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Type 2 diabetes pharmacotherapy trends in high-risk subgroups.

ABSTRACT: Medication use trends among patients with type 2 diabetes from 2015 to 2019 were investigated in relation to the clinical group-specific recommendations from the 2018 American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) consensus report. Data were drawn from a large health insurance claims database representing Commercial (total patient-year count: 2,379,704) and Medicare (total patient-year count: 845,823) insurance programmes (IBM® MarketScan®). The utilization of sodium-glucose co-transporter-2 inhibitors or glucagon-like peptide-1 receptor agonists increased over time but was lower in the Medicare cohort in every year evaluated. Patients diagnosed with obesity received recommended therapies at higher rates than those without obesity. Differences were more modest between those with versus without atherosclerotic cardiovascular disease (ASCVD) or chronic kidney disease, with greater treatment adoption in those without ASCVD in the Medicare cohort. Utilization of recommended treatments was paradoxically lower in those with versus without heart failure, and worse in the Medicare than in the Commercial cohort. Utilization of sulphonylureas was not different in those with versus without severe hypoglycaemia history. In conclusion, utilization of therapies recommended in the guidelines is increasing overall, which is not preferentially guided by ADA/EASD-defined clinical groups, and there exists a persistent gap in utilization between Commercial and Medicare populations.

SUBMITTER: Bae J

PROVIDER: S-EPMC9314938 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveMany healthcare systems employ population-based risk scores to prospectively identify patients at high risk of poor outcomes, but it is unclear whether single point-in-time scores adequately represent future risk. We sought to identify and characterize latent subgroups of high-risk patients based on risk score trajectories.Study designObservational study of 7289 patients discharged from Veterans Health Administration (VA) hospitals during a 1-week period in November 2012 and categorized in the top 5th percentile of risk for hospitalization.MethodsUsing VA administrative data, we calculated weekly risk scores using the validated Care Assessment Needs model, reflecting the predicted probability of hospitalization. We applied the non-parametric k-means algorithm to identify latent subgroups of patients based on the trajectory of patients' hospitalization probability over a 2-year period. We then compared baseline sociodemographic characteristics, comorbidities, health service use, and social instability markers between identified latent subgroups.ResultsThe best-fitting model identified two subgroups: moderately high and persistently high risk. The moderately high subgroup included 65% of patients and was characterized by moderate subgroup-level hospitalization probability decreasing from 0.22 to 0.10 between weeks 1 and 66, then remaining constant through the study end. The persistently high subgroup, comprising the remaining 35% of patients, had a subgroup-level probability increasing from 0.38 to 0.41 between weeks 1 and 52, and declining to 0.30 at study end. Persistently high-risk patients were older, had higher prevalence of social instability and comorbidities, and used more health services.ConclusionsOn average, one third of patients initially identified as high risk stayed at very high risk over a 2-year follow-up period, while risk for the other two thirds decreased to a moderately high level. This suggests that multiple approaches may be needed to address high-risk patient needs longitudinally or intermittently.

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Type 2 diabetes pharmacotherapy trends in high-risk subgroups.

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