"The [NAMI] Chicago branch has distributed materials from the [NAMI] Web site (Strategies for patients who are non-compliant and Levels of recovery from psychotic disorders) to 500 members," he added. "Instructors at the University of Minnesota division of health sciences teach from the Web site. Many Web sites have requested permission to create a link to the algorithm Web site. Despite the above, the potential for use would be far greater, based on experience in local performance improvement field trials and the informatics literature, if this kind of decision support were integrated into the workflow through computerized medical records. Answers to questions must be accessible extremely quickly and at the moment the question occurs to the clinician or the information will rarely be used. This is a major challenge."
Patterson and Osser also believe that clinicians would be more apt to use algorithms if they covered a greater number of specific clinical situations, especially those involving comorbid psychiatric and physical illnesses. Another challenge to the widespread use of algorithms is their need for desktop computers, which are difficult to use in typical clinical encounters. To help solve this problem, they noted that handheld versions are planned.
Madhukar Trivedi, M.D., professor at the University of Texas Southwestern Medical Center, department of psychiatry, said the algorithm products associated with the Texas Medication Algorithm Project are in use in 13 states. Trivedi has followed the work of Clement J. McDonald, M.D., who recommends that the algorithm be placed at the site of clinical decision for ease of reference.
Trivedi and colleagues noted (Methods Inf Med 2002;41:435-442):
Research indicates that computerized decision support systems (CDSSs) can improve clinical performance and patient outcomes, and yet CDSSs are not in widespread use. Physician guidelines, in general, face barriers in implementation. Guidelines in a computerized format can have novel aspects that have to be, considered, aspects such as technical problems/support and user interface issues that can act as barriers. Though the literature points out that human, organizational, and technical issues can act as barriers in the implementation of CDSSs, studies clearly indicate that there are methods that can overcome these barriers and improve CDSS acceptance and use. These methods come from lessons learned from a variety of CDSS implementation ventures. Notably, most of the methods that improve acceptance and use of a CDSS require feedback and involvement of end-users. Measuring and, addressing physician or user attitudes toward the computerized support system has been shown to be important in the successful implementation of a CDSS.
Making the algorithm available at the point of the clinical treatment decision, whether by PDA or other CDSS, can assist in utilizing the algorithm. A second way is utilizing the informatics field of innovation diffusion. Arun Vishwanath, Ph.D., M.B.A., professor at the University at Buffalo School of Informatics, says that an algorithm, like a product or an idea, can have its diffusion "exponentially increased by converting the opinion leaders to its use."
Stanford University department of psychiatry's Psychotic Depression Algorithm has had a suboptimal hit rate, according to Charles DeBattista, M.D., despite having many useful features and a large reference base. Thus, to paraphrase the father of information science Claude Shannon: Technical accuracy and semantic precision do not equate with effectiveness of diffusion.
The current project between CINP and IPAP to produce algorithms for the treatment of schizophrenia has to deal with the disparate formularies in different countries. A second issue is cost, which prohibits the use of a number of newer medications to some degree in all countries, but particularly in developing countries. The algorithms proposed for the treatment of schizophrenia can look very different, depending on the regulatory and financially practical formularies.
I am aware of early discussions between the developers of guidelines algorithms and officials involved in Medicaid and private managed care with a purpose of simultaneously focusing on quality of care and cost containment. Vishwanath pointed out that innovation diffusion is very different in closed or hierarchical systems than in the open population of potential users.