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Exploring Medicaid claims data to understand predictors of healthcare utilization and mortality for Medicaid individuals with or without a diagnosis of lung cancer: a feasibility study.

Health disparities in low-income populations complicate care for at-risk individuals or those diagnosed with lung cancer and may influence their patterns of healthcare utilization. The purpose of this study is to examine whether age, sex, provider's affiliation, Medicare dual eligibility, and number of comorbidities can predict healthcare utilization, as well as to examine factors influencing mortality in lung biopsy patients. A retrospective review of de-identified Medicaid claims of adults having a lung biopsy in 2013 resulted in classification into lung cancer and non-lung cancer cases based on a lung cancer diagnostic code within 30 days after biopsy. Biopsy cases were further divided by whether or not the provider's institution was accredited by the Commission on Cancer (CoC). Inpatient (IP), outpatient (OP), and emergency department (ED) utilization was followed from initial date of biopsy through 2015, or to the earliest date of death, disenrollment, or study end for both groups. The result of Cox proportional hazards regression model indicated that age and the number of comorbidities significantly predicted OP use and the number of comorbidities significantly predicted ED use in patients with lung cancer. However, for non-lung cancer patients, only the number of comorbidities significantly predicted IP and ED uses. Furthermore, for patients with lung cancer, the significant factors of mortality included IP use per month and the number of comorbidities. Patients with lung cancer who received a lung biopsy by a CoC-accredited organization had a longer time of survival from the biopsy event. Our findings suggest that understanding predictors of healthcare utilization and mortality may create opportunities to improve health and quality of life through better healthcare coordination.