Healthcare costs of foodborne diseases in the United States: an analysis using electronic health records.

Rotavirus is a major cause of gastroenteritis in children throughout Europe and the world. In addition to causing morbidity and mortality in children, rotavirus gastroenteritis (RVGE) creates a major economic burden on health care systems and families in Europe. The costs of hospital admissions for RVGE and nosocomial infections generate significant medical treatment costs throughout the region. Less information is available on the costs associated with less severe episodes and the costs borne by families, including lost time from work. The availability of rotavirus vaccines presents an effective opportunity to prevent RVGE and these associated economic costs, as well as providing protection to each child and hence benefiting the child's family. The adoption of rotavirus vaccine by health authorities in Europe will require a comparison of the costs and benefits. Economic evaluations that compare the costs of vaccination to the economic benefits of rotavirus vaccination will provide an estimate of its financial impact on health care systems and society. However, to provide a complete picture, economic evaluations of rotavirus vaccines will need to account for both the reduced costs and the reduced morbidity from prevented RVGE. Cost-effectiveness analyses based on quality-adjusted life years (QALYs) provide a systematic approach for assessing vaccination as a health investment, comparing the incremental costs associated with rotavirus vaccination and the reduced morbidity and mortality. QALYs provide a standardized approach for quantifying and comparing reductions in health-related quality of life and premature mortality. Although methodologic limitations exist in applying the QALY approach to childhood vaccines, their use in cost effectiveness analyses allows decision makers to consider the full health benefits of rotavirus and other vaccines.

This study aimed to study the influence of comorbidities on hospitalization costs for inpatients with cerebral infarction. The data from the medical records pertaining to 76,563 inpatients diagnosed with cerebral infarction were collected from public hospital records for the period between 1 January 2020 and 30 December 2020 in Gansu Province. EpiData 3.1 software was used for data collation, and SPSS 25.0 was used for data analysis. Numbers and percentages were calculated for categorical variables, the chi-squared test was used to compare differences between groups, and multiple independent-sample tests (Kruskal-Wallis H test, test level α = 0.05) and multiple linear regression were used to analyze the influence of different types of comorbidity on hospitalization costs. Among the 76,563 cerebral infarction inpatients, 41,400 were male (54.07%); the average age of the inpatients was 67.68 ± 10.75 years (the 60~80-year-old group accounted for 65.69%). Regarding the incidence of varied chronic disease comorbidities concomitant with cerebral infarction, hypertension was reported as the most frequent, followed by heart disease and chronic pulmonary disease. The average hospitalization cost of cerebral infarction inpatients is US $1219.66; the hospitalization cost increases according to the number of comorbidities with which a patient suffers (H = 404.506, p < 0.001); Regarding the types of comorbidities, the hospitalization cost of cancer was the highest, at US $1934.02, followed by chronic pulmonary disease (US $1533.02). Regarding the cost of hospitalization for combinations of comorbidities, cerebral infarction + chronic pulmonary disease was the most costly (US $1718.90), followed by cerebral infarction + hypertension + chronic pulmonary disease (US $1530.60). In the results of multiple linear regression analysis, cerebral infarction with chronic pulmonary disease had significant effects on hospitalization costs (β = 0.181, p < 0.001), drug costs (β = 0.144, p < 0.001) and diagnosis costs (β = 0.171, p < 0.001). Comorbidities are significantly associated with high hospitalization costs for cerebral infarction patients. Furthermore, relevant health departments should build preventative and control systems to reduce the risk of comorbidities, as well as to improve hospital clinical pathway management and to strengthen and refine the cost-control management of cerebral infarction from the perspective of comorbidities.

Background: During the COVID-19 pandemic, cardiovascular hospitalizations decreased and in-hospital mortality for ST-elevation myocardial infarction and heart failure increased. However, limited research has been conducted on hospitalization and mortality rates for cardiovascular disease (CVD) other than ischemic heart disease and heart failure. Methods and Results: We analyzed the records of 530 certified hospitals affiliated with the Japanese Circulation Society obtained from the nationwide JROAD-DPC database between April 2014 and March 2021. A quasi-Poisson regression model was used to predict the counterfactual number of hospitalizations for CVD treatment, assuming there was no pandemic. The observed number of inpatients compared with the predicted number in 2020 was 88.1% for acute CVD, 78% for surgeries or procedures, 77.2% for catheter ablation, and 68.5% for left ventricular assist devices. Furthermore, there was no significant change in in-hospital mortality, and the decrease in hospitalizations for catheter ablation and valvular heart disease constituted 47.6% of the total decrease in annual hospitalization costs during the COVID-19 pandemic. Conclusions: Cardiovascular hospitalizations decreased by more than 10% in 2020, and the number of patients scheduled for left ventricular assist device implantation decreased by over 30%. In addition, in response to the COVID-19 pandemic, annual cardiovascular hospitalization costs were reduced, largely attributed to decreased catheter ablation and valvular heart disease.

One-year costs associated with cardiovascular disease in Canada: Insights from the REduction of Atherothrombosis for Continued Health (REACH) registry

BackgroundReliable estimates of the impacts of chronic kidney disease (CKD) stage, with and without cardiovascular disease, on hospital costs are needed to inform health policy.MethodsThe Study of Heart and Renal Protection (SHARP) randomized trial prospectively collected information on kidney disease progression, serious adverse events and hospital care use in a cohort of patients with moderate-to-severe CKD. In a secondary analysis of SHARP data, the impact of participants’ CKD stage, non-fatal cardiovascular events and deaths on annual hospital costs (i.e. all hospital admissions, routine dialysis treatments and recorded outpatient/day-case attendances in United Kingdom 2011 prices) were estimated using linear regression.Results7,246 SHARP patients (2,498 on dialysis at baseline) from Europe, North America, and Australasia contributed 28,261 years of data. CKD patients without diabetes or vascular disease incurred annual hospital care costs ranging from £403 (95% confidence interval: 345-462) in CKD stages 1-3B to £525 (449-602) in CKD stage 5 (not on dialysis). Patients in receipt of maintenance dialysis incurred annual hospital costs of £18,986 (18,620-19,352) in the year of initiation and £23,326 (23,231-23,421) annually thereafter. Patients with a functioning kidney transplant incurred £24,602 (24,027-25,178) in hospital care costs in the year of transplantation and £1,148 (978-1,318) annually thereafter. Non-fatal major vascular events increased annual costs in the year of the event by £6,133 (5,608-6,658) for patients on dialysis and by £4,350 (3,819-4,880) for patients not on dialysis, and were associated with increased costs, though to a lesser extent, in subsequent years.ConclusionsRenal replacement therapy and major vascular events are the main contributors to the high hospital care costs in moderate-to-severe CKD. These estimates of hospital costs can be used to inform health policy in moderate-to-severe CKD.Electronic supplementary materialThe online version of this article (doi:10.1186/s12882-015-0054-0) contains supplementary material, which is available to authorized users.

Comparative effectiveness research (CER) and cost-effectiveness analysis are valuable tools for informing health policy and clinical care decisions. Despite the increased availability of rich observational databases with economic measures, few researchers have the skills needed to conduct valid and reliable cost analyses for CER. The objectives of this paper are to (i) describe a practical approach for calculating cost estimates from hospital charges in discharge data using publicly available hospital cost reports, and (ii) assess the impact of using different methods for cost estimation in maternal and child health (MCH) studies by conducting economic analyses on gestational diabetes (GDM) and pre-pregnancy overweight/obesity. In Florida, we have constructed a clinically enhanced, longitudinal, encounter-level MCH database covering over 2.3 million infants (and their mothers) born alive from 1998 to 2009. Using this as a template, we describe a detailed methodology to use publicly available data to calculate hospital-wide and department-specific cost-to-charge ratios (CCRs), link them to the master database, and convert reported hospital charges to refined cost estimates. We then conduct an economic analysis as a case study on women by GDM and pre-pregnancy body mass index (BMI) status to compare the impact of using different methods on cost estimation. Over 60 % of inpatient charges for birth hospitalizations came from the nursery/labor/delivery units, which have very different cost-to-charge markups (CCR = 0.70) than the commonly substituted hospital average (CCR = 0.29). Using estimated mean, per-person maternal hospitalization costs for women with GDM as an example, unadjusted charges ($US14,696) grossly overestimated actual cost, compared with hospital-wide ($US3,498) and department-level ($US4,986) CCR adjustments. However, the refined cost estimation method, although more accurate, did not alter our conclusions that infant/maternal hospitalization costs were significantly higher for women with GDM than without, and for overweight/obese women than for those in a normal BMI range. Cost estimates, particularly among MCH-related services, vary considerably depending on the adjustment method. Our refined approach will be valuable to researchers interested in incorporating more valid estimates of cost into databases with linked hospital discharge files.

SummaryBackgroundExcess weight is associated with poor health and increased health-care costs. However, a detailed understanding of the effects of excess weight on total hospital costs and costs for different health conditions is needed.MethodsWomen in England aged 50–64 years were recruited into the prospective Million Women Study cohort in 1996–2001 through 60 NHS breast cancer screening centres. Participants were followed up and annual hospital costs and admission rates were estimated for April 1, 2006, to March 31, 2011, in relation to body-mass index (BMI) at recruitment, overall and for categories of health conditions defined by the International Classification of Diseases 10th revision chapter of the primary diagnosis at admission. Associations of BMI with hospital costs were projected to the 2013 population of women aged 55–79 years in England.Findings1 093 866 women who provided information on height and weight, had a BMI of at least 18·5 kg/m2, and had no previous cancer at recruitment, were followed up for an average of 4·9 years from April 1, 2006 (12·3 years from recruitment), during which time 1·84 million hospital admissions were recorded. Annual hospital costs were lowest for women with a BMI of 20·0 kg/m2 to less than 22·5 kg/m2 (£567 per woman per year, 99% CI 556–577). Every 2 kg/m2 increase in BMI above 20 kg/m2 was associated with a 7·4% (7·1–7·6) increase in annual hospital costs. Excess weight was associated with increased costs for all diagnostic categories, except respiratory conditions and fractures. £662 million (14·6%) of the estimated £4·5 billion of total annual hospital costs among all women aged 55–79 years in England was attributed to excess weight (BMI ≥25 kg/m2), of which £517 million (78%) arose from hospital admissions with procedures. £258 million (39%) of the costs attributed to excess weight were due to musculoskeletal admissions, mainly for knee replacement surgeries.InterpretationExcess body weight is associated with increased hospital costs for middle-aged and older women in England across a broad range of conditions, especially knee replacement surgery and diabetes. These results provide reliable up-to-date estimates of the health-care costs of excess weight and emphasise the need for investment to tackle this public health issue.FundingCancer Research UK; Medical Research Council; National Institute for Health Research.

Accurate cost estimates are crucial for assessing the commercial viability and business case of well intervention projects, considering the limited available resources. This study presents the development of a comprehensive cost estimation model tailored specifically for rigless well intervention projects. We used the probabilistic approach to develop a cost estimation model for well intervention to achieve the research objective. The developed cost model was transformed into a computer program using pseudocodes in the C-Sharp programming language. The costs of well interventions performed on five (5) wells were used to validate the well intervention cost estimation software. We compared the cost estimation results using the Well Intervention Cost Estimation software and an existing deterministic cost estimate. For every cost estimate that the software generates, three probabilistic values are calculated (P90, P50 and P10). The cost-estimating application resulted in a higher cost than the deterministic estimate because it accounted for project uncertainties. As a result of implementing this cost estimation model, oil and gas industry cost analysts can optimize resource allocation, improve project planning, and mitigate financial risks associated with well interventions, thus improving operational efficiency and profitability.

The purpose of this study was to ascertain the impact of obesity on the cost of disease management in people with or at high risk of atherothrombotic disease from a governmental perspective using a bottom-up approach to cost estimation. In addition, the aim was also to explore the causes of any differences found. The health-care costs of obesity were estimated from 2819 participants recruited into the nationwide Australian REACH Registry with established atherothrombotic disease or at least three risk factors for atherothrombosis. Enrollment was in 2004, through primary care general practices. Information was collected on the use of cardiovascular drugs, hospitalizations and ambulatory care services. 'Bottom-up' costing was undertaken by assigning unit costs to each health-care item, based on Australian Government-reimbursed figures 2006-2007. Linear-mixed models were used to estimate associations between direct medical costs and body mass index (BMI) categories. Annual pharmaceutical costs per person increased with increasing BMI category, even after adjusting for gender, age, living place, formal education, smoking status, hypertension and diabetes. Adjusted annual pharmaceutical costs of overweight and obese participants were higher ($7 (P=0.004) and $144 (<0.001), respectively) than those of the normal weight participants. This was due to participants in higher BMI categories receiving more pharmaceuticals than normal weight participants. There was no significant change across the BMI categories in annual ambulatory care costs and annual hospital costs. In these participants with or at high risk of atherothrombotic disease, annual pharmaceutical costs were greater in participants of higher BMI category, but there was not such a gradient in the annual hospital or ambulatory care costs. The greater cardiovascular pharmaceutical costs for participants of higher BMI categories remained even after adjusting for a range of demographic factors and comorbidities. Our results suggest that these costs are explained by the higher number of drugs used among people with atherothrombotic disease. Further investigation is needed to understand the reasons for this level of drug use.

In the last five years NASA has experienced a renaissance in cost estimating. The small crew of remaining estimators at the Agency started an effort to rebuild the cost estimating capability at all of the Centers, including NASA Headquarters. This involved growing the number of trained cost estimators, educating cost estimating customers and providing guidance on the discipline of cost estimating at NASA. Without these three components credible cost estimates within NASA would not be possible. Five years later, with a robust cadre of trained estimators, how has the cost estimating message been delivered to customers? How have all of the Centers come to agreement on the guidance for their estimates, providing the consistency that leads to the credibility of recent NASA cost estimates? One of the most visible tools that has increased estimating credibility at NASA is the Cost Estimating Handbook (CEH). First published in 2002 and now in revision for the third edition, the NASA CEH has captured inputs from all of the NASA Centers and found consensus on how cost estimates should be conducted at NASA. This paper focuses on the methods and tools that have taken the initial avoidable guidelines originally found at NASA and transformed them into sensible cost estimating requirements that the NASA cost estimating community can follow. This paper will discuss how communication between the Centers led to consistency in requirements and cost estimates, resulting in credible cost estimates at NASA.

To investigate the current situation of drug cost, hospitalization cost and direct medical expense in community health management of hypertensive patients, in order to lay foundation for evaluating whether the community health management in basic public health service has cost-effect in Health Economics. A total of 8326 hypertensive patients from 10 survey pilots in 5 provinces were selected by cluster sampling methods, including 3967 patients who took part in community health management for over 1 year as management group and 4359 cases who have never taken part in community health management as control group. The essential information of research objects were collected by questionnaire; and the medical cost information in the last year (from November 2009 to November 2010) were collected retrospectively. The different annual medical treatment cost, hospitalization cost and direct medical expense in the two groups were compared and analyzed. The average annual drug cost in hypertension was (621.50 ± 1337.78) yuan per patient; while the cost was (616.13 ± 1248.40) yuan in management group and (626.44 ± 1414.30) yuan in control group respectively. The average annual drug cost of hypertensive patients who took medicine therapy was (702.05 ± 1401.79) yuan per person, while the cost in the management group ((688.50 ± 1300.70) yuan) was much lower than it in control group ((714.64 ± 1489.60) yuan). The annual average drug cost in urban was (731.88 ± 1403.31) yuan per person, which was higher than it in rural as (407.44 ± 1171.44) yuan per person. The average hospitalized rate was 12.2% (1014/8326), and the average annual cost among the hospitalized patients was (9264.47 ± 18 088.49) yuan per person; while the cost was (7583.70 ± 13 267.00) yuan in management group, which was lower than it in control group as (11 028.00 ± 21 919.00) yuan. The average annual hospitalized cost in hypertension was (1064.87 ± 6804.83) yuan per person; while the cost was (936.73 ± 5284.90) yuan in management group, which was lower than it in control group as (1181.50 ± 7937.90) yuan. The average annual direct medical expense in hypertension was (2275.08 ± 8225.66) yuan per person; while the expense was (2165.10 ± 6564.60) yuan in management group and (2375.20 ± 9487.60) yuan in control group. The average annual direct medical expense in urban ((2801.06 ± 9428.54) yuan per person) was higher than it in rural ((1254.70 ± 4990.27) yuan per person). The community health or standardized management of hypertensive patients can reduce the average annual drug cost and hospitalization cost (around 26 yuan and 245 yuan separately); and thereby save the annual direct medical expense per capita in hypertension (around 210 yuan). In the reform and development of national medical health system, we should enhance and promote the standardized community health management of hypertensive patients.

Congenital heart defects (CHDs) are common birth defects and are associated with high hospital costs. The objectives of this study were to assess hospitalization costs, across the lifespan, of patients with CHDs in Arkansas. Data from the 2006 to 2011 Healthcare Cost and Utilization Project Arkansas State Inpatient Databases were used. We included hospitalizations of patients whose admission occurred between January 1, 2006, and December 31, 2011, and included a principal or secondary CHD ICD-9-CM diagnosis code (745.0-747.49, except 747.0 and 745.5 for preterm infants). Hospitalizations were excluded if they involved out-of-state residents, normal newborn births, or if missing data included age at admission, state of residence, or hospital charges. Children were defined as those < 18 years-old at time of admission. Between 2006 and 2011, there were 2,242,484 inpatient hospitalizations in Arkansas. There were 9071 (0.4%) hospitalizations with a CHD, including 5,158 hospitalizations of children (2.2% of hospitalizations among children) and 3,913 hospitalizations of adults (0.2% of hospitalizations of adults). Hospital costs for these CHD hospitalizations totaled $355,543,696. The average annual cost of CHD hospitalizations in Arkansas was $59,257,283 during this time period. Infants accounted for 72% of all CHD-related hospital costs; total costs of CHD hospitalizations for children were almost five times those of hospitalization costs for adults with CHD. Hospitalizations with CHDs account for a disproportionate share of hospital costs in Arkansas. Hospitalizations of children with CHD accounted for a higher proportion of total hospitalizations than did hospitalizations of adults with CHD.

Cost estimation is an integral part of any project, and accuracy in the cost estimation process is critical in achieving a successful project. Manually computing cost estimates is mentally draining, difficult to compute, and error-prone. Manual cost estimate computation is a task that requires experience. The use of automated techniques can improve the accuracy of estimates and vastly improve the cost estimation process. Two main gaps in the automation of construction cost estimation are: (1) the lack of interoperability between different software platforms, and (2) the need for manual inputs to complete quantity take-off (QTO) and cost estimation. To address these gaps, this research proposed a new systems to support the computing of cost estimation using Model View Definition (MVD)-based checking, industry foundation classes (IFC) geometric analysis, logic-based reasoning, natural language processing (NLP), and automated 3D image generation to reduce/eliminate the labor-intensive, tedious, manual efforts needed in completing construction cost estimation. In this research, new IFC-based systems were developed: (1) Modeling – an automated IFC-based system for generating 3D information models from 2D PDF plans; (2) QTO - a construction MVD specification for IFC model checking to prepare for cost estimation analysis and a new algorithm development method that computes quantities using the geometric analysis of wooden building objects in an IFC-based building information modeling (BIM) and extracts the material variables needed for cost estimation through item matching based on natural language processing; and (3) Costing – an ontology-based cost model for extracting design information from construction specifications and using the extracted information to retrieve the pricing of the materials for a robust cost information provision.These systems developed were tested on different projects. Compared with the industry’s current practices, the developed systems were more robust in the automated processing of drawings, specifications, and IFC models to compute material quantities and generate cost estimates. Experimental results showed that: (1) Modeling - the developed component can be utilized in developing algorithms that can generate 3D models and IFC output files from Portable Document Format (PDF) bridge drawings in a semi-automated fashion. The developed algorithms utilized 3.33% of the time it took using the current state-of-the-art method to generate a 3D model, and the generated models were of comparative quality; (2) QTO – the results obtained using the developed component were consistent with the state-of-the-art commercial software. However, the results generated using the proposed component were more robust about the different BIM authoring tools and workflows used; (3) Extraction – the algorithms developed in the extraction component achieved 99.2% precision and 99.2% recall (i.e., 99.2% F1-measure) for extracted design information instances; 100% precision and 96.5% recall (i.e., 98.2% F1-measure) for extracted materials from the database; and (4) Costing - the developed algorithms in the costing component successfully computed the cost estimates and reduced the need for manual input in matching building components with cost items.

The automotive companies operate in a very competitive market. Competitiveness requires controlling product costs, and cost estimation is an important activity for this. Cost estimation requires quality information but the conducted research found several issues that hinder this activity, namely a lack of resources and information acquiring and validation difficulties. Data and Information requirements are a major issue in cost estimating. Research in cost estimating mainly focus on improving techniques and methodologies. There is a need to investigate the data and information requirements and corresponding sources of information for cost estimating. These issues have led to the extensive use of expert judgement. Experienced cost estimators use a variety of information resources and cost elements to create a cost estimate, and this causes communication issues. Better information is needed for both creating sound cost estimates and increasing understanding of these created cost estimates. This paper proposes a novel idea, an information infrastructure for automotive cost estimation to address the issue. The constructed Infrastructure provides relevant cost information needed to develop sound and robust cost estimates using a webportal design. It defines in depth the necessary cost information, explains why it is used and gives details where to find it and how to validate it. The research increases understanding of the cost estimation information requirements for the automotive industry.

The estimating process for cost estimates follows the approach of determining the cost of each step in the production process, which is considered the most cost, and summing the cost of each of the steps, or rolling up the costs to estimate the total cost of the product. An amount of profit is then determined based upon the total cost to result in a quote to the perspective customer. It is generally accepted that the actual costs are typically higher than costs used in preparing the quote as the estimate is often low as some items have been omitted from the estimate, the estimating data used is not up-to-date, or the costs increase during the time between the estimate and the production of the product and delivery to the customer. A cost-risk analysis would help the supplier to better evaluate the risk to achieve the cost utilized in the preparation of the quote. The solution to the problem would be to perform a formal cost-risk analysis. The formal cost-risk analysis would require that probability distributions be developed for each step of the process, developing correlations among these distributions, and sum the distributions statistically usually via the Monte Carlo simulation process. This would be a very expensive undertaking and may be cost effective for the aerospace and defense contractors, but it would not be cost effective to medium and small businesses. A simplified model was developed by Stephen Book for those who want the benefits of a cost-risk analysis, but cannot afford the cost or time to perform a formal cost risk analysis. The model has been modified to develop a Cost S Curve from the traditional point estimate value based upon the triangular distribution and using three parameters, H/L ratio, the percentile value for the point estimate and the percentile value for the likely cost. This approach eliminates the need for the traditional triangular distribution parameters of the high with a specified percentile, the low with a specified percentile, and the mode. It is difficult to get estimates of the high and low values associated with percentiles, whereas the H/L ratio is easier to obtain for estimates. The results from the model include the lowest cost, the likely cost, the median cost, the mean cost, and the highest cost estimate as well as the cost values over the entire range in five percentile increments. The model has also been modified to develop a Cost S curve from the traditional point estimate value based upon the normal distribution using the H/L ratio and the percentile for the point estimate. The primary assumption made is that the distance between the high and low values is six sigma. The results from the model include the lowest cost, the mean cost, the highest cost as well as the cost values over the entire range in five percentile increments. The normal distribution is preferred for estimating the mean of a sum of components, but it is not necessarily a good estimate about the distribution. The Triangular Distribution The triangular distribution is a good distribution for cost estimating in that cost estimates tend to be low and that the high cost estimate is further from the likely or mode value than the low cost estimate. The extreme lowest cost would be zero, but the highest cost could theoretically go to infinity and thus the likely, or mode, is closer to the low cost point than to the high cost point. The typical triangular distribution for cost estimating is illustrated in Figure 1.