Impact of Pre-existing Type 2 Diabetes Mellitus and Cardiovascular Disease on Healthcare Resource Utilization and Costs in Patients With COVID-19.

Background: The economic burden associated with type 2 diabetes mellitus (T2DM) and concurrent cardiovascular disease (CVD) among patients with COVID-19 is unclear. Objective: We compared healthcare resource utilization (HCRU) and costs in patients with COVID-19 and T2DM and CVD (T2DM + CVD), T2DM only, or neither T2DM nor CVD (T2DM/CVD). Methods: A retrospective observational study in COVID-19 patients using data from the Healthcare Integrated Research Database (HIRD®) was conducted. Patients with COVID-19 were identified between March 1, 2020, and May 31, 2021, and followed from first diagnosis or positive lab test to the end of health plan enrollment, end of study period, or death. Patients were assigned one of 3 cohorts: pre-existing T2DM+CVD, T2DM only, or neither T2DM/CVD. Propensity score matching and multivariable analyses were performed to control for differences in baseline characteristics. Study outcomes included all-cause and COVID-19-related HCRU and costs. Results: In all, 321 232 COVID-19 patients were identified (21 651 with T2DM + CVD, 28 184 with T2DM only, and 271 397 with neither T2DM/CVD). After matching, 6967 patients were in each group. Before matching, 46.0% of patients in the T2DM + CVD cohort were hospitalized for any cause, compared with 18.0% in the T2DM-only cohort and 6.3% in the neither T2DM/CVD cohort; the corresponding values after matching were 34.2%, 26.0%, and 21.2%. The proportion of patients with emergency department visits, telehealth visits, or use of skilled nursing facilities was higher in patients with COVID-19 and T2DM + CVD compared with the other cohorts. Average all-cause costs during follow-up were 12 324,7882, and $7277 per-patient-per-month after matching for patients with T2DM + CVD, T2DM-only, and neither T2DM/CVD, respectively. COVID-19-related costs contributed to 78%, 75%, and 64% of the overall costs, respectively. The multivariable model showed that per-patient-per-month all-cause costs for T2DM + CVD and T2DM-only were 54% and 21% higher, respectively, than those with neither T2DM/CVD after adjusting for residual confounding. Conclusion: HCRU and costs in patients were incrementally higher with COVID-19 and pre-existing T2DM + CVD compared with those with T2DM-only and neither T2DM/CVD, even after accounting for baseline differences between groups, confirming that pre-existing T2DM + CVD is associated with increased HCRU and costs in COVID-19 patients, highlighting the importance of proactive management.

Variation in incidence rates of outcomes relevant to vaccine safety monitoring in a US commercially insured population by case identification algorithm.

BACKGROUND: Large health insurance claims databases can be used to estimate rates of rare safety outcomes. We measured incidence rates of rare outcomes that could be used to contextualize adverse events among people receiving pneumococcal vaccines in clinical trials or clinical practice. However, algorithms used to identify outcomes in administrative databases are subject to error. Using two algorithms for each outcome, we assessed the influence of algorithm choice on the rates of the outcomes. METHODS: We used closed administrative medical and pharmacy claims in the Healthcare Integrated Research DatabaseSM (HIRD) to construct a broad cohort of individuals less than 100 years old (i.e., the target cohort) and a trial-similar cohort of individuals resembling those potentially eligible for a vaccine clinical trial (e.g., for a pneumococcal vaccine). We stratified by age and sex and used specific and sensitive algorithms to estimate rates of 39 outcomes including cardiac/cerebrovascular, metabolic, allergic/autoimmune, neurological, and hematologic outcomes. Specific algorithms intended to reduce false positive errors, while sensitive algorithms intended to reduce false negative errors, thereby providing lower and upper bounds for the "true" rates. RESULTS: We followed approximately 40 million individuals in the target cohort for an average of 3 years. Of 39 outcomes, 14 (36 %) had a rate from the specific algorithm that was less than half the rate from the sensitive algorithm. Rates of cardiac/cerebrovascular outcomes were most consistent (mean ratio of rates from specific algorithms compared to rates from sensitive algorithms = 0.76), while the rates of neurological and hematologic outcomes were the least consistent (mean ratio of rates = 0.33 and 0.36, respectively). CONCLUSIONS: For many cardiac/cerebrovascular outcomes, rates were similar regardless of the algorithm. For other outcomes, rates varied substantially by algorithm. Using multiple algorithms to ascertain outcomes in claims data can be informative about the extent of uncertainty due to outcome misclassification.

Descriptive study of the economic burden among patients with type 2 diabetes mellitus, chronic kidney disease, and chronic kidney disease and type 2 diabetes mellitus in a large US commercially insured population.

BACKGROUND: Chronic kidney disease (CKD) is a major public health concern that affects 37 million adults in the United States. It is well known that CKD presents a large economic burden, especially in the Medicare population. However, studies of the economic burden of CKD in younger populations are scarce. In particular, there is a gap in understanding how the presence of type 2 diabetes mellitus (T2DM) affects the burden of CKD in commercially insured populations. OBJECTIVE: To describe the economic and health care resource utilization (HCRU) burden of CKD within 3 patient groups (T2DM only, CKD only, and CKD and T2DM) aged 45-64 years overall and by Kidney Disease Improving Global Outcomes (KDIGO) CKD estimated glomerular filtration rate-based stage categories. METHODS: A descriptive, observational retrospective cohort study was conducted using administrative medical and pharmacy claims integrated with laboratory results data available in the HealthCore Integrated Research Database from January 1, 2017, to December 31, 2019. Three mutually exclusive groups of commercially insured patients aged 45-64 years were identified: T2DM only, CKD only, and CKD and T2DM. All-cause and disease-specific HCRU and costs in total, by medical and pharmacy benefits and across all places of service, were described for each of these groups 12 months after index date. For the CKD only and CKD and T2DM groups, costs were also described by KDIGO CKD stage. RESULTS: The CKD and T2DM group (n = 13,052) had numerically higher 12-month post-index all-cause and CKD/T2DM-related HCRU across all places of service. Mean 12-month all-cause costs for this group were $35,649, whereas costs for the CKD only group (n = 7,876) were $25,010 and costs for the T2DM only group (n = 120,364) were $16,121. Costs also tended to increase as CKD stage increased, with the greatest increases beginning at KDIGO stage 3b and higher. Mean 12-month all-cause costs for the CKD and T2DM group ranged from $29,993 to $41,222 for stages 1 to 3a and from $46,796 to $119,944 for stages 3b to 5. CONCLUSIONS: Commercially insured patients aged 45-64 years with CKD, especially those who also have T2DM, present a substantial burden in terms of elevated HCRU and costs. Costs tend to increase across KDIGO CKD stages and increase most rapidly at stage 3b and later. Therefore, there is an opportunity to reduce the burden of CKD in this population by investing in interventions to prevent or delay CKD disease progression. DISCLOSURES: HealthCore, Inc, received funding to perform this research, as well as funding from multiple pharmaceutical companies to perform various research studies outside of the submitted work. Mr Crowe and Dr Willey are employees of HealthCore, Inc., a wholly owned subsidiary of Elevance Health, Inc. Ms Chung was an employee of HealthCore, Inc., a wholly owned subsidiary of Elevance Health, Inc, at the time of study performance. Ms Chung and Dr Willey are shareholders of Elevance Health, Inc. Dr Kong, Dr Singh, Mr Farej, Dr Elliot, and Dr Williamson are employees of Bayer US, LLC. Dr Singh is a shareholder of Bayer US, LLC.

Testing Black-White Disparities in Biological Aging Among Older Adults in the United States: Analysis of DNA-Methylation and Blood-Chemistry Methods.

Biological aging is a proposed mechanism through which social determinants drive health disparities. We conducted proof-of-concept testing of 8 DNA-methylation (DNAm) and blood-chemistry quantifications of biological aging as mediators of disparities in healthspan between Black and White participants in the 2016 wave of the Health and Retirement Study (n = 9,005). We quantified biological aging from 4 DNAm "clocks" (Horvath, Hannum, PhenoAge, and GrimAge clock), a DNAm pace-of-aging measure (DunedinPoAm), and 3 blood-chemistry measures (PhenoAge, Klemera-Doubal method biological age, and homeostatic dysregulation). We quantified Black-White disparities in healthspan from cross-sectional and longitudinal data on physical performance tests, self-reported limitations in activities of daily living, and physician-diagnosed chronic diseases, self-rated health, and survival. DNAm and blood-chemistry quantifications of biological aging were moderately correlated (Pearson's r = 0.1-0.4). The GrimAge clock, DunedinPoAm, and all 3 blood-chemistry measures were associated with healthspan characteristics (e.g., mortality effect-size hazard ratios were 1.71-2.32 per standard deviation of biological aging) and showed evidence of more advanced/faster biological aging in Black participants than in White participants (Cohen's d = 0.4-0.5). These measures accounted for 13%-95% of Black-White differences in healthspan-related characteristics. Findings suggest that reducing disparities in biological aging can contribute to building health equity.