May 2005

Grant Results

SUMMARY

Between 1997 and 2003, the Texas Department of Mental Health and Mental Retardation joined with the state's medical schools and universities in evaluating the clinical and economic impact of an algorithm-guided treatment package on seriously mentally ill patients treated in the Texas public mental health system.

This multiphase initiative, known as the Texas Medication Algorithm Project, was the first effort by a state to create and evaluate medication algorithms for patients in a public mental health system.

In this phase of the project, researchers assessed the clinical and economic impact of algorithm-guided treatment compared with treatment-as-usual in a sample of 926 patients served in public mental health centers.

Key Findings
As summarized their findings in articles in the Journal of Clinical Psychiatry, Archives of General Psychiatry, Schizophrenia Bulletin, and in reports to RWJF:

  • Patients with a history of mania or bipolar disease who were treated with medication algorithms experienced a larger initial decrease in the overall severity of psychiatric symptoms compared to patients receiving treatment-as-usual.
  • There were no differences between the two groups of patients with bipolar disorder with respect to depressive symptoms.
  • All patients with major depressive disorder improved during the 12-month study period, but patients treated with the algorithm package had significantly greater reductions in symptoms and improvement in mental health functioning than patients receiving treatment-as-usual.
  • Treatment with the medication algorithm had its major effect on depressed patients within the first three months but continued to exceed the effects of treatment-as-usual for the entire one-year study period.
  • Substantial symptoms of depression for patients with major depressive disorder remained, even among patients who benefited from algorithm-guided treatment.
  • For patients with schizophrenia, treatment with the medication algorithm produced better symptom reduction than treatment-as-usual, a difference that was statistically significant but clinically modest.
  • Based upon change in symptoms and mental health care costs, cost-effectiveness varied depending on the disorder being treated.
    • For major depressive disorder, while clinical outcomes were better in algorithm treatment, the one-year treatment cost for improvement was somewhat higher.
    • For bipolar disorder, both clinical and cost outcomes were better in the algorithm group.
    • For schizophrenia cost-effectiveness did not differ between algorithm-based care and treatment-as-usual.

Funding
The Robert Wood Johnson Foundation (RWJF) provided two grants to the University of Texas Southwestern Medical Center at Dallas totaling $2,389,581 to support the research study.

RWJF also provided grant of $353,747 to the Texas Department of Mental Health and Mental Retardation for a technical assistance project that helped other states implement the algorithm treatment package.

 See Grant Detail & Contact Information
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THE PROBLEM

In the 1980s and 1990s, as pharmaceutical companies began producing new and more efficacious medications to treat people with serious mental disorders such as depression, bipolar disorder, and schizophrenia, the question arose of how to choose the most appropriate treatment options. Concerns about wide variation in prescribing practices by physicians and complaints from consumer advocates about the negative consequences of this variation spurred the creation of evidence-based guidelines and medication treatment algorithms. Algorithms, more specific than guidelines, are step-by-step procedures for aiding clinical decision-making.

Although they showed promise of improving clinical outcomes and the quality and efficiency of care, no medication algorithms had undergone evaluation for their utility in treating seriously and persistently mentally ill patients, many of whom receive publicly funded care.

In 1995, the Texas Department of Mental Health and Mental Retardation decided to address this research gap by entering into a collaborative relationship with the Texas medical schools and universities, led by the Department of Psychiatry at the University of Texas Southwestern Medical Center, Dallas, and the University of Texas at Austin College of Pharmacy. Their multiphase initiative, known as the Texas Medication Algorithm Project (TMAP), was the first effort by a state to create and evaluate medication algorithms for patients in a public mental health system, 75 percent of whom suffer from one of the three major disorders.

In Phase 1, a research team convened consensus conferences in which panels of experts on mental illness reviewed the literature and constructed evidence-based algorithm-guided disease management packages. Phase 2 of TMAP, completed in 1997, was a four-month feasibility trial that found positive clinical outcomes and a high level of consumer satisfaction among 235 inpatients and outpatients treated with the algorithm packages at 16 clinics in the Texas mental health system.

This initial evidence of the effectiveness of the Texas Medication Algorithm Project increased interest in applying the algorithms in public mental health settings. Before widespread adoption of the algorithms, however, A. John Rush, M.D., TMAP Project Director, argued that a rigorous formal evaluation was important in preventing a "codification of ignorance that mandates implementation of algorithms in patient care without information regarding their effects on clinical outcomes or costs." In addition, as interest in TMAP grew outside Texas, states required technical assistance to build support among stakeholders and funding agencies and to train providers to adapt and implement algorithm-based care in their systems.

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RWJF STRATEGY

This project relates to RWJF's strategic objective, current at the time the grants were issued, of improving chronic illness care through the use of evidence-based disease management protocols or algorithms. TMAP is the first attempt to evaluate clinical and economic outcomes associated with algorithm-based care for seriously mentally ill patients treated in a public mental health system. Since many of these patients are poor, poorly educated and unemployed, the project also addresses RWJF's goal of improving the health and well-being of society's most vulnerable populations.

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THE PROJECT

Phase 3 of TMAP (ID# 031023 and 039931) was a multisite, prospective study that assessed the clinical and economic impact of algorithm-guided treatment compared with treatment-as-usual for patients served in public mental health centers. The intervention tested was a comprehensive disease management package for the treatment of severe and persistent mental illnesses. The intervention package included:

  • Evidence-based medication algorithms for each of the three disorders (schizophrenia, bipolar disease and major depressive disorder); each algorithm has multiple, increasingly complex stages to which patients advance only after simpler treatment fails.
  • Clinical coordinators to enhance patient care, assist the physician in algorithm implementation and provide algorithm prompting.
  • Initial and ongoing education for physicians and clinical coordinators.
  • Ongoing clinical and technical consultation for algorithm implementation.
  • A comprehensive patient/family psychoeducation program.
  • Uniform assessment and documentation of symptoms and side effects at each clinic visit to guide treatment adjustments.
  • Medical documentation system including chart auditing, technical assistance and prompting from on-site clinical coordinators.

A. John Rush, Jr., M.D., of the University of Texas Southwestern Medical Center led the evaluation study (see Appendix 2 for a roster of research group members). The research group received guidance from an External Advisory Group, seven nationally recognized mental health researchers who helped design the evaluation study (see Appendix 3 for a roster of members). The research group tested the hypothesis that patients treated with the algorithm package will experience greater reduction in symptoms and improvement in functioning than those who receive treatment-as-usual. In addition, the researchers predicted that improved symptom outcomes would lead to healthier patients who required fewer mental and general medical services in the long term — thus offsetting program costs and enhancing cost-effectiveness.

At study sites, the team selected 19 outpatient clinics operated by seven local authorities within the Texas public mental health system. To reduce the risk that differences among the clinics would affect clinical outcomes, the researchers matched the clinics by local authority, rural or urban status, and, when feasible, ethnic composition. Twelve of the 19 clinics were intervention sites, offering algorithm treatment for one of the three disorders (four clinics for each disorder). (See Appendix 4 for list of clinics, intervention sites and disorders treated.)

There were two comparison groups, one consisting of patients who received treatment-as-usual at the seven clinic sites that did not use algorithms, and one consisting of patients who received treatment-as-usual at the 12 sites that offered the algorithm package, but for a different illness. The purpose of the second comparison group was to determine if use of an algorithm at a clinic produced a "culture effect" that influenced physicians' treatment of all patients, including those who were not directly receiving algorithm-guided treatment.

The TMAP team recruited and enrolled 1,421 patients from the 19 clinics (465 with schizophrenia, 409 with bipolar disorder and 547 with major depressive disorder). Patient enrollment in the study occurred over 13 months, beginning March 1998 and concluding with the final active patient visit in April 2000. After adjusting the sample size to reduce the impact of baseline differences between the intervention and comparison groups, the researchers analyzed outcomes for a total of 926 patients: 309 with schizophrenia (165 who received algorithm-guided treatment and 144 who received treatment-as-usual); 267 with bipolar disorder (141 who received algorithm-guided care and 126 who received treatment-as-usual); and 350 with major depressive disorder (175 who received algorithm-guided care and 175 who received treatment-as-usual). Outcomes assessed at baseline and periodically for at least one year included:

  1. symptoms
  2. functioning
  3. cognitive functioning (for schizophrenia)
  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
  10. alcohol and substance abuse information.

Under Grant ID# 031023, the researchers completed data collection as well as the major analyses of clinical outcomes to determine if the algorithm package improved symptoms and functioning and reduced side effects compared to treatment-as-usual. Under Grant ID# 039931, the research team continued their analysis of the data and also designed and tested methodological tools and procedures to support the implementation of the Texas Medication Algorithm Project, including measures of clinician adherence to the algorithm treatment protocol and symptom severity. In addition, the researchers conducted a consensus conference in January 2002 to resolve issues concerning the use of both medication and psychotherapy for depressed patients.

Under Grant ID# 038700, Steven Shon, M.D., Medical Director of the Texas Department of Mental Health and Mental Retardation, assembled a project team that responded to requests from other states for technical assistance in implementing the medication algorithms. Goals of the project were to build community, administrative and policy support for the algorithms among stakeholders and funding agencies and to work with providers to adapt and implement algorithm-based care for patients within publicly funded mental health systems.

The research study and technical assistance project had numerous other sources of support, including Texas-based foundations (the Meadows Foundation, Moody Foundation and Nanny Hogan Boyd Charitable Trust), the National Institute of Mental Health, the federal Substance Abuse and Mental Health Services Administration, the Texas Department of Mental Health and Mental Retardation. Eleven pharmaceutical companies, including Pfizer, Wyeth and Janssen Pharmaceutica (a subsidiary of Johnson & Johnson) also supported the project with unrestricted educational grants. The companies, which manufacture many of the new psychotropic medications used in the algorithm-based treatment, contributed about $285,000, less than 5 percent of the $6 million in total project support. Although their contribution was relatively small, project personnel took steps to avoid any appearance of a conflict of interest by restricting the use of their grants to activities unrelated to the development of the algorithms, such as printing, travel and training. (See Appendix 1 for a list of supporters and the amounts provided by each.)

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FINDINGS

The researchers have reported their findings from Phase 3 of the Texas Medication Algorithm Project in numerous articles in peer-reviewed journals. Highlighted below are key clinical findings from three published articles and reports to RWJF. The researchers will report additional findings related to clinical outcomes and other outcomes of interest, including cost, in forthcoming articles.

  • Patients with a history of mania or bipolar disease who were treated with medication algorithms experienced a larger initial decrease in the overall severity of psychiatric symptoms compared to patients receiving treatment-as-usual. They noted that the impact of algorithm-guided treatment may be a function of the algorithm group's ready access to the newer anti-manic agents or to their access to care through the clinical coordinators. In the most severely ill patients, those receiving treatment-as-usual caught up with the algorithm group by the end of the twelve-month period. For patients presenting with moderate psychiatric severity, treatment with the algorithm package appeared to provide an advantage that was sustained over time. ("Texas Medication Algorithm Project, Phase 3 (TMAP-3): Clinical Results for Patients with a History of Mania," in the Journal of Clinical Psychiatry)
  • There were no differences between the two groups of patients with bipolar disorder with respect to depressive symptoms. Although algorithm-treated patients with the highest levels of initial depression showed a significant early effect, the treatment-as-usual group was able to "catch up" over time. This finding may reflect the difficulty of treating depression in patients with bipolar disorder, according to the project director. ("Texas Medication Algorithm Project, Phase 3 (TMAP-3): Clinical Results for Patients with a History of Mania," in the Journal of Clinical Psychiatry)
  • All patients with major depressive disorder improved during the 12-month study period, but patients treated with the algorithm package had significantly greater reductions in symptoms and improvement in mental health functioning than patients receiving treatment-as-usual. When clinicians rated their patients on a thirty-item inventory of depressive symptoms, the reduction for algorithm-treated patients was twice that for treatment-as-usual patients (an average 4.2 point decline on the depression scale for the treatment-as-usual group compared to an 8.6 point decline for the algorithm group). When patients rated their own symptoms, the average self-reported decline for algorithm-treated patients was three times that of the treatment-as-usual patients. ("Clinical Results for Patients with Major Depressive Disorder in the Texas Medication Algorithm Project," in the Archives of General Psychiatry)
  • Treatment with the medication algorithm had its major effect on depressed patients within the first three months but continued to exceed the effects of treatment-as-usual for the entire one-year study period. As they note in their article in the Archives of General Psychiatry, the researchers found no evidence that the treatment-as-usual group caught up with their algorithm-treated counterparts during the ensuing nine months. ("Clinical Results for Patients with Major Depressive Disorder in the Texas Medication Algorithm Project," in the Archives of General Psychiatry)
  • Substantial symptoms of depression for patients with major depressive disorder remained, even among patients who benefited from algorithm-guided treatment. The researchers had previously defined "response to treatment" as occurring when patients achieved at least a 50 percent reduction in their baseline score on the 30-item inventory of depressive symptoms. Researchers considered patients who had achieved an inventory score of 12 or less to be in remission. However, using a subgroup of 118 algorithm-treated patients, researchers found, after one year, an average response rate of only 26.3 percent. They also found that only 11 percent of the patients were in remission. Younger patients and those with full-time employment were more likely to respond. According to the project director, the persistence of symptoms and functional impairment point to the severity and chronicity of the disease, the presence of co-occurring physical problems or a possible treatment resistance among patients in the public mental health system. ("One-Year Clinical Outcomes of Depressed Public Sector Outpatients: A Benchmark for Subsequent Studies," in the World Journal of Biological Psychiatry)
  • For patients with schizophrenia, treatment with the medication algorithm produced better symptom reduction than treatment-as-usual, a difference that was statistically significant but clinically modest. The algorithm group had modestly greater improvement in symptoms during the first quarter of treatment, but the treatment-as-usual group caught up by the end of one year. ("The Texas Medication Algorithm Project: Clinical Results for Patients with Schizophrenia," in Schizophrenia Bulletin)
  • Cognitive functioning was more improved in the algorithm group than in the treatment-as-usual group. The algorithm treatment group had superior effects on improving cognitive functioning at the end of three months, and this difference was even greater at the end of nine months. Since cognition is thought to be more closely associated with daily functioning than are symptoms, these findings are of particular interest. ("The Texas Medication Algorithm Project: Clinical Results for Patients with Schizophrenia," in Schizophrenia Bulletin)

Results

In a report to RWJF, the project team identified the following results of their technical assistance activities:

  • The project team held 71 orientation presentations on the Texas Medication Algorithm Project for groups of stakeholders, who included clinical providers, professional groups, administrators, payers, mental health authority officials, Medicaid officials, behavioral health organizations and consumer advocacy groups. The purpose of these sessions was to spark stakeholders' interest in implementing TMAP within their state mental health system. Although RWJF and federal grants were the primary resource used for training and consultation to organizations that adopted TMAP, various pharmaceutical companies sponsored TMAP staff to present educational seminars on TMAP and evidence-based practices in mental health. This support from the drug industry was the focus of a New York Times article, which questioned whether the drug industry had too much influence over physician education and prescribing practices. (See Communications for details about this article.)
  • Sixteen sites in 12 states and the District of Columbia received training to begin implementation of the medication algorithm project. The states were: New Mexico, Virginia, Ohio, Florida, Illinois, Georgia, Pennsylvania, Nevada, Kentucky, California, Colorado and South Carolina. Rather than implementing algorithms for the three disorders as Texas did, the public mental health sites in these states chose to implement only the schizophrenia algorithm due to concerns about the scarcity of resources and the high cost of antipsychotic drugs. Training consisted of two day-long sessions with an additional day of training for patient educators, consumers and family members.
  • Five additional states (Wyoming, Oregon, Washington, Hawaii and Minnesota) began planning for TMAP implementation. The project team provided these states with training materials for review and conducted teleconferences with them to address system factors that might affect implementation. In addition, mental health organizations in Arizona, Michigan and Connecticut reported to the project team that they implemented programs based on the Texas Medication Algorithm Project on their own without technical assistance from the project team.
  • The project team conducted two quality management studies to evaluate how well clinicians and organizations implemented TMAP. One study examined quality management programs at two Texas community mental health centers and the other examined the effects of staff education on implementation at a state hospital. The project team used their findings to create a quality management toolkit to assist other Texas clinics.
  • The research team created and tested three brief measures to assess the severity of symptoms of depression and psychosis. The team designed a 16-item Quick Inventory of Depressive Symptomatology with both a clinician-rated and self-reported version. The self-report instrument was able to gauge the symptomatic effects of treatment as accurately as the more costly clinician ratings. The team also developed an eight item clinician assessment for psychosis and a ten item clinician assessment for bipolar disorder. These tools streamlined data collection in public-sector clinics, where lengthy assessments are not feasible.
  • The investigators developed a new analytic approach, called Declining Effects Analyses. This tool was used to examine both an initial effect, and a separately estimated time trend, to investigate the impact of TMAP on patient health outcomes.

Communications

More than 50 articles on the Texas Medication Algorithm Project have appeared in the Journal of Clinical Psychiatry, Psychiatry Research, Managed Care, Health Services Research, Journal of the American Academy of Child and Adolescent Psychiatry and other peer-reviewed journals. (See the Bibliography for details.] Over the next two years, Project Directors Rush and Shon and their colleagues plan to publish additional articles on other areas of interest, including treatment costs, service utilization, and physician and patient satisfaction, as they continue their analyses of the data and their implementation of the algorithms in Texas and other states. The researchers have presented their findings at numerous conferences, including annual meetings of the American Psychiatric Association and the American Academy of Child and Adolescent Psychiatry. Procedural manuals describing the three algorithms and how to apply them in clinical settings are available from both the Texas Medication Algorithm Project Web site and Texas Implementation of Medication Algorithm (TIMA) Web site. The Web sites also contain patient/family education materials and users manuals.

TMAP was the subject of a New York Times article, "Making Drugs, Shaping the Rules," (February 1, 2004). In the article, journalist Melody Peterson suggested that the drug companies' support for TMAP, including sponsorship of educational presentations by TMAP staff, may have promoted the new antipsychotic medications by shaping the writing of the medication algorithms and influencing state health officials to recommend them for the treatment of patients in public mental health systems. In a fact sheet, Project Director Shon asserted that TMAP was a response to consumers' concerns about the side effects of the older antipsychotics and their desire for greater consistency in physicians' prescribing of the new drug treatments. He pointed out that TMAP researchers did not accept pharmaceutical funding for algorithm development, using it only for non-related educational purposes. (See the Bibliography for details.)

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SIGNIFICANCE TO THE FIELD

According to Project Director Rush, the Texas Medication Algorithm Project was the first study to assess the effectiveness of treatment algorithms for seriously mentally ill patients in the public mental health sector. In an article entitled, "Texas Medication Algorithm Project, Phase 3 (TMAP-3): Rationale and Study Design" (Journal of Clinical Psychiatry), Rush and his co-authors note that TMAP is remarkable "for the inclusion of a group of severely and persistently ill patients not usually observed in research settings." The ethnically diverse TMAP subjects presented with significant length of illness, poor psychosocial functioning, heavy reliance on public assistance, and substantial concurrent alcohol and drug problems as well as other medical and psychiatric co-morbidities.

In a related article ("One-Year Clinical Outcomes of Depressed Public Sector Outpatients: A Benchmark for Subsequent Studies," published in World Journal of Biological Psychiatry), Rush suggests that these factors, along with treatment resistance and lower quality treatment delivery, may account for the "remarkably low response and remission rates" (26 percent and 11 percent respectively) found in the TMAP population. In contrast, notes Rush, randomized controlled trials, which typically recruit subjects who have minimal concurrent psychiatric and general medical co-morbidities, have found much higher response and remission rates. Rush concludes that the clinical outcomes of the Texas Medication Algorithm Project "clearly suggest that more powerful treatments or the better delivery of available treatments are needed for this patient group."

In a report to RWJF, Rush notes that TMAP has also contributed to the research community's "increased emphasis on multistep treatment studies" and its growing recognition "that only a modest number of patients with any major mental disorder will respond satisfactorily to a single, first step treatment." The National Institute of Mental Health is currently funding the University of Texas Southwestern Medical Center to serve as the National Coordinating Center for Sequenced Treatment Alternatives to Relieve Depression (STAR*D), a study designed to determine which treatment strategies are the most effective for clinically depressed patients who fail to benefit adequately after initial treatment. (See After the Grant for details.)

Limitations

In a number of articles, including "Texas Medication Algorithm Project, Phase 3 (TMAP-3): Rationale and Study Design," the researchers discuss the project limitations but add that "despite its limitations, the results of this study have significant implications for the provision of mental health care." Among the limitations cited are the following:

  • Although the researchers matched the clinics, they did not randomly assign the clinics, patients or physicians to either the algorithm or treatment-as-usual study groups. Lack of randomization opens up the possibility that baseline differences between patient populations at the study clinics, rather than the algorithm package alone, influenced clinical outcomes.
  • The research coordinators who assessed the treatment outcomes were not "blinded" and knew whether the patients belonged to the algorithm or treatment-as-usual group. This awareness could have introduced bias in favor of the algorithm group.
  • TMAP is actually a study of a bundle of interventions, and not just the effects of using medication algorithms. As a result, the researchers could not fully ascertain which of the several components of the disease management program (e.g., algorithms, clinical support, patient/family education) substantially account for any differences between the intervention and treatment-as-usual groups.

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CONCLUSIONS

For patients with serious mental illness, the research team concluded that the algorithm-intervention package produced greater initial and sustained improvement in symptoms when compared to treatment-as-usual. They recommend further research to clarify which elements of the treatment package — e.g., algorithms, clinical support or patient/family education — contributed to the differences between patient groups. They also recommend that future studies need to evaluate how to ensure more consistent implementation of these disease management programs.

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LESSONS LEARNED

Project Directors Rush and Shon identified the following lessons in their reports to RWJF:

  1. To implement treatment algorithms within a system, as opposed to a single clinic or hospital, project leaders need to enlist the support and involvement of a broad spectrum of stakeholders. These include clinical providers, advocacy groups, professional groups, administrators (including fiscal) and legislative and executive government leaders. Repetitive exposure to the algorithm philosophy is necessary for the mental buy-in for change to actually occur. (Project Director/Shon)
  2. When no local champion is available to advocate for algorithm-guided treatment, implementation is still feasible, but the project team needs to provide additional technical assistance in the planning stages. "Local champions, with the skills to lead implementation, were present in some states but not in others," according to the project director. In states that lacked a strong local advocate, the project team provided additional on-site assistance as well as support by telephone, fax and e-mail. (Project Director/Shon)
  3. Performing outcomes research in the public mental health sector is difficult, requiring a collaboration between the public health system and multiple academic institutions. In order to pursue outcomes research within the public mental health system, the historically under-resourced Texas Department of Mental Health Mental Retardation sought alliances with researchers from the academic community, psychiatrists and clinical psychopharmacologists, who are not accustomed to addressing health services-related research. The project team addressed potential problems involved in conducting multidisciplinary, multi-institutional research by creating an organizational structure able to respond to issues on a daily basis while obtaining broad representation for major policy decisions. (Project Director/Rush)
  4. Researchers who study drug therapies and accept financial support from drug companies should have a clear sense of mission. According to former RWJF President Steven Schroeder, M.D., who first oversaw the TMAP project for RWJF, pharmaceutical companies have become a "lightning rod" for negative media attention. Because articles like the New York Times' "Making Drugs, Shaping the Rules" may be published, grantees who accept drug industry support should make sure that "their motives are pure." In the case of TMAP, RWJF saw an opportunity to improve treatment of a vulnerable population — seriously mentally ill patients in public mental health systems. (Former RWJF President/Schroeder)

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AFTER THE GRANT

Phase 3, the research component of the Texas Medication Algorithm Project, has ended. Phase 4, known as the Texas Implementation of Medication Algorithms Project, is under way with the goal of implementing the algorithms in all the clinics and hospitals of the Texas Department of Mental Health and Mental Retardation (now the Texas Department of State Health Services). A grant from the federal Substance Abuse and Mental Health Services Administration (SAMHSA) initially helped support the implementation process.

Efforts continue to expand use of the medication algorithms in other states and countries. California, Illinois and Ohio, which received technical assistance under Grant ID# 038700 to implement the algorithms at selected sites, are in the process of expanding their use statewide. Members of the project team are also planning consensus conferences to revise and update the algorithms for all states implementing them; a May 2004 conference, funded by the Texas Department of Mental Health and Mental Retardation, updated the bipolar algorithm. A conference scheduled for late 2005 will address the depression algorithms.

Several closely related spin-off projects created by members of the project team also continue. They include:

  • Children's Medication Algorithm Project (CMAP), which defines medication practices for the treatment of attention deficit hyperactivity disorder and major depressive disorder in children and adolescents.
  • A computerized decision-support software program (CompTMAP), which allows physicians to enter evaluation data on clients and then guides them to the appropriate medication treatment choice.
  • A study funded by the National Institute of Mental Health to determine the feasibility of using the Quick Inventory of Depressive Symptomatology to assess adolescents and the elderly; it was developed under Grant ID# 039931.
  • Sequenced Treatment Alternatives to Relieve Depression (STAR*D), a large clinical study funded by the National Institute of Mental Health; it explores the use of medication algorithms to benefit patients suffering from treatment-resistance depression.

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GRANT DETAILS & CONTACT INFORMATION

Project

Evaluating the Impact of Medication Algorithms on People with Chronic Mental Illnesses

Grantee

The University of Texas Southwestern Medical Center at Dallas (Dallas,  TX)

  • Development and Evaluation of the Impact of Medication Algorithms for People with Chronic Mental Illnesses
    Amount: $ 1,789,985
    Dates: September 1997 to August 2000
    ID#:  031023

  • Evaluating the Impact of Medication Algorithms on People with Chronic Mental Illnesses
    Amount: $ 599,596
    Dates: September 2000 to September 2003
    ID#:  039931

Contact

A. John Rush, M.D.
(214) 648-4601
john.rush@utsouthwestern.edu

Grantee

State of Texas, Texas Department of Mental Health and Mental Retardation (Austin,  TX)

(now the Texas Department of State Health Services)

  • Amount: $ 353,747
    Dates: June 2000 to August 2003
    ID#:  038700

Contact

Steven P. Shon, M.D.
(512) 206-4502
steven.shon@dshs.state.tx.us

Web Site

http://www.dshs.state.tx.us/mhprograms/TMAP.shtm
http://www.mhmr.state.tx.us/CentralOffice/MedicalDirector/TIMA.html

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APPENDICES


Appendix 1

(Current as of the time of the grant; provided by the grantee organization; not verified by RWJF.)

Texas Medication Algorithm Project Sources of Funding

The following funders awarded grants to support the project:

  • The Houston Endowment, $250,000
  • The Lightner-Sams Foundation, unknown
  • The Meadows Foundation, $725,000
  • Mental Health Connections Research (National Institute of Mental Health), $700,000
  • Nanny Hogan Boyd Charitable Trust, $450,000
  • Substance Abuse and Mental Health Services Administration, $98,193

The following sources contributed in-kind support to the project:

  • Betty Jo Hay Distinguished Chair in Mental Health and the Rosewood Corporation Chair in Biomedical Science (support for Dr. John Rush)
  • Center for Mental Health Services
  • Department of Veterans Affairs
  • Health Services Research and Development Research Career Scientist Award
  • Texas Department of Mental Health and Mental Retardation, $1,300,000
  • United States Pharmacopoeia Convention, Inc.
  • The University of Texas at Austin College of Pharmacy

The following pharmaceutical companies contributed donations of medications and small unrestricted educational grants:

  • Abbott
  • AstraZeneca
  • Bristol-Myers Squibb
  • Eli Lilly
  • Forest
  • GlaxoSmithKline
  • Janssen
  • Novartis
  • Organon
  • Pfizer
  • Wyeth


Appendix 2

Texas Medication Algorithm Project Research Group

(These researchers were integral to the TMAP-3 evaluation study. As provided by the grantee organization in an article entitled "TMAP-3: Rationale and Study Design," published in the Journal of Clinical Psychiatry.)

Rudy Arredondo, Ed.D.
Texas Tech University Health Science Center
Lubbock, Texas

Charles Bowden, M.D.
University of Texas Health Science Center
San Antonio, Texas

Kenny Dudley
Cindy Hopkins
Tex Killion
Vijay Ganju, Ph.D.
Mark Mason, M.S.
Texas Department of Mental Health and Mental Retardation
(now the Texas Department of State Health Services)
Austin, Texas

Alan Swann, M.D.
University of Texas Health Science Center
Houston, Texas

Jeffrey Lieberman, M.D.
University of North Carolina School of Medicine
Chapel Hill, N.C.

Steven Schnee, Ph.D.
Denise Ingham, M.D.
Tuan Nguyen, Ph.D.
MHMR Authority of Harris County
Houston, Texas

Harold Sackeim, Ph.D.
New York State Psychiatric Institute
New York, N.Y.

Robert M.A. Hirschfeld, M.D.
University of Texas Medical Branch
Galveston, Texas

Ross Taylor, M.D.
John T. Montford Psychiatric/Medical Facility
Lubbock, Texas

Daryl Knox, M.D.
Riceland Regional Mental Health Authority
Bay City, Texas

James Doluisio. Ph.D.
Larry Ereshefsky, Pharm. D.
Marvin Shepherd, Ph.D.
The University of Texas at Austin
College of Pharmacy
Austin, Texas

Mark S. Bauer, M.D.
Providence VA Medical Center and Brown University
Providence, R.I.

M. Katherine Shear, M.D.
University of Pittsburgh Medical Center and Western Psychiatric Institute and Clinic
Pittsburgh, Pa.

La Verne Knezek, Ph.D.
Tarrant County MHMR Center
Fort Worth, Texas


Appendix 3

(Current as of the time of the grant; provided by the grantee organization; not verified by RWJF.)

Texas Medication Algorithm Project External Advisory Group

William Hargreaves, Ph.D.
Department of Psychiatry
University of California
San Francisco, Calif.

The-wei Hu, Ph.D.
Department of Social & Administrative Health Services
University of California
Berkeley School of Public Health
Berkeley, Calif.

Anthony Lehman, M.D.
Department of Psychiatry
University of Maryland
College Park, Md.

Susan Essock, Ph.D.
Department of Psychiatry
Mount Sinai School of Medicine
Mount Sinai Hospital
New York, N.Y.

Robert Drake, M.D.
Psychiatric Research Center
Lebanon, N.H.

Barbara Burns, Ph.D.
Departmental Epidemiology Program
Department of Psychiatry/Behavioral Sciences
Duke University Medical Center
Durham, N.C.

Greg Teague, Ph.D.
Dartmouth University
Hanover, N.H.


Appendix 4

Texas Medication Algorithm Project Study and Intervention Sites

Mental Health AuthorityStudy SiteDisorder Treated
El Paso East Valley Clinic*Schizophrenia
Central Clinic
HoustonBayshore Clinic*Major Depressive Disorder
Northwest Clinic*Major Depressive Disorder
Ripley Clinic*Schizophrenia
Southeast Clinic*Bipolar Disorder
Mid City Clinic
LubbockCity Clinic*Schizophrenia
San AntonioCommerce Clinic*Bipolar Disorder
Zarzamora Clinic*Schizophrenia
San Pedro Clinic
Tri-CountyConroe Clinic*Major Depressive Disorder
Cleveland Clinic
Huntsville Clinic
Liberty Clinic
TropicalEdinburg Clinic*Bipolar Disorder
Harlingen Clinic*Major Depressive Disorder
Brownsville Clinic
TylerAndrews Clinic*Bipolar Disorder

* Intervention Site

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BIBLIOGRAPHY

(Current as of date of this report; as provided by grantee organization; not verified by RWJF; items not available from RWJF.)

Book Chapters

Crismon ML and Dorson PG. "Schizophrenia." In Pharmacotherapy: A Pathophysiologic Approach, 5th ed., DiPiro JT, Talbert RL, Yee GC, Matzke GR, Wells BG, Posey LM (eds.). New York: McGraw-Hill, 2002.

Crismon ML and Buckley PF. "Schizophrenia." In Pharmacotherapy: A Pathophysiologic Approach, 6th ed., DiPiro JT, Talbert RL, Yee GC, Matzke GR, Wells BG, Posey LM (eds.). New York: McGraw-Hill, 2005.

Miller AL, Crismon ML, Hall CS, Baker CB. "Advances in Psychopharmacology and Pharmacoeconomics." In Mental Health Services: A Public Health Perspective, 2nd ed., Levin B and Petrila J (eds.). New York: Oxford University Press, 2004.

Miller AL, Dassori A, Ereshefsky L, Crismon ML. "Recent Issues and Developments in Antipsychotic Use." In The Psychiatric Clinics of North America Annual Review of Drug Therapy, 2001, Dunner DL, Rosenbaum JF (eds.). Philadelphia: W.B. Saunders, 2001.

Rago WV and Shon SP. "The Texas Medication Algorithm Project." In Improving Mental Health Care. Commitment to Quality, Dickey B and Sederer LI (eds.). Washington: American Psychiatric Press, 2001.

Rush AJ. "Practice Guidelines and Algorithms." In Treatment of Depression. Bridging the 21st Century, Weissman MM (ed.). Washington: American Psychiatric Press, 2001.

Rush AJ and Kupfer DJ. "Strategies and Tactics in the Treatment of Depression." In Treatments of Psychiatric Disorders, Volume 2, 3rd ed., Gabbard GO (ed.). Washington: American Psychiatric Press, 2001.

Trivedi MH, Kern JK, Voegtle TM, Baker SM,Springer-Verlag Altshuler KZ. "Computerized Medication Algorithms in Behavioral Health Care." In Behavioral Health Care Informatics, Dewan NA, Lorenzi N, Riley R, Bhattacharya SR (eds.). New York: Springer Verlag, 2001.

Trivedi MH, Rush AJ, Crismon ML, O'Neal B, Toprac M. "Treatment Guidelines and Algorithms." In Psychiatric Clinics of North America: Annual of Drug Therapy, Volume 7. Dunner DL and Rosenbaum JF (eds.). Philadelphia: W.B. Saunders, 2000.

Articles

Adli M, Rush AJ, Moller HJ and Bauer M. "Algorithms for Optimizing Treatment of Depression: Making the Right Decision at the Right Time." Pharmacopsychiatry, 36(Suppl. 3): S222–229, 2003. Abstract available online.

Bettinger TL, Crismon ML, Trivedi MH, Grannemann B and Shon SP. "Clinician Adherence to a Major Depressive Disorder Algorithm in the Public Mental Health Sector." Psychiatric Services, 55(6): 703–705, 2004. Abstract available online.

Biggs MM, Shores-Wilson K, Rush AJ, Carmody TJ, Trivedi MH, Crismon ML, Toprac MG and Mason M. "A Comparison of Alternative Assessments of Depressive Symptom Severity: A Pilot Study." Psychiatry Research, 96(3): 269–279, 2000. Abstract available online.

Brown ES, Rush AJ, Biggs MM, Shores-Wilson K, Carmody TJ and Suppes TS. "Clinician Ratings vs. Global Ratings of Symptom Severity: A Comparison of Symptom Measures in the Bipolar Disorder Module, Phase II, Texas Medication Algorithm Project." Psychiatry Research, 117(2):167–175, 2003. Abstract available online.

Chiles JA, Miller AL, Crismon ML, Rush AJ, Krasnoff AS and Shon SP. "The Texas Medication Algorithm Project. Development and Implementation of the Schizophrenia Algorithm." Psychiatric Services, 50(1): 69–74, 1999. Abstract available online.

Chuang WC and Crismon ML. "Evaluation of a Schizophrenia Medication Algorithm in a State Hospital." American Journal of Health-System Pharmacology, 60(14): 1459–1467, 2003. Abstract available online.

Crismon ML, Trivedi MH, Pigott TA, Rush AJ, Hirschfeld RMA, Kahn DA, DeBattista C, Nelson JC, Nierenberg AA, Sackeim HA, Tase ME and the Texas Consensus Conference Panel on Medication Treatment of Major Depressive Disorder. "The Texas Medication Algorithm Project: Report of the Texas Consensus Conference Panel on Medication Treatment of Major Depressive Disorder." Journal of Clinical Psychiatry, 60(3): 142–156, 1999. Abstract available online.

Crismon ML and Canales PL. "Side-Effect Profiles of Antipsychotic Medications: Basis for Individualizing Drug Treatment. Part 1: Typical Antipsychotics." Informed Prescriber, 2(1): 1–4, 2002. Merck-Medco Managed Care, LLC.

Crismon ML and Canales PL. "Side-Effect Profiles of Antipsychotic Medications: Basis for Individualizing Drug Treatment. Part 2: Atypical Antipsychotics." Informed Prescriber, 2(2): 1–4, 2002. Merck-Medco Managed Care, LLC.

Dassori AM, Velligan DI, Prihoda TJ, Miller AL, Chiles JA, Rush J, Shores-Wilson K, Biggs M and Crismon ML. "Ethnic/Racial Comparisons in Symptomatology in a Large Sample of Patients with Schizophrenia in Texas." Schizophrenia Research, 60(Suppl.): 14, 2003.

DeBattista C, Trivedi M, Kern JK and Lembke A. "The Status of Evidence-Based Guidelines and Algorithms in the Treatment of Depression." Psychiatric Annals, 32(11): 2002.

Dennehy EB and Suppes T. "Medication Algorithms for Bipolar Disorder." Journal of Practical Psychiatry and Behavioral Health, 5: 142–152, 1999.

Dennehy EB, Suppes T, Rush AJ, Crismon ML, Witte B and Webster J. "Development of a Computerized Assessment of Physician Adherence to a Treatment Guideline for Patients with Bipolar Disorder." Journal of Psychiatric Research, 38(3): 285–294, 2004. Abstract available online.

Dennehy EB, Suppes T, Crismon ML, Toprac M, Carmody TJ and Rush AJ. "Development of the Brief Bipolar Disorder Symptom Scale for Patients with Bipolar Disorder." Journal of Psychiatric Research, 127: 137–145, 2004.

Dewan NA, Conley D, Svendsen D, Shon SP, Staup JR, Miller AI, Crismon ML, Rush AJ, Trivedi M, Skale T, Keck PE and Strawkowski SM. "A Quality Improvement Process for Implementing the Texas Algorithm for Schizophrenia in Ohio." Psychiatric Services, 54(12): 1646–1649, 2003. Abstract available online.

Emslie GJ, Hughes CW, Crismon ML, Lopez M, Pliszka S, Toprac MG and Boemer C. "A Feasibility Study of the Childhood MDD Medication Algorithm: The Texas Children's Medication Algorithm Project (CMAP)." Journal of the American Academy of Child and Adolescent Psychiatry, 43(5): 519–527, 2004. Abstract available online.

Ereshefsky L. "The Texas Medication Algorithm Project for Major Depression." Managed Care, 10(8 Suppl.): 16–17, 2001.

Gilbert DA, Altshuler KZ, Rago WV, Shon SP, Crismon ML, Toprac MG and Rush AJ. "Texas Medication Algorithm Project: Definitions, Rationale and Methods to Develop Medication Algorithms." Journal of Clinical Psychiatry, 59(7): 345–351, 1998. Abstract available online.

Hollon SD, Jarrett RB, Nierenberg AA, Thase ME, Trivedi M and Rush AJ. "Psychotherapy and Medication in the Treatment of Adult and Geriatric Depression: Which Monotherapy or Combined Treatment?" Journal of Clinical Psychiatry, 66(4): 455–468, 2005. Abstract available online.

Hughes CW, Emslie GJ, Crismon ML, Wagner KD, Birmaher B, Geller B, Pliszka S, Ryan N, Stober M, Trivedi MH, Toprac MG, Sedillo A, Llana ME, Lopez M and Rush AJ. "The Texas Children's Medication Algorithm Project: Report of the Texas Consensus Conference Panel on Medication Treatment of Childhood Major Depressive Disorder." Journal of the American Academy of Child and Adolescent Psychiatry, 38(11): 1442–1454, 1999. Abstract available online.

Kashner TM, Rush AJ and Altshuler KZ. "Measuring Costs of Guideline-Driven Mental Health Care: The Texas Medication Algorithm Project." Journal of Mental Health Policy and Economics, 2: 111–121, 1999.

Kashner TM, Carmody TJ, Suppes T, Rush AJ, Crismon ML, Miller AL, Toprac MG and Trivedi M. "Catching-Up on Health Outcomes: The Texas Medication Algorithm Project." Health Services Research, 38(1 Pt. 1): 311–331, 2003. Abstract available online.

Kashner TM, Rush AJ, Surís A, Biggs MM, Gajewski V, Hooker DJ, Shoaf T and Altshuler KZ. "Impact of Structured Clinical Interviews on Physician Behavior in Community Mental Health Settings." Psychiatric Services, 54(5): 712–718, 2003. Abstract available online.

Lopez MA, Toprac MG, Crismon ML, Boemer C, Baumgartner J, Peyson R and Sheldon S. "A Psychoeducational Program for Children with ADHD or Depression and Their Families: Results from the CMAP Feasibility Study." Community Mental Health Journal, 41(1): 51–66, 2005. Abstract available online.

Mellman TA, Miller AL, Weissman E, Crismon ML, Essock SM and Marder SR. "Evidence-Based Medication Treatment for Severe Mental Illness: A Focus on Guidelines and Algorithms." Psychiatric Services, 52(5): 619–625, 2001. Abstract available online.

Miller AL, Chiles JA, Chiles JK, Crismon ML, Rush AJ and Shon SP. "The Texas Medication Algorithm Project (TMAP) Schizophrenia Algorithms." Journal of Clinical Psychiatry, 60(10): 649–657, 1999. Abstract available online.

Miller AL and Craig CS. "Algorithms for the Treatment of Schizophrenia: An Absolute Need." Journal of Psychotic Disorders: Reviews & Commentaries, 5(3): 3, 2001.

Miller AL, Hall CS, Buchanan RW, Buckley PF, Chiles J, Conley RR, Crismon ML, Ereshefsky L, Essock SM, Finnerty M, Marder SR, Miller D, McEvoy J, Rush AJ, Saeed SA, Schooler NR, Shon S, Stroup S and Tarin-Godoy B. "The Texas Medication Algorithm Project Antipsychotic Algorithm for Schizophrenia: 2003 Update." Journal of Clinical Psychiatry, 65(4): 500–508, 2004. Abstract available online.

Miller AL, Crismon ML, Rush AJ, Chiles J, Kashner M, Toprac M, Carmody T, Biggs M, Shores-Wilson K, Chiles J, Witte B, Bow-Thomas C, Velligan DI, Trivedi M, Suppes T and Shon S. "The Texas Medication Algorithm Project: Clinical Results for Schizophrenia." Schizophrenia Bulletin, 30(3): 627–647, 2004.

Pliszka SR, Greenhill LM, Crismon ML, Sedillo A, Carlson C, Conners MK, McCracken JT, Swanson JM, Hughes CW, Llana M, Lopez M, Toprac M and the Texas Consensus Conference Panel on Medication Treatment of Childhood Attention Deficit Hyperactivity Disorder. "The Texas Children's Medication Algorithm Project: Report of the Texas Consensus Conference Panel on Medication Treatment of Childhood Attention Deficit Hyperactivity Disorder, Part I." Journal of the American Academy of Child and Adolescent Psychiatry, 39(7): 908–919, 2000. Abstract available online.

Pliszka SR, Greenhill LM., Crismon ML, Sedillo A, Carlson C, Conners MK, McCracken JT, Swanson JM, Hughes CW, Llana M, Lopez M, Toprac M and the Texas Consensus Conference Panel on Medication Treatment of Childhood Attention Deficit Hyperactivity Disorder. "The Texas Children's Medication Algorithm Project: Report of the Texas Consensus Conference Panel on Medication Treatment of Childhood Attention Deficit Hyperactivity Disorder, Part II: Tactics." Journal of the American Academy of Child and Adolescent Psychiatry, 39(7): 920–927, 2000. Abstract available online.

Pliszka SR, Lopez M, Crismon ML, Toprac M, Hughes CW, Emslie GJ and Boemer C. "A Feasibility Study of the Children's Medication Algorithm Project (CMAP) Algorithm for the Treatment of ADHD." Journal of the American Academy of Child and Adolescent Psychiatry, 42(3): 279–287, 2003. Abstract available online.

Rush AJ, Crismon ML, Toprac MG, Trivedi MH, Rago WV, Shon S and Altshuler KZ. "Consensus Guidelines in the Treatment of Major Depressive Disorder." Journal of Clinical Psychiatry, 59(Suppl. 20): 73–84, 1998. Abstract available online.

Rush AJ, Crismon ML, Toprac MG, Shon S, Rago WV, Miller AL, Suppes T, Trivedi MH, Biggs MM, Shores-Wilson K, Kashner TM and Altshuler KZ. "Implementing Guidelines and Systems of Care: Experiences with the Texas Medication Algorithm Project (TMAP)." Journal of Practical Psychiatry and Behavioral Health, 5: 75–86, 1999.

Rush AJ, Rago WV, Crismon ML, Toprac MG, Shon SP, Suppes T, Miller AL, Trivedi MH, Swann A, Biggs MM, Shores-Wilson K, Kashner M, Pigott TA, Chiles CA, Gilbert DA and Altshuler KZ. "Medication Treatment for the Severely and Persistently Mentally Ill: The Texas Medication Algorithm Project." Journal of Clinical Psychiatry, 60(5): 284–291, 1999. Abstract available online.

Rush AJ, Crismon ML, Kashner TM, Toprac MG, Carmody TJ, Trivedi MH, Suppes T, Miller AL, Biggs MM, Shores-Wilson K, Witte BP, Shon SP, Rago WV and Altshuler KZ for the TMAP Research Group. "Texas Medication Algorithm Project, Phase 3 (TMAP-3): Rationale and Study Design." Journal of Clinical Psychiatry, 64(4): 357–369, 2003. Abstract available online.

Rush AJ, Trivedi M, Carmody TJ, Biggs MM, Shores-Wilson K, Ibrahim H and Crismon ML. "One-Year Clinical Outcomes of Depressed Public Sector Outpatients: A Benchmark for Subsequent Studies." World Journal of Biological Psychiatry, 56: 46–53, 2004.

Shon SP, Toprac MG, Crismon ML and Rush AJ. "Strategies for Implementing Psychiatric Medication Algorithms in the Public Sector." Journal of Practical Psychiatry and Behavioral Health, 5: 35–39, 1999.

Shon SP, Crismon ML, Toprac MG, Trivedi M, Miller AL, Suppes T and Rush AJ. "Mental Health Care for the Public Perspective: The Texas Medication Algorithm Project." Journal of Clinical Psychiatry, 60(3 Suppl.): 16–20, 1999. Abstract available online.

Shores-Wilson K, Biggs MM, Miller AL, Carmody TJ, Chiles JA, Rush AJ, Crismon ML, Toprac MG, Witte BP and Webster JC. "Itemized Clinician Ratings vs. Global Ratings of Symptom Severity in Patients with Schizophrenia." International Journal of Methods in Psychiatric Research, 11(1): 45–53, 2002. Abstract available online.

Starkweather K and Shon SP. "Implementing Medication Algorithms: The Texas Experience." Psychiatrist Administrator, 1(Spring): 13–18, 2001.

Starkweather K, Shon SP and Crismon ML. "A Texas-Sized Prescription: Providers Report Progress with Medication Guidelines." Behavioral Healthcare Tomorrow, 9(4): 44–46, 2000.

Suppes T, Dennehy EB, Swann AC, Bowden CL, Calabrese JR, Hirschfeld RM, Keck PE Jr, Sachs GS, Crismon ML, Toprac MG, Shon SP and the Texas Consensus Conference Panel on Medication Treatment of Bipolar Disorder. "Report of the Texas Consensus Conference Panel on Medication Treatment of Bipolar Disorder, 2000." Journal of Clinical Psychiatry, 63(4): 288–299, 2002. Abstract available online.

Suppes T, Rush AJ, Dennehy EB, Crismon ML, Kashner TM, Toprac MG, Carmody TJ, Brown ES, Biggs MM, Shores-Wilson K, Witte BP, Trivedi MH, Miller AL, Altshuler KZ and Shon SP. "Texas Medication Algorithm Project, Phase 3 (TMAP-3): Clinical Results for Patients with a History of Mania." Journal of Clinical Psychiatry, 64(4): 370–382, 2003. Abstract available online.

Suppes T, Swann AC, Dennehy EB, Habermacher ED, Mason M, Crismon ML, Toprac MG, Rush AJ, Shon SP and Altshuler KZ. "Texas Medication Algorithm Project: Development and Feasibility Testing of a Treatment Algorithm for Patients with Bipolar Disorder." Journal of Clinical Psychiatry, 62(6): 439–447, 2001. Abstract available online.

Toprac MG, Rush AJ, Conner TM, Crismon ML, Dees M, Hopkins C, Rowe V and Shon SP. "The Texas Medication Algorithm Project Patient and Family Education Program: A Consumer-Guided Initiative." Journal of Clinical Psychiatry, 61(7): 477–486, 2000. Abstract available online.

Torrey WC, Drake RE, Dixon L, Burns BJ, Rush AJ, Clark RE and Klatzker D. "Implementing Evidence-Based Practices for Persons with Severe Mental Illnesses." Psychiatric Services, 52(1): 45–50, 2001. Abstract available online.

Trivedi MH. "Algorithms in Clinical Psychiatry: A Stepped Approach Toward the Path to Recovery." Psychopharmacology Bulletin, 36(2): 142–149, 2002.

Trivedi MH. "Using Treatment Algorithms to Bring Patients to Remission." Journal of Clinical Psychiatry, 64(2 Suppl.): 8–13, 2003. Abstract available online.

Trivedi MH. "Remission of Depression and the Texas Medication Algorithm Project." Managed Care Interface, (Suppl. B): 9–13, 2003.

Trivedi MH, Kern JK, Baker SM and Altshuler KZ. "Computerizing Medication Algorithms and Decision Support Systems for Major Psychiatric Disorders." Journal of Psychiatric Practice, 6(5): 237–246, 2000. Abstract available online.

Trivedi MH, Kern JK, Marcee AK, Kleiber B, Granneman B, Bettinger T, Altshuler KZ and McClelland A. "Development and Implementation of Computerized Clinical Guidelines: Barriers and Solutions." Methods of Information in Medicine, 41(5): 435–442, 2002. Abstract available online.

Trivedi MH and Kleiber BA. "Algorithm for the Treatment of Chronic Depression." Journal of Clinical Psychiatry, 62(Suppl. 6): 22–29, 2001. Abstract available online.

Trivedi MH and Kleiber BA. "Using Treatment Algorithms for the Effective Management of Treatment-Resistant Depression." Journal of Clinical Psychiatry, 62(Suppl. 18): 25–29, 2001. Abstract available online.

Trivedi MH, Rush AJ, Ibrahim HM, Carmody TJ, Biggs MM, Suppes T, Crismon ML, Shores-Wilson K, Toprac MG, Dennehy EB, Witte B and Kashner TM. "The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SIR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SIR) in Public Sector Patients with Mood Disorders. A Psychometric Evaluation." Psychological Medicine, 34(1): 73–82, 2004. Abstract available online.

Trivedi MH, Rush AJ, Crismon ML, Kashner TM, Toprac MG, Carmody TJ, Key T, Biggs MM, Shores-Wilson K, Witte B, Suppes T, Miller AL, Altshuler KZ and Shon SP. "The Texas Medication Algorithm Project (TMAP): Clinical Results for Patients with Major Depressive Disorder." Archives of General Psychiatry, 61(7): 669–680, 2004. Abstract available online.

Velligan DI, Prihoda TJ, Dennehy EB, Biggs MM, Shores-Wilson K, Crismon ML, Rush AJ, Miller AL, Suppes T, Trivedi M, Kashner TM, Witte BS, Toprac M, Carmody T, Chies J and Shon S. "Brief Psychiatric Rating Scale Expanded Version: How Do New Items Affect Factor Structure?" Psychiatry Research, 135(3): 217–228, 2005. Abstract available online.

Velligan DI, DiCocco M, Bow-Thomas C, Cadle C, Glahn DC, Miller AL, Biggs MM, Shores-Wilson K, McKenzie CA and Crismon ML. "A Brief Cognitive Assessment (BCA) for Use with Schizophrenia Patients in a Community Clinic." Schizophrenia Research, 71(2–3): 273–283, 2004. Abstract available online.

Reports

Miller AL, Chiles JA, Chiles J and Crismon ML. TIMA Procedural Manual: Schizophrenia Algorithm. Austin, Texas: Texas Department of Mental Health and Mental Retardation, 2001. Available online.

Miller AL, Hall CS, Crismon ML and Chiles J. TIMA Procedural Manual: Schizophrenia Algorithm (Revised). Austin, Texas: Texas Department of Mental Health and Mental Retardation, 2003. Available online.

Suppes T and Dennehy EB. TIMA Procedural Manual: Bipolar Algorithms. Austin, Texas: Texas Department of Mental Health and Mental Retardation, 2002. Available online.

Trivedi MH, Shon S, Crismon ML and Key T. TIMA Procedural Manual: Depression Algorithms. Austin, Texas: Texas Department of Mental Health and Mental Retardation, 2000. Available online.

Audio-Visuals and Computer Software

Linden M, Bauer M, Trivedi MH and Rush AJ. Treatment Pathways (Algorithms) in Managing Depression, Parts 1 and 2, audiotape from American Psychiatric Association Annual Meeting, May 5–10, 2001, New Orleans, La. Valencia, Calif.: Mobiltape Company, 2001; www.mobiltape.com.

Rush AJ, Crismon ML, Miller AL, Suppes T and Trivedi MH. Results from the Texas Medication Algorithm Project (TMAP), Parts 1 and 2, audiotape from American Psychiatric Association Annual Meeting, May 5–10, 2001, New Orleans, La. Valencia, Calif.: Mobiltape Company, 2001; www.mobiltape.com.

Rush AJ. Updates from the Texas Medication Algorithm Project, videotape from N.Y. Office of Mental Health Best Practices Conference, "Evidence-Based Practices: Challenges and Opportunities," June 10, 2001. www.omh.state.ny.us/omhweb/about.

Rush AJ. Medication Treatment Algorithms for Mental Illness: What Are They? Do They Work? videotaoe from NY Office of Mental Health 11th Institute on Mental Health Management Information, "A Forum on the Integration of Technology and Quality Mental Health Services Delivery," November 7, 2001. www.omh.state.ny.us/omhweb/about.

Toprac M and Baer P. Depression: Moving Towards Recovery, an educational videotape for patients. Austin, Texas: Texas Department of Mental Health and Mental Retardation, 2001.

World Wide Web Sites

www.dshs.state.tx.us/mhprograms/TMAP.shtm. The Web site of the Texas Medication Algorithm Project contains a project overview, procedural manuals (reports) on the three medication algorithms and patient/family educational materials.

www.dshs.state.tx.us/mhprograms/TIMA.shtm. The Web site of the Texas Implementation of Medication Algorithms project contains a project overview, procedural manuals (reports) on implementation of the three medication algorithms and patient/family educational materials.

Sponsored Conferences

"Integrating Psychotherapy into Medication Algorithms for Mood Disorders. A Consensus Conference," January 24–25, 2002, Dallas, Texas. Led by TMAP Project Director and an expert panel of research physicians, psychiatrists and pharmacists. Attended by approximately 60 people, including providers, administrators, consumers, patients, family members and advocates for the mentally ill. Two day-long panel presentations, discussions and recommendations; no workshops.

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Report prepared by: Jayme Hannay
Reviewed by: Robert Crum
Reviewed by: Marian Bass
Program Officer: Constance M. Pechura

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