Decision Support Systems

Decision support systems (DSSs) are computer-based applications that use data, models, and knowledge for enhancing effective decision making. The premise is that a decision maker is likely to select the best alternative when all pertinent information regarding each choice and its potential outcome is available. A decision maker can thus evaluate the implications of each decision alternative and choose the one most likely to accomplish the goal. DSS applications are proactive and become the basis for effective planning.

DSS applications use factual historical information (“what was” and “what is”) to provide the ability to forecast (“what can be”) scenarios. By using appropriate representations (models) of a phenomenon, a DSS lets the user evaluate the potential outcome of various assumptions and alternatives. Such applications of information technology are proactive in nature, with the ability to perform various analyses to optimize the process of alternative selection in uncertain (lack of appropriate information) and complex (too many attributes) situations.

Data-based DSS applications are designed for the retrieval of relevant information. Such applications may integrate information from several databases or a data [Page 132]warehouse. Retrieval of patient information and treatment histories is an example. By combining such records with similar profiles, a doctor may become better able to diagnose or predict medical disorders. Model-based DSSs use various mathematical representations to combine several attributes of a phenomenon. Appropriate models can be used to maximize revenues, improve scheduling and staffing, and manage inventories of various supplies. Knowledge-based DSS applications use qualitative expertise and rules (expert systems) to make the expertise of several specialists available to the health care professional.

Health care applications of DSS technologies can be categorized into clinical, financial, and administrative applications. Clinical applications combine the use of medical/clinical knowledge with a patient's characteristics to accurately diagnose a patient's condition, determine proper drug dosage, administer preventive services to given patients at specific times, and carry out diagnostic or therapeutic procedures (Wong, 2000). Many such applications combine the expertise of several specialists. Through such an application, Vanderbilt Hospital has demonstrated huge savings by eliminating unnecessary orders, unnecessarily high drug costs, and delays in patient recovery caused by insufficient information (Morrissey, 2002).

Susquehanna Health System, a multihospital system, is realizing benefits of implementing a comprehensive decision support system that uses data-warehousing technology to provide pertinent patient, administrative, and procedural information (Orefic, 2001). Such systems allow users to determine the optimum service by integrating all relevant facts about the patient, provider network, hospital, and health plan resulting in various efficiencies (Troy, 1999).

Financial applications allow users to analyze the performance of various procedures and processes to best use available resources. Examples include monitoring the financial performance of each activity, determining cost savings, improving collections, and forecasting future financial needs. Administrative applications may include scheduling personnel, managing inventories of supplies, determining staffing requirements, and managing relationships with business partners.