Biomedical subjects

Marcia Toprac

Publications and source records attributed to Marcia Toprac.

7 recordsLinked to original sources

PubMed2006

An empirical analysis of cost outcomes of the Texas Medication Algorithm Project.

OBJECTIVE: Disease management systems that incorporate medication algorithms have been proposed as cost-effective means to offer optimal treatment for patients with severe and chronic mental illnesses. The Texas Medication Algorithm Project was designed to compare health care costs and clinical outcomes between patients who received algorithm-guided medication management or usual care in 19 public mental health clinics. METHODS: This longitudinal cohort study for patients with major depression (N=350), bipolar disorder (N=267), and schizophrenia (N=309) applied a multi-part declining-effects cost model. Outcomes were assessed by the Inventory of Depressive Symptomatology and the Brief Psychiatric Rating Scale. RESULTS: Compared with patients in usual care, patients in algorithm-based care incurred higher medication costs and had more frequent physician visits, although these differences often became smaller with time. For major depression, algorithm-based care achieved better outcomes sustainable with time but at higher agency and non-agency costs (mixed cost-effective). For bipolar disorder, patients in algorithm-based management achieved better outcomes at lower agency costs (cost-effective). For schizophrenia, patients in algorithm-based care achieved better outcomes that diminished with time, with no detectable difference in health care costs (cost-effective). CONCLUSIONS: Cost outcomes of algorithm-based care and usual care varied by disorder and over time. For bipolar disorder and schizophrenia, algorithm-based care improved outcomes without higher costs for health care services. For major depression, substantively better and sustained outcomes were obtained but at greater costs.

Algorithms↗

PubMed2005

Brief psychiatric rating scale expanded version: How do new items affect factor structure?

Our goal was to suggest a factor structure for the Brief Psychiatric Rating Scale Expanded Version (BPRS-E) based upon a large and diverse sample and to determine which of the new items improved the factors derived from the 18-item version of the scale that have been used in clinical research for decades. We investigated the consistency of our proposed model over time and across demographic groups. As part of the Texas Medication Algorithm Project, the BPRS-E was administered to a total of 1440 psychiatric outpatients in three different diagnostic groups on multiple occasions. The sample was randomly split so that exploratory factor analysis could be done with the first half, and the model could be confirmed on the second half. A four-factor structure including factors assessing depression/anxiety, psychosis, negative symptoms, and activation was found. For each factor, we specify items in the expanded version that added to the breadth of the commonly used clinical factors while improving or maintaining goodness of fit and reliability. The final model proposed was consistent over time and across diagnosis, phase of illness, age, gender, ethnicity, and level of education. The BPRS-E has a stable four-factor structure, making it useful as a clinical outcome measure.

Adult↗

PubMed2005

Effects of job development and job support on competitive employment of persons with severe mental illness.

OBJECTIVES: Few studies have sought to determine which specific supported employment services improve employment outcomes for people with pyschiatric disabilities. This study examined the effects of job development and job support among other services on acquisition and retention of competitive employment. METHODS: Data used in the analysis came from seven sites of the Employment Intervention Demonstration Program. Employment data were collected weekly for a period up to 24 months for 1,340 participants. A random-effects meta-analysis was conducted. RESULTS: Job development increased the probability of obtaining competitive employment. The effects of job development on job acquisition remained after the effects of other factors were controlled for. Job support was associated with more months in the first competitive job but not total hours worked. However, no evidence for the causal role of job support was found in analyses that tested the effects of job support after the job support was provided. The causal role of job support alone was also cast in doubt by the fact that a substantial overlap existed between individuals who received job support and vocational counseling. CONCLUSIONS: Job development is a very effective service when the goal is job acquisition. Job support is associated with retention of a first competitive job, but its causal role is questionable.

Adult↗

PubMed2004

Development of the Brief Bipolar Disorder Symptom Scale for patients with bipolar disorder.

The Brief Bipolar Disorder Symptom Scale (BDSS) is a 10-item measure of symptom severity that was derived from the 24-item Brief Psychiatric Rating Scale (BPRS24). It was developed for clinical use in settings where systematic evaluation is desired within the constraints of a brief visit. The psychometric properties of the BDSS were evaluated in 409 adult outpatients recruited from 19 clinics within the public mental health system of Texas, as part of the Texas Medication Algorithm Project (TMAP). The selection process for individual items is discussed in detail, and was based on multiple analyses, including principal components analysis with varimax rotation. Selection of the final items considered the statistical strength and factor loading of items within each of those factors as well as the need for comprehensive coverage of critical symptoms of bipolar disorder. The BDSS demonstrated good psychometric properties in this preliminary investigation. It demonstrated a strong association with the BPRS24 and performed similarly to the BPRS24 in its relationship to other symptom measures. The BDSS demonstrated superior sensitivity to symptom change, and an excellent level of agreement for classification of patients as either responders or non-responders with the BPRS24.

Ambulatory Care↗

PubMed2004

The Texas medication algorithm project: clinical results for schizophrenia.

In the Texas Medication Algorithm Project (TMAP), patients were given algorithm-guided treatment (ALGO) or treatment as usual (TAU). The ALGO intervention included a clinical coordinator to assist the physicians and administer a patient and family education program. The primary comparison in the schizophrenia module of TMAP was between patients seen in clinics in which ALGO was used (n = 165) and patients seen in clinics in which no algorithms were used (n = 144). A third group of patients, seen in clinics using an algorithm for bipolar or major depressive disorder but not for schizophrenia, was also studied (n = 156). The ALGO group had modestly greater improvement in symptoms (Brief Psychiatric Rating Scale) during the first quarter of treatment. The TAU group caught up by the end of 12 months. Cognitive functions were more improved in ALGO than in TAU at 3 months, and this difference was greater at 9 months (the final cognitive assessment). In secondary comparisons of ALGO with the second TAU group, the greater improvement in cognitive functioning was again noted, but the initial symptom difference was not significant.

Adolescent↗

PubMed2004

Combining evidence-based practice with stakeholder consensus to enhance psychosocial rehabilitation services in the Texas benefit design initiative.

This article describes the use of evidence-based practice along with a multi-stakeholder consensus process to design the psychosocial rehabilitation components in a benefit package of publicly funded mental health services in Texas. The Texas Benefit Design initiative demonstrates how the combination of science and consensus can be used as a powerful tool for change. It applies the findings of rigorous research regarding psychosocial rehabilitation service delivery approaches that achieve positive outcomes in real world, community settings. At the same time, it makes use of the unique knowledge and experience that mental health service consumers, providers and other advocates can bring to service system design and planning.

Consensus↗

PubMed2003

Catching up on health outcomes: the Texas Medication Algorithm Project.

OBJECTIVE: To develop a statistic measuring the impact of algorithm-driven disease management programs on outcomes for patients with chronic mental illness that allowed for treatment-as-usual controls to "catch up" to early gains of treated patients. DATA SOURCES/STUDY SETTING: Statistical power was estimated from simulated samples representing effect sizes that grew, remained constant, or declined following an initial improvement. Estimates were based on the Texas Medication Algorithm Project on adult patients (age > or = 18) with bipolar disorder (n = 267) who received care between 1998 and 2000 at 1 of 11 clinics across Texas. STUDY DESIGN: Study patients were assessed at baseline and three-month follow-up for a minimum of one year. Program tracks were assigned by clinic. DATA COLLECTION/EXTRACTION METHODS: Hierarchical linear modeling was modified to account for declining-effects. Outcomes were based on 30-item Inventory for Depression Symptomatology-Clinician Version. PRINCIPAL FINDINGS: Declining-effect analyses had significantly greater power detecting program differences than traditional growth models in constant and declining-effects cases. Bipolar patients with severe depressive symptoms in an algorithm-driven, disease management program reported fewer symptoms after three months, with treatment-as-usual controls "catching up" within one year. CONCLUSIONS: In addition to psychometric properties, data collection design, and power, investigators should consider how outcomes unfold over time when selecting an appropriate statistic to evaluate service interventions. Declining-effect analyses may be applicable to a wide range of treatment and intervention trials.

Adult↗