MDS Associates, Laguna Research Associates. Final report to the Bureau of Primary Health Care. Wheaton, MD, USA: MDS Associates.
Wheaton, MD, USA; San Francisco, CA, USA
In 1996, Community Health Centers (CHCs) served seven million people nationwide, approximately one-third of whom were enrolled in Medicaid while another 40 percent were uninsured.1 As with other low-income populations, CHC users are generally high-risk and experience high incidence of chronic conditions (e.g., asthma, diabetes). With the emergence of new medical and social risks (e.g., HIV, substance abuse, violence), some have argued that the CHC population is increasingly medically compromised. There is, however, very limited information on the extent to which the case mix of CHC patients differs from low-income populations served by other providers. Consequently, much of the existing research on differences in utilization between CHC users and non users has not accounted for any potential differences in case mix. With the growth of managed care, addressing case mix has become increasingly important as health centers seek to negotiate payment rates that appropriately reflect risk of utilization among their enrollees.
Case mix adjustment is an evolving art. Current methodologies use the conditions for which individuals have received medical care to understand differences in risk of utilization and expenditures for services. Often referred to as “risk” adjustment, these methodologies assign individuals to predetermined diagnostic groups, using the diagnoses recorded by clinicians on claims or encounter forms. For any given population, the mix of diagnostic groups is termed its “case mix”. Because the data derive from diagnostic codes associated with specific instances of services, case mix adjustment methods incorporate direct indicators of morbidity and disease that can lead to utilization.
At the same time, characterizing case mix adjustment as a “method of accounting for health status” is somewhat of a misnomer. The current methodologies do not account for differences in severity of illness. Because they rely on data recorded on claims and encounter forms, they only incorporate information on services people received – untreated problems and/or needed services that were not received cannot, by definition, be included. Finally, these diagnostic models are dependent upon the accuracy of diagnostic (ICD-9) coding by clinicians and mis-coding can influence the case mix assessment.
This study, funded by the Bureau of Primary Health Care/HRSA, is both a methodological assessment and a pilot exploration of case mix differences between CHC users and non users. From the methodological perspective, the project involved testing application of a case mix adjustment methodology, developing approaches for tailoring the methodology to available data on CHC populations and comparing results of a utilization analysis developed with and without case mix adjusters. From an analytic perspective, the study explored two research questions:
The study examined data for two states – Washington and Missouri; separate analyses compared non users with (1) all CHC users and (2) CHC users, categorized by the extent of their reliance on a health center for primary care