Risk-adjusted outcome models for public mental health outpatient programs.
OBJECTIVE: To develop and test risk-adjustment outcome models in publicly funded mental health outpatient settings. We developed prospective risk models that used demographic and diagnostic variables; client-reported functioning, satisfaction, and quality of life; and case manager clinical ratings to predict subsequent client functional status, health-related quality of life, and satisfaction with services. DATA SOURCES/STUDY SETTING: Data collected from 289 adult clients at five- and ten-month intervals, from six community mental health agencies in Washington state located primarily in suburban and rural areas. Data sources included client self-report, case manager ratings, and management information system data. STUDY DESIGN: Model specifications were tested using prospective linear regression analyses. Models were validated in a separate sample and comparative agency performance examined. PRINCIPAL FINDINGS: Presence of severe diagnoses, substance abuse, client age, and baseline functional status and quality of life were predictive of mental health outcomes. Unadjusted versus risk-adjusted scores resulted in differently ranked agency performance. CONCLUSIONS: Risk-adjusted functional status and patient satisfaction outcome models can be developed for public mental health outpatient programs. Research is needed to improve the predictive accuracy of the outcome models developed in this study, and to develop techniques for use in applied settings. The finding that risk adjustment changes comparative agency performance has important consequences for quality monitoring and improvement. Issues in public mental health risk adjustment are discussed, including static versus dynamic risk models, utilization versus outcome models, choice and timing of measures, and access and quality improvement incentives. (+info)
Evaluation of outcomes for atypical antipsychotic therapy and psychosocial rehabilitation in a community mental health center setting. Based on a presentation by Douglas Noordsy, MD.
Efficacy studies provide information on drug safety and its effect on symptoms, but their designs limit the general application of results to other settings. Functional outcomes, although difficult to measure, offer the most complete view of a medication's effect on the patient. A community mental health center (CMHC) is a common forum for treating schizophrenic patients, which presents an opportunity to study a drug's effect on patients in a natural setting. This study setting is useful because in the community patients face daily life situations, interact with family members and caregivers, and may suffer from comorbid illnesses or conditions that can affect outcomes. Douglas Noordsy, MD, Medical Director of the Mental Health Center of Greater Manchester, New Hampshire, has begun a study to examine the effectiveness of olanzapine compared with the effectiveness of typical antipsychotic medications in the CMHC setting. The initial data in Dr. Noordsy's study confirm the benefits of olanzapine for clinical symptoms and suggest positive results for functional outcomes in the future. (+info)
Mental health costs and access under alternative capitation systems in Colorado.
OBJECTIVE: To examine service cost and access for persons with severe mental illness under Medicaid mental health capitation payment in Colorado. Capitation contracts were made with two organizational models: community mental health centers (CMHCs) that manage and deliver services (direct capitation [DC]) and joint ventures between CMHCs and a for-profit managed care firm (managed behavioral health organization, [MBHO]) and compared to fee for service (F.F.S.). DATA SOURCES/STUDY SETTING: Both primary and secondary data were collected for the year prior to the new financing policy and the following two years (1995-1998). STUDY DESIGN: A stratified random sample of 522 severely mentally ill subjects was selected from comparable geographic areas within the capitated and FFS regions of Colorado. Major variables include service cost, utilization, and access (probability of service use) derived from secondary claims data, subject reported access collected at six-month intervals, and baseline outcomes (symptoms, functioning, and quality of life). PRINCIPAL FINDINGS: In comparison to the FFS area, cost per person was reduced in the capitated areas in each of the two years following implementation. By the end of year two, cost per person was reduced by two-thirds in the MBHO areas and by one-fifth in the DC areas. Reductions in access were found for both capitated areas, although reductions in utilization for those receiving service were found only in the MBHO model. CONCLUSIONS: Medicaid mental health capitation in Colorado resulted in cost reducing service changes for persons with severe mental illness. Assessment of outcome change is necessary to identify cost effectiveness. (+info)
Two-year outcomes of fee-for-service and capitated medicaid programs for people with severe mental illness.
OBJECTIVE: To examine the effects of two models of capitation on the clinical outcomes of Medicaid beneficiaries in the state of Colorado. DATA SOURCE: A large sample of adult, Medicaid beneficiaries with severe mental illness drawn from regions where capitation contracts were (1) awarded to local community mental health agencies (direct capitation), (2) awarded to a joint venture between local community mental health agencies and a large, private managed behavioral health organization, and (3) not awarded and care continued to be reimbursed on a fee-for-service basis. STUDY DESIGN: The three samples were compared on treatment outcomes assessed over 2 years (total n = 591). DATA COLLECTION METHODS: Study participants were interviewed by trained, clinical interviewers using a standardized protocol consisting of the GAF, BPRS, QOLI, and CAGE. PRINCIPAL FINDINGS: Outcomes were comparable across most outcome measures. When outcome diffrences were evident, they tended to favor the capitation samples. CONCLUSIONS: Medicaid capitation in Colorado does not appear to have negatively affected the outcomes of people with severe mental illness during the first 2 years of the program. Furthermore, the type of capitation model was unrelated to outcomes in this study. (+info)
HIV testing policy and serious mental illness.
OBJECTIVES: Using opinion data from experts, we examined the context of the argument for mandatory testing of psychiatric patients. METHODS: Vignettes were distributed to experts on HIV and mental illness. Respondents were asked to provide appropriateness ratings for different hypothetical clinical decisions regarding HIV management. RESULTS: Respondents were reluctant to impose testing without informed consent in most circumstances. The presence of risk factors or danger to another increased appropriateness ratings modestly. CONCLUSIONS: Despite experts' tendency to emphasize individual rights, public reluctance to mandate testing is unlikely to extend to people with serious mental illness. No argument for mandatory testing can be persuasive if improved voluntary testing can achieve adequate detection rates. Voluntary testing protocols should be studied to determine which successfully identify infected individuals. (+info)
Catching up on health outcomes: the Texas Medication Algorithm Project.
OBJECTIVE: To develop a statistic measuring the impact of algorithm-driven disease management programs on outcomes for patients with chronic mental illness that allowed for treatment-as-usual controls to "catch up" to early gains of treated patients. DATA SOURCES/STUDY SETTING: Statistical power was estimated from simulated samples representing effect sizes that grew, remained constant, or declined following an initial improvement. Estimates were based on the Texas Medication Algorithm Project on adult patients (age > or = 18) with bipolar disorder (n = 267) who received care between 1998 and 2000 at 1 of 11 clinics across Texas. STUDY DESIGN: Study patients were assessed at baseline and three-month follow-up for a minimum of one year. Program tracks were assigned by clinic. DATA COLLECTION/EXTRACTION METHODS: Hierarchical linear modeling was modified to account for declining-effects. Outcomes were based on 30-item Inventory for Depression Symptomatology-Clinician Version. PRINCIPAL FINDINGS: Declining-effect analyses had significantly greater power detecting program differences than traditional growth models in constant and declining-effects cases. Bipolar patients with severe depressive symptoms in an algorithm-driven, disease management program reported fewer symptoms after three months, with treatment-as-usual controls "catching up" within one year. CONCLUSIONS: In addition to psychometric properties, data collection design, and power, investigators should consider how outcomes unfold over time when selecting an appropriate statistic to evaluate service interventions. Declining-effect analyses may be applicable to a wide range of treatment and intervention trials. (+info)
Measuring continuity of care for clients of public mental health systems.
OBJECTIVES: The aims of this research were to generate a set of time-variant measures of continuity of outpatient care using administrative data, and to evaluate the validity of these measures for persons in the community with serious mental illness (SMI) who use public mental health services. DATA SOURCES: Individuals with SMI were identified using multistage random sampling from shelters, streets, and public mental health clinics in Houston, Texas. STUDY DESIGN: The study design was observational, cross-sectional, and retrospective. Based on a review of the literature, five distinct conceptual dimensions of continuity of care were defined: timeliness, intensity, comprehensiveness, stability, and coordination. Repeated measures of continuity were generated for each day of the year. Construct validity was assessed by comparing continuity for housed persons and homeless persons based on the assumption that homelessness is a risk factor for low continuity of outpatient care. DATA COLLECTION: Subjects were interviewed to collect sociodemographic and clinical information. Service use was retrospectively tracked through the administrative records of multiple public sector agencies. PRINCIPAL FINDINGS: All five continuity measures demonstrated good construct validity by the fact that homelessness was significantly (p < 0.001) and substantially associated with lower continuity of care. DISCUSSION: The five continuity-of-care measures are relatively easy and inexpensive to generate using administrative data. The five continuity-of-care measures may be useful for identifying individuals at risk for poor outcomes and for evaluating the ability of public service systems to keep clients engaged in care over time. (+info)
The 'quiet' crisis in mental health services.
The failure of insurers and managed care organizations to reimburse providers of mental health services for the costs of care has led to a crisis in access to these services. Using the situation in Massachusetts as a case example, this paper explores the impact of this defunding. Unable to sustain continued losses, hospitals are closing psychiatric units, and outpatient services are contracting or closing altogether. The situation has been compounded by the withdrawal of many practitioners from managed care networks and cuts in public-sector mental health services. Unless purchasers demand effective coverage of mental health treatment, mental health services will likely continue to wither away. (+info)