William V. Rubin, MA - PI
Synthesis, Inc.

Phyllis C. Panzano, Ph.D. - Co-PI
Decision Support Services, Inc.


Two key theoretical premises of managed care are that standard service protocols, best practices, or benchmarks exist that can 1) guide quality of care, and 2) be modified to improve quality or control cost. However, many efforts to define a standard menu of services to be made available in specified quantities (i.e. best or evidence-based practices) have been less than enlightening. This is particularly true in regards to providing services for citizens who are severely mentally disabled. One reason may be that while, it is generally acknowledged "...that the population is heterogeneous, and what works in some instances may not be appropriate in others," (1) previous efforts to describe this heterogeneity and to use this information to plan and manage services have been only moderately successful.

Traditionally adults with severe mental disabilities have been described in several ways. The most widely recognized classification system is the diagnosis-based DSM IV (3). Here individuals have been described in terms of the characteristics of their illness. The DSM-IV system provides important guidance for the prescription of medication and other somatic interventions, however it is not as helpful for predicting the need for or utilization of other community mental health services (4,5,6,7,8,9). Another approach, Diagnostic Related Groups (DRG's), is based on illness-episodes (10). DRG's were initially developed more than 20 years ago to help manage inpatient care. They have however, shown limited ability to provide clinical pictures (11) or predict resource utilization and cost (12,13,14). DRG's are still not available for community mental health or community support systems. Approaches, such as the Level of Need Care Assessment (15) are based on need profiles. This system has been used to identify need patterns and gaps in community services.

While the above approaches are valid for specific purposes, a process that has broader utility has been needed. One barrier to the development of best practice models and the management of adequate systems of care (e.g. recovery-oriented community support systems or capitated managed care systems) has been the lack of more holistic pictures of the citizens to be served. This has also limited attempts to assess the effectiveness of mental health services and policy (16, 17, 18, 19).

To address the above limitations, the Goodness of Fit study has employed a process known as Cluster-Based Planning and Outcomes Management (Rubin et al.,1992; NEED NEW REFERENCES). This approach, derived in part from the cognitive psychology literature, seeks to describe mental health consumers in terms of "prototypes " (20) or Clusters that are based on a multitude of characteristics. This prototype model assumes that those who work with such special populations identify naturally occurring clusters whose typical members share common strengths, problems, treatment need, and prospects for recovery (21). In contrast to more classical categorization approaches that require individual cases to meet necessary and sufficient conditions, clusters are often characterized by a set of correlated or typical features (22). Descriptions of members of different clusters can take into account both the strengths and weaknesses of members of the group, and can consider "whole" people embedded in history, community, and social contexts. They frequently describe both common elements and capture the variability among members of the same cluster (23). Cluster descriptions of adults with severe mental disabilities would be expected to include a broad array of information such as: social and living skills, work history and work skills, family role and support, history and/or effectiveness of treatment, psychiatric symptomatology, interference from substance abuse or chronic physical health problems, housing and living environments, personal strengths, and integration in the community (24, 25, 26, 27, 28, 29, 30, 31).

Between 1988 and 1996, research based on this conceptual approach, identified generalizable clusters of adults with SMD. Clusters were identified in a multi-step process using functional assessment ratings, statistical clustering procedures, and expert-based knowledge elicitation and validation techniques involving consumers, family members and providers. The basic methods were replicated in 8 different geographic service areas in Ohio. The overall effort resulted in holistic Prose Cluster Descriptions of individuals who share common strengths, problems, treatment histories, social and/or environmental contexts, and life situations (Rubin and Panzano in review Psychiatric Services).

In each of the eight geographical service areas, the process also identified targeted treatment goals for each cluster (Rubin et al., 1994). The pattern of treatment goals suggested that cluster had considerable utility for differentiating desired outcomes among clusters. Empirical evidence also indicated that clusters had utility for predicting costs and the utilization of presently available resources and services (e.g. case management and hospitalization) (Rubin et al., 1994; Rubin, Kurth & Coyne, 1997). However, the question remained as to whether the present services represented the "best practices" for members of each cluster.
Study Methods

The Goodness of Fit research is being conducted in two urban areas, both of which participated in the cluster development and validation efforts described above. Three large mental health centers serving a total of 5000 to 6000 adults with SMD initially agreed to serve as research sites. However, over the course of the study, one center withdrew. The overall research objectives are:

1. To Use A Community-Based, Expert-Driven Planning Process To Define Best Practice Models For Each Cluster,

2. To Pilot-Test Portions Of These Models In Mental Health Agencies For A Period Of Two Years,

3. To Assess Whether Clients Who Receive These Model Services Are Doing Better Than Clients, In The Same Cluster, At The Same Agency, Who Do Not Receive The Model Services.

4. To Test The Overall "Goodness Of Fit" Hypothesis Which States That:

There Is A Positive Association Between The Degree Of Fit Between Prescribed Services And Actual Services, And The Extent Of Progress Made Toward Targeted Outcomes


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