Patterns of primary and specialty care among children with sickle cell anemia

Pediatr Blood Cancer. 2024 Jul;71(7):e31048. doi: 10.1002/pbc.31048. Epub 2024 May 1.


Background and objective: National guidelines recommend that children with sickle cell anemia (SCA) be seen regularly by primary care providers (PCPs) as well as hematologists to receive comprehensive, multidisciplinary care. The objective is to characterize the patterns of primary and hematology care for children with SCA in Michigan.

Methods: Using validated claims definitions, children ages 1-17 years with SCA were identified using Michigan Medicaid administrative claims from 2010 to 2018. We calculated the number of outpatient PCP and hematologist visits per person-year, as well as the proportion of children with at least one visit to a PCP, hematologist, or both a PCP and hematologist annually. Negative binomial regression was used to calculate annual rates of visits for each provider type.

Results: A total of 875 children contributed 2889 person-years. Of the total 22,570 outpatient visits, 52% were with a PCP and 34% with a hematologist. Annually, 87%-93% of children had a visit with a PCP, and 63%-85% had a visit with a hematologist. Approximately 66% of total person-years had both visit types within a year. The annual rate ranged from 2.3 to 2.5 for hematologist visits and from 3.7 to 4.1 for PCP visits.

Conclusions: Substantial gaps exist in the receipt of annual hematology care. Given that the majority of children with SCA see a PCP annually, strategies to leverage primary care visits experienced by this population may be needed to increase receipt of SCA-specific services.

Keywords: Medicaid administrative claims; healthcare utilization; outpatient care; sickle cell anemia.

MeSH terms

  • Adolescent
  • Anemia, Sickle Cell* / therapy
  • Child
  • Child, Preschool
  • Female
  • Follow-Up Studies
  • Hematology
  • Humans
  • Infant
  • Male
  • Medicaid / statistics & numerical data
  • Michigan
  • Primary Health Care* / statistics & numerical data
  • Prognosis
  • United States