The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with mood disorders: a psychometric evaluation.

BACKGROUND: The present study provides additional data on the psychometric properties of the 30-item Inventory of Depressive Symptomatology (IDS) and of the recently developed Quick Inventory of Depressive Symptomatology (QIDS), a brief 16-item symptom severity rating scale that was derived from the longer form. Both the IDS and QIDS are available in matched clinician-rated (IDS-C30; QIDS-C16) and self-report (IDS-SR30; QIDS-SR16) formats. METHOD: The patient samples included 544 out-patients with major depressive disorder (MDD) and 402 out-patients with bipolar disorder (BD) drawn from 19 regionally and ethnicically diverse clinics as part of the Texas Medication Algorithm Project (TMAP). Psychometric analyses including sensitivity to change with treatment were conducted. RESULTS: Internal consistencies (Cronbach's alpha) ranged from 0.81 to 0.94 for all four scales (QIDS-C16, QIDS-SR16, IDS-C30 and IDS-SR30) in both MDD and BD patients. Sad mood, involvement, energy, concentration and self-outlook had the highest item-total correlations among patients with MDD and BD across all four scales. QIDS-SR16 and IDS-SR30 total scores were highly correlated among patients with MDD at exit (c = 0.83). QIDS-C16 and IDS-C30 total scores were also highly correlated among patients with MDD (c = 0.82) and patients with BD (c = 0.81). The IDS-SR30, IDS-C30, QIDS-SR16, and QIDS-C16 were equivalently sensitive to symptom change, indicating high concurrent validity for all four scales. High concurrent validity was also documented based on the SF-12 Mental Health Summary score for the population divided in quintiles based on their IDS or QIDS score. CONCLUSION: The QIDS-SR16 and QIDS-C16, as well as the longer 30-item versions, have highly acceptable psychometric properties and are treatment sensitive measures of symptom severity in depression.

Texas Medication Algorithm Project: development and feasibility testing of a treatment algorithm for patients with bipolar disorder.

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

A comparison of alternative assessments of depressive symptom severity: a pilot study.

This study compared the performance of an itemized symptom self-report (Inventory of Depressive Symptomatology - Self-Report; IDS-SR), patient global ratings, and clinician global ratings with an itemized clinician-rated symptom severity measure (Inventory of Depressive Symptomatology - Clinician-Rated; IDS-C) in detecting treatment effects in patients with major depressive disorder (MDD). A total of 28 inpatients (30.8% psychotic) and 34 outpatients (17.9% psychotic) with MDD began treatment that followed the Texas medication algorithm. The clinicians completed the IDS-C and a Physician Global Rating Scale (PhGRS) at each assessment visit, while the patients completed the IDS-SR and a Patient Global Rating Scale (PtGRS). Change scores from the baseline to subsequent weeks were computed for all subjects, utilizing all four measures. The IDS-SR was a significant independent predictor of the response to treatment as compared to the two global ratings. The IDS-SR was as sensitive to change as the IDS-C. While the clinician-rated itemized symptom severity rating scale remains the standard to assess the symptomatic outcome of the treatment of MDD, a self-report of identical symptomatology may be a reasonable alternative for many patients.

The Texas Medication Algorithm Project Patient and Family Education Program: a consumer-guided initiative.

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

A comparison of alternative assessments of depressive symptom severity: a pilot study.

This study compared the performance of an itemized symptom self-report (Inventory of Depressive Symptomatology - Self-Report; IDS-SR), patient global ratings, and clinician global ratings with an itemized clinician-rated symptom severity measure (Inventory of Depressive Symptomatology - Clinician-Rated; IDS-C) in detecting treatment effects in patients with major depressive disorder (MDD). A total of 28 inpatients (30.8% psychotic) and 34 outpatients (17.9% psychotic) with MDD began treatment that followed the Texas medication algorithm. The clinicians completed the IDS-C and a Physician Global Rating Scale (PhGRS) at each assessment visit, while the patients completed the IDS-SR and a Patient Global Rating Scale (PtGRS). Change scores from the baseline to subsequent weeks were computed for all subjects, utilizing all four measures. The IDS-SR was a significant independent predictor of the response to treatment as compared to the two global ratings. The IDS-SR was as sensitive to change as the IDS-C. While the clinician-rated itemized symptom severity rating scale remains the standard to assess the symptomatic outcome of the treatment of MDD, a self-report of identical symptomatology may be a reasonable alternative for many patients.

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. Attention-Deficit/Hyperactivity Disorder.

OBJECTIVES: Expert consensus methodology was used to develop evidence-based, consensually agreed-upon medication treatment algorithms for attention-deficit/hyperactivity disorder (ADHD) in the public mental health sector. Although treatment algorithms for adult mental disorders have been developed, this represents one of the first attempts to develop similar algorithms for childhood mental disorders. Although these algorithms were developed initially for the public sector, the goals of this approach are to increase the uniformity of treatment and improve the clinical outcomes of children and adolescents with ADHD in a variety of treatment settings. METHOD: A consensus conference of academic clinicians and researchers, practicing clinicians, administrators, consumers, and families was convened to develop evidence-based consensus algorithms for the pharmacotherapy of childhood ADHD. After a series of presentations of current research evidence and panel discussion, the consensus panel met and drafted the algorithms along with guidelines for implementation. RESULTS: The panel developed consensually agreed-upon algorithms for ADHD with and without specific comorbid disorders. The algorithms consist of systematic strategies for psychopharmacological interventions and tactics to ensure successful implementation of the strategies. While the algorithms focused on the medication management of ADHD, the conference emphasized that psychosocial treatments are often a critical component of the overall management of ADHD. CONCLUSIONS: Medication algorithms for ADHD can be developed with consensus. A companion article will discuss the implementation of these algorithms.

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. Attention-Deficit/Hyperactivity Disorder.

OBJECTIVES: Expert consensus methodology was used to develop a medication treatment algorithm for attention-deficit/hyperactivity disorder (ADHD). The algorithm broadly outlined the choice of medication for ADHD and some of its most common comorbid conditions. Specific tactical recommendations were developed with regard to medication dosage, assessment of drug response, management of side effects, and long-term medication management. METHOD: The consensus conference of academic clinicians and researchers, practicing clinicians, administrators, consumers, and families developed evidence-based tactics for the pharmacotherapy of childhood ADHD and its common comorbid disorders. The panel discussed specifics of treatment of ADHD and its comorbid conditions with stimulants, antidepressants, mood stabilizers, alpha-agonists, and (when appropriate) antipsychotics. RESULTS: Specific tactics for the use of each of the above agents are outlined. The tactics are designed to be practical for implementation in the public mental health sector, but they may have utility in many practice settings, including the private practice environment. CONCLUSIONS: Tactics for psychopharmacological management of ADHD can be developed with consensus.

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.

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.

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.

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.

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.

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.

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.