Feedback: a key to improving therapy outcomes.
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Feedback↗
Biomedical subjects
G V Gray
Publications and source records attributed to G V Gray.
Automating psychiatric tasks: taking quality to the next level.
Advances in information technology have allowed the creation of databases and decision support systems for behavioral health care as well as other areas of medicine. The authors describe the state of the art in automating behavioral health care tasks and how automated information analyses provided in real time can measurably improve patient outcomes.
Decision Support Systems, Clinical↗
Primary care and the de facto mental health care system: improving care where it counts.
Only 28% of individuals suffering from psychiatric disorders seek care from mental health specialists. In this paper, the authors describe how the de facto PCP mental health care system gained ground when it seemed the financing and organizational structure of managed care would have predicted the opposite result. They argue that the new realities of mental health practice require new approaches to improving behavioral health treatment. These approaches, they believe, will maximize the benefit of care delivered in and accessed through the primary care office.
Contract Services↗
Psychometric properties of a decision-support tool for the era of managed care.
This article reports psychometric properties of a decision-support scale designed to quantify the decision-making process for allocating psychiatric care. The authors developed a scale to evaluate the level of care needed for patients requiring psychiatric treatment in a health maintenance organization (HMO) setting. This study examines the reliability and validity of that scale by measuring interrater agreement among utilization reviewers from the HMO and between those reviewers and the clinicians who evaluated the patients directly. Agreement (kappa) among the five clinical raters acting in a utilization review capacity on dimensions of the scale ranged from .71 to .98. Kappas for agreement between the treatment intensity proposed by the reviewer/rater and used by the treating clinician were .41, .38, .40, .35, .36, and .39, respectively. The scale is reliable in the hands of trained personnel. Although there were important differences between clinicians' ratings and those of utilization review raters, these differences do not suggest that use of the scale would limit patient access to care.
Connecticut↗
Psychiatric decision making in the 90's: the coming era of decision support.
Guidelines for how mental health care is allocated form a pivotal point on the fulcrum balancing preservation of quality care and containment of costs. Advances in information system technology are creating new opportunities for research-based decision support tools in this area. Such tools can systematically and reliably scale the domains of evidence used in psychiatric assessment in order to more precisely describe the severity of impairment and point to appropriateness of care decisions. The first psychiatric decision support tools were introduced in the 1960s in response to changes in the mental health community, but research in this area tended to have limited inter-rater reliability or validity. More recently, several computerized decision support tools have been developed, with a stronger research base and consequently a wider application. These tools are reviewed, and one such tool is described in greater depth to illustrate the possibilities of computer technology and the direction in which decision support software is headed.
Decision Support Techniques↗