Economic Modelling

2011 ◽  
pp. 201-219 ◽  
Author(s):  
John K. Stanley ◽  
David A. Hensher
Keyword(s):  
Economic Modelling

Economic impact of sudden cardiac arrest

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
E Paratz ◽  
L Rowsell ◽  
J Ball ◽  
D Zentner ◽  
S Parsons ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Economic Impact ◽  
Terminal Illness ◽  
Sudden Cardiac Arrest ◽  
Economic Security ◽  
Funding Source ◽  
Economic Modelling ◽  
Markov Modelling ◽  
Healthcare Budget ◽  
Returning To Work

Abstract Background Each year, there are approximately 5,000 out-of-hospital cardiac arrests (OHCAs) in the state of Victoria, Australia (population 6.4 million, state healthcare budget AUD$2.9 billion / €1.8billion). Mortality from OHCA approaches ninety percent. High mortality rates and survivors not returning to work is likely to have an adverse effect on the Victorian economy but this has not been previously investigated. Purpose To model the economic impact of OHCA mortality and survivors not returning to work. Methods Data on all OHCAs transported by Ambulance Victoria from July 2017- June 2018 in Victoria, Australia was collected, including age, gender, survival to hospital, survival to discharge, and survival to 12 months. Cases were excluded if arrest was precipitated by trauma, exsanguination, overdose, terminal illness, hanging, SIDS, electrocution, sepsis, respiratory causes, drowning, or neurological causes. Pre-arrest employment status of patients was modelled using the Australian Bureau of Statistics Economic Security dataset, which provides contemporary employment rates for gender-matched five-year cohorts for Australians aged 15–79 years. For survivors to 12 months, pre-arrest and post-arrest work status were confirmed. Economic impact was then calculated to a five year horizon utilizing a Markov model with probabilistic sensitivity analysis. Results 4,934 arrests meeting the inclusion criteria were transported by Ambulance Victoria in twelve months, of whom 4,639 were determined to be cardiac arrests without any exclusion criteria as a precipitant. 695 patients survived to hospital (15.0%), and 325 to discharge (7.0%). At 12 months, 303 patients were alive (6.5% of overall cases, 93.2% of those discharged from hospital). Economic modelling of age and gender-matched data indicated that 1516 patients (35%) would have been employed pre-cardiac arrest, but only 216 survivors (4.7%) would be employed at five years post-arrest. Using Markov modelling incorporating estimated earnings and the pre-determined value of a statistical life, the annual economic burden of cardiac arrest approximated AUD$4 billion (€2.5 billion) at a five-year horizon. Conclusion The annual economic impact of cardiac arrest in Victoria, Australia is approximately AUD$4 billion (€2.5 billion) in a five-year horizon. As the annual Victorian state budget for all healthcare is AUD$2.93 billion (€1.8 billion), our data suggests that the economic impact of cardiac arrest is under-appreciated. Therefore, research in this area and providing state-of-the-art care for all cardiac arrest patients should be a healthcare priority. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): NHMRC/NHF Postgraduate Scholarship, RACP JJ Billings Scholarship

scholarly journals Indoor Air Quality at Home—An Economic Analysis

2021 ◽  
Vol 18 (4) ◽  
pp. 1679
Author(s):  
Amy Dymond ◽  
Stuart Mealing ◽  
Jessica McMaster ◽  
Hayden Holmes ◽  
Lesley Owen
Keyword(s):  
Cost Saving ◽  
Indoor Air ◽  
Indoor Air Pollution ◽  
Health Condition ◽  
Relative Reduction ◽  
Economic Modelling ◽  
Modelling Framework ◽  
Economic Framework ◽  
Extreme Risk ◽  
Intervention Cost

Background: People with respiratory conditions are susceptible to health problems caused by exposure to indoor air pollutants. An economic framework was developed to inform a guideline developed by National Institute for Health and Care Excellence (NICE) to estimate the required level of efficacy necessary for an intervention to be cost-saving in dwellings across England. Methods: An economic modelling framework was built to estimate the incremental costs pre- and post-implementation of interventions designed to reduce exposure to indoor air pollution within dwellings of varying building-related risk factors and profiles. The intervention cost was varied simultaneously with the relative reduction in symptomatic cases of each health condition to estimate the point at which an intervention may become cost-saving. Four health conditions were considered. Results: People living in dwellings with either an extreme risk profile or usable floor area <90 m2 have the greatest capacity to benefit and save National Health Service (NHS) costs from interventions at any given level of effectiveness and upfront cost. Conclusions: At any effectiveness level, the threshold for the upfront intervention cost to remain cost-saving is equivalent across the different home characteristics. The flexible model can be used to guide decision-making under a range of scenarios.

scholarly journals Early health economic modelling of single-stage cartilage repair. Guiding implementation of technologies in regenerative medicine

2016 ◽  
Vol 11 (10) ◽  
pp. 2950-2959 ◽  
Author(s):  
Tommy S. de Windt ◽  
Juliette C. Sorel ◽  
Lucienne A. Vonk ◽  
Michelle M. A. Kip ◽  
Maarten J. Ijzerman ◽  
...  
Keyword(s):  
Health Economic ◽  
Regenerative Medicine ◽  
Cartilage Repair ◽  
Single Stage ◽  
Economic Modelling ◽  
Early Health ◽  
Health Economic Modelling

Empirical models and policy making: special issue of economic modelling

1998 ◽  
Vol 15 (3) ◽  
pp. 307-308
Author(s):  
Frank A.G. den Butter ◽  
Mary S. Morgan
Keyword(s):  
Policy Making ◽  
Empirical Models ◽  
Economic Modelling ◽  
Special Issue

OP443 Evaluating The Value Of Endovascular Innovations For Aortic Valve Replacement Through Clinical Benefits, Patient-reported Outcomes And Resource Consumption.

2021 ◽  
Vol 37 (S1) ◽  
pp. 17-17
Author(s):  
Eduardo Pinar ◽  
Juan García de Lara ◽  
José Hurtado ◽  
Miguel Robles ◽  
Gunnar Leithold ◽  
...  
Keyword(s):  
High Risk ◽  
Aortic Valve ◽  
Short Form ◽  
Systematic Evaluation ◽  
Special Importance ◽  
Economic Modelling ◽  
Sf 36 ◽  
Patient Reported ◽  
Clinical Benefits ◽  
Sapien 3

IntroductionThe use of most recent Transcatheter aortic valve implants (TAVI) in the treatment of symptomatic severe aortic stenosis (SAS) is evolving with expanded indications from inoperable/high-risk to intermediate and low risk patients. Consequently, TAVI outcomes must be monitored to highlight its value under real-world conditions. Our aim was to prospectively evaluate TAVI (SAPIEN 3) outcomes in terms of patient's health-related quality of life (HRQoL), clinical outcomes, and healthcare resource utilization (HRU).MethodsAn observational prospective study including all consecutive patients with SAS undergoing a transcatheter valve implantation with Edwards SAPIEN 3 valve (transfemoral access) was conducted in full accordance with clinical guidelines from the European Society of Cardiology. Patients were evaluated before the intervention (baseline), at discharge, and after one, six and twelve months from the implant. A thoughtful and systematic evaluation of patients’ HRQoL (EQ-5D 5L, the Short Form-36 Health Survey -SF-36- and the Kansas City Cardiomyopathy Questionnaire -KCCQ-), clinical endpoints (that is, cardiovascular mortality, and rates of stroke, major bleeding, myocardial infarction, and re-hospitalization), echocardiographic measurements, and HRU (that is, Length of stay-LOS- in ward/intensive care unit -ICU-) was implemented. Multivariate regression models were applied to test outcomes while controlling key risk factors (that is, patient’ severity at baseline).ResultsA total of seventy-six patients (fifty percent female, fifty-five percent of intermediate-high risk) with a mean age of 82.1 ± 4.78 years were included. Implant success was 97.34% and cardiovascular death was 2.6% at one year. Significant reductions in mean and maximum gradients were achieved and maintained during follow-up. Mean LOS in ward (5.2 ± 4.0days) and ICU (0.22 ± 0.64 days) were low. Statistically significant improvements were detected in the KCCQ overall summary scores, EQ-5D, and SF-36 (Physical component summary) - all adjusted - p < 0.05 - after the intervention.ConclusionsTAVI represents a safe and effective innovation for SAS with clinical benefits translated into significant improvements in terms of HRQoL. Besides, the low HRU provides new insights for health-economic modelling and the optimization of limited resources of special importance under current pandemic situation.

Sign in / Sign up

Export Citation Format

Share Document