This study was conducted to update national estimates of the economic burden of undiagnosed diabetes, prediabetes, and gestational diabetes mellitus (GDM) in the United States for year 2017 and ...provide state-level estimates. Combined with published estimates for diagnosed diabetes, these updated statistics provide a detailed picture of the economic costs associated with elevated blood glucose levels.
This study estimated medical expenditures exceeding levels occurring in the absence of diabetes or prediabetes and the indirect economic burden associated with reduced labor force participation and productivity. Data sources analyzed included Optum medical claims for ∼5.8 million commercially insured patients continuously enrolled from 2013 to 2015, Medicare Standard Analytical Files containing medical claims for ∼2.8 million Medicare patients in 2014, and the 2014 Nationwide Inpatient Sample containing ∼7.1 million discharge records. Other data sources were the U.S. Census Bureau, Centers for Disease Control and Prevention, and Centers for Medicare & Medicaid Services.
The economic burden associated with diagnosed diabetes (all ages), undiagnosed diabetes and prediabetes (adults), and GDM (mothers and newborns) reached nearly $404 billion in 2017, consisting of $327.2 billion for diagnosed diabetes, $31.7 billion for undiagnosed diabetes, $43.4 billion for prediabetes, and nearly $1.6 billion for GDM. Combined, this amounted to an economic burden of $1,240 for each American in 2017. Annual burden per case averaged $13,240 for diagnosed diabetes, $5,800 for GDM, $4,250 for undiagnosed diabetes, and $500 for prediabetes.
Updated statistics underscore the importance of reducing the burden of prediabetes and diabetes through better detection, prevention, and treatment.
Parkinson's disease (PD) is one of the world's fastest growing neurological disorders. Much is unknown about PD-associated economic burdens in the United States (U.S.) and other high-income nations. ...This study provides a comprehensive analysis of the economic burdens of PD in the U.S. (2017) and projections for the next two decades. Multiple data sources were used to estimate the costs of PD, including public and private administrative claims data, Medicare Current Beneficiary Survey, Medical Expenditure Panel Survey, and a primary survey (n = 4,548) designed for this study. We estimated a U.S. prevalence of approximately one million individuals with diagnosed Parkinson's disease in 2017 and a total economic burden of $51.9 billion. The total burden of PD includes direct medical costs of $25.4 billion and $26.5 billion in indirect and non-medical costs, including an indirect cost of $14.2 billion (PWP and caregiver burden combined), non-medical costs of $7.5 billion, and $4.8 billion due to disability income received by PWPs. The Medicare program bears the largest share of excess medical costs, as most PD patients are over age 65. Projected PD prevalence will be more than 1.6 million with projected total economic burden surpassing $79 billion by 2037. The economic burden of PD was previously underestimated. Our findings underscore the substantial burden of PD to society, payers, patients, and caregivers. Interventions to reduce PD incidence, delay disease progression, and alleviate symptom burden may reduce the future economic burden of PD.
The Economic Burden Of Diabetes Dall, Timothy M; Zhang, Yiduo; Chen, Yaozhu J ...
Health Affairs,
02/2010, Letnik:
29, Številka:
2
Journal Article
Recenzirano
New research provides revised comprehensive estimates that suggest that the U.S. national economic burden of pre-diabetes and diabetes reached $218 billion in 2007. This estimate includes $153 ...billion in higher medical costs and $65 billion in reduced productivity. The average annual cost per case is $2,864 for undiagnosed diabetes, $9,975 for diagnosed diabetes ($9,677 for type 2 and $14,856 for type 1), and $443 for pre-diabetes (medical costs only). For each American, regardless of diabetes status, this burden represents a cost of approximately $700 annually. These results underscore the urgency of better understanding how prevention and treatment strategies may or may not help reduce costs.
The effective utilization rate of river-dredged silt was extremely low, and common disposal methods such as dumping it into the ocean have already threatened the ecological environment. To ...demonstrate that dredged silt can be used as a mineral admixture to modify magnesium potassium phosphate cement (MKPC), the mechanical properties and hydration degree of sintered silt ash (SSA)-blended MKPC in the early stage of hydration were studied systematically in this paper, with MKPC as the reference group. The mechanical experiment results showed that in the process of increasing the SSA content to 25%, the compressive strength first increased and then decreased. Among the samples, the compressive strength of cement aged by 1d and 3d with 15% content was the highest, which increased by 11.5% and 17.2%, respectively, compared with the reference group. The setting time experiment found that with the increase in SSA content, the hydration reaction rate of MKPC slowed down significantly. Its effect of delaying hydration was most obvious when the SSA content was 10–15%. The X-ray diffraction pattern showed that there was no large amount of new crystalline substances formed in the hydration product. The results obtained by scanning electron microscopy show that the microstructure tended to be denser and the hydration products tended to be plump when the SSA content was in the range of 0–15%. The non-contact electrical resistivity experiment showed that the addition of SSA delayed the early hydration of MKPC. Combined with the above experiment results, it was found that when the content of SSA was less than 15%, it not only delayed the early hydration of MKPC, but also deepened its hydration degree.
Essential proteins are vital for maintaining life activities and play a crucial role in biological processes. Identifying essential proteins is of utmost importance as it helps in understanding the ...minimal requirements for cell life, discovering pathogenic genes and drug targets, diagnosing diseases, and comprehending the mechanism of biological evolution. The latest research suggests that integrating protein–protein interaction (PPI) networks and relevant biological sequence features can enhance the accuracy and robustness of essential protein identification. In this paper, a deep neural network (DNN) method was used to identify a yeast essential protein, which was named IYEPDNN. The method combines gene expression profiles, PPI networks, and orthology as input features to improve the accuracy of DNN while reducing computational complexity. To enhance the robustness of the yeast dataset, the common least squares method is used to supplement absenting data. The correctness and effectiveness of the IYEPDNN method are verified using the DIP and GAVIN databases. Our experimental results demonstrate that IYEPDNN achieves an accuracy of 84%, and it outperforms state-of-the-art methods (WDC, PeC, OGN, ETBUPPI, RWAMVL, etc.) in terms of the number of essential proteins identified. The findings of this study demonstrate that the correlation between features plays a crucial role in enhancing the accuracy of essential protein prediction. Additionally, selecting the appropriate training data can effectively address the issue of imbalanced training data in essential protein identification.
Does a claims diagnosis of autism mean a true case? Burke, James P; Jain, Anjali; Yang, Wenya ...
Autism : the international journal of research and practice,
04/2014, Letnik:
18, Številka:
3
Journal Article
Recenzirano
The purpose of this study was to validate autism spectrum disorder cases identified through claims-based case identification algorithms against a clinical review of medical charts. Charts were ...reviewed for 432 children who fell into one of the three following groups: (a) more than or equal to two claims with an autism spectrum disorder diagnosis code (n = 182), (b) one claim with an autism spectrum disorder diagnosis code (n = 190), and (c) those who had no claims for autism spectrum disorder but had claims for other developmental or neurological conditions (n = 60). The algorithm-based diagnoses were compared with documented autism spectrum disorders in the medical charts. The algorithm requiring more than or equal to two claims for autism spectrum disorder generated a positive predictive value of 87.4%, which suggests that such an algorithm is a valid means to identify true autism spectrum disorder cases in claims data.
IntroductionMedical expenditures of individuals with type 2 diabetes escalate before clinical diagnosis. How increases in medical expenditures are related to glucose levels remains unclear. We ...examined changes in HbA1c and medical expenditures in years prior to and shortly after type 2 diabetes diagnosis.Research design and methodsUsing insurance claims and laboratory test results from a commercially insured population in the USA, we built three (2014, 2015, 2016) longitudinal cohorts with type 2 diabetes up to 10 years before and 2 years after the diagnosis (index year). We identified diabetes diagnosis using International Classification of Diseases, Ninth Revision and Tenth Revision codes and antidiabetic medication use. We ran two individual fixed regression models with annual total medical expenditures and average HbA1c values as dependent variables and number of years from diagnosis as the main independent variable and examined the risk-adjusted movement of the outcomes.ResultsOur study included 9847 individuals (83 526 person-years). Medical expenditures and HbA1c levels increased before and peaked at the diagnosis year. Medical expenditures were $8644 lower 10 years and $5781 lower 1 year before diagnosis compared with the index year. HbA1c was 12.18 mmol/mol (1.11 percentage points) and 3.49 mmol/mol (0.32 percentage points) lower, respectively. Average annual increases in medical expenditures and HbA1c values over the prediagnosis period were $318 and 0.97 mmol/mol (0.09 percentage points), respectively.ConclusionsMedical expenditures and HbA1c values followed similar trajectories before and after diabetes diagnosis. Our results can inform economic evaluations of programs and policies aimed at preventing type 2 diabetes.
Mycorrhizal types are a predictive framework for nutrient cycling within and across ecosystems, and their types represent different nutrient-acquisition strategies for plants. Carbon (C), nitrogen ...(N) and phosphorus (P) stoichiometric ratios are essential for understanding biogeochemical processes. The purpose of this study was to reflect the balance in the process of plant resource acquisition by exploring the C, N and P stoichiometric ratios (C/N, N/P, and C/P) in shrub organs in different mycorrhizal types. In this study, the C, N, and P stoichiometric ratios in leaves, stems and roots were analyzed in the types of arbuscular mycorrhizal (AM), ectomycorrhizal (ECM) and AM + ECM of shrubs in Northern China. The results showed that C/N in the stems and roots of AM plants (95.75 and 81.42) was significantly lower than in AM + ECM plants (109.89 and 102.37) and ECM plants (107.67 and 96.93), while both N/P and C/P in the leaves, stems and roots of AM shrubs (38.67, 36.17, 40.69; 1028.14, 2989.13, and 2659.18) were significantly higher than in ECM shrubs (30.52, 22.31, 20.47; 796.51, 2208.28, and 1714.95). Moreover, different elements among the same plant organs were closely correlated, and the same pattern was found among the same element ratios among different plant organs. This suggests that mycorrhizal type can influence C, N and P ratios among different organs.
To determine allopurinol treatment patterns and adherence to published standards of care for patients with gout.
This retrospective claims analysis in a managed care database included patients 18 ...years or older, with continuous eligibility for 1 year before and after the start date and 2 or more visits during which the gout disease code (274.xx) was assigned or 1 or more pharmacy prescriptions for a gout-specific medication between January 1, 2000, and December 31, 2002 (intake period). Factors associated with compliance with allopurinol therapy were measured based on the medication possession ratio, and adherence to 2 quality-of-care indicators for gout management was assessed using multivariable logistic regression analysis.
A total of 64.9% of allopurinol users had a modal daily dose or the most commonly observed daily dose of 300 mg/d, median length of therapy was 3 months, and a high proportion of patients had a medication possession ratio of 10% or less. Suggested quality-of-care indicators for gout had low performance: 53% of patients with renal impairment received a modal daily dose of 300 mg or greater, and 83% of patients who started taking allopurinol did not have their serum urate levels measured within 180 days. Patients with gout flares were less likely to be compliant with allopurinol (odds ratio, 0.50; 95% confidence interval, 0.40-0.63). Patients with renal impairment at baseline were 3.2 times more likely to undergo serum urate testing than patients without renal impairment (odds ratio, 3.20; 95% confidence interval, 1.25-8.23).
There was low compliance with allopurinol therapy for treatment of gout. Patients potentially received suboptimal quality of care as measured by serum urate testing and appropriateness of allopurinol dosing in patients with renal impairment.
This study updates previous estimates of the economic burden of diagnosed diabetes and quantifies the increased health resource use and lost productivity associated with diabetes in 2017.
We use a ...prevalence-based approach that combines the demographics of the U.S. population in 2017 with diabetes prevalence, epidemiological data, health care cost, and economic data into a Cost of Diabetes Model. Health resource use and associated medical costs are analyzed by age, sex, race/ethnicity, insurance coverage, medical condition, and health service category. Data sources include national surveys, Medicare standard analytical files, and one of the largest claims databases for the commercially insured population in the U.S.
The total estimated cost of diagnosed diabetes in 2017 is $327 billion, including $237 billion in direct medical costs and $90 billion in reduced productivity. For the cost categories analyzed, care for people with diagnosed diabetes accounts for 1 in 4 health care dollars in the U.S., and more than half of that expenditure is directly attributable to diabetes. People with diagnosed diabetes incur average medical expenditures of ∼$16,750 per year, of which ∼$9,600 is attributed to diabetes. People with diagnosed diabetes, on average, have medical expenditures ∼2.3 times higher than what expenditures would be in the absence of diabetes. Indirect costs include increased absenteeism ($3.3 billion) and reduced productivity while at work ($26.9 billion) for the employed population, reduced productivity for those not in the labor force ($2.3 billion), inability to work because of disease-related disability ($37.5 billion), and lost productivity due to 277,000 premature deaths attributed to diabetes ($19.9 billion).
After adjusting for inflation, economic costs of diabetes increased by 26% from 2012 to 2017 due to the increased prevalence of diabetes and the increased cost per person with diabetes. The growth in diabetes prevalence and medical costs is primarily among the population aged 65 years and older, contributing to a growing economic cost to the Medicare program. The estimates in this article highlight the substantial financial burden that diabetes imposes on society, in addition to intangible costs from pain and suffering, resources from care provided by nonpaid caregivers, and costs associated with undiagnosed diabetes.
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