Marcia G. Toprac

Use of treatment guidelines for treatment of major psychiatric illnesses has increased in recent years. The Texas Medication Algorithm Project (TMAP) was developed to study the feasibility and process of developing and implementing guidelines for bipolar disorder, major depressive disorder, and schizophrenia in the public mental health system of Texas. This article describes the consensus process used to develop the first set of TMAP algorithms for the Bipolar Disorder Module (Phase 1) and the trial testing the feasibility of their implementation in inpatient and outpatient psychiatric settings across Texas (Phase 2). The feasibility trial answered core questions regarding implementation of treatment guidelines for bipolar disorder. A total of 69 patients were treated with the original algorithms for bipolar disorder developed in Phase 1 of TMAP. Results support that physicians accepted the guidelines, followed recommendations to see patients at certain intervals, and utilized sequenced treatment steps differentially over the course of treatment. While improvements in clinical symptoms (24-item Brief Psychiatric Rating Scale) were observed over the course of enrollment in the trial, these conclusions are limited by the fact that physician volunteers were utilized for both treatment and ratings. and there was no control group. Results from Phases 1 and 2 indicate that it is possible to develop and implement a treatment guideline for patients with a history of mania in public mental health clinics in Texas. TMAP Phase 3, a recently completed larger and controlled trial assessing the clinical and economic impact of treatment guidelines and patient and family education in the public mental health system of Texas, improves upon this methodology.

Educating patients with mental illness and their families about the illness and its treatment is essential to successful medication (disease) management. Specifically, education provides patients and families with the background they need to participate in treatment planning and implementation as full "partners" with clinicians. Thus, education increases the probability that appropriate and accurate treatment decisions will be made and that a treatment regimen will be followed. The Texas Medication Algorithm Project (TMAP) has incorporated these concepts into its philosophy of care and accordingly created a Patient and Family Education Program (PFEP) to complement the utilization of medication algorithms for the treatment of schizophrenic, bipolar, and major depressive disorders. This article describes how a team of mental health consumers, advocates, and professionals developed and implemented the PFEP. In keeping with the TMAP philosophy of care, consumers were true partners in the program's development and implementation. They not only created several components of the program and incorporated the consumer perspective, but they also served as program trainers and advocates. Initially, PFEP provides basic and subsequently more in-depth information about the illness and its treatment, including such topics as symptom monitoring and management and self-advocacy with one's treatment team. It includes written, pictorial, videotaped, and other media used in a phased manner by clinicians and consumer educators, in either individual or group formats.

Medication treatment algorithms have been suggested as a strategy to provide uniform care at predictable costs. The Texas Medication Algorithm Project is a 3-phase study designed to provide solid data on the usefulness of medication algorithms. In phase 1, medication algorithms for the treatment of schizophrenia, major depressive disorder, and bipolar disorder were developed. Phase 2 was a feasibility study of these algorithms, and phase 3, now underway, compares the costs and outcome in 3 groups, one using a combination of an algorithm and patient/family education, a second using treatment as usual in a clinic that uses an algorithm for a different disorder, and a third using treatment as usual in a nonalgorithm clinic.

The Texas Medication Algorithm Project (TMAP), a public-academic collaborative effort, is a 3-phase project to develop, implement, and evaluate medication treatment algorithms for public sector patients with schizophrenia, major depressive disorders, or bipolar disorders. This paper, the first in a series describing the activities of the TMAP, focuses on the various definitions and reasons why guidelines have gained popularity. Also discussed are their strengths, the limitations of the various methods used to develop them, and potential barriers to their implementation.

The article presents a description of processes involved in developing and implementing a statewide continuous evaluation system for the Texas Children's Mental Health Plan (TCMHP) and quality management tools used to approach implementation challenges. Implementation issues are discussed relating to stakeholder involvement, evaluation design evolution, measurement method modification, evaluation integration, staff training, data quality control, communication of results, and use of results in decision making. A review of implementation processes suggests evaluation design and activities should be seen as constantly evolving in response to ongoing stakeholder input. Involving stakeholders in design and implementation can result in increased data quality, data-informed decision making to improve service delivery, and increased public accountability. The TCMHP evaluation system development demonstrates that quality management tools can provide a useful framework to work through design and implementation problems, and a continuous evaluation system can provide an infrastructure for meeting data needs in a managed care environment.

The number of available antidepressant medications has increased dramatically in the last 10 years. Furthermore, no single medication is a panacea for all depressed patients-a fact underscored by randomized, controlled trial evidence showing that when one medication fails, an alternative may succeed. Thus, a key issue in the treatment of depression is how to optimally orchestrate available medication options to maximally benefit the greatest number of patients most rapidly. One approach is the use of consensus guidelines or medication algorithms. This paper discusses the rationale for and critical issues in the development of medication algorithms, and the timely use of symptom measures to ensure proper implementation. Once developed, guidelines must be appropriately implemented by clinicians, adhered to by patients, and supported by administrators. These three stakeholder groups often need education, incentives, and ongoing support to implement such guidelines. Whether guidelines actually improve outcome is largely uninvestigated, although a recent study of depressed patients in primary care found that using guidelines did improve outcome but at an increased treatment cost. The clinical and economic impact of guideline-driven treatment for the severe and persistently depressed deserves study.