Our purpose in this article is to describe and illustrate the application of cluster analysis to identify clinically relevant multimorbidity groups. Multimorbidity is the co-occurrence of 2 or more illnesses within a single person, which raises the question whether consistent, clinically useful multimorbidity groups exist among sets of chronic illnesses. Our purpose in this article is to describe and illustrate the application of cluster analysis to identify clinically relevant multimorbidity groups. Application of cluster analysis involves a sequence of critical methodological and analytic decisions that influence the quality and meaning of the clusters produced. We illustrate the application of cluster analysis to identify multimorbidity clusters in a set of 45 chronic illnesses in primary care patients (N = 1,327,328), with 2 or more chronic conditions, served by the Veterans Health Administration. Six clinically useful multimorbidity clusters were identified: a Metabolic Cluster, an Obesity Cluster, a Liver Cluster, a Neurovascular Cluster, a Stress Cluster and a Dual Diagnosis Cluster. Cluster analysis appears to be a useful technique for identifying multiple disease clusters and patterns of multimorbidity.

Medicare beneficiaries in fair or poor health are more likely to experience a potentially preventable hospitalization if they live in a county designated as a primary care shortage area. Provision of Medicare coverage alone may not be enough to prevent poor ambulatory health care outcomes such as preventable hospitalizations. Improving health care outcomes for vulnerable elderly patients may require structural changes to the primary care ambulatory delivery system in the United States, especially in designated shortage areas.

Handheld computers are widely used in family practice residency programs in the United States. Although handheld computers were designed as electronic organizers, in family practice residencies they are used as medication reference tools, electronic textbooks, and clinical computational programs and to track activities that were previously associated with desktop database applications.

Background: Patients with schizophrenia have difficulty managing their medical healthcare needs, possibly resulting in delayed treatment and poor outcomes. We analyzed whether patients reduced primary care use over time, differentially by diagnosis with schizophrenia, diabetes, or both schizophrenia and diabetes. We also assessed whether such patterns of primary care use were a significant predictor of mortality over a 4-year period.