The HELP system is currently operational in multiple hospitals of LDS Hospital's parent health care enterprise--Intermountain Health Care (IHC). The HELP system has also been integrated into the daily operations of several other hospitals in addition to those at IHC. Evaluations of the system have shown: (1) it to be widely accepted by clinical staff; (2) computerized clinical decision-support is feasible; (3) the system provides improvements in patient care; and (4) the system has aided in providing more cost-effective patient care. Plans for making the transition from the 'function rich' HELP system to more modern hardware and software platforms are also discussed."


" The HELP system is one of the longest running and most successful clinical information systems. Concepts developed with the HELP system have shown: 1. that clinical care can be provided with such a system; 2. that computerized decision-support is feasible; 3. that computerized decision-support can aid in providing more cost-effective and improved patient care; and 4. that clinical user attitudes toward computerized decision-support are positive and supportive. The major challenges with the ‘success’ of the HELP system is to be able to move forward into the next generation of enterprise-wide ‘integrated’ clinical information systems. The experience provided during the development of the HELP system gives us confidence and enthusiasm to develop the next generation of computerized patient record and decision-support systems. "
Kuperman GJ, Gardner RM, Pryor TA, The HELP System, Springer-Verlag, New York, 1991. " "

Haug PJ, Rocha BH, Evans RS. Decision support in medicine: lessons from the HELP system. Int J Med Inf. 2003 Mar;69(2-3):273-84.

[PubMed]   [ScienceDirect]

" PURPOSE: This report describes an ongoing transition from the HELP Hospital Information System to HELP II, a replacement Health Information System built to manage clinical information captured in a variety of medical settings. The focus of the article is on the medical decision support provided by this system and studied by researchers at the University of Utah and Intermountain Health Care (IHC), a large health care organization in Utah, for many years. METHODS: Select success features of the original HELP system's decision support environment are identified and lessons learned are related. Plans for transferring these features to HELP II are discussed. RESULTS: The article focuses on four features: (1) the importance of easy access to patient data essential for decision support, (2) the commitment to continued measurement and revision of both the logic and the interventional strategy in a decision support application, (3) experience with data mining as a tool for developing decision support tools, and (4) the role of clinical reports in supporting the decision making process. "
References: decision support components

Haug PJ, Gardner RM, Tate KE, Evans RS, East TD, Kuperman G, Pryor TA, Huff SM, Warner HR. Decision support in medicine: examples from the HELP system. Comput Biomed Res. 1994

[PubMed]   []

" Computerized health information systems can contribute to the care received by patients in a number of ways. Not the least of these is through interactions with health care providers to modify diagnostic and therapeutic decisions. Since its beginning, developers have used the HELP hospital information system to explore computerized interventions into the medical decision making process. By their nature these interventions imply a computer-directed interaction with the physicians, nurses, and therapists involved in delivering care. In this paper we describe four different approaches to this intervention. These include: (1) processes that respond to the appearance of certain types of clinical data by issuing an alert informing caregivers of these data's presence and import, (2) programs that critique new orders and propose changes in those orders when appropriate, (3) programs that suggest new orders and procedures in response to patient data suggesting their need, and (4) applications that function by summarizing patient care data and that attempt to retrospectively assess the average or typical quality of medical decisions and therapeutic interventions made by health care providers. These approaches are illustrated with experience from the HELP system. "

Aronsky D, Haug PJ. An integrated decision support system for diagnosing and managing patients with community-acquired pneumonia. Proc AMIA Symp. 1999;:197-201.

[PubMed]   [AMIA]

" Decision support systems that integrate guidelines have become popular applications to reduce variation and deliver cost-effective care. However, adverse characteristics of decision support systems, such as additional and time-consuming data entry or manually identifying eligible patients, result in a "behavioral bottleneck" that prevents decision support systems to become part of the clinical routine. This paper describes the design and the implementation of an integrated decision support system that explores a novel approach for bypassing the behavioral bottleneck. The real-time decision support system does not require health care providers to enter additional data and consists of a diagnostic and a management component. "

Gardner RM, Golubjatnikov OK, Laub RM, Jacobson JT, Evans RS. Computer-critiqued blood ordering using the HELP system. Comput Biomed Res. 1990 Dec;23(6):514-28.

[PubMed]   []

" Recently the medical risk of blood transfusions has emphasized the need to improve the safe use of blood products. For the past 2 1/2 years at LDS Hospital we have used the HELP computer system to assist and critique ordering of blood products "on-line" by physicians and nurses. This report details the computer methods used to order blood products and to critique the appropriateness of those orders. Physicians personally enter the orders for more than 45% of the blood products using computer terminals, whereas 7% are from physician standing orders. Nurses enter the remaining orders from written orders (26%), verbal orders (14%), and phone orders (8%). There were 3396 blood orders for 1043 patients generated by 273 physicians during the fourth quarter of 1989. Each order is justified at the time it is entered by selecting from a menu of physician-approved criteria. The criteria are linked to supportive data in the data base, i.e., laboratory results and clinical data. The computer verified that 82% of these orders met criteria. Quality Assurance nurses verified the remaining 18%. Of these 18% only one in eight required manual chart review. After computer and Quality Assurance review, only eight (0.24%) of the orders were found to be true exceptions to established criteria. Physicians and nurses have accepted the computerized critiquing system. Through use of the computer we provide "on-line" critiquing and improve the use of scarce blood product resources. "

Larsen RA, Evans RS, Burke JP, Pestotnik SL, Gardner RM, Classen DC. Improved perioperative antibiotic use and reduced surgical wound infections through use of computer decision analysis. Infect Control Hosp Epidemiol. 1989 Jul;10(7):316-20.

[PubMed]   []

" A prospective study was performed over a two-year period to determine whether computer-generated reminders of perioperative antibiotic use could improve prescribing habits and reduce postoperative wound infections. During the first year, baseline patterns of antibiotic use and postoperative infection rates were established. During the second year, computer-generated reminders regarding perioperative antibiotic use were placed in the patient's medical record prior to surgery and patterns of antibiotic use and postoperative wound infections monitored. Hospitalized patients undergoing non-emergency surgery from June to November 1985 (3,263 patients), and from June to November 1986 (3,568) were monitored with respect to indications for perioperative antibiotic use, timing of antibiotic use and postoperative infectious complications. Perioperative antibiotic use was considered advisable for 1,621 (50%) patients in the 1985 sample and for 1,830 (51%) patients in the 1986 sample. Among these patients, antibiotics were given within two hours before the surgical incision in 638 (40%) of the 1985 sample and 1,070 (58%) of the 1986 sample (p less than 0.001). Overall, postoperative wound infections were detected in 28 (1.8%) of 1,621 patients in 1985 compared with 16 (0.9%) of 1,830 such patients in 1986 (p less than 0.03). We conclude that computer-generated reminders of perioperative antibiotic use improved prescribing habits with a concurrent decline in postoperative wound infections. "
contact links

Department of Medical Informatics
LDS Hospital
Salt Lake City
Utah 84143

 bullet  Department of Medical Informatics, University of Utah

Archive of AI systems in clinical practice previously administered by Enrico Coiera. Used with permission. Maintained and extended since 2001 by OpenClinical.

Entry on archive: January 2 1995
Last main update: July 21 2004
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