Computer decision support systems are computer applications designed to aid clinicians in making diagnostic and therapeutic decisions in patient care. They can simplify access to data
needed to make decisions, provide reminders and prompts at the time of a patient encounter,
assist in establishing a diagnosis and in entering appropriate orders, and alert clinicians when
new patterns in patient data are recognized. Decision support systems that present patientspecific recommendations in a form that can save clinicians time have been shown to be highly effective, sustainable tools for changing clinician behavior. Designing and implementing such systems is challenging because of the computing infrastructure required, the need for patient data in a machine-processible form, and the changes to existing workflow that may result. Despite these difficulties, there is substantial evidence from trials in a wide range of clinical settings that computer decision support systems help clinicians do a better job caring for patients. As computer-based records and order-entry systems become more common, automated decision support systems will be used more broadly.
Over the last 20 years, computing systems have become increasingly common in health-care settings. Initially they were used for administrative and financial purposes—a role that continues today—butthe use of computer systems to aid clinical decision making is growing. Computer decision support systems are computer applications designed to aid clinicians in making diagnostic and therapeutic decisions in patient care. There is substantial evidence
from trials in a wide range of clinical settings that computer decision support systems help clinicians do a better job caring for patients. Computers are designed to follow predefined instructions provided to them. In health-care decision support systems, these instructions range from simple statements of the form IF this has occurred, THEN do the following pertaining to a specific laboratory result, to highly complex clinical guidelines that include hundreds of interconnected rules. The early use of computers in clinical decision making and one of the most successful uses today involved use of simple rules governing the myriad of small decisions clinicians make every day. For example, IF the patient has the diagnosis of obstructive lung disease, THEN an influenza vaccine should be given annually. As one of the pioneers in
computing decision support systems has stated, “Careful attention to mundane and tedious detail can be more important than brilliance in the day-to-day care of patients . . . the kind of work that humans neither relish nor reliably perform.
How Can Computers Aid Decision Making?
There are several ways that computers can help
clinicians make better decisions. Simplify Access to Data Needed To Make Decisions Most practitioners use computing systems, either directly or indirectly, to gather laboratory results, radiology reports, or the narrative text of notes or consultations. This is because laboratories and transcription services have long used computing systems to report these data. Reporting of results and the creation of a customized report or graph can make patterns more apparent, leading to faster decision making. The value of flow sheets for following chronic conditions has long been recognized.
Graphic display of laboratory data can make patterns rapidly apparent; if combined with display of medications or other interventions, a better understanding of the course of disease may result. This is one of the simplest forms of decision support, and it is highly popular with clinicians because it does not require data entry and saves time.
Provide Reminders and Prompts One of the most powerful tools in the field of clinical computing is the capability to generate reminders and prompts to clinicians. As several reviews have shown, reminders change clinician behavior to improve delivery of chronic, acute, and preventive medical care.4–6 Reminders can be brought to the attention of clinicians in a variety of ways: printed sheets can be affixed to a chart before a visit,7 windows can appear on a screen, or a list of reminders can appear on an electronic “cover sheet.” Usually, reminders include a short message recommending some action be taken along with the rationale for the reminder appearing on that particular patient (Fig 1). Methods of creating, editing, and using rules
to trigger reminders vary greatly among computer decision support systems.8 Assist in Order Entry Among the most successful uses of clinical computing applications is to check orders directly entered by a clinician in real time. Feedback to the clinician through screen dialog boxes can alert the clinician to drug sensitivity, drug-allergy, drug-drug, drug-disease, and drug-laboratory interactions, and potential duplication of services. Orders that should be considered when one order is placed (“corollary” orders, such as blood levels when an aminoglycoside is prescribed) are much more likely to be ordered when presented at the time of order entry.9 If order-entry screens are designed to display the results of previously ordered tests of the type being ordered, test ordering has been shown to be reduced by 13%. Applications to allow direct entry of medication orders are among the most difficult clinical computing applications to develop, yet they have been demonstrated to dramatically reduce serious
medication errors. Assist in Diagnosisn early goal of computing systems used in clinical
care was to help the physician establish a diagnosis. Programs such as Internist 1, Quick Medical Reference (First Data Bank; San Bruno, CA), DXplain (Laboratory of Computer Science; Boston, MA), and Iliad (Applied Medical Informatics; Salt Lake City, UT) were designed to consider historical and physical examination findings, laboratory and test results, and create a list of diagnoses to explain those findings. These systems were based on large collection of rules and tables that related the presence or absence of findings with diseases and other conditions.
Though they performed remarkably well, the requirement that large amounts of data be entered limited their broad use in clinical care. Freestanding applications are now less common than applications that are tightly integrated with patient data in a repository or computer-based medical record system. Moreover, much of the information needed to use these applications—for example the presence or absence of symptoms or physical examination findings is not routinely captured in computing systems in a form that can be processed by decision support systems.
Review New Clinical Data; Alert When Important Patterns Are Recognized Reminders and order checks are useful methods for drawing clinicians’ attention to important occurrences when the clinician is viewing a computer screen or paper chart, or is in the process of ordering. However, in some cases, there is a need to bring clinical events such as a new or changed laboratory result, hospital discharge, or combination of events to the attention of the clinician at the moment the event occurs. Event monitors are applications that can “eavesdrop” on newly available data or the occurrence of events (hospital admission, discharge, etc) by receiving electronic messages from computing systems when specified events occur. When an electronic message is received, a specified rule can then be run to determine if there is a need to notify the clinician or take other action. An example of the use of an event monitor is in the handling of culture and sensitivity results. An event monitor can notify the clinician when there is a mismatch between newly available sensitivity results and antimicrobials being given to the patient.
Characteristics of Successful Computer Decision Support Systems
There is now substantial literature describing the design, implementation, and evaluation of computer decision support systems. From this literature, and from our own experience, we can describe several characteristics of successful computer decision support systems. They Give Patient-Specific Recommendations When a computing system provides advice based on a guideline, it is most useful if the recommendation is based on that patient’s data. Of course, this
requires that data needed to make the recommendation be available to the decision support system in machine-processible form. Collecting these data from their source (laboratory, pharmacy, and other systems) is preferable to requiring data entry by the clinician. Passive display of guideline documents in the literature, on the World Wide Web, or in other
electronic media is not a reliable method for improving compliance or changing practitioner behavior. There are several reasons for this. First, there are myriad guidelines available on the World Wide Web, and finding credible guideline documents quickly can take substantial time.18 Second, no matter how convenient access to the documents becomes, simply viewing a document describing a guideline will be less effective than making it easy to follow thatguideline.
They Save Time Most
clinicians note that they have less time available than in the past, because of increased patient volumes, greater demands for documentation, 19 and the complexity of modern practice. An extremely effective method for changing clinician behavior is to make it as fast or faster to comply with a recommendation or guideline than not to comply. There are many strategies for helping clinicians save time in the process of complying with a guideline. One approach is to save the time required for visit documentation. If applications can guide clinicians through a guideline and at the same time speed documentation of the visit, then there is an additional incentive to use the application, thereby increasing compliance with the guideline.20 If the same application allows simple and fast ordering of services, there is yet another incentive to use the application. Some guidelines can be implemented in part or in full by creating collections of orders that can be
selected in particular clinical situations. For example, when patients are admitted to the hospital for treatment of community-acquired pneumonia, guidelines cover the ordering of cultures and other diagnostic tests, and empirical selection of antibiotics. Collections of orders—often referred to as order sets or order templates—can be created and offered to the clinician either in paper form or in an order-entry application. Since the orders are conveniently grouped to save time during the ordering process, this is a potentially useful method of implementing
some types of guidelines. They Are Incorporated Into Workflow of Clinic, Office, or Hospital Health-care delivery is a complex effort with labor divided among many professions: physicians, nurses, pharmacists, other professionals, and support staff. Computing systems should be designed to fit into this workflow as smoothly as possible, because changing the workflow of large numbers of profesi.
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