Biomedical subjects

Marcia G Toprac

Publications and source records attributed to Marcia G Toprac.

7 recordsLinked to original sources

PubMed2004

Clinical results for patients with major depressive disorder in the Texas Medication Algorithm Project.

CONTEXT: The Texas Medication Algorithm Project is an evaluation of an algorithm-based disease management program for the treatment of the self-declared persistently and seriously mentally ill in the public mental health sector. OBJECTIVE: To present clinical outcomes for patients with major depressive disorder (MDD) during 12-month algorithm-guided treatment (ALGO) compared with treatment as usual (TAU). DESIGN: Effectiveness, intent-to-treat, prospective trial comparing patient outcomes in clinics offering ALGO with matched clinics offering TAU. SETTING: Four ALGO clinics, 6 TAU clinics, and 4 clinics that offer TAU to patients with MDD but provide ALGO for schizophrenia or bipolar disorder. Patients Male and female outpatients with a clinical diagnosis of MDD (psychotic or nonpsychotic) were divided into ALGO and TAU groups. The ALGO group included patients who required an antidepressant medication change or were starting antidepressant therapy. The TAU group initially met the same criteria, but because medication changes were made less frequently in the TAU group, patients were also recruited if their Brief Psychiatric Rating Scale total score was higher than the median for that clinic's routine quarterly evaluation of each patient. MAIN OUTCOME MEASURES: Primary outcomes included (1) symptoms measured by the 30-item Inventory of Depressive Symptomatology-Clinician-Rated scale (IDS-C(30)) and (2) function measured by the Mental Health Summary score of the Medical Outcomes Study 12-item Short-Form Health Survey (SF-12) obtained every 3 months. A secondary outcome was the 30-item Inventory of Depressive Symptomatology-Self-Report scale (IDS-SR(30)). RESULTS: All patients improved during the study (P<.001), but ALGO patients had significantly greater symptom reduction on both the IDS-C(30) and IDS-SR(30) compared with TAU. ALGO was also associated with significantly greater improvement in the SF-12 mental health score (P =.046) than TAU. CONCLUSION: The ALGO intervention package during 1 year was superior to TAU for patients with MDD based on clinician-rated and self-reported symptoms and overall mental functioning.

Adult↗

PubMed2004

A feasibility study of the childhood depression medication algorithm: the Texas Children's Medication Algorithm Project (CMAP).

OBJECTIVE: To evaluate the feasibility and impact on clinical response and function associated with the use of an algorithm-driven disease management program (ALGO) for children and adolescents treated for depression with or without attention-deficit/hyperactivity disorder (ADHD) in community mental health centers. METHOD: Interventions included (1). medication algorithms, (2). clinical and technical support for the physician, (3). uniform chart documentation of outcomes, and (4). a patient/family psychoeducation program. Children eligible for entry into the study were referred to the child psychiatrist for initiation or change in medicine. Outcomes of treatment with the ALGO for up to 4 months are presented. Measures of change included clinical symptoms, functioning, and global improvement (Clinical Global Impression Scale). A historical chart cohort from the same clinics was used as a quasi-control. RESULTS: Thirty-nine individuals (depression = 24; comorbid depression with ADHD = 15) were enrolled for treatment with ALGO. One hundred fourteen children were in the control cohort (74 depressed, 40 comorbid). For the ALGO groups, Children's Depression Rating Scale-Revised depression severity scores decreased from 48.2 to 32.5 and Child Adolescent Functioning Assessment Scale function scores improved from 70.3 to 40.9 (all p < or =.0005). Clinical Global Impression Scale severity scores decreased from 5.7 to 3.7 in ALGO compared to only 5.8 to 4.8 in the control (p <.003). CONCLUSIONS: There was clear improvement in clinical symptoms, functioning, and global response with ALGO treatment. The magnitude of the improvement was greater in children and adolescents treated with the ALGO program compared with a historical cohort. These data support the need for controlled studies in larger populations examining the effects of algorithm-driven disease management programs on the clinical outcomes of children with mental illness.

Adolescent↗

PubMed2003

A feasibility study of the children's medication algorithm project (CMAP) algorithm for the treatment of ADHD.

OBJECTIVE: To determine whether an algorithm for the treatment of attention-deficit/hyperactivity disorder (ADHD) can be implemented in a community mental health center. METHOD: Fifty child and adolescent patients at Texas community mental health centers who met criteria for ADHD were treated according to an algorithm-based disease management program for ADHD. Psychiatrists were trained in the use of the algorithm, and each subject underwent a baseline assessment consisting of a structured interview and standardized rating scales. Subjects were monitored for 4 months. At the end of treatment, the psychiatrists completed the Clinical Global Impression Scale (CGI) and the baseline rating scales were repeated. The primary variables of interest were psychiatrist and family adherence to the algorithm. To examine impact on treatment outcome, the CGI of the algorithm subjects was compared with CGIs based on chart reviews of 118 historical controls. RESULTS: Psychiatrists implemented the major aspects of the algorithm, but the detailed tactics of the algorithm (use of fixed titration of stimulants) were less well adhered to. CONCLUSIONS: An algorithm for the treatment of ADHD can be implemented in a community mental health center.

Adolescent↗

PubMed2003

Texas Medication Algorithm Project, phase 3 (TMAP-3): rationale and study design.

BACKGROUND: Medication treatment algorithms may improve clinical outcomes, uniformity of treatment, quality of care, and efficiency. However, such benefits have never been evaluated for patients with severe, persistent mental illnesses. This study compared clinical and economic outcomes of an algorithm-driven disease management program (ALGO) with treatment-as-usual (TAU) for adults with DSM-IV schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) treated in public mental health outpatient clinics in Texas. DISCUSSION: The disorder-specific intervention ALGO included a consensually derived and feasibility-tested medication algorithm, a patient/family educational program, ongoing physician training and consultation, a uniform medical documentation system with routine assessment of symptoms and side effects at each clinic visit to guide ALGO implementation, and prompting by on-site clinical coordinators. A total of 19 clinics from 7 local authorities were matched by authority and urban status, such that 4 clinics each offered ALGO for only 1 disorder (SCZ, BD, or MDD). The remaining 7 TAU clinics offered no ALGO and thus served as controls (TAUnonALGO). To determine if ALGO for one disorder impacted care for another disorder within the same clinic ("culture effect"), additional TAU subjects were selected from 4 of the ALGO clinics offering ALGO for another disorder (TAUinALGO). Patient entry occurred over 13 months, beginning March 1998 and concluding with the final active patient visit in April 2000. Research outcomes assessed at baseline and periodically for at least 1 year included (1) symptoms, (2) functioning, (3) cognitive functioning (for SCZ), (4) medication side effects, (5) patient satisfaction, (6) physician satisfaction, (7) quality of life, (8) frequency of contacts with criminal justice and state welfare system, (9) mental health and medical service utilization and cost, and (10) alcohol and substance abuse and supplemental substance use information. Analyses were based on hierarchical linear models designed to test for initial changes and growth in differences between ALGO and TAU patients over time in this matched clinic design.

Adolescent↗

PubMed2003

Texas Medication Algorithm Project, phase 3 (TMAP-3): clinical results for patients with a history of mania.

BACKGROUND: The Texas Medication Algorithm Project (TMAP) assessed the clinical and economic impact of algorithm-driven treatment (ALGO) as compared with treatment-as-usual (TAU) in patients served in public mental health centers. This report presents clinical outcomes in patients with a history of mania (BD), including bipolar I and schizoaffective disorder, bipolar type, during 12 months of treatment beginning March 1998 and ending with the final active patient visit in April 2000. METHOD: Patients were diagnosed with bipolar I disorder or schizoaffective disorder, bipolar type, according to DSM-IV criteria. ALGO was comprised of a medication algorithm and manual to guide treatment decisions. Physicians and clinical coordinators received training and expert consultation throughout the project. ALGO also provided a disorder-specific patient and family education package. TAU clinics had no exposure to the medication algorithms. Quarterly outcome evaluations were obtained by independent raters. Hierarchical linear modeling, based on a declining effects model, was used to assess clinical outcome of ALGO versus TAU. RESULTS: ALGO and TAU patients showed significant initial decreases in symptoms (p =.03 and p <.001, respectively) measured by the 24-item Brief Psychiatric Rating Scale (BPRS-24) at the 3-month assessment interval, with significantly greater effects for the ALGO group. Limited catch-up by TAU was observed over the remaining 3 quarters. Differences were also observed in measures of mania and psychosis but not in depression, side-effect burden, or functioning. CONCLUSION: For patients with a history of mania, relative to TAU, the ALGO intervention package was associated with greater initial and sustained improvement on the primary clinical outcome measure, the BPRS-24, and the secondary outcome measure, the Clinician-Administered Rating Scale for Mania (CARS-M). Further research is planned to clarify which elements of the ALGO package contributed to this between-group difference.

Adolescent↗

PubMed2002

Itemized clinician ratings versus global ratings of symptom severity in patients with schizophrenia.

This study compares ratings obtained with an itemized clinician-rated symptom severity measure--the 24-item Brief Psychiatric Rating Scale (BPRS24)--with a Physician Global Rating Scale (PhGRS) and a Patient Global Rating Scale (PtGRS) in assessing treatment outcomes in patients with schizophrenia (SCZ). A total of 91 patients (31 inpatients and 60 outpatients) with SCZ were enrolled in a feasibility study of the use of medication algorithms in the treatment of SCZ. Clinicians completed the BPRS24 and the PhGRS; patients completed the PtGRS at each visit. The analyses reported here were conducted using the original BPRS18 and four items from the BPRS18 that rate the positive symptoms of psychosis (the Positive Symptom Rating Scale or PSRS), comparing anchored with global rating scales and with one another. The PtGRS had the lowest effect size (0.8) and was negatively correlated with the other ratings in inpatients. The PhGRS was significantly correlated (0.46) with the BPRS18, but the same person completed both ratings. The effect size of the PhGRS (0.6) was generally lower than with the BPRS18 (1.4) in differentiating responders from non-responders. On average, the PSRS had a slightly lower effect size than the longer itemized BPRS18, but the results support its use as a quantitative rating in circumstances where it is not feasible to routinely use a lengthier scale.

Adolescent↗

PubMed2002

Report of the Texas Consensus Conference Panel on medication treatment of bipolar disorder 2000.

BACKGROUND: The process and outcome of a consensus conference to develop revised algorithms for treatment of bipolar disorder to be implemented in the public mental health system of Texas are described. These medication algorithms for bipolar disorder are an update of those developed for the Texas Medication Algorithm Project, a research study that tested the clinical and economic impact of treatment guidelines for major psychiatric illnesses treated in the Texas public mental health system (Texas Department of Mental Health and Mental Retardation [TDMHMR]). METHOD: Academic clinicians and researchers, practicing clinicians in the TDMHMR system, administrators, advocates, and consumers participated in a consensus conference in August 2000. Participants attended presentations reviewing new evidence in the pharmacologic treatment of bipolar disorder and discussed the needs of consumers in the TDMHMR system. Principles were enumerated, including balancing of evidence for efficacy, tolerability, and safety in medication choices. A set of 7 distinct algorithms was drafted. In the following months, a subcommittee condensed this product into 2 primary algorithms. RESULTS: The panel agreed to 2 primary algorithms: treatment of mania/hypomania, including 3 pathways for treatment of euphoric symptoms, mixed or dysphoric symptoms, and psychotic symptoms; and treatment of depressive symptoms. General principles to guide algorithm implementation were discussed and drafted. CONCLUSION: The revised algorithms are currently being disseminated and implemented within the Texas public mental health system. The goals of the Texas initiative include increasing the consistency of appropriate treatment of bipolar disorder, encouraging systematic and optimal use of available pharmacotherapies, and improving the outcomes of patients with bipolar disorder.

Algorithms↗