Biomedical subjects

M L Crismon

Publications and source records attributed to M L Crismon.

At least 19 recordsLinked to original sources

PubMed2001

Evidence-based pharmacologic treatment for people with severe mental illness: a focus on guidelines and algorithms.

Medication treatment of severe mental illness has been advanced and complicated by the introduction of numerous therapeutic agents. Practice guidelines based on research evidence have been developed to help clinicians make complex decisions. Studies of usual care suggest an important potential role for guidelines in improving the quality of medication treatment for people with severe mental illness. The authors review current evidence-based guidelines for medication treatment of persons with severe mental illness. Four categories of guidelines are described: recommendations, comprehensive treatment options, medication algorithms, and expert consensus. The authors note that more research is needed on optimal next-step strategies and the treatment of patients with comorbidity and other complicating problems. They discuss barriers to the implementation of guidelines, and they observe that the potential of guidelines and algorithms to promote evidence-based medication treatment for persons with severe mental illness depends on refinement of tools, progress in research, and cooperation of physicians, nonphysician clinicians, administrators, and consumers and family members.

Depressive Disorder↗

PubMed2000

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.

Adult↗

PubMed2000

Comparison of three a priori methods and one empirical method in predicting lithium dosage requirements.

The precision and bias of three a priori methods and an empirical method for predicting lithium dosage requirements were studied. Data on serum lithium concentrations were collected from inpatient medical records at a state psychiatric hospital. Predicted daily lithium doses were calculated by using a priori methods proposed by Zetin et al., Jermain et al. and Pepin et al., and an empirical method and compared with the patients' actual dosages. Similar comparisons were made with respect to serum lithium concentrations at steady state. Absolute mean error and mean error were calculated to assess the precision and bias of each a priori method. The records of 47 patients were used in the study. Average mean error for dosage predictions was -130.41, -187.69, 170.80, and -357.23 mg/day for the Jermain, Pepin, Zetin, and empirical methods, respectively. Average mean error for serum lithium concentration predictions was 0.11, -0.09, and 0.37 meq/L for the Jermain, Pepin, and empirical methods, respectively. The Jermain and empirical methods significantly overpredicted concentration and underpredicted dosage. The Zetin method overpredicted dosage. The Pepin method underpredicted dosage but not concentration. The average difference in dosage error among the methods was only 73.3 mg/day. Three a priori dosing methods were similar to an empirical method in their ability to predict lithium dosages. All methods were biased. Although all a priori methods were more precise than the empirical method, the clinical significance is unclear.

Adult↗

PubMed2000

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

Adult↗

PubMed2000

Medical services utilization and charge comparisons between elderly patients with and without Alzheimer's disease in a managed care organization.

OBJECTIVES: The purposes of this study were to describe the health service utilization patterns and the associated charges for elderly patients (aged > or = 65 years) diagnosed with Alzheimer's disease (AD) enrolled in a managed care organization (MCO), and to compare these patterns and charges with those of elderly enrollees not diagnosed with AD (non-AD). METHODS: We analyzed medical claims data over a 12-month period for the population of elderly patients with a diagnosis of AD or AD-related dementia, and for all other elderly patients enrolled in an integrated MCO. Comparisons were made at the level of service location (eg, inpatient hospital, outpatient hospital, physician's office). RESULTS: For a total of 250 patients diagnosed with AD (66.0% female, 34.0% male; mean age. 80.5 years), health care charges were 1.6 times higher per patient per year than the corresponding charges for 13,553 non-AD patients (58.6% female, 41.4% male; mean age, 73.3 years). AD patients received 1.7 times more health care services per patient per year than their non-AD counterparts. CONCLUSIONS: Despite the lack of nursing home and prescription drug data, our results show that AD patients in this MCO used more health care services and had higher annual medical care charges than non-AD patients. If MCOs conduct similar analyses of elderly AD patients' patterns of care and compare these with the patterns of elderly non-AD patients, they may be able to pinpoint areas of disparity in medical care and improve service delivery for AD patients.

Aged↗

PubMed2000

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.

Adrenergic alpha-Agonists↗

PubMed2000

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.

Adrenergic alpha-Agonists↗

PubMed2000

Antipsychotic agents in patients with dementia.

We conducted a MEDLINE search to obtain data on various antipsychotics administered to patients with dementia and psychosis or behavioral symptoms. Additional unpublished data from conference proceedings and unpublished clinical trials were provided by Janssen Pharmaceutica, Eli Lilly and Company, and Zeneca Pharmaceuticals. All clinical trials that evaluated traditional typical or atypical antipsychotics in patients with dementia were reviewed for efficacy and safety data. Consensus guidelines published in 1994 or later were considered. After reviewing clinical trials and expert opinions, we devised an algorithm for optimal treatment of these patients. Although data are limited and do not conclusively show superiority of one agent over another, based on clinical experience and side effect profiles, risperidone is considered to be the drug of choice for treating patients with dementia and psychosis. Alternative treatment options in an algorithmic format also are recommended.

Antipsychotic Agents↗

PubMed2000

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.

Algorithms↗

PubMed1999

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

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

Adolescent↗

PubMed1999

The Texas Medication Algorithm Project: development and implementation of the schizophrenia algorithm.

The Texas Medication Algorithm Project is a program designed to improve the quality of care of persons with serious mental disorders across sites in the Texas public mental health system and to create a uniform clinical environment from which cost estimates can be made. This paper describes the process of developing a pharmacological treatment algorithm for schizophrenia that addresses use of antipsychotics as well as other medications for side effects and co-existing symptoms. Input from clinicians, consultants, and consumers informed development of the algorithm, which was based on existing expert consensus guidelines. Information about the project can be found on the Internet at www.mhmr.state.tx.us/meds/tmap.htm. The authors present and describe the original and current versions of the algorithm, outline the feedback process by which it will be refined, and discuss how new medications will be incorporated as they enter the market.

Algorithms↗

PubMed1999

A critical review of selected pharmacoeconomic analyses of antidepressant therapy.

OBJECTIVE: To evaluate the pharmacoeconomic benefits of treating depression and compare the available therapies by reviewing the current literature on economic analyses of depression. DATA SOURCES: A MEDLINE search (January 1966-June 1998) of English-language literature relating to economic analyses of depression was conducted. Key search terms included depression, antidepressant, economics, pharmacoeconomics, outcomes, and costs. Additional literature was collected from reference lists of articles found through the MEDLINE search. STUDY SELECTION AND DATA EXTRACTION: A MEDLINE search was performed using the above key words. Search and evaluation were limited to pharmacoeconomic evaluations of major depressive disorder. All available studies were considered for inclusion in the review. DATA SYNTHESIS: The advent of newer, brand-name antidepressants as well as increased concern regarding healthcare costs has raised interest in the costs associated with treating depression. Although the selective serotonin-reuptake inhibitors (SSRIs) and other newer antidepressants have higher acquisition costs, both modeling and naturalistic studies have shown that the total cost of treating depression is no higher with SSRIs than with the tricyclic antidepressants. These differences are primarily due to increased patient adherence with the newer agents and lower costs secondary to physician visits, laboratory monitoring, and hospitalization. CONCLUSIONS: The economic aspects of treating depression are becoming more frequently evaluated as newer antidepressant medications become available and as healthcare entities attempt to address increasing costs. In general, most pharmacoeconomic research on depression has been conducted on one of the SSRIs in comparison with various tricyclic antidepressants. These studies frequently use simulation techniques and rely heavily on data from clinical trials. Few studies have compared the newer antidepressants, and no clear evidence exists that any one of these agents is more cost-effective than others. Even fewer studies have addressed the pharmacoeconomics of medication management of depression in various healthcare environments (e.g., public mental health care vs. private psychiatry vs. primary care).

Antidepressive Agents↗

PubMed1999

Seizure associated with olanzapine.

OBJECTIVE: To report a case of seizures in a patient who started receiving olanzapine, and to review seizure risk associated with antipsychotic use. CASE SUMMARY: A 31-year-old African-American woman with multiple psychiatric and medical disorders, including generalized seizure disorder, experienced seizure activity when switched from haloperidol to olanzapine. Olanzapine was discontinued, haloperidol was quickly titrated to the previous dose, and the patient was started on oral phenytoin with no further seizure activity noted. The patient remained seizure free and phenytoin was discontinued without complications. DISCUSSION: Determining causality in this case is complicated by the number of confounding factors that may have contributed to the occurrence of seizures in this patient. These factors include: (1) diagnosis of generalized seizure disorder, (2) diagnosis of organic mental disorder, (3) concurrent pharmacotherapy with medications implicated in lowering the seizure threshold, and (4) abrupt change in pharmacotherapy. The likelihood that a significant drug interaction precipitated seizure activity is doubtful. CONCLUSIONS: Considering all factors related to causality, the likelihood that olanzapine was responsible for precipitating seizure activity in this patient was judged possible. Although premarketing studies have indicated that olanzapine may be associated with minimal seizure liability, this case serves as a reminder that postmarketing surveillance of newly released medications is essential.

Adult↗

PubMed1999

CYP2D6 mutations and therapeutic outcome in schizophrenic patients.

STUDY OBJECTIVE: To investigate whether a relationship exists between the most common known cytochrome P450 (CYP) isozyme 2D6 mutations and schizophrenia. Because most antipsychotic and antidepressant agents interact with CYP2D6, we also investigated clinical outcomes in schizophrenic poor metabolizers (PMs) and extensive metabolizers (EMs). DESIGN: Prospective, observational study. SETTING: Two psychiatric hospitals and a university-affiliated nonpsychiatric hospital. SUBJECTS: Thirty-nine consecutive schizophrenic patients (POP 1), 89 schizophrenics of French Canadian origin (POP 2), and 384 healthy French Canadians (POP 3). INTERVENTION: All study subjects were genotyped for CYP2D6 mutant alleles. POP 1 patients were evaluated before and after 21 or more days of treatment with antipsychotic drugs metabolized at least in part by CYP2D6. MEASUREMENTS AND MAIN RESULTS: Whole blood was collected to determine CYP2D6 alleles *1, *3, *4, *5, *6, and *7 using standard restriction fragment length polymorphisms and polymerase chain reaction techniques. In comparison, CYP2D6 genotypes were determined in POP 2 and POP 3. Twenty-three (59.0%) of 39 patients in POP 1 were genotypically EM homozygotes, 15 (38.4%) were EM heterozygotes, and 1 (2.6%) was a PM. Similar genotype distributions were determined in POP 2 and in POP 3. Genotype distributions for all three populations were in Hardy-Weinberg equilibrium (p>0.05), and there was no significant difference among them (p=0.857). In POP 1, no differences were seen among genotypes in disease symptom severity, number and severity of adverse drug effects, or attitudes toward drug treatment at baseline and at the end of the study. In fact, all patients improved significantly during their hospital stay (all p<0.05), although independent of the CYP2D6 genotype. CONCLUSION: Common CYP2D6 mutant alleles were not associated with schizophrenia or with disease symptoms, antipsychotic-related adverse effects, or attitudes toward treatment.

Adolescent↗

PubMed1999

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

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

Algorithms↗

PubMed1999

The Texas Medication Algorithm Project (TMAP) schizophrenia algorithms.

BACKGROUND: In the Texas Medication Algorithm Project (TMAP), detailed guidelines for medication management of schizophrenia and related disorders, bipolar disorders, and major depressive disorders have been developed and implemented. DISCUSSION: This article describes the algorithms developed for medication treatment of schizophrenia and related disorders. The guidelines recommend a sequence of medications and discuss dosing, duration, and switch-over tactics. They also specify response criteria at each stage of the algorithm for both positive and negative symptoms. The rationale and evidence for each aspect of the algorithms are presented.

Algorithms↗

PubMed1999

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

Medication treatment algorithms have been suggested as a strategy to provide uniform care at predictable costs. The Texas Medication Algorithm Project is a 3-phase study designed to provide solid data on the usefulness of medication algorithms. In phase 1, medication algorithms for the treatment of schizophrenia, major depressive disorder, and bipolar disorder were developed. Phase 2 was a feasibility study of these algorithms, and phase 3, now underway, compares the costs and outcome in 3 groups, one using a combination of an algorithm and patient/family education, a second using treatment as usual in a clinic that uses an algorithm for a different disorder, and a third using treatment as usual in a nonalgorithm clinic.

Algorithms↗

PubMed1999

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

BACKGROUND: This article describes the development of consensus medication algorithms for the treatment of patients with major depressive disorder in the Texas public mental health system. To the best of our knowledge, the Texas Medication Algorithm Project (TMAP) is the first attempt to develop and prospectively evaluate consensus-based medication algorithms for the treatment of individuals with severe and persistent mental illnesses. The goals of the algorithm project are to increase the consistency of appropriate treatment of major depressive disorder and to improve clinical outcomes of patients with the disorder. METHOD: A consensus conference composed of academic clinicians and researchers, practicing clinicians, administrators, consumers, and families was convened to develop evidence-based consensus algorithms for the pharmacotherapy of major depressive disorder in the Texas mental health system. After a series of presentations and panel discussions, the consensus panel met and drafted the algorithms. RESULTS: The panel consensually agreed on algorithms developed for both nonpsychotic and psychotic depression. The algorithms consist of systematic strategies to define appropriate treatment interventions and tactics to assure optimal implementation of the strategies. Subsequent to the consensus process, the algorithms were further modified and expanded iteratively to facilitate implementation on a local basis. CONCLUSION: These algorithms serve as the initial foundation for the development and implementation of medication treatment algorithms for patients treated in public mental health systems. Specific issues related to adaptation, implementation, feasibility testing, and evaluation of outcomes with the pharmacotherapeutic algorithms will be described in future articles.

Algorithms↗