Biomedical subjects

M G Toprac

Publications and source records attributed to M G Toprac.

7 recordsLinked to original sources

PubMed1999

Clinical and economic impact of newer versus older antipsychotic medications in a community mental health center.

This pilot study was conducted to compare both the clinical effectiveness and the treatment costs of newer (atypical) antipsychotic medications (clozapine and risperidone) with those of older (classic) neuroleptic medications (chlorpromazine and haloperidol) for psychosis in a community mental health care setting. The study used a retrospective, uncontrolled, open, nonrandomized, within-subjects design and relied on medical records as a data source for 37 clients. All clients received older antipsychotics for at least 1 year, newer antipsychotics for a transition period of 3 months, and the newer agents for at least an additional year. The newer antipsychotic medications were more effective and less costly (total cost of care, $3000 less per client per year [1997 dollars]) than the older medications. Effect-size estimates for the measured variables provide a guide for future research into the cost-effectiveness of these newer medications within the community mental health care setting. These findings can provide policy makers with guidance on treating people with major mental disorders in the most effective and efficient manner. Because of limited budgets, community mental health centers making the investment in newer, more expensive medications to improve client outcomes have to maintain the same or lower total cost of care. Results of the current study suggest that short-term investment in the newer medications by community mental health centers offers superior clinical effectiveness and lower long-term overall cost of care.

Adult↗

PubMed1999

The Texas Children's Medication Algorithm Project: report of the Texas Consensus Conference Panel on Medication Treatment of Childhood Major Depressive Disorder.

OBJECTIVES: To develop consensus guidelines for medication treatment algorithms for childhood major depressive disorder (MDD) based on scientific evidence and clinical opinion when science is lacking. The ultimate goal of this approach is to synthesize research and clinical experience for the practitioner and to increase the uniformity of preferred treatment for childhood MDD. A final goal is to develop an approach that can be tested as to whether it improves clinical outcomes for children and adolescents with MDD. METHOD: A consensus conference was held. Participants included academic clinicians and researchers, practicing clinicians, administrators, consumers, and families. The focus was to review and use clinical evidence to recommend specific pharmacological approaches for treatment of MDD in children and adolescents. After a series of presentations of current research evidence and panel discussion, the consensus panel met, agreed on assumptions, and drafted the algorithms. The process initially addressed strategies of treatment and then tactics to implement the strategies. RESULTS: Consensually agreed-upon algorithms for major depressions (with and without psychosis) and comorbid attention deficit disorders were developed. Treatment strategies emphasized the use of selective serotonin reuptake inhibitors. The algorithm consists of systematic strategies for treatment interventions and recommended tactics for implementation of the strategies, including medication augmentation and medication combinations. Participants recommended prospective evaluation of the algorithms in various public sector settings, and many volunteered as sites for such an evaluation. CONCLUSIONS: Using scientific and clinical experience, consensus-derived algorithms for children and adolescents with MDD can be developed.

Adolescent↗

PubMed1999

Medication treatment for the severely and persistently mentally ill: the Texas Medication Algorithm Project.

This article provides an overview of the issues involved in developing, using, and evaluating specific medication guidelines for patients with psychiatric disorders. The potential advantages and disadvantages, as well as the essential elements in the structure of algorithms, are illustrated by experience to date with the Texas Medication Algorithm Project, a public-academic collaboration. Phase 1 entailed assembling research findings on the efficacy of medications for schizophrenic, bipolar, and major depressive disorders. This knowledge was evaluated for its quality and relevance, integrated with expert clinical judgment as well as input by practicing clinicians, family advocates, and patients. Phase 1 (the design and development of the algorithms) was followed by a feasibility test (Phase 2). Phase 3 is an ongoing evaluation comparing the clinical and economic effects of using specific medication guidelines (algorithms) versus treatment as usual in public sector patients with severe and persistent mental illnesses.

Algorithms↗

PubMed1999

Mental health care from the public perspective: the Texas Medication Algorithm Project.

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.

Algorithms↗

PubMed1998

The development of a statewide continuous evaluation system for the Texas Children's Mental Health Plan: a total quality management approach.

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.

Adolescent↗

PubMed1998

Texas Medication Algorithm Project: definitions, rationale, and methods to develop medication algorithms.

BACKGROUND: 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. DISCUSSION: 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.

Algorithms↗

PubMed1998

Consensus guidelines in the treatment of major depressive disorder.

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.

Algorithms↗