The development and evaluation of a hybrid decision support system for clinical decision making: The case of discharge from the military

This article reports on the development, implementation, and evaluation of a decision support system (DSS), a hybrid of a statistical model (regression equation) and expert rules, to support this decision. The study focused on the decisions made by social workers, psychologists, and psychiatrists serving as military mental health officers to recommend discharge from compulsory duty in the Israeli army because of mental or emotional difficulties. The process involved three consecutive steps: modeling decisions by statistical analysis of past and current decisions and by eliciting expert rules, developing o hybrid decision support system, and evaluating the DSS through empirical validation and a user survey. The validity of this hybrid DSS was established. The DSS was able to predict 86.5 percent of new decisions made by mental health officers and 70 percent of post decisions. User acceptance, on the other hand, was low. This article discusses these findings and their implications for practice. Key words; clinical judgment; decision support systems; expert rules; mental health officers; military Social workers and other helping professionals make clinical judgments on a routine basis. Many of these decisions have important consequences for clients. Relying on clinical judgment and expertise, practitioners make daily decisions whether to accept clients for treatment, render services, hospitalize, discharge, or commit to involuntary care; such decisions can be of immeasurable significance to people's lives. Our empirical study of these important judgments and decisions made in the helping professions revealed how these professions are fallible and prone to error (Gambrill, 1990; Gibbs & Gambrill, 1996; Nisbett & Ross, 1980). Almost all clinical decisions are made under some degree of uncertainty (Hogarth, 1980). Many factors in the decision-making process, such as incomplete or unreliable information relevant to the decision, and errors or inconsistencies in the application of decision-making rules introduce uncertainty. Much of the uncertainty results from the probabilistic nature of the outcomes of decisions. Decisions made under what seem to be identical situations lead to different outcomes (Cooksey, 1996). Fallibility, therefore, is an inseparable feature of clinical judgment under uncertainty. Our study focused on the decisions made by social workers, psychologists, and psychiatrists serving as military mental health officers (MHOs) to recommend discharge from compulsory duty in the Israeli military services because of mental or emotional difficulties. This decision has significant consequences for the individual soldier, as well as for the soldier's social environment. Compulsory service in the military is a major duty and right of all Jewish citizens in Israel (most non-Jewish citizens are exempt from compulsory service). A discharge on the basis of psychiatric dysfunction stigmatizes the individual in civilian life. Consequences range from difficulties in obtaining a driver's license or in securing employment to less blatant discriminatory attitudes in Israeli society. On the other hand, a misguided decision not to discharge a dysfunctional soldier may lead to dire outcomes such as psychotic breakdown, suicide, and violent behavior within the unit, which in turn could lead to failure in battle (Benbenishty, Zirlin-Shemesh, & Kaplan, 1993). Military MHOs, the majority of whom are social workers, assess the soldier and decide whether or not to lower the soldier's medical rating on psychiatric grounds, thereby causing an immediate dismissal from the military. This decision is based on clinical judgment and not on any preset requirements or guidelines. Thus, it is open to the same problems in judgment identified in so many other contexts. Furthermore, given the consequences of the decision, the need to maintain consistency among MHOs making the decision is of special importance. …