This study constructs optimal medical management areas (MMAs) in the State of Michigan for the purpose of visualizing and exploring the spatial patterns of two health indicators: ischemic heart disease (IHD) (ICD-9-CM: 410-414) and diabetes (ICD-9-CM: 250) for the purpose of assessing population-demand for health services. Data on IHD and diabetes are obtained from the Michigan Inpatient Hospital Discharge Database (MIDB) for the year 2008. MMA boundary definitions are optimized using Automated Zone Matching (AZM) methodology software. Optimization is conducted by aggregating the residential ZIP Codes of patients discharged from hospitals with IHD or diabetes, using three constraint parameters: (1) minimum case threshold, to ensure rate stability; (2) maximum shape compactness, to avoid irregular or elongated MMAs; and (3) maximum internal homogeneity, to construct MMAs with populations that demographically similar. The modifiable area unit problem (MAUP) is examined within the context of MMA design and epidemiological scale by evaluating IHD and diabetes in relation to their relevant broader disease groups, diseases of the circulatory system (ICD-9-CM: 390-459) and endocrine, nutritional and metabolic diseases, and immunity disorders (ICD-9-CM: 240-279). Following the optimization of AZM-MMAs area-based proportions, crude rates and age-adjusted rates are calculated to represent the various views of demand for health services. The limitations and benefits of using AZM versus traditional ZIP Code boundary definitions to construct MMAs to assess the demand for inpatient hospital services are discussed for future applications.
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