Richard C. Hermann

Cost-effectiveness of donepezil in the treatment of mild or moderate Alzheimer’s disease

Objective: To demonstrate the use of cost-effectiveness analysis to assess the economic impact of donepezil in the treatment of mild or moderate AD. Background: Cost-effectiveness analyses show the relationship between resources used (costs) and health benefits achieved (effects) for an intervention compared with an alternative strategy. Methods: We developed a model to estimate the incremental cost-effectiveness of donepezil compared with no treatment. We determined costs per quality-adjusted life-years gained, a measurement that enhances the comparability of diverse studies. The model projects the progression of AD patients into more severe disease stages and into nursing homes. Data from a randomized clinical trial of donepezil were used to assess the drug’s impact on the 6-week probabilities of progression. Data on the costs and health-related quality of life associated with different disease stages and settings were taken from published estimates and our companion cross-sectional study, respectively. Results: Donepezil costs are partially offset by a reduction in the costs of care due to enhancement in cognitive functioning and the delay to more costly disease stages and settings. The magnitude of this cost offset and of the effect of donepezil on health-related quality of life depends on the model’s assumptions about the duration of the drug effect, where controlled data are lacking. If the drug effect exceeds 2 years, the model predicts that for mild AD the drug would pay for itself in terms of cost offsets. Conclusions: The results of the cost-effectiveness model presented here suggest that donepezil may be cost-effective but additional controlled data on long-term drug efficacy are needed.

The influence of psychiatric disorders on patients' ratings of satisfaction with health care.

OBJECTIVES Patient ratings of satisfaction with health care have been used by patients, insurers, and employers seeking data to compare the quality of health plans and systems of care. Concerns with these ratings include their subjective nature and potential for being influenced by patient characteristics unrelated to the quality of their care. The authors examined the influence of an active psychiatric disorder on patient satisfaction with health care, hypothesizing that patients with psychiatric disorders would be less satisfied with their health care, due to the adverse effects of these conditions on mood and cognition. METHODS The authors used linked claims and survey data from the 1991 Medicare Current Beneficiary Survey. Using logistic regressions that controlled for patient sociodemographic and clinical characteristics, the authors examined the influence of an active psychiatric disorder on satisfaction with overall quality of health care and with specific dimensions of quality. The authors also examined the effects of specific types of psychiatric disorders. RESULTS Aged and disabled beneficiaries with psychiatric disorders were significantly less likely than those without disorders to be satisfied with the overall quality of health care, follow-up care, and the physicians concern for their overall health. Disabled beneficiaries were also less likely to be satisfied with the health information provided. Further variation was found by type of psychiatric disorder. CONCLUSIONS One interpretation of these findings is that Medicare beneficiaries with psychiatric disorders receive lower quality care, a possibility that warrants further investigation. Alternatively, patients with psychiatric disorders may report lower satisfaction despite receiving comparable health care; this interpretation points toward the need for casemix adjustment when comparing satisfaction ratings across health plans and the development of quality measures less susceptible to subjective biases.

Achieving consensus across diverse stakeholders on quality measures for mental healthcare

Objective:Quality-improvement efforts are hindered by a lack of consensus on meaningful and feasible measures of care. The objective of this study was to develop a core set of quality measures for mental health and substance-related care that are meaningful to stakeholders, feasible to implement, and broadly representative of diverse dimensions of the mental health system. Method:A 12-member panel of stakeholders from national organizations evaluated 116 process measures in a 2-stage modified Delphi consensus development process. Drawing on a conceptual framework and literature review, panelists rated each measure on 7 domains using a 9-point scale (1 = best). Measures were then mapped to a framework of system dimensions to identify a core set with the highest ratings for system characteristics within each dimension. Results:Twenty-eight measures were identified assessing treatment (12), access (2), assessment (2), continuity (4), coordination (2), prevention (1), and safety (5). Overall, mean ratings for meaningfulness were: clinical importance 2.29; perceived gap between actual and optimal care 2.59; association between improved performance and outcome 2.61. For feasibility, mean ratings were clarity of specifications 3.39; acceptability of data collection burden 4.77; and adequacy of case mix adjustment 4.20. The measures address a range of treatment modalities, clinical settings, diagnostic categories, vulnerable populations, and other dimensions of mental healthcare. Conclusions:A structured consensus process identified a core set of quality measures that are meaningful and feasible to multiple stakeholders, as well as broadly representative of the mental healthcare system. By yielding quantitative assessments of meaningfulness, feasibility and degree of consensus among stakeholders, these results can inform ongoing national efforts to adopt common quality measures for mental healthcare.

Quality Measures for Mental Health Care: Results from a National Inventory

The National Inventory of Mental Health Quality Measures was funded by the Agency for Healthcare Research and Quality to (1) inventory process measures for assessing the quality of mental health care; (2) identify clinical, administrative, and quality domains where measures have been developed; and (3) identify areas where further research and development is needed. Among the 86 measures identified, most evaluated treatment of major mental disorders, for example, schizophrenia (24 percent) and major depression (21 percent). A small proportion focused on children (8 percent) or the elderly (9 percent). Domains of quality included treatment appropriateness (65 percent), continuity (26 percent), access (26 percent), coordination (13 percent), detection (12 percent), and prevention (6 percent). Few measures were evaluated for reliability (12 percent) or validity (3 percent). Measures imposing a lower burden were more likely to be in use (chi 2 = 4.41, p = .036). Further measures are needed to assess care for several priority clinical and demographic groups. Research should focus on measure validity, reliability, and implementation costs. In order to foster quality improvement activities and use of common measures and specifications for mental health care, the inventory of quality measures will be made available at www.challiance.org/cqaimh.

The role of profit status under imperfect information: evidence from the treatment patterns of elderly Medicare beneficiaries hospitalized for psychiatric diagnoses

Medicare claims for elderly admitted for psychiatric care were used to estimate the impact of hospital profit status on costs, length of stay (LOS), and rehospitalizations. No evidence was found that not-for-profits (NFPs) treated sicker patients or had fewer rehospitalizations. For-profits (FPs) actually treated poorer patients. Longer LOS and lower daily costs of NFPs were attributable to their other characteristics, e.g. medical school affiliation. Instrumental variables (IV) estimates suggested that NFP general hospitals actually have lower adjusted costs. These findings fail to support concerns that FP growth leads to declining access and quality or contentions that NFPs are less efficient.

When Is Antipsychotic Polypharmacy Supported by Research Evidence? Implications for QI

BACKGROUND Concurrent use of multiple standing antipsychotics (antipsychotic polypharmacy) is increasingly common among both inpatients and outpatients. Although this has often been cited as a potential quality-of-care problem, reviews of research evidence on antipsychotic polypharmacy have not distinguished between appropriate versus inappropriate use. METHODS A MEDLINE search from 1966 to December 2007 was completed to identify studies comparing changes in symptoms, functioning, and/or side effects between patients treated with multiple antipsychotics and patients treated with a single antipsychotic. The studies were reviewed in two groups on the basis of whether prescribing was concordant with guideline recommendations for multiple-antipsychotic use. RESULTS A review of the literature, including three randomized controlled trials, found no support for the use of antipsychotic polypharmacy in patients without an established history of treatment resistance to multiple trials of monotherapy. In patients with a history of treatment resistance to multiple monotherapy trials, limited data support antipsychotic polypharmacy, but positive outcomes were primarily found in studies of clozapine augmented with a second-generation antipsychotic. DISCUSSION Research evidence is consistent with the goal of avoiding antipsychotic polypharmacy in patients who lack guideline-recommended indications for its use. The Joint Commission is implementing a core measure set for Hospital-Based Inpatient Psychiatric Services. Two of the measures address antipsychotic polypharmacy. The first measure assesses the overall rate. The second measure determines whether clinically appropriate justification has been documented supporting the use of more than one antipsychotic medication.

Impact of a work-focused intervention on the productivity and symptoms of employees with depression.

Objective: To test a new programs effectiveness in reducing depressions work burden. Methods: A brief telephonic program to improve work functioning was tested in an early-stage randomized controlled trial involving 79 Maine State Government employees who were screened in for depression and at-work limitations (treatment group = 59; usual care group = 27). Group differences in baseline to follow-up change scores on the Work Limitations Questionnaire (WLQ), WLQ Absence Module, and Patient Health Questionnaire (PHQ)-9 depression severity scale were tested with analysis of covariance. Results: Although there were no baseline group differences (P ≥ 0.05), by follow-up, the treatment group had significantly better scores on every outcome and differences in the longitudinal changes were all statistically significant (P = 0.0.27 to 0.0001). Conclusions: The new program was superior to usual care. The estimated productivity cost savings is

Risk-adjusting outcomes of mental health and substance-related care: a review of the literature.

6041.70 per participant annually.

Do women who screen positive for mental disorders in primary care have lower mammography rates

Risk adjustment is increasingly recognized as crucial to refining health care reimbursement and to comparing provider performance in terms of quality and outcomes of care. Risk adjustment for mental and substance use conditions has lagged behind other areas of medicine, but model development specific to these conditions has accelerated in recent years. After describing outcomes of mental health and substance-related care and associated risk factors, we review research studies on risk adjustment meeting the following criteria: (1) publication in a peer-reviewed journal between 1980 and 2002, (2) evaluation of one or more multivariate models used to risk-adjust comparisons of utilization, cost, or clinical outcomes of mental or substance use conditions across providers, and (3) quantitative assessment of the proportion of variance explained by patient characteristics in the model (e.g., R(2) or c-statistic). We identified 36 articles that included 72 models addressing utilization, 74 models of expenditures, and 15 models of clinical outcomes. Models based on diagnostic and sociodemographic information available from administrative data sets explained an average 6.7% of variance, whereas models using more detailed sources of data explained a more robust 22.8%. Results are appraised in the context of the mental health care systems needs for risk adjustment; we assess what has been accomplished, where gaps remain, and directions for future development.

Associations between adherence to guidelines for antipsychotic dose and health status, side effects, and patient care experiences

Disparities in mammography rates have been documented for underserved populations, yet no data are available for women with mental illness in primary care settings. We analyzed data on mammography rates for 526 women age 40-70 who were new patients and completed the Primary Care Evaluation of Mental Disorders (PRIME-MD). There were no significant differences in mammography rates among women who screened negative and positive for any mental illness (56% and 53%, respectively). Screening for mental disorders in primary care does not appear to identify women at risk for nonreceipt of mammography.