How to Classify Super-Utilizers: A Methodological Review of Super-Utilizer Criteria Applied to the Utah Medicaid Population, 2016–2017

Details

• Alternative Title:
  Popul Health Manag
• Personal Author:
  Grafe, Carl J. ; Horth, Roberta Z. ; Clayton, Nelson ; Dunn, Angela ; Forsythe, Navina
• Description:
  A limited number of patients, commonly termed super-utilizers, account for the bulk of health care expenditures. Multiple criteria for identifying super-utilizers exist, but no standard methodology is available for determining which criteria should be used for a specific population. Application is often arbitrary, and poorly aligned super-utilizer criteria might result in misallocation of resources and diminished effects of interventions. This study sought to apply an innovative, data-driven approach to classify super-utilizers among Utah Medicaid beneficiaries. The authors conducted a literature review of research methods to catalogue applied super-utilizer criteria. The most commonly used criteria were applied to Utah Medicaid beneficiaries enrolled during July 1, 2016-June 30, 2017, using their previous 12 months of claims data (N = 309,921). The |-medoids algorithm cluster analysis was used to find groups of beneficiaries with similar characteristic based on criteria from the literature. In all, 180 super-utilizer criteria were identified in the literature, 21 of which met the inclusion criteria. When these criteria were applied to Utah Medicaid data, 5 distinct subpopulation clusters were found: non-super-utilizers (n = 163,118), beneficiaries with multiple chronic or mental health conditions (n = 68,054), beneficiaries with a single chronic health condition (n = 43,939), emergency department super-utilizers with chronic or mental health conditions (n = 7809), and beneficiaries with uncomplicated hospitalizations (n = 27,001). This study demonstrates how cluster analysis can aid in selecting characteristics from the literature that systematically differentiate super-utilizer groups from other beneficiaries. This methodology might be useful to health care systems for identifying super-utilizers within their patient populations.
• Subjects:
  Chronic Disease Cluster Analysis Databases, Factual Emergency Service, Hospital Health Services Misuse Humans Medicaid Mental Disorders United States Utah
• Keywords:
  Cluster Analysis Medical Overuse Systematic Review
• Source:
  Popul Health Manag. 23(2):165-173
• Pubmed ID:
  31424319
• Pubmed Central ID:
  PMC8995378
• Document Type:
  Journal Article
• Funding:
  CC999999/ImCDC/Intramural CDC HHSUnited States/
• Volume:
  23
• Issue:
  2
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha-512:8c18f9f9132f976e7fb137ff75df37673b1fe1a086946b82fed20cc0213c30f47723aae131065635528378af128281c7a971b4ae0cfbfe38b4c9141624e62687
• Download URL:
  https://stacks.cdc.gov/view/cdc/116196/cdc_116196_DS1.pdf
• File Type:
  [PDF - 482.07 KB ]