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In: Grady M, eds. Primary care research: theory and methods. Washington, DC: USDHHS. AHCPR Pub 91-0011:75-81.
Johns Hopkins University, Baltimore, MD, USA
This paper describes several ambulatory case-mix measures that can be determined with commonly available data, such as ICD-9-CM and CPT codes captured by billing systems. These methodologies include: Diagnosis Clusters, Ambulatory Visit Groups (AVGs), Ambulatory Patient Groups (APGs), Products of Ambulatory Care (PACs), and Ambulatory Care Groups (ACGs). In addition to presenting an overview of each system, potential applications for primary care research are discussed.
Interest in primary and ambulatory care has risen dramatically among policymakers, payers, and managers. This has occurred largely because hospital-oriented cost containment has squeezed the health care resource “balloon” towards outpatient care; utilization and costs in the ambulatory sector are growing rapidly (Annual Report to Congress, 1990). This attention has led to greater efficiency and effectiveness in the provision of ambulatory care. Health services research to accomplish this has been deemed a priority (Mayfield and Grady, 1990).
Case-mix systems have been actively applied to the payment and management of inpatient care for more than a decade. These adjustment methodologies have also proven critical to the advancement of health services research in related areas of inquiry. Ambulatory case-mix measures, even though they are currently available, have not been applied on a wide scale for payment or analysis. This is likely to change very soon (Gold, 1988).
The area of ambulatory care case-mix is one that holds considerable potential for health services researchers interested in primary and ambulatory care. Therefore, the goals of this paper are to:
1. Identify issues surrounding the development of ambulatory care case-mix measures
2. Provide an overview of several available measures based mainly on the International Classification of Diseases (ICD) and Current Procedural Terminology (CPT) coding schemes
3. Discuss how these methods might be applied to primary care health services research
4. Aid in the transfer of these new measurement technologies to members of the primary care research community