Health and resource burden of a cancer diagnosis on the caregiver: an analysis of administrative claims data.

PURPOSE: Cancer diagnosis is known to affect the family; however, administrative claims data are not commonly used to evaluate the broader impact of cancer diagnosis. This study was designed to evaluate the feasibility of using claims data to explore the impact of cancer diagnosis on the caregiver. METHODS: IBM Marketscan data were used to identify eligible cancer patients, who were required to have a second adult over the age of 18 (defined as "caregiver" for this study) covered by the same the healthcare policy. Eligible control pairs included any two adults in the same policy with no evidence of cancer; for each pair one adult was randomly assigned to be the "patient control" while their partner was assigned as "caregiver control". Probabilistic stratified sampling was used select control pairs for analysis by matching the relative frequencies within sex and age group strata to those of patient/caregiver pairs. Eligible control pairs were probabilistically sampled without replacement until the stratum with at least 0.5 % relative frequency had been completely sampled. Caregiver and caregiver control healthcare resource utilization (HCRU), new diagnoses, and healthcare costs were compared during the 12-month post-diagnosis period. Subgroup analyses were conducted by cancer subtypes (breast, colorectal, lung, gastric, sarcoma) and by sex of the patient and caregiver. RESULTS: A total of 62,893 patient/caregiver pairs and 449,177 control pairs were included. Overall, caregivers used slightly fewer healthcare resources and expended less costs during the 12-month period after the cancer diagnosis than controls (physician visits; 85.8 % vs. 95.7 %; hospitalizations 5.4 % vs. 7.0 %; emergency room visits 15.7 % versus 16.2 %, all p ≤ 0.001). This finding was consistent in all subgroup analyses. New diagnoses were lower in the caregiver cohort, except for mental disorders, which were higher than controls (14.3 % vs. 9.9 %, p < 0.0001). Psychotherapeutic/antidepressant utilization occurred among 21.0 % of caregivers versus 17.2 % of caregiver controls during this period. CONCLUSIONS: It is feasible to use administrative claims data to evaluate the impact of a cancer diagnosis on the caregiver to evaluate outcomes such as HCRU, diagnoses and costs. These findings raise hypotheses about deferment of health care and increased mental distress during the caregiving period.

Diabetic ketoacidosis at diabetes onset: still an all too common threat in youth.

OBJECTIVE: To define the demographic and clinical characteristics of children at the onset of type 1 diabetes (T1D), with particular attention to the frequency of diabetic ketoacidosis (DKA). STUDY DESIGN: The Pediatric Diabetes Consortium enrolled children with new-onset T1D into a common database. For this report, eligible subjects were aged <19 years, had a pH or HCO(3) value recorded at diagnosis, and were positive for at least one diabetes-associated autoantibody. Of the 1054 children enrolled, 805 met the inclusion criteria. A pH of <7.3 and/or HCO(3) value of <15 mEq/L defined DKA. Data collected included height, weight, hemoglobin A1c, and demographic information (eg, race/ethnicity, health insurance status, parental education, family income). RESULTS: The 805 children had a mean age of 9.2 years, 50% were female; 63% were non-Hispanic Caucasian. Overall, 34% of the children presented in DKA, half with moderate or severe DKA (pH <7.2). The risk for DKA was estimated as 54% in children aged <3 years and 33% in those aged ≥ 3 years (P = .006). In multivariate analysis, younger age (P = .002), lack of private health insurance (P < .001), African-American race (P = .01), and no family history of T1D (P = .001) were independently predictive of DKA. The mean initial hemoglobin A1c was higher in the children with DKA compared with those without DKA (12.5% ± 1.9% vs 11.1% ± 2.4%; P < .001). CONCLUSION: The incidence of DKA in children at the onset of T1D remains high, with approximately one-third presenting with DKA and one-sixth with moderate or severe DKA. Increased awareness of T1D in the medical and lay communities is needed to decrease the incidence of this life-threatening complication.

Costs and Outcomes Comparison of Diabetes Technology Usage Among People With Type 1 or 2 Diabetes Using Rapid-Acting Insulin.

BACKGROUND: Does initiation of a continuous glucose monitor (CGM) or insulin pump lower health care utilization and/or costs? METHODS: Distinct cohorts of people with type 1 diabetes (T1D) or type 2 diabetes (T2D) using a blood glucose monitor (BGM), CGM, pump, or CGM with pump were identified from a large claims database. Patients ≥40 years old with 12 months of continuous enrollment before and after the device start date qualified for the study. Outcomes included one-year medical utilization and costs (minus device) for events such as hospitalizations and office visits. Generalized linear models were fitted, controlling for numerous baseline covariates. The Holm method corrected for the multiplicity of hypotheses tested. RESULTS: Of the 8235 total patients, the BGM control group was the largest, had the lowest percentage of patients with T1D, and was significantly different from the device groups in most baseline categories. Formally, only two comparisons were statistically significant: Compared with BGM, the pump cohort had greater adjusted first-year total medical and office visit costs. Other secondary outcomes such as days hospitalized, emergency department visits and labs, favored pump. Most endpoints were favorable for CGM. Results for CGM with pump generally were intermediate between CGM and pump alone. CONCLUSIONS: During a one-year follow-up, unadjusted medical costs of both CGM and pump appear lower than BGM, but multivariable modeling yielded adjusted savings only for CGM use. Economic benefits might be observable sooner for CGMs than for pumps. Generalized linear models fitted to health care utilization event rates produced favorable results for both CGM and pump.

Health care resource utilization and cost of severe hypoglycemia treatment in insulin-treated patients with diabetes in the United States.

BACKGROUND: Hypoglycemia is a major limiting factor in achieving glycemic control in persons with diabetes. In some instances, recovery from a severe hypoglycemia event may require health care resource utilization (HCRU), including the use of emergency medical services (EMS), visits to the emergency department (ED), and inpatient hospitalization. OBJECTIVES: To (a) describe the profiles of patients who experience severe hypoglycemic events and (b) characterize HCRU and the associated cost related to severe hypoglycemia treatment. METHODS: This retrospective, observational cohort study used administrative claims data from IBM MarketScan Research Databases. The study examined a cohort of subjects who experienced severe hypoglycemic events that involved HCRU during the 1-year index period. Baseline patient demographic data were collected according to patient profiles, such as payer type, type of diabetes, age, and type of insulin. HCRU and the associated cost data categorized by the patient profiles and care progression scenarios were described. RESULTS: 9,563 patients from the IBM MarketScan Research Databases experienced a severe hypoglycemic event during the index period and were included in the study; approximately 75% of those patients did not experience a severe hypoglycemic event in the previous year. Of the 9,563 patients in the cohort, the largest patient profile (n = 1,767, 18.5%) consisted of those who were on Medicaid, had type 2 diabetes, and used basal/bolus or premixed-only insulins. Overall, more than 90% of the index severe hypoglycemic events involved visits to the ED. EMS claims in the 24 hours before the ED visit were found for half of the severe hypoglycemic events (51.5%). CONCLUSIONS: Differences in HCRU and the associated costs for the treatment of severe hypoglycemia were observed among patients based on insurance, diabetes, and insulin types. Clinicians need to be aware of these differences. Optimizing treatment of severe hypoglycemia, specifically EMS care, and examining patient profiles to develop targeted interventions could potentially provide benefits to patients and reduce cost and resource utilization. DISCLOSURES: This study was funded by Eli Lilly and Company. All authors are employees and shareholders of Eli Lilly and Company. The data presented here have been presented in poster form at AMCP Nexus 2020 Virtual, October 19-23, 2020; ADCES Virtual Conference 2020, August 13-16, 2020; and Virtual ISPOR 2020, May 18-20, 2020.