Questions related to Cost-Effectiveness Analysis
Major operations of M&A's involving global companies are taking place. It is natural that arise concerns about possible undesirable byproducts, such as future price increases of products sold by entities resulting from these M&A's. Regulatory competition agencies are charged to decide in short time. Faced with this overview, these control agencies could count on new and more efficient rules to prevent abuse detrimental to competition? Which would be these rules?
I am comparing the different platforms for a paper. The approximate cost of constructs and vectors are dependent on the cell line and experiments, varying from hundreds to several thousands but I'm more interested in the cost of setting up the entire platform and the price of the equipment/cost per run.
I am guessing that CRISPR being the newest would be more expensive than its predecessors but I cannot be sure. It isn't available on the website of large biotech companies and I would have to send a query for it to each one for comparison. I was hoping someone here would have an idea. Any input would be greatly appreciated.
Also, if you have any disadvantages for CRISPR that would be helpful too. So far, there seems to be a lot of researchers opting for CRISPR over the other systems. I only have PAM-dependency and off-target edits as major disadvantages so I am looking for financial burdens or other limitations.
Thanks so much.
I'm currently working on a research and a part of it is to make an economic analysis. The aim is to make a cost-effectiveness analysis but before that the PI suggested to make a cost analysis (only the cost without considering the outcome) for each of the two medications. So, I have the following parameters collected from real patients follow up (N=229), and want you please to guide me on how to make cost analysis for each of the two medications:
1- Duration of receiving the treatment till the end of follow up period
2- Number of specific lab tests during the overall treatment duration
3- Number of specific procedure during the overall treatment duration
4- Duration of hospitalization during the overall treatment duration
5- Number of boxes of medications completed during the study follow up period or before the discontinuation of the medication
I have the unit cost for each of these parameters. HOWEVER, cannot just take the mean and multiply it by the unit cost as my data are NOT normally distributed. The median seems to be misleading to use (I'm not sure). What do you think I should do in this case to make this cost analysis? I need it to be cost per patient per year. Thank youuu )))
I am new to fmm. If I run a two component mixture model I will have two sets of predicted values (one for each component). I can also generate the posterior prob and the most likely latent class membership. How do I combine these two sets of values to produce single predicted values which correspond to my dependent variable?
I am currently working a cost effective design a hybrid solar-pv gen-set for a rural community. I need help on finding the cost function of the system and a code sample could also be of help.
Are Big Data database technologies already used to improve fundamental and technical analysis for capital companies whose securities issued by these companies are traded on the stock exchange market?
Fundamental and technical analysis are basic research methods of verification of available economic and financial data, market data and developments on the stock exchange market, whose primary function is to provide the necessary information for the purpose of making decisions on investing in securities.
For many years, discussions and considerations inspired by such questions have been conducted:
- What kind of analysis of economic and other data provides better knowledge for investing in securities listed on the stock exchange?
- Which analysis, ie fundamental or technical analysis, provides better knowledge for investing in securities listed on the stock exchange?
- Thanks to which analysis, ie fundamental and technical analysis, investors achieve the best results in investing, the highest returns on investment in securities listed on the stock exchange?
- Which investment strategies are the most effective? Are the most effective investment strategies based on conducting fundamental or technical analysis and maybe on a specific combination of both types of analysis?
However, due to the development of new computerized technologies of advanced processing of large collections of information, new questions have recently appeared in the field of fundamental and technical analysis in the context of investment decisions made for financial and investment transactions carried out on capital markets.
The current technological revolution, known as Industry 4.0, is determined by the development of the following technologies of advanced information processing: Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence, Business Intelligence and other advanced data mining technologies.
Some of the advanced technology information technologies typical of the current technological revolution are already used for the improvement of analytical processes conducted in various fields of knowledge. One of these areas is the issue of economic and financial analyzes, the aim of which is to diagnose the situation of a particular enterprise, financial institution, issuer of securities or another economic entity.
In connection with the above, I am asking you with the following query:
Are Big Data database technologies already used to improve fundamental and technical analysis for capital companies whose securities issued by these companies are traded on the stock exchange market?
I invite you to the discussion
Thank you very much
I trying to build a model and conduct cost effectiveness analysis of diagnostic test. I have sensitivity data of different diagnostic test like ultrasonography, MRI, Tomosynthesis. What is the most appropriate way to calculate probabilities from sensitivity data.
I'm trying to do a partitioned survival analysis (PartSA) to model a cohort of patients directly from survival data in the trial and evaluate cost-effectiveness of two different treatments. There are Kaplan-Meier OS and PFS curves published for one of these trials, so I have fitted both curves separately with Weibull distribution and extrapolated them to the time horizon of interest (15 years). However, the extrapolated PFS curve turned out to be higher than extrapolated OS curve, which obviously does not make sense for the analysis.
I'm sure this is happening quite a lot because the fact that correlation between time-to-event outcomes is not considered is one of the major limitations of this model. I was wondering if there any practical solutions on how to troubleshoot this. Is it possible to transform the data in any way to overcome this problem?
I want to submit a paper exploring a cost-effectiveness analysis for a novel technology. The model we developed is currently being published as a subsection in a paper (with all details in the supplementary) with the manuscript's primary aim focused on the clinical aspects of the technology and there are many aspects of the cost-effectiveness analysis which are not included in that paper.
I am looking for advise on the best way I can reference the model structure to the initial paper and develop a manuscript which can aptly explain the scope and type of findings such an evaluation can report, specially when the initial paper in itself is under review and not published. Also, I feel that a health economics related journal would be better able to review and validate the model structure and methods as the model methods is an addition on the existing methodology being used and would be of interest for the readers of health economics and HTA focussed journals.
I look forward to some guidance on this matter, thank you so much in advance!
I am comparing the existing methods of government support for creative industries. Could you tell me, in your view, what methods of quantitative analysis are reasonable to use to estimate the effectiveness of government support measures for the development of creative industries planned for implementation? Is it appropriate to use cost-effectiveness analysis method for this purpose? Is it possible to use any other methods and what kind of literature would you recommend for study practical examples of their use?
What we know:
- We know that ~35-45% of colorectal cancer cells bear the KRAS mutation.
- We know that certain chemotherapy drugs are NOT effective in treating colorectal cancer cells bearing K-ras mutations (cetuximab (Erbitux) and panitumumab (Vectibix)).
- We know that most experts agree KRAS testing is important in determining chemotherapy treatment.
So, what percentage of physicians actually order KRAS genetic testing for their colon cancer patients? To be determined.
Is it cost effective? Turns out it's average.
Screening for both KRAS and BRAF mutations compared with the base strategy (of no anti-EGFR therapy) increases expected overall survival by 0.034 years at a cost of $22 033, yielding an incremental cost-effectiveness ratio of approximately $650 000 per additional year of life. Compared with anti-EGFR therapy without screening, adding KRAS testing saves approximately $7500 per patient; adding BRAF testing saves another $1023, with little reduction in expected survival.
Screening for KRAS and BFAF mutation improves the cost-effectiveness of anti-EGFR therapy, but the incremental cost effectiveness ratio remains above the generally accepted threshold for acceptable cost effectiveness ratio of $100 000/quality adjusted life year."
(1) What drugs might be more effective against colon cancer cells bearing the KRAS mutation?
(2) What drugs might be more cost effective against colon cancer cells bearing the KRAS mutation?
(3) Relating to cost effective treatment, how often do we prescribe drugs or assign treatment plans that are expensive $$$, decrease the length of the patient's life, and decrease the patient's quality of life? How can this be prevented? (E.g., recommending surgery procedures for aged colon cancer patients). How do we incentivize treatment that is most cost effective?
Health Economics, Cost-effectiveness analysis, Uncertainty analysis and Oncology modelling
Autism is a disorder which effects the behavioral skills of a child for the rest of his/ her life. Trying to estimate the cost of different variables to asses the cost benefit effectiveness of a Communication centered Parent mediated intervention for Autism in South Asia. Maximum literature is from the developed parts of the world which makes it in appropriate to adopt similar tools in Low and Middle Income Countries in South Asia.
For further details kindly refer to this link for the project description.
I want to do a cost-benefit analysis for the removal of heavy metals by biosorption . Can someone give me some basic materials? Thank you very much!
Can anyone please explain me how to determine effectiveness of any treatment over the other in cost effective analysis.
I'm working on a project; a pharmacoeconomics study, I want to know the exact no of patients to take into my study, given that:
My study is a cost effectiveness analysis that, I'll do on patients.
So, I used G Power, but, the main problem is how to know the effect size?.
The previous studies were done on a large samples and only mentioning confidence interval and RR, OR.
Can anyone guide me for an easy way to calculate the effect size?
I am working on an economic evaluation of a drug to promote wound healing on diabetic foot ulcers based on retrospective data (cost-consequences). I need to make a sensitivity analysis of efficacy and cost of the intervention. To an univariate analysis how to select the range of these variables? Which other alternatives can I use for the analysis?
I had conducted study on cost effectiveness analysis of oral hypoglycemic agents in Type II DM, i calculated ACER and ICER, now i need to apply modeling techniques to select best cost effectiveness option in treatment DM. I am interested in Markov-modelling tool in decision making. Any literature or source is required to make completion of this study. suggest me?
Presently i am working on cost effective analysis by using decision tree model. in this process i conducted met analysis on safety of an intervention and results were presented as polled relative risk (RR,1.67,95%CI,1.2-1.8) when compared to placebo.
I want to convert this relative risk into probability.
Please help me how to calculate this probability from odds ratio OR relative risk
Namibia is one of the countries in sub-Sahara Africa with high HIV/AIDS prevalance, HIV/AIDS consumes most of the health expenditure which is currently mainly funded by donors, and the donors are withdrawing for the government to take full financing. I am thinking of an intervention on the youths in schools, if effective to be extended to communities. The intervention is continuous screening and testing of HIV in youths, by knowing their status can empower them to take full responsibility on protection against HIV and also those diagnosed can be supported and properly managed early. A main limitation to this can be fear of stigmatization but yet creating awareness with this intervention can also help fight stigma in HIV.
i would like your ideas in how i can do a cost analysis for this intervention and its feasibility as a cost-effective study/intervention.
Where could I find quality sources, databases for evidence-based cost effectiveness analysis, or cost benefit research, for online work training programs?
Please give suggestion which simulator can be useful to find out area and number of solar panels, if we have initial parameters volume and temperature. We need to heat a district with population 5000 sitizens
I'm developing a cost-effectiveness analysis where I need to calculate time-dependent reintervention rates derived from published sources. I have multiple studies with different follow-up times and different presentations of the data (Kaplan-Meier risk estimates, cumulative probabilities...)
How would I go about calculating a yearly probability of recurrence that could be applied consistently through out my model, and reducing the probability by a constant factor every year?
I am conducting a cost-efffectiveness analysis of uterine fibroid treatments and will be using quality of life values from published literature. However, many articles only publish the raw data obtained from SF-36 questionnaires or present them in SSS mean scores. How can I change these scores into utility values that I can incorporate in my economic model?
regarding optimum solution, we are implementing algorithm in workflowsim,
steps to find processing cost
random allocation start;
cost+=cloudlet.getProcessingCost(); // is this way right to find processing cost.
after getting processing cost, how we allocate solution from among solutions,
which has minimum cost.
I need to explore the economics of various countries in context with health related issues. I mean the money being spent for treating/preventing any diseases/disorders. If any one came across such kind of database or websites or institutes, Please let me know.
In this case we are considering 3 goods. And we are considering only one country as a trade partner. In addition w*a is used as the determinant of the comparative advantage, being 'w' nominal wage and 'a' the unit labour requirement. The lower w*a is the better. Could someone explain me how is this possible and how could I justify?
One of the outcomes of my cost-effectiveness analysis is admission to a nursing home prevented (at patient level 0=no, 1=yes, prevented), calculated as a proportion per group. Differences between groups are quite small, for example 0.2 with +€250 differences in cost, resulting in an ICER of €1250 for 1....?? It should be one nursing home admission prevented...but what, 1 proportion, 1 person?? 1 proportion is odd, as that equals 100%,right?
Kind regards, Ronald
I am conducting cost -effectiveness analysis comparing different treatments. I am using the life-year gained, i.e. survival time as the primary effectiveness outcomes. Although the survival times follow a normal distribution, it is inappropriate to fit a normal distribution because negative values may randomly be generated from this distribution. I am not sure what is the best distribution for fitting this data to make it probabilistic?
what parameters can be considered that helps in designing cost function in VANETs for finding always best connected network ?
In any academic fora and in most institutions in India, NICE guidelines (UK) are given the status of "gold standard" especially when considering incorportation of newer medications /procedures that are expensive. NICE guidelines are considered conservative compared to many US guidelines and hence when a drug is approved by NICE, many institutes are happy to adopt it in India. I wonder if we have got it even remotely right.
Notwithstanding the various criticisms of the basis of identifying the NICE Cost-Effectiveness Threshold and how they calculated QALY (http://www.echoutcome.eu/images/Echoutcome__Leaflet_Guidelines___final.pdf) the value of 1 QALY in NICE was taken at between GBP 20000-30000 (or USD 30000-USD 45000). Though nowhere is it mentioned how this figure was arrived at (See the article "NICE’s cost effectiveness threshold How high should it be? BMJ 2007") but is is suspiciously close to their per capita income and I suspect that was the deciding factor.
So, In UK , where the per capita income is about GBP 30000-35000, the NICE says it is fine to spend GBP 30000 for a procedure to get 1 QALY. In India, where the per capita is just USD 1600, can NICE guidelines make instinctive sense.
It is all the more relevant when newer drugs like the biological agents (eg anti TNF etc costing USD 6000-8000 per year) or various anticancer drugs or cardiac stents flood Indian markets at astronomical prices. Many of us get taken in by various cost effectiveness studies and NICE guidelines that possibly are not relevant all in Indian context.
I guess it is time we took the Indian reality into account and made our own cost analysis yardsticks.
We conducted a study to estimate the economic burden of ADHD in United States using the Medical Expenditure Panel Survey (national survey by Agency of Healthcare Research and Quality). Our primary objective was to estimate the incremental cost for ADHD compared to the non-ADHD population. We used a two-part model to estimate the incremental cost for ADHD. The variable total cost is the sum of direct and indirect cost categories mentioned in the table attached here. We ran separate models to estimate incremental costs for each category. However, when we add the incremental estimates of each cost category, it does not equal to the incremental estimate of the variable "total cost". We looked for literature that might explain this anomaly but could not find any explanation. Can total cost ever be lower than the sum of individual incremental cost estimates? Did anyone come across a similar situation before. Please share your thoughts on it. I have attached the results table (Title: Cost) for your reference.
I am analyzing cohort data for cancer patients in order to estimate life-year gained that will subsequently be used in decision tree analysis . The final outcomes in my decision tree are either death or alive .
For the treatment -pathway branch that end with death , will the life-year gained attached to the terminal node be zero or do I have to attach the life-year gained for patients until they died using the survival curve?. Moreover, regarding the patients who remained alive at the end of follow up. Do I have to attach the life-year gained estimated from the area under curve for the patients who only still alive or do I have to attach the ones estimated from the area under the curve for all the patients, considering death as the event of interest ?
I am working on a cost effectiveness analysis linking with survival of patients with cancer. The survival part of the analysis is necessary to estimate the "number of life-years gained". To find this quantity I need to calculate the area under the survival curve. In this specific context of long term survival of cancer patient, i need to choose the parametric function of Gompertz which fit the survival in the best way. I'm working on stata software and I would to know if anyone has already done a Gompertz model in STATA, and how to calculate the area under the curve which is the integration of the Gompertz function. Thank you so much for you suggestions.
In a cost-effectiveness analysis, we need to estimate probability of an event at each node. The probability can be calculated by the formula, p = 1- e-(rt), where r = rate (n/N) and t= time. However, when researchers utilize network meta-analysis data to estimate the probability of an event, they need to convert odds ratio/risk ratio to probability of an event for treatment A versus treatment B. How can we derive such probability estimates ?
For example, estimation of probability of death with drug A and B:
Published Network-meta-analysis of indirect comparison:
A vs C : Odds ratio: 0.43 (0.34-1.38),
B vs C: Odds ratio: 1.2 (0.80-1.40)
A vs B: This estimates are usually derived from the indirect comparison: 0.3 (0.2-1.2)
If I am conducting a cost-effectiveness analysis of A versus B per death averted how should I calculate the probability of death for A and B from the given estimate with or without out any denominator on rates?
Is there any good literature for Cost-Effectiveness Analysis in Health (specially oncology and Rad Onc)?
Suggestion of books or articles
I found that most checklists are used for either model or trial-based economic evaluations. However, some checklists, like the one by Evers, 2005 seems to be model-based, yet classified as to be used for trial- based. Can someone please explain? Also, is it alright to use a model-based checklist for studies not model-based?
The study objective was to see if intervention improved adherence in a sample of patients, using claims data. Adherence was calculated using proportion of days covered (pdc).
For N=101, pdc_pre is the baseline pdc value for each patient, range 0-1, mean=0.74 , the outcome variable is adherent or not (post intervention pdc>0.8 vs not). Additional variables in the model were age, gender, type of insurance, CMS risk score. The c-statistic of the logistic model is 0.75, and the convergence criterion was satisfied. The adjusted OR for pre_pdc is 18 (95% CI, <.0001 to >999.99). Also, every patient has a pdc_pre value which is non-missing and >0. What is the reason for such a wide CI for this variable?
In a simple decision-tree, consider the phenomena of only two branches with two events 1) bleeding and 2) death. In a clinical phenomena, suppose after taking drug A or B, individuals are at risk of bleeding or death.
I am interested in making first-node of bleeding (yes/no) and second node as death (yes/no). I find a clinical trial assessing rates of bleeding and death of A and B. The calculated probability would depend on the drug A and drug B for bleeding and death are independent probability. However, in a decision-tree, when I am calculating probability, it is joint-probability,
i.e. probability of death among the individuals with bleeding given drug A
probability of death among the individuals without bleeding given drug A
However, I am using the probability of death from drug A based on literature ignoring the joint-probability of death with bleeding. Is this approach wrong? What would be ideal way to deal with it?
GRADE remains skeptical about the trustworthiness of cost effectiveness analysis in the development of recommendations, but other researchers have opposing opinions.
Some studies examine individual preferences, these type of works have specific methodology. For example the questionnaire they use might not necessarily need to be validated. The type of biases are pretty different from usual quantitative studies. I think quality appraisal tools which are designed for quantitative or cross-sectional studies, may not cover all essential aspects.
cutoff......... cost ........ Walking distance
175 ......... 16.8 ....... 17606.2
200 ........ 13.2 ..... 19278.1
225.......... 10.8 ....... 21858.2
250 ....... 8.4 ...... 24698.2
275 ...... 7.2 ....... 27714.9
300 ...... 7.2 ...... 28462.1
325 ....... 6 ....... 33006.4
350 ....... 6........ 31805.0
The cutoff column represents the alternatives while the next column (Cost) is the cost associated with each alternative. The "walking distance" is the benefit of each alternative. The lower the "walking distance" the better benefit to the public. However Government tend to favor lower cost. Which alternative is the best? Or how can one arrive at an optimum solution i.e. considering tradeoff between cost and benefits
I am particularly interested to know what types of POCT have been in use at A&E, and whether there is any evidence on benefits and disadvantages.
I am interested in knowing how cost-effectiveness results are used in different systems, particularly those with no explicit threshold.
Cost effectiveness analysis needs you evaluate cost first and probably more difficult, effectiveness of research? In complex situation you have to be simple, I just consider researchers’ production evaluated in number of publication in a major database. I work in life sciences domain, so my reference is PubMed.
In France, the national bureau of statistic INSEE produces an amount of spending in R&D each year at nation level and region by region. In 2008, each publication costs € 619 842 for the whole country. This figure has no sense in absolute value, namely because the gross national spending in R&D has a perimeter much larger than the PubMed domain. But the comparison of the figure from region to region should be valid.
I observe big differences between regions.
Paris and Lyon area are closed to the national mean, which is not surprising since around 60% of publications are localized here. But for Languedoc Roussillon (Montpellier, 4.7% of France ‘Publications) the cost is 799 691 €, 34 % over the mean and the other Mediterranean shore region, Provence, Alpes Cote d’Azur (Marseille and Nice area 8.4% of France ‘Publications ) is 561 550 €, -6% from the national mean.
I suspect a flaw, is someone has an idea?
In both experimental and quasi-experimental studies, sometimes it becomes known to the researcher that one or more participants have been compromised with regard to the study goals. This "contamination" can occur when a member of the control/comparison group is exposed to factors (eg, receives treatment) that are similar to the experimental group. It can also occur when members of the experimental group unintentionally receive a different or additional type of treatment than the original study design intends. Does removal or censoring of a limited number of participants impact the reliability of the study results?