scholarly journals Health care costs in the last four years of life for private health plan beneficiaries in Brazil

Author(s):  
Marcos Bosi Ferraz ◽  
Isaura Cristina Miranda ◽  
Jorge Padovan ◽  
Patricia Coelho de Soárez ◽  
Rozana Ciconelli
2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 433-433
Author(s):  
Henry J. Henk ◽  
Connie Chen ◽  
Agnes Benedict ◽  
Jane Sullivan ◽  
April Teitelbaum

433 Background: Survival and costs outcomes for patients with mRCC receiving palliative or best supportive care (BSC) after stopping active therapy have been poorly characterized. This information is important to understand how resources are utilized at the end of life and to put current treatment costs into perspective. The objective of this retrospective database analysis was to examine survival and costs associated with BSC after receiving 1 or 2 lines of mRCC treatment. Methods: A retrospective cohort analysis using claims data from commercially insured or Medicare Advantage (MCR) enrollees of a large US health plan, with medical and pharmacy benefits. The study cohort consisted of patients with an index diagnosis for RCC [ICD-9-CM 189.0] from 1/1/07 to 6/30/10 initiating any of the following treatments from 30 days prior to index date through disenrollment: sunitinib, temsirolimus, sorafenib, bevacizumab, everolimus, pazopanib, cytokines. Patients were required to have a 6 mos. continuous enrollment ± index date (patients disenrolling due to death within the 6 mos. were retained). Lines of therapy (LOT) were identified based on prescription fill and administration dates, began following the last LOT and continued until disenrollment. Health care costs reported represent the health plan + patient paid amount. Results: The overall study cohort (n=274) was 73% male; mean (±SD) age 63.3 ± 11.1 yr. with the majority of patients commercially insured (80% vs 20% MCR). The majority started BSC following 1st LOT (68% vs 32%). Median survival from start of BSC was similar following 1st and 2nd LOT (126 and 118 days). The mean (median) duration of BSC after 1 LOT was 223 (114) days and 176 (109) days for 2 LOT. Total health care costs incurred during BSC averaged $50,187 ± 96,984 and $37,294 ± 51,101 and monthly costs were similar ($10,284 ± 17979) after 1 and 2 LOT, respectively. In both cases, inpatient hospital costs represented the largest proportion of these costs (47%) while outpatient costs represented 36%. Conclusions: Our study estimating BSC survival and costs in patients with mRCC based on US claims data found monthly cost of $10, 284. These estimates suggest that BSC costs are not insignificant.


Author(s):  
Edward S. Kielb ◽  
Corwin N. Rhyan ◽  
James A. Lee

Health insurance plans with high deductibles increase exposure to health care costs, raising concerns about how the growth in these plans may be impacting both the financial burden of health care expenditures on families and their access to health care. We find that foregoing medical care is common among low-income, privately insured families, occurring at a greater rate than those with higher incomes or Medicare coverage. To better understand the relationship between out-of-pocket (OOP) spending and access, we used the 2011-2014 Medical Expenditure Panel Survey (MEPS) data and a logistic model to analyze the likelihood of avoiding or delaying needed medical care based on health insurance design and other individual and family characteristics. We find that avoiding or delaying medical care is strongly correlated with coverage under a high-deductible health plan, and with depression, poor perceived health, or poverty. However, it is relatively independent of the percent of income spent on OOP costs, making the percent of income spent on OOP costs by itself a poor measure of health care unaffordability. Individuals who spend a small percentage of their income on health care costs may still be extremely burdened by their health plan when financial concerns prevent access to health care. This work emphasizes the importance of insurance design as a predictor of access and the need to expand the definition of financial barriers to care beyond expenditures, particularly for the low-income, privately insured population.


Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 4700-4700
Author(s):  
Nicole M. Engel-Nitz ◽  
Benjamin Eckert ◽  
Rui Song ◽  
Erin M. Hulbert ◽  
Jeffrey McPheeters ◽  
...  

Abstract Abstract 4700 Introduction: Advances in diagnostic testing, including molecular profiling, have improved diagnostic accuracy for hematologic cancers, but with increased need for integration and interpretation of data from multiple tests. Accurate and earlier diagnosis may be achieved with use of hematopathology specialty laboratories, supporting appropriate patient management. This study compares diagnostic changes, patterns of additional testing, treatment decisions, and health care costs for patients with suspected hematologic cancers whose diagnostic tests were managed by specialty hematology and other types of laboratories. Methods: Patients with bone marrow procedure (biopsy/aspirate) and suspected hematologic cancer/disease were identified from claims data (2005 – 2011) from a large US health plan. Included patients had ≥6 pre- & ≥3-months post-biopsy health plan coverage. Lab tests in the 30 days post-biopsy were identified. Patient cohorts were based upon laboratories performing marrow morphology assessment/directing testing sequence: Genoptix (GX, a specialty hematology-testing laboratory); large commercial laboratories (LL), and other laboratories (OL) such as community hospital laboratories; academic labs were not included. Following the bone marrow testing, initial diagnoses were identified. As a proxy for diagnostic uncertainty, we determined whether patients' initial diagnoses remained stable and whether diagnostic changes were recorded in the 1 year following initial biopsy; codes indicative of disease progression or hematologic signs/symptoms were explicitly not counted as instability or change. Health care costs (per patient per month) for the 1 year period post-biopsy were examined. Chi-square and F-tests assessed unadjusted differences between cohorts. Logistic regression assessed differences between cohorts in stability, change in diagnosis and repeat biopsies. Generalized linear models assessed costs, adjusting for demographics, baseline clinical characteristics and initial and final diagnoses. Results: The study population included a total of 1,387 GX, 4,162 LL, and 19,115 OL patients with suspected hematologic malignancy/disease and bone marrow morphology assessment. OL patients were slightly younger (average age 58.19 OL vs. 59.88 GX, 59.39 LL, P<0.001), and slightly more likely to be enrolled in MedicareAdvantage plans (25.24% OL, vs. 23.00% GX and 21.19% LL, p<0.001). Stability of initial diagnosis varied across the cohorts; 6.16% GX, 8.04% LL, and 9.73% OL patients had unstable initial diagnoses (p<0.001); compared to OL, adjusted odds ratios were 0.864 for GX [95% CI: 0.678,1.1] and 1.07 for LL [95% CI: 0.93, 1.23]. Changes to hematologic diagnoses occurred for 7.88% of GX, 11.19% of LL, and 14.08% OL patients (p<0.001), with adjusted odds ratios of change vs. OL of 0.82 for GX [95% CI: 0.72, 0.93] and 0.93 for LL [95% CI: 0.86, 1.01]. Fewer GX patients underwent repeat marrow biopsies (9.59% GX, vs. 17.11% LL and 28.16% OL, p<0.001), with differences remaining after adjusting for types of cancer diagnoses and other characteristics (odds ratios vs. OL: GX 0.31 [0.25, 0.37]; LL 0.54 [0.49, 0.60]). Among patients who began chemotherapy, 4.58% GX, 6.68% LL, and 7.37% OL (p=0.91) changed treatment within 30 days of treatment initiation; an additional 1.78% GX, 3.68% LL, and 5.12% OL (p=0.001) patients changed treatment within 60 days. 1-year PPPM costs adjusted for differences in patient characteristics were $8,202 GX, $7,711 LL, and $10,302 OL p<0.05); unadjusted costs were $5,362 GX, $6,409 LL, and $10,061 OL (P<0.001). Adjusted costs PPPM excluding the testing period were $6,019 GX, $6,649 LL, and $7,801 OL (p<0.05); unadjusted costs for this period were $3,853 GX, $5,171 LL, and $7,653 OL (P<0.0001). Conclusions: Stability and changes in hematologic diagnoses varied by the type of lab performing the initial testing on the bone marrow sample, with a trend for fewer changes observed for the hematology specialty lab. Repeat bone marrow biopsies, changes in chemotherapy, and costs in the period following initial diagnostic workup were lower for patients whose samples were assessed by the specialty laboratory versus other types of laboratories after adjusting for differences in patient populations. Further exploration of the impact of management by specialized (hematopathologist) compared to general pathology services on outcomes is warranted. Disclosures: Engel-Nitz: Novartis Molecular Diagnostics: Research Funding to OptumInsight Other. Eckert:Novartis Molecular Diagnostics: Employment. Song:Novartis Molecular Diagnostics: Research funding to OptumInsight. Other. Hulbert:Novartis Molecular Diagnostics: Research Funding to OptumInsight. Other. McPheeters:Novartis Molecular Diagnostics: Research funding to OptumInsight Other. Teitelbaum:Novartis Molecular Diagnostics: Research funding to OptumInsight. Other.


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