Michael S. Hendryx

The relationship of community quality to the health of women and men

Using a 1996 community survey of behavioral risk factors, this cross-sectional study of 804 residents in a rural community examines the relationship of community quality to the health status of women and men. We use two categories of community factors to assess community quality: measures of the social quality of community life, and measures of community quality that focus on the physical environment. Health status is assessed by four measures that examine perceived health status and functioning. Regression results indicate that there is a significant relationship between the quality of the community and health status for both women and men. Specifically, womens perceptions about the social quality of their community are positively associated with their perceived health status and functioning; furthermore, these relationships are significantly different from those of men. Mens perceptions of their physical environment are significantly related to their reported functioning and health, to a limited extent these relationships are different from women. These relationships support our hypothesis that gender differentially affects the relationship between community quality and health.

Access to Mental Health Services and Health Sector Social Capital

Mental health services are underused relative to mental illness rates. We hypothesized a positive correlation between use of mental health services and community-level health care social capital. Community Tracking Study data from 43 cities (N=43,278), merged with the National Profile of Local Health Departments and other sources, show that use of mental health services was greater when public health districts collaborated with managed care organizations and other community groups, independent of individual predictors and health care system variables. Use was also positively associated with community levels of public insurance coverage and with direct public health provision of behavioral health care services. Research is needed to understand the mechanisms by which social capital may improve access to mental health services.

Predicting rehospitalization and outpatient services from administration and clinical databases

The study tests whether psychiatric services utilization may be predicted from administrative databases without clinical variables equally as well as from databases with clinical variables. Persons with a psychiatric hospitalization at an urban medical center were followed for 1 year postdischarge (N=1384.) Dependent variables included statewide rehospitalization and the number of hours of outpatient services received. Three linear and logistic regression models were developed and cross-validated: a basic model with limited administrative independent variables, an intermediate model with diagnostic and limited clinical indicators, and a full model containing additional clinical predictors. For rehospitalization, the clinical cross-validated model accounted for twice the variance accounted by the basic model (adjusted R2=.13 and .06, respectively). For outpatient hours, the basic cross-validated model performed as well as the clinical model (adjusted R2=.36 and .34, respectively.) Clinical indicators such as assessment of functioning and co-occurring substance use disorder should be considered for inclusion in predicting rehospitalization.

The effects of CEO-board relations on hospital performance.

This article assesses the relationship between CEO–board relations and hospital financial performance. A study of 90 acute care California hospitals examined changes in the relations between the CEO and governing board over two time periods in 1985 and 1989. The results show that CEO–board participation is an effective governance mechanism that significantly enhances hospital performance.

Social capital and risk for chronic illnesses

Objectives: This study used an ecological model of social capital to examine the relationship between social capital and chronic illness. The model hypothesizes that personal social support and collective social capital are related to risk for chronic illnesses. Methods: Data were taken from the American Changing Lives public use database. Seven hundred and sixty-nine persons meeting inclusion criteria were included. Dependent variables were the reported presence of hypertension and diabetes. Logistic regression analysis was used to identify correlates of these chronic illnesses, including demographic variables, and social capital and social support variables measured at both the personal and collective levels. Results: Significant results were usually consistent with model hypotheses; that is, measures of social capital and social support were related to the presence of diabetes and hypertension in expected ways. However, in other cases, the hypothesized relationships were not statistically significant, due to limitations in the model or data. Discussion: Social support and social capital both serve as protective factors against chronic illness. Development of social capital may proceed from the personal family and social environment to collective measures of trust and engagement, and this suggests that family relationships are the foundation on which to base efforts to build social capital.

Comparing alternative risk-adjustment models

The use of mental health indicators to compare provider performance requires that comparisons be fair. Fair provider comparisons mean that scores are risk adjusted for client characteristics that influence scores and that are beyond provider control. Data for the study are collected from 336 outpatients receiving publicly funded mental health services in Washington State. The study compares alternative specifications of multiple regression-based risk-adjustment models to argue that the particular form of the model will lead to different conclusions about comparative treatment agency performance. In order to evaluate performance fairly it is necessary to not only incorporate risk adjustment, but also identify the most correct form that the risk-adjustment model should take. Future research is needed to specify, test, and validate the mental health risk-adjustment models best suited to particular treatment populations and performance indicators.

Introduction: Risk-adjustment issues in mental health services

State mental health authorities and other public and private entities are developing outcome measures and comparing results across providers, programs, and systems. To make comparisons equitable, outcomes must be risk adjusted. This article provides an introduction to mental health risk adjustment and outlines issues involved in the selection of outcome and risk variables, data collection protocols, and analytic methods. It stresses the importance of proper identification of risk-adjustment variables and models. The article concludes with the next steps necessary to develop a valid approach to the risk-adjustment methodology.

The relationship between supply and hospitalization rates for mental illness and substance use disorders

This study investigated the extent to which mental illness and substance use hospitalization rates were related to the supply of psychiatric treatment services. Supply variables, notably the per capita rate of psychiatrists, primary care physicians, and specialty units, were strongly related to mental illness and substance use hospitalization rates to acute care hospitals across 114 small geographic areas in Iowa. The supply of outpatient services was not related to hospitalization rates. The need to study the reliability of patient assessment processes, refine guidelines and admissions criteria, and understand the contributions of supply variables to hospitalization rates are indicated by these results. A conceptual model is offered within which the dynamic cycle from patient functioning to service delivery may be framed.

Psychiatric Hospitalization Decision Making by CMHC Staff

The decision to recommend hospitalization for patients with psychiatric illness is often made on the basis of unknown reliability and validity. The purpose of this study was to examine the characteristics and reliability of self-reported psychiatric hospitalization decision making among staff at a Community Mental Health Center. Foremost among the results, the conditions that staff consider to be appropriate indicators of hospitalization show only modest reliability. Kappa interrater reliabilities of .10 to .60 persist across different staff types and different patient problems. Results from hypothetical cases support a micro-certainty, macro-uncertainty hypothesis: staff are highly confident in the appropriateness of their treatment recommendations, but the recommendations across staff are variable. The results empirically demonstrate the need to improve the reliability of the hospitalization decision, and to work towards valid outcomes-based hospitalization criteria.

Psychiatric Hospitalization Characteristics Associated with Insurance Type

This study examines the relationship among types of insurance and characteristics of inpatient psychiatric treatment. Data include 46,998 adult psychiatric or substance abuse cases from all 1991–1992 Washington State discharges from short-stay general hospitals. Large and significant differences among payers exist in treatment characteristics, controlling for diagnosis and patient age. For example, length of stay is longest among commercial and Medicare payers. Emergency admissions are more common among public payers, and elective admissions are more common among private payers, including HMOs. Results are discussed in light of policy and administration issues that will arise as financing for mental health services comes under greater capitation.