scholarly journals What Is the Cost of Disease Progression Among Patients with Indolent or Aggressive Non-Hodgkin Lymphoma (NHL)?

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5957-5957
Author(s):  
Nicole Engel-Nitz ◽  
Stacey Dacosta Byfield ◽  
Timothy Bancroft ◽  
Anderson J. Amy ◽  
Carolina Reyes ◽  
...  
Keyword(s):  
Health Care ◽  
Index Date ◽  
Progressive Disease ◽  
Hospice Care ◽  
Diagnosis Codes ◽  
Equity Ownership ◽  
The Cost ◽  
The Impact ◽  
Care Costs

Abstract Background: The natural histories of aggressive and indolent NHL vary in terms of the timing and pattern of disease progression. However, little is known about the impact of progression of disease (PD) on costs, and in particular how this differs between aggressive and indolent subtypes of NHL. This study examined patterns of care and outcomes for patients with aggressive and indolent NHL, and the impact of PD on health care costs. Methods: To identify cases of NHL, this retrospective studyused medical and pharmacy claims from a large national US health plan to identify commercially insured and Medicare Advantage (MA) patients age ≥18 years from 1/2007 - 8/2014 with ≥2 medical claims for NHL based on ICD-9-CM diagnosis codes. Patients were divided into cohorts of aggressive (AGG) NHL and indolent (IND) and based on diagnosis codes. Patients were required to have ≥1 claim for systemic anti-cancer therapy, with the index date being defined as the first observed claim for such therapy. Continuous enrollment in the health plan for 6 months prior to (baseline period), and ≥6 months after, the index date (variable follow-up period) was required; patients with <6 months of follow-up due to death were included. An algorithm to identify line of therapy (LOT) periods was implemented. PD was defined as: start of a second LOT, receipt of hospice care (based on procedure or revenue codes) or death (based on Social Security Administration death data). Health care costs were calculated over 6-month periods of follow-up (6, 12, 18, 24 months), with costs calculated for pharmacy, inpatient hospital, ambulatory, and other sites of service. Results: A total of 1,197 AGG and 2,454 IND patients met study criteria. Progression was experienced by 40.6% of AGG and 49.4% of IND patients respectively during the entire study period; 6-month progression was 18.9% (AGG) and 18.5% (IND). Compared to patients without PD during the study period, patients who progressed had higher average costs over each time period: in the first 6-months, costs were $138,957 PD vs. $108,607 for non-PD among AGG, and $114,644 PD vs. $80,873 for non-PD among IND (Figure, Table). Similarly, total costs for PD were higher than non-PD over 12, 18, and 24 months (Figure). Costs by site of service were higher for PD patients compared to non-PD patients among both the AGG and IND groups, particularly for inpatients costs; the table shows costs by site of service for the first 6 months, and results were similar over 12, 18, and 24 months. A higher proportion of AGG patients died compared with IND patients. Approximately one third of patients who died used hospice services among AGG and IND, and of these, 90.1% of AGG and 91.3% of IND used 3 or more days of hospice care. Conclusion: Among both aggressive and indolent NHL populations, costs were higher for patients with progressive versus without progressive disease, and increased over longer follow-up time. Patients with aggressive NHL had higher costs compared with patients with indolent NHL for both progressive and non-progressive disease. This study is the first to quantify systematically the cost of progression in NHL, both indolent and aggressive, and can inform efforts to improve value-based care, taking into account costs not just of therapy, but of subsequent progression. Disclosures Engel-Nitz: Optum: Employment, Other: UnitedHealth Group stock. Dacosta Byfield:UnitedHealth Group: Equity Ownership; Optum: Employment. Bancroft:Optum: Employment, Other: UnitedHealth Group stock. Amy:Optum: Employment, Other: UnitedHealth Group stock. Reyes:Genentech: Employment; Roche: Equity Ownership.

scholarly journals Differences in Patients with Progressive Versus Non-Progressive AML, CLL, or NHL: Implications for Proposed Bundled Payment Strategies

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4528-4528
Author(s):  
Stacey Dacosta Byfield ◽  
Nicole Engel-Nitz ◽  
Timothy Bancroft ◽  
Amy J Anderson ◽  
Carolina Reyes ◽  
...  
Keyword(s):  
Health Plan ◽  
Index Date ◽  
Hospice Care ◽  
Cell Transplant ◽  
Bundled Payment ◽  
Health Group ◽  
Equity Ownership ◽  
The Impact ◽  
Payment Policies

Abstract Background: Increasingly, payers are redefining how payments for cancer care are structured. Demonstration programs and policy proposals by insurers and oncology organizations have bundled payments for various services, including chemotherapy. The impact of such payment policies may vary for patients (pts) with hematologic malignancies given their widely varying disease severity. Progression of disease (PD), and costs associated with it, may stress bundled payment programs, particularly if such programs do not accurately assess risk of progression across the insured cohort. To inform this ongoing development of new payment strategies for pts with hematologic malignancy, this study compared patterns of care in pts with AML, CLL or other forms of NHL who do, or do not, experience PD. Methods: This retrospective studyused medical and pharmacy claims from a large national US health plan to identify commercially insured and Medicare Advantage (MA) pts age ≥18 years from 1/2007 - 8/2014 with ≥2 medical claims for AML (ICD-9-CM code 205.0x), CLL ( ICD-9-CM code 204.1x), or other NHL (ICD-9-CM codes 200.xx, 202.0x-202.2x, 202.4x, 202.7x-202.9x, 203.8x, 204.8x-204.9x, 273.3x). Pts required ≥1 claim for systemic anti-cancer therapy (SACT); the first observed claim was the index date. Continuous enrollment (CE) in the health plan for 6 months (mths) prior to (baseline period) and ≥6 mths after index date (variable follow-up period) was required; pts with <6 mths of follow-up due to death were included. Pts with baseline SACT or additional primary malignancies were excluded. Line of therapy (LOT) periods were defined. The 1st LOT (LOT1) started on index date; regimens included all drugs received in the first 45 days. LOT1 ended at the earliest of: start of a new drug, ≥60-day gap in initial regimen, death or end of CE or study period. LOT2 started with a SACT after LOT1 end. PD was defined as: start of LOT2, receipt of hospice care (based on procedure or revenue codes) or death (based on Social Security Administration death data). Results: Among 667 AML, 1354 CLL and 9399 NHL pts who met study criteria, 70%, 45%, and 46% respectively had PD during the study period. Mean (median) time in mths to PD was 6.6 (4.2) for AML, 12.8 (9.2) for CLL and 10.0 (7.1) for NHL. Descriptive results are shown in the Table. Compared to pts without PD during the study period, pts who progressed were MA pts, older and had shorter initial LOTs. The most common initial therapy varied across PD cohorts. Among pts with PD, the AML cohort had the highest percentage of death and evidence of hospice care. Conclusion: Characteristics and treatment patterns varied for pts with PD versus non-PD AML, CLL and NHL. Understanding the variability across patient groups will aid in the development of new bundled payment policies and help providers determine whether and in which payment systems to participate. Table 1. AML CLL NHL PD N=464 No PD N=203 PD N=604 No PD N=750 PD N=4291 No PD N=5108 Age, yrs mean (SD), median^# 60 (17), 62 58 (17), 59 71 (11), 72 67 (11), 67 64 (14), 65 60 (16), 62 Baseline Quan-Charlson comorbidity score mean (SD), median# 3.1 (1.6), 2 3.1 (1.6), 2 2.8 (1.3), 2 2.7 (1.2), 2 3.4 (2.0), 3 3.3 (1.9), 2 Male, N (%)# 271 (58) 115 (57) 366 (61) 490 (65) 2480 (58) 2832 (55) Insurance, N (%)*^# Commercial 300 (65) 148 (73) 284 (47) 428 (57) 2,723 (63) 3489 (68) MA 164 (35) 55 (27) 320 (53) 322 (43) 1568 (37) 1619 (32) Stem Cell Transplant, N (%) 105 (23) 61 (30) 11 (2) 5 (1) 443 (10) 169 (3) Length of follow-up, mths, mean (SD), median ^# 17.6 (17.1), 12.1 19.9 (15.5), 14.4 28.6 (21.4), 23.7 22.4 (15.9), 17.2 28.2 (21.5), 22.3 27.2 (19.9), 20.9 Length of LOT1, mths, mean (SD), median *^# 3.8 (4.3), 2.5 5.4 (6.5), 3.5 3.6 (4.0), 2.8 4.8 (4.0), 4.3 4.1 (3.6), 3.6 5.2 (5.1), 4.5 Monotherapy in LOT1*^# 322 (69) 158 (78) 371 (61) 272 (36) 1623 (38) 1254 (25) Biologic in LOT*^# 136 (29) 38 (19) 384 (64) 603 (80) 3523 (82) 4066 (80) Most common LOT1 regimens (%)┼ 1st aza (19) cyt (17) R (24) FCR (23) R (26) RCHOP (39) 2nd dec (15) dec (17) chl (19) BR (21) RCHOP (25) R (14) 3rd cyt (9) aza (17) FCR (12) R (16) RCVP (9) BR (7) Hospice, N (%) 124 (27) - 74 (12) - 664 (15) - Died, N (%) 204 (44) - 177 (29) - 1040 (24) - *^# p<0.05 for AML, CLL and NHL progression cohorts respectively ┼no testing Aza-azacitadine, B-bendamustine, C-cyclophosphamide, chl-chlorambucil, cyt-cytarabine, dec-decitabine, F-fludarabine, R-rituximab, V-vincristine RCHOP=R,C,V,doxorubicin±prednisone RCVP=R,C,V±prednisone Disclosures Dacosta Byfield: Optum: Employment. Engel-Nitz:United Health Group: Equity Ownership; Optum: Employment. Bancroft:Optum: Employment; United Health Group: Equity Ownership. Anderson:Optum: Employment; United Helath Group: Equity Ownership. Reyes:Genentech: Employment; Roche: Equity Ownership. Ravelo:Roche: Equity Ownership; Genentech, Inc.: Employment. Ogale:Roche: Equity Ownership; Genentech, Inc.: Employment.

scholarly journals Health Care Costs Associated with Contemporary Chronic Myelogenous Leukemia (CML) Therapy Compared to Other Hematologic Malignancies (HEM)

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4753-4753
Author(s):  
Jennifer J. Wilkes ◽  
Gary H. Lyman ◽  
David R Doody ◽  
Shasank R Chennupati ◽  
Laura Becker ◽  
...  
Keyword(s):  
Health Care ◽  
Research Funding ◽  
Index Date ◽  
Stem Cell Transplant ◽  
Kinase Inhibitor ◽  
Hematologic Malignancies ◽  
Geographic Region ◽  
Cell Transplant ◽  
The Cost ◽  
Care Costs

Introduction: CML accounts for 15-20% of leukemias. Tyrosine kinase inhibitor (TKI) therapy has led to significant improvement in survival rates, approaching the life expectancy of the general public in some settings, with less than three life years lost in a recent Swedish registry study.[1] Understanding cost associated with CML care compared to HEM in the setting of long-term survival on prolonged therapy can aid with resource allocation and clinical decision making. Methods: A retrospective cohort was constructed from OptumLabs® Data Warehouse using claims data between 2000-16. Eligible patients had ≥2 claims for CML and were continuously enrolled for ≥6m prior to diagnosis and ≥1y afterwards. CML patients were compared with HEM and general patients without history of cancer (GEN). As the CML group was the primary group of interest, the HEM and GEN groups were each frequency-matched on an approximate 4:1 ratio to the CML group on the basis of age (10-year increments), sex, year of diagnosis (3-year increments), geographic region (10 US census divisions), and insurance (commercial vs. Medicare Advantage). Follow-up data were available for this analysis through October 31, 2017. The primary outcome was total mean annualized health care costs including medical and outpatient drugs paid by health plan and patient (inflation adjusted to 2017). We used generalized linear models (GLM) to assess the variation in total costs in the three cohorts, using a gamma distribution and a log link. Models were adjusted for frequency-matched factors (sex, age, year of diagnosis, geographic region, insurance). Within the CML cohort, GLM was also used to examine the influence of factors hypothesized to be associated with costs: sex, age at index year, index year, race/ethnicity, insurance, modified Charlson comorbidity index, percent (%) days with TKI prescription, stem cell transplant, and number of inpatient and ambulatory days per year. Results: We identified 1909 enrollees with CML; mean diagnosis age 56y. They were matched with 7,268 HEM patients and 7,636 GEN patients. Mean annualized costs for CML were $82,054, $25,000 more than HEM and approximately $75,000 more than GEN (p<0.001 in 3-way and pairwise comparisons; Table 1). This difference persisted after multivariate adjustment, with cost $25,471 higher in the CML population versus the HEM (95% CI: $20,808 to 30,133). Costs for CML care increased over each 5-year diagnostic interval until 2015 ($64,158 in 2000-04, peaking at $91,990 in 2010-14) (Table 1). Following index date, the trend in costs differ by cancer with HEM costs decreasing after the first six months post index date (Figure 1). In multivariable analysis, % days on a tyrosine kinase inhibitor had the greatest influence on cost among CML treatment factors. After adjustment for additional demographic and treatment factors, there was an association with increased cost by percent of days on a TKI (trend p<0.001); for those with 75% of days on a TKI, the cost was $110,790 more than those without TKIs. Other factors associated with cost included receipt of stem cell transplant compared to no transplant ($55,549, 95% CI: $30,077 to 81,021), greater number of inpatient days ($148,664 for greater than 7 days versus none, 95% CI: $120,628 to 176,699) and greater number of ambulatory visits (20+ visits in one year versus <5, $62,255, 95% CI $52,969 to 71,541) Conclusions: Contemporary CML costs exceed the cost of treatment for other hematologic malignancies. This is primarily driven by the use of TKIs. The plateau in CML costs in those diagnosed between 2015-16 needs further evaluation for associations with TKI availability and the introduction of generics. [1] Bower H et al. JCO 2016 Aug 20; 34(24):2851-7 Disclosures Lyman: G1 Therapeutics, Halozyme Therapeutics, Partners Healthcare, Hexal, Bristol-Myers Squibb, Helsinn Therapeutics, Amgen Inc., Pfizer, Agendia, Genomic Health, Inc.: Consultancy; Generex Biotechnology: Membership on an entity's Board of Directors or advisory committees; Janssen Scientific Affairs, LLC: Research Funding; Amgen Inc.: Other: Research support, Research Funding.

Abstract MP76: Assessing the Impact of the "Health Bucks" Program on Cardiovascular Disease in New York City: A Modeling Study

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Heesun Eom ◽  
Stella S Yi ◽  
Daniel Bu ◽  
Rienna Russo ◽  
Brandon Bellows ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Health Care ◽  
New York ◽  
New York City ◽  
Health Care Costs ◽  
York City ◽  
Fruits And Vegetables ◽  
The Cost ◽  
The Impact ◽  
Care Costs

Background: Low fruit and vegetable (FV) consumption is considered one of the leading causes of deteriorating health outcomes, and has been linked to obesity, diabetes, and cardiovascular disease. Yet, few adults in New York City (NYC) consume the daily recommended amounts. In order to address the need for fresh and affordable fruits and vegetables, the NYC Department of Health and Mental Hygiene has implemented the “Health Bucks” program, which provides low-income population with coupons that can be used to purchase fruits and vegetetabls. Previous studies have shown the impact of the Health Bucks program on fruit and vegetable consumption; however, it is unclear how the program would influence cardiovascular health and the associated health care costs in the long term. Objective: To estimate the health and economic impact of the Health Bucks program using a validated microsimulation model of cardiovascular disease (CVD) in NYC. Methods: We used the Simulations for Health Improvement and Equity (SHINE) CVD Model to estimate the impact of the Health Bucks program on lifetime CVD events and direct medical costs (2019 USD). We considered different program strengths by assuming the program can reduce the cost of fruits and vegetables by 20%, 30%, and 40%. Population characteristics were estimated based on data from the 2013-2014 NYC Health and Nutrition Examination Survey. CVD risk factor trajectories and risk of incident CVD events were derived from six pooled longitudinal US cohorts. Policy effects were derived from the literature. We run 1,000 simulations to account for uncertainties in the parameter. We discounted costs by 3% and reported health care costs in 2019 dollars. Results: A Health Bucks program that can reduce the cost of fruits and vegetables by 20%, 30%, and 40% would prevent 2,690 (95% CI: -14,793, 20,173), 27,386 (95% CI: 9,967, 44,805), and 50,014 (95% CI: 15,227, 50,014) coronary heart disease events, respectively, over the simulated lifetimes of the NYC population. The program would also prevent 47,469 (95% CI: 35,008, 59,931), 59,127 (95% CI: 46,676, 71,579), and 85,359 (95% CI: 72,902, 97,815) stroke events based on the price reduction level. The program would result in savings in health care costs, ranged from $937 million to $1.8 billion based on the price reduction level over the lifetime or from $19 million to $37 million annually. Conclusions: We projected that the Health Bucks program could prevent a significant number of CVD events among adults in NYC and yield substantial health care cost savings. Public health practitioners and policymakers may consider adopting this program in other locations.

Health Care Utilization and Associated Costs in Elderly Persons with Non-CML Myeloproliferative Neoplasms: Real-World Evidence From a United States Medicare Population

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 4273-4273 ◽  
Author(s):  
Sudeep Karve ◽  
Gregory L Price ◽  
Keith L Davis ◽  
Gerhardt M Pohl ◽  
Richard A Walgren
Keyword(s):  
Health Care ◽  
Health Care Utilization ◽  
Index Date ◽  
Myeloproliferative Neoplasms ◽  
Care Utilization ◽  
Cell Transplant ◽  
Elderly Persons ◽  
Employment Equity ◽  
Equity Ownership

Abstract Abstract 4273 Background: Non-CML myeloproliferative neoplasms (MPNs), which include essential thrombocythemia (ET), polycythemia vera (PV), myelofibrosis (MF) and MPN not otherwise specified (MPN-NOS), are characterized by activation of JAK2 signaling and abnormal blood cell production. Median survival ranges from months to years for MF and up to a decade or more for PV and ET. Some symptomatic treatment options exist, but with the exception of hematopoietic stem cell transplant, none are curative. Although MPN incidence is highest in persons aged ≥65 years, little is known about overall health care utilization and costs in elderly persons with these diseases. MPNs are more prevalent in the elderly and therefore Medicare enrollees are a highly relevant source for US-based resource utilization and cost data for these diseases. Objective: To compare all-cause health care utilization and costs from four subtypes of elderly MPN patients (ET, PV, MF and MPN-NOS) with matched non-MPN/non-cancer controls. Methods: Retrospective data were taken from the Survey, Epidemiology, and End Results (SEER)-Medicare linked database in the US, which combines clinical information from the SEER cancer registry (MPN reporting has been required since 2001) with medical and pharmacy claims for Medicare enrollees. Patients with a new MPN diagnosis between Jan 1, 2001 and Dec 31, 2007 were selected and evaluated for all-cause health care utilization and costs from Jan 1, 2008 (index date) through Dec 31, 2008 (follow-up end date). Patients were classified by MPN subtype based on the most recent diagnosis information (ICD-O-3 from the SEER registry or ICD-9-CM from Medicare claims) before the index date. Patients who died before follow-up end, had HMO or discontinuous Medicare enrollment during the follow-up year, had enrollment based on end stage renal disease, or a diagnosis of a non-MPN malignancy before follow-up end were excluded from the study. Separate non-MPN/non-cancer control groups were selected for each MPN subtype and matched (5:1) on birth year, gender, ethnicity, geography, and reason for Medicare eligibility. Per patient health care utilization and costs during the follow-up year were aggregated and stratified by care setting. Costs were adjusted to 2010 US$ and represent amounts reimbursed by Medicare to providers. Costs were compared between MPN cases and controls using univariate t-tests. Results: A total of 1,355 MPN patients (n = 445 ET, 684 PV, 81 MF, 145 MPN-NOS) were identified for study inclusion and assigned matching controls. For ET, PV, MF and MPN-NOS cases, respectively, mean [SD] age at index was 75.5 [9.7], 70.8 [11.3], 70.8 [10.4] and 74.1 [8.9] years and % female was 69.0, 43.9, 54.3, and 55.2. Mean [SD] years between first MPN diagnosis and study index date was 3.1 [2.0], 3.4[1.9], 2.7 [2.0], and 3.1 [2.1] for ET, PV, MF and MPN-NOS cases, respectively. A significantly (p<0.05) higher proportion of MPN cases, regardless of subtype, had ≥1 hospitalization during follow-up vs. controls (ET vs. control: 22% vs. 16%, PV vs. control: 27% vs. 15%, MF vs. control: 31% vs. 12%, MPN-NOS vs. control: 36% vs. 17%). Mean [SD] total days of hospital care were similarly higher in MPN cases (ET vs. control: 2.7 [12.8] vs. 1.6 [6.6], PV vs. control: 2.6 [7.0] vs. 1.7 [9.5], MF vs. control: 2.5 [6.2] vs. 1.2 [5.9], MPN-NOS vs. control: 4.0 [10.0] vs. 2.1 [13.7]), although the PV vs. control difference was not statistically significant. The ER visit rate during follow-up was also significantly (p<0.05) higher in MPN cases (ET vs. control: 34% vs. 24%, PV vs. control: 38% vs. 25%, MF vs. control: 46% vs. 21%, MPN-NOS vs. control: 44% vs. 29%). All-cause costs for MPN cases vs. matched controls are presented in the figure. Mean total costs per patient, driven equally by inpatient and outpatient services, were significantly (p<0.001) higher in MPN cases (ET vs. control: $11,259 vs. $8,897, PV vs. control: $13,337 vs. $8,530, MF vs. control: $20,917 vs. $7,367, MPN-NOS vs. control: $20,174 vs. $9,800). Conclusions: Total health care costs during a given year for elderly patients with MPNs are 1.3 to 3 times higher (depending on subtype) than those of matched controls. These findings may help inform future cost effectiveness evaluations of novel MPN treatments, as well as decision making in the provision of optimal MPN care within a Medicare system in which resources are finite and must be allocated ethically and efficiently. Disclosures: Karve: RTI Health Solutions: Consultancy, Research Funding. Price:Eli Lilly and Company: Employment, Equity Ownership. Davis:Eli Lilly, Merck, GlaxoSmithKline, Bristol-Myers Squibb, Pfizer, Eisai, Sanof-Aventis, Gilead Sciences, MedImmune: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Pohl:Eli Lilly and Company: Employment, Equity Ownership. Walgren:Eli Lilly and Company: Employment, Equity Ownership.

Abstract 124: The Effect of Renal Impairment on The Venous Thromboembolism Recurrence and Major Bleeding Risk and Total Health Care Costs in Patients With Acute Venous Thromboembolism

2015 ◽  
Vol 8 (suppl_2) ◽  
Author(s):  
Jennifer Cai ◽  
Jackie Kwong ◽  
Ron Preblick ◽  
Qiaoyi Zhang
Keyword(s):  
Health Care ◽  
Venous Thromboembolism ◽  
Renal Impairment ◽  
Health Care Costs ◽  
Anticoagulant Therapy ◽  
Major Bleeding ◽  
Index Date ◽  
Disease Stage ◽  
Care Costs

Background: Renal impairment could be a risk factor for venous thromboembolism (VTE) recurrence and anticoagulation related bleeding in VTE patients. The objective of this study was to assess the effect of renal impairment on the risk of VTE recurrence, major bleeding and total health care costs in patients with acute VTE. Methods: In this retrospective analysis of IMS PharMetrics Plus TM claims database, patients (≥18 years old) who had ≥ 1 inpatient or ≥ 2 outpatient VTE claims during January 2010-December 2013 (the index period) were identified. Patients who had continuous enrollment eligibility for at least 12 months before (baseline) and 12 months after (follow-up) the index date (first VTE claim) and had no VTE diagnosis and anticoagulant treatment during baseline period were included. Patients who required dialysis or had end stage renal disease were excluded. VTE patients with chronic kidney disease (stage I-IV or equivalent) during baseline based on ICD- 9 diagnosis codes were compared with those without renal impairment. Recurrent VTE was identified by inpatient or emergency department claims associated with VTE diagnosis after hospital discharge of the index VTE event or 7 days after index date for patients with index VTE events treated in the outpatient setting during the follow-up period. Major bleeding events were identified by inpatient claims with a bleeding diagnosis that occurred after an anticoagulant prescription fill among patients receiving anticoagulant therapy. Cox proportional hazards models adjusted for age, gender, index VTE type, health insurance type, outpatient anticoagulant therapy use, and baseline comorbidities was used to assess the risk of VTE recurrence and anticoagulation related major bleeding. Generalized linear model with gamma distribution and log link was used to evaluate the total health care costs (inclusive of medical and pharmacy costs) over the 1-year follow-up period adjusting for the same baseline characteristics. Results: Of 20,873 eligible VTE patients (median age 57 years; 50% female), 238 had diagnosed renal impairment. Compared with patients without renal impairment, patients with renal impairment had higher rates for VTE recurrence (24% vs. 18%; adjusted hazard ratio (HR) = 1.32, 95% CI 1.06-1.63, p<0.01), and post anticoagulation major bleeding (4% vs 1%; HR=1.75, 95% CI 1.01-3.03, p=0.046). Patients with renal impairment had higher adjusted mean total health care costs ($41,283 vs. $30,757, p<0.01) than patients without renal impairment. Conclusion: VTE patients with renal impairment had higher risk for VTE recurrence and major bleeding associated with anticoagulant therapy, resulting in increased utilization of health care resources than VTE patients without renal impairment. Sponsorship: This research was funded by Daiichi Sankyo Inc, Parsippany, NJ.

Impact of new technologies on health-care costs and on the nation's "health"

1990 ◽  
Vol 36 (8) ◽  
pp. 1612-1616 ◽  
Author(s):  
T A Massaro
Keyword(s):  
Health Care ◽  
New Technologies ◽  
Well Being ◽  
Cost Of Care ◽  
American Health Care System ◽  
The Public ◽  
American Health Care ◽  
The Cost ◽  
The Impact ◽  
Care Costs

Abstract By virtually all criteria, the American health-care system has the largest and most widely distributed technology base of any in the world. The impact of this emphasis on technology on the cost of care, the rate of health-care inflation, and the well-being of the population is reviewed from the perspective of the patient, the provider, and the public health analyst.

Reflections on the Cost Consequences of the New Gene Technology for Health Policy

1994 ◽  
Vol 10 (4) ◽  
pp. 546-561 ◽  
Author(s):  
Pauline Vaillancourt Rosenau
Keyword(s):  
Health Care ◽  
Health Care Costs ◽  
Subjective Assessment ◽  
Genetically Engineered ◽  
Gene Technology ◽  
Short Term ◽  
New Gene ◽  
The Cost ◽  
The Impact ◽  
Care Costs

AbstractThis article presents a preliminary and necessarily tentative and subjective assessment of the impact of new gene technology on health care costs. In the short term, diagnosis and treatment of genetic disease are likely to increase costs. Treatment with nongene therapy will continue to be far less expensive than gene therapy where it is available. Research developments to monitor as indicators of forthcoming cost reductions in genetic therapy are set forth. Some forms of genetic screening may soon reduce health care costs, and an example is provided. Genetically engineered Pharmaceuticals are described and their impact on costs reviewed. Conditions under which they are likely to reduce health care costs are indicated.

scholarly journals Comparison of Approaches to Select a Propensity Score Matched Control Group in the Absence of an Obvious Start of Follow Up for this Group: An Example Study on the Economic Impact of the DMP Bronchial Asthma

2019 ◽  
Vol 82 (S 02) ◽  
pp. S151-S157
Author(s):  
Josephine Jacob ◽  
Niklas Schmedt ◽  
Lennart Hickstein ◽  
Wolfgang Galetzka ◽  
Jochen Walker ◽  
...  
Keyword(s):  
Health Care ◽  
Propensity Score ◽  
Bronchial Asthma ◽  
Health Care Costs ◽  
Index Date ◽  
Control Group ◽  
Random Index ◽  
One Year ◽  
Care Costs

Abstract Background Claims data are a valuable data source to investigate the economic impact of new health care services. While the date of enrollment into the new service is an obvious start of follow-up for participants, the strategy to select potential controls is not straightforward due to a missing start of follow-up to ascertain possible confounders. The aim of this study was to compare different approaches to select controls via Propensity Score Matching (PSM) using the disease management program (DMP) bronchial asthma (BA) as an example. Methods We conducted a retrospective cohort study of BA patients between 2013 and 2016 to examine total one-year health care costs and all-cause mortality. We implemented different scenarios regarding the selection of potential controls: I) allotment of a random index date with subsequent PSM, II) calendar year-based PSM (landmark analysis) and III) calendar quarter-based PSM. In scenario I, we applied 2 approaches to assign a random index date: a) assign random index date among all quarters with a BA diagnosis and b) assign random index date and thereafter examine if a BA diagnosis was documented in that quarter. Results No significant differences in total one-year health care costs between DMP BA participants and non-participants were observed in any of the scenarios. This could to some extent be explained by the higher mortality in the control groups in all scenarios. Conclusion If the loss of potential controls can be compensated, scenario Ib is a pragmatic option to select a control group. If that is not the case, scenario III is the more sophisticated approach, with the limitation that baseline characteristics prior PSM cannot be depicted and computational time or memory size needed to conduct the analysis need to be sufficient.

Does New Technology Increase or Decrease Health Care Costs? The Treatment of Peptic Ulceration

1998 ◽  
Vol 3 (4) ◽  
pp. 215-218 ◽  
Author(s):  
Shaun Murphy
Keyword(s):  
Health Care ◽  
Health Care Costs ◽  
New Technology ◽  
Peptic Ulceration ◽  
Peptic Ulcers ◽  
Cost Of Treatment ◽  
The Cost ◽  
The Impact ◽  
Care Costs ◽  
Formal Health Care

Objectives: To determine whether new technology increases or decreases formal health care costs, with reference to the diagnosis and treatment of peptic ulcers. Methods: A costing method has been devised which is designed to investigate directly the way in which the costs to formal health services of diagnosing and treating an individual illness have changed with changes in technology. Results: The cost of diagnosis has increased almost entirely as a result of the high cost of endoscopy compared with X-ray examination. The introduction of H2-receptor antagonist drugs increased the cost of treatment compared with the earlier phases of surgical treatment. Subsequently, Helicobacter pylori eradication treatment has reduced the cost of treatment compared with all earlier phases of technology. Conclusions: A method has been devised that allows the impact of changes in medical technology on formal health care costs to be investigated for individual illnesses. In the treatment of peptic ulceration, the current technology, H. pylori eradication, has lower treatment costs than all previous technologies. The evidence from previous studies and this study is insufficient to support the assertion that new technology in general leads either to an increase or to a decrease in health care costs.

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